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Twin curved tunnels are often encountered in shield tunnelling, where significant complexities in densely exploited underground space are observed. In this study, the ground settlement and tunnel deformation due to twin-curved shield tunnelling in soft ground were investigated using numerical simulation and field monitoring. Different curvature radii of twin curved tunnels and subsequent effects of tunnel construction were considered to reveal the tunnelling effect on ground surface settlement and tunnel deformation. The results show that the settlement trough yields one offset towards inside of curved shield tunnelling. The location of settlement trough and maximum settlement were affected by curvature radius but except for the shape and width of settlement trough. Adjacent parallel twin-curved shield tunnelling could increase the offset of existing settlement trough and maximum settlement. Then, an empirical prediction of surface settlement trough due to twin-curved shield tunnelling with same tunnel diameters in soft clay was proposed, which was applicable to curvature radius less than 800 m. Finally, a minimum radius of 600 m of curvature tunnel was proposed in terms of allowable convergence deformation of tunnel. The result could provide guidance on safety evaluation for twin curved shield tunnelling construction.

Objective To construct applicable models suitable for predicting the risk of suicidal behavior among individuals with depression, particularly on the progression from no history of suicidal behavior to suicide attempts, as well as from suicidal ideation to suicide attempts. Methods Based on a prospective cohort from the UK Biobank, a total of 55,139 individuals aged 50 and above with depression were enrolled in the study, among whom 29,528 exhibited suicidal behavior. Specifically, they were divided into control (25,611), suicidal ideation (24,361), and suicide attempt (5167) groups. Least absolute shrinkage and selection operator (LASSO) regression was used to identify a subset of important features for distinguishing suicidal ideation and suicide attempts. We used the Gradient Boosting Decision Tree (GBDT) algorithm with stratified 10-fold cross-validation and grid-search to construct the prediction models for suicidal ideation or suicide attempts. To address the dataset imbalance in classifying suicide attempts, we used random under-sampling. The SHapley Additive exPlanations (SHAP) were used to estimate the important variables in the GBDT model. Results Significant differences in sociodemographic, economic, lifestyle, and psychological factors were observed across the three groups. Each classifier optimally utilized 8–11 features. Overall, the algorithms predicting suicide attempts demonstrated slightly higher performance than those predicting suicidal ideation. The GBDT classifier achieved the highest accuracy, with AUROC scores of 0.914 for suicide attempts and 0.803 for suicidal ideation. Distinctive predictive factors were identified for each group: while depression's inherent characteristics crucially distinguished the suicidal ideation group from controls, some key predictors, including the age of depression onset and childhood trauma events, were identified for suicide attempts. Conclusions We established applicable machine learning-based models for predicting suicidal behavior, particularly suicide attempts, in individuals with depression, and clarified the differences in predictors between suicidal ideation and suicide attempts.

Abstract Silk nanofibrils (SNFs), the fundamental building blocks of silk fibers, endow them with exceptional properties. However, the intricate mechanism governing SNF assembly, a process involving both protein conformational transitions and protein molecule conjunctions, remains elusive. This lack of understanding has hindered the development of artificial silk spinning techniques. In this study, we address this challenge by employing a graphene plasmonic infrared sensor in conjunction with multi-scale molecular dynamics (MD). This unique approach allows us to probe the secondary structure of nanoscale assembly intermediates (0.8–6.2 nm) and their morphological evolution. It also provides insights into the dynamics of silk fibroin (SF) over extended molecular timeframes. Our novel findings reveal that amorphous SFs undergo a conformational transition towards β-sheet-rich oligomers on graphene. These oligomers then connect to evolve into SNFs. These insights provide a comprehensive picture of SNF assembly, paving the way for advancements in biomimetic silk spinning.

Power grids, due to their lack of network redundancy and structural interdependence, are particularly vulnerable to cascading failures, a phenomenon where a few failed nodes—having their loads exceeding their capacities—can trigger a widespread collapse of all nodes. Here, we extend the cascading failure (Motter-Lai) model to a more realistic perspective, where each node’s load capacity is determined to be nonlinearly correlated with the node’s centrality. Our analysis encompasses a range of synthetic networks featuring small-world or scale-free properties, as well as real-world network configurations like the IEEE bus systems and the US power grid. We find that fine-tuning this nonlinear relationship can significantly enhance a network’s robustness against cascading failures when the network nodes are under attack. Additionally, the selection of initial nodes and the attack strategies also impact overall network robustness. Our findings offer valuable insights for improving the safety and resilience of power grids, bringing us closer to understanding cascading failures in a more realistic context.

Background Numerous studies have linked the inflammatory pathway in psoriasis and metabolic disease, while no specific marker defined it. It is worth exploring the association of β2-microglobulin (β2M) in psoriasis severity and comorbidities.Objectives To investigate the correlation between blood β2M level and psoriasis severity, to explore the inflammatory factors influencing the occurrence of psoriasis comorbidities such as arthritis, diabetes, and hypertension.Methods Ninety-seven psoriasis patients were analyzed in the cohort retrospective study during 12 weeks.Results Significantly higher levels of blood β2M and ESR were observed in the group that patients’ PASI ≥10 than in the group that PASI

Aim Comparing the anxiety and depression severity and their impact on subsequent birth outcomes in pregnant women before and during Omicron wave in Shanghai in 2022.Methods The depression-anxiety symptoms networks were compared between the pregnant women during the outbreak period (outbreak group; n = 783) and a matched control group of pregnant women before the outbreak (pre-outbreak group; n = 783). The impact of baseline mental state on follow-up pregnancy and neonatal outcomes was also explored by logistic regression.Findings Levels of depression and anxiety between the two groups were not significant different. Network analysis showed that central symptom "trouble relaxing" and bridge symptom "depressed mood" shared by both groups. Different symptom associations in different periods of the pandemic. Total scores and sub-symptom scores of prenatal depressive and anxious severities increased the odds ratios of maternal and neonatal syndromes. The influence of mental state on gestational and neonatal outcomes differed across different pandemic periods.Conclusion The Omicron wave did not have a significant negative impact on the depressive and anxious mood in pregnant women. Targeting central and bridge symptoms intervention may be effective in reducing their adverse effects on co-occurring of anxious and depressive mood and birth outcomes.

ABSTRACTSystemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p

Severe left ventricular outflow tract obstruction (LVOTO) of hypertrophic cardiomyopathy is an acutely life-threatening, must-not miss, cardiology emergency that infrequently presents to the emergency department (ED). Patients with this condition usually manifest chest pain, syncope, cardiogenic shock, and severe ischemia. LVOTO is easy misdiagnosed as acute coronary syndrome. In our patient, the ECG showed a significant ST-segment depression and a 0/0 mmHg blood pressure when the peak left ventricular outflow tract gradient was abruptly increased by provocable activities. However, the patient had normal coronaries on cardiac catheterization, and, upon being immediately treated with intravenous esmolol, his symptoms were relieved and blood pressure was normal after 30 minutes. This case highlights, not only that early and exact diagnosis of LVOTO is crucial, but also the importance of the therapeutic strategies used.

Background The associations between cardiovascular disease (CVD) and multiple psychiatric disorders and suicide attempt, and whether different genetic susceptibilities affect such links, have not been investigated clearly. Methods and Results Based on the UK Biobank, we conducted a matched cohort study involving 63 923 patients who were first hospitalized with a CVD diagnosis between 1997 and 2020, and their 127 845 matched unexposed individuals. Cox models were used to examine the subsequent risk of psychiatric disorders and suicide attempt (ie, anxiety, depression, stress‐related disorder, substance misuse, psychotic disorder, and suicide behaviors) following CVD. We further performed stratified analyses by polygenic risk score for each studied psychiatric condition to detect the possible effects of genetic susceptibility on the observed associations. We found an increased risk of any psychiatric disorders and suicide attempt among CVD patients, compared with matched unexposed individuals, particularly within 1 year following the CVD (fully adjusted hazard ratio [HR] within 1 year, 1.83 [95% CI, 1.58–2.12]; HR after 1 year, 1.24 [95% CI, 1.16–1.32]). By subtype, the risk elevations existed for any psychiatric disorders and suicide attempt following most categories of CVDs. Analyses stratified by polygenic risk score revealed little impact of genetic predisposition to studied psychiatric conditions on these observed links. Conclusions Patients hospitalized for CVD were at increased subsequent risk of multiple types of psychiatric disorders and suicide attempt, especially in the first year after hospitalization, irrespective of their genetic susceptibilities to studied psychiatric conditions, and these findings underscore the necessity of developing timely psychological interventions for this vulnerable population.

Introduction: Sodium zirconium cyclosilicate (SZC) is a nonabsorbed cation-exchanger approved in China for the treatment of hyperkalemia [HK; serum potassium (sK+) levels >5.0 mmol/L]. This is the first real-world study aimed to assess the effectiveness, safety, and treatment patterns of SZC in Chinese patients with HK. Here we present the results of the first interim analysis.Methods: This multicenter, prospective, cohort study included patients aged ≥18 years with documented HK within 1-year before study enrollment day. These patients were followed up for 6 months from the enrollment day after initiating SZC treatment. The treatment was categorized into correction phase (FAS-P1) and maintenance phase (FAS-P2 new and ongoing users). Subgroup analysis was performed in patients on hemodialysis (FAS-H). The primary objective was evaluation of safety profile of SZC; secondary objectives included assessment of treatment patterns of SZC and its effectiveness.Results: Of 421 screened patients, 193, 354, and 162 patients were enrolled in the FAS-P1, FAS-P2, and FAS-H groups, respectively. sK+ levels were reduced significantly from 5.9 mmol/L to 5.0 mmol/L after the correction phase. For the maintenance phase, the mean sK+ levels were maintained at 5.2 mmol/L and 5.0 mmol/L in the FAS-P2 new and ongoing user, respectively, and 5.3 mmol/L in the FAS-H subgroup. A considerable proportion of patients showed normokalemia after 48 h of SZC treatment (FAS-P1:51.3%) which was maintained up to 6 months in the maintenance phase (FAS-P2:44%). SZC was well-tolerated.Conclusion: SZC was effective and safe for the treatment of HK in real-world clinical practice in China.

IntroductionSymptoms during the onset of major depressive disorder [MDD] and bipolar disorder type II [BD-II] are similar. The difference of hippocampus subregion could be a biological marker to distinguish MDD from BD-II.MethodsWe recruited 61 drug-naïve patients with a first-episode MDD and BD-II episode and 30 healthy controls (HC) to participate in a magnetic resonance imaging [MRI] study. We built a general linear model (one-way analysis of covariance) with 22 hippocampal subfields and two total hippocampal volumes as dependent variables, and the diagnosis of MDD, BD-II, and HC as independent variables. We performed pair-wise comparisons of hippocampal subfield volumes between MDD and HC, BD-II and MDD, BD-II and HC with post hoc for primary analysis.ResultsWe identified three regions that differed significantly in size between patients and controls. The left hippocampal fissure, the hippocampal–amygdaloid transition area (HATA), and the right subiculum body were all significantly larger in patients with MDD compared with the HC. In the onset of first-episode of MDD, the hippocampal volume increased significantly, especially on the left side comparing to HC. However, we found differences between MDD and BD-II were not statistically significant. The volume of the left HATA and right subiculum body in BD-II was larger.ConclusionsThe sample size of this study is relatively small, as it is a cross-sectional comparative study. In both MDD and BD-II groups, the volume of more left subregions appeared to increase. The left subregions were severely injured in the development of depressive disorder.

Abstract Climate change is altering precipitation regimes that amplify hydrological extremes and increase vulnerability to schistosomiasis, a water‐related parasitic disease with hundreds of millions at risk globally. Explicit recognition of the elements of hydrological variability and linkages with extreme precipitation is necessary to combat the spread of schistosomiasis. We call for the use of a vulnerability framework to account holistically for the dynamic interplay among environmental and human factors that influence susceptibility to schistosomiasis infection across spatial scales.

3,3′,4,4′,5-Pentachlorobiphenyl (PCB126) is the most toxic congener of dioxin-like polychlorinated biphenyls (DL PCBs), while nanoplastics (NPs) have recently emerged as significant marine pollutants, both posing threats to aquatic organisms and human health. They coexist in the environment, but their comprehensive toxicological effects remain unclear. In this study, zebrafish embryos were simultaneously exposed to PCB126 and 80-nanometer nanoplastyrene (NPS). Researchers utilized fluorescence microscopy, qPCR, histopathological examination, and transcriptomic sequencing to investigate the developmental toxicity of different concentrations of PCB126 and NPS individually or in combination on zebrafish embryos and larvae. Results indicate that the chorion significantly impedes the accumulation of NPS (p < 0.05). It is noteworthy that this barrier effect diminishes upon simultaneous exposure to PCB126. In this experiment, the semi-lethal concentration of PCB126 for larvae was determined to be 6.33 μg/L. Exposure to PCB126 induces various deformities, primarily mediated through the aryl hydrocarbon receptor (AHR). Similarly, exposure to NPS also activates AHR, leading to developmental impairments. Furthermore, transcriptomic sequencing revealed similar effects of PCB126 and NPS on the gene expression trends in zebrafish larvae, but combined exposure to both exacerbates the risk of cancer and induces more severe cardiac toxicity. At this level, co-exposure to PCB126 and NPS adversely affects the development of zebrafish larvae. This study contributes to a deeper understanding of the in vivo accumulation of DL polychlorinated biphenyls and microplastics in actual aquatic environments and their impact on fish development.

Abstract Background Adverse childhood experiences (ACEs), including childhood maltreatment, have been linked with increased risk of diabetes and obesity during adulthood. A comprehensive assessment on the associations between childhood maltreatment and all major endocrine diseases, as well as the relative importance of different proposed mechanistic pathways on these associations, is currently lacking. Methods Based on the UK Biobank, we constructed a cohort including 151,659 participants with self-reported data on childhood maltreatment who were 30 years of age or older on/after January 1, 1985. All participants were followed from the index date (i.e., January 1, 1985, or their 30th birthday, whichever came later) until the first diagnosis of any or specific (12 individual diagnoses and 9 subtypes) endocrine diseases, death, or the end of follow-up (December 31, 2019), whichever occurred first. We used Cox models to examine the association of childhood maltreatment, treated as continuous (i.e., the cumulative number of experienced childhood maltreatment), ordinal (i.e., 0, 1 and ≥ 2), or binary (

Background: We sought to establish a prospective hospital-based cohort, featuring detailed multidimensional data of trauma patients with active follow-ups, which can be a reliable data source for all studies focusing on the effects or underlying mechanistic pathways of environmental and biological factors on multiple interested trauma-related outcomes, particularly the incidence and trajectory of trauma-related psychopathology, in a Chinese population. Methods: The China Severe Trauma Cohort (CSTC) enrolled all traumatized individuals aged 12 to 80 years admitted to the Trauma Center of West China Hospital between March 1st, 2020 and July 8th, 2022. The bio-sample and detailed questionnaire data were collected at recruitment, and phone/internet follow-ups were scheduled at 1, 3, 6, and 12 months after the baseline. Long-term health outcomes are planned to be obtained from administrative databases through data linkage. Results: A total of 2,500 trauma patients were enrolled (response rate = 87.1%) with an average age of 46.01 years, and most of the participants were males (62.6%). The proportions of participants with blood and fecal sample collected at baseline were 93.8% and 66.3%, respectively. As of August 31st, 2022, the follow-up rate was 90.0%, 77.0%, 76.5%, and 89.0% for 1-, 3-, 6-, and 12-month follow-ups, respectively. Fall/wrench (47.6%) and traffic accident (26.2%) were the top causes of current trauma. The most common psychopathology at recruitment was sleep disturbance (39.4%), followed by depression (22.6%), anxiety (18.2%), and acute stress reaction (7.8%), all of which showed recovering trajectories during the follow-up period, particularly the first 3 months after baseline. Conclusion: CSTC provides a platform with multidimensional data to study both short-term and long-term trauma-related health consequences, prompting early identification and intervention for individuals with high risk of health decline after trauma exposures.

Aspheric surfaces are widely used in advanced optical instruments. Measuring the aspheric surface parameters (ASPs) with high accuracy is vital for manufacturing and aligning optical aspheric surfaces. This paper provides a review of various techniques for measuring ASPs and discusses the advantages/disadvantages of these approaches. The aim of this review is to contribute to advancements in the fabrication and testing of aspheric optical elements and their practical applications in diverse fields.

Biomass-derived carbon materials (BDCs) are highly regarded for their renewability, environmental friendliness, and broad potential for application. A significant advantage of these materials lies in the high degree of customization of their physical and chemical properties, especially in terms of pore structure. Pore engineering is a key strategy to enhance the performance of BDCs in critical areas, such as energy storage, catalysis, and environmental remediation. This review focuses on pore engineering, exploring the definition, classification, and adjustment techniques of pore structures, as well as how these factors affect the application performance of BDCs in energy, catalysis, and environmental remediation. Our aim is to provide a solid theoretical foundation and practical guidance for the pore engineering of BDCs to facilitate the rapid transition of these materials from the laboratory to industrial applications.

The Bailing Capsule is a commonly used traditional Chinese medicine for the treatment of chronic kidney disease (CKD). However, its therapeutic effects and pharmacological mechanisms have not been fully explored. In this study, we integrated meta-analysis and network pharmacology to provide scientific evidence for the efficacy and pharmacological mechanism of Bailing Capsule in treating CKD. We conducted searches for randomized controlled studies matching the topic in PubMed, the Cochrane Library, Embase, Web of Science, and the Wanfang Database, and screened them according to predefined inclusion and exclusion criteria. Dates from the included studies were extracted for meta-analysis, including renal function indicators, such as 24-h urinary protein (24UP), blood urea nitrogen (BUN), and serum creatinine (Scr), as well as inflammatory indicators like high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Network pharmacology was employed to extract biological information, including active drug ingredients and potential targets of the drugs and diseases, for network construction and gene enrichment. Our findings indicated that 24UP, BUN, and Scr in the treatment group containing Bailing Capsule were lower than those in the control group. In terms of inflammatory indicators, hs-CRP, IL-6, and TNF-α, the treatment group containing Bailing Capsule also exhibited lower levels than the control group. Based on network pharmacology analysis, we identified 190 common targets of Bailing Capsule and CKD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that the pharmacological mechanism of Bailing Capsule might be related to immune response, inflammatory response, vascular endothelial damage, cell proliferation, and fibrosis. This demonstrates that Bailing Capsule can exert therapeutic effects through multiple targets and pathways, providing a theoretical basis for its use.

Abstract Cold surge events in the South China Sea (over 110–117.5° E longitude at 15° N latitude) from 1979 to 2019 are divided into four types depending on their correlation with North Pacific extratropical cyclones (ECs). Climatologic relationships between the two phenomena reveal that 92% (39%) of all cold surges are accompanied by ECs (explosive extratropical cyclones, abbreviated as EC‐E), while 31% of ECs are accompanied by cold surges. The occurrence and development of ECs favour eruptions of cold air from higher latitudes, which in turn produce conditions conducive to cold surges. In the North Pacific, ECs travel in a northeastward direction, ultimately contributing to the Aleutian low. Meanwhile, the westerly jet is observed to strengthen following cold surge events. Both actions drive further EC activity, which in turn facilitates subsequent cold surges. Therefore, when ECs occur before and after cold surges, the cold surge event itself tends to be relatively strong and long lived. The transmission of energy by ECs is a primary link between the high and middle latitudes and contributes to the impact of cold surges on low latitudes. This study also explores the respective influences of the Siberia High and Aleutian Low on cold surges. The majority of cold surges that do not involve ECs occur in the context of the weaker Siberia High and Aleutian Low. Cold surges accompanied with ECs can be even stronger and longer lasting when the Siberia High and Aleutian Low strengthen.

The modern building sector faces the challenge of meeting energy demands while minimizing environmental impacts and promoting energy efficiency. This research paper presents a comprehensive approach to optimizing building energy systems using a modified metaheuristic, the Developed Coyote Algorithm (DCO). The increasing importance of storage equipment in energy organizations, driven by changes in peak-load demand and the growing adoption of renewable energy sources, necessitates efficient storage solutions. Battery Energy Storage (BES) and Thermal Energy Storage (TES) are commonly used to store excess energy generated from renewable sources and supply it during peak demand. By applying the DCO algorithm, the operational plans of energy systems comprising BES, air-source heat pumps, and TES can be efficiently optimized with minimal computational requirements. The proposed method aims to enhance the productivity and sustainability of energy systems while providing valuable insights for policymakers and stakeholders involved in renewable energy development. The discharge of batteries and thermal energy storage occurs during low electricity prices, with charging power fluctuating between 100 and 150 kW. GWO and IWWO results show that charging is done at night with 150 kW, with a reduced amount used during other times. Thermal energy storage can store energy from 500 to 800 kW during night time, while DCO generates 700–900 kW. The results of this research contribute to the effective management of batteries, heat sources, and thermal storage in building energy systems, further advancing the utilization of renewable energy resources.

Abstract Background To improve early diagnosis and chemotherapy efficacy monitoring in primary central nervous system lymphoma (PCNSL), cerebrospinal fluid (CSF) exosomal microRNA (miRNA) studies were performed. Method Small RNA sequencing was performed to identify candidate exosomal miRNAs as CSF biopsy biomarkers from two patients with de novo PCNSL and two patients in remission after chemotherapy. miR-200c and miR-141 expression in CSF exosomes was further validated using relative quantitative real-time polymerase chain reaction in patients with PCNSL (n = 20), patients with other neurological diseases (n = 10), and normal subjects (n = 10). Receiver operating characteristic (ROC) curve analyses of miR-200c and miR-141 in the diagnosis and prediction of chemotherapy efficacy in PCNSL were performed in patients treated with methotrexate. Additionally, bioinformatics tools were utilized to predict the potential targets of miR-200c and miR-141. Results Exosomal miR-200c and miR-141 levels in CSF from patients with PCNSL were significantly lower than those in control subjects. Importantly, miR-200c and miR-141 were upregulated in patients with PCNSL after chemotherapy (P = 0.002). There was a significant correlation between the levels of miR-141 and IL-10 in CSF (P = 0.04). The combination of miR-200c and miR-141 yielded an area under the ROC curve of 0.761 for distinguishing PCNSL with sensitivity and specificity of 60.0% and 96.7%, respectively. The potential target genes of miR-200c and miR-141 in PCNSL included ATP1B3, DYNC1H1, MATR3, NUCKS1, ZNF638, NUDT4, RCN2, GNPDA1, ZBTB38, and DOLK. Conclusion Collectively, miR-200c and miR-141 are likely to be upregulated in CSF exosomes after chemotherapy in patients with PCNSL, highlighting their potential as reliable liquid biopsy biomarkers for PCNSL diagnosis and chemotherapy efficacy monitoring.

Abstract Background Immense attention has been given to the outcome of COVID-19 infection. However, comprehensive studies based on large populational cohort with long-term follow-up are still lacking. This study aimed to investigate the risk of various short-term comorbidities (within one month) and long-term sequelae (above one month) after COVID-19 infection. Methods In this large prospective cohort study with 14 months follow-up information based on UK biobank, we included 16,776 COVID-19-positive participants and 58,281 COVID-19-negative participants matched for comparison. The risk of each comorbidity and sequela was evaluated by multivariable logistic regression analysis and presented as hazard ratio (HR) and 95% confidence interval (95% CI). Results COVID-19-positive individuals had a higher risk of 47 types of comorbidities within one month following COVID-19 infection, especially those who were older, male, overweight/obese, ever-smoked, with more pre-existing comorbidities and hospitalized. About 70.37% of COVID-19 patients with comorbidities had more than one co-occurring comorbidities. Additionally, only 6 high-risk sequelae were observed after one month of COVID-19 infection, and the incidence was relatively low (

A macroscopic fundamental diagram (MFD) is an important basis for road network research. It describes the functional relationship between the average flow and average density of the road network. We proposed an MFD estimation method based on the traffic flow condition. Firstly, according to statistical theories, the road network data are divided into three traffic flow conditions (free flow, chaotic and congested) bounded by a 95% confidence interval of the maximum traffic capacity of each intersection in the road network. Then, in each condition, we combined principal component analysis and the Jolliffe B4 method to reduce dimension for extracting critical intersections. Finally, the full-scale dataset of the road network was reconstructed to estimate the road network MFD. Through numerical simulation and empirical research, it is found that the root mean square error and absolute percentage error between estimated MFD and true MFD considering the traffic flow condition are smaller than those without considering the traffic flow condition. The MFD estimation and the division of the traffic states of the road network were completed at the same time. The proposed method effectively saves the time cost of road network research and is highly accurate.

A miniaturized and wideband four-port multiple-input multiple-output (MIMO) antenna pair for Wi-Fi mobile terminals application is proposed. The proposed antenna pair consists of four multi-branch antenna elements arranged orthogonally, with an overall size of 40 × 40 × 3.5 mm3 and each antenna element size of 15.2 × 3.5 mm × 0.8 mm3. The performance of the proposed antenna shows the advantages of a wide frequency band, low mutual coupling, high efficiency, and a compact structure. The wideband characteristics of the antenna elements are achieved through multi-mode resonance. The suppression of coupling is accomplished by strategically positioning the four compact antenna elements to ensure their maximum radiation directions are orthogonal, thus eliminating the need for an additional decoupling structure. In this paper, the proposed antenna is optimized in terms of the parameters then simulated and measured. The simulated results illustrate that an impedance bandwidth of the antenna is about 15% (5.06~5.88 GHz) with S11 < −10 dB, excellent port isolation exceeds 20 dB between all ports, a high radiation efficiency ranges from 51.2% to 89.9%, the maximum gain is 4.5 dBi, and the ECCs are less than 0.04. The measured results show that the −10 dB impedance bandwidth of the antenna is about 13% (5.13~5.80 GHz), the isolation between the antenna elements is better than 21 dB, the radiation efficiency ranges from 51.8% to 92.3%, the maximum gain is 5.3 dBi, and the ECCs are less than 0.05. The proposed four-port MIMO antenna works on the 5G LTE band 46 and Wi-Fi 6E operating bands. As a mobile terminal antenna, the proposed design scheme demonstrates excellent performance and applicability, fulfilling the requirements for 5G mobile terminal applications.

Background: Head and neck squamous cell carcinoma (HNSCC) is a common invasive malignant tumor that lacks powerful predictive or prognostic biomarkers. Ferroptosis and cuproptosis are two new forms of programmed cell death. Our study was aimed at constructing a prognostic model with a combination of cuproptosis and ferroptosis-related genes (CFRGs) for the early clinical detection of HNSCC. Methods: We obtained the information of CFRGs, including the RNASeq data and corresponding clinical data in HNSCC patients from the TCGA and GEO databases. We assessed 28 CFRGs, and analyzed the relationship between those genes and their clinical features and prognosis of HNSCC. The consensus cluster analysis was employed to generate three CFRGclusters. Then, we investigated the association of molecular patterns and prognostic significance in these subtypes. The clinical indicators of the prognosis-related genes were identified and prognostic CFRG_score were constructed. We then built a predictive nomogram with confirmed consistency and reliability by calibration curve analysis. At last, we verified the expression of CFRGs in HNSCC tissues by qRT-PCR and immunohistochemical results. Results: The DEGs were different between the normal and HNSCC tumor tissues and we screened out 28 CFRGs related to the prognosis in HNSCC. Associations between the clinical information and prognosis were found in the molecular subtypes related to prognosis. We utilized enrichment analysis of the differential genes and showed that those DEGs were mostly enriched in the biological processes associated with the pathways of neurodegeneration-multiple diseases, Alzheimer disease, Prion disease, Parkinson disease and Amyotrophic lateral sclerosis. CFRG_score was established to predict the survival of HNSCC patients and found that higher CFRG_score suggested favorable OS for patients, indicating the prediction of better prognosis. Moreover, we created highly reliable nomogram which could predict well for the expected prognosis. In addition, we confirmed that the expression of EGFR, VEGFA, HSPA5, SLC3A2, CAV1 and CD44 were consistent with qRT-PCR and immunohistochemical analysis in HNSCC tissues by qRT-PCR. Conclusions: This prognostic model based on prognostic differential CFRG_score is strongly related to clinical characteristics, prognosis, and therapy in HNSCC patients and could be used as a promising tool which is dedicated to guiding the treatment of HNSCC.

Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a “short-term” causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.

Background: Nausea and vomiting, which cause considerable multifaceted effects, are commonly experience in early pregnancy. Various therapeutic strategies are employed, including both conventional agents and complementary medicine. However, the effectiveness of complementary medicine remains controversial. The objective of this meta-analysis is to evaluate efficacy and safety of acupuncture and moxibustion in pregnant women. Methods: We conducted a comprehensive search using electronic databases such as PubMed, Embase, ISI Web, Medline, Cochrane, clinicaltrial.gov, and several Chinese databases. A total of 21 randomized controlled trials were included in this study for quantitative analysis. Forest plots were utilized to evaluate the efficacy and safety of acupuncture and moxibustion. Egger's test was employed to assess publication bias. Results: The pooled analysis revealed that the acupuncture/moxibustion group was more effective than control group in alleviating nausea and vomiting in early pregnant women (RR: 0.28; 95%CI: 0.21, 0.37). Similar results were observed when comparing the acupuncture group to traditional herbs (RR: 0.08; 95 % CI: 0.01, 0.60), conventional therapy (RR: 0.15; 95 % CI: 0.04, 0.57), and the blank control group (RR: 0.33; 95 % CI: 0.22, 0.51). Moxibustion also exhibited the ability to alleviate nausea and vomiting compared with the blank control group (RR: 0.21; 95 % CI: 0.08, 0.52). As for safety, there were no significant differences in severe adverse events between the acupuncture group and the control group (RR: 0.77; 95%CI: 0.52, 1.14), the blank control group (RR: 0.61; 95%CI: 0.34, 1.10), the sham acupuncture group (RR: 1.05; 95%CI: 0.63, 1.73), or the conventional therapy group (RR: 0.32; 95%CI: 0.06, 1.55). Conclusion: Acupuncture and moxibustion might be effective for the management of nausea and vomiting in early pregnant women. Moreover, acupuncture might be a relatively safe treatment for pregnancy.

ObjectivesTo dissect clinical and biological heterogeneity in clinical states of bipolar disorder (BD), and investigate if neuropsychological symptomatology, comorbidity, vital signs, and blood laboratory indicators are predictors of distinct BD states.MethodsA retrospective BD cohort was established with data extracted from a Chinese hospital’s electronic medical records (EMR) between 2009 and 2018. Subjects were inpatients with a main discharge diagnosis of BD and were assessed for clinical state at hospitalization. We categorized all subjects into manic state, depressive state, and mixed state. Four machine learning classifiers were utilized to classify the subjects. A Shapley additive explanations (SHAP) algorithm was applied to the classifiers to aid in quantifying and visualizing the contributions of each feature that drive patient-specific classifications.ResultsA sample of 3,085 records was included (38.54% as manic, 56.69% as depressive, and 4.77% as mixed state). Mixed state showed more severe suicidal ideation and psychomotor abnormalities, while depressive state showed more common anxiety, sleep, and somatic-related symptoms and more comorbid conditions. Higher levels of body temperature, pulse, and systolic and diastolic blood pressures were present during manic episodes. Xgboost achieved the best AUC of 88.54% in manic/depressive states classification; Logistic regression and Random forest achieved the best AUCs of 75.5 and 75% in manic/mixed states and depressive/mixed states classifications, respectively. Myocardial enzymes and the non-enzymatic antioxidant uric acid and bilirubin contributed significantly to distinguish BD clinical states.ConclusionThe observed novel biological associations with BD clinical states confirm that biological heterogeneity contributes to clinical heterogeneity of BD.

Abstract Nisin is a natural bacteriocin that exhibits good antibacterial activity against Gram-positive bacteria. It has good solubility, stability, and activity under acidic conditions, but it becomes less soluble, stable, and active when the solution pH exceeds 6.0, which severely restricted the industrial application range of nisin as antibacterial agent. In this study, we investigated the potential of complexing nisin with a cyclodextrin carboxylate, succinic acid-β-cyclodextrin (SACD), to overcome the disadvantages. Strong hydrogen bonding was shown between the nisin and SACD, promoting the formation of nisin-SACD complexes. These complexes exhibited good solubility under neutral and alkaline conditions, and good stability after being held at high pH values during processing with high-steam sterilization. Moreover, the nisin-SACD complexes displayed significantly improved antibacterial activity against model Gram-positive bacteria (S. aureus). This study shows that complexation can improve the efficacy of nisin under neutral and alkaline situations, which may greatly broaden its application range in food, medical, and other industries.

Pole-type structures are vulnerable to earthquake events due to their slender shapes, particularly porcelain cylindrical equipment in electrical substations, which has inherent fragility and low strength in its materials. Traditional base isolation designs configure the bottom of the pole-type equipment as hinges with restraints. It fully relies on the restrainers to re-center the pole-type equipment, posing a risk of tilting and functionality failure after earthquakes. This study proposes a solution to this challenge by introducing a restrained rocking mechanism at the base of the structure. The design leverages the self-centering nature of rocking motion and uses restrainers to control the amplitude of rotation. Hence, it can effectively avoid tilting of the pole-type structures after earthquakes. Experimental investigations conducted on a 1:1 full-scale specimen revealed that the proposed restrained rocking design can achieve a reduction in seismic internal forces of over 50% while maintaining equipment in an upright position. Furthermore, an analytical model for the proposed isolation system of pole structures was developed and validated through comparison with experimental results. This paper introduces a novel solution for seismic isolation of pole-type structures through restrained rocking, specifically addressing the research gap regarding a reliable self-centering mechanism under seismic excitation. This advancement significantly enhances the seismic resilience of fragile pole-type structures and provides practical design methodologies for the seismic isolation of slender structures.

Introduction The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations.Methods Here, we examined how ancestrally diverse studies could clarify Lp(a)’s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations.Results Fourteen genome-wide significant loci with numerous population specific signals of large effect were identified that enabled construction of Lp(a) PRS of moderate (R2=15% in East Asians) to high (R2=50% in Europeans) accuracy. For all populations, PRS showed promise as a ‘rule out’ for elevated Lp(a) because certainty of assignment to the low-risk threshold was high (88.0%–99.9%) across PRS thresholds (80th–99th percentile). Causal effects of increased Lp(a) with increased glycated haemoglobin were estimated for Europeans (p value =1.4×10−6), although inverse effects in Africans and East Asians suggested the potential for heterogeneous causal effects. Finally, Hispanic/Latinos were the only population in which known associations with coronary atherosclerosis and ischaemic heart disease were identified in external testing of Lp(a) PRS phenotypic effects.Conclusions Our results emphasise the merits of prioritising ancestral diversity when addressing Lp(a) evidence gaps.

This paper aims at giving structural designers guidance on how to transform seismic demand on a building structure from two-dimensional (2D) to three-dimensional (3D) in an expedient manner, taking into account amplification of the torsional actions. This paper is to be read in conjunction with either paper #3 or #4. Torsional amplification of the drift demand in a building is of major concern in the structural design for countering seismic actions on the building. Code-based seismic design procedures based on elastic analyses may understate torsional actions in a plan of asymmetric building. This is because the inability of elastic analyses to capture the abrupt increase in the torsional action as the limit of yield of the supporting structural walls is surpassed. Nonlinear dynamic analysis can provide accurate assessment of torsional actions in a building which has been excited to respond in the inelastic range. However, a 3D whole building analysis of a multi-storey building can be costly and challenging, and hence not suited to day-to-day structural design. To simplify the analysis and reduce the scale of the computation, closed-form expressions are introduced in this paper for estimation of the Δ3D/Δ2D drift demand ratio for elastic conditions when buildings are subjected to moderate-intensity ground shaking. The drift demand of the 3D model can be estimated as a product of the 2D drift demand and the Δ3D/Δ2D drift demand ratio. In dealing with higher-intensity ground shaking causing yielding to occur, a macroscopic modelling methodology may be employed. The estimated Δ3D/Δ2D drift demand ratio of an equivalent single-storey building is combined with separate analysis for determination of the 2D drift demand. The deflection profile of the multi-storey prototype taking into account 3D effects, including torsional actions, is hence obtained. The accuracy of the presented methodologies has been verified by case studies in which drift estimates generated by the proposed calculation procedure were compared against results from whole building analyses, employing a well-established computer software.

The use of approximate communication has emerged as a promising approach for enhancing the efficiency of communication in parallel computer systems. By sending incomplete or imprecise messages, approximate communication can significantly reduce communication time. In this study, we examine application-level techniques for approximate communication to enable high portability on high-performance interconnection networks. Specifically, we focus on lossy compression of floating-point data, which is frequently exchanged between compute nodes in parallel applications. Our approach involves a simple application scenario where a source process compresses a communication dataset and a destination process decompresses it in an MPI parallel program. We use two bitwise procedures for compression: lossy bit-zip compression and lossless bit-mask compression. Our aim is to transmit the largest possible amount of approximate data with the least possible compression overhead. Additionally, we explore error check and correction techniques to ensure bit-flip fault tolerance for the compressed data during transmission. We implement our scheme in several communication-intensive MPI applications and demonstrate that our approximate communication approach effectively speeds up total execution time while staying within a specified quality-of-result error bound.

The Message Passing Interface (MPI) is a crucial programming tool for enabling communication between processes in parallel applications. The goal of MPI users is to allocate tasks to processors in a way that maximizes both spatial and temporal locality in the network. However, this can be challenging, especially in large-scale networks where maximizing processor locality may not be feasible at runtime. To address this issue, we propose the use of Hamorder, an offline node reassignment approach that takes into account physical processor locations based on graph reordering for Random network topologies. Hamorder aims to optimize task mapping for improved performance in parallel applications, whether for multiple tasks or within a single task. Additionally, we investigate the potential of improving MPI applications through runtime parameter tuning based on Hamorder. Our evaluation results show that Hamorder provides a 27.3% improvement in performance compared to the Gorder algorithm on Random topologies, which is a state-of-the-art solution designed with the aim of enhancing cache locality and achieves this goal by rearranging the vertices of a graph in a way that places the vertices that are typically accessed together in close proximity. Moreover, our autotuning framework using Hamorder results in an average speedup of $1.38\times $ for targeted MPI applications by searching through various runtime parameter combinations.

Abstract Serious concerns have been raised about the negative effects of the COVID-19 pandemic on population psychological well-being. However, limited data exist on the long-term effects of the pandemic on incident psychiatric morbidities among individuals with varying exposure to the pandemic. Leveraging prospective data from the community-based UK Biobank cohort, we included 308,400 participants free of diagnosis of anxiety or depression, as well as 213,757 participants free of anxiolytics or antidepressants prescriptions, to explore the trends in incident diagnoses and drug prescriptions for anxiety and depression from 16 March 2020 to 31 August 2021, compared to the pre-pandemic period (i.e., 1 January 2017 to 31 December 2019) and across populations with different exposure statuses (i.e., not tested for COVID-19, tested negative and tested positive). The age- and sex-standardized incidence ratios (SIRs) were calculated by month which indicated an increase in incident diagnoses of anxiety or depression among individuals who were tested for COVID-19 (tested negative: SIR 3.05 [95% confidence interval 2.88–3.22]; tested positive: 2.03 [1.76–2.34]), especially during the first six months of the pandemic (i.e., March-September 2020). Similar increases were also observed for incident prescriptions of anxiolytics or antidepressants (tested negative: 1.56 [1.47–1.67]; tested positive: 1.41 [1.22–1.62]). In contrast, individuals not tested for COVID-19 had consistently lower incidence rates of both diagnoses of anxiety or depression (0.70 [0.67–0.72]) and prescriptions of respective psychotropic medications (0.70 [0.68–0.72]) during the pandemic period. These data suggest a distinct rise in health care needs for anxiety and depression among individuals tested for COVID-19, regardless of the test result, in contrast to a reduction in health care consumption for these disorders among individuals not tested for and, presumably, not directly exposed to the disease.

This study tried to explore the ground movement induced by triple stacked tunneling (TST) with different construction sequences. A case study in Tianjin, China was used to investigate the ground movement during the TST (upper tunneling (UT)). For this, a modified Peck formula was proposed to predict the surface settlement induced by TST. Next, three sets of finite element analyses (FEA) were used to compare the effects of construction sequences (i.e. UT, middle tunneling (MT), and lower tunneling (LT)) on vertical and lateral ground displacements. The results of Tianjin case and UT reveal that compared to a Gaussian distribution for a single tunnel, the surface settlement curve of triple stacked tunnels is a bimodal distribution. It seems that the proposed modified Peck formula can effectively predict the surface settlement induced by TST. The results of the three sets of FEA demonstrate that the construction sequence has a significant influence on the ground movement. Among the three construction sequences, the largest lateral displacement is observed in the MT and the smallest one in UT. The existing tunnel has an inhibitory effect on the vertical displacement. The maximum value of the lateral displacement occurs at the depth of the new tunnel in each construction sequence.

Objectives: Chronic hepatitis B (CHB) is associated with high morbidity and mortality. We aimed to investigate associations between hepatic histology and clinical characteristics in treatment-naïve children with CHB in Shanghai, China. Methods: The liver biopsy specimens of 278 treatment-naïve children with CHB virus infection were scored for inflammation and fibrosis, and correlations with clinical and laboratory data were determined. Results: CHB clinical, virologic, and pathologic features were studied in 278 treatment-naïve children (177 [63.7%] males) in Shanghai, China. Maternal sera were positive for hepatitis B surface antigen for 277 children. At biopsy, 87.4% of patients were hepatitis B e antigen–positive. The median age at biopsy was 5.1 years (interquartile range 2.8-8.4 years). Hepatitis B virus (HBV) deoxyribonucleic acid levels were generally high (mean 7.4 log10 IU/ml), as were levels of serum alanine aminotransferase (ALT, median 105 U/l). Using the Metavir histology activity index scoring system, no, mild, moderate, and severe inflammation were seen in 2.9%, 22.3%, 73.4%, and 1.4% of patients, respectively. No fibrosis, mild fibrosis, moderate fibrosis, and cirrhosis were seen in 11.5%, 32.7%, 47.5%, and 8.3% of patients, respectively. When the serum ALT level was ≤80 (two times the upper limit of normal) and >80 U/l, the inflammation score (P 3 years (P 80 U/l may be a strong indicator of the degree of hepatic inflammation and fibrosis severity. Moderate fibrosis and cirrhosis can appear in children aged 3 years or younger.

In traffic monitoring data analysis, the magnitude of traffic density plays an important role in determining the level of traffic congestion. This study proposes a data imputation method for spatio-functional principal component analysis (s-FPCA) and unifies anomaly curve detection, outlier confirmation and imputation of traffic density at target intersections. Firstly, the detection of anomalous curves is performed based on the binary principal component scores obtained from the functional data analysis, followed by the determination of the presence of outliers through threshold method. Secondly, an improved method for missing traffic data estimation based on upstream and downstream is proposed. Finally, a numerical study of the actual traffic density data is carried out, and the accuracy of s-FPCA for imputation is improved by 8.28%, 8.91% and 7.48%, respectively, when comparing to functional principal component analysis (FPCA) with daily traffic density data missing rates of 5%, 10% and 20%, proving the superiority of the method. This method can also be applied to the detection of outliers in traffic flow, imputation and other longitudinal data analysis with periodic fluctuations.

Hydraulic fracture propagation has a great influence on reservoir reconstruction in shale gas exploitation. The study on mechanism of hydraulic fracture propagation is important. Based on the fluid-solid coupling theory, the propagation criterion under hydraulic pressure of shale is deduced in this paper. In combination with large-scale true triaxial experiment and numerical simulation, the law of hydraulic fracture propagation is researched, and the mechanism of hydraulic fracture propagation is obtained. The results show that shale will produce tensile failure and shear failure under the interaction of water pressure and ground stress. Acoustic emission monitoring data show that the initiation of microfracture is related to water pressure. When the fracture occurs, the number of acoustic emission events increases, and the water pressure drops sharply. Tensile failure occurs mainly at the crack tip, while shear failure occurs mainly at the weak structural plane. When bedding is encountered, hydraulic fracture will be diverted and spread along the bedding. If the strength of the cement inside the bedding is high, the hydraulic fracture passes directly through the weak structural plane. In this paper, the mechanism of shale hydraulic fracture propagation is studied, which has a certain theoretical and practical significance for shale gas fracturing effect evaluation and reservoir stimulation.

Autism spectrum disorder (ASD) poses as a multifaceted neurodevelopmental condition, significantly impacting children’s social, behavioral, and communicative capacities. Despite extensive research, the precise etiological origins of ASD remain elusive, with observable connections to brain activity. In this study, we propose a novel framework for ASD detection, extracting the characteristics of functional magnetic resonance imaging (fMRI) data and phenotypic data, respectively. Specifically, we employ recursive feature elimination (RFE) for feature selection of fMRI data and subsequently apply graph neural networks (GNN) to extract informative features from the chosen data. Moreover, we devise a phenotypic feature extractor (PFE) to extract phenotypic features effectively. We then, synergistically fuse the features and validate them on the ABIDE dataset, achieving 78.7% and 80.6% accuracy, respectively, thereby showcasing competitive performance compared to state-of-the-art methods. The proposed framework provides a promising direction for the development of effective diagnostic tools for ASD.

Abstract There is growing evidence supporting the implications of exosomes-shuttled microRNAs (miRs) in the phenotypes of glioblastoma stem cells (GSCs), whilst the role of exosomal miR-27b-3p remains to be established. Herein, the aim of this study was to investigate the effect of M2 tumor-associated macrophage (TAM)-derived exosomal miR-27b-3p on the function of GSCs. Clinical glioblastoma (GBM) specimens were obtained and GSCs and M2-TAMs were isolated by fluorescence-activated cell sorting (FACS), and exosomes were separated from M2-TAMs. It was observed that M2-TAM-derived exosomes promoted the stem-like properties of GSCs. Gain- and loss- of function assays were then conducted to explore the effects of exosomal miR-27b-3p and the miR-27b-3p/MLL4/PRDM1 axis on GSC phenotypes. A xenograft tumor model of GBM was further established for in vivo substantiation. Inhibition of miR-27b-3p in M2-TAMs reduced exosomal miR-27b-3p transferred into GSCs and consequently diminished GSC viability in vitro and tumor-promoting effects of GSCs in vivo. The interaction among miR-27b-3p, mixed linked leukemia 4 (MLL4), positive regulatory domain I (PRDM1) was validated by dual-luciferase and ChIP assays. MLL4 positively regulated PRDM1 expression by inducing methylation in the PRDM1 enhancer region and ultimately reduced IL-33 expression. miR-27b-3p targeted MLL4/PRDM1 to activate IL-33 and maintain the stem-like function of GSCs. In conclusion, our study elucidated that M2-TAM-derived exosomal miR-27b-3p enhanced the tumorigenicity of GSCs through the MLL4/PRDM1/IL-33 axis.

Abstract Background Whether a genetic predisposition to psychiatric disorders is associated with coronavirus disease 2019 (COVID-19) is unknown. Methods Our analytic sample consisted of 287,123 white British participants in UK Biobank who were alive on 31 January 2020. We performed a genome-wide association study (GWAS) analysis for each psychiatric disorder (substance misuse, depression, anxiety, psychotic disorder, and stress-related disorders) in a randomly selected half of the study population (“base dataset”). For the other half (“target dataset”), the polygenic risk score (PRS) was calculated as a proxy of individuals’ genetic predisposition to a given psychiatric phenotype using discovered genetic variants from the base dataset. Ascertainment of COVID-19 was based on the Public Health England dataset, inpatient hospital data, or death registers in UK Biobank. COVID-19 cases from hospitalization records or death records were considered “severe cases.” The association between the PRS for psychiatric disorders and COVID-19 risk was examined using logistic regression. We also repeated PRS analyses based on publicly available GWAS summary statistics. Results A total of 143,562 participants (including 10,868 COVID-19 cases) were used for PRS analyses. A higher genetic predisposition to psychiatric disorders was associated with an increased risk of any COVID-19 and severe COVID-19. The adjusted odds ratio (OR) for any COVID-19 was 1.07 (95% confidence interval [CI] 1.02–1.13) and 1.06 (95% CI 1.01–1.11) among individuals with a high genetic risk (above the upper tertile of the PRS) for substance misuse and depression, respectively, compared with individuals with a low genetic risk (below the lower tertile). Slightly higher ORs were noted for severe COVID-19, and similar result patterns were obtained in analyses based on publicly available GWAS summary statistics. Conclusions Our findings suggest a potential role of genetic factors in the observed phenotypic association between psychiatric disorders and COVID-19. Our data underscore the need for increased medical surveillance for this vulnerable population during the COVID-19 pandemic.

Abstract. Background:. The risk for chronic kidney disease (CKD) is influenced by genetic predisposition, sex, and lifestyle. Previous research indicates that coffee is a potentially protective factor in CKD. The current study aims to investigate whether sex disparity exists in the coffee–CKD association, and whether genetic risk of CKD or genetic polymorphisms of caffeine metabolism affect this association. Methods:. A total of 359,906 participants from the UK Biobank who were enrolled between 2006 and 2010 were included in this prospective cohort study, which aimed to estimate the hazard ratios for coffee intake and incident CKD using a Cox proportional hazard model. Allele scores of CKD and caffeine metabolism were additionally adjusted for in a subsample with qualified genetic data (n = 255,343). Analyses stratified by genetic predisposition, comorbidities, and sex hormones were performed. Tests based on Bayesian model averaging were conducted to ascertain the robustness of the results. Results:. Coffee was inversely associated with CKD in a dose-dependent manner. The effects of coffee did not differ across different strata of genetic risk for CKD, but were more evident among slower genetically predicted caffeine metabolizers. Significant sex disparity was observed (P value for interaction = 0.013), in that coffee drinking was only associated with the risk reduction of CKD in females. Subgroup analysis revealed that testosterone and sex hormone-binding globulin (SHBG), but not estradiol, modified the coffee–CKD association. Conclusions:. In addition to the overall inverse coffee–CKD association that was observed in the general population, we could also establish that a sex disparity existed, in that females were more likely to experience the benefit of the association. Testosterone and SHBG may partly account for the sex disparity.

Purpose To investigate the capability of an Magnetic resonance imaging (MRI) radiomics model based on pretreatment texture features in predicting the short-term efficacy of recombinant human endostatin (RHES) plus concurrent chemoradiotherapy (CCRT) for nasopharyngeal carcinoma (NPC). Methods We retrospectively enrolled 65 patients newly diagnosed as having NPC and treated with RHES + CCRT. A total of 144 texture features were extracted from the MRI before RHES + CCRT treatment of all the NPC patients. The maximum relevance minimum redundancy (mRMR) method was used to remove redundant, irrelevant texture features, and calculate the Rad score of the primary tumor. Multivariable logistic regression was used to select the most predictive features subset, and prediction models were constructed. The performance of the 3 models in predicting the early response of RHES + CCRT for NPC was explored. Results The diagnostic efficiency of combined model and radiomics model in distinguishing between the effective and the ineffective groups of patients was found to be moderate. The area under the ROC curve (AUC) of the combined model and radiomics model was 0.74 (95% confidence interval [CI]: 0.62-0.86) and 0.71 (95% CI: 0.58-0.84), respectively, with both being higher than the AUC of the clinics model (0.63, 95% CI: 0.49-0.78). Compared with the radiomics model, the combined model showed marginally improved diagnostic performance in predicting RHES + CCRT treatment response. The accuracy of combined model and radiomics model for RHES + CCRT response assessment in NPC were higher than those of the clinics model (0.723, 0.723 vs 0.677). Conclusion The pretreatment MRI-based radiomics may be a noninvasive and effective method for the prediction of RHES + CCRT early response in patients with NPC.

ObjectiveThis study was conducted to develop and validate a radiomics-clinics combined model-based magnetic resonance imaging (MRI) radiomics and clinical features for the early prediction of radiation-induced temporal lobe injury (RTLI) in patients with nasopharyngeal carcinoma (NPC).MethodsThis retrospective study was conducted using data from 130 patients with NPC (80 patients with and 50 patients without RTLI) who received radiotherapy. Cases were assigned randomly to training (n = 91) and testing (n = 39) datasets. Data on 168 medial temporal lobe texture features were extracted from T1WI, T2WI, and T1WI-CE MRI sequences obtained at the end of radiotherapy courses. Clinics, radiomics, and radiomics–clinics combined models (based on selected radiomics signatures and clinical factors) were constructed using machine learning software. Univariate logistic regression analysis was performed to identify independent clinical factors. The area under the ROC curve (AUC) was performed to evaluate the performance of three models. A nomogram, decision curves, and calibration curves were used to assess the performance of the combined model.ResultsSix texture features and three independent clinical factors associated significantly with RTLI were used to build the combined model. The AUCs for the combined and radiomics models were 0.962 [95% confidence interval (CI), 0.9306–0.9939] and 0.904 (95% CI, 0.8431–0.9651), respectively, for the training cohort and 0.947 (95% CI, 0.8841–1.0000) and 0.891 (95% CI, 0.7903–0.9930), respectively, for the testing cohort. All of these values exceeded those for the clinics model (AUC = 0.809 and 0.713 for the training and testing cohorts, respectively). Decision curve analysis showed that the combined model had a good corrective effect.ConclusionThe radiomics–clinics combined model developed in this study showed good performance for predicting RTLI in patients with NPC.

Introduction Hyperkalaemia (HK) is a potentially life-threatening electrolyte imbalance associated with several adverse clinical outcomes. The efficacy and negative effects of currently existing treatment options have made HK management questionable. Sodium zirconium cyclosilicate (SZC), a novel highly selective potassium binder, is approved for the treatment of HK. The present study will be aimed to assess the safety, effectiveness and treatment patterns of SZC in Chinese patients with HK in a real-world clinical setting as it is required by China’s drug review and approval process.Methods and analysis This is a multicentre, prospective cohort study which plans to enrol 1000 patients taking SZC or willing to take SZC from approximately 40 sites in China. Patients ≥18 years of age at the time of signing the written informed consent and with documented serum potassium levels ≥5.0 mmol/L within 1 year before study enrolment day will be included. Eligible patients will receive SZC treatment and will be followed up for 6 months from enrolment day. The primary objective will be to evaluate the safety of SZC for the management of HK in Chinese patients in terms of adverse events (AEs), serious AEs as well as discontinuation of SZC. The secondary objectives will include understanding the SZC dosage information in terms of its effectiveness and treatment patterns under real-world clinical practice and assessing effectiveness of SZC during the observational period.Ethics and dissemination This study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University (approval number: YJ-JG-YW-2020). All the participating sites have received the ethics approval. Results will be disseminated through national and international presentations and peer-reviewed publications.Trial registration number NCT05271266.

Abstract Glioblastoma (GBM) cell-derived extracellular vesicles (EVs) have been demonstrated to modulate tumor microenvironment. In the present study, we attempted to discuss the role of hsa-microRNA-27a-3p (miR-27a-3p) delivered by GBM-EVs in M2 macrophage polarization. The isolated GBM-EVs were co-cultured with macrophages. After co-culture under normoxia/hypoxia, the effect of EV-derived hsa-miR-27a-3p on GBM cell biological processes was analyzed. Additionally, the target genes of hsa-miR-27a-3p were predicted. Moreover, the binding of enhancer of zeste homologue 1 (EZH1) to lysine-specific demethylase 3A (KDM3A) promoter region and the interaction between KDM3A and connective tissue growth factor (CTGF) were analyzed. GBM mouse models were established to verify the functions of EV-derived hsa-miR-27a-3p in vivo. We found increased hsa-miR-27a-3p in GBM tissues as well as GBM-EVs, which induced M2 polarization, thus promoting proliferative, migrative and invasive potentials of GBM cells. hsa-miR-27a-3p targeted EZH1 and promoted KDM3A expression to elevate the CTGF expression. GBM-EV-delivered hsa-miR-27a-3p promoted the KDM3A-upregulated CTGF by downregulating EZH1, thereby promoting M2 macrophage polarization and development of GBM in vivo. We demonstrated that EV-derived hsa-miR-27a-3p may promote M2 macrophage polarization to induce GBM.

Based on the hourly rainfall data and other conventional data from 52 surface weather stations， and the National Centers for Environmental Prediction （NCEP） Final Analysis （FNL） data， the synoptic circulation patterns for the short-time heavy rainfall over the Qinghai Plateau are classified into three categories， namely the westerly airflow pattern， the subtropical high pattern， and the plateau low vortex-shear line pattern.Results show that the short-time heavy rainfall over the Qinghai Plateau occurs in the area east of 95°E， with the center in the southeast of the plateau.It mainly occurs from May to September， with the maximum in August， followed by July.For the diurnal variation， the short-time heavy rainfall occurs most from 17:00 to 22:00 （Beijing Time）， i.e.， the nightfall to midnight.The influence systems of the westerly airflow pattern are the high-level trough and the straight westerly short-wave trough.The dynamical instability caused by the vertical wind shear induces the short-time heavy rainfall.For the subtropical high pattern， the thermal instability caused by the low-level southerly or easterly warm-humid airflows results in the short-time heavy rainfall.For the plateau low vortex-shear line pattern， the plateau heating， and the weak cold airflow strenthen the low-level frontal area and trigger the short-time heavy rainfall.The composite analysis shows that the South Asian high， the subtropical westerly jet in the upper troposphere， the short-wave trough in the middle-lower troposphere， the shear line， the southerly warm-humid airflow， and the plateau heating field are the main influence systems for the short-time heavy rainfall.The convergence of water vapor from the Indian monsoon， the southeast of the western Pacific subtropical high and the northwest of the westerly trough is conducive to the short-time heavy rainfall in eastern Qinghai.

Abstract Patients with major depressive disorder (MDD) are at high risk of psychiatric readmission while the factors associated with such adverse illness trajectories and the impact of the same factor at different follow-up times remain unclear. Based on machine learning (ML) approaches and real-world electronic medical records (EMR), we aimed to predict individual psychiatric readmission within 30, 60, 90, 180, and 365 days of an initial major depression hospitalization. In addition, we examined to what extent our prediction model could be made interpretable by quantifying and visualizing the features that drive the predictions at different follow-up times. By identifying 13,177 individuals discharged from a hospital located in western China between 2009 and 2018 with a recorded diagnosis of MDD, we established five prediction-modeling cohorts with different follow-up times. Four different ML models were trained with features extracted from the EMR, and explainable methods (SHAP and Break Down) were utilized to analyze the contribution of each of the features at both population-level and individual-level. The model showed a performance on the holdout testing dataset that decreased over follow-up time after discharge: AUC 0.814 (0.758–0.87) within 30 days, AUC 0.780 (0.728–0.833) within 60 days, AUC 0.798 (0.75–0.846) within 90 days, AUC 0.740 (0.687–0.794) within 180 days, and AUC 0.711 (0.676–0.747) within 365 days. Results add evidence that markers of depression severity and symptoms (recurrence of the symptoms, combination of key symptoms, the number of core symptoms and physical symptoms), along with age, gender, type of payment, length of stay, comorbidity, treatment patterns such as the use of anxiolytics, antipsychotics, antidepressants (especially Fluoxetine, Clonazepam, Olanzapine, and Alprazolam), physiotherapy, and psychotherapy, and vital signs like pulse and SBP, may improve prediction of psychiatric readmission. Some features can drive the prediction towards readmission at one follow-up time and towards non-readmission at another. Using such a model for decision support gives the clinician dynamic information of the patient’s risk of psychiatric readmission and the specific features pulling towards readmission. This finding points to the potential of establishing personalized interventions that change with follow-up time.