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Abstract The impact of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) traits on suicidal thoughts and behaviors (STBs) remains inadequately explored. Hence, the present study aims to delve deeper into these intricate issues, contributing to a better understanding of these complex challenges among Chinese youth. The data of 90,882 participants was collected from 63 Chinese universities and colleges in Jilin, China. We aim to explore the risks of STBs on ASD, ADHD, and co-occurrence of ASD + ADHD by using the Autism Spectrum Quotient-10 items (AQ-10) and Adult ADHD Self Report Scale (ASRS). Propensity score matching (PSM) was implemented to balance demographical variables across the four groups. Binary logistic regression was then conducted to further analyze and compare suicide risk across the four groups, also accounting for sex differences. Suicide risks were significantly higher in the ADHD (OR = 1.24, p

Abstract China’s higher education system is shifting from quantitative expansion to connotative development to advance its quality. Since 2015, Chinese governments have been implementing a strategic policy for higher education called “double first-class”, which aims to promote a number of Chinese top universities to construct world-class universities or to establish world-class disciplines. “Double first-class” universities have received a large amount of educational resources through this policy. Taking advantage of resources efficiently is an important element in promoting the development of higher quality higher education. However, research on resource allocation in China’s “double first-class” universities is incomplete. Current research has not clarified the level of resource allocation efficiency or the factors affecting China’s “double first-class” universities. With the help of the superefficient data envelopment analysis (DEA)-Malmquist–Tobit model, this study actively explores the current status of the resource allocation efficiency of China’s “double first-class” universities to fill this gap in the field. Specifically, the development level and change trend of the resource allocation efficiency of 13 “double first-class” universities in China from 2015 to 2019 were measured with the help of the superefficient DEA-Malmquist model. The internal and external factors affecting the resource allocation efficiency of “double first-class” universities are also analysed with the help of the Tobit model. The overall level of resource allocation efficiency of “double first-class” universities is high, but the internal variability is large. From the perspective of efficiency decomposition, it is found that both technical efficiency change (EFch) and technical progress efficiency (TEch) play important roles in improving the total factor productivity (TFP) of resource allocation. Compared with TEch, EFch plays a more significant pulling role. This study confirms that the factors affecting resource allocation efficiency are complex. Among them, the regional economic environment, faculty title structure, and degree of international exchange have significant roles in promoting the resource allocation efficiency of “double first-class” universities, but local financial support and the time of policy implementation have certain negative effects.

ABSTRACTUnintended end-of-process depression (EOPD) commonly occurs in laser powder bed fusion (LPBF), leading to poor surface quality and lower fatigue strength, especially for many implants. In this study, a high-fidelity multi-physics meso-scale simulation model is developed to uncover the forming mechanism of this defect. A defect-process map of the EOPD phenomenon is obtained using this simulation model. It is found that the EOPD formation mechanisms are different under distinct regions of process parameters. At low scanning speeds in keyhole mode, the long-lasting recoil pressure and the large temperature gradient easily induce EOPD. While at high scanning speeds in keyhole mode, the shallow molten pool morphology and the large solidification rate allow the keyhole to evolve into an EOPD quickly. Nevertheless, in the conduction mode, the Marangoni effects along with a faster solidification rate induce EOPD. Finally, a ‘step’ variable power strategy is proposed to optimise the EOPD defects for the case with high volumetric energy density at low scanning speeds. This work provides a profound understanding and valuable insights into the quality control of LPBF fabrication.

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.

Abstract Copper (Cu) has been regarded as a highly efficient electrocatalyst for the conversion of CO2 into a multicarbon product. However, the catalytic mechanism and the active sites of Cu catalysts under operating conditions still remain elusive. Yang's team applied systematic operando characterization techniques to provide a quantitative analysis of the valence states and the chemical environment of Cu nanocatalysts under electrochemical reaction conditions, which clearly reveal the evolution of Cu nanocatalysts before and after the entire electrochemical CO2 reduction.

Abstract Optoelectronic properties of semiconductors are significantly modified by impurities at trace level. Oxygen, a prevalent impurity in organic semiconductors (OSCs), has long been considered charge-carrier traps, leading to mobility degradation and stability problems. However, this understanding relies on the conventional deoxygenation methods, by which oxygen residues in OSCs are inevitable. It implies that the current understanding is questionable. Here, we develop a non-destructive deoxygenation method (i.e., de-doping) for OSCs by a soft plasma treatment, and thus reveal that trace oxygen significantly pre-empties the donor-like traps in OSCs, which is the origin of p-type characteristics exhibited by the majority of these materials. This insight is completely opposite to the previously reported carrier trapping and can clarify some previously unexplained organic electronics phenomena. Furthermore, the de-doping results in the disappearance of p-type behaviors and significant increase of n-type properties, while re-doping (under light irradiation in O2) can controllably reverse the process. Benefiting from this, the key electronic characteristics (e.g., polarity, conductivity, threshold voltage, and mobility) can be precisely modulated in a nondestructive way, expanding the explorable property space for all known OSC materials.

Abstract Glioblastoma (GBM) remains the most lethal malignant tumours. Gboxin, an oxidative phosphorylation inhibitor, specifically restrains GBM growth by inhibiting the activity of F0F1 ATPase complex V. However, its anti-GBM effect is seriously limited by poor blood circulation, the blood brain barrier (BBB) and non-specific GBM tissue/cell uptake, leading to insufficient Gboxin accumulation at GBM sites, which limits its further clinical application. Here we present a biomimetic nanomedicine (HM-NPs@G) by coating cancer cell-mitochondria hybrid membrane (HM) on the surface of Gboxin-loaded nanoparticles. An additional design element uses a reactive oxygen species responsive polymer to facilitate at-site Gboxin release. The HM camouflaging endows HM-NPs@G with unique features including good biocompatibility, improved pharmacokinetic profile, efficient BBB permeability and homotypic dual tumour cell and mitochondria targeting. The results suggest that HM-NPs@G achieve improved blood circulation (4.90 h versus 0.47 h of free Gboxin) and tumour accumulation (7.73% ID/g versus 1.06% ID/g shown by free Gboxin). Effective tumour inhibition in orthotopic U87MG GBM and patient derived X01 GBM stem cell xenografts in female mice with extended survival time and negligible side effects are also noted. We believe that the biomimetic Gboxin nanomedicine represents a promising treatment for brain tumours with clinical potential.

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.

Abstract With the advent of the big data era, artificial intelligence technology has penetrated and deeply affected our daily life. In addition, data‐based machine learning algorithms have been applied to physics, chemistry, material science, and other basic science fields. However, the scarcity of data sets is known as the main obstacle to its development. Mining effective information from the limited data samples and building an appropriate machine learning algorithms framework are the major breakthroughs. For solid materials, the intrinsic properties are closely related to their atomic composition and relative positions, namely crystal structures. Here, inspired by the emerging of graph convolution neural network and material crystal graph, we proposed an integrated algorithms framework embedded crystal graph to train and predict the lattice thermal conductivities of crystal materials. This machine learning algorithms framework showed superior learning and generalization ability. In addition, not only in predicting thermal conductivities, but our framework also has great performance in predicting other phonon or electron‐related properties. This strategy provided a new approach in the design of machine learning framework, which indicated the great potential for the application of machine learning in material science.

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 Organic thermoelectric materials have the potential to be used as power supplies for wearable electronics, implantable medical devices, and sensors in Internet of Things. The past 10 years has witnessed the rapid development of the research on organic thermoelectric materials, different material systems and optimizing strategies are developed, and the ZT values of some organic materials have approached that of many inorganic thermoelectric material systems in the low‐temperature region. Among different material systems, organic composite materials, especially multicomponent organic composite materials show very promising thermoelectric properties and offer more tunability compared to single component thermoelectric materials. Multicomponent organic composite thermoelectric materials can not only further improve the ZT values, but also have unique advantages of combining the merits of different materials, thus rendering the composites with better processing, mechanical, or other properties on demand. This review summarizes the concepts, the design criteria, the research progress of organic–inorganic and all‐organic multicomponent thermoelectric materials which contain three or more different ingredients, as well as their applications. Furthermore, the challenges and prospects are also analyzed to provide guidelines for the development of multicomponent organic composite thermoelectric materials.

Objective The specific roles of phosphorylated signal transducer and activator of transcription-3 (p-STAT3) and β-Catenin in laryngeal squamous cell carcinoma (LSCC) remain unclear. Methods In this study, the correlations between p-STAT3, β-Catenin, and clinicopathological characteristics were investigated using tissues and clinical data from 124 LSCC cases. Immunohistochemistry and immunofluorescence assays were used to examine p-STAT3 and β-Catenin expression and localization in these samples. Kaplan–Meier survival and Cox regression analyses were performed to evaluate the prognostic significance of these proteins. LSCC cell lines were treated with a STAT3 inhibitor (dihydroartemisinin) or activator (interleukin-6) to explore the mechanism of p-STAT3 and β-Catenin. Results There was an inverse correlation between p-STAT3 and β-Catenin expression in the LSCC samples. Patients with high p-STAT3 and low β-Catenin expression levels had significantly worse overall survival. Multivariate Cox regression analysis revealed that lymph node metastasis and β-Catenin expression were both independently correlated with unfavorable overall survival. Cell treatment with the p-STAT3 inhibitor inhibited the nuclear accumulation of β-Catenin, while p-STAT3 activator treatment could promote β-Catenin translocation to the nucleus. Conclusion Overall, our data indicate that p-STAT3 expression is associated with LSCC by promoting β-Catenin degradation.

Aggregate state instability is a major cause of device degradation in organic field-effect transistors. Here, authors elucidate the origin of such instability and provide a strategy to overcome it, such that devices with ultra-long lifetimes can be obtained.

Abstract Background To elucidate the influence of childhood asthma on adult height after consideration of genetic heterogeneity in height. Methods Based on the UK Biobank, we conducted a matched cohort study, including 13,602 European individuals with asthma diagnosed before 18 years old and 136,008 matched unexposed individuals without such an experience. Ascertainment of asthma was based on self-reported data (97.6%) or clinical diagnosis in healthcare registers (2.4%). We studied three height outcomes, including (1) the attained adult height (in centimeters), (2) the height deviation measured as the difference between a person’s rank of genetically determined height (based on generated polygenetic risk score) and their rank of attained adult height in the study population (deviation in % of height order after standardization), and (3) the presence of height deficit comparing genetically determined and attained height (yes or no). We applied linear mixed-effect models to assess the associations of asthma diagnosed at different ages with attained adult height and height deviation, and conditional logistic regression models to estimate the associations of asthma with the risk of height deficit. Results 40.07% (59,944/149,610) of the study participants were born before 1950, and most of them were men (57.65%). After controlling for multiple covariates, childhood asthma was associated with shorter attained adult height, irrespective of age at asthma diagnosis. However, in the analysis of height deviation (deviation in %), we observed the greatest height deviation among individuals with asthma diagnosed before 4 years of age (− 2.57 [95% CI − 4.14 to − 1.00] and − 2.80 [95% CI − 4.06 to − 1.54] for the age of ≤ 2 and 3–4 years, respectively). The magnitude of height deviation in relation to asthma declined thereafter and became null after age 6. Similarly, there was a statistically significant height deficit in relation to an asthma diagnosis at ages ≤ 2 and 3–4 (odds ratios = 1.21, 95% CI 1.04 to 1.40, and 1.15, 95% CI 1.02 to 1.29) but not thereafter. The result pattern was similar when separately analyzing asthma with or without inhaled glucocorticoid (ICS) use, despite that the estimates were consistently stronger among asthma individuals who used ICS. Conclusions Our results suggest a notable association of childhood asthma, primarily asthma diagnosed at an early age, with adult height, after consideration of genetic heterogeneity in height and use of ICS. This finding highlights the need for surveillance on the growth problems among children with asthma.

Abstract Background This study aimed to explore the validity and reliability of the Patient Health Questionnaire-9 (PHQ-9) on screening of depression among patients with neurological disorders, and to explore factors influencing such patients. Methods In this study, 277 subjects who were admitted to the department of neurology of our hospital due to different neurological disorders completed the PHQ-9 questionnaire. The Mini-International Neuropsychiatric Interview (MINI) and Hamilton Rating Scale for Depression (HAMD) were employed to evaluate the depressive symptoms of patients who completed the PHQ-9 questionnaire. The internal consistency, criterion validity, structural validity, and optimal cut-off values of PHQ-9 were evaluated, and the consistency assessment was conducted between the depression severity as assessed by PHQ-9, HAMD and MINI. Logistic regression analysis was used to calculate the risk factors of depression. Results The Cronbach’s α coefficient of the PHQ-9 was 0.839. The Pearson’s correlation coefficient among the 9 items of the PHQ-9 scale was 0.160 ~ 0.578 (P

Abstract Background An increased susceptibility to COVID-19 has been suggested for individuals with neurodegenerative diseases, but data are scarce from longitudinal studies. Methods In this community-based cohort study, we included 96,275 participants of the UK Biobank who had available SARS-CoV-2 test results in Public Health England. Of these, 2617 had a clinical diagnosis of neurodegenerative diseases in the UK Biobank inpatient hospital data before the outbreak of COVID-19 (defined as January 31st, 2020), while the remaining participants constituted the reference group. We then followed both groups from January 31st, 2020 to June 14th, 2021 for ascertainment of COVID-19 outcomes, including any COVID-19, inpatient care for COVID-19, and COVID-19 related death. Logistic regression was applied to estimate the association between neurogenerative disease and risks of COVID-19 outcomes, adjusted for multiple confounders and somatic comorbidities. Results We observed an elevated risk of COVID-19 outcomes among individuals with a neurodegenerative disease compared with the reference group, corresponding to a fully adjusted odds ratio of 2.47 (95%CI 2.25–2.71) for any COVID-19, 2.18 (95%CI 1.94–2.45) for inpatient COVID-19, and 3.67 (95%CI 3.11–4.34) for COVID-19 related death. Among individuals with a positive test result for SARS-CoV-2, individuals with neurodegenerative diseases had also a higher risk of COVID-19 related death than others (fully adjusted odds ratio 2.08; 95%CI 1.71–2.53). Conclusion Among UK Biobank participants who received at least one test for SARS-CoV-2, a pre-existing diagnosis of neurodegenerative disease was associated with a subsequently increased risk of COVID-19, especially COVID-19 related death.

BackgroundSuicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice. ObjectiveWe aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide. MethodsBased on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality. ResultsIndividuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low (

PurposeThis study used the latent profile analysis technique to investigate the latent categories of high school students’ sense of hope and their relationship with mental health.MethodsA total of 1,513 high school students from six middle schools in China was tested using the Adult Dispositional Hope Scale and the Symptom Checklist 90. Analysis of variance was used to explore the relationship between latent categories of sense of hope and mental health.ResultsHigh school students’ sense of hope scores are negatively associated with mental health scores. The high school students’ sense of hope could be divided into three latent categories: negative sense of hope group, moderate sense of hope group and positive sense of hope group. The differences in scores on each dimension of mental health among high school students with different latent categories of sense of hope were statistically significant. The positive sense of hope group had lower scores on the dimensions of somatization, compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, terror, paranoia, and psychosis than the negative sense of hope group and the moderate sense of hope group.ConclusionThere are three latent categories of high school students’ sense of hope, and the sense of hope category is closely related to mental health. Based on the different categories of high school students’ sense of hope, the program of mental health education can be reasonably selected to create a positive general environment for mental health education and ultimately enhance the mental health of high school students.

IntroductionThe study assesses the moderated mediation effect of sense of hope on the mental health of secondary school students.MethodsThe Adult Dispositional Hope Scale (ADHS), Connor-Davidson Resilience Scale (CD-RISC), and the Symptom Check List 90 (SCL-90) were used to conduct a questionnaire survey on 1776 secondary school students.ResultsThe results showed that total mental health scores of secondary school students were significantly negatively correlated with sense of hope and psychological resilience; sense of hope was significantly positively correlated with psychological resilience; sense of hope significantly and positively predicted the level of mental health of secondary school students, and psychological resilience played a mediating role in it; gender plays a moderating role in the relationship between sense of hope and psychological resilience.DiscussionThe study further revealed the mechanism of the effect of sense of hope on secondary school students’ mental health, and provided suggestions for cultivating positive psychological qualities and promoting the mental health development of secondary school students.

Abstract Phase‐change semiconductor is one of the best candidates for designing nonvolatile memory, but it has never been realized in organic semiconductors until now. Here, a phase‐changeable and high‐mobility organic semiconductor (3,6‐DATT) is first synthesized. Benefiting from the introduction of electrostatic hydrogen bond (S···H), the molecular conformation of 3,6‐DATT crystals can be reversibly modulated by the electric field and ultraviolet irradiation. Through experimental and theoretical verification, the tiny difference in molecular conformation leads to crystalline polymorphisms and dramatically distinct charge transport properties, based on which a high‐performance organic phase‐change memory transistor (OPCMT) is constructed. The OPCMT exhibits a quick programming/erasing rate (about 3 s), long retention time (more than 2 h), and large memory window (i.e., large threshold voltage shift over 30 V). This work presents a new molecule design concept for organic semiconductors with reversible molecular conformation transition and opens a novel avenue for memory devices and other functional applications.

Financial management and decision-making of universities play an essential role in their development. Predicting fund revenue and expenditure of universities can provide a necessary basis for funds risk prevention. For the lack of solid data reference for financial management and funds risk prevention in colleges and universities, this paper presents a prediction model of University fund revenue and expenditure based on fuzzy time series with a periodic factor. Combined with the fuzzy time series, this prediction method introduces the periodic factor of university funds. The periodic factor is used to adjust the proportion of the predicted value of the fuzzy time series and the periodic observation value. A fund revenue prediction model and a fund expenditure prediction model are constructed, and an experiment is carried out with the actual financial data of a university in China. The experimental result shows the effectiveness of the proposed model, which can provide solid references for financial management and funds risk prevention in universities.

Abstract Background With the increasing number of people infected with and recovered from coronavirus disease 2019 (COVID-19), the extent of major health consequences of COVID-19 is unclear, including risks of severe secondary infections. Methods Based on 445,845 UK Biobank participants registered in England, we conducted a matched cohort study where 5151 individuals with a positive test result or hospitalized with a diagnosis of COVID-19 were included in the exposed group. We then randomly selected up to 10 matched individuals without COVID-19 diagnosis for each exposed individual (n = 51,402). The life-threatening secondary infections were defined as diagnoses of severe secondary infections with high mortality rates (i.e., sepsis, endocarditis, and central nervous system infections) from the UK Biobank inpatient hospital data, or deaths from these infections from mortality data. The follow-up period was limited to 3 months after the initial COVID-19 diagnosis. Using a similar study design, we additionally constructed a matched cohort where exposed individuals were diagnosed with seasonal influenza from either inpatient hospital or primary care data between 2010 and 2019 (6169 exposed and 61,555 unexposed individuals). After controlling for multiple confounders, Cox models were used to estimate hazard ratios (HRs) of life-threatening secondary infections after COVID-19 or seasonal influenza. Results In the matched cohort for COVID-19, 50.22% of participants were male, and the median age at the index date was 66 years. During a median follow-up of 12.71 weeks, the incidence rate of life-threatening secondary infections was 2.23 (123/55.15) and 0.25 (151/600.55) per 1000 person-weeks for all patients with COVID-19 and their matched individuals, respectively, which corresponded to a fully adjusted HR of 8.19 (95% confidence interval [CI] 6.33–10.59). The corresponding HR of life-threatening secondary infections among all patients with seasonal influenza diagnosis was 4.50, 95% CI 3.34–6.08 (p for difference < 0.01). Also, elevated HRs were observed among hospitalized individuals for life-threatening secondary infections following hospital discharge, both in the COVID-19 (HR = 6.28 [95% CI 4.05–9.75]) and seasonal influenza (6.01 [95% CI 3.53–10.26], p for difference = 0.902) cohorts. Conclusion COVID-19 patients have increased subsequent risks of life-threatening secondary infections, to an equal extent or beyond risk elevations observed for patients with seasonal influenza.

Objectives Given the role of intraocular pressure in glaucoma, the patient’s sleeping pattern might contribute to the development and progression of glaucoma. We performed a study to understand the association between sleep behaviours and glaucoma.Design Our study was a prospective cohort study.Setting This was a prospective cohort study in the UK Biobank. Self-reported data on five sleep behaviours were collected using a questionnaire at baseline. We identified four sleep patterns based on a cluster analysis of the sleep behaviours.Participants In the UK Biobank, 409 053 participants were recruited between 2006 and 2010 and followed for a diagnosis of glaucoma. We identified glaucoma as any hospital admission with a diagnosis of glaucoma, based on UK Biobank inpatient hospital data. Individuals who withdrew from the UK Biobank, or were diagnosed with glaucoma before recruitment, or had self-reported surgery or laser treatment for glaucoma, or had no information on sleep behaviors were excluded.Primary and secondary outcome measures We estimated hazard ratios (HRs) with 95% confidence intervals (CI) using Cox proportional hazards models to estimate the associations of different sleep behaviors, as well as identified sleep patterns, with the risk of glaucoma, adjusting for multiple confounders.Results Compared with individuals who had a healthy sleep pattern, an excess risk of any glaucoma was observed among individuals with snoring and daytime sleepiness (HR 1.11, 95% CI 1.03 to 1.19) or insomnia and short/long sleep duration (HR 1.13, 95% CI 1.06 to 1.20), but not late chronotype sleep pattern (HR 0.98, 95% CI 0.93 to 1.03).Conclusion Snoring, daytime sleepiness, insomnia, and short/long duration, individually or jointly, were all associated with the risk of glaucoma. These findings underscore the need for sleep intervention for individuals at high risk of glaucoma as well as potential ophthalmologic screening among individuals with chronic sleep problems for glaucoma prevention.

In this paper, five shapes of thermoelectric generator (TEG) models (cylindrical, barrel shaped, hourglass shaped, cup shaped, and inverse cup shaped) are built under the boundary conditions of heat flux at the hot end and convection at the cold end of the TEGs. Based on the numerical simulation results, the configuration of the variable cross-section can effectively boost the performance of TEGs. Remarkably, the hourglass-shaped TEG generated the maximum output power and efficiency, which were 69.62% and 70.96% higher than that of the conventional cylindrical TEG, respectively. The results indicate that the hourglass shape is beneficial to enlarge the temperature difference between the two ends of the TEG, which results in performance improvement. In addition, the effects of heat flux and convection on the performance of TEGs are explored and discussed. After choosing the appropriate boundary conditions, the relationships between the maximum output power and efficiency and the shape factor of the hourglass-shaped TEG are obtained according to the fitting results. Finally, some conclusions are drawn to provide guidance for TEG applications.

Abstract Background Health-related risky behaviors (HRB) generally refer to behaviors that have a negative influence on health and quality of life. HRB in adolescents with autism have not been well understood so far. We aim to explore health-related risky behaviors and their risk factors with autistic adolescents. Methods In this study, 150 adolescents with autism and 150 neurotypical adolescents were enrolled. Participants in both groups completed the Adolescent Health-Related Risky Behavior Inventory (AHRBI). Autism Spectrum Screening Questionnaire (ASSQ), Wechsler Intelligence Scale, Theory of Mind (ToM) Test, Zung Self-rating Anxiety Scale (SAS), Zung Self-rating Depression Scale (SDS), and Self-Esteem Scale (SES) were also assessed in the autism group to explore risk factors. Results The results showed that the total score of AHRBI and scores of "aggression and violence (AV)", "suicide or self-injury (SS)", "health-compromising behavior (HCB)", and "unprotected sex (US)" subscales in the autism group were significantly higher than those in the control group (Z value = − 4.58 ~ − 2.26, all P

Abstract Glioblastoma (GBM) is a central nervous system tumor with poor prognosis due to the rapid development of resistance to mono chemotherapy and poor brain targeted delivery. Chemoimmunotherapy (CIT) combines chemotherapy drugs with activators of innate immunity that hold great promise for GBM synergistic therapy. Herein, we chose temozolomide, TMZ, and the epigenetic bromodomain inhibitor, OTX015, and further co‐encapsulated them within our well‐established erythrocyte membrane camouflaged nanoparticle to yield ApoE peptide decorated biomimetic nanomedicine (ABNM@TMZ/OTX). Our nanoplatform successfully addressed the limitations in brain‐targeted drug co‐delivery, and simultaneously achieved multidimensional enhanced GBM synergistic CIT. In mice bearing orthotopic GL261 GBM, treatment with ABNM@TMZ/OTX resulted in marked tumor inhibition and greatly extended survival time with little side effects. The pronounced GBM treatment efficacy can be ascribed to three key factors: (i) improved nanoparticle‐mediated GBM targeting delivery of therapeutic agents by greatly enhanced blood circulation time and blood–brain barrier penetration; (ii) inhibited cellular DNA repair and enhanced TMZ sensitivity to tumor cells; (iii) enhanced anti‐tumor immune responses by inducing immunogenic cell death and inhibiting PD‐1/PD‐L1 conjugation leading to enhanced expression of CD4+ and CD8+ T cells. The study validated a biomimetic nanomedicine to yield a potential new treatment for GBM.

BackgroundThe association between hyperuricemia/gout with cardiovascular diseases (CVD) have been investigated. However, whether the magnitude of associations differs between hyperuricemia and gout, and the causality of these associations, remains inconclusive.MethodsBased on UK Biobank, we conducted a cohort analysis including 431,967 participants, who were categorized as gout, hyperuricemia, and normal groups at recruitment, and followed up for CVD until December 2019. The phenotypic association of hyperuricemia/gout with CVD was estimated by Cox regression, adjusting for multiple confounders. Further exploration on the causality of such links was performed using Mendelian Randomization (MR) analysis, where we selected exclusive genetic variants for hyperuricemia and for gout based on summary GWAS data from independent populations.ResultsDuring mean 10.20 years of follow-up, hyperuricemia patients were associated with increased CVD (HR = 1.33, 95% CI: 1.29–1.36), compared to individuals who were free of hyperuricemia/gout. The risk elevation was even higher for gout patients (HR = 1.54, 95% CI: 1.48–1.62). Furthermore, we found significantly positive association between genetic liability for hyperuricemia and CVD in both one-sample (OR = 1.06, 95% CI: 1.02–1.11) and two-sample (OR = 1.09, 95% CI: 1.03–1.16) MR analysis. However, genetic liability for gout was not associated with CVD (OR = 0.89, 95% CI: 0.79–1.01 in one-sample, and OR = 0.92, 95% CI: 0.82–1.21 in two-sample MR analysis).ConclusionIndividuals with hyperuricemia/gout were at increased risk of various types of CVD. As the MR analyses suggest a causal effect of hyperuricemia, but not gout, on CVD, these results indicate the possible effects of other gout-associated factors on the development of CVD, in addition to the uric acid pathway.

Abstract Background Bronchiolar adenoma(BA) is a recently recognized, rare tumor of the bronchioles. It can be divided into proximal and distal types according to the proportion of mucinous and ciliated cells on the luminal surface. BA is often misdiagnosed because it has similar ultrasonographic, gross and histological presentations as other diseases. Here, we report a rare case of BA characterized by many fused nodules. Case presentation A 68-year-old woman attended the Tianjin Taida Hospital surgical Clinic mainly because of “intermittent cough for >1 month”. Chest computed tomography (CT) showed multiple solid nodules in the upper and lower left lung. The nodules had irregular outlines, with a maximum diameter of 65 mm. A double needle lung biopsy specimen was removed guided by ultrasound under local anesthesia. Histologically, the biopsy specimen was finally diagnosed as the distal type of BA. Conclusion BA with diffuse pulmonary nodules is rare. Diagnosis of BA needs comprehensive analysis of imaging, gross specimen analysis, histopathology, and immunohistochemical staining to make a correct diagnosis and avoid misdiagnosis. There are few studies on prognosis, which needs close follow-up and more data accumulation.

Abstract Background Interferon-inducible 16 (IFI16)/caspase-1 inflammasome activates and secretes IL-1β. However, it is still unclear whether the IFI16 inflammasome is involved in human laryngeal squamous cell carcinoma. Autophagy directly removed inflammasome components and limited early IL-1β production. RalB is required for the crosstalk between inflammasome and autophagy in macrophages. Dihydroartemisinin (DHA), the main derived ingredient of artemisinin, has a variety of biological activities. The mechanism of DHA in regulating the crosstalk between IFI16 inflammasome and autophagy by inhibiting RalB expression was analyzed in order to provide clues for new therapeutic methods in laryngeal cancer. Methods The expression of IFI16 was analyzed by Oncomine and GEPIA databases and detected by Western blot and immunohistochemistry. The relationship between IFI16 inflammasome and autophagy was investigated by transmission electron microscopy, immunofluorescence assay, etc. in Hep-2, Cal-27 and HeLa cells treated with DHA. The xenograft tumor of hep-2 cell in nude mice were used to assess the effect of DHA on laryngeal cancer. Results It was reported for the first time in this study that IFI16 was overexpressed and positively correlated with caspase-1 in laryngeal carcinoma tissues. DHA significantly inhibited the activation of inflammasome and reduced IL-1β production in the microenvironment of Hep-2 cell xenograft tumor in nude mice. Mechanistically, we found that DHA degraded RalB, inhibited USP33 expression, and triggered autophagy. Meanwhile, enhanced autophagy can reduce the expression of RalB and USP33. Furthermore, DHA promotes autophagy, which suppresses the activation of IFI16/caspase-1 inflammasome and IL-1β production. Conclusions Therefore, our findings demonstrate that DHA may act as a RalB inhibitor to regulate the crosstalk between autophagy and IFI16/caspase-1 inflammasome, which inhibits IL-1β production in tumor microenvironment.

Objective To explore whether dihydroartemisinin (DHA) can block interleukin (IL)-6-induced epithelial–mesenchymal transition (EMT) in laryngeal squamous cell carcinoma (LSCC). Methods The expression of SLUG, signal transducer and activator of transcription 3 (STAT3), and microRNA (miR)-130b-3p was measured. In addition, a dual-luciferase reporter assay was performed to examine the interaction of miR-130b-3p with STAT3. Results We found that IL-6 can promote EMT and invasion in LSCC cells, whereas DHA can inhibit these two processes. However, DHA alone does not influence EMT and cancer invasion. Furthermore, DHA upregulated miR-130b-3p, which can downregulate STAT3 and β-catenin protein expression and decrease the activity of the IL-6/STAT3 signaling pathway. Moreover, we found that miR-130b-3p can target STAT3 directly. Conclusions DHA can block IL-6-triggered EMT and invasion in LSCC, and during these processes, DHA increases miR-130b-3p expression to decrease the activation of the IL-6/STAT3 and β-catenin signaling pathways. These findings may provide new insights into strategies for suppressing and even preventing LSCC metastasis.

Despite all sorts of innovations in medical researches over the past decades, cancer remains a major threat to human health. Mitochondria are essential organelles in eukaryotic cells, and their dysfunctions contribute to numerous diseases including cancers. Mitochondria-targeted cancer therapy, which specifically delivers drugs into the mitochondria, is a promising strategy for enhancing anticancer treatment efficiency. However, owing to their special double-layered membrane system and highly negative potentials, mitochondria remain a challenging target for therapeutic agents to reach and access. Polymeric nanoparticles exceed in cancer therapy ascribed to their unique features including ideal biocompatibility, readily design and synthesis, as well as flexible ligand decoration. Significant efforts have been put forward to develop mitochondria-targeted polymeric nanoparticles. In this review, we focused on the smart design of polymeric nanosystems for mitochondria targeting and summarized the current applications in improving cancer therapy.

Background: Stress disorders, such as post-traumatic stress disorder (PTSD), are attracting much attention. However, the relationship between traumatic stress and inflammation is rarely discussed.Subjects and Methods: As studies have linked PTSD to altered susceptibility to various diseases, such a psychiatric condition may lead to long-term systematic changes in physiological functions. We searched PubMed with the keywords “traumatic stress,” “stress disorders,” “post-traumatic stress disorder,” and “inflammation.”Results: Based on 65 previously published studies, we reviewed the long-term effects of PTSD, as well as traumatic events, on inflammatory function from both epidemiological and biological perspectives. Post-traumatic stress disorder is related to the immune response, including an increase in inflammatory factors and a reduction in anti-inflammatory factors. Additionally, it has been demonstrated that traumatic stress disorder and immune disease share a common genetic basis at the gene expression level.Conclusions: Understanding this relationship is of great significance for optimizing treatment plans for patients with PTSD.

Objective To assess the impact of the COVID-19 outbreak on cardiovascular disease (CVD) related mortality and hospitalisation.Design Community-based prospective cohort study.Setting The UK Biobank.Participants 421 372 UK Biobank participants who were registered in England and alive as of 1 January 2020.Primary and secondary outcome measures The primary outcome of interest was CVD-related death, which was defined as death with CVD as a cause in the death register. We retrieved information on hospitalisations with CVD as the primary diagnosis from the UK Biobank hospital inpatient data. The study period was 1 January 2020 to June 30 2020, and we used the same calendar period of the three preceding years as the reference period. In order to control for seasonal variations and ageing of the study population, standardised mortality/incidence ratios (SMRs/SIRs) with 95% CIs were used to estimate the relative risk of CVD outcomes during the study period, compared with the reference period.Results We observed a distinct increase in CVD-related deaths in March and April 2020, compared with the corresponding months of the three preceding years. The observed number of CVD-related deaths (n=218) was almost double in April, compared with the expected number (n=120) (SMR=1.82, 95% CI 1.58 to 2.07). In addition, we observed a significant decline in CVD-related hospitalisations from March onwards, with the lowest SIR observed in April (0.45, 95% CI 0.41 to 0.49).Conclusions There was a distinct increase in the number of CVD-related deaths in the UK Biobank population at the beginning of the COVID-19 outbreak. The shortage of medical resources for hospital care and stress reactions to the pandemic might have partially contributed to the excess CVD-related mortality, underscoring the need of sufficient healthcare resources and improved instructions to the public about seeking healthcare in a timely way.

The gut microbiome is a unique marker for cetaceans’ health status, and the microbiome composition of their skin wounds can indicate a potential infection from their habitat. Our study provides the first comparative analysis of the microbial communities from gut regions and skin wounds of an individual Indo-Pacific finless porpoise (Neophocaena phocaenoides). Microbial richness increased from the foregut to the hindgut with variation in the composition of microbes. Fusobacteria (67.51% ± 5.10%), Firmicutes (22.00% ± 2.60%), and Proteobacteria (10.47% ± 5.49%) were the dominant phyla in the gastrointestinal tract, while Proteobacteria (76.11% ± 0.54%), Firmicutes (22.00% ± 2.60%), and Bacteroidetes (10.13% ± 0.49%) were the dominant phyla in the skin wounds. The genera Photobacterium, Actinobacillus, Vibrio, Erysipelothrix, Tenacibaculum, and Psychrobacter, considered potential pathogens for mammals, were identified in the gut and skin wounds of the stranded Indo-Pacific finless porpoise. A comparison of the gut microbiome in the Indo-Pacific finless porpoise and other cetaceans revealed a possible species-specific gut microbiome in the Indo-Pacific finless porpoise. There was a significant difference between the skin wound microbiomes in terrestrial and marine mammals, probably due to habitat-specific differences. Our results show potential species specificity in the microbiome structure and a potential threat posed by environmental pathogens to cetaceans.

Background Gastric cancer is one of the most lethal tumors and is characterized by poor prognosis and lack of effective diagnostic or therapeutic biomarkers. The aim of this study was to find hub genes serving as biomarkers in gastric cancer diagnosis and therapy. Methods GSE66229 from Gene Expression Omnibus (GEO) was used as training set. Genes bearing the top 25% standard deviations among all the samples in training set were performed to systematic weighted gene co-expression network analysis (WGCNA) to find candidate genes. Then, hub genes were further screened by using the “least absolute shrinkage and selection operator” (LASSO) logistic regression. Finally, hub genes were validated in the GSE54129 dataset from GEO by supervised learning method artificial neural network (ANN) algorithm. Results Twelve modules with strong preservation were identified by using WGCNA methods in training set. Of which, five modules significantly related to gastric cancer were selected as clinically significant modules, and 713 candidate genes were identified from these five modules. Then, ADIPOQ, ARHGAP39, ATAD3A, C1orf95, CWH43, GRIK3, INHBA, RDH12, SCNN1G, SIGLEC11 and LYVE1 were screened as the hub genes. These hub genes successfully differentiated the tumor samples from the healthy tissues in an independent testing set through artificial neural network algorithm with the area under the receiver operating characteristic curve at 0.946. Conclusions These hub genes bearing diagnostic and therapeutic values, and our results may provide a novel prospect for the diagnosis and treatment of gastric cancer in the future.

Summary: Background: Psychiatric morbidities have been associated with a risk of severe infections through compromised immunity, health behaviours, or both. However, data are scarce on the association between multiple types of pre-pandemic psychiatric disorders and COVID-19. We aimed to assess the association between pre-pandemic psychiatric disorders and the subsequent risk of COVID-19 using UK Biobank. Methods: For this cohort analysis, we included participants from UK Biobank who were registered in England and excluded individuals who died before Jan 31, 2020, (the start of the COVID-19 outbreak in the UK) or had withdrawn from UK Biobank. Participants diagnosed with a psychiatric disorder before Jan 31 were included in the group of individuals with pre-pandemic psychiatric disorders, whereas participants without a diagnosis before the outbreak were included in the group of individuals without pre-pandemic psychiatric disorders. We used the Public Health England dataset, UK Biobank hospital data, and death registers to collect data on COVID-19 cases. To examine the relationship between pre-pandemic psychiatric disorders and susceptibility to COVID-19, we used logistic regression models to estimate odds ratios (ORs), controlling for multiple confounders and somatic comorbidities. Key outcomes were all COVID-19, COVID-19 specifically diagnosed in inpatient care, and COVID-19-related deaths. ORs were also estimated separately for each psychiatric disorder and on the basis of the number of pre-pandemic psychiatric disorders. As a positive disease control, we repeated analyses for hospitalisation for other infections. Findings: We included 421 014 UK Biobank participants in our study and assessed their COVID-19 status between Jan 31 and July 26, 2020. 50 809 participants were diagnosed with psychiatric disorders before the outbreak, while 370 205 participants had no psychiatric disorders. The mean age at outbreak was 67·80 years (SD 8·12). We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorders compared with that of individuals without such conditions. The fully adjusted ORs were 1·44 (95% CI 1·28–1·62) for All COVID-19 cases, 1·55 (1·34–1·78) for Inpatient COVID-19 cases, and 2·03 (1·59–2·59) for COVID-19-related deaths. We observed excess risk, defined as risk that increased with the number of pre-pandemic psychiatric disorders, across all diagnostic categories of pre-pandemic psychiatric disorders. We also observed an association between psychiatric disorders and elevated risk of hospitalisation due to other infections (OR 1·74, 95% CI 1·58–1·93). Interpretation: Our findings suggest that pre-existing psychiatric disorders are associated with an increased risk of COVID-19. These findings underscore the need for surveillance of and care for populations with pre-existing psychiatric disorders during the COVID-19 pandemic. Funding: National Natural Science Foundation of China.

Limited availability of the n-3 fatty acids EPA and DHA have led to an interest in better understanding of the n-3 biosynthetic pathway and its regulation. The biosynthesis of alpha-linolenic acid to EPA and DHA involves several complex reaction steps including desaturation-, elongation- and peroxisomal beta-oxidation enzymes. The aims of the present experiments were to gain more knowledge on how this biosynthesis is regulated over time by different doses and fatty acid combinations. Hepatocytes isolated from salmon were incubated with various levels and combinations of oleic acid, EPA and DHA. Oleic acid led to a higher expression of the Δ6 fatty acid desaturase (fad) genes Δ6fad_a, Δ6fad_b, Δ6fad_c and the elongase genes elovl2 compared with cells cultured in medium enriched with DHA. Further, the study showed rhythmic variations in expression over time. Levels were reached where a further increase in specific fatty acids given to the cells not stimulated the conversion further. The gene expression of Δ6fad_a_and Δ6fad_b responded similar to fatty acid treatment, suggesting a co-regulation of these genes, whereas Δ5fad and Δ6fad_c showed a different regulation pattern. EPA and DHA induced different gene expression patterns, especially of Δ6fad_a. Addition of radiolabelled alpha-linolenic acid to the hepatocytes confirmed a higher degree of elongation and desaturation in cells treated with oleic acid compared to cells treated with DHA. This study suggests a complex regulation of the conversion process of n-3 fatty acids. Several factors, such as that the various gene copies are differently regulated, the gene expression show rhythmic variations and gene expression only affected to a certain level, determines when you get the maximum conversion of the beneficial n-3 fatty acids.