[Retracted] Anthelmintic drug albendazole arrests human gastric cancer cells at the mitotic phase and induces apoptosis.

[This retracts the article DOI: 10.3892/etm.2016.3992.].

Untargeted metabolomics revealed the effect of soybean metabolites on poly(γ-glutamic acid) production in fermented natto and its metabolic pathway.

BACKGROUND: Natto mucus is mainly composed of poly(γ-glutamic acid) (γ-PGA), which affects the sensory quality of natto and has some effective functional activities. The soybean metabolites that cause different γ-PGA contents in different fermented natto are unclear. RESULTS: In this study, we use untargeted metabolomics to analyze the metabolites of high-production γ-PGA natto and low-production γ-PGA natto and their fermented substrate soybean. A total of 257 main significantly different metabolites with the same trend among the three comparison groups were screened, of which 114 were downregulated and 143 were upregulated. Through the enrichment of metabolic pathways, the metabolic pathways with significant differences were purine metabolism, nucleotide metabolism, fructose and mannose metabolism, anthocyanin biosynthesis, isoflavonoid biosynthesis and the pentose phosphate pathway. CONCLUSION: For 114 downregulated main significantly different metabolites with the same trend among the three comparison groups, Bacillus subtilis (natto) may directly decompose them to synthesize γ-PGA. Adding downregulated substances before fermentation or cultivating soybean varieties with the goal of high production of such substances has a great effect on the production of γ-PGA by natto fermentation. The enrichment analysis results showed the main pathways affecting the production of γ-PGA by Bacillus subtilis (natto) using soybean metabolites, which provides a theoretical basis for the production of γ-PGA by soybean and promotes the diversification of natto products. © 2023 Society of Chemical Industry.

Building a predictive model for hypertension related to environmental chemicals using machine learning.

Hypertension is a chronic cardiovascular disease characterized by elevated blood pressure that can lead to a number of complications. There is evidence that the numerous environmental substances to which humans are exposed facilitate the emergence of diseases. In this work, we sought to investigate the relationship between exposure to environmental contaminants and hypertension as well as the predictive value of such exposures. The National Health and Nutrition Survey (NHANES) provided us with the information we needed (2005-2012). A total of 4492 participants were included in our study, and we incorporated more common environmental chemicals and covariates by feature selection followed by regularized network analysis. Then, we applied various machine learning (ML) methods, such as extreme gradient boosting (XGBoost), random forest classifier (RF), logistic regression (LR), multilayer perceptron (MLP), and support vector machine (SVM), to predict hypertension by chemical exposure. Finally, SHapley Additive exPlanations (SHAP) were further applied to interpret the features. After the initial feature screening, we included a total of 29 variables (including 21 chemicals) for ML. The areas under the curve (AUCs) of the five ML models XGBoost, RF, LR, MLP, and SVM were 0.729, 0.723, 0.721, 0.730, and 0.731, respectively. Butylparaben (BUP), propylparaben (PPB), and 9-hydroxyfluorene (P17) were the three factors in the prediction model with the highest SHAP values. Comparing five ML models, we found that environmental exposure may play an important role in hypertension. The assessment of important chemical exposure parameters lays the groundwork for more targeted therapies, and the optimized ML models are likely to predict hypertension.

Associations between exposure to ambient particulate matter and advanced liver fibrosis in Chinese MAFLD patients.

BACKGROUND & AIMS: Liver fibrosis is an important feature in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). This study aimed to explore the association between long-term ambient particulate matter (PM) exposure and advanced liver fibrosis (ALF) in MAFLD participants. METHODS: A cross-sectional study of 23170 adults recruited from 33 provinces of China from 2010 to 2020. ALF was detected using the nonalcoholic fatty liver disease fibrosis score (NFS). The annual average levels of particulate matter with aerodynamic diameters of ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5) and ≤ 10 µm (PM10) were calculated using validated spatiotemporal models. Generalized additive models were applied to analyze the association between PM and ALF in patients with MAFLD. RESULTS: One-year exposure to higher levels of all PM was found to increase the risk of ALF, with odds ratios (ORs) of 1.10 (95% CI 1.06-1.14), 1.05 (1.03-1.07), and 1.03(1.02-1.04) for each 10 µg/m3 increase in PM1, PM2.5 and PM10, respectively. With the dissection of the impact of PM1 in PM2.5, PM2.5 in PM10 and PM1 in PM10, we found that PM2.5 had a stronger impact on ALF (both Pinteraction＜0.05) in comparison with PM1 and PM10. CONCLUSIONS: Long-term exposure to PM is associated with ALF in patients with MAFLD, with PM2.5 playing a dominant role.

Role of Serum CYFRA 21-1 in Diagnosis and Prognostic in Colorectal Liver Metastases.

Purpose: In current studies, the role of serum Cytokeratin-19 fragments (CYFRA 21-1) in colorectal cancer (CRC) remains unclear. This study aimed to clarify the diagnostic and prognostic value of CYFRA 21-1 in CRC. Patients and Methods: Data were collected for 196 stage I-III CRC patients and 50 colorectal liver metastases (CRLM) patients between January 2018 and December 2019. The serum CYFRA 21-1 levels were measured using the chemiluminescent particle immunoassay (CMIA) kit in all objects and common biomarkers such as CA19-9, CEA, HSP90α, and AFP were measured in all colorectal cancer patients. We investigated the association between CYFRA 21-1 level and clinicopathological features. In addition, we evaluated the ability of serum CRFRA21-1 to differentiate CRLM from CRC. To assess the potential prognostic value, we used Cox proportional hazard model for univariate or multivariate analyses. Results: Serum CYFRA 21-1 was significantly elevated in CRLM patients compared to stage I-III CRC patients (5.85 ng/mL vs 2.29 ng/mL, p < 0.001). For all CRC patients cohort, stage I-III CRC patients cohort and CRLM patients cohort, the optimal cutoff levels of CYFRA 21-1 for overall survival (OS) were 3.47 ng/mL, 2.14 ng/mL and 7.63 ng/mL, respectively, and the optimal cutoff levels for progression-free survival (PFS) were 3.47 ng/mL, 2.56 ng/mL and 7.63 ng/mL, respectively. For CRLM patients, Kaplan-Meier analysis showed that patients with high CYFRA 21-1 level had poor OS. Multivariate analysis indicated that the CYFRA 21-1 level was an independent prognostic factor for PFS in stage I-III patients. And CYFRA 21-1 levels and age were independent prognostic factors for OS and PFS in CRLM patients. Conclusion: CYFRA 21-1 can better differentiate CRLM patients from the whole CRC patients and has unique prognostic value for CRLM patients.

Dietary diversity and possible sarcopenia among older people in China: a nationwide population-based study.

Background: Sarcopenia is a common geriatric disease. Many dietary factors may contribute to the development of sarcopenia. Few studies have been conducted on dietary diversity and sarcopenia in Chinese older adults. Among a nationwide sample, the objective of this study is to assess the association between the dietary diversity score (DDS) and the prevalence of possible sarcopenia. We considered the different patterns of dietary diversity in relation to possible sarcopenia. Methods: We conducted this analysis utilizing the cross-sectional data from the 2012, 2014, and 2018 waves of the Chinese longitudinal healthy longevity survey (CLHLS). A standard developed by the Asian Working Group for Sarcopenia 2019 (AWGS2019) was used to assess the possibility of sarcopenia. On the basis of the DDS generated by previous studies, we have constructed four new indicators as follows: total diet, animal-based diet, plant-based diet, and plant-based diet without the consumption of legume products and nuts. We used the generalized estimation equation (GEE) model to evaluate the associations between the DDS of the total diet, animal-based diet, plant-based diet, and plant-based diet without the intake of legume products and nuts and possible sarcopenia. These associations were statistically adjusted for a variety of potential confounders. Sensitivity analysis was performed by excluding some participants who were long-term bedridden, had Alzheimer's disease, or were terminally ill. Results: The analysis included 6,624 participants (mean age 83.4 years at baseline). In our study, we found that participants with a higher DDS of the total diet (OR = 0.62; 95% CI: 0.51-0.77), animal-based diet (OR = 0.62; 95% CI: 0.49-0.79), and plant-based diet (OR = 0.64;95% CI: 0.51-0.80) were at a lower risk of developing sarcopenia. In sensitivity analyses, the associations remained unchanged. Conclusion: Taking a diversified diet, including animal foods, may reduce the risk of developing sarcopenia. According to the findings of this study, adopting a diversified diet might reduce the risk of sarcopenia for older adults.

Oral nicotinamide mononucleotide (NMN) to treat chronic insomnia: protocol for the multicenter, randomized, double-blinded, placebo-controlled trial.

BACKGROUND: The treatment of insomnia, which is the most common sleep disorder, includes drug and behavioral treatment, but each treatment measure has its limitations. So new treatment method needs to be taken to improve the treatment effect. MN supplementation is a potential promising new method for the treatment of insomnia, resulting in a rising need for methodological research towards verifying its efficacy. METHODS/DESIGN: We describe a proposal for a multicenter, patient-assessor-blinded, randomized controlled trial with two parallel arms. A total of 400 chronic insomnia patients will be allocated 1:1 to the intervention group (treatment with oral NMN 320 mg/day) or control group (treatment with oral placebo). All subjects are clinical chronic insomnia patients who meet all inclusion criteria. All subjects are treated by taking NMN or placebo. The primary outcome is the score on the Pittsburgh Sleep Quality Index (PSQI). Secondary outcomes are the score on the Insomnia Severity Index (ISI) and Epworth Sleeping Scale (ESS), the total sleep time (TST), sleep efficiency (SE), sleep latency, and REM sleep latency to assess sleep quality changes. Subjects are assessed at two time points: baseline and follow-up. The duration of the clinical trial is 60 days. DISCUSSION: This study will provide more evidence on the effects of NMN on improving sleep quality among patients with chronic insomnia. If proven effective, NMN supplement can be used as a new treatment for chronic insomnia in the future. TRIAL REGISTRATION: Chinese Clinical Trial Registry (chictr.org.cn) ChiCTR2200058001. Registered on 26 March 2022.

Negative electrodes for supercapacitors with good performance using conductive bismuth-catecholate metal-organic frameworks.

Metal-organic frameworks (MOFs) have attracted increasing research interest in various fields. Unfortunately, the poor conductivity of most traditional MOFs considerably hinders their application in energy storage. Benefiting from the full charge delocalization in the atomic plane, two-dimensional conductive coordination frameworks achieve good electrochemical performance. In this work, π-π coupling conductive bismuth-catecholate nanobelts with tunable lengths, Bi(HHTP) (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene), are synthesized by a simple hydrothermal reaction and their length-dependent electrochemical properties are also investigated. The Bi(HHTP) nanobelts (about 10 µm in length) possess appropriate porosity, numerous redox active sites and good electrical conductivity. Being a negative electrode for supercapacitors, Bi(HHTP) nanobelts display a high specific capacitance of 234.0 F g-1 and good cycling stability of 72% after 1000 cycles. Furthermore, the mechanism of charge storage is interpreted for both battery-type and surface-capacitive behavior. It is believed that the results of this work will help to develop battery-type negative electrode materials with promising electrochemical performance using some newly designed π-π coupling conductive coordination frameworks.

Association of IgG N-glycomics with prevalent and incident type 2 diabetes mellitus from the paradigm of predictive, preventive, and personalized medicine standpoint.

Objectives: Type 2 diabetes mellitus (T2DM), a major metabolic disorder, is expanding at a rapidly rising worldwide prevalence and has emerged as one of the most common chronic diseases. Suboptimal health status (SHS) is considered a reversible intermediate state between health and diagnosable disease. We hypothesized that the time frame between the onset of SHS and the clinical manifestation of T2DM is the operational area for the application of reliable risk assessment tools, such as immunoglobulin G (IgG) N-glycans. From the viewpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS and dynamic monitoring by glycan biomarkers could provide a window of opportunity for targeted prevention and personalized treatment of T2DM. Methods: Case-control and nested case-control studies were performed and consisted of 138 and 308 participants, respectively. The IgG N-glycan profiles of all plasma samples were detected by an ultra-performance liquid chromatography instrument. Results: After adjustment for confounders, 22, five, and three IgG N-glycan traits were significantly associated with T2DM in the case-control setting, baseline SHS, and baseline optimal health participants from the nested case-control setting, respectively. Adding the IgG N-glycans to the clinical trait models, the average area under the receiver operating characteristic curves (AUCs) of the combined models based on repeated 400 times fivefold cross-validation differentiating T2DM from healthy individuals were 0.807 in the case-control setting and 0.563, 0.645, and 0.604 in the pooled samples, baseline SHS, and baseline optimal health samples of nested case-control setting, respectively, which presented moderate discriminative ability and were generally better than models with either glycans or clinical features alone. Conclusions: This study comprehensively illustrated that the observed altered IgG N-glycosylation, i.e., decreased galactosylation and fucosylation/sialylation without bisecting GlcNAc, as well as increased galactosylation and fucosylation/sialylation with bisecting GlcNAc, reflects a pro-inflammatory state of T2DM. SHS is an important window period of early intervention for individuals at risk for T2DM; glycomic biosignatures as dynamic biomarkers have the ability to identify populations at risk for T2DM early, and the combination of evidence could provide suggestive ideas and valuable insight for the PPPM of T2DM. Supplementary information: The online version contains supplementary material available at 10.1007/s13167-022-00311-3.

End-to-end learned single lens design using improved Wiener deconvolution.

End-to-end single-lens imaging system design is a method to optimize both optical system and reconstruction algorithm. Most end-to-end single lens systems use convolutional neural networks (CNN) for image restoration, which fit the transformation relationship between the aberrated image and the ground truth image in the training set. Based on the principle of optical imaging, we realize non-blind image restoration through Wiener deconvolution. Wiener deconvolution is improved with the powerful fitting ability of depth learning so that the noise parameters and the blur kernel in Wiener deconvolution can be simultaneously optimized with the optical parameters in the lens. Extensive comparative tests have been conducted to demonstrate the single-lens imaging system obtained by our method has more stable imaging quality and a 40 times greater imaging speed than the method using CNN restoration algorithm.

Identification and Analysis of Metabolites That Contribute to the Formation of Distinctive Flavour Components of Laoxianghuang.

In addition to volatile compounds, metabolites also have a great effect on the flavour of food. Fresh finger citron cannot be eaten directly because of its spicy and bitter taste, so it is made into a preserved fruit product known as Laoxianghuang (LXH). To investigate the metabolites that have an effect on the flavour of LXH, untargeted metabolomics was performed using an ultrahigh-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS), and the metabolites of the Laoxianghuang samples from different locations in the Chaoshan area were compared and analysed. A total of 756 metabolites were identified and distinct differences were revealed among the different Laoxianghuang samples. A total of 33 differential metabolites with the most significant changes were screened through further multivariate analytical steps, and each group of samples had unique metabolites. For instance, pomolic acid had the highest content in the JG sample, while L-glycyl-L-isoleucine was rich in the QS sample. Moreover, flavonoid metabolites made the greatest contribution to the unique flavour of Laoxianghuang. The metabolic pathways involved are the biosynthetic pathways of flavonoids, isoflavonoids, flavones, and flavonols. This study can provide some creative information for distinguishing the quality differences of Laoxianghuang from the perspective of metabolites and offer preliminary theoretical support to characterise the formation of flavour substances in Laoxianghuang.

Development and validation of a deep learning algorithm based on fundus photographs for estimating the CAIDE dementia risk score.

BACKGROUND: the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk score is a recognised tool for dementia risk stratification. However, its application is limited due to the requirements for multidimensional information and fasting blood draw. Consequently, an effective and non-invasive tool for screening individuals with high dementia risk in large population-based settings is urgently needed. METHODS: a deep learning algorithm based on fundus photographs for estimating the CAIDE dementia risk score was developed and internally validated by a medical check-up dataset included 271,864 participants in 19 province-level administrative regions of China, and externally validated based on an independent dataset included 20,690 check-up participants in Beijing. The performance for identifying individuals with high dementia risk (CAIDE dementia risk score ≥ 10 points) was evaluated by area under the receiver operating curve (AUC) with 95% confidence interval (CI). RESULTS: the algorithm achieved an AUC of 0.944 (95% CI: 0.939-0.950) in the internal validation group and 0.926 (95% CI: 0.913-0.939) in the external group, respectively. Besides, the estimated CAIDE dementia risk score derived from the algorithm was significantly associated with both comprehensive cognitive function and specific cognitive domains. CONCLUSIONS: this algorithm trained via fundus photographs could well identify individuals with high dementia risk in a population setting. Therefore, it has the potential to be utilised as a non-invasive and more expedient method for dementia risk stratification. It might also be adopted in dementia clinical trials, incorporated as inclusion criteria to efficiently select eligible participants.

Anti-Inflammatory Dietary Diversity and Depressive Symptoms among Older Adults: A Nationwide Cross-Sectional Analysis.

The purpose of this study was to associate the anti-inflammatory dietary diversity and depressive symptoms among a nationwide sample of Chinese older adults. We used data from the 2018 wave of Chinese longitudinal healthy longevity survey (CLHLS). We assessed depressive symptoms using the 10 items of the center for epidemiologic studies depression scale (CES-D-10). Based on the dietary diversity index (DDI) generated by previous studies, we construct two novel indicators: the protein-enriched dietary diversity index diet (PEDDI) and the anti-inflammatory dietary diversity index diet (AIDDI). We used multivariate logistic models to evaluate the associations of DDI, PEDDI, and AIDDI with depressive symptoms, statistically adjusted for a range of potential confounders. A total of 12,192 participants (mean age 83.6 years) were included in the analysis. We found that participants with a higher score of DDI (OR = 0.91, 95% CI: 0.89-0.92) and PEDDI (OR = 0.91, 95% CI: 0.88-0.93) showed lower odds of having depressive symptoms, while the association between AIDDI and depressive symptoms was more marked (OR = 0.80, 95% CI: 0.78-0.83). The associations remained in subgroup analyses and sensitivity analyses. The results indicate that intaking diversified diet, particularly anti-inflammatory foods, may be associated with a lower risk of depressive symptoms. The findings of this study, if confirmed as causal, provide evidence that an intervention of adopting an anti-inflammatory diversified diet may reduce the burden of depression among older adults.

Integrating Choline and Specific Intestinal Microbiota to Classify Type 2 Diabetes in Adults: A Machine Learning Based Metagenomics Study.

Emerging evidence is examining the precise role of intestinal microbiota in the pathogenesis of type 2 diabetes. The aim of this study was to investigate the association of intestinal microbiota and microbiota-generated metabolites with glucose metabolism systematically in a large cross-sectional study in China. 1160 subjects were divided into three groups based on their glucose level: normal glucose group (n=504), prediabetes group (n=394), and diabetes group (n=262). Plasma concentrations of TMAO, choline, betaine, and carnitine were measured. Intestinal microbiota was measured in a subgroup of 161 controls, 144 prediabetes and 56 diabetes by using metagenomics sequencing. We identified that plasma choline [Per SD of log-transformed change: odds ratio 1.36 (95 confidence interval 1.16, 1.58)] was positively, while betaine [0.77 (0.66, 0.89)] was negatively associated with diabetes, independently of TMAO. Individuals with diabetes could be accurately distinguished from controls by integrating data on choline, and certain microbiota species, as well as traditional risk factors (AUC=0.971). KOs associated with the carbohydrate metabolism pathway were enhanced in individuals with high choline level. The functional shift in the carbohydrate metabolism pathway in high choline group was driven by species Ruminococcus lactaris, Coprococcus catus and Prevotella copri. We demonstrated the potential ability for classifying diabetic population by choline and specific species, and provided a novel insight of choline metabolism linking the microbiota to impaired glucose metabolism and diabetes.

Associations of Humidity and Temperature With Cataracts Among Older Adults in China.

Background: The burden of cataracts was substantial in the current aging world. However, few epidemiological studies have examined the associations between climate and weather conditions and cataract in older populations. We aimed to investigate the associations of air relative humidity and temperature with cataracts in older adults in China. Methods: We used the cohort data from 2002, 2005, 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A total of 62,595 Chinese older adults aged between 65 and 105 years were included in the analyses. City-level annual average air humidity and temperature during 2001 and 2017 (before the survey year) was used to measure population exposure. A cataract was self-reports based on the medical record or the doctor's diagnosis and 8,071 older adults had cataract. Covariates included socio-demographic, health status, lifestyles, and chronic conditions. We adopted the Generalized estimation equation (GEE) model to analyze the associations of relative humidity and temperature with cataracts. Results: We found that the average relative humidity (OR: 0.99; 95% CI: 0.98-0.99) in the past year was inversely associated with cataract likelihoods in older adults and a positive association between temperature (OR: 1.04; 95%CI: 1.03,1.05) in the past year and cataract likelihoods in older adults. The associations were robust in stratified analyses by sex, urban/rural residence, and education level. Furthermore, we found a nonlinear J-shaped relationship between temperature and cataract prevalence. Conclusion: Our findings provide the evidence that higher temperature and low relative humidity may be associated with cataracts in older adults.

Effect of the bacterial community on the volatile flavour profile of a Chinese fermented condiment - Red sour soup - During fermentation.

Red sour soup (RSS) is a traditional fermented seasoning used by people in Guizhou Province, China. The volatile compounds were detected by gas chromatography ion mobility spectrometry (GC-IMS), while the bacterial community compositions were revealed by 16S sequencing. A total of 70 volatile substances were assessed, and esters, terpenes, and alcohols played a dominant role in RSS. Lactic acid bacteria (LAB) were dominant in the microbial community. During fermentation, multiple volatile flavour substances and various LAB were mainly derived from the secondary fermentation stage. The core bacteria with an important influence on volatile flavour substances were analysed by the Mantel test, identifying Bacteroides, Lactobacillus, Lactococcus, Enterobacteriaceae, Pantoea, Clostridium, Enterobacter, unclassified genera, Caproiciproducens, Nitriliruptoraceae, Halomonas, Bradyrhizobium, Pediococcus, Caulobacteraceae, Weissella, Ligilactobacillus, and Levilactobacillus and et al.. This study provides us with useful information about flavour-generating bacteria among RSS fermentation periods. The abundances of these bacteria may be controlled to enrich the desired flavour metabolites while eliminating unwanted metabolites.

Acoustic Bioprinting of Patient-Derived Organoids for Predicting Cancer Therapy Responses.

Cancer models, which are biologically representative of patient tumors, can predict the treatment responses and help determine the most appropriate cancer treatment for individual patients. Here, a point-of-care testing system called acoustically bioprinted patient-derived microtissues (PDMs) that can model cancer invasion and predict treatment response in individual patients with colorectal cancer (CRC), is reported. The PDMs are composed of patient-derived colorectal tumors and healthy organoids which can be precisely arranged by acoustic bioprinting approach for recapulating primary tissue's architecture. Particularly, these tumor organoids can be efficiently generated and can apprehend histological, genomic, and phenotypical characteristics of primary tumors. Consequently, these PDMs allow physiologically relevant in vitro drug (5-fluorouracil) screens, thus predicting the paired patient's responses to chemotherapy. A correlation between organoid invasion speed and normalized spreading speed of the paired patients is further established. It provides a quantitative indicator to help doctors make better decisions on ultimate anus-preserving operation for extremely low CRC patients. Thus, by combing acoustic bioprinting and organoid cultures, this method may open an avenue to establish complex 3D tissue models for precision and personalized medicine.

Irreversible Primary Visual Cortex Impairment in a Mouse Model of High-Risk Schizophrenia.

PURPOSE: Although visual deficits can be observed at any stage of schizophrenia, few studies have focused on visual cortex alterations in individuals at high risk of schizophrenia. This study aimed to investigate the pathological changes of the primary visual cortex in a prenatal mouse model of MK801-induced high-risk schizophrenia. METHODS: The high-risk schizophrenia model was generated by MK801 injection into pregnant mice. The male offspring without schizophrenia-like behaviors in early adulthood were defined as the high-risk mouse model of schizophrenia (HRMMS) and divided into two groups. One HRMMS group received the antipsychotic agent risperidone beginning at postnatal week 4 and another group did not receive any treatment. After treatment for 4 weeks, in vivo two-photon calcium imaging was performed to characterize the primary visual cortex activity. The novel object recognition test and the prepulse inhibition apparatus test were also implemented to assess the cognitive and behavioral performance, respectively. RESULTS: Both groups of HRMMS mice, with or without antipsychotic treatment, had decreased neuronal calcium activity, demonstrating primary visual cortex impairment. More notably, antipsychotic treatment did not normalize the impaired neuronal activities in the primary visual cortex. Correspondingly, the treatment did not improve the cognitive or behavioral impairment. CONCLUSION: Visual cortex impairment might be a prominent feature of individuals at high risk of schizophrenia that cannot be normalized by early treatment with antipsychotic medication, indicating the presence of independent regulatory pathways for visual perception disturbance in schizophrenia. Thus, visual system impairment in schizophrenic patients must be further studied.

Comparative Cardio-Renal Outcomes of Type 2 Diabetes Patients Administered Glucagon-Like Peptide-1 Receptor Agonists: A Network Meta-Analysis.

Background: Cardio-renal profiles are available from cardiovascular outcome trials of glucagon-like peptide-1 receptor agonists (GLP-1 RAs). Methods: A comprehensive systematic review of Embase, Medline, Web of Knowledge, and CENTRAL databases was conducted. Randomized controlled cardiovascular outcome trials of type 2 diabetes mellitus (T2DM) patients administered GLP-1 RAs were included. The following primary outcomes were examined: cardiovascular death, major adverse cardiovascular events (MACE), myocardial infarction, stroke, mortality, heart failure, hypoglycemia, pancreatitis, and thyroid carcinoma. Secondary outcomes included: composite kidney outcome, worsening kidney function, macroalbuminuria, and retinopathy. Results: Seven trials involving 56,004 patients and eight interventions were identified. Albiglutide was associated with fewer MACE and myocardial infarction events compared with lixisenatide. Lixisenatide was related to a greater number of stroke events and cardiovascular deaths compared to once-weekly semaglutide and oral semaglutide, respectively. Improved mortality was associated with oral semaglutide compared with once-weekly semaglutide, albiglutide, dulaglutide, exenatide, or lixisenatide. Risks of heart failure, thyroid carcinoma, and pancreatitis were similar among all the treatments. Weighting of the nine primary outcomes identified oral semaglutide as first among the eight treatments examined. Among three of the secondary outcomes, once-weekly semaglutide ranked first. Better composite kidney outcome was observed with once-weekly semaglutide than with dulaglutide or exenatide; once-weekly semaglutide improved macroalbuminuria compared with exenatide or lixisenatide; and albiglutide, exenatide, and placebo was associated with fewer cases of retinopathy compared with once-weekly semaglutide. Meanwhile, kidney function was less likely to worsen with dulaglutide than with lixisenatide or placebo. Conclusion: Semaglutide should be considered when GLP-1 RAs are indicated for T2DM patients.

Self-powered technology based on nanogenerators for biomedical applications.

Biomedical electronic devices have enormous benefits for healthcare and quality of life. Still, the long-term working of those devices remains a great challenge due to the short life and large volume of conventional batteries. Since the nanogenerators (NGs) invention, they have been widely used to convert various ambient mechanical energy sources into electrical energy. The self-powered technology based on NGs is dedicated to harvesting ambient energy to supply electronic devices, which is an effective pathway to conquer the energy insufficiency of biomedical electronic devices. With the aid of this technology, it is expected to develop self-powered biomedical electronic devices with advanced features and distinctive functions. The goal of this review is to summarize the existing self-powered technologies based on NGs and then review the applications based on self-powered technologies in the biomedical field during their rapid development in recent years, including two main directions. The first is the NGs as independent sensors to converts biomechanical energy and heat energy into electrical signals to reflect health information. The second direction is to use the electrical energy produced by NGs to stimulate biological tissues or powering biomedical devices for achieving the purpose of medical application. Eventually, we have analyzed and discussed the remaining challenges and perspectives of the field. We believe that the self-powered technology based on NGs would advance the development of modern biomedical electronic devices.