chngpt: threshold regression model estimation and inference

Association between exposure to metalworking fluid aerosols, occupational noise and chronic kidney disease: a cross-sectional study in China

BACKGROUND

Chronic kidney disease (CKD) carries a high public health burden yet little is known about the relationship between metalworking fluid (MWF) aerosols, occupational noise and CKD. We aimed to explore the relationship between occupational MWF aerosols, occupational noise and CKD.

METHODS

A total of 2,738 machinists were sampled from three machining companies in Wuxi, China, in 2022. We used the National Institute for Occupational Safety and Health (NIOSH) method 5524 to collect individual samples for MWF aerosols exposure, and the Chinese national standard (GBZ/T 189.8-2007) method to test individual occupational noise exposure. The diagnostic criteria for CKD were urinary albumin/creatinine ratio (UACR) of ≥ 30 mg/g and reduced renal function (eGFR < 60 mL.min- 1. 1.73 m- 2) lasting longer than 3 months. Smooth curve fitting was conducted to analyze the associations of MWF aerosols and occupational noise with CKD. A segmented regression model was used to analyze the threshold effects.

RESULTS

Workers exposed to MWF aerosols (odds ratio [OR] = 2.03, 95% confidence interval [CI]: 1.21-3.41) and occupational noise (OR = 1.77, 95%CI: 1.06-2.96) had higher prevalence of CKD than nonexposed workers. A nonlinear and positive association was found between increasing MWF aerosols and occupational noise dose and the risk of CKD. When daily cumulative exposure dose of MWF aerosols exceeded 8.03 mg/m3, the OR was 1.24 (95%CI: 1.03-1.58), and when occupational noise exceeded 87.22 dB(A), the OR was 1.16 (95%CI: 1.04-1.20). In the interactive analysis between MWF aerosols and occupational noise, the workers exposed to both MWF aerosols (cumulative exposure ≥ 8.03 mg/m3-day) and occupational noise (LEX,8 h ≥ 87.22 dB(A)) had an increased prevalence of CKD (OR = 2.71, 95%CI: 1.48-4.96). MWF aerosols and occupational noise had a positive interaction in prevalence of CKD.

CONCLUSIONS

Occupational MWF aerosols and noise were positively and nonlinearly associated with CKD, and cumulative MWF aerosols and noise exposure showed a positive interaction with CKD. These findings emphasize the importance of assessing kidney function of workers exposed to MWF aerosols and occupational noise. Prospective and longitudinal cohort studies are necessary to elucidate the causality of these associations.

Identifying heat thresholds for South Africa towards the development of a heat-health warning system

Exposure to heatwaves may result in adverse human health impacts. Heat alerts in South Africa are currently based on defined temperature-fixed threshold values for large towns and cities. However, heat-health warning systems (HHWS) should incorporate metrics that have been shown to be effective predictors of negative heat-related health outcomes. This study contributes to the development of a HHWS for South Africa that can potentially minimize heat-related mortality. Distributed lag nonlinear models (DLNM) were used to assess the association between maximum and minimum temperature and diurnal temperature range (DTR) and population-adjusted mortality during summer months, and the effects were presented as incidence rate ratios (IRR). District-level thresholds for the best predictor from these three metrics were estimated with threshold regression. The mortality dataset contained records of daily registered deaths (n = 8,476,532) from 1997 to 2013 and data for the temperature indices were for the same period. Maximum temperature appeared to be the most statistically significant predictor of all-cause mortality with strong associations observed in 40 out of 52 districts. Maximum temperature was associated with increased risk of mortality in all but three of the districts. Our results also found that heat-related mortality was influenced by regional climate because the spatial distribution of the thresholds varied according to the climate zones across the country. On average, districts located in the hot, arid interior provinces of the Northern Cape and North West experienced some of the highest thresholds compared to districts located in temperate interior or coastal provinces. As the effects of climate change become more significant, population exposure to heat is increasing. Therefore, evidence-based HHWS are required to reduce heat-related mortality and morbidity. The exceedance of the maximum temperature thresholds provided in this study could be used to issue heat alerts as part of effective heat health action plans.

Groundwater-surface water interactions in a semi-arid irrigated agricultural valley: A hydrometric and tracer-aided approach

The purpose of this study was to assess hydrological controls (e.g., rainfall, irrigation practices, river discharge, dam operation, evaporation) on surface (SW)- ground water (GW) interactions in an irrigated valley within semi-arid Patagonia Argentina (-65.49 W, -43.29 S). We combined different sampling designs (watershed/sub-watershed scales, longitudinal and monthly samplings) from 2015 to 2019 to investigate the temporal and spatial variation of hydrometrics, electrical conductivity (EC) and stable isotope composition of surface and ground water. Results showed that plant transpiration in the upper basin, evaporation in the middle basin and the reservoir dynamics modified water salinity and left an imprint in stable isotopes. Water tables in the irrigated valley were high (0.5-2 m level from soil surface) and presented higher salinity than river water. Groundwater salinity, temporal variation of water table levels and stable isotopes suggested that groundwater is subjected to evaporation, is recharged from field seepage and, at a lesser extent, from local rainwater. River salinity increased downstream of the irrigated valley during the whole study period (3 years), showing the effects of agriculture and urbanization. EC also responded to the opening and closing of irrigation channels. EC and daily discharge statistical analysis revealed that groundwater recharge the stream below a threshold discharge of 26 m.s-1; with river salinity increasing linearly as daily discharge decrease. This study illustrates the deep modifications that agricultural systems, mainly surface irrigation, produce on semiarid watersheds. Given that SW and GW components are currently not isolated and flow regulation and irrigation practices are playing a critical role in soil quality and river chemistry at low flow conditions, a conjunctive water management strategy must be implemented in order to prevent further land and water quality degradation.

Modeling and estimating a threshold effect: An application to improving cardiac surgery practices

Estimating thresholds when a threshold effect exists has important applications in biomedical research. However, models/methods commonly used in the biomedical literature may lead to a biased estimate. For patients undergoing coronary artery bypass grafting (CABG), it is thought that exposure to low oxygen delivery (DO2) contributes to an increased risk of avoidable acute kidney injury. This research is motivated by estimating the threshold of nadir DO2 for CABG patients to help develop an evidence-based guideline for improving cardiac surgery practices. We review several models (sudden-jump model, broken-stick model, and the constrained broken-stick model) that can be adopted to estimate the threshold and discuss modeling assumptions, scientific plausibility, and implications in estimating the threshold. Under each model, various estimation methods are studied and compared. In particular, under a constrained broken-stick model, a modified two-step Newton-Raphson algorithm is introduced. Through comprehensive simulation studies and an application to data on CABG patients from the University of Michigan, we show that the constrained broken-stick model is flexible, more robust, and able to incorporate scientific knowledge to improve efficiency. The two-step Newton-Raphson algorithm has good computational performances relative to existing methods.

Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass

Crossing certain aridity thresholds in global drylands can lead to abrupt decays of ecosystem attributes such as plant productivity, potentially causing land degradation and desertification. It is largely unknown, however, whether these thresholds can be altered by other key global change drivers known to affect the water-use efficiency and productivity of vegetation, such as elevated CO2 and nitrogen (N). Using >5000 empirical measurements of plant biomass, we showed that crossing an aridity (1-precipitation/potential evapotranspiration) threshold of ∼0.50, which marks the transition from dry sub-humid to semi-arid climates, led to abrupt declines in aboveground biomass (AGB) and progressive increases in root:shoot ratios, thus importantly affecting carbon stocks and their distribution. N addition significantly increased AGB and delayed the emergence of its aridity threshold from 0.49 to 0.55 (P < 0.05). By coupling remote sensing estimates of leaf area index with simulations from multiple models, we found that CO2 enrichment did not alter the observed aridity threshold. By 2100, and under the RCP 8.5 scenario, we forecast a 0.3% net increase in the global land area exceeding the aridity threshold detected under a scenario that includes N deposition, in comparison to a 2.9% net increase if the N effect is not considered. Our study thus indicates that N addition could mitigate to a great extent the negative impact of increasing aridity on plant biomass in drylands. These findings are critical for improving forecasts of abrupt vegetation changes in response to ongoing global environmental change.

Widespread synchronous decline of Mediterranean-type forest driven by accelerated aridity

Large-scale, abrupt ecosystem change in direct response to climate extremes is a critical but poorly documented phenomenon1. Yet, recent increases in climate-induced tree mortality raise concern that some forest ecosystems are on the brink of collapse across wide environmental gradients2,3. Here we assessed climatic and productivity trends across the world's five Mediterranean forest ecosystems from 2000 to 2021 and detected a large-scale, abrupt forest browning and productivity decline in Chile (>90% of the forest in <100 days), responding to a sustained, acute drought. The extreme dry and warm conditions in Chile, unprecedented in the recent history of all Mediterranean-type ecosystems, are akin to those projected to arise in the second half of the century4. Long-term recovery of this forest is uncertain given an ongoing decline in regional water balance. This dramatic plummet of forest productivity may be a spyglass to the future for other Mediterranean ecosystems.

Threshold of 25(OH)D and consequently adjusted parathyroid hormone reference intervals: data mining for relationship between vitamin D and parathyroid hormone

PURPOSE

By recruiting reference population, we aimed to (1): estimate the 25(OH)D threshold that maximally inhibits the PTH, which can be defined as the cutoff value for vitamin D sufficiency; (2) establish the PTH reference interval (RI) in population with sufficient vitamin D.

METHODS

Study data were retrieved from LIS (Laboratory Information Management System) under literature suggested criteria, and outliers were excluded using Tukey fence method. Locally weighted regression (LOESS) and segmented regression (SR) were conducted to estimate the threshold of 25(OH)D. Multivariate linear regression was performed to evaluate the associations between PTH concentration and variables including 25(OH)D, gender, age, estimated glomerular filtration rate (EGFR), body mass index (BMI), albumin-adjusted serum calcium (aCa), serum phosphate(P), serum magnesium(Mg), and blood collection season. Z test was adopted to evaluate whether the reference interval should be stratified by determinants such as age and gender.

RESULTS

A total of 64,979 apparently healthy subjects were recruited in this study, with median (Q1, Q3) 25(OH)D of 45.33 (36.15, 57.50) nmol/L and median (Q1, Q3) PTH of 42.19 (34.24, 52.20) ng/L. The segmented regression determined the 25(OH)D threshold of 55 nmol/L above which PTH would somewhat plateau and of 22 nmol/L below which PTH would rise steeply. Multivariate linear regression suggested that gender, EGFR, and BMI were independently associated with PTH concentrations. The PTH RI was calculated as 22.17-72.72 ng/L for subjects with 25(OH)D ≥ 55 nmol/L with no necessity of stratification according to gender, age, menopausal status nor season.

CONCLUSION

This study reported 25(OH)D thresholds of vitamin D sufficiency at 55 nmol/L and vitamin D deficiency at 22 nmol/L, and consequently established PTH RIs in subjects with sufficient vitamin D for northern China population for the first time.

Effects of drought and recovery on soil volatile organic compound fluxes in an experimental rainforest

Drought can affect the capacity of soils to emit and consume biogenic volatile organic compounds (VOCs). Here we show the impact of prolonged drought followed by rewetting and recovery on soil VOC fluxes in an experimental rainforest. Under wet conditions the rainforest soil acts as a net VOC sink, in particular for isoprenoids, carbonyls and alcohols. The sink capacity progressively decreases during drought, and at soil moistures below ~19%, the soil becomes a source of several VOCs. Position specific 13C-pyruvate labeling experiments reveal that soil microbes are responsible for the emissions and that the VOC production is higher during drought. Soil rewetting induces a rapid and short abiotic emission peak of carbonyl compounds, and a slow and long biotic emission peak of sulfur-containing compounds. Results show that, the extended drought periods predicted for tropical rainforest regions will strongly affect soil VOC fluxes thereby impacting atmospheric chemistry and climate.

Vegetal protein hydrolysates reduce the yield losses in off-season crops under combined heat and drought stress

To deal with the vagaries of climate change, it is essential to develop climate-resilient agricultural practices, which improve crop productivity, and ensure food security. The impacts of high temperature and water deficit stress conditions pose serious challenges to a sustainable crop production. Several adaptation measures are practiced globally to address these challenges and among these altering the crop's typical growing season is one of the key management practices. Application of biostimulants and other growth hormones helps in compensating yield losses under abiotic stress significantly. Therefore, this study was conducted to evaluate the influence of vegetal protein hydrolysate based biostimulant to reduce the yield losses of off-season crops (soybean and chilli in summer and chickpea in early Kharif) when the temperature was higher than the regular season under water deficit stress conditions. The experiments were carried out with the foliar application of different protein hydrolysates (PHs) concentrations. The study revealed that the application of PHs significantly improved the membrane stability index, relative water content, total chlorophyll and proline content of leaves. Consequently, it led to an increase in the number of pods in soybean and chickpea, and fruits in chilli, leading to improved yields when plants were treated with the appropriate amount of PHs. Compared to untreated plants, PHs helped improve the efficiency of PS-II with significantly high photochemical efficiency (QYmax) even at higher excised leaf water loss or reduction in loss of relative water content. This study concluded that foliar application of PHs at 4, 2, and 6 ml L-1 can be beneficial for soybean, chickpea and chilli, which exhibited 17, 30, and 25% yield improvement respectively, over the untreated plants under water deficit stress. It is suggested that the benefits of PHs can be realized in soybean, chickpea and chilli under high temperature and water deficit stress. Therefore, vegetal PHs may be able to assist farmers in arid regions for boosting their income by raising market value and decreasing production barriers during the off-season.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01334-4.

Examining the role of ICT, transportation energy consumption, and urbanization in CO2 emissions in Asia: a threshold analysis

ICT is viewed in earlier research as a double-edged sword that may either help or hurt the environment. Asian nations' ICT penetration has significantly expanded in recent years, and they are eager to bring about a digital revolution by building up their ICT infrastructure while consuming less energy for transportation and urban growth. Therefore, the purpose of this article is to investigate how ICT might reduce CO₂ emissions through the use of transport energy and urban development. Empirical and theoretical debates have been remaining ambiguous and contentious topic of whether energy consumed by the transport sector and urbanization causes CO₂ emanation in Asia, and what role ICT played in determining the level of CO₂ remains unanswered. This study adds to the ongoing discussion for sustainable transportation in ten Asian nations for 30 years that concentrate on the relationship between the energy consumption of transport, urbanization, ICT, and carbon emanation (1990-2020) and checked the validity of EKC. The STIRPAT and panel threshold models having two regimes are used to explore the stochastic impacts of the dependent and explanatory variables. We have divided explanatory into two categories, that is, the threshold variable ICT and the regime-dependent variables urbanization and transport energy consumption. Our results confirm that the EKC hypothesis holds in these Asian economies. Thus, our findings indicate that the environmental quality improves in terms of reduction in CO₂ emissions when ICT passes the threshold level due to the technological advancement in ICT dominating the scale effect induced by ICT. Furthermore, the possible policy recommendations are discussed according to the findings.

Exploring the Association between Ambient Temperature and Daily Hospital Admissions for Diarrhea in Mopani District, Limpopo Province, South Africa

Diarrhea contributes significantly to global morbidity and mortality. There is evidence that diarrhea prevalence is associated with ambient temperature. This study aimed to determine if there was an association between ambient temperature and diarrhea at a rural site in South Africa. Daily diarrheal hospital admissions (2007 to 2016) at two large district hospitals in Mopani district, Limpopo province were compared to average daily temperature and apparent temperature (Tapp, 'real-feel' temperature that combined temperature, relative humidity, and wind speed). Linear regression and threshold regression, age-stratified to participants ≤5 years and >5 years old, considered changes in daily admissions by unit °C increase in Tapp. Daily ranges in ambient temperature and Tapp were 2-42 °C and -5-34 °C, respectively. For every 1 °C increase in average daily temperature, there was a 6% increase in hospital admissions for diarrhea for individuals of all ages (95% CI: 0.04-0.08; p < 0.001) and a 4% increase in admissions for individuals older than 5 years (95% CI: 0.02-0.05; p < 0.001). A positive linear relationship between average daily Tapp and all daily diarrheal admissions for children ≤5 years old was not statistically significant (95% CI: -0.00-0.03; p = 0.107). Diarrhea is common in children ≤5 years old, however, is more likely triggered by factors other than temperature/Tapp, while it is likely associated with increased temperature in individuals >5 years old. We are limited by lack of data on confounders and effect modifiers, thus, our findings are exploratory. To fully quantify how temperature affects hospital admission counts for diarrhea, future studies should include socio-economic-demographic factors as well as WASH-related data such as personal hygiene practices and access to clean water.

The impact of mortality underreporting on the association of ambient temperature and PM10 with mortality risk in time series study

Properly analyzing and reporting data remains a challenging task in epidemiologic research, as underreporting of data is often overlooked. The evaluation on the effect of underreporting remains understudied. In this study, we examined the effect of different scenarios of mortality underreporting on the relationship between PM₁₀, temperature, and mortality. Mortality data, PM₁₀, and temperature data in seven cities were obtained from Provincial Center for Disease Control and Prevention (CDC), China Meteorological Data Sharing Service System, and China National Environmental Monitoring Center, respectively. A time-series design with a distributed lag nonlinear model (DLNM) was used to examine the effects of five mortality underreporting scenarios: 1) Random underreporting of mortality; 2) Underreporting is monotonically increasing (MI) or monotonically decreasing (MD); 3) Underreporting due to holiday and weekends; 4) Underreporting occurs before the 20th day of each month, and these underreporting will be added after the 20th day of the month; and 5) Underreporting due to holiday, weekends, MI, and MD. We observed that underreporting at random (UAR) scenario had little effect on the association between PM₁₀, temperature, and daily mortality. However, other four underreporting not at random (UNAR) scenarios mentioned above had varying degrees of influence on the association between PM₁₀, temperature, and daily mortality. Additionally, in addition to imputation under UAR, the variation of minimum mortality temperature (MMT) and attributable fraction (AF) of mortality attributed to temperature in the same imputation scenarios is inconsistent in different cities. Finally, we observed that the pooled excess risk (ER) below MMT was negatively associated with mortality and the pooled ER above MMT was positively associated with mortality. This study showed that UNAR impacted the association between PM₁₀, temperature, and mortality, and potential underreporting should be dealt with before analyzing data to avoid drawing invalid conclusions.

Environment-specific selection alters flowering-time plasticity and results in pervasive pleiotropic responses in maize

Crop genetic diversity for climate adaptations is globally partitioned. We performed experimental evolution in maize to understand the response to selection and how plant germplasm can be moved across geographical zones. Initialized with a common population of tropical origin, artificial selection on flowering time was performed for two generations at eight field sites spanning 25° latitude, a 2800 km transect. We then jointly tested all selection lineages across the original sites of selection, for the target trait and 23 other traits. Modeling intergenerational shifts in a physiological reaction norm revealed separate components for flowering-time plasticity. Generalized and local modes of selection altered the plasticity of each lineage, leading to a latitudinal pattern in the responses to selection that were strongly driven by photoperiod. This transformation led to widespread changes in developmental, architectural, and yield traits, expressed collectively in an environment-dependent manner. Furthermore, selection for flowering time alone alleviated a maladaptive syndrome and improved yields for tropical maize in the temperate zone. Our findings show how phenotypic selection can rapidly shift the flowering phenology and plasticity of maize. They also demonstrate that selecting crops to local conditions can accelerate adaptation to climate change.

Drought Timing Modulates Soil Moisture Thresholds for CO2 Fluxes and Vegetation Responses in an Experimental Alpine Grassland

Drought timing determines the degree to which dry events impact ecosystems, with the ability of key processes to withstand change differing between drought periods. Findings indicate that drought timing effects vary across ecosystems, with few studies focusing on alpine grasslands. We conducted a mesocosm experiment using small grassland monoliths collected in September from the high Alps and left to overwinter at 0 °C until the experiment began in lowland Italy under late-winter outdoor conditions. Together with watered controls, we imposed three different drought treatments (zero precipitation): (1) one-month early-drought immediately after simulated snowmelt; (2) one-month mid-drought a month after melt-out; and (3) continuous two-month drought across the entire experimental period. Ecosystem responses were assessed by measuring CO2 fluxes, while vegetation responses were investigated by measuring aboveground net primary production (ANPP) of graminoids and forbs and post-harvest resprouting after one-month rehydration. We found that ecosystem respiration and gross ecosystem production (GEP) during the day were more negatively affected by mid-season drought compared to drought starting early in the season. By the end of treatments, GEP reduction under mid-season drought was similar to that of a continuous two-month drought. ANPP reduction was similar in early- and mid-drought treatments, showing a greater decrease under an enforced two-month period without precipitation. Plant resprouting, however, was only reduced in full- and mid-season drought pots, with forbs more negatively affected than graminoids. Seasonal soil moisture variation can account for these patterns: remaining winter moisture allowed almost full canopy development during the first month of the season, despite precipitation being withheld, while soil moisture depletion in the second month, resulting from higher temperatures and greater biomass, caused a collapse of gas exchange and diminished plant resprouting. Our data illustrates the importance of the timing of zero-precipitation periods for both plant and ecosystem responses in alpine grasslands.

Determining reclaimed water quality thresholds and farming practices to improve food crop yield: A meta-analysis combined with random forest model

Irrigated agricultural systems with reclaimed water (RW) play a crucial role in alleviating global water scarcity and increased food demand. However, appropriate reclaimed water quality thresholds and farming practices to improve food crop yield is virtually unclear. Therefore, for the first time, this study made a large compilation of previous studies using meta-analysis combined with a random forest (RF) model and analyzed the impact of RW versus freshwater (FW) on the yield of food crops (cereals, vegetables, and fruits). It was found that magnesium ion (Mg²⁺), calcium ion (Ca²⁺), electrical conductivity (EC), total nitrogen (TN), and potential of hydrogen (pH) were the most important factors for RW quality indicators. Based on the results, water managers should establish more conservative RW quality thresholds to promote food crop production, especially for salts and pollutants in RW. Compared to international water quality standards, it could be slightly relaxed the restrictions of TN in RW. The optimal farming practices obtained that irrigation amount of the mixed RW and FW (RW + FW) was from 1000 m³ ha^-1 to 5000 m³ ha^-1, and the cultivation period was no more than three years. Flood irrigation (FI) and drip irrigation (DI) for cereals were also recommended. Finally, a comparison of the determined results from this method with other scenarios published, finding a good agreement.

Estimating predation rates from molecular gut content analysis

Several methods have been published to estimate per capita predation rates from molecular gut content analysis relying on intuitive understanding of predation, but none have been formally derived. We provide a theoretical framework for estimating predation rates to identify an accurate method and lay bare its assumptions. Per capita predation can be estimated by multiplying the prey decay rate and the prey quantity in the predators. This assumes that variation in per capita predation rate is approximately normally distributed, prey decay occurs exponentially, and predation is in steady state. We described several ways to estimate steady state predation, including using only qualitative presence-absence data to estimate the decay rate and in addition, we provided a method for estimating per capita predation rate when predation is not in steady state. We used previously published data on aphid consumption by a ladybird beetle in a feeding trial to calculate the predation rate and compare published methods with this theoretically derived method. The estimated predation rate (3.29 ± 0.27 aphids/h) using our derived method was not significantly different from the actual predation rate, 3.11 aphids/h. In contrast, previously published methods were less accurate, underestimating the predation rate (0.33 ± 0.02 to 1.66 ± 0.8 aphids/h) or overestimating it (3.64 ± 0.30 aphids/h). In summary, we provide methods to estimate predation rates even when variation in predation rates is not exactly normally distributed and not in steady state and demonstrate that the prey decay rate, and not the prey detection period, is required.

Functional thresholds alter the relationship of plant resistance and recovery to drought

The ecological consequences of future droughts are difficult to predict due to a limited understanding of the nonlinear responses of plants to increasing drought intensity, which can change abruptly when critical thresholds of drought intensity are crossed. Drought responses are composed of resistance and postdrought recovery. Although it is well established that higher drought intensity increases the impact and, thus, reduces plant resistance, less is known about how drought intensity affects recovery and how resistance and recovery are related. In this study, we tested the hypothesis that resistance, recovery, and their relationship change abruptly upon crossing critical thresholds of drought intensity. We exposed mesocosms of two monospecific stands of the common grassland species Dactylis glomerata and Plantago lanceolata to a large gradient of drought intensity and quantified the resistance and recovery of multiple measures of plant productivity, including gross-primary productivity, vegetative height, Normalized Difference Vegetation Index, and aboveground biomass production. Drought intensity had nonlinear and contrasting effects on plant productivity during drought and recovery, which differed between the two species. Increasing drought intensity decreased the resistance of plant productivity and caused rapid compensatory growth during postdrought recovery, the degree of which was highly dependent on drought intensity. Across multiple response parameters two thresholds of drought intensity emerged, upon which we observed abrupt changes in plant resistance and recovery, as well as their relationship. We conclude that across gradients of drought intensity resistance and recovery are tightly coupled and that both the magnitude and the direction of drought effects on resistance and recovery can change abruptly upon specific thresholds of stress intensity. These findings highlight the urgent need to account for nonlinear responses of resistance and recovery to drought intensity as critical drivers of productivity in a changing climate.

Ecological thresholds of toxic plants for sheep production and ecosystem multifunctionality and their trade-off in an alpine meadow

Toxic plants are a natural component of alpine meadow which co-evolved with Tibetan sheep for thousands of years. One challenge for indigenous herders is to know the ecological thresholds of toxic plants and maintain their vital functions in ways that are compatible with economic income and ecological conservation. To achieve this, field trials with Tibetan sheep grazing in alpine meadow were conducted to examine the ecological thresholds of toxic plants for sheep production and ecosystem functions and their trade-offs. Our results demonstrated that the changing point values of biomass proportion of toxic plants for dry matter intake and liveweight gain of sheep were 17% and 22%, respectively. The changing point value of biomass (richness) proportion of toxic plants for soil carbon accumulation index was 31% (59%), for soil nutrient cycling index was 38% (42%), and for ecosystem multifunctionality index was 28% (50%). The trade-off between liveweight gain of sheep and ecosystem multifunctionality first decreased and then increased along the gradient of biomass proportion of toxic plants (the value of changing point was 37%), and had a significant negative correlation with richness of toxic plants. In addition, structural equation modeling indicated that toxic plants can affect the trade-off between liveweight gain of sheep and ecosystem multifunctionality though increasing acid detergent fiber of plant and decreasing plant species richness, belowground biomass and soil total phosphorus. Consequently, opinions towards toxic plants should shift from the conventional view that they are serious threat to grassland ecosystem health to an inclusive understanding that they are beneficial to livestock and ecosystem functions under certain ecological thresholds.

Non-linear effects of natural and anthropogenic drivers on ecosystem services: Integrating thresholds into conservation planning

Ecosystem services (ESs) have been widely used for ecological protection and land spatial planning. Natural and anthropogenic drivers exhibit a strong dynamic coupling relationship with ESs. However, current ESs-related research focused on mapping the ESs spatially or investing the trade-offs and synergies relationship between ES, ignoring the nonlinear response of ESs to natural and anthropogenic drivers. Here we aimed to investigate the nonlinear effect of 14 potential drivers (8 natural and 6 anthropogenic) on the total value of six typical ESs (ESV). Taking Beijing-Tianjin-Hebei urban agglomeration (BTH) in China as an example, we established 14 constrain lines and identified critical thresholds through the restricted cubic splines (RCS) regression. We found strong non-linear impacts of natural and anthropogenic drivers on ESV and critical thresholds existed among all the 14 constrain lines. The RCS plots showed that the overall ESV was kept at a high level before or after certain thresholds (e.g., altitude >687 m, slope >13.4°, NDVI >0.7, distance from water <31.2 km, etc.). We categorized these threshold combinations and found the potentially high ES delivery areas were mainly distributed in the Yanshan Mountian, accounting for approximately 5% of the total BTH region. These critical thresholds offer a new method to delineate conservation and restoration priority areas.

Prevalence and drivers of abrupt vegetation shifts in global drylands

The constant provision of plant productivity is integral to supporting the liability of ecosystems and human wellbeing in global drylands. Drylands are paradigmatic examples of systems prone to experiencing abrupt changes in their functioning. Indeed, space-for-time substitution approaches suggest that abrupt changes in plant productivity are widespread, but this evidence is less clear using observational time series or experimental data at a large scale. Studying the prevalence and, most importantly, the unknown drivers of abrupt (rather than gradual) dynamical patterns in drylands may help to unveil hotspots of current and future dynamical instabilities in drylands. Using a 20-y global satellite-derived temporal assessment of dryland Normalized Difference Vegetation Index (NDVI), we show that 50% of all dryland ecosystems exhibiting gains or losses of NDVI are characterized by abrupt positive/negative temporal dynamics. We further show that abrupt changes are more common among negative than positive NDVI trends and can be found in global regions suffering recent droughts, particularly around critical aridity thresholds. Positive abrupt dynamics are found most in ecosystems with low seasonal variability or high aridity. Our work unveils the high importance of climate variability on triggering abrupt shifts in vegetation and it provides missing evidence of increasing abruptness in systems intensively managed by humans, with low soil organic carbon contents, or around specific aridity thresholds. These results highlight that abrupt changes in dryland dynamics are very common, especially for productivity losses, pinpoint global hotspots of dryland vulnerability, and identify drivers that could be targeted for effective dryland management.

Vapour pressure deficit determines critical thresholds for global coffee production under climate change

Our understanding of the impact of climate change on global coffee production is largely based on studies focusing on temperature and precipitation, but other climate indicators could trigger critical threshold changes in productivity. Here, using generalized additive models and threshold regression, we investigate temperature, precipitation, soil moisture and vapour pressure deficit (VPD) effects on global Arabica coffee productivity. We show that VPD during fruit development is a key indicator of global coffee productivity, with yield declining rapidly above 0.82 kPa. The risk of exceeding this threshold rises sharply for most countries we assess, if global warming exceeds 2 °C. At 2.9 °C, countries making up 90% of global supply are more likely than not to exceed the VPD threshold. The inclusion of VPD and the identification of thresholds appear critical for understanding climate change impacts on coffee and for the design of adaptation strategies.

Multi-threshold proportional hazards model and subgroup identification

We propose a novel two-stage procedure for change point detection and parameter estimation in a multi-threshold proportional hazards model. In the first stage, we estimate the number of thresholds by formulating the threshold detection problem as a variable selection problem and applying the penalized partial likelihood approach. In the second stage, the change point locations are refined by a grid search and the standard inference for segment regression can then follow. The proposed model and estimation procedure could lend support to subgroup identification and personalized treatment recommendation in medical research. We establish the consistency of the threshold estimators and regression coefficient estimators under technical conditions. The finite sample performance of the method is demonstrated via simulation studies and two cancer data examples.

Effects of urbanization on woody plant phylogenetic diversity and its associations with landscape features in the high latitude northern hemisphere region, Northeast China

Urbanization is one of the primary drivers of terrestrial modification, with marked biological homogenization worldwide but relatively poor knowledge of woody phylogenetic diversity. Here, we investigated 943 plots, about 93,000 woody plants from 130 species in Northeast China, and calculated six phylogenetic diversity indexes, and urbanization landscape metrics; the responses of phylogenetic diversity to urbanization and its coupling relationship with landscape features were explored at 25 km × 25 km, 50 km × 50 km and 75 km × 75 km grid scales. We found that urbanization had enhanced the evolutionary distinctiveness of woody plants, characterizing as increasing Faith phylogenetic diversity (FPD) and their mean pairwise distance (MPD) while decreasing the mean nearest taxon distance (MNTD); these trends were independent of landscape scales and gymnosperm inclusion or not. As indicated by increasing SesMPD (Standardized MPD), the dominant role of community assemblage changed from environmental filtering in low urbanization intensity (UI) to competitive exclusion in high UI regions. Artificial surface area (ASA) and its percentage, SHAPE_F (Shape index of forest), and PD_F (Patch density of forest) had a threshold effect on phylogenetic diversity. ASA%, GDP (gross domestic product), and population density were the most potent predictors for the variations of phylogenetic diversity, and GDP contributed the most (42.9%). A higher GDP accompanied a higher FPD, SesPD (Standardized FPD), and SesMNTD (Standardized MNTD); higher PD_F and lower SHAPE_F were associated with higher MNTD, MPD, and SesMPD. In conclusion, urbanization strongly modifies woody plant phylogenetic diversity. Identifying the threshold effects and significant factors for phylogenetic variations allows biodiversity assessment and conservation through proper landscape configuration under the urbanization context.

EUS-guided hepaticogastrostomy in the management of malignant biliary obstruction: Experience and learning curve in a tertiary referral center

BACKGROUND

EUS-guided hepaticogastrostomy (EUS-HGS) is a recognized second-line strategy for biliary drainage when endoscopic retrograde cholangiopancreatography fails or is impossible. Substantial technical and procedural progress in performing EUS-HGS has been achieved. The present study wanted to analyze whether growing experience in current practice has changed patient outcomes over time.

METHODS

We retrospectively analyzed data from patients with malignant biliary obstruction treated by EUS-HGS between 2002 and 2018 at a tertiary referral center.

RESULTS

A total of 205 patients were included (104 male; mean age 68 years). Clinical success was achieved in 93% of patients with available 30-days follow-up (153), and the rate of procedure-related morbidity and mortality after one month was 18% and 5%, respectively. The cumulative sum (CUSUM) learning curve suggests a slight improvement in the rate of early complications during the second learning phase (23% vs 32%; P = 0.14; including death for any cause and intensive care). However, a significant threshold of early complications could not be determined. Recurrent biliary stent occlusion is the main cause for endoscopic reintervention (47/130; 37%).

CONCLUSION

The rate of procedure-related complications after EUS-HGS has improved over time. However, the overall morbidity rate remains high, emphasizing the importance of dedicated expertise, appropriate patient selection and multidisciplinary discussion.

Change-point analysis of lambda-cyhalothrin efficacy against soybean aphid (Aphis glycines Matsumura): identifying practical resistance from field efficacy trials

BACKGROUND

Soybean aphid (Aphis glycines Matsumura) remains the most economically important arthropod pest of soybean in the Upper Midwest Region of the USA. Soybean aphid resistance to the pyrethroid insecticides emerged in 2015; however, the reduction in the efficacy of field applications of pyrethroid insecticides has not been quantified. Based on time-series data from insecticide efficacy trials at two locations, a novel approach of continuous two-phase change point-regression models was used to indicate whether a change in percent control had occurred, and to provide an indication of when and to what degree the percent control had changed.

RESULTS

At both locations examined in this study, a significant change point for percent control of λ-cyhalothrin was detected in 2014, thus marking the onset of practical resistance in the soybean aphid. Percent control decreased at a rate of 4.30% and 19.90% per year at these locations. By contrast, percent control for chlorpyrifos remained high over time with no significant change point.

CONCLUSION

This research demonstrates that retrospective time-series analysis of insecticide efficacy data can identify the onset and magnitude of practical resistance in the field. This further validates and compliments the other lines of evidence related to pyrethroid resistance in soybean aphid. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Wildfire plumes in the Western US are reaching greater heights and injecting more aerosols aloft as wildfire activity intensifies

By producing a first-of-its-kind, decadal-scale wildfire plume rise climatology in the Western U.S. and Canada, we identify trends toward enhanced plume top heights, aerosol loading aloft, and near-surface smoke injection throughout the American West. Positive and significant plume trends suggest a growing impact of Western US wildfires on air quality at the local to continental scales and support the notion that wildfires may have an increasing impact on regional climate. Overlap of identified trends with regions of increasing wildfire emissions and burn severity suggests a link to climate driven trends toward enhanced wildfire activity. Further, time series of plume activity point to a possible acceleration of trends over recent years, such that the future impacts to air quality and regional climate may exceed those suggested by a linear fit to the multi-decadal data. These findings have significant implications for human health and exacerbate concern for the climate–wildfire connection.

Phytoplankton bloom stages estimated from chlorophyll pigment proportions suggest delayed summer production in low sea ice years in the northern Bering Sea

Decreased sea ice cover in the northern Bering Sea has altered annual phytoplankton phenology owing to an expansion of open water duration and its impact on ocean stratification. Limitations of satellite remote sensing such as the inability to detect bloom activity throughout the water column, under ice, and in cloudy conditions dictate the need for shipboard based measurements to provide more information on bloom dynamics. In this study, we adapted remote sensing land cover classification techniques to provide a new means to determine bloom stage from shipboard samples. Specifically, we used multiyear satellite time series of chlorophyll a to determine whether in-situ blooms were actively growing or mature (i.e., past-peak) at the time of field sampling. Field observations of chlorophyll a and pheophytin (degraded and oxidized chlorophyll products) were used to calculate pheophytin proportions, i.e., (Pheophytin/(Chlorophyll a + Pheophytin)) and empirically determine whether the bloom was growing or mature based on remotely sensed bloom stages. Data collected at 13 north Bering Sea stations each July from 2013–2019 supported a pheophytin proportion of 28% as the best empirical threshold to distinguish a growing vs. mature bloom stage. One outcome was that low vs. high sea ice years resulted in significantly different pheophytin proportions in July; in years with low winter-to-spring ice, more blooms with growing status were observed, compared to later stage, more mature blooms following springs with abundant seasonal sea ice. The detection of growing blooms in July following low ice years suggests that changes in the timing of the spring bloom triggers cascading effects on mid-summer production.

Natural selenium stress influences the changes of antibiotic resistome in seleniferous forest soils

BACKGROUND

Metal(loid)s can promote the spread and enrichment of antibiotic resistance genes (ARGs) in the environment through a co-selection effect. However, it remains unclear whether exposure of microorganisms to varying concentrations of selenium (Se), an essential but potentially deleterious metal(loid) to living organisms, can influence the migration and distribution of ARGs in forest soils.

RESULTS

Precisely 235 ARGs conferring resistance to seven classes of antibiotics were detected along a Se gradient (0.06-20.65 mg kg^-1) across 24 forest soils. (flor)/(chlor)/(am)phenicol resistance genes were the most abundant in all samples. The total abundance of ARGs first increased and then decreased with an elevated available Se content threshold of 0.034 mg kg^-1 (P = 2E-05). A structural equation model revealed that the dominant mechanism through which Se indirectly influences the vertical migration of ARGs is by regulating the abundance of the bacterial community. In addition, the methylation of Se (mediated by tehB) and the repairing of DNA damages (mediated by ruvB and recG) were the dominant mechanisms involved in Se resistance in the forest soils. The co-occurrence network analysis revealed a significant correlated cluster between Se-resistance genes, MGEs and ARGs, suggesting the co-transfer potential. Lelliottia amnigena YTB01 isolated from the soil was able to tolerate 50 μg mL^-1 ampicillin and 1000 mg kg^-1 sodium selenite, and harbored both Se resistant genes and ARGs in the genome.

CONCLUSIONS

Our study demonstrated that the spread and enrichment of ARGs are enhanced under moderate Se pressure but inhibited under severe Se pressure in the forest soil (threshold at 0.034 mg kg^-1 available Se content). The data generated in this pilot study points to the potential health risk associated with Se contamination and its associated influence on ARGs distribution in soil.

Species richness response to human pressure hides important assemblage transformations

SignificanceHuman activities are causing biodiversity loss, but there is still strong debate on their effect on species richness. Here, I propose a unification of five trajectories of species richness response to increasing human pressure under the "replace then remove framework." It consists in a first phase of assemblage transformation (with the replacement of "loser" by "winner" species), often followed by a second phase of steep decline in species richness (with the decline of many winner species) when human pressure exceeds a certain threshold. The empirical results presented in this study provide an outstanding illustration of assemblage transformations that may cause biotic homogenization, demonstrating how habitat specialist, endemic, sensitive, and threatened species are replaced by others with increasing human pressure.

Detecting Proximal Caries on Periapical Radiographs Using Convolutional Neural Networks with Different Training Strategies on Small Datasets

The present study aimed to evaluate the performance of convolutional neural networks (CNNs) that were trained with small datasets using different strategies in the detection of proximal caries at different levels of severity on periapical radiographs. Small datasets containing 800 periapical radiographs were randomly categorized into a training and validation dataset (n = 600) and a test dataset (n = 200). A pretrained Cifar-10Net CNN was used in the present study. Different training strategies were used to train the CNN model independently; these strategies were defined as image recognition (IR), edge extraction (EE), and image segmentation (IS). Different metrics, such as sensitivity and area under the receiver operating characteristic curve (AUC), for the trained CNN and human observers were analysed to evaluate the performance in detecting proximal caries. IR, EE, and IS recognition modes and human eyes achieved AUCs of 0.805, 0.860, 0.549, and 0.767, respectively, with the EE recognition mode having the highest values (p all < 0.05). The EE recognition mode was significantly more sensitive in detecting both enamel and dentin caries than human eyes (p all < 0.05). The CNN trained with the EE strategy, the best performer in the present study, showed potential utility in detecting proximal caries on periapical radiographs when using small datasets.

Metabolism is a major driver of hydrogen isotope fractionation recorded in tree-ring glucose of Pinus nigra

Stable isotope abundances convey valuable information about plant physiological processes and underlying environmental controls. Central gaps in our mechanistic understanding of hydrogen isotope abundances impede their widespread application within the plant and biogeosciences. To address these gaps, we analysed intramolecular deuterium abundances in glucose of Pinus nigra extracted from an annually resolved tree-ring series (1961-1995). We found fractionation signals (i.e. temporal variability in deuterium abundance) at glucose H¹ and H² introduced by closely related metabolic processes. Regression analysis indicates that these signals (and thus metabolism) respond to drought and atmospheric CO₂ concentration beyond a response change point. They explain ≈ 60% of the whole-molecule deuterium variability. Altered metabolism is associated with below-average yet not exceptionally low growth. We propose the signals are introduced at the leaf level by changes in sucrose-to-starch carbon partitioning and anaplerotic carbon flux into the Calvin-Benson cycle. In conclusion, metabolism can be the main driver of hydrogen isotope variation in plant glucose.

Mortality Related to Air Temperature in European Cities, Based on Threshold Regression Models

There is a wealth of scientific literature that scrutinizes the relationship between mortality and temperature. The aim of this paper is to identify the nexus between temperature and three different causes of mortality (i.e., cardiological, respiratory, and cardiorespiratory) for three countries (Scotland, Spain, and Greece) and eleven cities (i.e., Glasgow, Edinburgh, Aberdeen, Dundee, Madrid, Barcelona, Valencia, Seville, Zaragoza, Attica, and Thessaloniki), emphasizing the differences among these cities and comparing them to gain a deeper understanding of the relationship. To quantify the association between temperature and mortality, temperature thresholds are defined for each city using a robust statistical analysis, namely threshold regression analysis. In a more detailed perspective, the threshold used is called Minimum Mortality Temperature (MMT), the temperature above or below which mortality is at minimum risk. Afterward, these thresholds are compared based on the geographical coordinates of each city. Our findings show that concerning all-causes of mortality under examination, the cities with higher latitude have lower temperature thresholds compared to the cities with lower latitude. The inclusion of the relationship between mortality and temperature in the array of upcoming climate change implications is critical since future climatic scenarios show an overall increase in the ambient temperature.

Sea ice extent and phenology influence breeding of high-Arctic seabirds: 4 decades of monitoring in Nunavut, Canada

Seabirds breeding in the high Arctic contend with variable annual sea ice conditions, with important consequences depending on a species' unique reproductive and foraging ecology. We assessed the influence of sea ice extent and phenology on seabird breeding biology using monitoring data collected for northern fulmar (Fulmarus glacialis), glaucous gull (Larus hyperboreus), black-legged kittiwake (Rissa tridactyla), and thick-billed murre (Uria lomvia) breeding at Prince Leopold Island, Nunavut, Canada over 4 decades. We expected that years of later sea ice break-up and greater ice cover around the colony would create greater challenges to foraging and could result in delayed nest initiation, decreased colony attendance, and lower nesting success, but with distinct responses from each species. We also tested for time-lagged effects of ice conditions, where sea ice in a given year could impact food availability or juvenile recruitment in later years. Ice conditions around the colony exhibited no significant overall temporal trends or changepoints over the past 50 years (1970-2021), while counts of kittiwakes and murres increased over the study period 1975-2013. No trends were evident in counts of fulmars or gulls or in egg-laying dates or nest success for any species. However, three species (all but glaucous gulls) exhibited unique responses between breeding metrics and sea ice, highlighting how breeding decisions and outcomes may differ among species under the same environmental conditions in a given year. Time-lagged effects were only detected for kittiwake nest counts, where the date of spring ice break-up around the colony was negatively associated with counts at a 5-year lag. Greater distances to open water were associated with lower colony attendance by fulmars and later nest initiation by kittiwakes and murres. Our analyses provide additional insights to effects of sea ice on high-Arctic seabird breeding ecology, which will be useful in predicting and planning for the complex effects of a changing climate and changing human pressures on this high-latitude ecosystem and for the management of high-Arctic marine-protected areas.

OUP accepted manuscript

Background

Methods

Results

Conclusions

Complex axial growth patterns in an early Cambrian trilobite from South Australia

The exceptional fossil record of trilobites provides our best window on developmental processes in early euarthropods, but data on growth dynamics are limited. Here, we analyse post-embryonic axial growth in the Cambrian trilobite Estaingia bilobata from the Emu Bay Shale, South Australia. Using threshold models, we show that abrupt changes in growth trajectories of different body sections occurred in two phases, closely associated with the anamorphic/epimorphic and meraspid/holaspid transitions. These changes are similar to the progression to sexual maturity seen in certain extant euarthropods and suggest that the onset of maturity coincided with the commencement of the holaspid period. We also conduct hypothesis testing to reveal the likely controls of observed axial growth gradients and suggest that size may better explain growth patterns than moult stage. The two phases of allometric change in E. bilobata, as well as probable differing growth regulation in the earliest post-embryonic stages, suggest that observed body segmentation patterns in this trilobite were the result of a complex series of changing growth controls that characterized different ontogenetic intervals. This indicates that trilobite development is more complex than previously thought, even in early members of the clade.

Threshold for Relationship between Vitamin D and Parathyroid Hormone in Chinese Women of Childbearing Age

Background: The aim of this study was to assess the relationship between serum 25-hydroxyvitamin D [25(OH)D] and serum intact parathyroid hormone (PTH) in Chinese childbearing women, and to estimate the optimum threshold of 25(OH)D that maximally inhibits the PTH, which is considered to be the optimal status for vitamin D sufficiency. Methods: Serum samples were selected from the biological samples' bank of the Chinese Chronic Diseases and Nutrition Survey (CCDNS) 2015. The serum 25(OH)D concentration was determined by liquid chromatography tandem mass spectrometry and the serum PTH was determined by electronic chemiluminescence. Simple linear and partial correlation analysis, locally weighted regression smooth scatterplot (LOESS), nonlinear least squares estimation (NLS), and segmented regression (SR) were utilized to estimate the relationship of 25(OH)D and PTH, and to determine the threshold of 25(OH)D. Results: A total of 1568 serum samples of 25(OH)D concentration and PTH concentration were analyzed. A significant inverse relationship between 25(OH)D and PTH concentration was observed below 15.25 (14.22-16.28) ng/mL, and PTH decreased slowly with the increase of 25(OH)D above 16.75 (15.43-18.06) ng/mL after adjusting by age, latitude, city type, season, corrected calcium, and phosphorus. A very short plateau of PTH was found at 15.25 ng/mL and 16.75 ng/mL in terms of 25(OH)D according to LOESS, NLS, and SR. Conclusions: The serum 25(OH)D was negatively correlated with the serum PTH. The threshold of VitD sufficiency was found in the range of 14.22-18.06 ng/mL in terms of serum 25(OH)D concentration for Chinese childbearing women aged 18-44 years old.

Clinical and biomarker modifiers of vitamin D treatment response: the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Different 25-hydroxyvitamin D [25(OH)D] thresholds for treatment with vitamin D supplementation have been suggested and are derived almost exclusively from observational studies. Whether other characteristics, including race/ethnicity, BMI, and estimated glomerular filtration rate (eGFR), should also influence the threshold for treatment is unknown.

OBJECTIVES

The aim was to identify clinical and biomarker characteristics that modify the response to vitamin D supplementation.

METHODS

A total of 666 older adults in the Multi-Ethnic Study of Atherosclerosis (MESA) were randomly assigned to 16 wk of oral vitamin D3 (2000 IU/d; n = 499) or placebo (n = 167). Primary outcomes were changes in serum parathyroid hormone (PTH) and 1,25-dihydroxyvitamin D [1,25(OH)2D] concentrations from baseline to 16 wk.

RESULTS

Among 666 participants randomly assigned (mean age: 72 y; 53% female; 66% racial/ethnic minority), 611 (92%) completed the study. The mean (SD) change in PTH was -3 (16) pg/mL with vitamin D3 compared with 2 (18) pg/mL with placebo (estimated mean difference: -5; 95% CI: -8, -2 pg/mL). Within the vitamin D3 group, lower baseline 25-hydroxyvitamin D [25(OH)D] was associated with a larger decline in PTH in a nonlinear fashion. With baseline 25(OH)D ≥30 ng/mL as the reference, 25(OH)D <20 ng/mL was associated with a larger decline in PTH with vitamin D3 supplementation (-10; 95% CI: -15, -6 pg/mL), whereas 25(OH)D of 20-30 ng/mL was not (-2; 95% CI: -6, 1 pg/mL). A segmented threshold model identified a baseline 25(OH)D concentration of 21 (95% CI: 13, 31) ng/mL as an inflection point for difference in change in PTH. Race/ethnicity, BMI, and eGFR did not modify vitamin D treatment response. There was no significant change in 1,25(OH)2D in either treatment group.

CONCLUSIONS

Of characteristics most commonly associated with vitamin D metabolism, only baseline 25(OH)D <20 ng/mL modified the PTH response to vitamin D supplementation, providing support from a clinical trial to use this threshold to define insufficiency. This trial was registered at clinicaltrials.gov as NCT02925195.

Does COVID-19 pandemic disrupt sustainable supply chain process? Covering some new global facts

The adverse effects of the coronavirus 2019 (COVID-19) pandemic are widely visible in the economic structure, while the principal causal factor is the disruption of the supply chain process that leads to the economies into a global depression. The purpose of the study is to identify the critical factors that affect the global sustainable supply chain process in the cross-sectional panel of 38 European countries, 14 North American countries, 40 Asian countries, and a heterogeneous panel of 111 countries. The results show that an increase in susceptible coronavirus cases and death tolls limits the supply chain process because of nationwide closures of industries and business activities. In contrast, an increase in the number of recovered cases supports economic activities and improved logistic performance index across countries. The innovation accounting matrix shows that since August 2020, the global coronavirus cases will decline and start resuming economic activities to increase the supply chain process. The result is further supported by the estimates of reduction in the proportion of death to recovered cases (case fatality ratio 1) to increase sustainable logistics activities. However, the supply chain process could affect an increasing death toll and case fatality ratio 2 (i.e., the proportion of death to registered cases) over time. The global economies should ensure a free flow of sustainable logistics supply, especially the supply of healthcare medical equipment that would help control the coronavirus pandemic, which escapes from the nations from a global depression.

Defence by duplication: The relation between phenotypic glyphosate resistance and EPSPS gene copy number variation in Amaranthus palmeri

Gene copy number variation (CNV) has been increasingly associated with organismal responses to environmental stress, but we know little about the quantitative relation between CNV and phenotypic variation. In this study we quantify the relation between variation in EPSPS (5-enolpyruvylshikimate-3-phosphate synthase) copy number using digital drop PCR and variation in phenotypic glyphosate resistance in 22 populations of Amaranthus palmeri (Palmer Amaranth), a range-expanding agricultural weed. Overall, we detected a significant positive relation between population mean copy number and resistance. The majority of populations exhibited high glyphosate resistance yet maintained low-resistance individuals, resulting in bimodality in many populations. We also investigated threshold models for the relation between copy number and resistance, and found evidence for a threshold of ~15 EPSPS copies: there was a steep increase in resistance below the threshold, followed by a much shallower increase. Across 924 individuals, as copy number increased the range of variation in resistance decreased, yielding an increasing frequency of high phenotypic resistance individuals. Among populations we detected a decline in variation (s.d.) as mean phenotypic resistance increased from moderate to high, consistent with the prediction that as phenotypic resistance increases in populations, stabilizing selection decreases variation in the trait. Our study demonstrates that populations of A. palmeri can harbour wide variation in EPSPS copy number and phenotypic glyphosate resistance, reflecting the history of, and template for future, resistance evolution.

Wall stress analyses in patients with ≥5 cm versus <5 cm ascending thoracic aortic aneurysm

OBJECTIVE

Current guidelines for elective surgery of ascending thoracic aortic aneurysms (aTAAs) use aneurysm size as primary determinant for risk stratification of adverse events. Biomechanically, dissection may occur when wall stress exceeds wall strength. Determining patient-specific aTAA wall stresses by finite element analysis can potentially predict patient-specific risk of dissection. This study compared peak wall stresses in patients with ≥5.0 cm versus <5.0 cm aTAAs to determine correlation between diameter and wall stress.

METHODS

Patients with aTAA ≥5.0 cm (n = 47) and <5.0 cm (n = 53) were studied. Patient-specific aneurysm geometries obtained from echocardiogram-gated computed tomography were meshed and prestress geometries determined. Peak wall stresses and stress distributions were determined using LS-DYNA finite element analysis software (LSTC Inc, Livermore, Calif), with user-defined fiber-embedded material models under systolic pressure.

RESULTS

Peak circumferential stresses at systolic pressure were 530 ± 83 kPa for aTAA ≥5.0 cm versus 486 ± 87 kPa for aTAA <5.0 cm (P = .07), whereas peak longitudinal stresses were 331 ± 57 kPa versus 310 ± 54 kPa (P = .08), respectively. For aTAA ≥5.0 cm, correlation between peak circumferential stresses and size was 0.41, whereas correlation between peak longitudinal wall stresses and size was 0.33. However, for aTAA <5.0 cm, correlation between peak circumferential stresses and size was 0.23, whereas correlation between peak longitudinal stresses and size was 0.14.

CONCLUSIONS

Peak patient-specific aTAA wall stresses overall were larger for ≥5.0 cm than aTAA <5.0 cm. Although some correlation between size and peak wall stresses was found in aTAA ≥5.0 cm, poor correlation existed between size and peak wall stresses in aTAA <5.0 cm. Patient-specific wall stresses are particularly important in determining patient-specific risk of dissection for aTAA <5.0 cm.

The infant gut resistome is associated with E. coli and early-life exposures

BACKGROUND

The human gut microbiome harbors a collection of bacterial antimicrobial resistance genes (ARGs) known as the resistome. The factors associated with establishment of the resistome in early life are not well understood. We investigated the early-life exposures and taxonomic signatures associated with resistome development over the first year of life in a large, prospective cohort in the United States. Shotgun metagenomic sequencing was used to profile both microbial composition and ARGs in stool samples collected at 6 weeks and 1 year of age from infants enrolled in the New Hampshire Birth Cohort Study. Negative binomial regression and statistical modeling were used to examine infant factors such as sex, delivery mode, feeding method, gestational age, antibiotic exposure, and infant gut microbiome composition in relation to the diversity and relative abundance of ARGs.

RESULTS

Metagenomic sequencing was performed on paired samples from 195 full term (at least 37 weeks' gestation) and 15 late preterm (33-36 weeks' gestation) infants. 6-week samples compared to 1-year samples had 4.37 times (95% CI: 3.54-5.39) the rate of harboring ARGs. The majority of ARGs that were at a greater relative abundance at 6 weeks (chi-squared p < 0.01) worked through the mechanism of antibiotic efflux. The overall relative abundance of the resistome was strongly correlated with Proteobacteria (Spearman correlation = 78.9%) and specifically Escherichia coli (62.2%) relative abundance in the gut microbiome. Among infant characteristics, delivery mode was most strongly associated with the diversity and relative abundance of ARGs. Infants born via cesarean delivery had a trend towards a higher risk of harboring unique ARGs [relative risk = 1.12 (95% CI: 0.97-1.29)] as well as having an increased risk for overall ARG relative abundance [relative risk = 1.43 (95% CI: 1.12-1.84)] at 1 year compared to infants born vaginally.

CONCLUSIONS

Our findings suggest that the developing infant gut resistome may be alterable by early-life exposures. Establishing the extent to which infant characteristics and early-life exposures impact the resistome can ultimately lead to interventions that decrease the transmission of ARGs and thus the risk of antibiotic resistant infections.

Nested logistic regression models and ΔAUC applications: Change-point analysis

The area under the receiver operating characteristic curve (AUC) is one of the most popular measures for evaluating the performance of a predictive model. In nested models, the change in AUC (ΔAUC) can be a discriminatory measure of whether the newly added predictors provide significant improvement in terms of predictive accuracy. Recently, several authors have shown rigorously that ΔAUC can be degenerate and its asymptotic distribution is no longer normal when the reduced model is true, but it could be the distribution of a linear combination of some χ12 random variables [1,2]. Hence, the normality assumption and existing variance estimate cannot be applied directly for developing a statistical test under the nested models. In this paper, we first provide a brief review on the use of ΔAUC for comparing nested logistic models and the difficulty of retrieving the reference distribution behind. Then, we present a special case of the nested logistic regression models that the newly added predictor to the reduced model contains a change-point in its effects. A new test statistic based on ΔAUC is proposed in this setting. A simple resampling scheme is proposed to approximate the critical values for the test statistic. The inference of the change-point parameter is done via m-out-of-n bootstrap. Large-scale simulation is conducted to evaluate the finite-sample performance of the ΔAUC test for the change-point model. The proposed method is applied to two real-life datasets for illustration.

Inference on treatment effect modification by biomarker response in a three-phase sampling design

An objective in randomized clinical trials is the evaluation of "principal surrogates," which consists of analyzing how the treatment effect on a clinical endpoint varies over principal strata subgroups defined by an intermediate response outcome under both or one of the treatment assignments. The latter effect modification estimand has been termed the marginal causal effect predictiveness (mCEP) curve. This objective was addressed in two randomized placebo-controlled Phase 3 dengue vaccine trials for an antibody response biomarker whose sampling design rendered previously developed inferential methods highly inefficient due to a three-phase sampling design. In this design, the biomarker was measured in a case-cohort sample and a key baseline auxiliary strongly associated with the biomarker (the "baseline surrogate measure") was only measured in a further sub-sample. We propose a novel approach to estimation of the mCEP curve in such three-phase sampling designs that avoids the restrictive "placebo structural risk" modeling assumption common to past methods and that further improves robustness by the use of non-parametric kernel smoothing for biomarker density estimation. Additionally, we develop bootstrap-based procedures for pointwise and simultaneous confidence intervals and testing of four relevant hypotheses about the mCEP curve. We investigate the finite-sample properties of the proposed methods and compare them to those of an alternative method making the placebo structural risk assumption. Finally, we apply the novel and alternative procedures to the two dengue vaccine trial data sets.

Change-point analysis through INAR process with application to some COVID-19 data

In this article, we consider the problem of change-point analysis for the count time series data through an integer-valued autoregressive process of order 1 (INAR(1)) with time-varying covariates. These types of features we observe in many real-life scenarios especially in the COVID-19 data sets where the number of active cases over time starts falling and then again increases. In order to capture those features, we use Poisson INAR(1) process with a time-varying smoothing covariate. By using such model, we can model both the components in the active cases at time-point t namely - (i) number of non-recovery cases from the previous time-point, and (ii) number of new cases at time-point t. We study some theoretical properties of the proposed model along with forecasting. Some simulation studies are performed to study the effectiveness of the proposed method. Finally, we analyze two COVID-19 data sets and compare our proposed model to another PINAR(1) process which has time-varying covariate but no change-point, to demonstrate the overall performance of our proposed model.

Fast Grid Search and Bootstrap-based Inference for Continuous Two-phase Polynomial Regression Models

Two-phase polynomial regression models (Robison, 1964; Fuller, 1969; Gallant and Fuller, 1973; Zhan et al., 1996) are widely used in ecology, public health, and other applied fields to model nonlinear relationships. These models are characterized by the presence of threshold parameters, across which the mean functions are allowed to change. That the threshold is a parameter of the model to be estimated from the data is an essential feature of two-phase models. It distinguishes them, and more generally, multi-phase models, from the spline models and has profound implications for both computation and inference for the models. Estimation of two-phase polynomial regression models is a non-convex, non-smooth optimization problem. Grid search provides high quality solutions to the estimation problem, but is very slow when done by brute force. Building upon our previous work on piecewise linear two-phase regression models estimation, we develop fast grid search algorithms for two-phase polynomial regression models and demonstrate their performance. Furthermore, we develop bootstrap-based pointwise and simultaneous confidence bands for mean functions. Monte Carlo studies are conducted to demonstrate the computational and statistical properties of the proposed methods. Three real datasets are used to help illustrate the application of two-phase models, with special attention on model choice.

Trends in survival, neonatal morbidity and neurodevelopmental outcome of very preterm infants in Tainan, Southern Taiwan, 1995-2016

BACKGROUND

Using regression modeling analysis to investigate the breakpoints of the trends in survival-without-major-neonatal-morbidities (MNM) or -without-neurodevelopmental- impairment (NDI) by year and gestational age (GA) in preterm infants.

METHODS

We enrolled 2237 preterm infants (GA < 32 weeks) in Tainan, Taiwan. The trends in survival-without-MNM or -without-NDI by year (1995-2016) and GA (23-31 weeks), and the epochs and GA ranges with distinct changes were examined. Adjusted rate ratios (aRR) (95% confidence interval [CI]) were calculated using the rates in infants born at 23 weeks in 1995 as the reference.

RESULTS

For yearly trend, there were three epochs (1995-2000, 2001-2006, 2007-2016) with distinct changes in the rates of survival-without-MNM (aRR [95% CI] 1.07 [1.02-1.12], 1.04 [1.02-1.07], 1.02 [1.01-1.04]) and -without-NDI (1.03 [1.02-1.07], 1.02 [1.01-1.04], 1.01 [0.98-1.04]). For GA trend, the three GA ranges with different increases in the rates of survival-without-MNM were 23⁺⁰-26⁺⁶ (1.60 [1.31-1.94]), 27⁺⁰-28⁺⁶ (1.24 [1.14-1.34]) and 29⁺⁰-31⁺⁶ weeks (1.17 [1.02-1.34]), while those in the rates of survival-without-NDI were 23⁺⁰-25⁺⁶ (1.14 [1.03-1.25]), 26⁺⁰-28⁺⁶ (1.06 [1.02-1.12]) and 29⁺⁰-31⁺⁶ weeks (1.04 [1.02-1.07]). The trends in survival-without-MNM and -without-NDI increased over years in infants with GA 25-31 but not < 25 weeks.

CONCLUSION

The yearly trends in survival-without-MNM and -without-NDI had steady increases from 1995 to 2016 with distinct changes in three epochs, and the GA trends also increased with different rates per week in three GA ranges. Infants with GA < 25 weeks did not improve on the rates of survival-without-MNM or -without-NDI per year from 1995 to 2016.

Association of gestational weight gain with cesarean section: a prospective birth cohort study in Southwest China

Background

Cesarean section (CS) is a rising public health issue globally, and is particularly serious in China. Numerous studies have suggested that gestational weight gain (GWG) control may be an effective way to reduce the rate of CS. However, rare study has examined the association between GWG and CS among women in Southwest China. We proposed to examine their association based on a prospective birth cohort, and further to explore the optimal GWG range.

Methods

We retrieved data from a prospective birth cohort from Sichuan Provincial Hospital for Women and Children, Southwest China. Unconditional multivariable logistic regression was used to examine the association between GWG and CS by adjusting for potential confounders. In one analysis, we incorporated the GWG as a categorical variable according to the Institute of Medicine (IOM) recommendation, similar to the method used in the majority of previous studies. In the other analysis, we directly incorporated GWG as a continuous variable and natural cubic splines were used to characterize the potential nonlinear exposure-response relationship, aiming to identify the optimal GWG. We further stratified the above analysis by pre-pregnancy BMI and GDM, and then a heterogeneity test based on a multivariate meta-analysis was conducted to examine whether the stratum specific estimations agreed with each other.

Results

A total of 1363 participants were included. By adopting the IOM recommendation, the adjusted OR of CS was 0.63 (0.47, 0.84) for insufficient GWG and 1.42 (1.06, 1.88) for excessive GWG. After stratification by pre-pregnancy BMI, we found a higher risk of CS in associated with excessive GWG in the stratum of underweight compared with the other strata, which implied that pre-pregnancy BMI may be an effect modifier. By applying a flexible spline regression, the optimal GWG levels in terms of reducing the CS rate based on our data were more stringent than those of IOM recommendation, which were 9–12 kg for underweight women, < 19 kg for normal weight women and < 10 kg for overweight/obese women.

Conclusions

These results suggested that a more stringent recommendation should be applied in Southwest China, and that more attention should be given to underweight women.