Insights into drought stress response mechanism of tobacco during seed germination by integrated analysis of transcriptome and metabolome

Drought stress inhibits seed germination, plant growth and development of tobacco, and seriously affects the yield and quality of tobacco leaves. However, the molecular mechanism underlying tobacco drought stress response remains largely unknown. In this study, integrated analysis of transcriptome and metabolome was performed on the germinated seeds of a cultivated variety K326 and its EMS mutagenic mutant M28 with great drought tolerance. The result showed that drought stress inhibited seed germination of the both varieties, while the germination rate of M28 was faster than that of K326 under drought stress. Besides, the levels of phytohormone ABA, GA19, and zeatin were increased by drought stress in M28. Five vital pathways were identified through integrated transcriptomic and metabolomic analysis, including zeatin biosynthesis, aspartate and glutamate synthesis, phenylamine metabolism, glutathione metabolism, and phenylpropanoid synthesis. Furthermore, 20 key metabolites in the above pathways were selected for further analysis of gene modular-trait relationship, and then four highly correlated modules were found. Then analysis of gene expression network was carried out of Top30 hub gene of these four modules, and 9 key candidate genes were identified, including HSP70s, XTH16s, APX, PHI-1, 14-3-3, SCP, PPO. In conclusion, our study uncovered some key drought-responsive pathways and genes of tobacco during seeds germination, providing new insights into the regulatory mechanisms of tobacco drought stress response.

Genetically predicted causal effects of gut microbiota on spinal pain: a two-sample Mendelian randomization analysis

Background

Observational studies have hinted at a correlation between the gut microbiota and spinal pain (SP). However, the impact of the gut microbiota on SP remains inconclusive.

Methods

In this study, we employed a two-sample Mendelian randomization (MR) analysis to explore the causal relationship between the gut microbiota and SP, encompassing neck pain (NP), thoracic spine pain (TSP), low back pain (LBP), and back pain (BP). The compiled gut microbiota data originated from a genome-wide association study (GWAS) conducted by the MiBioGen consortium (n = 18,340). Summary data for NP were sourced from the UK Biobank, TSP from the FinnGen Biobank, and LBP from both the UK Biobank and FinnGen Biobank. Summary data for BP were obtained from the UK Biobank. The primary analytical approach for assessing causal relationships was the Inverse Variance Weighted (IVW) method, supplemented by various sensitivity analyses to ensure result robustness.

Results

The IVW analysis unveiled 37 bacterial genera with a potential causal relationship to SP. After Benjamini-Hochberg corrected test, four bacterial genera emerged with a strong causal relationship to SP. Specifically, Oxalobacter (OR: 1.143, 95% CI 1.061-1.232, P = 0.0004) and Tyzzerella 3 (OR: 1.145, 95% CI 1.059-1.238, P = 0.0007) were identified as risk factors for LBP, while Ruminococcaceae UCG011 (OR: 0.859, 95% CI 0.791-0.932, P = 0.0003) was marked as a protective factor for LBP, and Olsenella (OR: 0.893, 95% CI 0.839-0.951, P = 0.0004) was recognized as a protective factor for low back pain or/and sciatica. No significant heterogeneity or horizontal pleiotropy was observed through alternative testing methods.

Conclusion

This study establishes a causal relationship between the gut microbiota and SP, shedding light on the "gut-spine" axis. These findings offer novel perspectives for understanding the etiology of SP and provide a theoretical foundation for potential interventions targeting the gut microbiota to prevent and treat SP.

[Association between unhealthy lifestyles and diabetic dyslipidemia in occupational population and network analysis]

Objective: To understand the influence of unhealthy lifestyle on diabetic dyslipidemia and the key influencing factors in occupational population and provided scientific evidence for the prevention of diabetic dyslipidemia. Methods: Based on baseline data and follow-up data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during 2021. Diabetic dyslipidemia was defined as diabetes plus one or more forms of dyslipidemia, and unhealthy lifestyle factors included smoking, alcohol consumption, unhealthy dietary patterns, low physical activity, and abnormal BMI. Multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle scores and diabetic dyslipidemia, network analysis was used to find and explore the key lifestyles influencing glycolipid metabolism. Results: A total of 25 631 subjects were included. People with unhealthy lifestyle score 2 and 3 were 1.93 (95%CI: 1.31-2.86) times and 2.37 (95%CI: 1.60-3.50) times more likely to have diabetes with ≥1 forms of dyslipidemia than those with scores of 0; People with unhealthy lifestyle score 1, 2 and 3 were 1.98 (95%CI: 1.08-3.61) times, 2.87 (95%CI: 1.60-5.14) times and 3.95 (95%CI: 2.22-7.06) times more likely to have diabetes with ≥2 forms of dyslipidemia than those with score 0. Network analysis found that abnormal BMI and HDL-C were the "bridge nodes" that link unhealthy lifestyles with diabetic dyslipidemia. Conclusion: The higher the score of unhealthy lifestyle, the higher the risk for diabetic dyslipidemia, abnormal BMI and HDL-C are key factors influencing the association between unhealthy lifestyle and diabetic dyslipidemia.

[Progress in complex network theory-based studies on the associations between health-related behaviors and chronic non-communicable diseases]

In recent years, the research focus on health-related behavior and chronic non-communicable diseases has shifted from the analysis on independent effects of multiple causes on a single outcome to the evaluation the complex relationships between multiple causes and multiple effects. Complex network theory, an important branch of system science, considers the relationships among factors in a network and can reveal how health-related behaviors interact with chronic diseases through a series of complex network models and indicators. This paper summarizes the definition and development of complex network theory and its commonly used models, indicators, and case studies in the field of health-related behavior and chronic disease to promote the application of complex network theory in the field of health and provide reference and tools for future research of the relationship between health-related behavior and chronic disease.

[Mediating effects of body mass index and lipid levels on the association between alcohol consumption and hypertension in occupational population]

Objective: To investigate the association between alcohol consumption and hypertension and SBP, DBP and the mediating effects of body mass index (BMI) and lipid level in occupational population, and provide reference for the intervention and prevention of hypertension. Methods: Based on the data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd., the information about the demographic characteristics, behavior and lifestyle, blood pressure and lipids level of the participants were collected through questionnaire survey, physical examination and blood biochemical test. Logistic/linear regression was used to analyze the association between alcohol consumption and hypertension, SBP and DBP. The individual and joint mediating effects of BMI, HDL-C, LDL-C, TG, and TC were explored through causal mediating analysis. A network analysis was used to explore the correlation between alcohol consumption, BMI and lipid levels, and hypertension. Results: A total of 22 887 participants were included, in whom 1 825 had newly detected hypertension. Logistic regression analysis found that current/former drinkers had a 33% increase of risk for hypertension compared with never-drinkers (OR=1.33, 95%CI:1.19-1.48). Similarly, alcohol consumption could increase SBP (β=1.05, 95%CI:0.69-1.40) and DBP (β=1.10, 95%CI:0.83-1.38). Overall, BMI and lipid levels could mediate the associations between alcohol consumption and hypertension, SBP and DBP by 21.91%, 28.40% and 22.64%, respectively. BMI and TG were the main mediators, and they were also the two nodes with the highest edge weight and bridge strength centrality in the network of alcohol consumption, BMI, lipid levels and hypertension. Conclusions: Alcohol consumption was associated with increased risk for hypertension, and BMI and TG were important mediators and key nodes in the network. It is suggested that paying attention to the alcohol consumption, BMI and TG might help prevent hypertension in occupational population.

[Association between unhealthy lifestyles and hypertension, diabetes and dyslipidemia in old adults in China]

Objective: To analyze the individual and cumulative effects of unhealthy lifestyle on the prevalence of hypertension, diabetes and dyslipidemia in old adults in China, and find out the critical lifestyle in the network. Methods: Based on the baseline data of Yunnan Behavior and Disease Surveillance Cohort in 2021, a total of 16 763 older adults aged ≥60 years were included in our study. The unhealthy lifestyle factors including smoking, drinking, unhealthy eating habit, lower physical activity level, abnormal BMI and abnormal waist circumference. We calculated the unhealthy lifestyle score by using the cumulative exposures of each participant. Multiple logistic regression and mixed graphical models were used to describe the association between unhealthy lifestyle and the prevalence of hypertension, diabetes and dyslipidemia. Results: The prevalence of hypertension, diabetes and dyslipidemia were 57.0%, 11.5% and 37.0%, respectively. Most of the unhealthy lifestyles included in the study were risk factors for hypertension, diabetes and dyslipidemia, and the risks of disease increased with the increase of the unhealthy lifestyle score. The participants with the highest score (score: 6) had significantly higher prevalence of hypertension (OR=3.99, 95%CI: 1.81-8.80), diabetes (OR=4.64, 95%CI: 1.64-13.15) and dyslipidemia (OR=4.26, 95%CI: 2.08-8.73) compared with those with lowest score (score: 0). In the network constructed by mixed graphical model, abnormal waist circumference (bridge strength=0.81) and hypertension (bridge strength=0.55) were vital bridge nodes connecting unhealthy lifestyle and hypertension, diabetes and dyslipidemia. Conclusions: The unhealthy lifestyle score was associated with risks for hypertension, diabetes and dyslipidemia. Abnormal waist circumference was the key factor for chronic diseases in old adults.

[Association between work environment noise perception and cardiovascular diseases, depressive symptoms, and their comorbidity in occupational population]

Objective: To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses. Methods: A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity. Results: A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95%CI: 1.73-2.65) times, 8.80 (95%CI: 7.91-9.78) times, and 17.02 (95%CI: 12.78-22.66) times respectively compared with low-level occupational noise perception. Conclusions: Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.

Small is Beautiful: Compressing Deep Neural Networks for Partial Domain Adaptation

Domain adaptation is a promising way to ease the costly data labeling process in the era of deep learning (DL). A practical situation is partial domain adaptation (PDA), where the label space of the target domain is a subset of that in the source domain. Although existing methods yield appealing performance in PDA tasks, it is highly presumable that computation overhead exists in deep PDA models since the target is only a subtask of the original problem. In this work, PDA and model compression are seamlessly integrated into a unified training process. The cross-domain distribution divergence is reduced by minimizing a soft-weighted maximum mean discrepancy (SWMMD), which is differentiable and functions as regularization during network training. We use gradient statistics to compress the overparameterized model to identify and prune redundant channels based on the corresponding scaling factors in batch normalization (BN) layers. The experimental results demonstrate that our method can achieve comparable classification performance to state-of-the-art methods on various PDA tasks, with a significant reduction in model size and computation overhead.

PFENet++: Boosting Few-Shot Semantic Segmentation With the Noise-Filtered Context-Aware Prior Mask

In this work, we revisit the prior mask guidance proposed in "Prior Guided Feature Enrichment Network for Few-Shot Segmentation". The prior mask serves as an indicator that highlights the region of interests of unseen categories, and it is effective in achieving better performance on different frameworks of recent studies. However, the current method directly takes the maximum element-to-element correspondence between the query and support features to indicate the probability of belonging to the target class, thus the broader contextual information is seldom exploited during the prior mask generation. To address this issue, first, we propose the Context-aware Prior Mask (CAPM) that leverages additional nearby semantic cues for better locating the objects in query images. Second, since the maximum correlation value is vulnerable to noisy features, we take one step further by incorporating a lightweight Noise Suppression Module (NSM) to screen out the unnecessary responses, yielding high-quality masks for providing the prior knowledge. Both two contributions are experimentally shown to have substantial practical merit, and the new model named PFENet++ significantly outperforms the baseline PFENet as well as all other competitors on three challenging benchmarks PASCAL-5 i, COCO-20 i and FSS-1000. The new state-of-the-art performance is achieved without compromising the efficiency, manifesting the potential for being a new strong baseline in few-shot semantic segmentation.

Two-dimensional MXene Nanomaterials: Preparation, Structure Modulation and the Applications in Electrochemical Energy Storage

BACKGROUND

MXenes have attracted intensive attention owing to their unique twodimensional (2D) layered structure, high specific surface area, excellent conductivity, superior surface hydrophilicity, and chemical stability. In recent years, selective etching of the A element layers from MAX phases by fluorine-containing etchants (HF, LiF-HCl, etc) is a common method to prepare multilayered MXene nanomaterials (NMs) with plentiful surface terminations. At present, many studies have been reported on the use of fluorine-free etchants (NaOH, ZnCl2, etc) to etch MAX phases. The properties of MXene NMs are dependent on their structures.

OBJECTIVE

The purpose of this review is to focus on a comprehensive and systematical survey on the preparation, structure modulation, and applications of MXene NMs in electrochemical energy storage devices, including supercapacitors, lithium-ion battery, sodium-ion battery, potassium-ion battery, and aluminum-ion battery.

METHODS

Extensive information related to the preparation and applications of 2D MXene NMs for electrochemical energy storage and their associated patents were collected. This review highlights the recently reported 2D MXene NMs which are used in supercapacitor and various metal ion.

RESULTS

It is found that the preparation methods have great impacts on the layer spacing and surface terminations of MXenes, consequently affecting their performance. Hence, this paper summarizes the research progress of the preparation strategies, layer spacing and surface termination modulation of MXene NMs.

CONCLUSION

The applications of 2D MXene NMs in electrochemical energy storage are outlined. The forward-looking challenges and prospects for the development of MXenes are also proposed.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a_{μ}≡(g_{μ}-2)/2, from the Fermilab Muon g-2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω[over ˜]_{p}^{'}, and of the anomalous precession frequency corrected for beam dynamics effects, ω_{a}. From the ratio ω_{a}/ω[over ˜]_{p}^{'}, together with precisely determined external parameters, we determine a_{μ}=116 592 057(25)×10^{-11} (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a_{μ}(FNAL)=116 592 055(24)×10^{-11} (0.20 ppm). The new experimental world average is a_{μ}(exp)=116 592 059(22)×10^{-11} (0.19 ppm), which represents a factor of 2 improvement in precision.

Does Dual Anti-HER2 Therapy Increase Early Cardiac Toxicity in Comparison with Trastuzumab Alone in Breast Cancer Patients Receiving Adjuvant Radiotherapy? A Multicenter Retrospective Study

PURPOSE/OBJECTIVE(S)

Adjuvant trastuzumab in combination with RT has proved its safety in terms of cardiac events. Dual anti-HER2 therapy with pertuzumab is currently standard adjuvant therapy in N+ and high-risk N0 early breast cancer (BC) patients. Our study aims to find if it increases early cardiac toxicity compared with trastuzumab alone in BC patients receiving adjuvant radiotherapy.

MATERIALS/METHODS

Operable BC patients who received adjuvant radiotherapy (RT) and trastuzumab with or without pertuzumab between January 2017 and September 2020 in 7 Chinese centers were retrospectively reviewed. The cardiac examination included ultrasonography, electrocardiogram (ECG), NT-proBNP, and cTnI before RT and during follow-up. The cardiac event was any new-onset symptomatic heart disease or abnormality in the cardiac examination after RT.

RESULTS

In total, 711 patients with a median age of 52 years were included, of whom 567 (79.7%) patients were treated with trastuzumab-only and 144 (20.3%) patients received dual anti-HER2 therapy. Adjuvant RT was given concurrently in 140/144 (97.2%) of dual anti-HER2 therapy and 562/567 (99.1%) of trastuzumab alone, respectively. With a median follow-up of 11 months, no patients developed symptomatic heart diseases. Among patients with normal baseline, 17 (2.4%), 86 (12.1%), 18 (2.5%) and 14 (7.3%) developed new-onset diastolic dysfunction, left ventricular ejection fraction (LVEF) decline, abnormal ECG, and abnormal NT-proBNP, respectively. No significant difference was found between the trastuzumab-only and dual anti-HER2 cohort in the incidence of all kinds of new-onset cardiac events (all p > 0.1). Multivariate analysis showed that left-sided (vs right-sided) RT significantly increased the risk of ECG abnormality (HR = 2.32, 95% CI 1.62-3.32, p<0.001). Increased age was an independent risk factor for diastolic dysfunction (HR = 1.1, 95% CI 1.02-1.18, p = 0.0098). Dosimetric analysis showed that patients who developed any cardiac events had increased mean heart dose (397.67±251.08 vs 344.87±236.75 cGy, p = 0.032). A significant increase in risk of cardiac events was found in patients with mean heart dose > 450 cGy (HR = 1.55, 95% CI 1.17-2.05, p = 0.0024), V5 > 26% (HR = 1.51, 95% CI 1.09-2.09, p = 0.013), and V30 > 5.5% (HR = 1.49, 95% CI 1.09-2.04, p = 0.0117), respectively. Further analysis was done in the subgroup of patients treated with left-sided RT, internal mammary nodes RT, or anthracyclines, no difference in risk of cardiac events was found between trastuzumab alone and dual anti-HER2 therapy in concurrent with RT (all p > 0.05).

CONCLUSION

Compared with trastuzumab-only, dual anti-HER2 therapy does not increase early cardiac toxicity in combination with adjuvant RT in BC patients. Cardiac radiation exposure remains the primary risk factor associated with early cardiac toxicity.

Quality Assurance of Protocol Compliance in a Multicenter Randomized Trial Investigating the Role of Hypofractionated Comprehensive Reginal Nodal Irradiation in Node-Positive Breast Cancer (HARVEST)

PURPOSE/OBJECTIVE(S)

The HARVEST trial (NCT03829553) is a phase III, multicenter, randomized clinical trial to explore efficacy and safety of hypofractionated irradiation (HFI) involving regional nodal irradiation (RNI, including internal mammary nodes, IMN) in N+ breast cancer patients treated with mastectomy or breast conserving surgery (BCS). Current study aims to analyze the dosimetric quality assurance so as to evaluate the compliance to the trial protocol.

MATERIALS/METHODS

Eligible patients were randomly assigned (1:1) to receive conventional fractionated irradiation (CFI: 50 Gy/25Fx) or HFI (40.05 Gy/15Fx), which is delivered to ipsilateral chest wall or whole breast (CW/WB) with tumor bed boost (HFI: 10.68 Gy/4Fx; CFI: 10 Gy/5Fx) and comprehensive RNI (supra/infraclavicular nodes and IMN in each patient, lower axilla if indicated) by using IMRT technique. The plan quality was evaluated based on dose distribution, dose volume histogram (DVH) and field parameters. The target coverage, including planning target volume of CW/WB (PTV1) and tumor bed (PTV2) and doses of the organs at risk (OARs) were evaluated. The LQ model was used to convert doses of OARs in HFI group using α/β = 3 Gy (EQD23) for comparison.

RESULTS

Between Feb 21, 2019 and Feb 14, 2022, 801 patients were enrolled at 8 centers with 401 and 400 in CFI and HFI group, respectively. There were 182 patients received BCS and 387 patients were with more than three positive lymph nodes. In the CFI group, the D90 and V45 of PTV1 reached the prescribed dose in 70.6% and 96.0% of the patients, respectively. In the HFI group, the D90 and V36 of PTV1 reached the prescribed dose in 87.8% and 95.5% of the patients, respectively. When the tumor bed was irradiated, the D90 of PTV2 reached the prescribed dose in 95.6% in the CFI group and 100% in the HFI group, respectively. The mean D90 of PTV1 and PTV2 were 50.09±0.65 Gy and 60.63±0.91 Gy in CFI group while 40.11±0.56 Gy and 50.79±2.03 Gy in HFI group. For OARs constraints, protocol compliance was all above 95% (heart: 95.3%; ipsilateral lung: 95.5%; contralateral lung: 97.1%; humeral head: 98.2% and spinal cord: 100%) with no significant difference between CFI and HFI groups. For patients with left-sided breast cancer, the Dmean of the heart was 5.10±1.75 Gy vs. 4.59±1.86 Gy (EQD23) in CFI and HFI groups (p = 0.51), respectively. No significant differences in Dmean of the heart (1.45±0.71 Gy vs. 1.33±0.77 Gy (EQD23), p = 0.40) was found either between two groups in right-sided patients. The differences were significant in the Dmean of the ipsilateral lung (13.37±1.99 Gy vs. 11.17±3.50 Gy (EQD23), p<0.01), contralateral lung (0.88±0.73 Gy vs. 0.74±0.61 Gy (EQD23), p<0.01) and the ipsilateral humeral head (15.27±7.62 Gy vs. 13.05±6.19 Gy (EQD23), p<0.01) and the Dmax of spinal cord (21.40±8.82 Gy vs. 19.47±7.99 Gy (EQD23), p = 0.05) between CFI and HFI groups.

CONCLUSION

A high degree of compliance with protocol dose constraints was found for treatment plans in the HARVEST trial and doses to the most of OARs decreased in HFI group.

Integrating single-cell and bulk RNA sequencing to predict prognosis and immunotherapy response in prostate cancer

Prostate cancer (PCa) stands as a prominent contributor to morbidity and mortality among males on a global scale. Cancer-associated fibroblasts (CAFs) are considered to be closely connected to tumour growth, invasion, and metastasis. We explored the role and characteristics of CAFs in PCa through bioinformatics analysis and built a CAFs-based risk model to predict prognostic treatment and treatment response in PCa patients. First, we downloaded the scRNA-seq data for PCa from the GEO. We extracted bulk RNA-seq data for PCa from the TCGA and GEO and adopted "ComBat" to remove batch effects. Then, we created a Seurat object for the scRNA-seq data using the package "Seurat" in R and identified CAF clusters based on the CAF-related genes (CAFRGs). Based on CAFRGs, a prognostic model was constructed by univariate Cox, LASSO, and multivariate Cox analyses. And the model was validated internally and externally by Kaplan-Meier analysis, respectively. We further performed GO and KEGG analyses of DEGs between risk groups. Besides, we investigated differences in somatic mutations between different risk groups. We explored differences in the immune microenvironment landscape and ICG expression levels in the different groups. Finally, we predicted the response to immunotherapy and the sensitivity of antitumour drugs between the different groups. We screened 4 CAF clusters and identified 463 CAFRGs in PCa scRNA-seq. We constructed a model containing 10 prognostic CAFRGs by univariate Cox, LASSO, and multivariate Cox analysis. Somatic mutation analysis revealed that TTN and TP53 were significantly more mutated in the high-risk group. Finally, we screened 31 chemotherapeutic drugs and targeted therapeutic drugs for PCa. In conclusion, we identified four clusters based on CAFs and constructed a new CAFs-based prognostic signature that could predict PCa patient prognosis and response to immunotherapy and might suggest meaningful clinical options for the treatment of PCa.

Quantization via Distillation and Contrastive Learning

Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This process necessitates a delicate balance between model size and performance. In this work, we explore knowledge distillation (KD) as a promising approach for improving quantization performance by transferring knowledge from high-precision networks to low-precision counterparts. We specifically investigate feature-level information loss during distillation and emphasize the importance of feature-level network quantization perception. We propose a novel quantization method that combines feature-level distillation and contrastive learning to extract and preserve more valuable information during the quantization process. Furthermore, we utilize the hyperbolic tangent function to estimate gradients with respect to the rounding function, which smoothens the training procedure. Our extensive experimental results demonstrate that the proposed approach achieves competitive model performance with the quantized network compared to its full-precision counterpart, thus validating its efficacy and potential for real-world applications.

Generalized Parametric Contrastive Learning

In this paper, we propose the Generalized Parametric Contrastive Learning (GPaCo/PaCo) which works well on both imbalanced and balanced data. Based on theoretical analysis, we observe supervised contrastive loss tends to bias on high-frequency classes and thus increases the difficulty of imbalanced learning. We introduce a set of parametric class-wise learnable centers to rebalance from an optimization perspective. Further, we analyze our GPaCo/PaCo loss under a balanced setting. Our analysis demonstrates that GPaCo/PaCo can adaptively enhance the intensity of pushing samples of the same class close as more samples are pulled together with their corresponding centers and benefit hard example learning. Experiments on long-tailed benchmarks manifest the new state-of-the-art for long-tailed recognition. On full ImageNet, models from CNNs to vision transformers trained with GPaCo loss show better generalization performance and stronger robustness compared with MAE models. Moreover, GPaCo can be applied to semantic segmentation task and obvious improvements are observed on 4 most popular benchmarks. Our code is available at https://github.com/dvlab-research/Parametric-Contrastive-Learning.

Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase ~50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.

DSGN++: Exploiting Visual-Spatial Relation for Stereo-Based 3D Detectors

Camera-based 3D object detectors are welcome due to their wider deployment and lower price than LiDAR sensors. We first revisit the prior stereo detector DSGN for its stereo volume construction ways for representing both 3D geometry and semantics. We polish the stereo modeling and propose the advanced version, DSGN++, aiming to enhance effective information flow throughout the 2D-to-3D pipeline in three main aspects. First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features. Second, for grasping differently spaced features, we present a novel stereo volume - Dual-view Stereo Volume (DSV) that integrates front-view and top-view features and reconstructs sub-voxel depth in the camera frustum. Third, as the foreground region becomes less dominant in 3D space, we propose a multi-modal data editing strategy - Stereo-LiDAR Copy-Paste, which ensures cross-modal alignment and improves data efficiency. Without bells and whistles, extensive experiments in various modality setups on the popular KITTI benchmark show that our method consistently outperforms other camera-based 3D detectors for all categories. Code is available at https://github.com/chenyilun95/DSGN2.

Effective Active Learning Method for Spiking Neural Networks

A large quantity of labeled data is required to train high-performance deep spiking neural networks (SNNs), but obtaining labeled data is expensive. Active learning is proposed to reduce the quantity of labeled data required by deep learning models. However, conventional active learning methods in SNNs are not as effective as that in conventional artificial neural networks (ANNs) because of the difference in feature representation and information transmission. To address this issue, we propose an effective active learning method for a deep SNN model in this article. Specifically, a loss prediction module ActiveLossNet is proposed to extract features and select valuable samples for deep SNNs. Then, we derive the corresponding active learning algorithm for deep SNN models. Comprehensive experiments are conducted on CIFAR-10, MNIST, Fashion-MNIST, and SVHN on different SNN frameworks, including seven-layer CIFARNet and 20-layer ResNet-18. The comparison results demonstrate that the proposed active learning algorithm outperforms random selection and conventional ANN active learning methods. In addition, our method converges faster than conventional active learning methods.

Digital imaging and qPCR analysis and comparison of short-term plaque removal effects of tooth brushing

Purpose

Digital image technology and a real-time fluorescent quantitative polymerase chain reaction (RQ-PCR) were used to determine the changes in dental plaque caused by different toothbrushing tools.

Methods

A total of 120 subjects were selected and divided into four groups: a manual toothbrush group, a manual toothbrush combined with an oral irrigator group, an electric toothbrush combined with an oral irrigator group, and an electric toothbrush group. We compared the changes in plaque count, plaque area, and colony colonization of the four groups after different cleaning tools had been used for a period of time.

Results

Dental plaque count and plaque area decreased in all four groups. The decreases in plaque count and Streptococcus mutans in the electric toothbrush combined with an oral irrigator group were significantly higher than those in other groups.

Conclusion

Electric toothbrush combined with an oral irrigator shows a good result for plaque removal effect. Digital image analysis combined with biological methods can be used to evaluate dental plaque.

[Efficacy and safety of various doses of hybutimibe monotherapy or in combination with atorvastatin for primary hypercholesterolemia: a multicenter, randomized, double-blind, double-dummy, parallel-controlled phase Ⅲ clinical trial]

Objective: To evaluate the efficacy and safety of hybutimibe monotherapy or in combination with atorvastatin in the treatment of primary hypercholesterolemia. Methods: This was a multicenter, randomized, double-blind, double-dummy, parallel-controlled phase Ⅲ clinical trial of patients with untreated primary hypercholesterolemia from 41 centers in China between August 2015 and April 2019. Patients were randomly assigned, at a ratio of 1∶1∶1∶1∶1∶1, to the atorvastatin 10 mg group (group A), hybutimibe 20 mg group (group B), hybutimibe 20 mg plus atorvastatin 10 mg group (group C), hybutimibe 10 mg group (group D), hybutimibe 10 mg plus atorvastatin 10 mg group (group E), and placebo group (group F). After a dietary run-in period for at least 4 weeks, all patients were administered orally once a day according to their groups. The treatment period was 12 weeks after the first dose of the study drug, and efficacy and safety were evaluated at weeks 2, 4, 8, and 12. After the treatment period, patients voluntarily entered the long-term safety evaluation period and continued the assigned treatment (those in group F were randomly assigned to group B or D), with 40 weeks' observation. The primary endpoint was the percent change in low density lipoprotein cholesterol (LDL-C) from baseline at week 12. Secondary endpoints included the percent changes in high density lipoprotein cholesterol (HDL-C), triglyceride (TG), apolipoprotein B (Apo B) at week 12 and changes of the four above-mentioned lipid indicators at weeks 18, 24, 38, and 52. Safety was evaluated during the whole treatment period. Results: Totally, 727 patients were included in the treatment period with a mean age of (55.0±9.3) years old, including 253 males. No statistical differences were observed among the groups in demographics, comorbidities, and baseline blood lipid levels. At week 12, the percent changes in LDL-C were significantly different among groups A to F (all P<0.01). Compared to atorvastatin alone, hybutimibe combined with atorvastatin could further improve LDL-C, TG, and Apo B (all P<0.05). Furthermore, there was no significant difference in percent changes in LDL-C at week 12 between group C and group E (P=0.991 7). During the long-term evaluation period, there were intergroup statistical differences in changes of LDL-C, TG and Apo B at 18, 24, 38, and 52 weeks from baseline among the statins group (group A), hybutimibe group (groups B, D, and F), and combination group (groups C and E) (all P<0.01), with the best effect observed in the combination group. The incidence of adverse events was 64.2% in the statins group, 61.7% in the hybutimibe group, and 71.0% in the combination group during the long-term evaluation period. No treatment-related serious adverse events or adverse events leading to death occurred during the 52-week study period. Conclusions: Hybutimibe combined with atorvastatin showed confirmatory efficacy in patients with untreated primary hypercholesterolemia, which could further enhance the efficacy on the basis of atorvastatin monotherapy, with a good overall safety profile.

Adaptive Perspective Distillation for Semantic Segmentation

Strong semantic segmentation models require large backbones to achieve promising performance, making it hard to adapt to real applications where effective real-time algorithms are needed. Knowledge distillation tackles this issue by letting the smaller model (student) produce similar pixel-wise predictions to that of a larger model (teacher). However, the classifier, which can be deemed as the perspective by which models perceive the encoded features for yielding observations (i.e., predictions), is shared by all training samples, fitting a universal feature distribution. Since good generalization to the entire distribution may bring the inferior specification to individual samples with a certain capacity, the shared universal perspective often overlooks details existing in each sample, causing degradation of knowledge distillation. In this paper, we propose Adaptive Perspective Distillation (APD) that creates an adaptive local perspective for each individual training sample. It extracts detailed contextual information from each training sample specifically, mining more details from the teacher and thus achieving better knowledge distillation results on the student. APD has no structural constraints to both teacher and student models, thus generalizing well to different semantic segmentation models. Extensive experiments on Cityscapes, ADE20K, and PASCAL-Context manifest the effectiveness of our proposed APD. Besides, APD can yield favorable performance gain to the models in both object detection and instance segmentation without bells and whistles.

Characterizing and predicting the relationship between translaminar fracture toughness and pull-out length distributions under distinct temperatures

The translaminar fracture toughness reflects the damage tolerance of a fibre-reinforced composite under longitudinal tension, which often governs the final failure of structures. One of the main energy-dissipation mechanisms that contributes to the translaminar toughness of composites is the fibre pull-out process. The present study aims to quantify and model the statistical distribution of fibre pull-out lengths formed on the translaminar fracture surface of composites, for the first time in the literature; this is done under different temperatures, so that the relationship between pull-out length distributions, micromechanical properties and the translaminar fracture toughness can be established. The fracture surfaces of cross-ply compact tension specimens tested under three different temperatures have been scanned through X-ray computed tomography to quantify the extent of fibre pull-out on the fracture surfaces; the distribution of pull-out lengths showed alarger average and larger variability with an increase in temperature, which also lead to an increase in translaminar fracture toughness. A similar trend has been captured by the proposed analytical model, which predicts the pull-out length distribution based on the analysis of quasi-fractal idealizations of the fracture surface, yielding an overall accuracy of more than 85%. This article is part of the theme issue 'Ageing and durability of composite materials'.

Ferroptosis in neurodegenerative diseases: inhibitors as promising candidate mitigators

OBJECTIVE

Ferroptosis is a new form of iron-dependent programmed cell death, characterized by intracellular iron overload and lipid peroxidation. Several studies have revealed that ferroptosis is associated with the occurrence and development of various neurodegenerative diseases (NDs). Therefore, this paper reviews the mechanism and related genes of ferroptosis, focusing on the research of antiferroptosis drugs in NDs to provide theoretical support for future experimental research and clinical application.

MATERIALS AND METHODS

This work focuses on ferroptosis, and the authors searched the literature on PubMed related to ferroptosis using the keywords "neurodegenerative diseases" and "neurons". All articles were from August 2022 and earlier, excluding irrelevant or retracted articles, and articles from the last five years were used as the main inclusion criteria.

RESULTS

After collection and summary, it was found that ferroptosis in NDs was not only related to iron metabolism, lipid metabolism, and amino acid metabolism but also related to genes such as Nrf2, FSP1, VDACs, and p53. We also summarized drugs that inhibited ferroptosis in NDs and classified them according to their mechanism of action.

CONCLUSIONS

Ferroptosis was involved in the progression of NDs through its production mechanism and related genes. Targeting ferroptosis might be a new strategy for treating NDs.

Comparison of Good Clinical Practice Inspection Processes for Marketing Applications Between the United States Food and Drug Administration and the European Medicines Agency

BACKGROUND

The U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA) began collaboration on Good Clinical Practice (GCP) inspections for marketing applications since 2009. The main characteristics of the GCP inspection processes between FDA and EMA were never evaluated. This is the first analysis comparing the GCP inspection processes between the two agencies.

METHODS

We examined and analyzed the key characteristics of the GCP inspection processes, including the geographical distribution, inspection types and timelines from application submission to final inspection reporting for marketing applications from September 2009 through December 2015.

RESULTS

Fifty-five shared applications were included for analysis. For these applications, a total of 433 GCP inspections were conducted in 47 countries. Most clinical investigator (CI) inspections were conducted in regions outside of each agency's own regulatory jurisdiction, while most sponsor/contract research organization (CRO) inspections were conducted in the U.S. by both agencies. Twenty-eight shared applications included common sites inspected by both agencies. There were 15 joint inspections conducted for seven of these applications and the remaining applications had common sites inspected by both agencies at separate times. Of the joint inspections, 73% were conducted in the U.S and 20% in the E.U. The median time from submission of an application to generation of final inspection reports was 232 days for FDA and 204 days for EMA, with no significant differences noted among applications with and without common sites.

CONCLUSION

The inspection processes and timelines between the two agencies were similar, providing support for continued FDA-EMA GCP collaboration.

Effect of CTP-mediated PTEN on 5637 bladder cancer cells and the underlying molecular mechanism

OBJECTIVE

The aim of the present study was to explore the effect of cytoplasmic transduction peptide (CTP)-phosphatase and tensin homolog (PTEN) on the proliferation, cell cycle, apoptosis, migration and invasion of bladder cancer cells and the underlying molecular mechanism.

METHODS

A eukaryotic expression vector, pTT5-CTP-PTEN, was constructed. The constructed vector was transfected into HEK 293-6E cells to express a fusion protein, CTP-PTEN. The fusion protein was purified. 5637 bladder cancer cells were cocultured with purified CTP-PTEN fusion protein. Target gene expression, protein expression, cell proliferation, cell cycle, apoptosis, cell invasion and cell migration were examined by reverse transcription polymerase chain reaction (RT-PCR), western blot, MTT assay, flow cytometry, Transwell assay, and cell scratch assay, respectively.

RESULTS

Both PTEN and CTP-PTEN fusion protein inhibited the proliferation, cell cycle, invasion and migration of bladder cancer cells and promoted the apoptosis of bladder cancer cells. The effect of CTP-PTEN was more significant.

CONCLUSIONS

The fused expression of CTP and PTEN significantly increased the penetrability of the tumor suppressor gene PTEN into cancer cells. The CTP-PTEN fusion protein exhibited a significant carcinostatic effect on 5637 bladder cancer cells.

An Efficient Sharing Grouped Convolution via Bayesian Learning

Compared with traditional convolutions, grouped convolutional neural networks are promising for both model performance and network parameters. However, existing models with the grouped convolution still have parameter redundancy. In this article, concerning the grouped convolution, we propose a sharing grouped convolution structure to reduce parameters. To efficiently eliminate parameter redundancy and improve model performance, we propose a Bayesian sharing framework to transfer the vanilla grouped convolution to be the sharing structure. Intragroup correlation and intergroup importance are introduced into the prior of the parameters. We handle the Maximum Type II likelihood estimation problem of the intragroup correlation and intergroup importance by a group LASSO-type algorithm. The prior mean of the sharing kernels is iteratively updated. Extensive experiments are conducted to demonstrate that on different grouped convolutional neural networks, the proposed sharing grouped convolution structure with the Bayesian sharing framework can reduce parameters and improve prediction accuracy. The proposed sharing framework can reduce parameters up to 64.17%. For ResNeXt-50 with the sharing grouped convolution on ImageNet dataset, network parameters can be reduced by 96.875% in all grouped convolutional layers, and accuracies are improved to 78.86% and 94.54% for top-1 and top-5, respectively.

[Research advances on interleukin-6 in hypertrophic scar formation]

Hypertrophic scar is a pathological repair result of excessive accumulation of extracellular matrix after skin damage, which affects the appearance and function of patients with varying degrees. The degree of scar formation is directly related to the strength of inflammatory reaction during wound healing, and excessive or prolonged inflammatory response increases the incidence of hypertrophic scars. Interleukin-6 (IL-6) is a pleiotropic cytokine that is involved in regulating the fibrotic network composed of fibroblasts, macrophages, keratinocytes, and vascular endothelial cells, and is closely related to the formation of hypertrophic scars. This article reviews the role of IL-6 and its signaling pathway in hypertrophic scar formation.

[A retrospective controlled study on the treatment effect of distraction osteogenesis and maxillomandibular advancement for severe obstructive sleep apnea hypopnea syndrome patients]

Objective: To compare the treatment effect of distraction osteogenesis (DO) and maxillomandibular advancement (MMA) for severe obstructive sleep apnea hypopnea syndrome (OSAHS) patients and to guide clinical decisions about treatment of OSAHS. Methods: Thirty-seven OSAHS patients which accepted maxillomandibular advancement (MMA) or distraction osteogenesis (DO) in Stomatological Hospital of the Department of Maxillofacial Trauma and Orthognathic Surgery, School of Stomatology, The Forth Military Medical University from June 2017 to June 2019 were collected. Their preoperative and postoperative data of cephalometry, polysomnography (PSG), Pittsburgh sleep quality index (PSQI) and Epworth sleepiness scale (ESS) scores were collected and analyzed. With propensity score matching method, the treatment effect of MMA and DO was analyzed and compared. Results: According to the statistics of MMA group, only AHI was correlated with operative successful rate and cure rate. With the increase of AHI, the treatment effect of MMA on OSAHS patients gradually decreased. The cut-off point of AHI as a predictor of MMA treatment failure was 78.2 n/h. All the matched cases were severe OSAHS patients. Statistical analysis showed that the mandibular elongation of DO patients[(24.00±4.39) mm] was significantly more than that of MMA group [(11.20±1.37) mm] (t=-6.11, P<0.001), the improvement of PSG index [including lowest oxygen saturation (LSpO₂), longest apnea (LA) and longest hypopnea (LH)] in DO group [LSpO₂=(93.40±1.82)%; LA=(18.28±8.32) s; LH=(61.84±32.94) s] was significantly higher than that in the MMA group [LSpO₂=(86.00±4.06)%, LA=(64.08±21.78) s, LH=(172.40±30.70) s](t=-3.72, P=0.005; t=4.39, P=0.003; t=5.49, P=0.004). The PSQI and the ESS scores of DO group (PSQI=4.20±0.83; ESS=3.40±1.52) were also significantly better than that of MMA group (PSQI=8.80±2.39, ESS=9.40±2.88)(t=4.07, P=0.001; t=4.12, P=0.002). Conclusions: For severe OSAHS patients, the objective and subjective indicators of DO treatment group showed a better therapeutic effect than that of MMA.

Synchrotron radiation X-ray imaging with large field of view and high resolution using micro-scanning method

In synchrotron radiation X-ray imaging, the imaging field of view and spatial resolution are mutually restricted, which makes it impossible to have both a large field of view and high resolution when carrying out experiments. Constructing an oversampled image through the micro-scanning method and using the deconvolution algorithm to eliminate the point spread function introduced by pixel overlap can increase the resolution under a fixed imaging field of view, thereby improving the ratio of the field of view to the spatial resolution. In this paper, numerical simulation and synchrotron radiation experiments are carried out with a different number of micro-scanning steps. In numerical simulation experiments only affected by the image pixel size, as the number of micro-scanning steps increases, the ability of the oversampled image with deconvolution to improve the resolution is stronger. The achievable resolution of the oversampled image with deconvolution is basically the same as that of the sample image. In the synchrotron radiation experiments, the resolution of the oversampled image with deconvolution in the 2 × 2 mode is significantly improved. However, as the number of micro-scanning steps increases, the resolution improvement is limited, or even no longer improved. Finally, by analyzing the results of numerical simulation and synchrotron radiation experiments, three factors (four other factors affecting the resolution besides the camera resolution, translational accuracy of micro-scanning, and the signal-to-noise ratio of projections) affecting the micro-scanning method are proposed and verified by experiments.

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.

Fermented soybean meal increases nutrient digestibility via the improvement of intestinal function, anti-oxidative capacity and immune function of weaned pigs

The nutritional components of fermented soybean meal (FSBM) vary because of the complex process of microbial fermentation. The objective of this study was to investigate the nutritional value of FSBM from two sources and explore the mode of actions of FSBM on the improvement of nutrient digestibility with the measurements of digestive enzymes and serum biomarkers. Eight weaned barrows (initial BW: 14.12 ± 0.24 kg) equipped with T-cannula in the distal ileum were allotted to a duplicated 4 × 4 Latin-square design with four experimental diets and four periods. Four experimental diets included a soybean meal control diet, two FSBM diets, and a nitrogen-free diet. The two sources of FSBM increased the contents of CP, amino acid and lactic acid, while decreased the levels of anti-nutritional factors, including glycinin, β-conglycinin and trypsin inhibitors. Compared to soybean meal control diet, both FSBM diets significantly increased the apparent and standardised ileal digestibility of CP and amino acids (P < 0.05), increased the activities of lipase, maltase and invertase in digesta (P < 0.05), increased total antioxidant capacity, activities of glutathione peroxidase and superoxide dismutase, the levels of interleukin-4, IgA, IgG and IgM in serum (P < 0.05), while decreased the levels of diamine oxidase, malondialdehyde, interleukin-6, and interleukin-2 in serum (P < 0.05). Additionally, the standardised ileal digestibility of amino acids were highly correlated with the aforementioned digestive enzymes and health-related serum biomarkers. In summary, FSBM diets showed an improved nutritional value evidenced by the higher nutrient digestibility, which may be partially derived from its beneficial effects on intestinal integrity, anti-oxidative capacity and immune function.

Abnormal keratin expression pattern in prurigo nodularis epidermis

Background

Prurigo nodularis (PN) is a highly pruritic, chronic dermatosis and difficult to treat. PN lesions are characterized by existence of many hyperkeratotic, erosive papules and nodules. However, the pathogenesis of PN still remains unelucidated.

Aim

To clarify the keratin role in the epidermis hyperproliferation, the keratin expression pattern in the PN lesional skin.

Methods

In this study, we enrolled 24 patients with PN and 9 healthy control volunteers. K1/K10, K5/K14, K6/K16/K17 expression pattern were investigated by using immunohistochemical staining.

Results

The lesional skin consists of the thickened spinous layers, in which active cell division was found. K5/K14 were upregulated in PN lesional epidermis, the staining signal localized in the basal layer and lower suprabasal layers. Hyperproliferation‐associated K6 was found in all layers of epidermal lesional skin, especially in the spinous layers. In contrast, K16 was only detected in the basal and lower suprabasal layers, K17 was observed in the basal and spinous layers. Terminal differential keratins K1/K10 were upregulated, detected in the pan‐epidermis, but spared in the basal and low suprabasal layers.

Conclusion

The keratinocytes enter an alternative differentiation pathway, which are responsible for the activated keratinocyte phenotype, abnormal keratins expression potentially contributes to the keratinocytes proliferation, subsequently lead to increased lesional skin epidermis thickness, hyperkeratiosis and alteration of skin barrier properties.

Autophagy mediates ER stress and inflammation in Helicobacter pylori-related gastric cancer

Autophagy is a cellular degradation mechanism, which is triggered by the bacterium Helicobacter pylori. A single nucleotide polymorphism (SNP) in the autophagy gene ATG16L1 (rs2241880, G-allele) has been shown to dysregulate autophagy and increase intestinal endoplasmic reticulum (ER) stress. Here, we investigate the role of this SNP in H.pylori-mediated gastric carcinogenesis and its molecular pathways. ATG16L1 rs2241880 was genotyped in subjects from different ethnic cohorts (Dutch and Australian) presenting with gastric (pre)malignant lesions of various severity. Expression of GRP78 (a marker for ER stress) was assessed in gastric tissues. The effect of ATG16L1 rs2241880 on H.pylori-mediated ER stress and pro-inflammatory cytokine induction was investigated in organoids and CRISPR/Cas9 modified cell lines. Development of gastric cancer was associated with the ATG16L1 rs2241880 G-allele. Intestinal metaplastic cells in gastric tissue of patients showed increased levels of ER-stress. In vitro models showed that H.pylori increases autophagy while reducing ER stress, which appeared partly mediated by the ATG16L1 rs2241880 genotype. H.pylori-induced IL-8 production was increased while TNF-α production was decreased, in cells homozygous for the G-allele. The ATG16L1 rs2241880 G-allele is associated with progression of gastric premalignant lesions and cancer. Modulation of H.pylori-induced ER stress pathways and pro-inflammatory mediators by ATG16L1 rs2441880 may underlie this increased risk.

[Associations between adverse childhood experiences and adulthood substance use among lesbians]

Objective: To investigate the associations between adverse childhood experiences (ACE) and substance use behaviors among lesbians to provide a scientific basis for high-risk population identification and formulation of targeted intervention measures. Methods: Lesbians who participated in routine AIDS voluntary counseling, testing services, activities, and peer recommendations were recruited from July to December 2018, with the help of LesPark in Beijing. Convenient sampling method was used. Demographic characteristics, ACE, and substance use behaviors of subjects were investigated using an online platform powered by www.wjx.cn. Subsequently, the associations between ACE and adulthood substance use behaviors were evaluated using the logistic regression model. The SPSS 22.0 was used for statistical analysis. Results: A total of 294 lesbians were recruited in the study, 81.3% (239/294) of them were lesbians, and 18.7% (55/294) were bisexuals. Besides, 55.8% (164/294) of subjects reported they had had ACE, with proportions of lesbians experiencing abuse, neglect, and family dysfunction as 33.3% (98/294), 24.5% (72/294), and 32.7% (96/294), respectively. 55.1% (162/294) of the lesbians reported they had smoked in the past 30 days, 11.2% (33/294) reported having drug-use behavior in the past three months, and 22.8% (67/294) claimed drinking alcohol weekly. Multivariate logistic regression analysis showed that lesbians with ACE were at high risks to smoke (OR=1.87, 95%CI: 1.13-3.08), drink (OR=2.13, 95%CI: 1.18-3.84), and use drugs (OR=3.33, 95%CI: 1.29-8.61) in adulthood. Moreover, lesbians with childhood family dysfunction were at higher risk of smoking cigarettes (OR=2.60, 95%CI: 1.46-4.62) and drinking alcohol (OR=2.65, 95%CI: 1.44-4.87). At the same time, those with abuse experience were at higher risk of drug use (OR=3.17, 95%CI: 1.26-7.96). Conclusions: Substance use behaviors, including cigarette smoking, drinking alcohol, and drugs use, were common among lesbians. Positive associations were found between ACE and adulthood substance use behaviors.

[Analysis of suspected occupational chronic lead poisoning reported online and subsequent diagnosis in Jiangsu Province from 2014 to 2018]

Objective: To understand the distribution and characteristics of suspected occupational chronic lead poisoning reported online by Jiangsu Province, and to track the final diagnosis of suspected cases. Methods: The suspected occupational chronic lead poisoning cases in Jiangsu Province reported online from 2014 to 2018 were collected as the survey objects. Based on the reporting of the Occupational Disease Report Card from January 1, 2014 to November 5, 2019, the distribution characteristics and reporting institutions of suspected cases and final confirmed cases were analyzed. Results: From 2014 to 2018, 312 cases of suspected occupational chronic lead poisoning were reported online in Jiangsu Province. There were significant differences in the number of online reported cases of occupational chronic lead poisoning, online reported cases of suspected occupational chronic lead poisoning and confirmed cases of suspected occupational chronic lead poisoning in different years (P<0.05) , especially in 2015. Among the suspected occupational lead poisoning cases reported online, 236 cases (75.6%) were male, mainly distributed in the manufacturing industry, and 246 cases (79.1%) were operators. All the suspected occupational chronic lead poisoning cases reported online were concentrated in private enterprises, 229 cases (73.4%) in small and medium-sized enterprises. The top three cities were Suqian with 111 cases (35.6%) , Yangzhou with 79 cases (25.3%) and Huai'an with 50 cases (16.0%) . From 2014 to 2018, 19 suspected cases of occupational chronic lead poisoning were finally confirmed in Jiangsu Province, with a diagnosis rate of 6.1%. Conclusion: The majority of suspected occupational chronic lead poisoning cases reported online in Jiangsu Province are men, manufacturing and small and medium-sized enterprises, and the final diagnosis rate of suspected occupational chronic lead poisoning cases reported online is low.

[Analysis on migration of HIV/AIDS cases and related factors in Liangshan Yi Autonomous Prefecture in Sichuan province, 2020]

Objective: To analyze the migration of the HIV/AIDS cases and related factors in Liangshan Yi autonomous prefecture (Liangshan). Methods: According to HIV/AIDS Comprehensive Response Information Management System of China Information System for Disease Control and Prevention, a total of 28 772 HIV/AIDS cases who had follow-up records in Liangshan in 2020 were included in the survey. The migration of the HIV/AIDS cases was described and the related factors were analyzed using multiple logistic regression models, and the migration destinations of the HIV/AIDS cases were mapped. Results: Among the 28 772 HIV/AIDS cases, 20.89% (6 010/28 772) had migration in 2020. Multivariate logistic regression analysis showed that among the HIV/AIDS cases, the migration related factors included being aged 15-24 years (compared with being aged 0-14 years, OR=2.74, 95%CI:2.04-3.69) and ethnic group (compared with Han ethnic group, OR=2.44, 95%CI:2.19-2.72), having education level of junior high school (compared with having education level of primary school or below, OR=1.25, 95%CI:1.14-1.38), being unmarried (compared with being married, OR=1.29, 95%CI:1.20-1.39), being engaged in business services (compared with being engaged in farming, OR=1.96, 95%CI:1.31-2.92), receiving antiviral treatment <1 year (compared with receiving antiviral treatment >3 years, OR=1.42, 95%CI:1.26-1.61), having recent CD4⁺T lymphocytes (CD4) counts >500 cells/μl (compared with having recent CD4 counts <200 cells/μl, OR=1.15, 95%CI:1.03-1.29). The geographical distribution maps showed that among all cities in Sichuan, Xichang (13.26%, 797/6 010) and Chengdu (10.12%,608/6 010) were the main migration destinations of the HIV/AIDS cases, and the provinces outside Sichuan where the HIV/AIDS cases would like to migrate to were mainly Guangdong (18.19%, 1 093/6 010) and Zhejiang provinces (7.67%, 461/6 010) in 2020. The HIV/AIDS cases who migrated where Liangshan, within Sichuan province, and to other provinces accounted for 27.67% (1 663/6 010), 15.34% (922/6 010) and 56.99% (3 425/6 010), respectively. Conclusions: More attention should be paid to the mobility characteristics and the classification management of HIV/AIDS cases according to their characteristics in Liangshan. Timely access to information on changes in the place of work and residence of HIV/AIDS cases should be warranted when they have migration. Good referrals and management for mobility of HIV/AIDS cases in different places should be made to reduce loss to follow-up and improving interventions.

3-D ultrasonic image reconstruction in frequency domain using a virtual transducer model

In ultrasonic non-destructive testing, image reconstruction is essential to restore the diffracted ultrasound signals to improve the lateral resolution of images. Some reconstruction methods, like DAS-based synthetic aperture imaging, are inefficient, especially for reconstructing three-dimensional (3-D) images. Other methods do not provide high-resolution results, because they neglect the distortion effect introduced by transducer geometry. To overcome these disadvantages, we propose a 3-D ultrasonic image reconstruction method based on synthetic aperture wavenumber algorithm. It considers wave diffraction and transducer geometry effects, and can refocus the reflectors even in non-focal zone, which suits for large depth range imaging. This method builds a virtual transducer model in frequency domain by treating the focused transducer as a virtual planar transducer on its focal plane. In addition, the method uses non-uniform fast Fourier transform and deconvolution operation to achieve the 3-D image reconstruction, which has remarkably improved the efficiency and accuracy. According to the experimental results, the lateral resolution of an image reconstructed by the proposed method can reach 290.2 μm, exceeding the lateral resolution limitation of the 15 MHz focused transducer (523.24 μm). Furthermore, the proposed method only takes 0.744 s to reconstruct a 3-D image with 1000×100×100 pixels, while the time domain SAFT takes about 1163.8 s. It shows the potential for real-time 3-D imaging under advanced hardware.

Serum Leptin and Adiponectin: Indicators of Cardiovascular Disease Secondary to Psoriasis

Background

To explore the role and clinical significance of serum adiponectin and leptin levels in patients with psoriasis accompanied by atherosclerosis.

Methods

Eighty patients diagnosed with psoriasis in our dermatology department and 40 healthy people in our physical examination centre were included as the study group and control group, respectively. All the included patients underwent fasting blood and serum tests. Levels of adiponectin, leptin, and the blood lipid content; colour Doppler ultrasonography of both common carotid arteries, internal carotid and external carotid arteries; and intimal-medial thickness (IMT) and carotid plaque were evaluated.

Results

In the study group, the leptin level increased, and the serum adiponectin level decreased; these levels were statistically significantly different compared with those in the control group (t = 6.774, P < 0.001 and t = -3.511, P < 0.05, respectively). IMT was negatively correlated with adiponectin levels (r = -0.378, P < 0.001) and positively correlated with leptin levels (r = 0.581, P < 0.001).

Conclusions

The imbalanced expression of serum and adiponectin levels will aggravate psoriasis and promote the occurrence of atherosclerosis. Serum levels can be used to assess the disease severity, detect vascular lesions early, and prevent the development of psoriasis to cardiovascular disease.

Serum Irisin: A Potential Diagnostic Marker for Insulin Resistance in Acne Vulgaris

Background

Acne vulgaris (AV) is a chronic inflammatory disease of the pilosebaceous unit. Many factors are involved in the occurrence of acne. It has been confirmed that some adipokines play an important role in the development of AV. Irisin is a novel adipokine, which is highly expressed in skeletal muscle, liver, and fat. It improves insulin resistance (IR) by inducing the browning of white adipose tissue, increasing heat production and energy expenditure.

Objective

The purpose of this study was to investigate the role of serum irisin as an adipokine to explore its function in the pathogenesis of AV and its correlation with IR, and whether it can be used as a potential biomarker of insulin sensitivity. Although the hyperinsulinemic-euglycemic clamp remains the gold standard for accurate determination of IR, it cannot be performed routinely. Various alternative simpler measures have been used, the most common being homeostasis model assessment. However, these metrics are limited by their accuracy, cost, and blood collection requirements.[1] Therefore, an effective and feasible serum biomarker is an attractive and relatively straightforward method, which may provide clinicians with a more accurate and simple method for the prediction and diagnosis of IR. IR can often be detected before other symptoms appear, so establishing an early diagnosis method will allow for the appropriate treatment of patients before the disease develops.

Patients and Methods

The study included 171 subjects; 115 patients with newly diagnosed AV and 56 apparently healthy subjects. The contents of irisin and interleukin-1 alpha in serum were determined by enzyme-linked immunosorbent assay. The IR index was calculated by the homeostasis model.

Results

Serum irisin levels in AV patients and control group were (24.0 ± 11.3) and (104.3 ± 27.0) ng/dl, respectively, which were significantly lower than those in control group (P < 0.001). Serum irisin was negatively correlated with IR (r = -0.711, P 0.001). The sensitivity of irisin was 100.0%, the specificity was 92.8%, and the cutoff point was 53.32. The decrease of serum irisin level could predict the patients with IR in acne.

Conclusion

Serum irisin levels in AV patients were significantly decreased. Serum irisin showed acceptable performance criteria in the diagnosis of AV with IR. Serum irisin seems to be a good diagnostic and prognostic marker for IR. Further multi-center studies are needed to confirm this link, which could pave the way for new treatment options.

Belantamab mafodotin for the treatment of multiple myeloma

Multiple myeloma is the second most common hematologic malignancy worldwide. Despite the growing number of available therapeutic options and advances in the treatment since the 2000s, relapse of multiple myeloma is inevitable. Currently, the main therapeutic agents for multiple myeloma treatment include proteasome inhibitors, immunomodulatory drugs, monoclonal antibodies and others. Patients who relapse or are refractory to the above-mentioned treatments have poor prognosis. B-cell maturation antigen (BCMA) is a cell-surface receptor which is expressed on the membrane of multiple myeloma cells, but absent on naive and memory B cells, making it an ideal target for multiple myeloma treatment. Belantamab mafodotin (GSK-2857916) is a first-in-class BCMA antibody-drug conjugate with an overall response rate of 32% in the phase II clinical trial DREAMM-2, which is a phase II study designed to investigate the efficacy and safety of belantamab mafodotin in relapsed/refractory patients with multiple myeloma. In August 2020, based on the results of this pivotal DREAMM-2 study, the U.S. Food and Drug Administration (FDA) approved belantamab mafodotin as a monotherapy for relapsed/refractory multiple myeloma. Thereafter, the European Medicines Agency (EMA) also approved this indication. Although belantamab mafodotin has demonstrated single-agent activity in relapsed/refractory multiple myeloma, further studies to evaluate its efficacy and its combinational use with other drugs are necessary and ongoing.