Acupuncture as Add-on Therapy to SSRIs Can Improve Outcomes of Treatment for Anxious Depression: Subgroup Analysis of the AcuSDep Trial

Purpose

Anxious depression (AD) is a common, distinct depression subtype. This exploratory subgroup analysis aimed to explore the effects of acupuncture as an add-on therapy of selective serotonin reuptake inhibitors (SSRIs) for patients with AD or non-anxious depression (NAD).

Patients and Methods

Four hundred and sixty-five patients with moderate-to-severe depression from the AcuSDep pragmatic trial were included in analysis. Patients were randomly assigned to receive MA+SSRIs, EA+SSRIs, or SSRIs alone (1:1:1) for six weeks. AD was defined by using dimensional criteria. The measurement instruments included 17-items Hamilton Depression Scale (HAMD-17), Self-Rating Depression Scale (SDS), Clinical Global Impression (CGI), Rating Scale for Side Effects (SERS), and WHO Quality of Life-BREF (WHOQOL-BREF). Comparison between AD and NAD subgroups and comparisons between groups within either AD or NAD subgroups were conducted.

Results

Eighty percent of the patients met the criteria for AD. The AD subgroup had poorer clinical manifestations and treatment outcomes compared to those of the NAD subgroup. For AD patients, the HAMD response rate, remission rate, early onset rate, and the score changes on each scale at most measurement points on the two acupuncture groups were significantly better than the SSRIs group. For NAD patients, the HAMD early onset rates of the two acupuncture groups were significantly better than the SSRIs group.

Conclusion

For AD subtype patients, either MA or EA add-on SSRIs showed comprehensive improvements, with small-to-medium effect sizes. For NAD subtype patients, both the add-on acupuncture could accelerate the response to SSRIs treatment. The study contributed to the existing literature by providing insights into the potential benefits of acupuncture in combination with SSRIs, especially for patients with AD subtypes. Due to its limited nature as a post hoc subgroup analysis, prospectively designed, high-quality trials are warranted.

Clinical Trials Registration

ChiCTR-TRC-08000297.

Eye movements as predictor of cognitive improvement after cognitive remediation therapy in patients with schizophrenia

Aim

Baseline cognitive functions of patients predicted the efficacy of cognitive remediation therapy (CRT), but results are mixed. Eye movement is a more objective and advanced assessment of cognitive functions than neuropsychological testing. We aimed to investigate the applicability of eye movements in predicting cognitive improvement after patients with schizophrenia were treated with CRT.

Methods

We recruited 79 patients with schizophrenia to complete 8 weeks of CRT and assessed their cognitive improvement outcomes. Eye movements were assessed by prosaccades, antisaccades, and free-viewing tasks at baseline, and neuropsychological tests in four cognitive domains were assessed before and after treatment to calculate treatment outcomes. Predictors of demographic information, clinical characteristics, and eye movement measures at baseline on cognitive improvement outcomes were analyzed using logistic regression analysis. We further compared the predictive performance between eye movement measurements and neuropsychological test regarding the effect of CRT on cognitive improvement, and explored factors that could be affect the treatment outcomes in different cognitive domains.

Results

As operationally defined, 33 patients showed improved in cognition (improved group) and 46 patients did not (non-improved group) after CRT. Patients with schizophrenia being employed, lower directional error rate in antisaccade task, and lower the gap effect (i.e., the difference in saccadic latency between the gap condition and overlap condition) in prosaccade task at baseline predicted cognitive improvement in CRT. However, performance in the free-viewing task not associated with cognitive improvement in patients in CRT. Our results show that eye-movement prediction model predicted the effect of CRT on cognitive improvement in patients with schizophrenia better than neuropsychological prediction model in CRT. In addition, baseline eye-movements, cognitive reserve, antipsychotic medication dose, anticholinergic cognitive burden change, and number of training sessions were associated with improvements in four cognitive domains.

Conclusion

Eye movements as a non-invasiveness, objective, and sensitive method of evaluating cognitive function, and combined saccadic measurements in pro- and anti-saccades tasks could be more beneficial than free-viewing task in predicting the effect of CRT on cognitive improvement in patients with schizophrenia.

Debiased Graph Neural Networks With Agnostic Label Selection Bias

Most existing graph neural networks (GNNs) are proposed without considering the selection bias in data, i.e., the inconsistent distribution between the training set with the test set. In reality, the test data are not even available during the training process, making selection bias agnostic. Training GNNs with biased selected nodes leads to significant parameter estimation bias and greatly impacts the generalization ability on test nodes. In this article, we first present an experimental investigation, which clearly shows that the selection bias drastically hinders the generalization ability of GNNs, and theoretically proves that the selection bias will cause the biased estimation on GNN parameters. Then to remove the bias in GNN estimation, we propose a novel debiased GNNs (DGNN) with a differentiated decorrelation regularizer. The differentiated decorrelation regularizer estimates a sample weight for each labeled node such that the spurious correlation of learned embeddings could be eliminated. We analyze the regularizer in causal view and it motivates us to differentiate the weights of the variables based on their contribution to the confounding bias. Then, these sample weights are used for reweighting GNNs to eliminate the estimation bias, and thus, help to improve the stability of prediction on unknown test nodes. Comprehensive experiments are conducted on several challenging graph datasets with two kinds of label selection biases. The results well verify that our proposed model outperforms the state-of-the-art methods and DGNN is a flexible framework to enhance existing GNNs.

Diagnosis of Inverted Meckel's diverticulum by double-balloon enteroscopy: a case report

Background

Meckel's diverticulum (MD) is the most common congenital defect of the gastrointestinal tract, occurring in about 1% to 2% of population. Most MD are rarely symptomatic, with presenting symptoms including diverticulitis, digestive tract hemorrhage and intestinal obstruction. The semblance of symptoms to enteritis and appendicitis makes preoperative diagnosis challenging. Current diagnosis of MD includes technetium-99m pertechnate scan, laparoscopic or intraoperative findings and examining surgical specimens. Here, we report that a double-balloon enteroscopy (DBE) improves the diagnosis accuracy of MD and presents high clinical application value.

Case Description

A 12-year-old male patient was admitted to our hospital due to recurrent abdominal pain and black stools for more than half a year, recurrence for 2 days, accompanied by vomiting. The boy had anemic appearance, with periumbilical tenderness, and no mass was detected upon palpations. Past medical records revealed recurrent abdominal pain episodes thrice. Pre-surgery 99TcmO4-single-photon emission computed tomography/computed tomography (SPECT/CT) imaging was performed but did not reach the condition for diagnosis of MD. DBE was then performed and identified an upper ileum mass. After surgery, it was confirmed that the patient was an inverted MD, and the pathology showed gastric mucosa and pancreatic tissue. The patient recovered well after surgery and was discharged.

Conclusions

DBE is not widely used in the diagnosis of MD, but its accuracy is higher than that of radionuclide scanning imaging. In addition, several advantages such as hemostasis treatment, direct detection and observation of the diverticulum, and demarcation of the site and scope of the lesion prior to surgery brings high clinical application value.

The LiV3 O8 Superlattice Cathode with Optimized Zinc Ion Insertion Chemistry for High Mass-Loading Aqueous Zinc-Ion Batteries

Resolving the sluggish transport kinetics of divalent Zn2+ in the cathode lattice and improving mass-loading performance are crucial for advancing the zinc-ion batteries (AZIBs) application. Herein, PEO-LiV3 O8 superlattice nanosheets (PEO-LVO) with expanded interlayer spacing (1.16 nm) are fabricated to provide a high-rate, stable lifetime, and large mass-loading cathode. The steady in-plane expansion without shrinkage after the first cycle, but reversible H+ /Zn2+ co-insertion in PEO-LVO are demonstrated by operando synchrotron X-ray diffraction and ex situ characterizations. Moreover, the large capacity of PEO-LVO is traced back to the optimized Zn2+ insertion chemistry with increased Zn2+ storage ratio, which is facilitated by the interlayer PEO in lowering the Zn2+ diffusion barrier and increased number of active sites from additional interfaces, as anticipated by density functional theory. Due to the optimized ion insertion resulting in stalled interfacial byproducts and rapid kinetics, PEO-LVO achieves excellent high mass-loading performance (areal capacity up to 6.18 mAh cm-2 for freestanding electrode with 24 mg cm-2 mass-loading and 2.8 mAh cm-2 at 130 mA cm-2 for conventional electrode with 27 mg cm-2 mass-loading). As a proof-of-concept, the flexible all-solid-state fiber-shaped AZIBs with high mass-loading woven into a fabric can power an electronic watch, highlighting the application potential of PEO-LVO cathode.

Generation of High-Quality African Swine Fever Virus Complete Genome from Field Samples by Next-Generation Sequencing

African swine fever (ASF) is a lethal contagious viral disease of domestic pigs and wild boars caused by the African swine fever virus (ASFV). The pandemic spread of ASF has caused severe effects on the global pig industry. Whole-genome sequencing provides crucial information for virus strain characterization, epidemiology analysis and vaccine development. Here, we evaluated the performance of next-generation sequencing (NGS) in generating ASFV genome sequences from clinical samples. Thirty-four ASFV-positive field samples including spleen, lymph node, lung, liver and blood with a range of Ct values from 14.73 to 25.95 were sequenced. For different tissue samples collected from the same sick pigs, the proportion of ASFV reads obtained from the spleen samples was 3.69-9.86 times higher than other tissues. For the high-viral-load spleen samples (Ct < 20), a minimum of a 99.8% breadth of ≥10× coverage was revealed for all the samples. For the spleen samples with Ct ≥ 20, 6/12 samples had a minimum of a 99.8% breadth of ≥10× coverage. A high average depth of sequencing coverage was also achieved from the blood samples. According to our results, high-quality ASFV whole-genome sequences could be obtained from the spleen or blood samples with Ct < 20. The high-quality ASFV genome sequence generated in this study was further used for the high-resolution phylogenetic analysis of the ASFV genomes in the early stage of the ASF epidemic in China. Our study demonstrates that NGS may act as a useful tool for efficient ASFV genome characterization, providing valuable information for disease control.

Generalizing Graph Neural Networks on Out-of-Distribution Graphs

Graph Neural Networks (GNNs) are proposed without considering the agnostic distribution shifts between training graphs and testing graphs, inducing the degeneration of the generalization ability of GNNs in Out-Of-Distribution (OOD) settings. The fundamental reason for such degeneration is that most GNNs are developed based on the I.I.D hypothesis. In such a setting, GNNs tend to exploit subtle statistical correlations existing in the training set for predictions, even though it is a spurious correlation. This learning mechanism inherits from the common characteristics of machine learning approaches. However, such spurious correlations may change in the wild testing environments, leading to the failure of GNNs. Therefore, eliminating the impact of spurious correlations is crucial for stable GNN models. To this end, in this paper, we argue that the spurious correlation exists among subgraph-level units and analyze the degeneration of GNN in causal view. Based on the causal view analysis, we propose a general causal representation framework for stable GNN, called StableGNN. The main idea of this framework is to extract high-level representations from raw graph data first and resort to the distinguishing ability of causal inference to help the model get rid of spurious correlations. Particularly, to extract meaningful high-level representations, we exploit a differentiable graph pooling layer to extract subgraph-based representations by an end-to-end manner. Furthermore, inspired by the confounder balancing techniques from causal inference, based on the learned high-level representations, we propose a causal variable distinguishing regularizer to correct the biased training distribution by learning a set of sample weights. Hence, GNNs would concentrate more on the true connection between discriminative substructures and labels. Extensive experiments are conducted on both synthetic datasets with various distribution shift degrees and eight real-world OOD graph datasets. The results well verify that the proposed model StableGNN not only outperforms the state-of-the-arts but also provides a flexible framework to enhance existing GNNs. In addition, the interpretability experiments validate that StableGNN could leverage causal structures for predictions.

Revealing the role of hydrogen bond coupling structure for enhanced performance of the solid-state electrolyte

Achieving practical applications of PEO-based composite solid electrolyte (CPE) batteries requires the precise design of filler structures at the molecular level to form stable composite interfacial phases, which in turn improve the conductivity of Li+ and inhibit the nucleation growth of lithium dendrites. Some functional fillers suffer from severe agglomeration due to poor compatibility with the polymer base or grain boundary migration, resulting in limited improvement in cell performance. In this paper, ILs@KAP1 is reported as a filler to enhance the performance of PEO-based batteries. Thereinto, the hypercrosslinked phosphorus ligand polymer-containing KAP1, designed at the molecular level, has an abundant porous structure, hydrogen bonding network, and a rigid skeleton structure of benzene rings. These can be used both to improve the flammability with PEO-based and to reduce the crystallinity of the polymer electrolyte. Ionic liquids (ILs) are encapsulated in the nanochannels of KAP1, and thus a 3D Li+ conducting framework could be formed. In this case, it could not only facilitate the wettability of the contact interface with the electrode, significantly promoting its compatibility and providing a fast Li+ transport path, but also facilitate the formation of LiF, Li3N and Li2O rich SEI components, further fostering the uniform deposition/exfoliation of lithium. The LFP||CPE||Li battery assembled with ILs@KAP1-PEO-CPE has a high initial discharge specific capacity about 156 mAh/g at 1C and a remaining capacity about 121.8 mAh/g after 300 cycles (capacity retention of 78.07%).

Initial attitudes toward a drug predict medication adherence in first-episode patients with schizophrenia: a 1-year prospective study in China

BACKGROUND

Patients' attitudes toward medication have been shown to be a predictor of nonadherence to antipsychotic treatment. However, most previous studies that explored this relationship used a cross-sectional design. It is important to explore the association of attitudes toward drugs with discontinuation at different time points during antipsychotic treatment. In this study, we investigated the association of attitudes toward drugs (measured by the Drug Attitude Inventory (DAI-10)) with adherence at seven time points (baseline, 4 weeks, 8 weeks, 12 weeks, 26 weeks, 39 weeks, and 52 weeks) during 1 year of treatment. Factors that were potentially associated with attitudes toward drugs at the time point of interest were also studied.

METHODS

Demographic characteristics, psychopathology, social functioning, and attitudes toward drugs (measured by the DAI-10) were collected at baseline, 4 weeks, 8 weeks, 12 weeks, 26 weeks, 39 weeks and 52 weeks. The association of attitudes toward drugs (measured by DAI-10) with adherence at the seven time points was calculated using the Mann‒Whitney U test. The optimal cutoff point for the DAI-10 was then determined using receiver operating characteristic (ROC) analysis. Cox regression analysis was conducted to further investigate the association of DAI-10 scores with discontinuation, controlling for potential confounding variables. We used multiple regression analysis to identify the factors associated with DAI-10 scores.

RESULTS

Among the six time points, only baseline DAI-10 total scores were significantly different between the completed and discontinued groups (p = 0.004). Female sex and a baseline DAI-10 total score greater than - 1 were found to be independent protective factors against discontinuation of antipsychotic drug treatments during the 1-year follow-up. At baseline, the severity of the disease (CGI-s) and insight regarding the disease were shown to be associated with DAI-10 total scores.

CONCLUSION

Attitudes toward antipsychotic drugs at baseline were shown to play a crucial role in predicting treatment discontinuation.

TRIAL REGISTRATION

The data were collected from a clinical trial and the clinical trials.gov ID of the study is NCT01057849.

A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study

BACKGROUND

Dementia has become a major public health concern due to its heavy disease burden. Mild cognitive impairment (MCI) is a transitional stage between healthy aging and dementia. Early identification of MCI is an essential step in dementia prevention.

OBJECTIVE

Based on machine learning (ML) methods, this study aimed to develop and validate a stable and scalable panel of cognitive tests for the early detection of MCI and dementia based on the Chinese Neuropsychological Consensus Battery (CNCB) in the Chinese Neuropsychological Normative Project (CN-NORM) cohort.

METHODS

CN-NORM was a nationwide, multicenter study conducted in China with 871 participants, including an MCI group (n=327, 37.5%), a dementia group (n=186, 21.4%), and a cognitively normal (CN) group (n=358, 41.1%). We used the following 4 algorithms to select candidate variables: the F-score according to the SelectKBest method, the area under the curve (AUC) from logistic regression (LR), P values from the logit method, and backward stepwise elimination. Different models were constructed after considering the administration duration and complexity of combinations of various tests. Receiver operating characteristic curve and AUC metrics were used to evaluate the discriminative ability of the models via stratified sampling cross-validation and LR and support vector classification (SVC) algorithms. This model was further validated in the Alzheimer's Disease Neuroimaging Initiative phase 3 (ADNI-3) cohort (N=743), which included 416 (56%) CN subjects, 237 (31.9%) patients with MCI, and 90 (12.1%) patients with dementia.

RESULTS

Except for social cognition, all other domains in the CNCB differed between the MCI and CN groups (P<.008). In feature selection results regarding discrimination between the MCI and CN groups, the Hopkins Verbal Learning Test-5 minutes Recall had the best performance, with the highest mean AUC of up to 0.80 (SD 0.02) and an F-score of up to 258.70. The scalability of model 5 (Hopkins Verbal Learning Test-5 minutes Recall and Trail Making Test-B) was the lowest. Model 5 achieved a higher level of discrimination than the Hong Kong Brief Cognitive test score in distinguishing between the MCI and CN groups (P<.05). Model 5 also provided the highest sensitivity of up to 0.82 (range 0.72-0.92) and 0.83 (range 0.75-0.91) according to LR and SVC, respectively. This model yielded a similar robust discriminative performance in the ADNI-3 cohort regarding differentiation between the MCI and CN groups, with a mean AUC of up to 0.81 (SD 0) according to both LR and SVC algorithms.

CONCLUSIONS

We developed a stable and scalable composite neurocognitive test based on ML that could differentiate not only between patients with MCI and controls but also between patients with different stages of cognitive impairment. This composite neurocognitive test is a feasible and practical digital biomarker that can potentially be used in large-scale cognitive screening and intervention studies.

[Study of the predictive role of serum HBV RNA on HBeAg serological conversion in children with chronic hepatitis B]

Objective: To investigate the role of serum hepatitis B virus RNA (HBV RNA) in predicting HBeAg serological conversion in children with chronic hepatitis B. Methods: 175 children aged 1~17 years with chronic hepatitis B who received interferon α (IFNα) for 48 weeks were selected. Patients were divided into HBeAg seroconversion and non-conversion based on whether HBeAg seroconversion occurred at 48 weeks of treatment.T-test and Mann-Whitney U test were used to compare between groups; chisquare test or Fisher exact probability method was used to compare the frequency between groups of classified variables; and Pearson correlation was used to analyze the correlation between indicators. Univariate and multivariate logistic regression analyses were used to identify influencing factors associated with HBeAg serological conversion. The predictive effect of HBV RNA, HBV DNA, and HBsAg on HBeAg serological conversion was compared and analyzed by the receiver operating characteristic curve (ROC). Results: The seroconversion rate of HBeAg at 48 weeks was 36.0% (63/175). The reduction in HBVRNA levels from baseline to the 12th, 24th, 36th, and 48th weeks of antiviral therapy was significantly greater in the HBeAg serological conversion group than that in the non-conversion group, and the difference was statistically significant between the two groups (P < 0.05). Univariate and multivariate regression analyses showed that age and a decline in HBV RNA levels at week 12 were independent predictors of HBeAg serological conversion. The area under the ROC curve (AUROC) of HBV RNA decline at week 12 was 0.677(95% CI∶0.549-0.806, P = 0.012), which was significantly better than the same period of AUROC of HBV DNA (0.657, 95% CI∶0.527-0.788, P = 0.025) and HBsAg (0.660, 95% CI∶0.526-0.795, P = 0.023) decline. HBV RNA levels decreased (>1.385 log10 copies/ml) at week 12, with a positive predictive value of 53.2%, a negative predictive value of 72.2%, a sensitivity of 77.4%, and a specificity of 57.9% for HBeAg seroconversion. Conclusion: HBV RNA level lowering during the 12th week of antiviral therapy can serve as an early predictor marker for HBeAg serological conversion in children with chronic hepatitis B.

A Comparison of Dynamic SPECT Coronary Flow Reserve with TIMI Frame Count in the Treatment of Non-Obstructive Epicardial Coronary Patients

Background

Microvascular dysfunction in patients with non-obstructive epicardial coronary may aggravate patient's symptoms or lead to various clinical events.

Objective

To investigate the correlation between dynamic single photon emission computed tomography (D-SPECT) derived coronary flow reserve (CFR) and TIMI frame count (TFC) in patients with non-obstructive epicardial coronary patients.

Methods

Patients with suspected or known stable CAD who were recommended to undergo invasive coronary angiography were prospectively enrolled in this study. Those who had non-obstructive coronary received TIMI frame count (TFC) and D-SPECT. A cut-off value of >40 was defined as slow flow referred to TFC.

Results

A total of 47 patients diagnosed with non-obstructive coronary were enrolled. The mean age of patients was 66.09 ± 8.36 years, and 46.8% were male. Dynamic SPECT derived coronary flow reserve (CFR) was significantly correlated with TIMI frame count in 3 epicardial coronary (LAD: r=-0.506, P = 0.0003; LCX: r= -0.532, P = 0.0001; RCA: r= -0.657, P < 0.0001). The sensitivity and specificity of CFR in identifying abnormal TIMI frame count < 40 was 100.0% and 57.6% in LAD, 62.5% and 87.0% in LCX, 83.9% and 75.0% in RCA, respectively. The optimal CFR cut-off values were 2.02, 2.47, and 1.96 among the three vessels.

Conclusion

In patients with non-obstructive coronary, CFR derived from D-SPECT was strongly correlated with TFC. This study demonstrates that that CFR may be an alternative non-invasive method for identifying slow flow in non-obstructive coronary.

An Explainable Framework for Predicting Drug-Side Effect Associations via Meta-Path-Based Feature Learning in Heterogeneous Information Network

Side effects of drugs have gained increasing attention in the biomedical field, and accurate identification of drug side effects is essential for drug development and drug safety surveillance. Although the traditional pharmacological experiments can accurately detect the side effects of drugs, the identifying process is time-consuming, costly, and may lead to incomplete identification of side effects. With the expanding of various biomedical databases, many computational methods have been developed for the task of drug-side effect associations (DSAs) prediction. However, existing methods have the following three drawbacks: 1). multiple drug-related databases are not fully used; 2). the complex semantics among drugs and side effects are not effectively captured; 3). the explainability of the predicted DSAs is missed for most existing methods. Therefore, there is an urgent need to find a more effective method for predicting DSAs. To address these issues, we propose a novel meta-path-based graph neural network model for drug-side effect associations prediction (MPGNN-DSA). In MPGNN-DSA, a heterogeneous information network is first constructed by combining multiple biological datasets. Then, a meta-path-based feature learning module is utilized for learning high-quality representations of drugs and side effects by capturing the semantics contained in meta-paths of the constructed HIN. With the learned features, the prediction module is conducted to derive the predicted side effects for drugs. In addition, the explainability of the predicted DSAs can be provided as well with the semantics contained in meta-paths. We conduct comprehensive experiments, and the results demonstrate the effectiveness of MPGNN-DSA, suggesting that the proposed method will be a feasible solution to the task of DSAs prediction.

Enhancement Patterns of Metastatic Intrahepatic Cholangiocarcinoma and Outcomes after Chemotherapy and Radiation

PURPOSE/OBJECTIVE(S)

Patients with metastatic intrahepatic cholangiocarcinoma (M1-iCCA) have a poor prognosis with a 5-year survival rate of less than 20%. Definitive doses of radiation therapy (RT) after upfront chemotherapy (chemo/RT) in this patient population have shown to prolong survival by reducing the risk of tumor-related liver failure compared to chemotherapy alone. Our group has also identified a baseline radiographic feature, the arterial enhancement pattern, which has pathological and prognostic associations for iCCA. We tested the hypothesis that baseline arterial enhancement is independently associated with survival outcomes for patients who receive chemo/RT or chemo alone.

MATERIALS/METHODS

Patients with M1-iCCA from 2010 to 2021 were included in this retrospective study. Patients were grouped into those who underwent chemo alone and those who underwent chemo/RT. The inclusion criteria included confirmed diagnosis of M1-iCCA, availability of baseline multi-phasic computed tomography (CT), and follow-up for at least six months or until death. Tumor arterial enhancement patterns were categorized as previously described into hypovascular or hypervascular, where the tumors that were hypervascular had either peripheral enhancement or central enhancement. Mean tumor density in Hounsfield units was recorded for each patient. Survival was estimated using the Kaplan Meier method, and Cox proportional models were used to adjust for prognostic variables.

RESULTS

A total of 281 patients with iCCA were identified and 229 had evaluable CT scans. Demographic and baseline characteristics of patient groups are shown in the Table. On univariate analysis, patient age, ECOG performance status (PS) at diagnosis, treatment type, and arterial enhancement patterns associated with overall survival (OS). On multivariable analysis, the arterial enhancement pattern independently associated with OS after accounting for covariates. Patients with hypervascular tumors had prolonged OS compared to those with hypovascular tumors (HR = 0.72, [0.54 - 0.96], p = 0.02). Prolonged OS was also observed in the chemo/RT group compared to the chemo alone group (HR = 0.37, [0.25-0.54], p< 0.0001).

CONCLUSION

Baseline enhancement patterns of M1-iCCA were prognostic in the contexts of chemo alone and chemo/RT. This imaging-based biomarker may improve the ability to stratify patients for therapeutic management.

Diagnosis, Genetics, and Management of 24 Patients With Cardiac Paragangliomas: Experience From a Single Center

Context

Paragangliomas located within the pericardium represent a rare yet challenging clinical situation.

Objective

The current analysis aimed to describe the clinical characteristics of cardiac paragangliomas, with emphasis on the diagnostic approach, genetic background, and multidisciplinary management.

Methods

Twenty-four patients diagnosed with cardiac paraganglioma (PGL) in Peking Union Medical College Hospital, Beijing, China, between 2003 and 2021 were identified. Clinical data was collected from medical record. Genetic screening and succinate dehydrogenase subunit B immunohistochemistry were performed in 22 patients.

Results

The median age at diagnosis was 38 years (range 11-51 years), 8 patients (33%) were females, and 4 (17%) had familial history. Hypertension and/or symptoms related to catecholamine secretion were present in 22 (92%) patients. Excess levels of catecholamines and/or metanephrines were detected in 22 (96%) of the 23 patients who have completed biochemical testing. Cardiac PGLs were localized with 131I-metaiodobenzylguanidine scintigraphy in 11/22 (50%), and 99mTc-hydrazinonicotinyl-tyr3-octreotide scintigraphy in 24/24 (100%) patients. Genetic testing identified germline SDHx mutations in 13/22 (59%) patients, while immunohistochemistry revealed succinate dehydrogenase (SDH) deficiency in tumors from 17/22 (77%) patients. All patients were managed by a multidisciplinary team through medical preparation, surgery, and follow-up. Twenty-three patients received surgical treatment and perioperative death occurred in 2 cases. Overall, 21 patients were alive at follow-up (median 7.0 years, range 0.6-18 years). Local recurrence or metastasis developed in 3 patients, all of whom had SDH-deficient tumors.

Conclusion

Cardiac PGLs can be diagnosed based on clinical manifestations, biochemical tests, and appropriate imaging studies. Genetic screening, multidisciplinary approach, and long-term follow-up are crucial in the management of this disease.

Reliability and validity of the electronic version of the Hopkins verbal learning test-revised in middle-aged and elderly Chinese people

Background

The aging population is increasing, making it essential to have a standardized, convenient, and valid electronic memory test that can be accessed online for older people and caregivers. The electronic version of the Hopkins Verbal Learning Test-Revised (HVLT-R) as a test with these advantages and its reliability and validity has not yet been tested. Thus, this study examined the reliability and validity of the electronic version of the HVLT-R in middle-aged and elderly Chinese people to provide a scientific basis for its future dissemination and use.

Methods

We included 1,925 healthy participants aged over 40, among whom 38 were retested after 3-6 months. In addition, 65 participants completed both the pad and paper-and-pencil versions of the HVLT-R (PAP-HVLT-R). We also recruited 42 Alzheimer's disease (AD) patients, and 45 amnestic mild cognitive impairment (aMCI) patients. All participants completed the Pad-HVLT-R, the Hong Kong Brief Cognitive Test (HKBC), the Brief Visual Memory Test-Revised (BVMT-R), and the Logical Memory Test (LM).

Results

(1) Reliability: the Cronbach's α value was 0.94, the split-half reliability was 0.96. The test-retest correlation coefficients were moderate, ranging from 0.38 to 0.65 for direct variables and 0.16 to 0.52 for derived variables; (2) Concurrent validity: the Pad-HVLT-R showed a moderate correlation with the HKBC and BVMT-R, with correlation coefficients between total recall of 0.41 and 0.54, and between long-delayed recall of 0.42 and 0.59, respectively. It also showed a high correlation with the LM, with correlation coefficients of 0.72 for total recall and 0.62 for long-delayed recall; (3) Convergent validity: the Pad-HVLT-R was moderately correlated with the PAP version, with correlation coefficients ranging from 0.29 to 0.53 for direct variables and 0.15 to 0.43 for derived variables; (4) Discriminant capacity: the Pad-HVLT-R was effective in differentiating AD patients, as demonstrated by the ROC analysis with AUC values of 0.834 and 0.934 for total recall and long-delayed recall, respectively.

Conclusion

(1) The electronic version of HVLT-R has good reliability and validity in middle-aged and elderly Chinese people; (2) The electronic version of HVLT-R can be used as an effective tool to distinguish AD patients from healthy people.

Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks

Information diffusion prediction is an important task, which studies how information items spread among users. With the success of deep learning techniques, recurrent neural networks (RNNs) have shown their powerful capability in modeling information diffusion as sequential data. However, previous works focused on either microscopic diffusion prediction, which aims at guessing who will be the next influenced user at what time, or macroscopic diffusion prediction, which estimates the total numbers of influenced users during the diffusion process. To the best of our knowledge, few attempts have been made to suggest a unified model for both microscopic and macroscopic scales. In this article, we propose a novel full-scale diffusion prediction model based on reinforcement learning (RL). RL incorporates the macroscopic diffusion size information into the RNN-based microscopic diffusion model by addressing the nondifferentiable problem. We also employ an effective structural context extraction strategy to utilize the underlying social graph information. Experimental results show that our proposed model outperforms state-of-the-art baseline models on both microscopic and macroscopic diffusion predictions on three real-world datasets.

Re-Dispersion of Platinum From CNTs Substrate to α-MoC1 - x to Boost the Hydrogen Evolution Reaction

Developing high-performance electrocatalysts toward hydrogen evolution reaction (HER) is important for clean and sustainable hydrogen energy, yet still challenging. Herein, an α-MoC_1 - x induced redispersing strategy to construct a superior HER electrocatalyst (Pt/CNTs-N + α-MoC_1 - x ) by mechanical mixing of α-MoC_1 - x with Pt/CNTs-N followed by thermal reduction is reported. It is found that thermo-activation treatment enables partial Pt atoms to redisperse on α-MoC_1 - x substrate from carbon nanotubes, which creates dual active interfaces of Pt species dispersed over carbon nanotubes and α-MoC_1 - x . Benefiting from the strong electronic interaction between the Pt atom and α-MoC_1 - x , the utilization efficiency of the Pt atom and the zero-valence state of Pt is evidently enhanced. Consequently, Pt/CNTs-N + α-MoC_1 - x catalyst exhibits excellent HER activity with low overpotentials of 17 and 34 mV to achieve a current density of 10 mA cm^-2 in acidic and alkaline electrolytes, respectively. Density functional theory calculations further reveal that the synergistic effect between Pt and α-MoC_1 - x makes it accessible for the dissociation of water molecules and subsequent desorption of hydrogen atoms. This work reveals the crucial roles of α-MoC_1 - x additives, providing practical solutions to enhance platinum dispersion, and thereby enhance the catalytic activity in HER.

Weight changes following treatment with aripiprazole, risperidone and olanzapine: A 12-month study of first-episode schizophrenia patients in China

OBJECTIVES

This study aimed to assess weight changes following antipsychotic treatment in first-episode schizophrenia (FES) patients and make a comparison of aripiprazole, risperidone and olanzapine. Predictors for long-term clinically relevant weight gain (CRW, ≥7%) were examined.

METHODS

We carried out a second analysis of data from the Chinese First-Episode Schizophrenia Trial. Repeated measures general linear model (GLM) statistics were used to compare body weight at each follow-up point (month of 1, 2, 3, 6, 9and 12). Logistic regression models were constructed to evaluate possible predictors for CRW.

RESULTS

Body weight increased with an average rate of 0.93 % per month, with the fastest growth rate occurring in first 3 months. CRW was observed in 79 % of patients. Participants from olanzapine group showed significantly higher weight gain than risperidone group and aripiprozole group. Repeated measures GLM revealed a significant main effect of time (p < 0.001) and asignificant time*group interaction was revealed (p < 0.001), while the between-subject group effect was not statistically significant (p = 0.272). Multivariate logistic regressionmodel showed that with smaller baseline BMI (OR = 1.33, p < 0.001), with a family history of mental disorder (OR = 5.08, p = 0.004), receiving olanzapine (OR = 2.35, p = 0.001), and CRW at first-month (OR = 4.29, p = 0.032) were independent predictors for first-year CRW.

CONCLUSION

Antipsychotics are associated with a clinically significant weight gain in FES patients, which occurs mostly in first 3 months. Aripiprazole might not be an ideal choice in terms of long-term metabolic side-effects. Early and close metabolic monitoring should accompany antipsychotic prescription.

Tracing the Origin of Genotype II African Swine Fever Virus in China by Genomic Epidemiology Analysis

The pandemic spread of African swine fever (ASF) has caused serious effects on the global pig industry. Virus genome sequencing and genomic epidemiology analysis play an important role in tracking the outbreaks of the disease and tracing the transmission of the virus. Here we obtained the full-length genome sequence of African swine fever virus (ASFV) in the first outbreak of ASF in China on August 3rd, 2018 and compared it with other published genotype II ASFV genomes including 9 genomes collected in China from September 2018 to October 2020. Phylogenetic analysis on genomic sequences revealed that genotype II ASFV has evolved into different genetic clusters with temporal and spatial correlation since being introduced into Europe and then Asia. There was a strong support for the monophyletic grouping of all the ASFV genome sequences from China and other Asian countries, which shared a common ancestor with those from the Central or Eastern Europe. An evolutionary rate of 1.312 × 10−5 nucleotide substitutions per site per year was estimated for genotype II ASFV genomes. Eight single nucleotide variations which located in MGF110-1L, MGF110-7L, MGF360-10L, MGF505-5R, MGF505-9R, K145R, NP419L, and I267L were identified as anchor mutations that defined genetic clusters of genotype II ASFV in Europe and Asia. This study expanded our knowledge of the molecular epidemiology of ASFV and provided valuable information for effective control of the disease.

Improving drug-drug interactions prediction with interpretability via meta-path-based information fusion

Drug-drug interactions (DDIs) are compound effects when patients take two or more drugs at the same time, which may weaken the efficacy of drugs or cause unexpected side effects. Thus, accurately predicting DDIs is of great significance for the drug development and the drug safety surveillance. Although many methods have been proposed for the task, the biological knowledge related to DDIs is not fully utilized and the complex semantics among drug-related biological entities are not effectively captured in existing methods, leading to suboptimal performance. Moreover, the lack of interpretability for the predicted results also limits the wide application of existing methods for DDIs prediction. In this study, we propose a novel framework for predicting DDIs with interpretability. Specifically, we construct a heterogeneous information network (HIN) by explicitly utilizing the biological knowledge related to the procedure of inducing DDIs. To capture the complex semantics in HIN, a meta-path-based information fusion mechanism is proposed to learn high-quality representations of drugs. In addition, an attention mechanism is designed to combine semantic information obtained from meta-paths with different lengths to obtain final representations of drugs for DDIs prediction. Comprehensive experiments are conducted on 2410 approved drugs, and the results of predictive performance comparison show that our proposed framework outperforms selected representative baselines on the task of DDIs prediction. The results of ablation study and cold-start scenario indicate that the meta-path-based information fusion mechanism red is beneficial for capturing the complex semantics among drug-related biological entities. Moreover, the results of case study demonstrate that the designed attention mechanism is able to provide partial interpretability for the predicted DDIs. Therefore, the proposed method will be a feasible solution to the task of predicting DDIs.

Brief Report: Sex Differences in the Association Between Cerebrovascular Function and Cognitive Health in People Living With HIV in Urban China

BACKGROUND

Cardiometabolic and cerebrovascular disease are strong independent contributors to cognitive impairment in people living with HIV. Data suggest that cardiovascular risk may play a greater role in cognitive health in women than in men with HIV.

METHODS

We performed a cross-sectional study of 104 participants with virologically suppressed HIV from 2 clinics in urban China. Participants underwent neuropsychological testing from which we calculated T scores globally and in 5 cognitive domains. We assessed cerebral vasoreactivity of the middle cerebral arteries in response to breath holding. We constructed linear regression models to determine associations between cerebrovascular and cognitive function overall and stratified by sex.

RESULTS

Women were younger than men (48 versus 51 years, P = 0.053), had fewer years of education (9 years versus 12 years, P = 0.004), and fewer cardiometabolic risk factors (0 versus 1 factor, P = 0.008). In a model with all participants, cerebrovascular function was significantly associated with global cognition (2.74 higher T score per 1-point higher cerebral vasoreactivity [SE 1.30], P = 0.037). Cerebrovascular function remained significantly associated with global cognition among women (4.15 higher T score [SE 1.78], P = 0.028) but not men (1.70 higher T score [SE 1.74], P = 0.33). The relationships between cerebrovascular function and specific cognitive domains followed a similar pattern, with significant associations present among women but not men.

CONCLUSIONS

Women with well-controlled HIV may be more vulnerable to the effect of cerebrovascular injury on cognitive health than men. Studies evaluating strategies to protect against cognitive impairment in people living with HIV should include adequate representation of women and stratification of analyses by sex.

The association of sleep quality and burnout among Chinese medical residents under standardized residency training in a tertiary hospital

PURPOSE

To investigate the impact of sleep quality and chronotype on job burnout among medical residents under standardized residency training (SRT) in a tertiary hospital in Beijing, China.

METHODS

Medical residents in the Department of Internal Medicine of Peking Union Medical College Hospital were assessed by Morning and Evening Questionaire-5 (MEQ-5), Pittsburgh sleep quality index (PSQI), and Maslach Burnout Inventory-General Survey (MBI-GS). Factors associated with burnout were analyzed.

RESULTS

A total of 142 respondents returned completed questionnaires. Burnout was present in 85 (60%) residents. Prevalence of high emotional exhaustion, high depersonalization, and low personal accomplishment were 51%, 28%, and 18%, respectively. The global PSQI score of residents was 5.9 ± 2.4, and the self-reported sleep duration was 6.2 ± 0.8 h/day. The MEQ-5 distribution skewed towards morningness, with a median score of 14.5 [13.0, 16.3]. Poor daytime function significantly predicted emotional exhaustion and depersonalization. Chronotypes were not associated with any of the burnout components.

CONCLUSION

Sleep-related daytime dysfunction was strongly related to burnout. Strategies protecting the sleep of residents should be incorporated into the SRT programs for both efficiency and sustainability considerations.

Compensating for gyroradius effects in beamlines with small Helmholtz coils

Measurements of lighter, low-energy charged particles in a laboratory beamline are complicated due to the influence of Earth's magnetic field. Rather than nulling out the Earth's magnetic field over the entire facility, we present a new way to correct particle trajectories using much more spatially limited Helmholtz coils. This approach is versatile and easy to incorporate in a wide range of facilities, including the existing ones, enabling measurements of low-energy charged particles in a laboratory beamline.

[Nontuberculous mycobacteria infection and pulmonary alveolar proteinosis in a patient with hematopoietic defects]

A 28-year-old male with a history of leukopenia was admitted with complaints of fever, cough, and dyspnea for 3 months. Initial work-up identified reduced circulating levels of granulocytes, monocytes, lymphocytes, and NK cells. Computed tomography revealed bilateral reticulonodular opacities and mediastinal lymph node enlargement. Peripheral blood culture and mediastinal lymph node aspiration yielded Mycobacterium avium. Genetic testing revealed a heterozygous germline GATA2 mutation (c.1187G>A, R396Q). Despite standard anti-mycobacterial therapy, the patient's dyspnea worsened and subsequent imaging studies revealed diffuse ground-glass opacification. A transbronchial lung biopsy confirmed the development of pulmonary alveolar proteinosis. Bone marrow transplantation had not been performed due to the unavailability of suitable donors. The disease progressed after whole lung lavage, and the patient died at the age of 31 years from respiratory failure. The current case report emphasized the importance of raising awareness about the rare GATA2 deficiency, which is characterized by hematologic abnormalities, primary immunodeficiency, and pulmonary alveolar proteinosis.

[Clinical and pathological features and differential diagnosis of fibro-osseous tumors and dysplasias]

Fibro-osseous lesions is a class of diseases with obvious similarities in clinical manifestations and pathological features, which has been attracting the attention of clinicians and pathologists. The latest WHO 2022 Classification (5th edition) included six of these diseases (cemento-osseous dysplasia, segmental odontomaxillary dysplasia, fibrous dysplasia, juvenile trabecular ossifying fibroma, psammomatoid ossifying fibroma and familial gigantiform cementoma) in the " fibro-osseous tumours and dysplasias ", and put forward new ideas on the diagnosis and treatment of these diseases. According to the latest WHO 2022 Classification (5th edition), the clinical and pathological features, diagnosis and differential diagnosis of these six diseases were described.

Stigmatized experience is associated with exacerbated pain perception in depressed patients

Patients with depression not only have to cope with depressive and physical symptoms but also face stigmatization due to mental illness. Pain is a clinical symptom of many patients with depression. However, it is unclear whether stigmatized experience associated with mental illness directly affects depressed patients' pain perception. Here, using the event reflection task, Study 1 (N = 95) examined whether stigmatized experiences due to depression would affect patients' self-reported pain assessment. Study 2 (N = 43) further employed thermal stimuli at different intensities to examine whether stigmatization would affect patients' evoked pain. We found that patients with depression who experienced stigmatization based on mental illness reported higher pain catastrophizing and performed increased pain perception for noxious stimuli than those who did not. Our studies provide first-hand experimental evidence of the effect of stigmatized experiences on depressed patients' pain perception. The findings contribute insights for improving clinical treatment, suggesting that interventions should minimize stigmatization associated with mental illness to help patients maintain healthier physical and psychological states.

[Research progress of tunneling nanotube in bone biology]

Tunneling nanotube (TNT) is a newly discovered communication mode between animal cells in recent years, which have important physiological and pathological significance. However, the role of TNT in bone biology is still unclear. At present, there are many reports about tunneling nanotubes in bone marrow mesenchymal stem cells, osteoclast precursor cells, osteoblasts and immune cells. This review describes the research advances of TNT and its research progress in bone biology. It looks forward to the research direction of TNT in oral and maxillofacial bone development and bone biology, to provide new strategies for the maintenance of bone homeostasis and the treatment of bone diseases.

Response of sugar metabolism in the cotyledons and roots of Ricinus communis subjected to salt stress

Ricinus communis is an important oilseed crop worldwide and is also considered one of the best potential plants for salt-affected soil improvement in northeast China. However, little is known about photosynthesis and carbohydrate metabolism in this plant, nor the distribution of carbohydrates in cotyledons and roots under salinity stress. In the present study, seedling growth, gas exchange parameters (P_N , E, g_s and C_i ), carbohydrate (fructose, sucrose, glucose, soluble sugar and starch) metabolism and related enzymes and genes were measured in Ricinus plants. Under salt stress, P_N of cotyledons decreased significantly (P < 0.05), resulting in weak photosynthetic capacity. Furthermore, salt stress increased sucrose and glucose content in cotyledons, but decreased soluble sugar and starch content. However, sucrose increased and starch decreased in roots. This may be correlated with the increasing sugar metabolism under salinity, including notable changes in sugar-related enzyme activities (SPS, SuSy, α-amylase and β-amylase) and gene expression of RcINV, RcSUS, RcAmY, RcBAM and RcGBE1. The results suggest that salinity reduces photosynthesis of cotyledons, alters carbohydrate allocation between cotyledons and roots and also promotes starch utilization in cotyledons and starch biosynthesis in roots, leading to a functional imbalance between cotyledons and roots. Together, these findings provide insights into the crucial role of sugar metabolism in improving salt-tolerance of Ricinus during the early seedling growth stage.

High-risk group and functional subtypes of non-suicidal self-injury in young adults with mental disorders

BACKGROUND

Identifying high-risk groups of non-suicidal self-injury (NSSI) with multiple risk factors and different functional subtypes contribute to implementing person-centered interventions.

METHODS

We investigated NSSI profiles among a sample of 258 psychiatric inpatients aged 18-25 years. All participants completed well-validated measures of internal personal and external environmental characteristics. One-hundred and ninety patients reported a lifetime history of NSSI and completed an additional NSSI assessment. A k-means cluster analysis was conducted to extract characteristics of risk factors and functional subtypes. Independent sample t-test, analysis of variance and χ ² test were used to test the difference of demographic statistical factors, risk factors and functional scores among groups with different frequency of NSSI.

RESULTS

The clustering of risk factors analyses supported 4-clusters. The proportion of repeat NSSI patients was the highest (67.1%) in the group with unfavorable personal and unfavorable environmental characteristics. Functional subtype clustering analyses supported 5-clusters. Among patients with repeated NSSI, those with depression were mainly accompanied by the "Sensation Seeking" subtype (39.7%), bipolar disorder mainly supported the "Anti-suicide" subtype (37.9%), and eating disorders were mostly "Social Influence" subtype (33.3%). There was an interaction between functional subtypes and mental disorders.

LIMITATIONS

All participants were in treatment in a psychiatric service and the results may not be generalizable to a community sample. The data included retrospective self-report which may be inaccurate due to recall bias.

CONCLUSION

It is necessary to identify high-risk groups of NSSI who with unfavorable personal and environmental characteristics and clinical interventions need to consider the heterogeneity of patients' functional subtypes of NSSI.

Optimal cutoff scores of the Chinese version of 15-item negative symptom assessment that indicate prominent negative symptoms of schizophrenia

Objective

The Chinese version of 15-item negative symptom assessment (NSA-15) is an instrument with a three-factor structure specifically validated for assessing negative symptoms of schizophrenia. To provide a reference for future practical applications in the recognition of schizophrenia patients with negative symptoms, this study aimed to determine an appropriate NSA-15 cutoff score regarding negative symptoms to identify prominent negative symptoms (PNS).

Methods

A total of 199 participants with schizophrenia were recruited and divided into the PNS group (n = 79) and non-PNS group (n = 120) according to scale for assessment of negative symptoms (SANS) scores. Receiver-operating characteristic (ROC) curve analysis was used to determine the optimal NSA-15 cutoff score for identifying PNS.

Results

The optimal cutoff NSA-15 score for identifying PNS was 40. Communication, emotion and motivation factors in the NSA-15 had cutoffs of 13, 6, and 16, respectively. The communication factor score had slightly better discrimination than scores on the other two factors. The discriminant ability of the global rating of the NSA-15 was not as good as that of the NSA-15 total score (area under the curve (AUC): 0.873 vs. 0.944).

Conclusion

The optimal NSA-15 cutoff scores for identifying PNS in schizophrenia were determined in this study. The NSA-15 provides a convenient and easy-to-use assessment for identifying patients with PNS in Chinese clinical situations. The communication factor of the NSA-15 also has excellent discrimination.

The alternate-form reliability study of six variants of the Brief Visual-Spatial Memory Test-Revised and the Hopkins Verbal Learning Test-Revised

Introduction

The revised Hopkins Verbal Learning Test-Revised (HVLT-R) and the Brief Visual-Spatial Memory Test-Revised (BVMT-R) are two widely used test involving verbal and visual learning and memory. In the two tests, six different versions are assembled, respectively, to prevent learning effects. Currently, no researchers have compared the six versions of the two tests. Thus, their usefulness in clinical studies requiring multiple follow-ups is limited. In this work, we confirm the equivalence of six HVLT-R and BVMT-R versions.

Methods

20 people completed all six HVLT-R and BVMT-R versions, while 120 people were randomly assigned to complete one of the six versions of each test. The Intelligence Quotient (IQ) level is measured using the short version of the Wechsler Adult Intelligence test. R4.2.0 is used for statistical analysis. The K-Related sample test (a non-parametric test) is used to observe the differences in test scores among the 20 subjects. The one-way Analysis of Variance (ANOVA) test is utilized to analyze the differences in test scores among the 120 subjects. The scores on different versions are compared using two similar sample tests. The HVLT-R Total Learning, the HVLT-R Delayed Recall, the BVMT-R Total Learning, and the BVMT-R Delayed Recall are indexes for comparison. Version and test scores are used as research factors, while different versions are used as research levels.

Results

The results suggest that HVLT-R and BVMT-R versions 3, 5 and 6 are equally difficult, and relatively easy compared to versions 1, 2 and 4. HVLT-R versions 3, 5, and 6 show good reliability and can be used interchangeably when testing word learning ability or short-term memory; BVMT-R Versions 3, 5, and 6 show acceptable reliability and can be can be used interchangeably.

Discussion

In the study of multiple follow-ups, it is a must to avoid discrepant versions and choose other equivalent versions. The results from this study could be used as a guide for upcoming studies and clinical applications in China.

The Chinese Version of Oxford Depression Questionnaire: A Validation Study in Patients with Mood Disorders

Background

Emotional blunting is prevalent in patients with mood disorders and adversely affects the overall treatment outcome. The Oxford Depression Questionnaire is a validated psychometric instrument for assessing emotional blunting. We aimed to evaluate the reliability and validity of the Chinese version of the ODQ (ODQ) in Chinese patients with mood disorders.

Methods

136 mood disorders patients and 95 healthy control participants were recruited at the First Affiliated Hospital of Zhejiang University, School of Medicine. Patients were assessed using the ODQ, Beck Depression Inventory-II (BDI-II), and Montgomery-Asberg Depression Rating Scale (MADRS). Internal consistency reliability and test-retest reliability were analyzed. Confirmatory factor analysis and correlation analysis were used to evaluate construct and convergent validity.

Results

A total of 136 patients with mood disorders and 95 healthy controls participated in this study. Cronbach α values were 0.928 (ODQ-20) and 0.945 (ODQ-26). Test-retest reliability coefficients were 0.798 (ODQ-20) and 0.836 (ODQ-26) (p<0.05); intraclass correlation coefficient values were 0.777 (ODQ-20) and 0.781 (ODQ-26) (p<0.01). The score of ODQ was positively correlated with BDI-II and MADRS (r=0.326~0.719, 0.235~0.537, p<0.01). The differences in the ODQ scores between the patient and control groups were statistically significant.

Conclusion

The reliability, structural validity, and criterion validity of the ODQ applied to patients with mood disorders meet the psychometric requirements, and the scale can be used to assess emotional blunting in Chinese patients with mood disorders.

Relationship between Social Support, Sarcopenia, and Cognitive Impairment in Chinese Community-Dwelling Older Adults

BACKGROUND

Cognitive impairment and sarcopenia have become important challenges for the growing aging population. Social support has been shown to protect against cognitive impairment, but its impact on sarcopenia remains unknown. The purpose of this study was to explore the correlation between social support, sarcopenia, and cognitive impairment in Chinese older adults.

METHOD

A multi-stage whole group sampling method was used to conduct a cross-sectional survey of 720 community-dwelling older people in Shanghai. The definition of sarcopenia was in accordance with the criteria of the Asian Working Group for Sarcopenia (AWGS) 2019. Cognitive impairment was evaluated using a computerized neuropsychological assessment device that had been previously validated. Social support was assessed using the Social Support Rate Scale. Logistic regression analyses were conducted to explore the relationship between social support cognitive impairment and sarcopenia, fully adjusting for all potential confounding factors.

RESULTS

Our study found that 230 (31.94%) of the participants had cognitive impairment and 97 (13.47%) of the participants had sarcopenia. The mean social support score was 35.10 ± 7.54. Besides, the results showed that cognitive impairment was associated with sarcopenia (OR:1.650, 95% CI: 1.048, 2.596, P=0.030) after adjusting for confounding factors. Older adults with high level social support had the lowest risk of cognitive impairment (OR: 0.297, 95% CI: 0.115, 0.680, P=0.021) and sarcopenia (OR: 0.113, 95% CI: 0.031, 0.407, P=0.001), respectively.

CONCLUSION

Our analysis revealed that high level social support was negatively associated with sarcopenia and cognitive impairment. These findings provide strong support for the health promotion effect of social networks against sarcopenia and cognitive impairment in Chinese community-dwelling older adults, with important implications for healthcare policy makers.

Evaluation of pH regulation in carbohydrate-type municipal waste anaerobic co-fermentation: Roles of pH at acidic, neutral and alkaline conditions

This study investigated and evaluated the roles of acidic (pH 4.0), neutral (pH 7.0) and alkaline (pH 10.0) in anaerobic co-fermentation of sewage sludge and carbohydrate-type municipal waste. CO₂, CH₄ and H₂ are produced in acidic, neutral and alkaline fermentation, respectively. The neutral co-fermentation contained the vast number of aqueous metabolites as total of 22.12 g/L, with the advantage of over 50 % biodegradable components in extracellular polymeric substance and over 80 % hydrolysis rate. Acidic and alkaline pH facilitated ammonia release, with the max concentration of 0.46 g/L and 0.44 g/L, respectively. Microbial analysis indicated that pH is the key parameter to impact microbial activity and drive microbial community transition. The high abundance of Lactobacillus, Bifidobacterium and Clostridium was associated with harvest of ethanol, lactic acid and acetate in acidic, neutral and alkaline fermentation. Meanwhile, the floc feature showed better dewaterability (zeta potential -8.48 mV) and poor nutrient convey (distribution spread index 1.03) in acidic fermentation. In summary, acidic and alkaline fermentation were prioritised for targeted spectrum. Neutral fermentation was prioritised for high production. This study presented an upgraded understanding of the pH role in fermentation performance, microbial structure and sludge behaviour, which benefits the development of fermentation processing unit.

The Analgesic Efficacy of Intraperitoneal Ropivacaine Versus Bupivacaine for Laparoscopic Cholecystectomy: a Meta-Analysis

Introduction This meta-analysis aimed to compare the analgesic efficacy of intraperitoneal ropivacaine versus bupivacaine for laparoscopic cholecystectomy.

Methods We searched PubMed, EMbase, Web of Science, EBSCO, and Cochrane Library databases from inception through January 2020 and included randomized controlled trials (RCTs) evaluating the analgesic efficacy of ropivacaine versus bupivacaine for laparoscopic cholecystectomy.

Results Five RCTs are included in the meta-analysis. In patients with laparoscopic cholecystectomy, ropivacaine and bupivacaine demonstrated comparable pain scores at 2 h (SMD = –0.22; 95% CI = –0.54 to 0.10; p = 0.18), 4 h (SMD = –0.16; 95% CI = –0.42 to 0.10; p = 0.22), 8 h (SMD = –0.60; 95% CI = –1.19 to –0.01; p = 0.05), and 24 h (SMD = 0.33; 95% CI = –1.19 to 1.84; p = 0.67), as well as time to first analgesic requirement (SMD = 0.10; 95% CI = –0.23 to 0.42; p = 0.56).

Conclusions Intraperitoneal ropivacaine and bupivacaine have a similar analgesic efficacy for laparoscopic cholecystectomy.

Ion Flux Self-Regulation Strategy with a Volume-Responsive Separator for Lithium Metal Batteries

Lithium metal batteries (LMBs) are regarded as one of the most promising next-generation energy storage devices due to their high energy density. However, the conversion of LMBs from laboratory to factory is hindered by the formation of lithium dendrites and volume change during lithium stripping and deposition processes. In this work, a volume-responsive separator with core/shell structure thermoplastic polyurethane (TPU)/polyvinylidene fluoride (PVDF) fibers and SiO₂ coating layers is designed to restrict dendrite growth. The TPU/PVDF-SiO₂ separator can accommodate the volume change like an artificial lung and keep intimate contact with the electrodes, which leads to the formation of a uniform and high-density solid-electrolyte interphase. Meanwhile, the separator can regulate the transport channels and diffusion coefficients (D) of lithium ions with the change of porosity from both experimental and ab initio molecular dynamic analysis. The Li symmetric cells assembled with the TPU/PVDF-SiO₂ can run for 1000 h at the current of 1.0 mA cm^-2 without a short circuit. Moreover, the low melting point of PVDF can shut the ionic conduction down at 170 °C, guaranteeing the thermal safety of the batteries. With the above advantages, the TPU/PVDF-SiO₂ separator presents great potential to promote the commercial and industrial application of LMBs.

[Changes of the World Health Organization 2022 classification (5th edition) of salivary glands tumors]

Pathological diagnosis of salivary gland tumors is one of the most challenging areas in all head and neck surgical pathology. The classification of salivary gland tumors was updated in the 5th edition of the World Health Organization Classification of Head and Neck Tumours, most of which were based on their molecular pathological characteristerics. This new classification features a description of several new entitiesamong benign and malignant neoplasms, salivary gland tumors with updated naming or diagnostic criteria, and lesions deleted from this section, etc.This present review focuses on the updates and changes in the new classification of salivary gland tumors, and provides some reference for head and neck surgeons and pathologists.

Plasma synthesis of defect-rich flexible carbon cloth decorated with PtRu alloyed nanoclusters for highly efficient pH-universal electrocatalytic hydrogen evolution

Designing electrocatalysts with superior activity and stability to Pt/C for the highly efficient pH-universal electrochemical hydrogen evolution reaction (HER) still remains an urgent challenge. Herein, we report a facile plasma method for the preparation of defect-rich flexible carbon cloth decorated with ultralow-loading (0.1 wt%) PtRu alloyed nanoclusters (PtRu/CC-P) to resolve these problems. Remarkably, the developed PtRu/CC-P catalyst delivered a high mass activity of 3.77 A mg^-1 (η = 100 mV), almost 3.6 times higher than that of the benchmark HER electrocatalyst 20%Pt/C (1.05 A mg^-1). Meanwhile, it only required a low overpotential of 44 mV to achieve a current density of 10 mA cm^-2 in alkaline media. Systematic experimental and DFT calculation results revealed that the Pt-Ru bridge of PtRu alloyed nanoclusters in PtRu/CC-P can optimize the adsorption strength of HER intermediates at active sites, decrease the H₂O dissociation energy barrier, and consequently facilitate the HER kinetics. Inspiringly, when the PtRu content was increased to 1 wt%, PtRu/CC-P still exhibited a relatively low overpotential of 276 mV even at a high current density of 1000 mA cm^-2 and maintained excellent durability at a relatively high current density of 50-500 mA cm^-2 for more than 15 h in alkaline media. In addition, PtRu/CC-P also showed brilliant HER activity and stability in neutral and acidic media. This facile method provides a feasible route for the rational design of Pt-based alloyed catalysts toward industrial hydrogen production at all-pH values.

Aromatic chloroosmacyclopentatrienes

Aromatic metallacycles are of considerable current interest. Reported aromatic metallacycles are mainly those with carbon, nitrogen, oxygen and sulfur. In this work, we report the synthesis and characterization of aromatic chloroosmacyclopentatrienes, which represent the first structurally confirmed metallaaromatics with a chlorine atom in its framework. Single crystal X-ray diffraction studies show that these planar chloroosmacyclopentatrienes possess a very short Os–ClC distance suggesting M = ClC bond character.

Genome-Wide Diversity Analysis of African Swine Fever Virus Based on a Curated Dataset

Simple Summary

African swine fever (ASF) is one of the most important animal diseases affecting the domestic swine population globally. Whole-genome sequence analysis on the circulating African swine fever virus (ASFV) strains would provide valuable information in tracking the outbreaks of the disease. The aim of this study was to prepare a curated dataset of ASFV genome sequences and investigate genome-wide diversity of circulating ASFV strains. We prepared a curated dataset containing 123 high-quality ASFV genome sequences representing 10 genotypes collected from 28 countries between 1949 and 2020. Phylogenetic analysis based on whole-genome sequences provided high-resolution topology in genotyping ASFV isolates, which was supported by pairwise genome sequence similarity comparison. Wide distribution and high variation of tandem repeat sequences were found in ASFV genomes. Structural variation and highly variable poly G or poly C tracts were also identified. This study improved our understanding on the patterns of genetic variation of ASFV and facilitated future studies on ASFV molecular epidemiology.

Abstract

African swine fever (ASF) is a lethal contagious viral disease of domestic pigs and wild boars caused by the African swine fever virus (ASFV). The pandemic spread of ASF has had serious effects on the global pig industry. Virus genome sequencing and comparison play an important role in tracking the outbreaks of the disease and tracing the transmission of the virus. Although more than 140 ASFV genome sequences have been deposited in the public databases, the genome-wide diversity of ASFV remains unclear. Here we prepared a curated dataset of ASFV genome sequences by filtering genomes with sequencing errors as well as duplicated genomes. A total of 123 ASFV genome sequences were included in the dataset, representing 10 genotypes collected between 1949 and 2020. Phylogenetic analysis based on whole-genome sequences provided high-resolution topology in differentiating closely related ASFV isolates, and drew new clues in the classification of some ASFV isolates. Genome-wide diversity of ASFV genomes was explored by pairwise sequence similarity comparison and ORF distribution comparison. Tandem repeat sequences were found widely distributed and highly varied in ASFV genomes. Structural variation and highly variable poly G or poly C tracts also contributed to the genome diversity. This study expanded our knowledge on the patterns of genetic diversity and evolution of ASFV, and provided valuable information for diagnosis improvement and vaccine development.

Activation of PI3K/Akt prevents hypoxia/reoxygenation-induced GnRH decline via FOXO3a

Recent studies have suggested that the hypothalamus has an important role in aging by regulating nuclear factor-κB (NF-κB)-directed gonadotropin-releasing hormone (GnRH) decline. Moreover, our previous study has shown that ischemia-reperfusion (IR) injury activates NF-κB to reduce hypothalamic GnRH release, thus suggesting that IR injury may facilitate hypothalamic programming of system aging. In this study, we further examined the role of phosphoinositide 3-kinase (PI3K)/Protein kinase B (Akt) pathway, a critical intracellular signal pathway involved in the repair process after IR, in hypoxia-reoxygenation (HR)-associated GnRH decline in vitro. We used GT1-7 cells and primarily-cultured mouse GnRH neurons as cell models for investigation. Our data revealed that the activation of the PI3K/Akt/Forkhead box protein O3a (FOXO3a) pathway protects GnRH neurons from HR-induced GnRH decline by preventing HR-induced gnrh1 gene inhibition and NF-κB activation. Our results further the understanding of the regulatory mechanisms of HR-associated hypothalamic GnRH decline.

Effects of age, sex, and education on California Verbal Learning Test-II performance in a Chinese-speaking population

The California Verbal Learning Test-Second Edition (CVLT-II), is a commonly used tool to assess episodic memory. This study analyzed learning and memory characteristics in a cognitively healthy Chinese population, as well as the effects of age, sex and education on CVLT-II factors. In total, 246 healthy people aged 20–80 years and 29 persons with multiple sclerosis (MS) were included in this study and completed the CVLT-II. Factors including total learning, learning strategy, serial position effects, short-delay free and cued recall, long-delay free and cued recall, repetitions and intrusions during recall, hits and false positives of recognition, and total recognition discriminability were calculated. The effects of age, sex and education on these factors were analyzed using ANCOVA or independent two-sample t-tests and further confirmed by multiple regression analysis. The regression-based normative data were then computed by the equivalent scores method. Moreover, differences in learning and memory were compared between persons with MS and age-, sex- and education-matched healthy individuals. Most CVLT-II factors significantly differed between different age and education groups; in particular, better performance in total learning, recall, semantic clustering and recognition was observed in the younger and more educated groups than in the older and less educated groups. Male participants showed higher recency effect scores, more repetitions and fewer hits than female participants. Compared with healthy individuals, persons with MS showed extensive impairments in memory processes, such as learning, recall, learning strategy and recognition (p &lt; 0.05). These findings indicated that verbal learning and memory were highly dependent on age and educational level but not strongly affected by sex. The CVLT-II effectively assesses episodic memory impairment in the Chinese-speaking population.