Long-term cultivation reduces soil carbon storage by altering microbial network complexity and metabolism activity in macroaggregates

Cultivation alters soil aggregation, microbial compositions and the potential for carbon sequestration in cropland soils. However, the specific effects of long-term cultivation and the underlying mechanisms on soil organic carbon (SOC) storage at different aggregate sizes remain poorly understood. We characterized the dynamics of SOC storage in macroaggregates (>0.25 mm) and microaggregates (<0.25 mm) across four paddy soils successively cultivated for 60, 100, 125, and 150 years. Microbial community compositions, network patterns, enzyme activities and carbon use efficiency (CUE) were examined to elucidate the underlying microbial pathways governing SOC storage. The results showed that prolonged cultivation led to an average reduction of 45 % in SOC storage, particularly in macroaggregates. Partial least squares path modeling revealed that shifts in microorganisms in macroaggregates explained almost 80 % of the variation in SOC storage. Specifically, variations in fungal composition and decreased complexity of microbial interaction networks were strongly correlated with SOC storage. Fungal community and microbial interactions also indirectly affected SOC storage by positively correlating with extracellular enzyme activity. Moreover, bacterial composition indirectly regulated SOC storage by positively correlating with carbon use efficiency. Our findings indicated that the macroaggregate-associated microbial interactions and the metabolism activities had significant implications for SOC sequestration in paddy fields. We suggest that implementation of management practices targeted at improvement of these microbial attributes could enhance agroecosystems sustainability.

Sense of coherence as a predictor for patients' quality of recovery after total hip or knee arthroplasty - A descriptive cohort study

BACKGROUND

Patients' postoperative quality of recovery (QOR) is an important outcome measurement and predicting and preventing impaired quality of recovery is essential. In this study, we aimed to investigate if patients Sense of Coherence (SOC) could be a potential predictor and screening instrument for impaired quality of recovery. We hypothesized that patients' SOC is positively related to their QOR.

MATERIAL AND METHODS

The study was performed as a descriptive single-center prospective cohort study. Data was collected using digital questionnaires. Patients undergoing total hip (THA) or knee arthroplasty (TKA) received the SOC13 questionnaire prior to their surgery to establish their SOC and a questionnaire on postoperative day 2 and 7, respectively, establishing their QOR. Multiple linear regression was used to fit a model for the QOR score using SOC, age, sex, and type of surgery as potential explanatory variables.

RESULTS

206 patients were included in the study analysis. The results showed a highly significant positive correlation between patients' SOC and their postoperative QOR on both postoperative day 2 and 7 (p < 0.01). Patients with a lower SOC score also presented a significantly lower QOR score, meaning they experienced impaired QOR compared to patients with a higher SOC score.

CONCLUSIONS

The results indicate that a weak SOC (low SOC score) can be considered a clinically important indicator for risk of impaired QOR (low QOR score) after THA and TKA. The SOC13 questionnaire may be a potential screening instrument identifying patients in risk of impaired postoperative QOR based on a low SOC score.

Greenhouse gas emissions, carbon stocks and wheat productivity following biochar, compost and vermicompost amendments: comparison of non-saline and salt-affected soils

Understanding the impact of greenhouse gas (GHG) emissions and carbon stock is crucial for effective climate change assessment and agroecosystem management. However, little is known about the effects of organic amendments on GHG emissions and dynamic changes in carbon stocks in salt-affected soils. We conducted a pot experiment with four treatments including control (only fertilizers addition), biochar, vermicompost, and compost on non-saline and salt-affected soils, with the application on a carbon equivalent basis under wheat crop production. Our results revealed that the addition of vermicompost significantly increased soil organic carbon content by 18% in non-saline soil and 52% in salt-affected soil compared to the control leading to improvements in crop productivity i.e., plant dry biomass production by 57% in non-saline soil with vermicompost, while 56% with the same treatment in salt-affected soil. The grain yield was also noted 44 and 50% more with vermicompost treatment in non-saline and salt-affected soil, respectively. Chlorophyll contents were observed maximum with vermicompost in non-saline (24%), and salt-affected soils (22%) with same treatments. Photosynthetic rate (47% and 53%), stomatal conductance (60% and 12%), and relative water contents (38% and 27%) were also noted maximum with the same treatment in non-saline and salt-affected soils, respectively. However, the highest carbon dioxide emissions were observed in vermicompost- and compost-treated soils, leading to an increase in emissions of 46% in non-saline soil and 74% in salt-affected soil compared to the control. The compost treatment resulted in the highest nitrous oxide emissions, with an increase of 57% in non-saline soil and 62% in salt-affected soil compared to the control. In saline and non-saline soils treated with vermicompost, the global warming potential was recorded as 267% and 81% more than the control, respectively. All treatments, except biochar in non-saline soil, showed increased net GHG emissions due to organic amendment application. However, biochar reduced net emissions by 12% in non-saline soil. The application of organic amendments increased soil organic carbon content and crop yield in both non-saline and salt-affected soils. In conclusion, biochar is most effective among all tested organic amendments at increasing soil organic carbon content in both non-saline and salt-affected soils, which could have potential benefits for soil health and crop production.

Conservation Agriculture Impacts on Economic Profitability and Environmental Performance of Agroecosystems

The rationale of this study originates from the primary sector's multiple roles in the global warming issue. Agriculture is reported among the main causes of anthropogenic global warming. At the same time, it is profoundly impacted by climate change and concurrently holds potential as a solution through the sequestration of soil organic carbon (SOC) facilitated by Conservation Agriculture (CA). However, the findings in the literature are controversial on the SOC sequestration capacity and the profitability of CA implementation. Considering the new and old objectives of the sector, this paper tackles the assessment of the actual capabilities of CA to be a viable strategy to pursue the social good of climate change mitigation and concurrently be profitable for farmers. The economic profitability and environmental performance of CA are assessed analysing data from a field experiment in Northern Italy (European temperate area) and identifying the best management practice by means of a data envelopment analysis.

Sense of coherence, its components and depressive and anxiety symptoms in expecting women and their partners - A FinnBrain Birth Cohort Study

OBJECTIVE

Expecting mothers with high sense of coherence (SOC) exhibit improved physical, emotional, and childbearing health. However, the dimensions of SOC and the factor structure of the SOC-13 scale during prenatal period is slightly known. Especially the differences in experiencing SOC and its components (comprehensibility, manageability, meaningfulness) among both expecting parents (mothers and fathers) is poorly understood. The association between SOC and mood disorder symptoms (depression and anxiety) during pregnancy is scarcely studied.

METHODS

The structure of the SOC-13 scale, differences in SOC experiences, and the associations between SOC and depressive and anxiety symptoms were studied in a sample of 2784 pregnant women (mothers) and 1661 men/partners (fathers) belonging to the FinnBrain Birth Cohort Study. Self-reports (SOC-13, EPDS, SCL-90: ANX) from gestational week 24 were used. Confirmatory factor analysis (CFA) and invariance testing was carried out to investigate the factorial structure of SOC-13 among both groups (mothers and fathers). Group comparisons were used to study differences in the level of SOC among mothers vs. fathers, low vs. high depression and anxiety subgroups, and multiparous vs. nulliparous mothers.

RESULTS

A two-factor model for SOC-13 consisting of comprehensibility-manageability and meaningfulness fitted the data best. Mothers reported higher levels of meaningfulness, whereas fathers reported higher levels of comprehensibility-manageability. SOC was significantly higher among fathers vs. mothers, but mothers with depressive symptoms reported higher SOC than fathers with depressive symptoms.

CONCLUSIONS

During pregnancy, SOC can be viewed as a two-dimensional (vs. one- or three-dimensional) concept, and mothers and fathers have differences in the components of SOC. Importantly, mothers vs. fathers with depressive symptoms express higher overall SOC indicating that pregnancy may relate to higher than usual SOC especially among women with psychological distress. Understanding how expecting mothers and fathers experience SOC during pregnancy, particularly in relation to depressive symptoms, helps midwives and maternity care providers to focus health promoting support more precisely.

Tree growth and density enhanced, while diversity and spatial clustering reduced soil mycorrhizal C and N sequestration: Strong interaction with soil properties in northeastern China

In this paper, the effects of species diversity, tree growth, and spatial clustering on mycorrhizal carbon and nitrogen sequestration and the interaction of soil physicochemical properties in Northeast China were investigated. Based on 720 10 m ∗ 10 m plots in Harbin Experimental Forest Farm of Northeast Forestry University, we determined mycorrhizal biomarkers of easily extractable Glomalin-related soil protein (EEG) and total Glomalin-related soil protein (TG). Four plant diversity indices, seven structural metrics, and five soil properties were also measured. We found that: 1) The low tree diversity plots had 1.08-1.23 times higher TG, EEG, TG-N/TN (proportion of N in TG to TN), and TG-C/SOC (proportion of C in TG to SOC) than the high plots. 2) Tree diameter was negatively correlated with EEG and TG, but positively correlated with the EEG and TG contribution to soil TN and SOC. Soil EEG and TG were positively correlated with under-branch height and tree density. W (Uniform Angle Index, higher W indicates more clustering of tree distribution in the plot) was negatively correlated with the above four ratios and positively correlated with EEG/TG. 3) pH was the most powerful explainer for the GRSP variations (6.8 %, strongest negative association with GRSP/TN, R2 > 0.13), followed by soil electrical conductance (6.5 %, positive relation with TG, p < 0.05), AP (3.2 %). 4) Plant diversity mainly affected GRSP traits through the interaction with soils (0.07), tree growth and density directly increased TG, TG-N/TN, and TG-C/SOC, while tree spatial distribution directly reduced TG-N/TN. Our finding highlighted the important effects of tree diversity and forest structural traits on GRSP amount, carbon sequestration, and nutrient retentions, and could support glomalin-related forest soil management of temperate forests in the high-latitude northern hemisphere.

Themes and Topics on Diversity, Equity, and Inclusion in JMIR Dermatology Publications

Publications dealing with topics considered to be pertinent to diversity, equity, and inclusion are increasing. Due to the increasing trend, dermatology journals have started to implement ways to evaluate and understand these publications. Here, we discuss a keyword approach to identify and then categorize these publications. Keywords identified 43 manuscripts. Two reviewers screened the articles' titles and abstracts, and recommended a full manuscript review for 24 publications. Through the scope of definitions from the National Institutes of Health, an editorial board member performed a full-text review and assigned a primary theme to the publications. Themes included equity (n=20) and diversity/inclusion (n=4). Topics were racial/ethnic differences in care delivery or society (n=17), incomplete understanding of gender and sex (n=3), gender identity (n=2), socioeconomic class and its impact on health (n=1), care for rural underserved communities (n=1), and religion (n=1). The results of this review demonstrate a predominance of equity-related publications, particularly emphasizing racial/ethnic differences in health care delivery, in the publications identified in JMIR Dermatology. Future research can focus on creating a review aid to assist editorial board members when providing feedback to manuscripts, refining the keywords, and using thematic analysis methodology to evaluate large sets of publications.

Noninvasive imaging modalities in coronary artery disease: a meta analysis comparing coronary computed tomography angiography and standard of care

Introduction: Coronary artery disease has become a global pandemic and a major cause of death. The risk-factor calculation for coronary artery damage is an invasive procedure. Aim: To compare coronary computed tomography angiography (CCTA) with standard of care (SOC) to calculate need for revascularization, invasive coronary angiography as well as for myocardial infarction (MI) incidence and all-cause mortality. Methodology, results & conclusion: CCTA is significantly correlated with a reduction in MI episodes (RR = 0.752, 95% CI = 0.578-1.409; p < 0.033) and an increase in revascularizations (RR = 1.401, 95% CI = 1.315-1.492; p < 0.001) and invasive coronary angiography procedures (RR = 1.304, 95% CI = 1.208-1.409; p < 0.001). However, it was found that it did not affect all-cause mortality. On the contrary, standard care approaches were associated with greater rates of MI but lesser referrals for invasive coronary angiography and revascularization.

Management of everyday life after a hand operation-A qualitative study of patients with a weak sense of coherence

BACKGROUND

A hand-related disorder (HRD) has a more significant impact on participation in everyday life for patients with a weak sense of coherence (SOC) compared to those with a strong SOC. Therefore, understanding how patients with a weak SOC manage the conditions of everyday life after a hand operation is of clinical interest.

PURPOSE

This study aimed to explore how patients with a weak SOC experience and manage the conditions of everyday life after an operation for an HRD.

STUDY DESIGN

A qualitative design with a hermeneutic approach.

METHODS

An in-depth interview was conducted with each of eight adults-five women and three men-with an HRD and a weak SOC (SOC-13 score <52). Participants with varying HRDs were interviewed once between six and 13 weeks after the hand operation. Data were analyzed based on a hermeneutic approach.

RESULTS

The analyses resulted in five themes: even more conditions to handle, challenges in everyday life, managing everyday life, different expectations, and the influence of information on everyday life. The lives of most participants were significantly impacted: they experienced a range of difficulties managing their activities and roles after their operation. The participants felt uncertain about managing everyday life and the future and expressed unfulfilled expectations for different reasons. All wanted individualized information about what to expect.

CONCLUSIONS

Participants had several conditions in life that challenged their everyday lives, and the HRD made their everyday lives even more challenging. The extent to which they felt affected appeared to relate to their perception of their presurgery activities. They had several strategies to manage everyday life but used these to varying extent. Their expectations about the outcome had both positive and negative effects on their ability to manage everyday life, and individually adapted information was requested about what to expect and how to cope with everyday life after the surgery.

Vertical distribution characteristics of soil organic carbon and vegetation types under different elevation gradients in Cangshan, Dali

Background

The Cangshan National Nature Reserve of Dali City was adopted as the research object to clarify the vertical distribution characteristics of soil organic carbon (SOC) and vegetation types at different elevations in western Yunnan.

Methods

The contents of SOC, light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC), and water-soluble organic carbon (WSOC) in the 0-30 cm soil layer at different elevations (2,400, 2,600, 2,800, 3,000, 3,200, 3,400, and 3,600 m) were determined, and the above-ground vegetation types at different elevations were investigated.

Results

Results showed that the SOC content was the highest in 0-20 cm surface soil and gradually decreased with the deepening of the soil layer. It increased then decreased with the increase in elevation, and it peaked at 3,000 m. The LFOC content was between 1.28 and 7.3515 g kg-1. It exhibited a decreasing trend and little change in profile distribution. The HFOC content ranged between 12.9727 and 23.3708 g kg-1; it increased then decreased with the increase in profile depth. The WSOC content was between 235.5783 and 392.3925 mg kg-1, and the response sensitivity to elevation change was weak. With the increase in elevation, WSOC/SOC and LFOC/SOC showed a similar trend, whereas HFOC presented an opposite trend. This observation indicates that the active organic carbon content at 3,600 m was lower than that at 2,400 m, and the middle elevation was conducive to the storage of active organic carbon. Meanwhile, the physical and chemical properties of soil affected the distribution of organic carbon to a certain extent. The vegetation type survey showed that the above-ground dominant species within 2,400-2,800 m were Pinus yunnanensis and Pinus armandii. Many evergreen and mixed coniferous broadleaf forests were distributed from 3,000 m to 3,200 m. Species of Abies delavayi were mainly distributed from 3,400 m to 3,600 m. This research serves as a reference for the study of forest soil carbon stability in high-elevation areas and plays an important role in formulating reasonable land use management policies, protecting forest soil, reducing organic carbon loss, and investigating the carbon sequestration stability of forest ecosystems.

Impact of bioenergy feedstock carbon farming on sustainable aviation fuel viability in the United States

Biomass-derived sustainable aviation fuel holds significant potential for decarbonizing the aviation sector. Its long-term viability depends on crop choice, longevity of soil organic carbon (SOC) sequestration, and the biomass-to-biojet fuel conversion efficiency. We explored the impact of fuel price and SOC value on viable biojet fuel production scale by integrating an agroecosystem model with a field-to-biojet fuel production process model for 1,4-dimethylcyclooctane (DMCO), a representative high-performance biojet fuel molecule, from Miscanthus, sorghum, and switchgrass. Assigning monetary value to SOC sequestration results in substantially different outcomes than an increased fuel selling price. If SOC accumulation is valued at $185/ton CO2, planting Miscanthus for conversion to DMCO would be economically cost-competitive across 66% of croplands across the continental United States (US) by 2050 if conventional jet fuel remains at $0.74/L (in 2020 US dollars). Cutting the SOC sequestration value in half reduces the viable area to 54% of cropland, and eliminating any payment for SOC shrinks the viable area to 16%. If future biojet fuel prices increase to $1.24/L-Jet A-equivalent, 48 to 58% of the total cultivated land in the United States could support a more diverse set of feedstocks including Miscanthus, sorghum, or switchgrass. Among these options, only 8-14% of the area would be suitable exclusively for Miscanthus cultivation. These findings highlight the intersection of natural solutions for carbon removal and the use of deep-rooted feedstocks for biofuels and biomanufacturing. The results underscore the need to establish clear and consistent values for SOC sequestration to enable the future bioeconomy.

Meta-analysis protocol on the effects of cover crops on pool specific soil organic carbon

Soil organic carbon (SOC) plays an important role in agricultural soils, as it contributes to overall soil health as well as climate change mitigation and adaptation. By conducting a meta-analysis, we aim to quantitatively summarize research studying the effects of cover crops (CC) on SOC pools throughout soil depths in arable cropland. We included global studies located in the climatic zones present in Europe. The pools chosen for this analysis are the particulate organic carbon (POC) and the mineral associated organic carbon (MAOC) and the microbial biomass carbon (MBC). Alongside, we will study the effects of a broad range of moderators, such as pedo-climatic factors, other agricultural management practices and CC characteristics e.g., type. We identified 71 relevant studies from 61 articles, of which mean values for SOC pools, standard deviations and sample sizes for treatments (CC) and controls (no CC) were extracted. To perform the meta-analysis, an effect size will be calculated for each study, which will then be summarized across studies by using weighing procedure. Consequently, this meta-analysis will provide valuable information on the state of knowledge on SOC pool change influenced by CC, corresponding quantitative summary results and the sources of heterogeneity influencing these results.

Double gains: Boosting crop productivity and reducing carbon footprints through maize-legume intercropping in the Yellow River Delta, China

The increasing demand for environmentally friendly agricultural practices has driven the need for diversified crop cultivation to optimize crop productivity while minimizing carbon footprints (CFs). However, the impacts of crop diversification on crop production and environmental benefits are still poorly understood. In this study, conducted at two sites in the Yellow River Delta, China, we investigated the effects of legume intercropping, specifically maize/soybean (M/S) and maize/peanut (M/P) systems, on crop productivity, economic return, ecosystem economic budget (NEEB), CF, and carbon sustainability index (CSI) in comparison to conventional monocrops. Crops were grown in replicated field plots and fertilized in their strips according to common practice for monocrops. Compared to the expected averages of monocrops, maize/legume intercropping demonstrated higher crop yields, with M/S achieving a 37% and 43% increase at the two sites, respectively, and M/P achieving an 11% and 20% increase. The higher overyielding in M/S was attributed to stronger selection effects, i.e., interspecific facilitation. However, the complementarity effects induced by the competitive dominance of maize were similar in both intercropping systems. Additionally, M/S exhibited greater potential for improving net revenues compared to M/P. Life cycle assessments revealed lower CFs in the intercropping systems compared to monocultures. M/S reduced CFs per unit of area by 26.8% at both sites, CFs per unit of maize equivalent energy yield by 25% and 33%, and CFs per unit of revenue by 20% and 25% at the two sites, respectively. M/P also resulted in reduced CFs, albeit to a lesser extent. Intercropping enhanced the CSI, with the highest values observed in the M/S system. However, both intercropping systems showed limited effects on soil C sequestration. Overall, our results highlight that maize/legume intercropping is a feasible approach to enhance crop productivity while reducing CFs. The M/S system outperformed the M/P system in terms of crop yields, economic benefits, and CF reduction. However, the intercropping systems showed limited effects on SOC storage. This study provides important implications for sustainable agriculture by appropriate crop diversification.

Organic amendment-mediated reclamation and build-up of soil microbial diversity in salt-affected soils: fostering soil biota for shaping rhizosphere to enhance soil health and crop productivity

Soil salinization is a serious environmental problem that affects agricultural productivity and sustainability worldwide. Organic amendments have been considered a practical approach for reclaiming salt-affected soils. In addition to improving soil physical and chemical properties, organic amendments have been found to promote the build-up of new halotolerant bacterial species and microbial diversity, which plays a critical role in maintaining soil health, carbon dynamics, crop productivity, and ecosystem functioning. Many reported studies have indicated the development of soil microbial diversity in organic amendments amended soil. But they have reported only the development of microbial diversity and their identification. This review article provides a comprehensive summary of the current knowledge on the use of different organic amendments for the reclamation of salt-affected soils, focusing on their effects on soil properties, microbial processes and species, development of soil microbial diversity, and microbial processes to tolerate salinity levels and their strategies to cope with it. It also discusses the factors affecting the microbial species developments, adaptation and survival, and carbon dynamics. This review is based on the concept of whether addition of specific organic amendment can promote specific halotolerant microbe species, and if it is, then which amendment is responsible for each microbial species' development and factors responsible for their survival in saline environments.

Mid-Infrared Variable Selection for Soil Organic Matter Fractions Based on Soil Model Systems and Permutation Importance Algorithm

In this research, an attempt was made to classify soil samples according to the different fractions of soil organic matter (SOM) using model systems in which the ratio of the fractions of SOM is chemically mimicked. A mixture of starch and nicotinamide was used for the labile organic matter model, while a standard of humic acid was used for the stabile organic matter. Changing the threshold value in the selected ranges after a permutation importance algorithm is conducted using train models and test data set, a list of selected important wavelengths and their importance scores were obtained. Three regions for the classification of soil fractions within the estimated probability density function are most prominent: 800-1200 cm-1, 0.48-0.55; 1800-2000 cm-1, 0.52-0.62; and 2500-3200 cm-1, 0.48-0.62, where the first component represents the spectral range while the second component covers the range of the importance score. Obtained wavelength ranges indicate the importance of the aliphatic stretching and bending vibration region, as well as the total soil reflectance (mineral content) for the characterization of organic matter fractions. A comparative evaluation with literature data found that the obtained wavelengths have a potential for application in methods of proximal and remote detection/calibration of existing and development of new sensors for Advanced Spaceborne Thermal Emission and Reflection Radiometer satellites, specifically in the shortwave infrared and thermal infrared ranges.

Cover crop root morphology rather than quality controls the fate of root and rhizodeposition C into distinct soil C pools

Cover crops increase carbon (C) inputs to agricultural soils, and thus have the potential to mitigate climate change through enhanced soil organic carbon (SOC) storage. However, few studies have explored the fate of belowground C inputs associated with varying root traits into the distinct SOC pools of mineral-associated organic carbon (MAOC) particulate organic carbon (POC). Therefore, a packed 0.5 m column trial was established with 0.25 m topsoil and 0.25 m subsoil with four cover crops species (winter rye, oilseed radish, chicory, and hairy vetch) known to differ in C:N ratio and root morphology. Cover crops were 14 CO2 -labeled for 3 months, and then, half of the columns were sampled to quantify root and rhizodeposition C. In the remaining columns, plant shoots were harvested and the undisturbed soil and roots were left for incubation. Bulk soil from both sampling times was subjected to a simple fractionation scheme, where 14 C in the <50 and >50 μm fraction was assumed to represent MAOC and POC, respectively. The fast-growing rye and radish produced the highest root C. The percentage loss of C via rhizodeposition (%ClvR) showed a distinct pattern, with 22% for the more branched roots (rye and vetch) and 6%-8% for the less branched roots (radish and chicory). This suggests that root morphology plays a key role in determining rhizodeposition C. After 1 year of incubation at room temperature, the remaining MAOC and POC were positively correlated with belowground inputs in absolute terms. However, topsoil MAOC formation efficiencies (cover crop-derived MAOC remaining as a share of belowground inputs) were higher for vetch and rye (21% and 15%, respectively) than for chicory and radish (9% and 10%, respectively), suggesting a greater importance of rhizodeposition (or indirectly, root morphology) than solely substrate C:N ratio for longer term C stabilization.

An Italian cross-sectional study

The pandemic deeply changed young adults' life. Lockdown period and the social restrictions dramatically affected university students' mental health. The aim of our cross-sectional study was to describe psychological well-being, future anxiety (FA), and health complaints (HCs) in a sample of 3,001 students of the University of Florence in the middle of the first two pandemic waves. We assessed the role of subjective social status, chronic diseases, sense of coherence (SoC), and digital health literacy (DHL) as predictors of psychological well-being, FA, and HCs. Students expressed high levels of FA and reported being disturbed by not being able to achieve their desired future goals. About 40% reported a low or a very low well-being and 19.1% experienced two or more subjective health complaints more than once a week. The likelihood of having a better mental health status significantly increased with increasing SoC and among males. Subjective Social Status proved to be a predictor for FA. Enhancing SoC could improve the health status of the university students during the pandemic and beyond.

Effects of land use types on the depth distribution of selected soil properties in two contrasting agro-climatic zones

The depth distribution of soil properties are governed by several interacting factors including land use types (LUT) and agro-climate (AgC) factors. Yet, there is little information on the effects of LUT, AgC and their combination on soil properties along depth, which this study aimed to investigate. We collected a total of 36 composite soil samples using the manual percussion of a steel core tube layer by layer vertically up to 30 cm in sites representing both highland and lowlands, and analyzed for selected soil properties. A significant main effects of LUT on the depth distribution of bulk density (BD), Ca, Na, K and Cu, and AgC on soil texture, pH, EC, Ca, Na, K, P, Mn, Fe and Cu were noted. The two-way ANOVA analysis also revealed the significant effects of both LUT and AgC on the depth distribution of BD, Na, K, Cu and EC, reflecting their influences on the paths associated to bio-geo-recycling processes. Compared to crop and forestlands, the average SOC and Fe were lower while EC, CEC, Ca, Na, K, P, Mn and Zn were higher in homegarden located in highland than lowland, possibly the acid nature of the highland soil may make the extractable cations available. SOC was not significantly influenced by AgC, LUT and their interaction effect. Based on the Elemental Enrichment Ratio (EER), the SOC was concentrated in the upper surface soil in forest and cropland located both in highland (1.79, 1.33) and lowland (1.80, 1.57), respectively. The reverse propagation pattern SOC depth distribution in soils under homegarden with EER of 0.7 (highland) ad 0.8 (lowland) showed that implementing such system can accelerate carbon sinking and safely store it in subsoil. Also, diversified species composition associated with respective root architectures in the homegarden system, make it an efficient soil nutrient management, which should be widely promoted.

Response of cross-correlations between high PM2.5 and O3 with increasing time scales to the COVID-19: different trends in BTH and PRD

The air pollution in China currently is characterized by high fine particulate matter (PM_2.5) and ozone (O₃) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM_2.5 and O₃ are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM_2.5 and O₃. Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM_2.5 and O₃ in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM_2.5 decreased while O₃ increased in most cities due to the effect of COVID-19, and the increase in O₃ is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM_2.5-O₃ DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM_2.5-O₃ VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM_2.5 and O₃ are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM_2.5-O₃ DHP coordinated control strategies.

Distributed Intelligent Battery Management System Using a Real-World Cloud Computing System

In this work, a decentralized but synchronized real-world system for smart battery management was designed by using a general controller with cloud computing capability, four charge regulators, and a set of sensorized battery monitors with networking and Bluetooth capabilities. Currently, for real-world applications, battery management systems (BMSs) can be used in the form of distributed control systems where general controllers, charge regulators, and smart monitors and sensors are integrated, such as those proposed in this work, which allow more precise estimations of a large set of important parameters, such as the state of charge (SOC), state of health (SOH), current, voltage, and temperature, seeking the safety and the extension of the useful life of energy storage systems based on battery banks. The system used is a paradigmatic real-world example of the so-called intelligent battery management systems. One of the contributions made in this work is the realization of a distributed design of a BMS, which adds the benefit of increased system security compared to a fully centralized BMS structure. Another research contribution made in this work is the development of a methodical modeling procedure based on Petri Nets, which establishes, in a visible, organized, and precise way, the set of conditions that will determine the operation of the BMS. If this modeling is not carried out, the threshold values and their conditions remain scattered, not very transparent, and difficult to deal with in an aggregate way.

Stable and Accurate Estimation of SOC Using eXogenous Kalman Filter for Lithium-Ion Batteries

The state of charge (SOC) for a lithium-ion battery is a key index closely related to battery performance and safety with respect to the power supply system of electric vehicles. The Kalman filter (KF) or extended KF (EKF) is normally employed to estimate SOC in association with the relatively simple and fast second-order resistor-capacitor (RC) equivalent circuit model for SOC estimations. To improve the stability of SOC estimation, a two-stage method is developed by combining the second-order RC equivalent circuit model and the eXogenous Kalman filter (XKF) to estimate the SOC of a lithium-ion battery. First, approximate SOC estimation values are observed with relatively poor accuracy by a stable observer without considering parameter uncertainty. Second, the poor accuracy SOC results are further fed into XKF to obtain relative stable and accurate SOC estimation values. Experiments demonstrate that the SOC estimation results of the present method are superior to those of the commonly used EKF method. It is expected that the present two-stage XKF method will be useful for the stable and accurate estimation of SOC in the power supply system of electric vehicles.

The Influence of Soil Organic Carbon and Climate Variability on Crop Yields in Kongwa District, Tanzania

This study assessed the influence of soil organic carbon (SOC) accumulation and climate variability on crop yields in Kongwa District, central Tanzania. In doing so, climate data and soil samples were collected from Mnyakongo and Ugogoni villages through soil sampling, interviews and surveys. Walkley-Black method, Mann-Kendall test, and MS Excel were used to analyze SOC, climate, crop yields respectively. The results exhibited that the accumulation of SOC was significantly greater in soils under organic fertilization (1.15 and 0.80 MgC ha^-1 at soil 0-20 cm and 20-30 cm depth) than under no-fertilization (0.35 and 0.30 MgC ha^-1 at 0-20 cm and 20-30 cm) and decreased with increasing soil depths. Under these two soil treatments, the average yields for maize, sorghum and millet were almost 1.8 tn ha^-1 under organic fertilization and 0.6 tn ha^-1 under no-fertilization. Specifically, maize yields ranged from 1.5 to 2.2 tn ha^-1, while both sorghum and millet had 1.1-1.7 tn ha^-1. Therefore, yields were significantly higher under organic fertilizations than under no-fertilizations. Besides, the mean annual rainfall or temperature (1980‒2020) fluctuated at a decreasing (R² = 0.21) or an increasing trend (R² = 0.30). Comparatively, the yields for maize, sorghum or millet fluctuated at a decreasing trend at R² = 0.07, 0.05, or 0.85, respectively. Correspondingly, it was found that the temporal increase in rainfall and temperature had positive (R² ~0.5) and negative (R² ~0.3) correlations with crop yields, respectively. In contrast, the decline in rain's intensity and frequency had negative impacts on crop yields. Thus, both SOC and climate correlated with crop yields.

Variations in genetics, biology, and phenotype of cutaneous disorders in skin of color. Part II: Differences in clinical presentation and disparities in cutaneous disorders in skin of color

Skin of color (SOC) patients are projected to comprise the majority of the population by 2044, yet knowledge gaps in the clinical presentation and treatment of both common and uncommon dermatologic conditions in skin of color persist. Improved awareness of disparities that disproportionately impact SOC patients is necessary to address health inequity in the field of dermatology. The first part of this CME discussed structural, genetic, and immunophenotypic differences in SOC in common inflammatory disorders as well as cutaneous malignancies. The second part of this CME highlights clinical differences in the phenotypic presentation of the inflammatory disorders of atopic dermatitis, psoriasis, and hidradenitis suppurativa as well as the cutaneous malignancies of melanoma, basal cell carcinoma, and cutaneous T-cell lymphoma. Health disparities associated with each of these conditions are also discussed.

Variations in genetics, biology, and phenotype of cutaneous disorders in skin of color - Part I: Genetic, biologic, and structural differences in skin of color

Skin of color (SOC) populations include those who identify as Black/African, Hispanic/Latinx, Asian/Pacific Islander, American Indian/Native Alaskan, Indigenous Australian, Middle Eastern, biracial/multiracial, or non-White; this list is far from exhaustive and may vary between and within cultures. Recent genetic and immunological studies have suggested that cutaneous inflammatory disorders (atopic dermatitis, psoriasis, and hidradenitis suppurativa) and malignancies (melanoma, basal cell carcinoma, and cutaneous T-cell lymphoma) may have variations in their immunophenotype among SOC. Additionally, there is growing recognition of the substantial role social determinants of health play in driving health inequalities in SOC communities. It is critically important to understand that social determinants of health often play a larger role than biologic or genetic factors attributed to "race" in health care outcomes. Herein, we describe the structural, genetic, and immunological variations and the potential implications of these variations in populations with SOC. This article underscores the importance of increasing the number of large, robust genetic studies of cutaneous disorders in SOC to create more targeted, effective therapies for this often underserved and understudied population. Part II of this CME will highlight the clinical differences in the phenotypic presentation of and the health disparities associated with the aforementioned cutaneous disorders in SOC.

Digital Mapping of Soil Organic Carbon Based on Machine Learning and Regression Kriging

In the last two decades, machine learning (ML) methods have been widely used in digital soil mapping (DSM), but the regression kriging (RK) model which combines the advantages of the ML and kriging methods has rarely been used in DSM. In addition, due to the limitation of a single-model structure, many ML methods have poor prediction accuracy in undulating terrain areas. In this study, we collected the SOC content of 115 soil samples in a hilly farming area with continuous undulating terrain. According to the theory of soil-forming factors in pedogenesis, we selected 10 topographic indices, 7 vegetation indices, and 2 soil indices as environmental covariates, and according to the law of geographical similarity, we used ML and RK methods to mine the relationship between SOC and environmental covariates to predict the SOC content. Four ensemble models-random forest (RF), Cubist, stochastic gradient boosting (SGB), and Bayesian regularized neural networks (BRNNs)-were used to fit the trend of SOC content, and the simple kriging (SK) method was used to interpolate the residuals of the ensemble models, and then the SOC and residual were superimposed to obtain the RK prediction result. Moreover, the 115 samples were divided into calibration and validation sets at a ratio of 80%, and the tenfold cross-validation method was used to fit the optimal parameters of the model. From the results of four ensemble models: RF performed best in the calibration set (R²_c = 0.834) but poorly in the validation set (R²_v = 0.362); Cubist had good accuracy and stability in both the calibration and validation sets (R²_c = 0.693 and R²_v = 0.445); SGB performed poorly (R²_c = 0.430 and R²_v = 0.336); and BRNN had the lowest accuracy (R²_c = 0.323 and R²_v = 0.282). The results showed that the R² of the four RK models in the validation set were 0.718, 0.674, 0.724, and 0.625, respectively. Compared with the ensemble models without superimposed residuals, the prediction accuracy was improved by 0.356, 0.229, 0.388, and 0.343, respectively. In conclusion, Cubist has high prediction accuracy and generalization ability in areas with complex topography, and the RK model can make full use of trends and spatial structural factors that are not easy to mine by ML models, which can effectively improve the prediction accuracy. This provides a reference for soil survey and digital mapping in complex terrain areas.

A Social-Ecological Approach to Modeling Sense of Virtual Community (SOVC) in Livestreaming Communities

Participation in communities is essential to individual mental and physical health and can yield further benefits for members. With a growing amount of time spent participating in virtual communities, it's increasingly important that we understand how the community experience manifests in and varies across these online spaces. In this paper, we investigate Sense of Virtual Community (SOVC) in the context of live-streaming communities. Through a survey of 1,944 Twitch viewers, we identify that community experiences on Twitch vary along two primary dimensions: belonging, a feeling of membership and support within the group, and cohesion, a feeling that the group is a well-run collective with standards for behavior. Leveraging the Social-Ecological Model, we map behavioral trace data from usage logs to various levels of the social ecology surrounding an individual user's participation within a community, in order to identify which of these can be associated with lower or higher SOVC. We find that features describing activity at the individual and community levels, but not features describing the community member's dyadic relationships, aid in predicting the SOVC that community members feel within channels. We consider implications for the design of live-streaming communities and for fostering the well-being of their members, and we consider theoretical implications for the study of SOVC in modern, interactive online contexts, particularly those fostering large-scale or pseudonymized interactions. We also explore how the Social-Ecological Model can be leveraged in other contexts relevant to Computer-Supported Cooperative Work (CSCW), with implications for future work.

Root exudates contribute to belowground ecosystem hotspots: A review

Root exudates are an essential carrier for material cycling, energy exchange, and information transfer between the belowground parts of plants and the soil. We synthesize current properties and regulators of root exudates and their role in the belowground ecosystem as substances cycle and signal regulation. We discussed the composition and amount of root exudates and their production mechanism, indicating that plant species, growth stage, environmental factors, and microorganisms are primary influence factors. The specific mechanisms by which root secretions mobilize the soil nutrients were summarized. First, plants improve the nutrient status of the soil by releasing organic acids for acidification and chelation. Then, root exudates accelerated the SOC turnover due to their dual impacts, forming and destabilizing aggregates and MASOC. Eventually, root exudates mediate the plant-plant interaction and plant-microbe interaction. Additionally, a summary of the current collection methods of root exudates is presented.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM_2.5 in typical industrial areas of North China, manual sampling and analysis of PM_2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM_2.5 was 53.4 ± 43.9 μg·m^-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO₃^- ion, at 14.6 ± 14.2 μg·m^-3, followed by organic carbon (OC), SO₄^2-, and NH₄⁺, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m^-3, respectively. The concentrations of OC, NO₃^-, and SO₄^2- were highest in winter and lowest in summer, whereas the NH₄⁺ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO₂ emission and conversion rates in winter, resulting in the SO₄^2- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m^-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m^-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM_2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM_2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Can in situ spectral measurements under disturbance-reduced environmental conditions help improve soil organic carbon estimation?

In situ visible and near-infrared (Vis-NIR) spectroscopy has proven to be a reliable tool for determining soil organic carbon (SOC) content with a small loss of precision as compared to laboratory measurements. The loss of precision is a result of disturbing external environmental factors that disrupt spectral measurements. For example, roughness, changes in weather conditions, humidity, temperature, human factors, spectral noise and especially soil water. It has been assumed that, in situ predictive capability could be improved if some of these factors are either minimized or eliminated during the in situ measurement. For this study, the prediction of SOC was carried out under two different in situ measurement conditions; less favourable environmental conditions (with disturbances) and more favourable site-specific conditions (disturbance-reduced conditions). The primary goal is to determine whether the estimate of SOC can be improved under more favourable site-specific conditions, as well as the impact of pre-treatment algorithms on both less and more favourable disturbed conditions. The study employed a large range of pretreatment algorithms and their combinations. Three separate multivariate models were used to predict SOC, namely Cubist, support vector machine regression (SVMR), and partial least squares regression (PLSR). The result clearly shows that reduced disturbing factors (i.e., drier and unploughed soil as well as noise reduction) result in an improvement of SOC prediction with in situ Vis-NIR spectroscopy. The best overall result was achieved with SVMR (R²_CV = 0.72, RMSEPcv = 0.21, RPIQ = 2.34). Although the combination of pre-treatment algorithms resulted in an improvement, overall, these pre-treatment algorithms could not compensate for the factors affecting the measured spectra with disturbance. Though the obtained result is promising, further study is still needed to disentangle the impacts and interactions of various disturbing factors for different soil types.

The Grain-for-Green project offsets warming-induced soil organic carbon loss and increases soil carbon stock in Chinese Loess Plateau

The dynamics of soil organic carbon (SOC) stock is a vital element affecting the climate, and ecological restoration is potentially an effective measure to mitigate climate change by enhancing vegetation and soil carbon stocks and thereby offsetting greenhouse gas emissions. The Grain-for-Green project (GFGP) implemented in Chinese Loess Plateau (LP) since 1999 is one of the largest ecological restoration projects in the world. However, the contributions of ecological restoration and climate change to ecosystem soil carbon sequestration are still unclear. In this study, we improved a soil carbon decomposition framework by optimizing the initial SOC stock based on full spatial simulation of SOC and incorporating the priming effect to investigate the SOC dynamics across the LP GFGP region from 1982 through 2017. Our results indicated that SOC stock in the GFGP region increased by 20.18 Tg C from 1982 through 2017. Most portion (15.83 Tg C) of the SOC increase was accumulated when the GFGP was initiated, with a SOC sink of 16.12 Tg C owing to revegetation restoration and a carbon loss of 0.29 Tg C due to warming during this period. The relationships between SOC and forest canopy height and investigations on the SOC dynamics after afforestation revealed that the accumulation rate of SOC could be as high as 24.68 g C m^-2 yr^-1 during the 70 years following afforestation, and that SOC could decline thereafter (-8.89 g C m^-2 yr^-1), which was mainly caused by warming. This study provides a new method for quantifying the contribution of ecological restoration to SOC changes, and also cautions the potential risk of LP SOC loss in the mature forest soil under future warming.

A year-long study on PM2.5 and its carbonaceous components over eastern Himalaya in India: Contributions of local and transported fossil fuel and biomass burning during premonsoon

A year-long (March 2019-February 2020) study on the characterization of fine mode carbonaceous aerosols has been conducted over a high altitude urban atmosphere, Darjeeling (27.01°N, 88.15°E, 2200 m asl) in eastern Himalaya. The fine mode aerosol (PM_2.5; 41.7 ± 23.7 μgm^-3), total carbonaceous aerosols (TCA; 19.8 ± 7.7 μgm^-3), organic carbon (OC; 8.0 ± 3.9 μgm^-3) and elemental carbon (EC; 2.0 ± 0.9 μgm^-3) exhibited similar seasonal variability with the highest abundance during winter followed by premonsoon, postmonsoon and minimum in monsoon. The OC:EC varied over a range of 2.8-19.4 whereas the secondary organic carbon ranged between 1.9 and 17.1 μgm^-3 respectively. Higher PM_2.5 associated with higher winds and elevated mixing layer depth suggest a strong influence of regional and long-range transport. In addition to the usual morning and evening rush-hour peaks, the impact of low land plain regions driven by up-slope valley winds was observed for the carbonaceous components. A novel approach has been taken to find out the individual contributions from the local and transported fossil fuel, biomass burning, and biogenic sources to OC and EC during premonsoon. We observed that the local fossil fuel (43%) contributions dominated over the biomass burning (39%) for EC whereas the contributions of local biomass burning and the local fossil fuel were same (46%) for OC. EC exhibited a higher contribution (18%) from the regional/long-range transport compared to OC (8%). IGP and Nepal were found to be the maximum contributing long distant source regions for the carbonaceous aerosol loading over eastern Himalaya. Such individual source apportionment of carbonaceous aerosols over eastern Himalaya makes the study unique and first-ever of its kind and immensely helpful for building robust mitigation action plans.

Soil microbial community and physicochemical properties together drive soil organic carbon in Cunninghamia lanceolata plantations of different stand ages

Carbon sequestration in forest soil is critical for reducing atmospheric greenhouse gas concentrations and slowing down global warming. However, little is known about the difference in soil organic carbon (SOC) among different stand ages and the relative importance of biotic and abiotic variations such as soil microbial community and soil physicochemical properties in the regulation of SOC in forests. In the present study, we measured the SOC of the topsoil (0-10 cm) in Chinese subtropical Cunninghamia lanceolata plantations of three different stand ages (young plantation of 6 years, middle-aged plantation of 12 years, and mature plantation of 25 years). We further measured microbial community composition by phospholipid fatty acid (PLFA) analysis and soil organic carbon physical fractions by wet sieving and density floating as well as other physicochemical properties. The effects of the main impact factors on SOC were investigated. The results showed that: the middle-aged plantation had significantly higher SOC (10.63 g kg^-1) than the young plantation (5.33 g kg^-1), and that of the mature plantation (7.83 g kg^-1) was in between. Besides, the soil total PLFAs and all the functional groups (i.e., bacteria, fungi, actinomycetes, Gram-positive bacteria, and Gram-negative bacteria) of PLFAs were significantly higher in the middle-aged plantation than in the young plantation and the mature plantation. Soil physicochemical properties, including physical fractions, differed among plantations of the three stand ages. Notably, the proportion of organic carbon protected within microaggregates was significantly higher in the middle-aged plantation (40.4%) than those in the young plantation (29.2%) and the mature plantation (27.8%), indicating that the middle-aged Cunninghamia lanceolata plantation had stronger soil organic carbon stability. Both soil microbial community and physicochemical properties exerted dominant effects on SOC and jointly explained 82.7% of the variance of SOC among different stand ages. Among them, total and all the functional groups of PLFAs, nitrate nitrogen, total nitrogen, and organic carbon protected within microaggregates had a significant positive correlation with SOC. These results highlight the important role of soil biotic and abiotic factors in shaping the contents of SOC in forests of different stand ages. This study provides a theoretical basis for forestry management and forest carbon cycling models.

Estimation of Soil Organic Carbon Using Vis-NIR Spectral Data and Spectral Feature Bands Selection in Southern Xinjiang, China

Soil organic carbon (SOC) plays an important role in the global carbon cycle and soil fertility supply. Rapid and accurate estimation of SOC content could provide critical information for crop production, soil management and soil carbon pool regulation. Many researchers have confirmed the feasibility and great potential of visible and near-infrared (Vis-NIR) spectroscopy in evaluating SOC content rapidly and accurately. Here, to evaluate the feasibility of different spectral bands variable selection methods for SOC prediction, we collected a total of 330 surface soil samples from the cotton field in the Alar Reclamation area in the southern part of Xinjiang, which is located in the arid region of northwest China. Then, we estimated the SOC content using laboratory Vis-NIR spectral. The Particle Swarm optimization (PSO), Competitive adaptive reweighted sampling (CARS) and Ant colony optimization (ACO) were adopted to select SOC feature bands. The partial least squares regression (PLSR), random forest (RF) and convolutional neural network (CNN) inversion models were constructed by using full-bands (400-2400 nm) spectra (R) and feature bands, respectively. And we also analyzed the effects of spectral feature band selection methods and modeling methods on the prediction accuracy of SOC. The results indicated that: (1) There are significant differences in the feature bands selected using different methods. The feature bands selected methods substantially reduced the spectral variable dimensionality and model complexity. The models built by the feature bands selected by CARS, PSO and ACO methods showed the different potential of improvement in model accuracy compared with the full-band models. (2) The CNN model had the best performance for predicting SOC. The R² of the optimal CNN model is 0.90 in the validation, which was improved by 0.05 and 0.04 in comparison with the PLSR and RF model, respectively. (3) The highest prediction accuracy was archived by the CNN model using the feature bands selected by CARS (validation set R² = 0.90, RMSE = 0.97 g kg^-1, RPD = 3.18, RPIQ = 3.11). This study indicated that using the CARS method to select spectral feature bands, combined with the CNN modeling method can well predict SOC content with higher accuracy.

Spatiotemporal changes in greenhouse gas emissions and soil organic carbon sequestration for major cropping systems across China and their drivers over the past two decades

Chinese agricultural systems have experienced dramatic changes in crop planting area, cropping system, irrigation and fertilization managements, and crop yields in recent decades. These changes can substantially affect greenhouse gases (GHG) emissions and soil organic carbon (SOC) sequestration in croplands. However, the spatiotemporal patterns, as well as their driving factors and mechanisms, have not been well understood. Here, the Denitrification-Decomposition model is calibrated and validated to estimate nitrous oxide (N₂O) and methane (CH₄) emissions and SOC sequestration for seven major cropping systems in China during 2001-2020. The Logarithmic Mean Divisia Index method is further applied to attribute the net GHG emissions (NGEs) trend to various drivers. The results show that the total N₂O emissions, CH₄ emissions, and SOC sequestration were approximately 23.7, 182.0, and 177.6 Tg CO₂-eq/year in the croplands across China. The national average NGEs per unit area ranged from -8705 to 8431 kg CO₂-eq ha^-1 year^-1 across the major cropping systems. During 2001-2020, the trend in national annual NGEs was 0.66 kg CO₂-eq ha^-1 year^-2, ranging from -78.9 to 82.2 kg CO₂-eq ha^-1 year^-2 across the major cropping systems. The paddy lands were mainly a carbon source due to the large amount of CH₄ emissions while the uplands could be a carbon sink owing to SOC sequestration. As a whole, the cropland in China was a carbon source with the NGEs equal to 28.4 Tg CO₂-eq/year, and the NGEs increased by 0.047 Tg CO₂-eq/year² in the past 20 years. Nationally, changes in crop planting area and yields reduced the NGEs whereas changes in nitrogen use efficiency and cropping systems increased them, although the major factors and their impacts varied greatly among regions. Optimizing cropping systems and nitrogen fertilization based on the local genotype, environment and management should be the most effective method to reduce the NGEs in croplands.

Feasibility of a Novel Sparse Orthogonal Collimator-Based Preclinical Total Marrow Irradiation for Enhanced Dosimetric Conformality

Total marrow irradiation (TMI) has significantly improved radiation conditioning for hematopoietic cell transplantation in hematologic diseases by reducing conditioning-induced toxicities and improving survival outcomes in relapsed/refractory patients. Recently, preclinical three-dimensional image-guided TMI has been developed to enhance mechanistic understanding of the role of TMI and to support the development of experimental therapeutics. However, a dosimetric comparison between preclinical and clinical TMI reveals that the preclinical TMI treatment lacks the ability to reduce the dose to some of the vital organs that are very close to the skeletal system and thus limits the ability to evaluate radiobiological relevance. To overcome this limit, we introduce a novel Sparse Orthogonal Collimator (SOC)-based TMI and evaluate its ability to enhance dosimetric conformality. The SOC-TMI-based dose modulation technique significantly improves TMI treatment planning by reducing radiation exposures to critical organs that are close to the skeletal system that leads to reducing the gap between clinical and preclinical TMI.

Beware the Grizzlyman: A comparison of job- and industry-based noise exposure estimates using manual coding and the NIOSH NIOCCS machine learning algorithm

Recently, the National Institute for Occupational Safety and Health (NIOSH) released an updated version of the NIOSH Industry and Occupation Computerized Coding System (NIOCCS), which uses supervised machine learning to assign industry and occupational codes based on provided free-text information. However, no efforts have been made to externally verify the quality of assigned industry and job titles when the algorithm is provided with inputs of varying quality. This study sought to evaluate whether the NIOCCS algorithm was sufficiently robust with low-quality inputs and how variable quality could impact subsequent job estimated exposures in a large job-exposure matrix for noise (NoiseJEM). Using free-text industry and job descriptions from >700,000 noise measurements in the NoiseJEM, three files were created and input into NIOCCS: (1) N1, "raw" industries and job titles; (2) N2, "refined" industries and "raw" job titles; and (3) N3, "refined" industries and job titles. Standardized industry and occupation codes were output by NIOCCS. Descriptive statistics of performance metrics (e.g., misclassification/discordance of occupation codes) were evaluated for each input relative to the original NoiseJEM dataset (N0). Across major Standardized Occupational Classifications (SOC), total discordance rates for N1, N2, and N3 compared to N0 were 53.6%, 42.3%, and 5.0%, respectively. The impact of discordance on the major SOC group varied and included both over- and under-estimates of average noise exposure compared to N0. N2 had the most accurate noise exposure estimates (i.e., smallest bias) across major SOC groups compared to N1 and N3. Further refinement of job titles in N3 showed little improvement. Some variation in classification efficacy was seen over time, particularly prior to 1985. Machine learning algorithms can systematically and consistently classify data but are highly dependent on the quality and amount of input data. The greatest benefit for an end-user may come from cleaning industry information before applying this method for job classification. Our results highlight the need for standardized classification methods that remain constant over time.

Interleukin-6 inhibitors reduce mortality in coronavirus disease-2019: An individual patient data meta-analysis from randomized controlled trials

OBJECTIVE

To assess the efficacy of IL-6 inhibitors compared to standard of care (SOC) in COVID-19 patients.

DATA SOURCES

A systematic review of the MEDLINE and Scopus databases (last search: October 8^th, 2021) was performed according to the PRISMA statement.

STUDY SELECTION

Randomized control trials (RCTs) comparing IL-6 inhibitors to SOC in hospitalized COVID-19 patients were deemed eligible.

DATA EXTRACTION AND SYNTHESIS

Individual patient data were extracted from the Kaplan-Meier curves or were obtained from authors of included studies. Additionally, the reviewers independently abstracted data and assessed study quality of each eligible report.

RESULTS

Eleven studies were identified, incorporating 7467 patients (IL-6 inhibitors: 4103, SOC: 3364). IL-6 inhibitors were associated with decreased risk for death compared to SOC at the one-stage meta-analysis (Hazard Ratio [HR]: 0.75, 95% Confidence interval [CI]: 0.69-0.82, p<0.0001) and the two-stage meta-analysis (HR: 0.85, 95%CI: 0.77-0.93, p<0.001, I² = 0.0%). Meta-regression analysis revealed that the difference in OS between the two groups was not influenced by the mean age of patients. At secondary meta-analyses, IL-6 inhibitors were associated with decreased odds for intubation OR:0.74, 95%CI:0.65-0.85, p<0.001, I²=0.0%). IL-6 inhibitors were associated with increased odds for discharge compared to SOC (OR:1.28, 95% CI:1.15-1.42, p<0.001, I²=0.0%).

CONCLUSIONS AND RELEVANCE

This meta-analysis of individual patient data from randomized trials shows that IL-6 inhibitors significantly reduce the risk of death compared to SOC. IL-6 inhibitors are also associated with better outcomes in terms of intubation and discharge rates compared to SOC.

The effects of plastic film mulching and straw mulching on licorice root yield and soil organic carbon content in a dryland farming

The increasing worldwide demand for traditional herbs has been met by growing cultivated herbs. It is undoubtedly very important to seek a reasonable cultivation mode for the yield, quality and long-term production stability of traditional herbs. In this study, licorice (Glycyrrhiza uralensis Fisch.) was investigated using a field experiment and a process-based model (Denitrification-Decomposition (DNDC) model) to study the effects of mulching methods on root yield and soil organic carbon (SOC) long-term changes. The field experiment contained four treatments: plat planting without mulching (CK), ridge-furrow maize straw mulching (SM), ridge-furrow plastic film mulching (RP), and plat planting with plastic film mulching (FP). Licorice root yield was significantly higher in the SM, RP, and FP than in the CK. SM, RP and FP treatments increased the accumulation of liquiritin and glycyrrhizin in licorice roots. The SM significantly increased SOC content, SOC stocks, SOC sequestration rate, dissolved organic carbon (DOC) content and microbial biomass carbon (MBC) compared to CK, but there was no significant difference in SOC and DOC among CK, RP and FP. The DNDC model was calibrated based on the field test data and showed that under the four CMIP6 SSPs scenarios, the predicted root yield of each treatment was increasing obviously. The production and stability of RP and FP were greater than CK and SM. The SOC under SM showed an increasing trend, whereas it continuously decreased under CK, RP, and FP in the future. The SOC of simulated RS treatment of straw incorporation plus a plastic film mulch was always at the highest value in all the treatments, and its root yield was slightly lower than that of RP and FP, the latter both were very close. Therefore, it is suggested that RS should be adopted to achieve sustained high yield while maintaining a high SOC level.

Psychological factors and the use of psychoactive substances in relation to sexual orientation: A study on Israeli young adults

In the context of sexual minorities and the distress they may experience, recent years have witnessed a trend emphasizing the idea that protective factors may curb risk behaviors, while stressing that not all sexual minorities do experience distress. However, protective factors have been studied less frequently than have risk factors. To the extent that protective factors are identified among those at risk for psychological distress and risk behaviors, strategies can seek to address risk by enhancing these protective factors. The current study aimed to expand the knowledge in this area by simultaneously examining protective and risk factors as well as by examining the association between sexual orientation, psychological distress, sense of coherence (SOC), social support (e.g., parental and peer relationships), and alcohol and cannabis use among Israeli young adults. A self-reported questionnaire was distributed to 496 young adults: 254 heterosexual participants and 242 homosexual participants. As hypothesized, participants with a same-sex orientation reported higher psychological distress, lower SOC, a weaker relationship with their parents, and a greater use of alcohol and cannabis than did heterosexual participants. Regression analyses indicated that low SOC, low family support, and low peer support predicted higher psychological distress. However, sexual orientation was not found to predict distress levels among young adults in Israel. Similarly, no associations were found between alcohol and cannabis use and psychological distress. The results are discussed within the framework of resilience factors that can serve as a barrier to distress and to the use of psychoactive substances among young adults in general and sexual minorities in particular.

Does liming grasslands increase biomass productivity without causing detrimental impacts on net greenhouse gas emissions?

Soil acidification has negative impacts on grass biomass production and the potential of grasslands to mitigate greenhouse gas (GHG) emissions. Through a global review of research on liming of grasslands, the objective of this paper was to assess the impacts of liming on soil pH, grass biomass production and total net GHG exchange (nitrous oxide (N₂O), methane (CH₄) and net carbon dioxide (CO₂)). We collected 57 studies carried out at 88 sites and covering different countries and climatic zones. All of the studies examined showed that liming either reduced or had no effects on the emissions of two potent greenhouse gases (N₂O and CH₄). Though liming of grasslands can increase net CO₂ emissions, the impact on total net GHG emission is minimal due to the higher global warming potential, over a 100-year period, of N₂O and CH₄ compared to that of CO₂. Liming grassland delivers many potential advantages, which justify its wider adoption. It significantly ameliorates soil acidity, increases grass productivity, reduces fertiliser requirement and increases species richness. To realise the maximum benefit of liming grassland, we suggest that acidic soils should be moderately limed within the context of specific climates, soils and management.

Decipher soil organic carbon dynamics and driving forces across China using machine learning

The dynamics of soil organic carbon (SOC) play a critical role in modulating global warming. However, the long-term spatiotemporal changes of SOC at large scale, and the impacts of driving forces remain unclear. In this study, we investigated the dynamics of SOC in different soil layers across China through the1980s to 2010s using a machine learning approach and quantified the impacts of the key factors based on factorial simulation experiments.Our results showed that the latest (2000-2014) SOC stock in the first meter soil (SOC₁₀₀ ) was 80.68 ± 3.49 Pg C, of which 42.6% was stored in the top 20 cm, sequestrating carbon with a rate of 30.80 ± 12.37 g C m^-2  yr^-1 since the 1980s. Our experiments focusing on the recent two periods (2000s and 2010s) revealed that climate change exerted the largest relative contributions to SOC dynamics in both layers and warming or drying can result in SOC loss. However, the influence of climate change weakened with soil depth, while the opposite for vegetation growth. Relationships between SOC and forest canopy height further confirmed this strengthened impact of vegetation with soil depth and highlighted the carbon sink function of deep soil in mature forest. Moreover, our estimates suggested that SOC dynamics in 71% of topsoil were controlled by climate change and its coupled influence with environmental variation (CE). Meanwhile, CE and the combined influence of climate change and vegetation growth dominated the SOC dynamics in 82.05% of the first meter soil. Additionally, the national cropland topsoil organic carbon increased with a rate of 23.6 ± 7.6 g C m^-2  yr^-1 since the 1980s, and the widely applied nitrogenous fertilizer was a key stimulus. Overall, our study extended the knowledge about the dynamics of SOC and deepened our understanding about the impacts of the primary factors.

Can conservation agriculture mitigate climate change and reduce environmental impacts for intensive cropping systems in North China Plain?

Determining appropriate farming management practices to adapt to climate change with lower environmental costs is important for sustainable agricultural production. In this study, a long-term experiment (1985-2019) was conducted under different management practices combining fertilization rate (no, low and high N fertilizer, N₀, N₁ and N₂), straw additions (no, low and high addition, S₀, S₁ and S₂) with conservation tillage (no-tillage, NT) in the North China Plain (NCP). The Denitrification-Decomposition (DNDC) model was firstly evaluated using the experimental data, and then applied to simulate the changes of crop yields, soil organic carbon (SOC), and N₂O emissions under different management practices combined with climate change scenarios, under low and high emission scenarios of societal development pathways (SSP245 and SSP585, respectively) with climate projections from 2031 to 2100. Under the low emission scenario (SSP245), wheat yields were the highest with the NT-N₁-S₂ treatment (a 23% increase relative to the baseline (1981-2010)). For maize yields, the NT-N₁-S₁ treatment increased 46% relative to baseline under the SSP585, whereas, the yields increased less in all treatments under SSP245-2040s. The SOC was predicted to increase by 6-60% by 2100 under SSP245. Straw addition and tillage were the main factors influencing SOC. N fertilizer was the most important driver for wheat and maize yields, however, N₂O emissions from soil increased with increased application of N fertilizer. Therefore, the no-tillage method under low N fertilizer and high straw addition (NT-N₁-S₂) is recommended to promote crop yields and substantially increase SOC under SSP245 and SSP585. Conservation agriculture practices can potentially offset crop yield reductions, increase soil quality, and reduce greenhouse gas emissions in the NCP, and ensure crop production to meet the growing demand for food under future climate change.

Eight years organic amendment application alters N2O emission potential by increasing soil O2 consumption rate

Organic amendments are efficient measures that can be employed to increase both nitrogen use efficiency and soil organic carbon (SOC) content. However, the long-term effects of such measures on soil N₂O emission and the associated underlying mechanisms are still unclear. Here, we sampled soils that were part of two long-term trials after eight years of different amounts and types of organic amendment addition, and investigated the response of soil N₂O emissions to different types of mineral N addition under oxic condition. Further, we selected two soil samples with a large difference in SOC content and investigated the responses of soil CO₂, N₂O, NO, and N₂ emissions as well as O₂ consumption to NH₄⁺, NO₃^-, and nitrification inhibitor addition under limited O₂ diffusion condition and anoxic condition. Results showed that long-term organic amendments significantly increased SOC content, while the stimulated effect on N₂O and N₂ emissions owing to increased SOC contents was more pronounced with NH₄⁺ addition under limited O₂ diffusion condition than under oxic or anoxic conditions. Further, in all treatments under limited O₂ diffusion condition, soil O₂ concentration and N₂O production showed significant inverse relationships, suggesting that O₂ directly regulates N₂O production. We speculated that the decrease in O₂ availability with higher SOC contents owing to enhanced soil respiration, instead of the increased supply of electron donors, is primarily responsible for the stimulated N₂O emissions. This implied that practices which reduce limited O₂ diffusion conditions might help to minimize the stimulated N₂O emissions from increased SOC content.

Patient Perceptions of Dermatologic Photography: Scoping Review

BACKGROUND

Medical photography is used extensively in dermatology to record disease progression, measure treatment response, and help teach patients about skin disease; such photos are also commonly utilized in teledermatology, medical education, research, and medical reference websites. Understanding patient perceptions of medical photographs obtained during dermatologic care in the clinic or hospital setting is critical to enable the delivery of high-quality, patient-centered medical care.

OBJECTIVE

The aims of this study were to elucidate patient perceptions of skin photos in dermatology and to explore possible next steps in improving the patient experience with medical photography in the hospital or clinic setting.

METHODS

A scoping review of the literature was performed using the PubMed database, with clinic- or hospital-based full-text publications in English spanning the last 10 years considered for inclusion.

RESULTS

The majority of included studies (10/11, 91%) found positive patient attitudes toward medical photographs. The majority of patients (1197/1511, 79.2%) felt that medical photographs could improve medical care in the clinic setting. Written consent detailing all photo uses, including secondary uses (such as research or teaching), was preferred, apart from in 1 study. Patients preferred or found it acceptable for the photographer of their medical photos to be a physician (1301/1444, 90.1%). Clinic-owned cameras with departmental record storage were the preferred modality. Latinx and African American patients expressed less trust in the utility of medical photographs to improve care, compared with Asian and White patients. The minimal number of available publications on this topic and the inclusion of articles older than 5 years are limitations, since patient perceptions of medical photography may have rapidly changed during this time span, particularly in light of the COVID-19 pandemic and the subsequent increase in teledermatology visits.

CONCLUSIONS

Patients reported positive perceptions of dermatologic photography for improving their medical care. Ethnic disparities in patient perceptions require further exploration to better elucidate nuances and develop interventions to improve the experience of marginalized patients. Building patient trust in nonphysician photographers may enhance clinic efficiency. Although clinic-owned cameras are well-accepted by patients, improved patient education surrounding the safety of electronic medical record phone applications is needed.

A novel intelligence approach based active and ensemble learning for agricultural soil organic carbon prediction using multispectral and SAR data fusion

Monitoring agricultural soil organic carbon (SOC) has played an essential role in sustainable agricultural management. Precise and robust prediction of SOC greatly contributes to carbon neutrality in the agricultural industry. To create more knowledge regarding the ability of remote sensing to monitor carbon soil, this research devises a state-of-the-art low cost machine learning model for quantifying agricultural soil carbon using active and ensemble-based decision tree learning combined with multi-sensor data fusion at a national and world scale. This work explores the use of Sentinel-1 (S1) C-band dual polarimetric synthetic aperture radar (SAR), Sentinel-2 (S2) multispectral data, and an innovative machine learning (ML) approach using an integration of active learning for land-use mapping and advanced Extreme Gradient Boosting (XGBoost) for robustness of the SOC estimates. The collected soil samples from a field survey in Western Australia were used for the model validation. The indicators including the coefficient of determination (R²) and root - mean - square - error (RMSE) were applied to evaluate the model's performance. A numerous features computed from optical and SAR data fusion were employed to build and test the proposed model performance. The effectiveness of the proposed machine learning model was assessed by comparing with the two well-known algorithms such as Random Forests (RF) and Support Vector Machine (SVM) to predict agricultural SOC. Results suggest that a combination of S1 and S2 sensors could effectively estimate SOC in farming areas by using ML techniques. Satisfactory accuracy of the proposed XGBoost with optimal features was achieved the highest performance (R² = 0.870; RMSE = 1.818 tonC/ha) which outperformed RF and SVM. Thus, multi-sensor data fusion combined with the XGBoost lead to the best prediction results for agricultural SOC at 10 m spatial resolution. In short, this new approach could significantly contribute to various agricultural SOC retrieval studies globally.

Aspirin and Sulindac act via different mechanisms to inhibit store-operated calcium channel: Implications for colorectal cancer metastasis

Store-operated Ca²⁺ channel (SOC)-regulated Ca²⁺ entry is involved in inflammation and colorectal cancer (CRC) progression, but clinically applicable treatments targeting this mechanism are lacking. Recent studies have shown that nonsteroidal anti-inflammatory drugs (NSAIDs) not only inhibit inflammation but they also suppress Ca²⁺ entry via SOC (SOCE). Therefore, delineating the mechanisms of SOCE inhibition by NSAIDs may lead to new CRC treatments. In this study, we tested eight candidate NSAIDs in Ca²⁺ imaging experiments and found that Aspirin and Sulindac were the most effective at suppressing SOCE. Furthermore, time-lapse FRET imaging using TIRF microscopy and ground state depletion (GSD) super-resolution (SR) imaging revealed that SOC was inhibited by Aspirin and Sulindac via different mechanisms. Aspirin quickly interrupted the STIM1-Orai1 interaction, whereas Sulindac mainly suppressed STIM1 translocation. Additionally, Aspirin and Sulindac both inhibited metastasis-related endpoints in CRC cells. Both drugs were used throughout the study at doses that suppressed CRC cell migration and invasion without altering cell survival. This is the first study to reveal the differential inhibitory mechanisms of Aspirin and Sulindac on SOC activity. Thus, our results shed new light on the therapeutic potential of Aspirin for CRC and SOCE-related diseases.

CircSETDB1 knockdown inhibits the malignant progression of serous ovarian cancer through miR-129-3p-dependent regulation of MAP3K3

Background

Circular RNA (circRNA) is recently found to participate in the regulation of tumor progression, including ovarian cancer. However, the application of circRNA SET domain bifurcated histone lysine methyltransferase 1 (circSETDB1) as a therapeutic target in serous ovarian cancer (SOC) remains to be elucidated. Herein, circSETDB1 role in SOC malignant progression and underlying mechanism are revealed.

Methods

The expression of circSETDB1, microRNA-129-3p (miR-129-3p) and mitogen-activated protein kinase kinase kinase 3 (MAP3K3) messenger RNA (mRNA) was detected by quantitative real-time polymerase chain reaction. Protein abundance was determined by western blot analysis. Cell proliferation, apoptosis, invasion and migration were demonstrated by cell counting kit-8 and 5-Ethynyl-29-deoxyuridine assays, flow cytometry analysis, transwell invasion assay and wound-healing assay, respectively. The interaction between miR-129-3p and circSETDB1 or MAP3K3 was predicted by online database, and identified by mechanism assays. The effect of circSETDB1 knockdown on tumor formation in vivo was unveiled by mouse model experiment.

Results

CircSETDB1 and MAP3K3 expression were apparently upregulated, whereas miR-129-3p expression was downregulated in SOC tissues and cells in comparison with normal fallopian tube tissues or normal ovarian epithelial cells. CircSETDB1 knockdown inhibited cell proliferation, invasion and migration, but induced cell apoptosis in SOC cells. Additionally, miR-129-3p inhibitor impaired circSETDB1 silencing-mediated SOC malignant progression. MiR-129-3p repressed SOC cell processes via binding to MAP3K3. Furthermore, circSETDB1 knockdown suppressed tumor growth in vivo.

Conclusion

CircSETDB1 silencing repressed SOC malignant progression through miR-129-3p/MAP3K3 pathway. This study supports circSETDB1 as a new therapeutic target for SOC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00875-0.

1. CircSETDB1 expression was increased in SOC tissues and cells.

2. CircSETDB1 silencing repressed the malignancy of SOC cells.

3. CircSETDB1 mediated SOC malignant progression by interacting with miR-129-3p.

4. MAP3K3 served as a target gene of miR-129-3p.

5. CircSETDB1 knockdown inhibited tumor formation in vivo.

Apparent Power Laws Can Occur without Criticality

Power laws often lead to the conclusion that self-organized criticality is at work. This is not the case, and power laws can also occur away from criticality or can occur for other reasons.

Various Nodal Lines in P63/mmc-type TiTe Topological Metal and its (001) Surface State

Searching for existing topological materials is a hot topic in quantum and computational chemistry. This study uncovers P6₃/mmc type TiTe compound—an existing material—is a newly discovered topological metal that hosts the various type of nodal line states. Different nodal line states normally exhibit different properties; they may have their individual applications. We report that TiTe hosts I, II, and hybrid type nodal line (NL) states at its ground state without chemical doping and strain engineering effects. Specifically, two type I NLs, two hybrid-type NLs, and one Γ—centered type II NL can be found in the k_z = 0 plane. Moreover, the spin-orbit coupling induced gaps for these NLs are very small and within acceptable limits. The surface states of the TiTe (001) plane were determined to provide strong evidence for the appearance of the three types of NLs in TiTe. We also provide a reference for the data of the dynamic and mechanical properties of TiTe. We expect that the proposed NL states in TiTe can be obtained in future experiments.