The relationships among Taiwanese youth's polychronicity, multitasking behavior and perceived learning performance in online learning.

Background: The advancement of digital technology implies the importance of polychronic learning. Since polychronicity is not equivalent to multitasking behavior, they need to be considered separately. However, less research has been explored on how polychronicity is related to multitasking behavior in the educational field. Objective: To explore the relationships among polychronicity, multitasking behavior and learning performance (including knowledge acquisition and learning satisfaction) in an online learning environment. Methods: The relationship among variables was analyzed from 865 responses obtained from a questionnaire survey, and independent sample t tests and SEM analysis were used to examine the research hypotheses. Results: College students showed a higher frequency of multitasking behavior, time tangibility and scheduling preference, and learning satisfaction in multitasking online learning environments than high school students. Additionally, college students were different from high school students on the paths of involvement with people to multitasking behavior (Δ χ 2= 5.42, p = 0.02) and scheduling preference to learning satisfaction (Δχ 2 = 9.54, p = 0.002). Conclusion: The relationship among polychronicity, multitasking behavior and perceived learning performance in an online learning environment varies by student educational stage.

Genetic Underpinnings and Audiological Characteristics in Children With Unilateral Sensorineural Hearing Loss.

OBJECTIVE: Unilateral sensorineural hearing loss (USNHL) is a condition commonly encountered in otolaryngology clinics. However, its molecular pathogenesis remains unclear. This study aimed to investigate the genetic underpinnings of childhood USNHL and analyze the associated audiological features. STUDY DESIGN: Retrospective analysis of a prospectively recruited cohort. SETTING: Tertiary referral center. METHODS: We enrolled 38 children with USNHL between January 1, 2018, and December 31, 2021, and performed physical, audiological, imaging, and congenital cytomegalovirus (cCMV) examinations as well as genetic testing using next-generation sequencing (NGS) targeting 30 deafness genes. The audiological results were compared across different etiologies. RESULTS: Causative genetic variants were identified in 8 (21.1%) patients, including 5 with GJB2 variants, 2 with PAX3 variants, and 1 with the EDNRB variant. GJB2 variants were found to be associated with mild-to-moderate USNHL in various audiogram configurations, whereas PAX3 and EDNRB variants were associated with profound USNHL in flat audiogram configurations. In addition, whole-genome sequencing and extended NGS targeting 213 deafness genes were performed in 2 multiplex families compatible with autosomal recessive inheritance; yet no definite causative variants were identified. Cochlear nerve deficiency and cCMV infection were observed in 9 and 2, respectively, patients without definite genetic diagnoses. CONCLUSION: Genetic underpinnings can contribute to approximately 20% of childhood USNHL, and different genotypes are associated with various audiological features. These findings highlight the utility of genetic examinations in guiding the diagnosis, counseling, and treatment of USNHL in children.

Clinical use of mood stabilizers beyond treatment for bipolar disorder: The REAP-MS study.

OBJECTIVE: Mood stabilizers are psychotropic drugs mainly used to treat bipolar disorder in the acute phase or for maintenance therapy to prevent relapse. In clinical practice, mood stabilizers are commonly prescribed for conditions other than bipolar disorder. This study investigated the distribution of mood stabilizer prescriptions for different psychiatric diagnoses and studied differences in the drugs, dosage, and plasma concentration in 10 Asian countries including Taiwan, South Korea, Malaysia, China, Thailand, India, Pakistan, Singapore, Indonesia, and Myanmar. METHODS: Patients prescribed mood stabilizers (lithium, carbamazepine, valproic acid, or lamotrigine) for a psychiatric condition other than bipolar disorder (codes F31.0-F31.9 in the International Classification of Diseases, 10th Edition, Clinical Modification) were recruited through convenience sampling. A website-based data entry system was used for data collection. RESULTS: In total, 1557 psychiatric patients were enrolled. Schizophrenia, schizotypal, delusional, and other non-mood psychotic disorders (F20-F29, 55.8 %) was the most common diagnosis, followed by non-bipolar mood disorders (F30, F31- F39, 25.3 %), organic mental disorder (F00-F09, 8.8 %), mental retardation (F70-F79, 5.8 %) and anxiety, dissociative, stress-related, somatoform and other nonpsychotic mental disorders (F40-F48, 4.4 %). The most frequently targeted symptoms (>20 %) were irritability (48 %), impulsivity (32.4 %), aggression (29.2 %), anger (20.8 %), and psychosis (24.1 %). Valproic acid was the most frequently used medication. CONCLUSIONS: Clinicians typically prescribe mood stabilizers as empirically supported treatment to manage mood symptoms in patients with diagnoses other than bipolar disorders, though there is on official indication for these disorders. The costs and benefits of this add-on symptomatic treatment warrant further investigation.

Epidemiological characteristics of respiratory viruses in hospitalized children during the COVID-19 pandemic in southwestern China.

Background: Multinational studies have reported that the implementation of nonpharmaceutical interventions (NPIs) to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission coincided with the decline of other respiratory viruses, such as influenza viruses and respiratory syncytial virus. Objective: To investigate the prevalence of common respiratory viruses during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Respiratory specimens of children with lower respiratory tract infections (LRTIs) hospitalized at the Children's Hospital of Chongqing Medical University from January 1, 2018 to December 31, 2021 were collected. Seven common pathogens, including respiratory syncytial virus (RSV), adenovirus (ADV), influenza virus A and B (Flu A, Flu B), and parainfluenza virus types 1-3 (PIV1-3), were detected by a multiplex direct immunofluorescence assay (DFA). Demographic data and laboratory test results were analyzed. Results: 1) A total of 31,113 children with LRTIs were enrolled, including 8141 in 2018, 8681 in 2019, 6252 in 2020, and 8059 in 2021.The overall detection rates decreased in 2020 and 2021 (P < 0.001). The detection rates of RSV, ADV, Flu A, PIV-1, and PIV-3 decreased when NPIs were active from February to August 2020, with Flu A decreasing most predominantly, from 2.7% to 0.3% (P < 0.05). The detection rates of RSV and PIV-1 resurged and even surpassed the historical level of 2018-2019, while Flu A continued decreasing when NPIs were lifted (P < 0.05). 2) Seasonal patterns of Flu A completely disappeared in 2020 and 2021. The Flu B epidemic was observed until October 2021 after a long period of low detection in 2020. RSV decreased sharply after January 2020 and stayed in a nearly dormant state during the next seven months. Nevertheless, the detection rates of RSV were abnormally higher than 10% in the summer of 2021. PIV-3 decreased significantly after the COVID-19 pandemic; however, it atypically surged from August to November 2020. Conclusion: The NPIs implemented during the COVID-19 pandemic affected the prevalence and seasonal patterns of certain viruses such as RSV, PIV-3, and influenza viruses. We recommend continuous surveillance of the epidemiological and evolutionary dynamics of multiple respiratory pathogens, especially when NPIs are no longer necessary.

A Machine Learning Algorithm for Predicting 6-Week Survival in Spinal Metastasis: An External Validation Study Using 2,768 Taiwanese Patients.

INTRODUCTION: There are predictive algorithms for predicting 3-month and 1-year survival in patients with spinal metastasis. However, advance in surgical technique, immunotherapy, and advanced radiation therapy has enabled shortening of postoperative recovery, which returns dividends to the overall quality-adjusted life-year. As such, the Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) was proposed to predict 6-week survival in patients with spinal metastasis, whereas its utility for patients treated with nonsurgical treatment was untested externally. This study aims to validate the survival prediction of the 6-week SORG-MLA for patients with spinal metastasis and provide the measurement of model consistency (MC). METHODS: Discrimination using area under the receiver operating characteristic curve, calibration, Brier score, and decision curve analysis were conducted to assess the model's performance in the Taiwanese-based cohort. MC was also applied to detect the proportion of paradoxical predictions among 6-week, 3-month, and 1-year survival predictions. The long-term prognosis should not be better than the shorter-term prognosis in that of an individual. RESULTS: The 6-week survival rate was 84.2%. The SORG-MLA retained good discrimination with an area under the receiver operating characteristic curve of 0.78 (95% confidence interval, 0.75 to 0.80) and good prediction accuracy with a Brier score of 0.11 (null model Brier score 0.13). There is an underestimation of the 6-week survival rate when the predicted survival rate is less than 50%. Decision curve analysis showed that the model was suitable for use over all threshold probabilities. MC showed suboptimal consistency between 6-week and 90-day survival prediction (78%). CONCLUSIONS: The results of this study supported the utility of the algorithm. The online tool (https://sorg-apps.shinyapps.io/spinemetssurvival/) can be used by both clinicians and patients in informative decision-making discussion before management of spinal metastasis.

Symptom burden survey and symptom clusters in patients with cervical cancer: a cross-sectional survey.

PURPOSE: The purpose of this study is to determine the incidence and severity of symptoms of patients with cervical cancer within 6 months after radiotherapy and chemotherapy, form a symptom burden report, evaluate the distribution characteristics of symptoms, identify symptom clusters, and provide a basis for clinical doctors and nurses to improve the symptom management of patients with cervical cancer after radiotherapy and chemotherapy. METHODS: The patients with cervical cancer within 6 months after radiotherapy and chemotherapy were recruited to investigate their symptom burden. Exploratory factor analysis was used to identify symptom clusters. RESULTS: A total of 250 patients participated in the study. The study found that the most common symptom among the 40 symptoms was fatigue, and the most serious symptom was nocturia. Based on the occurrence rate and severity of symptoms, nine symptom clusters were identified, including psycho-emotion-related symptom cluster, pain-disturbed sleep-related symptom cluster, menopausal symptom cluster, tinnitus-dizziness-related symptom cluster, urinary-related symptom cluster, dry mouth-bitter taste-related symptom cluster, intestinal-related symptom cluster, memory loss-numbness-related symptom cluster, and emaciation-related symptom cluster. The three most serious symptom clusters are pain-disturbed sleep-related symptom cluster, urinary-related symptom cluster, and memory loss-numbness-related symptom cluster. CONCLUSION: The symptoms of patients with cervical cancer within 6 months after radiotherapy and chemotherapy are complex, and nine symptom clusters can be identified according to the incidence and severity of symptoms. We can find the potential biological mechanism of each symptom cluster through the discussion of previous mechanism research and clinical research. The number of symptom clusters and the number of symptoms within the symptom cluster are closely related to the symptom evaluation scale selected for the study. Therefore, the symptom cluster study urgently needs a targeted symptom evaluation scale that can comprehensively reflect the patient's condition.

Fretting corrosion behavior of Ti6Al4V alloy against zirconia-toughened alumina ceramic in simulated body fluid.

The fretting corrosion at the head-neck interface of artificial hip joints is an important reason for the failure of prostheses. The Ti6Al4V alloy-zirconia-toughened alumina (ZTA) ceramic combination has been widely used to make the head and neck of artificial hip joints. In this study, its fretting corrosion behavior in simulated body fluid was studied by electrochemical monitoring, surface morphology characterization, and chemical composition analysis. A running condition fretting map (RCFM) of load and displacement was established, including three regimes, namely partial slip regime (PSR), mixed fretting regime (MFR), and gross slip regime (GSR). The friction dissipation energy increased gradually from the PSR to MFR and GSR. In the PSR, the damage mechanisms were slight abrasive wear and tribocorrosion at the edge of contact area, as well as extremely slight adhesive wear at the center. In the MFR, the damage mechanisms were mainly adhesive wear, abrasive wear, and corrosive wear. In the GSR, the damage mechanism was serious abrasive wear, fatigue wear, and corrosive wear combined with slight adhesive wear. Finally, an ion-concentration map was created, displaying the material-loss transition of different displacements and loads. The material loss increased with the increased displacement, and increased first and then decreased with the increased load.

Reducing lipid peroxidation attenuates stress-induced susceptibility to herpes simplex virus type 1.

Psychological stress increases the susceptibility to herpes simplex virus type 1 (HSV-1) infection. There is no effective intervention due to the unknown pathogenesis mechanisms. In this study we explored the molecular mechanisms underlying stress-induced HSV-1 susceptibility and the antiviral effect of a natural compound rosmarinic acid (RA) in vivo and in vitro. Mice were administered RA (11.7, 23.4 mg·kg-1·d-1, i.g.) or acyclovir (ACV, 206 mg·kg-1·d-1, i.g.) for 23 days. The mice were subjected to restraint stress for 7 days followed by intranasal infection with HSV-1 on D7. At the end of RA or ACV treatment, mouse plasma samples and brain tissues were collected for analysis. We showed that both RA and ACV treatment significantly decreased stress-augmented mortality and alleviated eye swelling and neurological symptoms in HSV-1-infected mice. In SH-SY5Y cells and PC12 cells exposed to the stress hormone corticosterone (CORT) plus HSV-1, RA (100 µM) significantly increased the cell viability, and inhibited CORT-induced elevation in the expression of viral proteins and genes. We demonstrated that CORT (50 µM) triggered lipoxygenase 15 (ALOX15)-mediated redox imbalance in the neuronal cells, increasing the level of 4-HNE-conjugated STING, which impaired STING translocation from the endoplasmic reticulum to Golgi; the abnormality of STING-mediated innate immunity led to HSV-1 susceptibility. We revealed that RA was an inhibitor of lipid peroxidation by directly targeting ALOX15, thus RA could rescue stress-weakened neuronal innate immune response, thereby reducing HSV-1 susceptibility in vivo and in vitro. This study illustrates the critical role of lipid peroxidation in stress-induced HSV-1 susceptibility and reveals the potential for developing RA as an effective intervention in anti-HSV-1 therapy.

A multiplicative structural nested mean model for zero-inflated outcomes.

Zero-inflated nonnegative outcomes are common in many applications. In this work, motivated by freemium mobile game data, we propose a class of multiplicative structural nested mean models for zero-inflated nonnegative outcomes which flexibly describes the joint effect of a sequence of treatments in the presence of time-varying confounders. The proposed estimator solves a doubly robust estimating equation, where the nuisance functions, namely the propensity score and conditional outcome means given confounders, are estimated parametrically or nonparametrically. To improve the accuracy, we leverage the characteristic of zero-inflated outcomes by estimating the conditional means in two parts, that is, separately modelling the probability of having positive outcomes given confounders, and the mean outcome conditional on its being positive and given the confounders. We show that the proposed estimator is consistent and asymptotically normal as either the sample size or the follow-up time goes to infinity. Moreover, the typical sandwich formula can be used to estimate the variance of treatment effect estimators consistently, without accounting for the variation due to estimating nuisance functions. Simulation studies and an application to a freemium mobile game dataset are presented to demonstrate the empirical performance of the proposed method and support our theoretical findings.

Autonomous, untethered gait-like synchronization of lobed loops made from liquid crystal elastomer fibers via spontaneous snap-through.

The transition from one equilibrium state to another via rapid snap-through can store elastic energy and release it as kinetic energy for rapid motion as seen in Venus flytrap and hummingbird to catch insects mid-flight. They are explored in soft robotics for repeated and autonomous motions. In this study, we synthesize curved liquid crystal elastomer (LCE) fibers as the building blocks that can undergo buckling instability upon heated on a hot surface, leading to autonomous snap-through and rolling behaviors. When they are connected into lobed loops, where each fiber is geometrically constrained by the neighboring ones, they demonstrate autonomous, self-regulated, and repeated synchronization with a frequency of ~1.8 Hz. By adding a rigid bead on the fiber, we can fine-tune the actuation direction and speed (up to ~2.4 mm/s). Last, we demonstrate various gait-like locomotion patterns using the loops as the robot's legs.

Spatial and temporal dynamics of large natural lake areas and shoreline morphology in the Yellow River Basin.

Given their important roles in the regulation and storage functions for river flow and in the regional ecological environment and ecosystem services, natural lakes are essential for the ecological protection and high-quality development of the Yellow River Basin. We used the Landsat TM/OLI remote sensing data to analyze the area changes of Dongping Lake, Gyaring Lake, and Ngoring Lake, three representative large natural lakes in the Yellow River Basin from 1990 to 2020. We used the landscape ecology approach to study the morphological characteristics of lake shoreline and shoreland changes and the relationship between the landscape indices. The results showed that the main areas of Gyaring Lake and Ngoring Lake were mainly in the trend of expansion, while the main area of Dongping Lake significantly reduced during 1990-2000 and 2010-2020. The changes in the area of lake all occurred mainly near the lake inlet of the river. The shoreline morphology of Dongping Lake was more complex, with the fragmentation and aggregation of shoreland landscape significantly changed. The circularity ratio of Gyaring Lake gradually decreased with the expansion of the lake area, and the number of patches in its shoreland changed significantly. The fractal dimension index-mean of the shoreland of Ngoring Lake was relatively high, the complexity of its shoreline landscape was stronger, and the number of patches had increased significantly from 2000 to 2010. Meanwhile, there was a significant correlation between certain lake shoreline (shoreland) landscape indices. The changes in circularity ratio and shoreline development coefficient caused changes in the patch density of shoreland.

Controlled Synthesis and Enhanced Gas Sensing Performance of Zinc-Doped Indium Oxide Nanowires.

Indium oxide (In2O3) is a widely used n-type semiconductor for detection of pollutant gases; however, its gas selectivity and sensitivity have been suboptimal in previous studies. In this work, zinc-doped indium oxide nanowires with appropriate morphologies and high crystallinity were synthesized using chemical vapor deposition (CVD). An accurate method for electrical measurement was attained using a single nanowire microdevice, showing that electrical resistivity increased after doping with zinc. This is attributed to the lower valence of the dopant, which acts as an acceptor, leading to the decrease in electrical conductivity. X-ray photoelectron spectroscopy (XPS) analysis confirms the increased oxygen vacancies due to doping a suitable number of atoms, which altered oxygen adsorption on the nanowires and contributed to improved gas sensing performance. The sensing performance was evaluated using reducing gases, including carbon monoxide, acetone, and ethanol. Overall, the response of the doped nanowires was found to be higher than that of undoped nanowires at a low concentration (5 ppm) and low operating temperatures. At 300 °C, the gas sensing response of zinc-doped In2O3 nanowires was 13 times higher than that of undoped In2O3 nanowires. The study concludes that higher zinc doping concentration in In2O3 nanowires improves gas sensing properties by increasing oxygen vacancies after doping and enhancing gas molecule adsorption. With better response to reducing gases, zinc-doped In2O3 nanowires will be applicable in environmental detection and life science.

Synthesis and Physical Characteristics of Undoped and Potassium-Doped Cubic Tungsten Trioxide Nanowires through Thermal Evaporation.

We report an efficient method to synthesize undoped and K-doped rare cubic tungsten trioxide nanowires through the thermal evaporation of WO3 powder without a catalyst. The WO3 nanowires are reproducible and stable with a low-cost growth process. The thermal evaporation processing was conducted in a three-zone horizontal tube furnace over a temperature range of 550-850 °C, where multiple substrates were placed at different temperature zones. The processing parameters, including pressure, temperature, type of gas, and flow rate, were varied and studied in terms of their influence on the morphology, aspect ratio and density of the nanowires. The morphologies of the products were observed with scanning electron microscopy. High resolution transmission electron microscopy, X-ray photoelectron spectroscopy, and X-ray diffraction studies were conducted to further identify the chemical composition, crystal structure and growth direction of the nanostructures. Additionally, the growth mechanism has been proposed. Furthermore, we investigated the potassium doping effect on the physical properties of the nanostructures. Photoluminescence measurements show that there were shorter emission bands at 360 nm and 410 nm. Field emission measurements show that the doping effect significantly reduced the turn-on electric field and increased the enhancement factor. Furthermore, as compared with related previous research, the K-doped WO3 nanowires synthesized in this study exhibited excellent field emission properties, including a superior field enhancement factor and turn-on electric field. The study reveals the potential of WO3 nanowires in promising applications for sensors, field emitters and light-emitting diodes.

Liver three-dimensional cellular models for high-throughput chemical testing.

Drug-induced hepatotoxicity is a leading cause of drug withdrawal from the market. High-throughput screening utilizing in vitro liver models is critical for early-stage liver toxicity testing. Traditionally, monolayer human hepatocytes or immortalized liver cell lines (e.g., HepG2, HepaRG) have been used to test compound liver toxicity. However, monolayer-cultured liver cells sometimes lack the metabolic competence to mimic the in vivo condition and are therefore largely appropriate for short-term toxicological testing. They may not, however, be adequate for identifying chronic and recurring liver damage caused by drugs. Recently, several three-dimensional (3D) liver models have been developed. These 3D liver models better recapitulate normal liver function and metabolic capacity. This review describes the current development of 3D liver models that can be used to test drugs/chemicals for their pharmacologic and toxicologic effects, as well as the advantages and limitations of using these 3D liver models for high-throughput screening.

Sp1-like protein KLF13 acts as a negative feedback regulator of TGF-ß signaling and fibrosis.

Transforming growth factor ß (TGF-ß) is the primary factor that drives fibrosis in most forms of chronic kidney disease. The aim of this study was to identify endogenous regulators of TGF-ß signaling and fibrosis. Here, we show that tubulointerstitial fibrosis is aggravated by global deletion of KLF13 and attenuated by adeno-associated virus-mediated KLF13 overexpression in renal tubular epithelial cells. KLF13 recruits a repressor complex comprising SIN3A and histone deacetylase 1 (HDAC1) to the TGF-ß target genes, limiting the profibrotic effects of TGF-ß. Temporary upregulation of TGF-ß induces KLF13 expression, creating a negative feedback loop that triggers the anti-fibrotic effect of KLF13. However, persistent activation of TGF-ß signaling reduces KLF13 levels through FBXW7-mediated ubiquitination degradation and HDAC-dependent mechanisms to inhibit KLF13 transcription and offset the anti-fibrotic effect of KLF13. Collectively, our data demonstrate a role of KLF13 in regulating TGF-ß signaling and fibrosis.

[Effects of Phosphogypsum and Suaeda salsa on the Soil Moisture, Salt, and Bacterial Community Structure of Salinized Soil].

The improvement of saline soil is an important issue that cannot be ignored in the farmland soil environment. The change in soil salinity will inevitably affect the soil bacterial community. This experiment was based on moderately saline soil in the Hetao Irrigation Area, conducted by applying phosphogypsum (LSG), interplanting Suaeda salsa with Lycium barbarum (JP) and applying phosphogypsum and interplanting S. salsa with L. barbarum (LSG+JP),and the local unimproved soil of a L. barbarum orchard was used as the control (CK), to explore the effects of different improvement methods on soil moisture, salinity, nutrients, and bacterial community structure diversity during the growth period of L. barbarum. The results showed that compared with that under CK, the LSG+JP treatment significantly decreased the soil EC value and pH value from the flowering stage to the deciduous stage (P<0.05), with an average decrease of 39.96% and 7.25%, respectively; the LSG+JP treatment significantly increased soil organic matter (OM) and available phosphorus (AP) content during the whole growth period (P<0.05), with an average annual increase of 81.85% and 203.50%, respectively. The total nitrogen (TN) content was significantly increased in the flowering and deciduous stages (P<0.05), with an annual average increase of 48.91%. The Shannon index of LSG+JP in the early stage of improvement was increased by 3.31% and 6.54% compared with that of CK, and the Chao1 index was increased by 24.95% and 43.26% compared with that of CK, respectively. The dominant bacteria in the soil were Proteobacteria, Bacteroidetes, Actinobacteria, and Acidobacteria, and the dominant genus was Sphingomonas. Compared with that in CK, the relative abundance of Proteobacteria in the improved treatment increased by 0.50%-16.27% from the flowering stage to the deciduous stage, and the relative abundance of Actinobacteria in the improved treatment increased by 1.91%-4.98% compared with that in CK in the flowering and full-fruit stages. Redundancy analysis (RDA) results showed that pH, water content (WT), and AP were important factors affecting bacterial community composition, and the correlation heatmap showed that Proteobacteria, Bacteroidetes, and EC values were significantly negatively correlated (P<0.001); Actinobacteria and Nitrospirillum were significantly negatively correlated with EC values (P<0.01). In conclusion, the application of phosphogypsum and interplanting S. salsa with L. barbarum (LSG+JP) could significantly reduce soil salinity, increase nutrients, and improve the diversity of soil bacterial community structure, which is beneficial to the long-term improvement of saline soil in the Hetao Irrigation Area and the maintenance of soil ecological health.

Cognitive appraisal of health and its influencing factors among pregnant women with gestational diabetes mellitus: A cross-sectional study.

AIM: To investigate the status quo of cognitive appraisal of health and its influencing factors among pregnant women with gestational diabetes mellitus. METHODS: A cross-sectional survey was conducted from June 2020 to November 2020. Participants were recruited from a tertiary hospital by a convenient sample method. A total of 300 pregnant women with gestational diabetes mellitus completed the survey, including self-compiled individual information questionnaire, Cognitive Appraisal of Health Scale, Pregnancy Stress Rating Scale and General Self-Efficacy Scale. RESULTS: For cognitive appraisal of health, the median score of challenge dimension was 3.75 (3.50, 4.00), benign/irrelevant was 2.75 (2.00, 3.50), harm/loss was 2.38 (2.00, 3.00) and threat was 2.40 (2.00, 2.80), respectively. Regression analyses showed that gestational age, mode of conception, history of abortion, insulin usage, pregnancy stress and self-efficacy were the predictors of cognitive appraisal of health. CONCLUSIONS: This study revealed that pregnant women with gestational diabetes mellitus tended to make positive cognitive appraisal of health. And healthcare providers need to make full use of their predictors of cognitive appraisal of health to improve cognitive appraisal to manage stress and ameliorate pregnancy outcomes.

Characteristics, Thrombus Resolution, and Long-Term Outcomes in Patients with Nonvalvular Atrial Fibrillation and Atrial Thrombus.

To assess the prevalence and management of atrial thrombus in patients with nonvalvular atrial fibrillation (NVAF) and identify the risk factors of the nonresolution of atrial thrombus. This single-center retrospective observational study consecutively enrolled patients with NVAF and atrial thrombus detected using transesophageal echocardiography (TEE) or cardiac computed tomography angiography (CTA) from January 2012 to December 2020. Patients with prior left atrial appendage (LAA) intervention were excluded. The primary endpoint was the presence of atrial thrombus, while the secondary endpoint was the complete resolution of atrial thrombus. The prevalence of atrial thrombus in patients with NVAF was 1.4%. Ninety patients with atrial thrombus (mean age 62.8 ± 11.9 years and 61.1% men) were finally analyzed. Atrial thrombus was in the LAA in 82 (91.1%) patients. During follow up, 60% of the patients showed complete resolution of atrial thrombus. Congestive heart failure (odds ratio [OR]: 8.94; 95% confidence interval [CI]: 1.67-47.80) and a history of ischemic stroke (OR: 8.28; 95% CI: 1.48-46.42) were independently associated with the risk of the nonresolution of atrial thrombus. The presence of atrial thrombus in patients with NVAF who received anticoagulation therapy is non-negligible. Even in anticoagulated patients, TEE or cardiac CTA might still be needed. Congestive heart failure and a history of ischemic stroke are risk factors of the nonresolution of atrial thrombus.

Transcriptome comparative analysis of amygdala-hippocampus in depression: A rat model induced by chronic unpredictable mild stress (CUMS).

BACKGROUND: Depression is a common and complex mental disease, and its pathogenesis involves several brain regions. Abnormalities in the amygdala-hippocampal neural circuits have been shown to be involved in depression. However, the underlying molecular mechanisms remain unclear. METHODS: A rat model was used to determine the transcriptome changes in the amygdala-hippocampal neural network under chronic unpredictable mild stress (CUMS). Depression-related modules in this neural network were identified using weighted gene co-expression network analysis (WGCNA). Difference and enrichment analyses were used to determine differential gene expression in the two brain regions. RESULTS: The modules in the amygdala and hippocampus associated with depression-like behavior contained 363 and 225 genes, respectively. Forty-two differentially expressed genes were identified in the amygdala candidate module and 37 in the hippocampus. Enrichment analysis showed that candidate genes in the amygdala were associated with neuronal myelination and candidate genes in the hippocampus were associated with synaptic transmission. Finally, based on module hub gene statistics, differential gene expression, and protein-protein interaction networks, 11 central genes were found in the amygdala candidate module, and one central gene was found in the hippocampal module. LIMITATIONS: Our study was based on a rat CUMS model. Further evidence is needed to prove that our results are applicable to patients with depression. CONCLUSION: This study identified critical modules and central genes involved in the amygdala-hippocampal circuit in the context of depression, and may provide further understanding of the pathogenesis of depression and help identify potential targets for antidepressant therapy.

Specific correlation between childhood trauma and social cognition in Chinese Han first-episode, drug-naïve major depressive disorder.

BACKGROUND: Childhood trauma (CT) is a significant factor affecting social cognition in major depressive disorder (MDD). However, the relationship between CT, social cognition, and MDD is still not well-understood. METHODS: A total of 251 Han Chinese participants, comprising 117 first-episode drug-naïve MDD patients and 134 healthy controls (HCs), were recruited. The Childhood Trauma Questionnaire (CTQ), Toronto Alexithymia Scale (TAS-20), Interpersonal Reactivity Index-C (IRI), and Facial Emotion Recognition Test were used to measure CT and social cognition. Partial correlations were conducted to analyze the association between CT and social cognition. RESULTS: Our results showed that no significant correlation was observed between CTQ total score and social cognition in MDD (p > 0.05), while it was different in HCs (TAS-20 total score: r = 0.21, p = 0.016; difficulty identifying feelings (DIF): r = 0.219, p = 0.012; perspective-taking (PT): r = -0.214, p = 0.014; recognizing neutral facial emotions: r = -0.4, p < 0.001). CTQ subtyping analysis revealed that CTQ subscale scores in MDD were significantly correlated with PT, personal distress (PD), and recognizing angry facial emotions. Interestingly, physical abuse score was positively correlated with PT in MDD (r = 0.219, p = 0.019) but negatively with PT in HCs (r = -0.276, p = 0.001). LIMITATIONS: Insufficient sample size and cross-sectional designs. CONCLUSION: The correlation between CT and social cognition in MDD was weakened or reversed compared to HCs, highlighting the need for further investigation to determine the cause of this specific correlation.