Search

Abstract Background Primary health-care workers (PHWs) managed increased workloads and pressure during the COVID-19 pandemic. This study conducted a national survey examining burnout among PHWs at the end of the COVID-19 pandemic, and identifies related factors. By doing so, it addresses the gap in understanding the burnout situation among PHWs at a national level, taking into account urban-rural disparities. Methods We conducted a nationwide cross-sectional survey of PHWs in China from May to October 2022, covering 31 provinces. The MBI-HSS was used to measure overall burnout and emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (PA). We used multivariable logistic regression to identify risk factors, and subgroup analyses to identify differences between rural and urban areas. Results 3769 PHWs from 44 primary health-care institutions completed the survey. Overall, 16.6% reported overall burnout, and the prevalence of EE, DP, and reduced PA was 29.7%, 28.0%, and 62.9%, respectively. The prevalence of overall burnout (17.6% vs. 13.7%, P = 0.004) and EE (31.5% vs. 24.8%, P

Three chemical series of heterocyclic small molecules were designed and synthesized as the 3rd generation EGFR inhibitors. Detailed structure-activity relationship (SAR) studies and lead optimization (from 1a to 4d) were descripted. With the support of molecular modeling and evaluation through biochemical and cellular assays, liver microsomal/ plasma/ blood stability studies, preliminary rat PK screening and in vivo animal models, pyrrolopyrimidine-based compound 4d (abivertinib, AC0010), a novel potent and highly selective irreversible EGFR inhibitor, was discovered.Unlabelled ImageThis compound has been being clinically investigated in several countries including China, the United States, and Europe. Structurally distinct from those irreversible pyrimidine-based EGFR inhibitors (rociletinib, and recently approved osimertinib), abivertinib (AC0010) has demonstrated significant clinical benefit with good safety profiles (through a different metabolic pathway and possibly different resistance mechanism compared to both osimertinib and rociletinib) in NSCLC patients who had progressed on previous therapy, which provides an alternative therapeutic agent for NSCLC patients who develop acquired resistance to first generation EGFR TKIs.

Abstract Background/aims ErbB3 is an oncogene which has proliferation and metastasis promotion effects by several signaling pathways. However, the individual expression difference regulated by miRNA was almost still unknown. We focused on the miRNAs associated SNPs in the 3′-UTR of ErbB3 to investigate the further relationship of the SNPs with miRNAs among Chinese gastric cancer (GC) patients. Methods We performed case–control study including 851 GC patients and 799 cancer-free controls. Genotyping, real-time PCR assay, cell transfection, the dual luciferase reporter assay, western-blot, cell proliferation and trans-well based cell invasion assay were used to investigate the effects of the SNP on ErbB3 expression. Moreover, a 5-years-overall survival and relapse free survival were investigated between different genotypes. Results We found that patients suffering from Helicobacter pylori (Hp.) infection indicated to be the susceptible population by comparing with controls. Besides, SNP rs3202538 (G/T) in ErbB3 3′-UTR was involved in the occurrence of GC by acting as tumor risk factors. SNP rs3202538 (G/T) could be regulated by both miR-204 and miR-211 which caused an upregulation of ErbB3 in patients. Furthermore, the carriers of T genotype was related to the significantly high expression of ErbB3, and to big tumor size, poor differentiation as well as the high probability of metastasis. Both miR-211 and miR-204 can significantly decrease cell proliferation, metastasis as well as downstream AKT activation through G but not T allele of ErbB3 3′UTR. Moreover, the SNP of G/T was associated with shorter survival of post-surgery GC patients with 5 years of follow up study. Conclusion In conclusion, our findings have shown that the SNP rs3202538 (G/T) in ErbB3 3′-UTR acted as promotion factors in the GC development through disrupting the regulatory role of miR-204 and miR-211 in ErbB3 expression.

A growing understanding of the molecular interactions between immune effector cells and target tumor cells, coupled with refined gene therapy approaches, are giving rise to novel cancer immunotherapeutics with remarkable efficacy in the clinic against both solid and liquid tumors. While immunotherapy holds tremendous promise for treatment of certain cancers, significant challenges remain in the clinical translation to many other types of cancers and also in minimizing adverse effects. Therefore, there is an urgent need for functional potency assays, in vitro and in vivo, that could model the complex interaction of immune cells with tumor cells and can be used to rapidly test the efficacy of different immunotherapy approaches, whether it is small molecule, biologics, cell therapies or combinations thereof. Herein we report the development of an xCELLigence real-time cytolytic in vitro potency assay that uses cellular impedance to continuously monitor the viability of target tumor cells while they are being subjected to different types of treatments. Specialized microtiter plates containing integrated gold microelectrodes enable the number, size, and surface attachment strength of adherent target tumor cells to be selectively monitored within a heterogeneous mixture that includes effector cells, antibodies, small molecules, etc. Through surface-tethering approach, the killing of liquid cancers can also be monitored. Using NK92 effector cells as example, results from RTCA potency assay are very well correlated with end point data from image-based assays as well as flow cytometry. Several effector cells, i.e., PBMC, NK, CAR-T were tested and validated as well as biological molecules such as Bi-specific T cell Engagers (BiTEs) targeting the EpCAM protein expressed on tumor cells and blocking antibodies against the immune checkpoint inhibitor PD-1. Using the specifically designed xCELLigence immunotherapy software, quantitative parameters such as KT50 (the amount of time it takes to kill 50% of the target tumor cells) and % cytolysis are calculated and used for comparing the relative efficacy of different reagents. In summary, our results demonstrate the xCELLigence platform to be well suited for potency assays, providing quantitative assessment with high reproducibility and a greatly simplified work flow.

Global warming is primarily characterized by asymmetric temperature increases, with greater temperature rises in winter/spring and at night compared to summer/autumn and the daytime. We investigated the impact of winter night warming on the top expanded leaves of the spring wheat cultivar Yangmai 18 and the semi-winter wheat cultivar Yannong 19 during the 2020–2021 growing season. Results showed that the night-time mean temperature in the treatment group was 1.27°C higher than the ambient temperature, and winter night warming increased the yields of both wheat cultivars, the activities of sucrose synthase and sucrose phosphate synthase after anthesis, and the biosynthesis of sucrose and soluble sugars. Differentially expressed genes (DEGs) were identified using criteria of P-value2, and they were subjected to Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Genes differentially expressed in wheat leaves treated with night warming were primarily associated with starch and sucrose metabolism, amino acid biosynthesis, carbon metabolism, plant hormone signal transduction, and amino sugar and nucleotide sugar metabolism. Comparisons between the groups identified 14 DEGs related to temperature. These results highlight the effects of winter night warming on wheat development from various perspectives. Our results provide new insights into the molecular mechanisms of the response of wheat to winter night warming and the candidate genes involved in this process.

Abstract Background Chitinases (CHIs) are glycosidases that degrade chitin, playing critical roles in plant responses to both abiotic and biotic stress. Despite their importance, the CHI family’s systematic analysis and evolutionary pattern in F. tataricum (Tartary buckwheat) yet to be explored. Results This study analyzed their phylogenetic relationships, conserved motifs, gene structures, syntenic relationships, physiological functions, and biochemical properties. This research identified 26 FtCHIs and examined their expression patterns under different salt stress conditions and across various tissues. Differential expression analysis revealed a significant upregulation of multiple FtCHIs in response to salt stress, which RT-qPCR further validated. Additionally, subcellular localization experiments demonstrated that Ft_chitinaseIV-2 is localized in vacuoles. The results of transient·transformation showed that·overexpression of Ft_chitinaseIV-2 could·enhance the salt tolerance of plants. Conclusions The findings provide new insights into the role of CHIs in stress tolerance and lay the groundwork for future research on the functional characterization of FtCHIs. Understanding the molecular mechanisms of CHI-mediated stress responses could contribute to developing stress-resistant crops.

Abstract To identify patterns in big medical datasets and use Deep Learning and Machine Learning (ML) to reliably diagnose Cardio Vascular Disease (CVD), researchers are currently delving deeply into these fields. Training on large datasets and producing highly accurate validation results is exceedingly difficult. Furthermore, early and precise diagnosis is necessary due to the increased global prevalence of cardiovascular disease (CVD). However, the increasing complexity of healthcare datasets makes it challenging to detect feature connections and produce precise predictions. To address these issues, the Intelligent Cardiovascular Disease Diagnosis based on Ant Colony Optimisation with Enhanced Deep Learning (ICVD-ACOEDL) model was developed. This model employs feature selection (FS) and hyperparameter optimization to diagnose CVD. Applying a min–max scaler, medical data is first consistently prepared. The key feature that sets ICVD-ACOEDL apart is the use of Ant Colony Optimisation (ACO) to select an optimal feature subset, which in turn helps to upgrade the performance of the ensuring deep learning enhanced neural network (DLENN) classifier. The model reforms the hyperparameters of DLENN for CVD classification using Bayesian optimization. Comprehensive evaluations on benchmark medical datasets show that ICVD-ACOEDL exceeds existing techniques, indicating that it could have a significant impact on CVD diagnosis. The model furnishes a workable way to increase CVD classification efficiency and accuracy in real-world medical situations by incorporating ACO for feature selection, min–max scaling for data pre-processing, and Bayesian optimization for hyperparameter tweaking.

Abstract Background The undergraduate tutorial system (UTS) is a crucial measure in China for adhering to the principle of prioritizing foundational education, innovating the undergraduate talent training mode, and building a powerful country of higher education. This study investigated undergraduate students’ satisfaction with UTS and the influencing factors, aiming to promote the healthy and sustainable development of UTS and provide practical implications and suggestions for universities. Methods Based on relevant theories, we conducted a survey study and leveraged structural equation modeling to assess students’ satisfaction with UTS and explore the influencing factors. Results Our Pearson correlation analysis showed that students’ satisfaction with mentors was positively correlated with dimensions such as humanistic care (r = 0.844, P

Immunosubtyping enables the segregation of immune responders from non-responders. However, numerous studies failed to focus on the integration of cellular heterogeneity and immunophenotyping in the prediction of hepatocellular carcinoma (HCC) patients' response to immune checkpoint inhibitors (ICIs). We categorized HCC patients into various immune subtypes based on feature scores linked to ICI response. Single-cell sequencing technology was to investigate the cellular heterogeneity of different immune subtypes and acquire significant ICI response-associated cells. Candidate drugs were identified using a blend of various drug databases and network approaches. HCC patients were divided into two distinct immune subtypes based on characterization scores of 151 immune-related gene sets. Patients in both subtypes showed varying overall survival, immunity levels, biological activities, and TP53 mutation rates. Subtype 1-related natural killer cells showed a positive correlation with immune-promoting scores but a negative correlation with immune-suppressing scores. Notably, docetaxel sensitivity in HCC patients rose as the levels of subtype 1-related natural killer cells increased. Our study demonstrated that immune subtypes have cellular heterogeneity in predicting response to ICIs. A combination of subtype 1-associated natural killer cells and docetaxel may offer new hope for ICI treatment in HCC.

Background: Many respiratory pathogens have been identified in people living with HIV-1 and pulmonary infection, but their impact on clinical outcomes remains largely unclear. Methods: Metagenomic sequencing and traditional laboratory diagnostics were applied to identify bacterial, viral, and fungal respiratory pathogens. Clinical outcomes were assessed by (i) mortality or ICU transfer during hospitalization, and (ii) 30-day re-hospitalization and 180-day mortality after hospital discharge. Results: Microbiological analyses of bacterial, viral and fungal pathogens in 237 in-patients with HIV-1 and pulmonary infections revealed Pneumocystis jirovecii (58 %) as the most prevalent respiratory pathogen, followed by Cytomegalovirus (39 %), Mycobacterium tuberculosis (22 %), Talaromyces marneffei (17 %), and Epstein-Barr virus (16 %). Fifty-six patients (24 %) were coinfected with bacterial, viral and fungal pathogens, referred to as bacterial+fungal+viral coinfections. Risk factors for bacterial+fungal+viral coinfections (RR=8.41, 95 %CI: 4.2–14.3), severe pneumonia (RR=13.6, 95 %CI: 8.14–19.3), and elevated C-reactive protein levels (RR=6.42, 95 %CI: 1.58–10.13) were significantly associated with mortality or ICU transfer during hospitalization. After hospital discharge, 38 patients (16 %) were rehospitalized within 30 days. Antiretroviral therapy reduced the risk of 30-day rehospitalization (HR=0.21, p = 0.01). During the 180-day follow-up, 13 patients (5.5 %) died. Survival analyses identified severe pneumonia and age ≥ 60 years as risk factors for 180-day mortality. Conclusions: Multiple pulmonary coinfections are associated with severe outcomes in in-patients with HIV-1 infection. Effective management of both HIV-1 and pulmonary infections is crucial to reduce hospitalization rates and mortality risk.

Lung cancer is the leading cause of cancer-related deaths globally. Despite recent improvements in incidence and mortality rates, the prognosis of lung cancer remains dire.18F-FDG PET/CT plays a vital role in diagnosing, staging, and monitoring the therapeutic efficacy of lung cancer. However, the high glucose metabolism in inflammatory lesions, driven by macrophage activation, aggregation, and the release of inflammatory factors, is a primary source of false-positive results in FDG PET/CT oncology. This significantly diminishes the specificity and accuracy of PET/CT in diagnosing and staging lung cancer.Here we show FoxO1 plays a role in glucose metabolism in macrophages.We found that metformin regulated FoxO1 expression in macrophages, regulated the expression of inflammatory mediators and apoptosis of macrophages, thus reducing inflammatory glucose metabolism and improving the diagnostic accuracy of 18F-FDG PET/CT in lung cancer.We anticipate that our study could provide a credible approach to improve tumor diagnostic accuracy with PET/CT.

There has been a growing interest in using insects as sustainable protein sources for ruminant feed, such as the adults of the two-spotted cricket (Gryllus bimaculatus), larvae of the mealworm beetle (Tenebrio molitor), black soldier fly (Hermetia illucens), and pupae of the silkworm (Bombyx mori). The advantages of these insects over other plant materials lie in their elevated levels of crude protein and fat. However, this interest lacks a comprehensive understanding of the impact of insects on the ruminal fermentation processes, including digestibility and gas production, as well as the impact on animal performance and related health aspects. This review offers a comprehensive analysis of ruminal fermentation indices across diverse insect species. Employing descriptive and meta-analysis methodologies, we examined the impact of incorporating insect-derived meals in ruminants’ diets. Moreover, we evaluated the growth performance and biochemical parameters of blood in ruminants when species such as Tenebrio molitor, Hermetia illucens, Oriental Hornet (Vespa Orientalis), and Bombyx mori were incorporated into ruminants’ diets. The meta-analysis was performed on a limited dataset of 14 in vitro and eight in vivo trials, investigating insect meal as a potential feed source. A comparison is drawn between these insect-based feeds and conventional dietary sources such as soybean meal, alfalfa hay, and commercial concentrate diets. Our meta-analysis revealed that incorporating Gryllus bimaculatus and Hermetia illucens to partially replace protein sources in ruminants’ diet did not adversely affect digestibility, ruminal fermentation, and ruminant production, supporting the feasibility as a feed ingredient for ruminant animals. In addition, the oriental hornet showed an overall higher outcome on the final BW, ADG, digestibility, and volatile fatty acid (VFA) production, suggesting the promising effect of this insect for future use in ruminants. The data also indicates that dietary insect inclusion levels should not exceed 30% (DM basis) to achieve an optimal ruminal fermentation profile. Furthermore, it offers comparative insights into the nutritional value of these insects, which warrant further investigation at the in vivo level. Ultimately, the existing understanding of the nutritional utilization potential of these insects by ruminants, particularly concerning macro- and micronutrients, is evaluated and revealed to be significantly constrained.

Wetlands across North America are invaded by an introduced lineage of the common reed Phragmites australis, and sea level rise has exacerbated the spread of this species. P. australis at tidal marsh-forest ecotones has rapidly been expanding into deteriorating forest, colonizing understory environments ahead of native marsh species. Early detection of P. australis at the ecotone will be critical to the management of this invasive species in coming decades. In this study, we develop and validate a new method for early detection of P. australis, using open access airborne LiDAR data that can uniquely penetrate the tree canopy and detect P. australis within the forest understory. The method was designed for areas of sparse to moderate tree cover, such as the forest edge where trees are dying and P. australis is expanding, where understory species mapping was previously impossible with most spectral data. To differentiate P. australis from shrubs and other understory herbaceous plants, we tested the effectiveness of several LiDAR-derived spatial metrics, including Mean distance, Point density, Scatter, Omnivariance, and Eigentropy, as inputs to a Support Vector Machine (SVM) classifier, followed by a smoothing algorithm to avoid occasional obstacles or disturbances. We compare among metrics and single- vs. multiple- metric-based classifications. The resulting best early detection method of P. australis achieved a classification accuracy of 91.48% at the development site, and between 56.16% and 80.65% accuracy at other test sites. This algorithm provides a cost-effective and high accuracy method of detecting understory P. australis using public airborne LiDAR data. Larger-scale application of this method will provide coastal resource managers and policy-makers with distribution maps of P. australis through time in open environments and the forest understory. More generally, this approach provides a framework for mapping understory species and plant functional groups using LiDAR-derived metrics.

Abstract Background Pregnant women faced great challenges and psychological and physiological changes of varying degrees during the omicron epidemic outbreak. It is important to recognize the potential impact of these challenges on the mental health of pregnant women and to provide appropriate resources and support to mitigate their effects. Method By using the convenience sampling approach, a total of 401 pregnant women from two hospitals of different grades in two cities were included in the survey. The cross-sectional survey was conducted by basic characteristics, Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9), Insomnia Severity Index (ISI) and self-made questionnaire. Results Insomnia affected 207 participants (51.6%), depression affected 160 participants (39.9%) and anxiety affected 151 participants (37.7%). Moreover, pregnant women in provincial capital city were more likely to experience anxiety, depression and insomnia than those in county-level city (P 0.05). Conclusion Pregnant women frequently suffer from anxiety disorder, depression and insomnia as a result of the omicron pandemic in China. During this period, the community and medical professionals should provide more psychological counseling, conduct health education and offer virtual prenatal care to pregnant women (particularly in the provincial capital city).

After the occurrence of mine water inrush, choosing the appropriate emergency evacuation path is very important to reduce the casualty and the mine accident level. The traditional Dijkstra algorithm can not be effectively applied to the dynamic environment of mine water inrush. It can only statically plan a single optimal escape path. In view of the limitations of this algorithm, the time equivalent length is introduced to optimize the traditional Dijkstra algorithm to realize the dynamic change of the optimal escape path with time and water level height. Moreover, the optimized Dijkstra algorithm is combined with the K optimal path algorithm to realize the dynamic planning of multiple optimal escape paths. Field application shows that the optimized dynamic D-K algorithm can be effectively applied to mine water inrush with characteristics of randomness, dynamics and complex, which can provide important decision support for affected personnel to choose emergency escape path.

Abstract Several hematologic traits have been suggested to potentially contribute to the formation and rupture of intracranial aneurysms (IA). The purpose of this study is to explore the causal association between hematologic traits and the risk of IA. To explore the causal association between hematologic traits and the risk of IA, we employed two-sample Mendelian randomization (MR) analysis. Two independent summary-level GWAS data were used for preliminary and replicated MR analyses. The inverse variance weighted (IVW) method was employed as the primary method in the MR analyses. The stabilities of the results were further confirmed by a meta-analysis. In the preliminary MR analysis, hematocrit, hemoglobin concentration (p = 0.0047), basophil count (p = 0.0219) had a suggestive inverse causal relationship with the risk of aneurysm-associated subarachnoid hemorrhage (aSAH). The monocyte percentage of white cells (p = 0.00956) was suggestively positively causally correlated with the risk of aSAH. In the replicated MR analysis, only the monocyte percentage of white cells (p = 0.00297) remained consistent with the MR results in the preliminary analysis. The hematocrit, hemoglobin concentration, and basophil count no longer showed significant causal relationship (p > 0.05). Meta-analysis results further confirmed that only the MR result of monocyte percentage of white cells reached significance in the random effect model and fixed effect model. None of the 25 hematologic traits was causally associated with the risk of unruptured intracranial aneurysms (uIA). This study revealed a suggestive positive association between the monocyte percentage of white cells and the risk of aSAH. This finding contributes to a better understanding that monocytes/macrophages could participate in the risk of aSAH.

Multiquanta emission holds significant value for quantum computing and quantum information processing. In this study, we aim to enhance multiphoton bundle emission by introducing two-photon decay into cavity quantum electrodynamics systems. By implementing parity protection induced by two-photon decay in the quantum jump process, we achieve complete suppression of odd photon emissions, resulting in high-purity, high-efficiency 2n-photon bundle emission characterized by photon bunching and bundle antibunching. Our results indicate that this scheme can effectively produce 2n-photon sources. Unlike previous methods that enhanced 2n-photon bundle purity via parity protection during unitary processes which required ultrastrong cavity-atom coupling, this study is the first to focus on parity protection during nonunitary processes to improve emission purity. This innovative approach not only relaxes the ultrastrong coupling condition compared to earlier schemes, but it also opens new research directions for enhancing N-photon bundle emission. Furthermore, this work has the potential to advance the fields of multiphoton physics and parity theory.

Pain and depression comorbidity (PD) among older adults in China is common and significantly affects their physical and mental health. The psychosocial factors may affect people's feelings, understanding and expression of pain and depression, leading to inaccurate assessment of this condition. Educational attainment is thought to be associated with either pain or depression. However, we do not yet know the relationship between educational attainment and PD. Using data from the 2018 China Health and Retirement Longitudinal Study in 2018, we analyzed various variables in 7742 individuals aged 60 years and older. Our results indicate significant differences between the PD and non-PD populations in terms of social, lifestyle, and behavioral factors. We observed a significant decrease in the incidence of PD among older adults with higher levels of education (p

Abstract Background The causal association between gut microbiome and HIV infection remains to be elucidated. We conducted a two-sample mendelian randomization analysis to estimate the causality between gut microbiome and HIV infection. Methods Publicly released genome-wide association studies summary data were collected to perform the mendelian analysis. The GWAS summary data of gut microbiome was retrieved from the MiBioGen consortium, which contains 18 340 samples from 24 cohorts. GWAS summary data of HIV infection was collected from the R5 release of FinnGen consortium, including 357 HIV infected cases and 218 435 controls. The SNPs were selected as instrumental variables according to our selection rules. And SNPs with a F-statistics less than ten were regarded as weak instrumental variables and excluded. Mendelian randomization analysis was conducted by five methods, including inverse variance weighted (IVW), MR-Egger, weighted median, weighted mode, and simple mode. The Cochran’s Q test and MR-Egger intercept test were performed to identify heterogeneity and pleiotropy. Leave-one-out analysis were used to test the sensitivity of the results. Results Fifteen gut microbiota taxa showed causal effects on HIV infection according to the MR methods. Four taxa were observed to increase the risk of HIV infection, including Ruminococcaceae (OR: 2.468[1.043, 5.842], P: 0.039), Ruminococcaceae UCG005 (OR: 2.051[1.048, 4.011], P: 0.036), Subdoligranulum (OR: 3.957[1.762, 8.887], P < 0.001) and Victivallis (OR: 1.605[1.012, 2.547], P=0.044). Erysipelotrichaceae was protective factor of HIV infection (OR: 0.278[0.106, 0.731], P < 0.001) and Methanobrevibacter was also found to be associated with reduced risk of HIV infection (OR: 0.509[0.265, 0.980], P=0.043). Horizontal pleiotropy was found for Fusicatenibacter (P

China has experienced a rapid urbanization over the past three decades, resulting in a prominent “urban core-suburban-rural” (USR) triad structure of human settlements. The USR disparities, which are related to the spatial variations of human activity intensity, have significant impacts on the spatiotemporal variations in various environmental issues such as carbon dioxide (CO2) emissions, carbon storage, water quality, etc. However, there is a lack of national-level, long-term USR dataset compared to the large number of “Urban-Rural” dual-structure datasets. In this study, an annual USR dataset from 1992 to 2021 in China is delineated by using the nighttime light data, which is the first full coverage, long-term USR dataset of China. The consistency with other remote sensing products (global urban boundaries) and socio-economic data (demographic and point of interest data) demonstrates that the USR dataset is reliable for characterizing the spatial extents of human settlements with distinct socio-economic activity intensities. The USR maps have shown that the Chinese urban core area increased 9-fold from 16,500 km2 in 1992 to 165,000 km2 in 2021. The application of USR data in Fossil Fuel Combustion CO2 (ffco2) emissions indicates that ffco2 emissions in urban core, suburban, and rural area increased 1.34, 0.36, and 0.17 billion of tons from 2000 to 2019 in China, respectively. The dataset can be used for other environmental research issues in China, which has not been possible before because of the lack of the long-term USR triad structure of human settlements.

Abstract Two-dimensional (2D) semiconductors hold great promises for ultra-scaled transistors. In particular, the gate length of MoS2 transistor has been scaled to 1 nm and 0.3 nm using single wall carbon nanotube and graphene, respectively. However, simultaneously scaling the channel length of these short-gate transistor is still challenging, and could be largely attributed to the processing difficulties to precisely align source-drain contact with gate electrode. Here, we report a self-alignment process for realizing ultra-scaled 2D transistors. By mechanically folding a graphene/BN/MoS2 heterostructure, source-drain metals could be precisely aligned around the folded edge, and the channel length is only dictated by heterostructure thickness. Together, we could realize sub-1 nm gate length and sub-50 nm channel length for vertical MoS2 transistor simultaneously. The self-aligned device exhibits on-off ratio over 105 and on-state current of 250 μA/μm at 4 V bias, which is over 40 times higher compared to control sample without self-alignment process.

The hybrid switch (HyS), composed of Si insulated gate bipolar transistors (IGBTs) and SiC metal-oxide-semiconductor field-effect transistors (MOSFETs) in parallel, offers comparable overall performance to SiC at a significantly lower cost. However, in practical applications, HyS often encounters severe thermal stress imbalances, posing challenges for reliable operation and emphasizing the crucial role of accurately estimating the thermal characteristics of the HyS to enable effective thermal monitoring. In this paper, we first present a novel coupling thermal parameters extraction method of Si/SiC hybrid switch based on a thermal network zoning equivalent strategy. By partitioning the thermal network, we reduce the order of the nodal temperature expression, allowing for the construction of a lower-order thermal model. Subsequently, we establish a constraint relationship between the time constants of the case temperature cooling curve and the thermal parameters, enabling the estimation of RC parameters. Unlike traditional solutions, our method simplifies the parameter identification process and facilitates precise thermal monitoring of the HyS. Experimental results confirm the accuracy and effectiveness of our proposed approach. This research contributes to enhancing the understanding and optimization of thermal behavior in Si/SiC hybrid switch for improved performance and reliability in practical applications.

A reduction in adult neurogenesis is associated with behavioral abnormalities in patients with Alzheimer’s disease. Consequently, enhancing adult neurogenesis represents a promising therapeutic approach for mitigating disease symptoms and progression. Nonetheless, non-pharmacological interventions aimed at inducing adult neurogenesis are currently limited. Although individual non-pharmacological interventions, such as aerobic exercise, acousto-optic stimulation, and olfactory stimulation, have shown limited capacity to improve neurogenesis and cognitive function in patients with Alzheimer’s disease, the therapeutic effect of a strategy that combines these interventions has not been fully explored. In this study, we observed an age-dependent decrease in adult neurogenesis and a concurrent increase in amyloid-beta accumulation in the hippocampus of amyloid precursor protein/presenilin 1 mice aged 2–8 months. Amyloid deposition became evident at 4 months, while neurogenesis declined by 6 months, further deteriorating as the disease progressed. However, following a 4-week multifactor stimulation protocol, which encompassed treadmill running (46 min/d, 10 m/min, 6 days per week), 40 Hz acousto-optic stimulation (1 hour/day, 6 days/week), and olfactory stimulation (1 hour/day, 6 days/week), we found a significant increase in the number of newborn cells (5′-bromo-2′-deoxyuridine–positive cells), immature neurons (doublecortin-positive cells), newborn immature neurons (5′-bromo-2′-deoxyuridine-positive/doublecortin-positive cells), and newborn astrocytes (5′-bromo-2′-deoxyuridine-positive/glial fibrillary acidic protein–positive cells). Additionally, the amyloid-beta load in the hippocampus decreased. These findings suggest that multifactor stimulation can enhance adult hippocampal neurogenesis and mitigate amyloid-beta neuropathology in amyloid precursor protein/presenilin 1 mice. Furthermore, cognitive abilities were improved, and depressive symptoms were alleviated in amyloid precursor protein/presenilin 1 mice following multifactor stimulation, as evidenced by Morris water maze, novel object recognition, forced swimming test, and tail suspension test results. Notably, the efficacy of multifactor stimulation in consolidating immature neurons persisted for at least 2 weeks after treatment cessation. At the molecular level, multifactor stimulation upregulated the expression of neuron-related proteins (NeuN, doublecortin, postsynaptic density protein-95, and synaptophysin), anti-apoptosis–related proteins (Bcl-2 and PARP), and an autophagy-associated protein (LC3B), while decreasing the expression of apoptosis-related proteins (BAX and caspase-9), in the hippocampus of amyloid precursor protein/presenilin 1 mice. These observations might be attributable to both the brain-derived neurotrophic factor-mediated signaling pathway and antioxidant pathways. Furthermore, serum metabolomics analysis indicated that multifactor stimulation regulated differentially expressed metabolites associated with cell apoptosis, oxidative damage, and cognition. Collectively, these findings suggest that multifactor stimulation is a novel non-invasive approach for the prevention and treatment of Alzheimer’s disease.

Based on photoacoustic spectroscopy and finite element simulation technology, a simulation model of sound field excitation in a cylindrical resonant photoacoustic cell was established. The finite element simulation method was used to analyze the acoustic mode and sound pressure distribution of the cavity structure of the photoacoustic cell. The effects of the geometric parameters of the resonator and the buffer cavity on the performance of the photoacoustic cell were compared. The frequency response characteristics of the photoacoustic cell and the effects of the air intake and the air outlet were studied. Based on the simulation results, a cylindrical resonant photoacoustic cell was designed, and a photoacoustic sensor for NO2 detection was built. NO2 with a volume fraction of 10−5 was taken as the sample gas through frequency scanning to obtain the frequency response curve of the system. The resonant frequency is 1730 Hz, and the cell constant is about 542.3 (Pa*cm)/W. The quality factor is 10.05. By linear fitting the calibration curve of the sensor, the fitting slope is 0.012 µV/ppb, and R2 is 0.998. Atmospheric NO2 detection was carried out for two consecutive weeks, whose findings are in good agreement with the data released by a Huainan environmental monitoring site. The experimental results show that the system can detect NO2 in the atmosphere with high sensitivity.

Multi-station radar can provide better performance against deception jamming, but the harsh detection requirements and risk of network destruction undermine the practicability of the multi-station radar. Therefore, it is necessary to further explore the anti-deception jamming performance of a single-station radar. This paper introduces a novel method, based on parameter estimation with a virtual multi-station system, to discriminate range deceptive jamming. The system consists of a single-station radar assisted by the reconfigurable intelligent surfaces (RIS). A unified parameter estimation model for true and false targets is established, and the convex optimization method is applied to estimate the target location and deception range. The Cramer–Rao lower bound (CRLB) of the target localization and the measured deception range is then derived. By using the measured deception range and its CRLB, an optimal discrimination algorithm in accordance with the Neyman–Pearson lemma is designed. Simulation results demonstrate the feasibility of the proposed method and analyze the effects of factors such as signal-to-noise ratio (SNR), deception range, jammer location, and the RISs station arrangement on the discrimination performance.

IntroductionDairy industry growth faces challenges in China due to inadequate forage, leading to high-concentrate diets and potential rumen issues. Buffering agents, like sodium bicarbonate, play a crucial role in stabilizing rumen pH. Alkaline Mineral Complex (AMC), a liquid additive with a pH of 14, shows promise in supporting dairy cow health and mitigating heat stress through ionization.MethodsThis experiment was aimed to study the effect of adding AMC to total mixed ration (TMR) on in vitro ruminal fermentation and bacterial composition. AMCat 1, 2, 4, and 8 mL/kg was added to the substrate (0.5 g TMR). Nutrient digestibility was measured after 48 h fermentation, and fermentation parameters and microbial composition were measured after 48 h fermentation.Results and discussionThe results of the experiment indicated that: The different concentrations of AMC showed a significant impact on time taken for gas production to reach 1/2 of the total gas production (HT) parameters (p < 0.05). Linear pH increase occurs at 6 and 24 h with rising AMC concentration (p < 0.05), showing a quadratic trend at 12 h (p < 0.05). The optimal buffering effect on rumen acid-base balance was observed at a 2 mL/kg concentration of AMC. Microbial diversity analysis indicated that there was no significant change in α-diversity with different AMC concentrations (p > 0.05). The microbial level demonstrated no significant difference in species diversity of rumen fluid bacteria among the various AMC concentration treatment groups compared to the control group, further supporting that the advantage of adding AMC in stabilizing the rumen environment without altering the structure of the rumen microbiota. Besides, the addition of AMC significantly increased the concentrations of acetate, propionate, total fatty acids (TVFA), and NH3-N, suggesting that AMC contributed to enhancing the energy and nitrogen utilization efficiency in ruminants. Based on the above detection indicators, we recommend that the most favorable concentration is 2 mL/kg.

Ulcerative colitis (UC) is a recurrent inflammatory disease related to gut microbiota disorder. Metabolites and their sensors play an important role in the communication between gut microbes and their host. Our previous study revealed that G protein‐coupled receptor 35 (GPR35) is a key guardian of kynurenic acid (KA) and a core element of the defense responses against gut damage. However, the mechanism remains unknown. In this study, a DSS‐induced rat colitis model was established and 16S rRNA sequencing was applied to explore the influence of GPR35‐mediated KA sensing on gut microbiota homeostasis. Our results demonstrated that GPR35‐mediated KA sensing is a necessary component in maintaining gut barrier integrity against DSS‐induced damage. Furthermore, we provide compelling evidence suggesting that GPR35‐mediated KA sensing plays a crucial role in maintaining gut microbiota homeostasis, which contributes to alleviation of DSS‐induced colitis. In addition, five classes (Actinobacteria, Beta‐/Gamma‐proteobacteria, Erysipelotrichi, and Coriobacteriia) and six genera (Corynebacterium, Allobaculum, Parabacteroides, Sutterella, Shigella, and Xenorhabdus) were identified as the marked bacterial taxa that characterized the progression and outcome of colitis and are regulated by GPR35‐mediated KA sensing. Our findings highlight that GPR35‐mediated KA sensing is an essential defense mechanism against disorder of gut microbiota in UC. The results provide insights into the key role of specific metabolites and their monitor in maintaining gut homeostasis.

Abstract Background Identifying reliable biomarkers could effectively predict esophagus carcinoma (EC) patients with poor prognosis. In this work, we constructed an immune-related gene pairs (IRGP) signature to evaluate the prognosis of EC. Results The IRGP signature was trained by the TCGA cohort and validated by three GEO datasets, respectively. Cox regression model together with LASSO was applied to construct the overall survival (OS) associated IRGP. 21 IRGPs consisting of 38 immune-related genes were included in our signature, according to which patients were stratified into high- and low-risk groups. The results of Kaplan-Meier survival analyses indicated that high-risk EC patients had worse OS than low-risk group in the training set, meta-validation set and all independent validation datasets. After adjustment in multivariate Cox analyses, our signature continued to be an independent prognostic factor of EC and the signature-based nomogram could effectively predict the prognosis of EC sufferers. Besides, Gene Ontology analysis revealed this signature is related to immunity. ‘CIBERSORT’ analysis revealed the infiltration levels of plasma cells and activated CD4 memory T cells in two risk groups were significantly different. Ultimately, we validated the expression levels of six selected genes from IRGP index in KYSE-150 and KYSE-450. Conclusions This IRGP signature could be applied to select EC patients with high mortality risk, thereby improving prospects for the treatment of EC.

Purpose: Although the role of SARS-CoV-2-specfic immune cells has been revealed, a comprehensive understanding of immune patterns remains unknown. Methods: In this work, unsupervised consensus clustering analysis was used to classify 240 coronavirus disease 2019 (COVID-19) patients into different immune subtypes. Next, we performed differentially expressed analysis between different immune subtypes. Functional enrichment and pathway analyses were employed to reveal the biological significance of these differentially expressed genes (DEGs). Besides, we compared feature score of some DEGs between whole blood and lung tissues. Then, we utilized the “GSVA” algorithm to construct an immune cell infiltrating (ICI) tool based on the categories of these DEGs. Finally, we developed a nomogram associated with severity of COVID-19. Results: As a result, we identified two immune subtypes, and 238 DEGs which mainly participated in some immune-related functions and the COVID-19 pathway. Most importantly, the 238 DEGs could reflect the characterization of immune patterns in lung tissues. ICI scores were markedly negative associated with immune scores. It was worth noting that ICI score was a strong indicator for severity of COVID-19 and could accurately predict the severity of COVID-19. Conclusion: Our findings could provide more valuable strategies for the management of COVID-19.