Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma.

Background: Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechanism of co-morbidity. This study aims to explore the key genes, pathways, and immune cells that may link psoriasis and cervical squamous cell carcinoma (CESC). Methods: The cervical squamous cell carcinoma dataset (GSE63514) was downloaded from the Gene Expression Omnibus (GEO). Two psoriasis-related datasets (GSE13355 and GSE14905) were merged into one comprehensive dataset after removing batch effects. Differentially expressed genes were identified using Limma and co-expression network analysis (WGCNA), and machine learning random forest algorithm (RF) was used to screen the hub genes. We analyzed relevant gene enrichment pathways using GO and KEGG, and immune cell infiltration in psoriasis and CESC samples using CIBERSORT. The miRNA-mRNA and TFs-mRNA regulatory networks were then constructed using Cytoscape, and the biomarkers for psoriasis and CESC were determined. Potential drug targets were obtained from the cMAP database, and biomarker expression levels in hela and psoriatic cell models were quantified by RT-qPCR. Results: In this study, we identified 27 key genes associated with psoriasis and cervical squamous cell carcinoma. NCAPH, UHRF1, CDCA2, CENPN and MELK were identified as hub genes using the Random Forest machine learning algorithm. Chromosome mitotic region segregation, nucleotide binding and DNA methylation are the major enrichment pathways for common DEGs in the mitotic cell cycle. Then we analyzed immune cell infiltration in psoriasis and cervical squamous cell carcinoma samples using CIBERSORT. Meanwhile, we used the cMAP database to identify ten small molecule compounds that interact with the central gene as drug candidates for treatment. By analyzing miRNA-mRNA and TFs-mRNA regulatory networks, we identified three miRNAs and nine transcription factors closely associated with five key genes and validated their expression in external validation datasets and clinical samples. Finally, we examined the diagnostic effects with ROC curves, and performed experimental validation in hela and psoriatic cell models. Conclusions: We identified five biomarkers, NCAPH, UHRF1, CDCA2, CENPN, and MELK, which may play important roles in the common pathogenesis of psoriasis and cervical squamous cell carcinoma, furthermore predict potential therapeutic agents. These findings open up new perspectives for the diagnosis and treatment of psoriasis and squamous cell carcinoma of the cervix.

Association between visceral adipose tissue and asthma based on the NHANES and Mendelian randomization study.

BACKGROUND: Obesity is a crucial risk factor for asthma. Observational studies have examined the association between abdominal obesity and asthma symptoms. This study aimed to investigate the causal relationship between visceral adipose tissue (VAT) and asthma and its potential as an independent indicator. METHODS: This study utilized data from the National Health and Nutrition Examination Survey spanning 2011-8. Multivariable logistic regression and stratified variable selection were employed to identify associations between asthma and VAT. Moreover, a two-sample Mendelian randomization analysis, using 221 genetic variants as instrumental variables, was conducted to assess this relationship further. RESULTS: Our findings indicated that individuals with higher VAT levels were more likely to develop asthma. Visceral obesity remained a significant risk factor for asthma after adjusting for demographic characteristics. Genetic predictions suggest a positive association between VAT and an elevated risk of asthma (odds ratio [OR] = 1.393, 95% confidence interval [CI]: 1.266-1.534, and P = 1.43E-11). No significant polymorphisms were detected using the Mendelian randomization-Egger intercept test. CONCLUSIONS: This study presents potential evidence supporting the causal role of VAT in asthma development. Furthermore, the findings from the Mendelian randomization analysis further reinforce the relationship between VAT and asthma risk.

The causal relationship between psoriasis and chronic obstructive pulmonary disease: A bidirectional mendelian randomization study.

PURPOSE: Although many studies have investigated the association between psoriasis and chronic obstructive pulmonary disease (COPD), the causal relationship between psoriasis and COPD is still unknown. METHODS: We employed bidirectional Mendelian randomization to investigate the causal relationship between psoriasis and COPD. Genetic instruments for exposure were selected from two distinct genome-wide association study databases. Single nucleotide polymorphisms associated with exposures at the genome-wide significance level (p < 5 × 10^-8 ) and exhibiting low linkage disequilibrium (r^2  < 0.001) were chosen as instrumental variables. Causality was assessed using multiple MR methods, including Inverse-Variance Weighted (IVW), MR-Egger, Weighted Median, Simple Mode, and Weighted Mode. A significance level of p < 0.05 was considered statistically significant. Heterogeneity was examined using Cochran's Q test, and MR-Egger regression was employed to detect pleiotropy. The robustness and reliability of the results were further evaluated through leave-one-out analysis. RESULTS: We found a positive causal association between psoriasis and COPD [IVW: odds ratio (OR): 1.0006; p = 0.0056]. Heterogeneity and pleiotropy have not been discovered, so the results of the study are reliable. In the reverse analysis, no causal association between CPOD and psoriasis was found. CONCLUSION: Our findings revealed that psoriasis was associated with an elevated risk of COPD. However, no causal association between COPD and psoriasis was identified in our study.

Is Kidney Stone Associated with Thyroid Disease? The United States National Health and Nutrition Examination Survey 2007­2018

BACKGROUND: Kidney stones and thyroid disease are two common diseases in the general population, with multiple common risk factors. The associations between kidney stones and thyroid disease are unclear. AIM: This study aims to assess the association between 'once had a thyroid disease' and the odds of kidney stones. METHODS: Adult participants from the National Health and Nutrition Examination Survey (NHANES) 2007-2018 with reliable kidney stone and thyroid disease data were included. Adjusting for age, gender, race, education level, and marital status, diabetes, hypertension, gout, angina pectoris, stroke, and asthma, logistic regression was used to examine the relationship between kidney stones and thyroid illness. RESULTS: Using stratified analysis, the association between thyroid illness and kidney stones was investigated further. Among the participants, 4.9% had kidney stones, and 10.1% had thyroid disease. Kidney stone was associated with thyroid disease (OR=1.441, (95% CI:1.294-1.604), p <0.01), which remained significant (OR=1.166, (95% CI:1.041-1.305), p <0.01) after adjustments with age, gender, race, education level and marital status, diabetes, hypertension, gout, angina pectoris, stroke, and asthma. Stratified by blood lead, blood cadmium, and blood urea nitrogen levels in the human body, the odds of kidney stones still increased with once having a previous thyroid disease. CONCLUSIONS: In this large nationally representative survey over 10 years, kidney stone was strongly associated with thyroid disease. In this cross-sectional study, we explored the association between thyroid disease and kidney stones, which may help clinicians intervene in them early.

Objective Depression Detection Using EEG and Eye Movement Signals Induced by Oil Paintings.

Depression is a mental disorder characterized by persistent sadness and loss of interest, which has become one of the leading causes of disability worldwide. There are currently no objective diagnostic standards for depression in clinical practice. Previous studies have shown that depression causes both brain abnormalities and behavioral disorders. In this study, both electroencephalography (EEG) and eye movement signals were used to objectively detect depression. By presenting 40 carefully selected oil paintings-20 positive and 20 negative-as stimuli, we were able to successfully evoke emotions in 48 depressed patients (DPs) and 40 healthy controls (HCs) from three centers. We then used Transformer, a deep learning model, to conduct emotion recognition and depression detection. The experimental results demonstrate that: a) Transformer achieves the best accuracies of 89.21% and 92.19% in emotion recognition and depression detection, respectively; b) The HC group has higher accuracies than the DP group in emotion recognition for both subject-dependent and subject-independent experiments; c) The neural pattern differences do exist between DPs and HCs, and we find the consistent asymmetry of the neural patterns in DPs; d) For depression detection, using single oil painting achieves the best accuracies, and using negative oil paintings has higher accuracies than using positive oil paintings. These findings suggest that EEG and eye movement signals induced by oil paintings can be used to objectively identify depression.

Identifying sex differences in EEG-based emotion recognition using graph convolutional network with attention mechanism.

OBJECTIVE: Sex differences in emotions have been widely perceived via self-reports, peripheral physiological signals and brain imaging techniques. However, how sex differences are reflected in the EEG neural patterns of emotions remains unresolved. In this paper, we detect sex differences in emotional EEG patterns, investigate the consistency of such differences in various emotion datasets across cultures, and study how sex as a factor affects the performance of EEG-based emotion recognition models. APPROACH: We thoroughly assess sex differences in emotional EEG patterns on five public datasets, including SEED, SEED-IV, SEED-V, DEAP and DREAMER, systematically examine the sex-specific EEG patterns for happy, sad, fearful, disgusted and neutral emotions, and implement deep learning models for sex-specific emotion recognition. MAIN RESULTS: (1) Sex differences exist in various emotion types and both Western and Eastern cultures; (2) The emotion patterns of females are more stable than those of males, and the patterns of happiness from females are in sharp contrast with the patterns of sadness, fear and disgust, while the energy levels are more balanced for males; (3) The key features for emotion recognition are mainly located at the frontal and temporal sites for females and distributed more evenly over the whole brain for males, and (4) The same-sex emotion recognition models outperform the corresponding cross-sex models. SIGNIFICANCE: These findings extend efforts to characterize sex differences in emotional brain activation, provide new physiological evidence for sex-specific emotion processing, and reinforce the message that sex differences should be carefully considered in affective research and precision medicine.

Light-Reinforced Key Intermediate for Anticoking To Boost Highly Durable Methane Dry Reforming over Single Atom Ni Active Sites on CeO2.

Dry reforming of methane (DRM) has been investigated for more than a century; the paramount stumbling block in its industrial application is the inevitable sintering of catalysts and excessive carbon emissions at high temperatures. However, the low-temperature DRM process still suffered from poor reactivity and severe catalyst deactivation from coking. Herein, we proposed a concept that highly durable DRM could be achieved at low temperatures via fabricating the active site integration with light irradiation. The active sites with Ni-O coordination (NiSA/CeO2) and Ni-Ni coordination (NiNP/CeO2) on CeO2, respectively, were successfully constructed to obtain two targeted reaction paths that produced the key intermediate (CH3O*) for anticoking during DRM. In particular, the operando diffuse reflectance infrared Fourier transform spectroscopy coupling with steady-state isotopic transient kinetic analysis (operando DRIFTS-SSITKA) was utilized and successfully tracked the anticoking paths during the DRM process. It was found that the path from CH3* to CH3O* over NiSA/CeO2 was the key path for anticoking. Furthermore, the targeted reaction path from CH3* to CH3O* was reinforced by light irradiation during the DRM process. Hence, the NiSA/CeO2 catalyst exhibits excellent stability with negligible carbon deposition for 230 h under thermo-photo catalytic DRM at a low temperature of 472 °C, while NiNP/CeO2 shows apparent coke deposition behavior after 0.5 h in solely thermal-driven DRM. The findings are vital as they provide critical insights into the simultaneous achievement of low-temperature and anticoking DRM process through distinguishing and directionally regulating the key intermediate species.

Electrocatalytic Mechanism of Defect in Spinels for Water and Organics Oxidation.

Spinels display promising electrocatalytic ability for oxygen evolution reaction (OER) and organics oxidation reaction because of flexible structure, tunable component, and multifold valence. Unfortunately, limited exposure of active sites, poor electronic conductivity, and low intrinsic ability make the electrocatalytic performance of spinels unsatisfactory. Defect engineering is an effective method to enhance the intrinsic ability of electrocatalysts. Herein, the recent advances in defect spinels for OER and organics electrooxidation are reviewed. The defect types that exist in spinels are first introduced. Then the catalytic mechanism and dynamic evolution of defect spinels during the electrochemical process are summarized in detail. Finally, the challenges of defect spinel electrocatalysts are brought up. This review aims to deepen the understanding about the role and evolution of defects in spinel for electrochemical water/organics oxidation and provide a significant reference for the design of efficient defect spinel electrocatalysts.

Risk Factor Analysis and a Predictive Model of Postoperative Depressive Symptoms in Elderly Patients Undergoing Video-Assisted Thoracoscopic Surgery.

Among the elderly, depression is one of the most common mental disorders, which seriously affects their physical and mental health and quality of life, and their suicide rate is particularly high. Depression in the elderly is strongly associated with surgery. In this study, we aimed to explore the risk factors and establish a predictive model of depressive symptoms 1 month after video-assisted thoracoscopic surgery (VATS) in elderly patients. The study participants included 272 elderly patients (age > 65 years) undergoing VATS from April 2020 to May 2021 at 1 of 18 medical centers in China. The patients were divided into a depression group and a nondepression group according to the Chinese version of the nine-item Patient Health Questionnaire (PHQ-9). The patients' pre- and postoperative characteristics and questionnaires were collected and compared. Then, binary logistic regression was used to determine the risk factors that affect postoperative depressive symptoms, and the predictive model was constructed. The prediction efficiency of the model was evaluated by drawing the receiver operating characteristic curve (ROC), and the area under the curve (AUC) was calculated to evaluate the value of the predictive model. Among all of the included patients, 16.54% (45/272) suffered from depressive symptoms after VATS. The results of the univariate analysis showed that body mass index (BMI), chronic pain, leukocyte count, fibrinogen levels, prothrombin time, ASA physical status, infusion volume, anxiety, sleep quality, and postoperative pain were related to postoperative depressive symptoms (all p < 0.05). The results of multivariate logistic regression analysis showed that a high fibrinogen level (OR = 2.42), postoperative anxiety (OR = 12.05), poor sleep quality (OR = 0.61), and pain (OR = 2.85) were risk factors of postoperative depressive symptoms. A predictive model was constructed according to the regression coefficient of each variable, the ROC curve was drawn, and the AUC value was calculated to be 0.889. The prediction model may help medical personnel identify older patients at risk of developing depressive disorders associated with VATS and may be useful for clinical purposes.

The adenosinergic machinery in cancer: In-tandem insights from basic mechanisms to therapy.

Extracellular adenosine (eADO) signaling has emerged as an increasingly important regulator of immune responses, including tumor immunity. eADO is mainly produced from extracellular ATP (eATP) hydrolysis. eATP is rapidly accumulated in the extracellular space following cell death or cellular stress triggered by hypoxia, nutrient starvation, or inflammation. eATP plays a pro-inflammatory role by binding and activating the P2 purinergic receptors (P2X and P2Y), while eADO has been reported in many studies to mediate immunosuppression by activating the P1 purinergic receptors (A1, A2A, A2B, and A3) in diverse immune cells. Consequently, the hydrolysis of eATP to eADO alters the immunosurveillance in the tumor microenvironment (TME) not only by reducing eATP levels but also by enhancing adenosine receptor signaling. The effects of both P1 and P2 purinergic receptors are not restricted to immune cells. Here we review the most up-to-date understanding of the tumor adenosinergic system in all cell types, including immune cells, tumor cells, and stromal cells in TME. The potential novel directions of future adenosinergic therapies in immuno-oncology will be discussed.

Assessment of lake area in response to climate change at varying elevations: A case study of Mt. Tianshan, Central Asia.

Changes in lake area (water surface area) are often considered accurate and sensitive representations of climate change. However, the role that elevation plays in this dynamic is somewhat unclear; studies remain inconclusive as to whether lake responses are consistent across elevation gradients. Here, we used Landsat and keyhole satellite images to quantify lake area changes from the 1960s to 2020 at different elevations in Central Asia's Tianshan Mountains and relate them to both climatic and anthropogenic factors. The results revealed that all low-elevation lakes showed a decreasing trend, and the total area of all monitored low-elevation lakes was reduced by 18.50 %. The total area of the mid-elevation lakes decreased by 0.16 %, while the total area of the high-elevation glacial lakes increased by 4.35 %. Lakes are recharged by a variety of influxes including glacial meltwater and precipitation. Notably, human activities (urban and agricultural water consumption) were the dominant factors in the shrinkage of low-elevation lakes. Climatic factors were the main driving factors of mid-elevation lake changes, and these lakes appeared to be more sensitive to temperature changes than lakes at other elevations. In addition, significant warming dominated area changes in high-elevation proglacial and unconnected glacial lakes. Overall, those results emphasized that when using lakes to reconstruct paleoclimates or predict lake evolution, it is necessary to consider how elevation gradients and recharge types may affect lake sensitivity to variations in climatic and anthropogenic activity.

Exploring Sex Differences in Key Frequency Bands and Channel Connections for EEG-based Emotion Recognition.

Previous studies have demonstrated the existence of sex differences in emotion recognition by comparing the performance of same-sex and cross-sex training strategies. However, the EEG properties behind the sex differences have not been fully explored. To fill this research gap, we aim to investigate the sex differences in key frequency bands and channel connections of EEG signals. The single-modality attentive simple graph convolutional network (ASGC) is applied to three datasets SEED, SEED-IV and SEED-V under subject-dependence conditions. The classification rates are 90.86 ±4.84%, 83.14 ± 8.84% and 78.33±7.83%, respectively. The adjacency matrices learned by ASGC indicate that females and males have similar channel-connection patterns, but the degree of importance of channel connections varies by sex. Additionally, by comparing the classification results of 5 frequency bands, we find that males and females represent similar frequency band characteristics, i.e., high-frequency bands achieve better performance, indicating that these frequency bands are more related to emotion processing. Finally, we conduct the cross-subject experiment using ASGC and find that the same-sex strategy outperforms the cross-sex strategy, which is consistent with previous studies. The results also imply that males may be more suitable for sex generalization. However, this finding needs the support of more samples and advanced algorithms.

Transabdominal Ultrasound Evaluation of Pancreaticobiliary Maljunction in Children.

ABSTRACT: The development of high-frequency ultrasound made the diagnosis of pancreaticobiliary maljunction (PBM) possible. However, no study has been performed to clarify the sensitivity and specificity of transabdominal ultrasound (TAUS) in the diagnosis of PBM. The purpose of this study was to evaluate the accuracy of TAUS in the diagnosis of pediatric PBM and to assess factors that may influence the accuracy of ultrasound. This was a prospective study and 43 patients with suspected PBM were enrolled. All of these patients underwent TAUS examination to detect the pancreaticobiliary ductal union. Final diagnoses were determined by endoscopic retrograde cholangiopancreatography or intraoperative cholangiography. Sensitivity and specificity were calculated. Fisher exact test was used to analyze the difference of sonographic features between false-negative group and true-positive group. Transabdominal ultrasound demonstrated 77.4% (95% confidence interval, 58.5%-89.7%) sensitivity and 100% (95% confidence interval, 69.9%-100%) specificity for PMB diagnosis. In the false-negative group, infant patients (71.4% vs 16.7%, P = 0.012), cystic dilatation of the common bile duct (CBD) (71.4% vs 16.7%, P = 0.012), and stenosis of the distal CBD (71.4% vs 16.7%, P = 0.012) were more frequently observed than in the true-positive group. On the other hand, the true-positive group showed a higher incidence of protein plugs than the false-negative group (62.5% vs 0%, P = 0.007). Transabdominal ultrasound may serve as a potential alternative detection modality for pediatric patients with suspected PBM. Nondetection of the anomaly may be attributed to factors, such as younger age, cystic dilatation of the CBD, and stenosis of the distal CBD.

Realizable accessibility: evaluating the reliability of public transit accessibility using high-resolution real-time data.

The widespread availability of high spatial and temporal resolution public transit data is improving the measurement and analysis of public transit-based accessibility to crucial community resources such as jobs and health care. A common approach is leveraging transit route and schedule data published by transit agencies. However, this often results in accessibility overestimations due to endemic delays due to traffic and incidents in bus systems. Retrospective real-time accessibility measures calculated using real-time bus location data attempt to reduce overestimation by capturing the actual performance of the transit system. These measures also overestimate accessibility since they assume that riders had perfect information on systems operations as they occurred. In this paper, we introduce realizable real-time accessibility based on space-time prisms as a more conservative and realistic measure. We, moreover, define accessibility unreliability to measure overestimation of schedule-based and retrospective accessibility measures. Using high-resolution General Transit Feed Specification real-time data, we conduct a case study in the Central Ohio Transit Authority bus system in Columbus, Ohio, USA. Our results prove that realizable accessibility is the most conservative of the three accessibility measures. We also explore the spatial and temporal patterns in the unreliability of both traditional measures. These patterns are consistent with prior findings of the spatial and temporal patterns of bus delays and risk of missing transfers. Realizable accessibility is a more practical, conservative, and robust measure to guide transit planning.

Major adverse kidney events within 30 days in patients with acute pancreatitis: a tertiary-center cohort study.

BACKGROUND: To evaluate the event rate of major adverse kidney events within 30 days (MAKE30) in acute pancreatitis (AP) and its potential risk factors. METHODS: A retrospective analysis of a tertiary center data on all AP patients admitted within 72 h after onset of abdominal pain between June 2015 and June 2019 was conducted. MAKE30 - a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD) - and its individual components were retrieved at discharge or 30 days. Logistic regression analysis was used to assess the risk factors for MAKE30. RESULTS: 295 patients were enrolled and 16% experienced MAKE30. For individual components, the incidence was 3% for death, 15% for new RRT, and 5% for PRD. In multivariate logistic regression analysis, hyperchloremia at admission [OR = 8.38 (1.07-65.64); P = 0.043] and SOFA score [OR 1.63 (1.18-2.26); P = 0.003] were independent risk factors in predicting MAKE30. Further analysis showed that patients with hyperchloremia had more requirements of RRT (57% vs. 10%, P < 0.001), more PRD (14% vs. 4%, P = 0.034). CONCLUSION: MAKE30 is a common event in AP patients. Hyperchloremia and SOFA score at admission were two independent risk factors for MAKE30.

Methods to study phosphoinositide regulation of ion channels.

Ion channel are embedded in the lipid bilayers of biological membranes. Membrane phospholipids constitute a barrier to ion movement, and they have been considered for a long time as a passive environment for channel proteins. Membrane phospholipids, however, do not only serve as a passive amphipathic environment, but they also modulate channel activity by direct specific lipid-protein interactions. Phosphoinositides are quantitatively minor components of biological membranes, and they play roles in many cellular functions, including membrane traffic, cellular signaling and cytoskeletal organization. Phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] is mainly found in the inner leaflet of the plasma membrane. Its role as a potential ion channel regulator was first appreciated over two decades ago and by now this lipid is a well-established cofactor or regulator of many different ion channels. The past two decades witnessed the steady development of techniques to study ion channel regulation by phosphoinositides with progress culminating in recent cryoEM structures that allowed visualization of how PI(4,5)P2 opens some ion channels. This chapter will provide an overview of the methods to study regulation by phosphoinositides, focusing on plasma membrane ion channels and PI(4,5)P2.

Response of altitudinal vegetation belts of the Tianshan Mountains in northwestern China to climate change during 1989-2015.

Within the mountain altitudinal vegetation belts, the shift of forest tree lines and subalpine steppe belts to high altitudes constitutes an obvious response to global climate change. However, whether or not similar changes occur in steppe belts (low altitude) and nival belts in different areas within mountain systems remain undetermined. It is also unknown if these, responses to climate change are consistent. Here, using Landsat remote sensing images from 1989 to 2015, we obtained the spatial distribution of altitudinal vegetation belts in different periods of the Tianshan Mountains in Northwestern China. We suggest that the responses from different altitudinal vegetation belts to global climate change are different. The changes in the vegetation belts at low altitudes are spatially different. In high-altitude regions (higher than the forest belts), however, the trend of different altitudinal belts is consistent. Specifically, we focused on analyses of the impact of changes in temperature and precipitation on the nival belts, desert steppe belts, and montane steppe belts. The results demonstrated that the temperature in the study area exhibited an increasing trend, and is the main factor of altitudinal vegetation belts change in the Tianshan Mountains. In the context of a significant increase in temperature, the upper limit of the montane steppe in the eastern and central parts will shift to lower altitudes, which may limit the development of local animal husbandry. The montane steppe in the west, however, exhibits the opposite trend, which may augment the carrying capacity of pastures and promote the development of local animal husbandry. The lower limit of the nival belt will further increase in all studied areas, which may lead to an increase in surface runoff in the central and western regions.

Comparison of Prevalence and Risk Factors of PTSS Between Chinese Patients With Depression and Non-depressed Controls During COVID-19 Outbreak.

Background: COVID-19 pandemic is a traumatic event all over the world, and may lead to post-traumatic stress symptom (PTSS) in different population who are under the threat of novel corona virus. Therefore, the aim of our study was to compare the prevalence and risk factors of PTSS between Chinese patients with depression and non-depressed controls during the COVID-19 outbreak. Methods: 437 depressed patients and 2,940 non-depressed controls were enrolled in this cross-sectional study between February 14 and May 9, 2020.The Impact of Events Scale-Revised (IES-R), Zung Self-Rating Depression Scale (SDS), Zung Self-Rating Anxiety Scale (SAS) and Pittsburgh Sleep Quality Index (PSQI) were used to evaluate the psychological status of all the participants. Results: The prevalence of PTSS (IES-R ≥ 33) in depressed patients (45.08%) was higher than that in non-depressed controls (5.31%). Patients with depression were 16 times more likely to suffer from PTSS than those without depression. Correlation analyses showed that the IES-R total score was positively correlated with SDS, SAS, and PSQI scores in both depressed and non-depressed groups (Bonferroni corrected all p < 0.001). Multiple linear regression analysis showed that SAS score, and PSQI score were independently associated with IES-R total score in both depression and non-depression groups. In depressed patients, education level and duration of media exposure to COVID-19 were positively associated with PTSS, while in the non-depressed group, subjects who were married, in the 31-50 year group or with higher SDS score were more likely to develop PTSS. Conclusions: These results indicate that the prevalence rate of PTSS in patients with depression is very higher than that in subjects without depression. PTSS are associated with a number of socio-demographic and clinical variables.

The impacts of COVID-19 pandemic on public transit demand in the United States.

The COVID-19 pandemic and related restrictions led to major transit demand decline for many public transit systems in the United States. This paper is a systematic analysis of the dynamics and dimensions of this unprecedented decline. Using transit demand data derived from a widely used transit navigation app, we fit logistic functions to model the decline in daily demand and derive key parameters: base value, the apparent minimal level of demand and cliff and base points, representing the initial date when transit demand decline began and the final date when the decline rate attenuated. Regression analyses reveal that communities with higher proportions of essential workers, vulnerable populations (African American, Hispanic, Female, and people over 45 years old), and more coronavirus Google searches tend to maintain higher levels of minimal demand during COVID-19. Approximately half of the agencies experienced their decline before the local spread of COVID-19 likely began; most of these are in the US Midwest. Almost no transit systems finished their decline periods before local community spread. We also compare hourly demand profiles for each system before and during COVID-19 using ordinary Procrustes distance analysis. The results show substantial departures from typical weekday hourly demand profiles. Our results provide insights into public transit as an essential service during a pandemic.

Prevalence, risk factors and clinical correlates of depression in quarantined population during the COVID-19 outbreak.

BACKGROUND: The COVID-19 outbreak has brought tremendous psychological pressure to the general population, which may lead to depression. Therefore, this study aim to evaluate the prevalence and clinical correlates of depressive symptoms in the general population quarantined during the COVID-19 outbreak in Shenzhen. METHODS: 2237 quarantined general individuals participated in this cross-sectional study from February 14 to March 4, 2020, during their 14 days quarantine. They completed the Zung's Self-Rating Depression Scale (SDS) for depression, Zung's self-rating anxiety scale (SAS) for anxiety, the Pittsburgh Sleep Quality Index (PSQI) for sleep quality, and the Impact of Events Scale-Revised (IES-R) for post-traumatic stress symptoms (PTSS). RESULTS: The prevalence of depressive symptom was 6.21% in quarantined individuals. The depressed group were younger, less married and educated, and had higher SAS, PSQI, IES-R total scores (all p<0.05), as well as more avoidance, intrusion and hyperarousal symptoms than the non-depressed group. Correlation analysis showed significant correlations between SDS score and the following parameters: age, marriage, education, SAS, PSQI, IES-R total and its three subscale scores (Bonferroni corrected all p<0.05). Further multiple regression indicated that age, marriage, education, SAS, PSQI, IES-R total score, Avoidance and Hyperarousal factor were independent predictors of depressive symptom. LIMITATIONS: This study adopted a cross-sectional design and used self-report questionnaires. CONCLUSIONS: Our results suggest an elevated prevalence of depressive symptom in quarantined general individuals in Shenzhen. Some demographic and clinical variables were associated with depressive symptoms.