Leveraging intracellular ALDH1A1 activity for selective cancer stem-like cell labeling and targeted treatment via in vivo click reaction.

Inhibition of overexpressed enzymes is among the most promising approaches for targeted cancer treatment. However, many cancer-expressed enzymes are "nonlethal," in that the inhibition of the enzymes' activity is insufficient to kill cancer cells. Conventional antibody-based therapeutics can mediate efficient treatment by targeting extracellular nonlethal targets but can hardly target intracellular enzymes. Herein, we report a cancer targeting and treatment strategy to utilize intracellular nonlethal enzymes through a combination of selective cancer stem-like cell (CSC) labeling and Click chemistry-mediated drug delivery. A de novo designed compound, AAMCHO [N-(3,4,6-triacetyl- N-azidoacetylmannosamine)-cis-2-ethyl-3-formylacrylamideglycoside], selectively labeled cancer CSCs in vitro and in vivo through enzymatic oxidation by intracellular aldehyde dehydrogenase 1A1. Notably, azide labeling is more efficient in identifying tumorigenic cell populations than endogenous markers such as CD44. A dibenzocyclooctyne (DBCO)-toxin conjugate, DBCO-MMAE (Monomethylauristatin E), could next target the labeled CSCs in vivo via bioorthogonal Click reaction to achieve excellent anticancer efficacy against a series of tumor models, including orthotopic xenograft, drug-resistant tumor, and lung metastasis with low toxicity. A 5/7 complete remission was observed after single-cycle treatment of an advanced triple-negative breast cancer xenograft (~500 mm3).

Painful physical symptoms and antidepressant treatment outcome in depression: a systematic review and meta-analysis.

BACKGROUND: Painful physical symptoms (PPS) are highly prevalent in patients with major depressive disorder (MDD). Presence of PPS in depressed patients are potentially associated with poorer antidepressant treatment outcome. We aimed to evaluate the association of baseline pain levels and antidepressant treatment outcomes. METHODS: We searched PubMed, Embase and Cochrane Library databases from inception through February 2023 based on a pre-registered protocol (PROSPERO: CRD42022381349). We included original studies that reported pretreatment pain measures in antidepressant treatment responder/remitter and non-responder/non-remitter among patients with MDD. Data extraction and quality assessment were performed following the Preferred Reporting Items for Systematic Reviews and Meta-analyses by two reviewers independently. The primary outcome was the difference of the pretreatment pain levels between antidepressant treatment responder/remitter and non-responder/non-remitter. Random-effects meta-analysis was used to calculate effect sizes (Hedge's g) and subgroup and meta-regression analyses were used to explore sources of heterogeneity. RESULTS: A total of 20 studies were included. Six studies reported significantly higher baseline pain severity levels in MDD treatment non-responders (Hedge's g = 0.32; 95% CI, 0.13-0.51; P = 0.0008). Six studies reported the presence of PPS (measured using a pain severity scale) was significantly associated with poor treatment response (OR = 1.46; 95% CI, 1.04-2.04; P = 0.028). Five studies reported significant higher baseline pain interference levels in non-responders (Hedge's g = 0.46; 95% CI, 0.32-0.61; P < 0.0001). Four studies found significantly higher baseline pain severity levels in non-remitters (Hedge's g = 0.27; 95% CI, 0.14-0.40; P < 0.0001). Eight studies reported the presence of PPS significantly associated with treatment non-remission (OR = 1.70; 95% CI, 1.24-2.32; P = 0.0009). CONCLUSIONS: This study suggests that PPS are negatively associated with the antidepressant treatment outcome in patients with MDD. It is possible that better management in pain conditions when treating depression can benefit the therapeutic effects of antidepressant medication in depressed patients.

Association between alcohol consumption and sleep traits: observational and mendelian randomization studies in the UK biobank.

Previous studies have shown that excessive alcohol consumption is associated with poor sleep. However, the health risks of light-to-moderate alcohol consumption in relation to sleep traits (e.g., insomnia, snoring, sleep duration and chronotype) remain undefined, and their causality is still unclear in the general population. To identify the association between alcohol consumption and multiple sleep traits using an observational and Mendelian randomization (MR) design. Observational analyses and one-sample MR (linear and nonlinear) were performed using clinical and individual-level genetic data from the UK Biobank (UKB). Two-sample MR was assessed using summary data from genome-wide association studies from the UKB and other external consortia. Phenotype analyses were externally validated using data from the National Health and Nutrition Examination Survey (2017-2018). Data analysis was conducted from January 2022 to October 2022. The association between alcohol consumption and six self-reported sleep traits (short sleep duration, long sleep duration, chronotype, snoring, waking up in the morning, and insomnia) were analysed. This study included 383,357 UKB participants (mean [SD] age, 57.0 [8.0] years; 46% male) who consumed a mean (SD) of 9.0 (10.0) standard drinks (one standard drink equivalent to 14 g of alcohol) per week. In the observational analyses, alcohol consumption was significantly associated with all sleep traits. Light-moderate-heavy alcohol consumption was linearly linked to snoring and the evening chronotype but nonlinearly associated with insomnia, sleep duration, and napping. In linear MR analyses, a 1-SD (14 g) increase in genetically predicted alcohol consumption was associated with a 1.14-fold (95% CI, 1.07-1.22) higher risk of snoring (P < 0.001), a 1.28-fold (95% CI, 1.20-1.37) higher risk of evening chronotype (P < 0.001) and a 1.24-fold (95% CI, 1.13-1.36) higher risk of difficulty waking up in the morning (P < 0.001). Nonlinear MR analyses did not reveal significant results after Bonferroni adjustment. The results of the two-sample MR analyses were consistent with those of the one-sample MR analyses, but with a slightly attenuated overall estimate. Our findings suggest that even low levels of alcohol consumption may affect sleep health, particularly by increasing the risk of snoring and evening chronotypes. The negative effects of alcohol consumption on sleep should be made clear to the public in order to promote public health.

Genome-wide association identifies a missing hydrolase for tocopherol synthesis in plants.

The tocopherol biosynthetic pathway, encoded by VTE genes 1 through 6, is highly conserved in plants but most large effect quantitative trait loci for seed total tocopherols (totalT) lack VTE genes, indicating other activities are involved. A genome-wide association study of Arabidopsis seed tocopherols showed five of seven significant intervals lacked VTE genes, including the most significant, which mapped to an uncharacterized, seed-specific, envelope-localized, alpha/beta hydrolase with esterase activity, designated AtVTE7. Atvte7 null mutants decreased seed totalT 55% while a leaky allele of the maize ortholog, ZmVTE7, decreased kernel and leaf totalT 38% and 49%, respectively. Overexpressing AtVTE7 or ZmVTE7 partially or fully complemented the Atvte7 seed phenotype and increased leaf totalT by 3.6- and 6.9-fold, respectively. VTE7 has the characteristics of an esterase postulated to provide phytol from chlorophyll degradation for tocopherol synthesis, but bulk chlorophyll levels were unaffected in vte7 mutants and overexpressing lines. Instead, levels of specific chlorophyll biosynthetic intermediates containing partially reduced side chains were impacted and strongly correlated with totalT. These intermediates are generated by a membrane-associated biosynthetic complex containing protochlorophyllide reductase, chlorophyll synthase, geranylgeranyl reductase (GGR) and light harvesting-like 3 protein, all of which are required for both chlorophyll and tocopherol biosynthesis. We propose a model where VTE7 releases prenyl alcohols from chlorophyll biosynthetic intermediates, which are then converted to the corresponding diphosphates for tocopherol biosynthesis.

Constitutive MHC class I molecules negatively regulate TLR-triggered inflammatory responses via the Fps-SHP-2 pathway.

The molecular mechanisms that fine-tune Toll-like receptor (TLR)-triggered innate inflammatory responses remain to be fully elucidated. Major histocompatibility complex (MHC) molecules can mediate reverse signaling and have nonclassical functions. Here we found that constitutively expressed membrane MHC class I molecules attenuated TLR-triggered innate inflammatory responses via reverse signaling, which protected mice from sepsis. The intracellular domain of MHC class I molecules was phosphorylated by the kinase Src after TLR activation, then the tyrosine kinase Fps was recruited via its Src homology 2 domain to phosphorylated MHC class I molecules. This led to enhanced Fps activity and recruitment of the phosphatase SHP-2, which interfered with TLR signaling mediated by the signaling molecule TRAF6. Thus, constitutive MHC class I molecules engage in crosstalk with TLR signaling via the Fps-SHP-2 pathway and control TLR-triggered innate inflammatory responses.

A systematic review and meta-analysis of long term physical and mental sequelae of COVID-19 pandemic: call for research priority and action.

The long-term physical and mental sequelae of COVID-19 are a growing public health concern, yet there is considerable uncertainty about their prevalence, persistence and predictors. We conducted a comprehensive, up-to-date meta-analysis of survivors' health consequences and sequelae for COVID-19. PubMed, Embase and the Cochrane Library were searched through Sep 30th, 2021. Observational studies that reported the prevalence of sequelae of COVID-19 were included. Two reviewers independently undertook the data extraction and quality assessment. Of the 36,625 records identified, a total of 151 studies were included involving 1,285,407 participants from thirty-two countries. At least one sequelae symptom occurred in 50.1% (95% CI 45.4-54.8) of COVID-19 survivors for up to 12 months after infection. The most common investigation findings included abnormalities on lung CT (56.9%, 95% CI 46.2-67.3) and abnormal pulmonary function tests (45.6%, 95% CI 36.3-55.0), followed by generalized symptoms, such as fatigue (28.7%, 95% CI 21.0-37.0), psychiatric symptoms (19.7%, 95% CI 16.1-23.6) mainly depression (18.3%, 95% CI 13.3-23.8) and PTSD (17.9%, 95% CI 11.6-25.3), and neurological symptoms (18.7%, 95% CI 16.2-21.4), such as cognitive deficits (19.7%, 95% CI 8.8-33.4) and memory impairment (17.5%, 95% CI 8.1-29.6). Subgroup analysis showed that participants with a higher risk of long-term sequelae were older, mostly male, living in a high-income country, with more severe status at acute infection. Individuals with severe infection suffered more from PTSD, sleep disturbance, cognitive deficits, concentration impairment, and gustatory dysfunction. Survivors with mild infection had high burden of anxiety and memory impairment after recovery. Our findings suggest that after recovery from acute COVID-19, half of survivors still have a high burden of either physical or mental sequelae up to at least 12 months. It is important to provide urgent and appropriate prevention and intervention management to preclude persistent or emerging long-term sequelae and to promote the physical and psychiatric wellbeing of COVID-19 survivors.

A unitary mechanism underlies adaptation to both local and global environmental statistics in time perception.

Our duration estimation flexibly adapts to the statistical properties of the temporal context. Humans and non-human species exhibit a perceptual bias towards the mean of durations previously observed as well as serial dependence, a perceptual bias towards the duration of recently processed events. Here we asked whether those two phenomena arise from a unitary mechanism or reflect the operation of two distinct systems that adapt separately to the global and local statistics of the environment. We employed a set of duration reproduction tasks in which the target duration was sampled from distributions with different variances and means. The central tendency and serial dependence biases were jointly modulated by the range and the variance of the prior, and these effects were well-captured by a unitary mechanism model in which temporal expectancies are updated after each trial based on perceptual observations. Alternative models that assume separate mechanisms for global and local contextual effects failed to capture the empirical results.

Phenylacetyl glutamine (PAGln) enhances cardiomyocyte death after myocardial infarction through ß1 adrenergic receptor.

This study aims to explore the roles of phenylacetyl glutamine (PAGln) on myocardial infarction (MI) pathogenesis. Here, using targeted metabolomics analysis, it was found that the plasma metabolite PAGln was upregulated in coronary artery disease (CAD) patients and MI mice and could be an independent risk factor for CAD. In vivo and in vitro functional experiments revealed that PAGln pretreatment enhanced MI-induced myocardial injury and cardiac fibrosis, as evident by the increased infarct size, cardiomyocyte death, and the upregulated expression of cardiac fibrosis markers (Col1a1 and α-SMA). Combined with RNA-sequencing analysis and G protein-coupled receptor (GPCR) inhibitor, we found that the GPCR signaling activation is essential for PAGln-mediated effects on cardiomyocyte death. Furthermore, drug affinity responsive target stability and cellular thermal shift assay demonstrated that PAGln could interact with ß1-adrenergic receptor (AR). Moreover, ß1-AR blocker treatment indeed extended the cardiac remodeling after PAGln-enhanced MI. These results suggest that PAGln might be a potential therapeutic target for extending the cardiac remodeling window in MI patients that signals via ß1-AR.

Quantifying the Impact of Environment Loads on Displacements in a Suspension Bridge with a Data-Driven Approach.

Long-span bridges are susceptible to damage, aging, and deformation in harsh environments for a long time. Therefore, structural health monitoring (SHM) systems need to be used for reasonable monitoring and maintenance. Among various indicators, bridge displacement is a crucial parameter reflecting the bridge's health condition. Due to the simultaneous bearing of multiple environmental loads on suspension bridges, determining the impact of different loads on displacement is beneficial for the better understanding of the health conditions of the bridges. Considering the fact that extreme gradient boosting (XGBoost) has higher prediction performance and robustness, the authors of this paper have developed a data-driven approach based on the XGBoost model to quantify the impact between different environmental loads and the displacement of a suspension bridge. Simultaneously, this study combined wavelet threshold (WT) denoising and the variational mode decomposition (VMD) method to conduct a modal decomposition of three-dimensional (3D) displacement, further investigating the interrelationships between different loads and bridge displacements. This model links wind speed, temperature, air pressure, and humidity with the 3D displacement response of the span using the bridge monitoring data provided by the GNSS and Earth Observation for Structural Health Monitoring (GeoSHM) system of the Forth Road Bridge (FRB) in the United Kingdom (UK), thus eliminating the temperature time-lag effect on displacement data. The effects of the different loads on the displacement are quantified individually with partial dependence plots (PDPs). Employing testing, it was found that the XGBoost model has a high predictive effect on the target variable of displacement. The analysis of quantification and correlation reveals that lateral displacement is primarily affected by same-direction wind, showing a clear positive correlation, and vertical displacement is mainly influenced by temperature and exhibits a negative correlation. Longitudinal displacement is jointly influenced by various environmental loads, showing a positive correlation with atmospheric pressure, temperature, and vertical wind and a negative correlation with longitudinal wind, lateral wind, and humidity. The results can guide bridge structural health monitoring in extreme weather to avoid accidents.

Application of Response Surface-Corrected Finite Element Model and Bayesian Neural Networks to Predict the Dynamic Response of Forth Road Bridges under Strong Winds.

With the rapid development of big data, the Internet of Things (IoT), and other technological advancements, digital twin (DT) technology is increasingly being applied to the field of bridge structural health monitoring. Achieving the precise implementation of DT relies significantly on a dual-drive approach, combining the influence of both physical model-driven and data-driven methodologies. In this paper, two methods are proposed to predict the displacement and dynamic response of structures under strong winds, namely, a Bayesian Neural Network (BNN) model based on Bayesian inference and a finite element model (FEM) method modified based on genetic algorithms (GAs) and multi-objective optimization (MOO) using response surface methodology (RSM). The characteristics of these approaches in predicting the dynamic response of large-span bridges are explored, and a comparative analysis is conducted to evaluate their differences in computational accuracy, efficiency, model complexity, interpretability, and comprehensiveness. The characteristics of the two methods were evaluated using data collected on the Forth Road Bridge (FRB) as an example under unusual weather conditions with strong wind action. This work proposes a dual-driven approach, integrating machine learning and FEM with GNSS and Earth Observation for Structural Health Monitoring (GeoSHM), to bridge the gap in the limited application of dual-driven methods primarily applied for small- and medium-sized bridges to large-span bridge structures. The research results show that the BNN model achieved higher R2 values for predicting the Y and Z displacements (0.9073 and 0.7969, respectively) compared to the FEM model (0.6167 and 0.6283). The BNN model exhibited significantly faster computation, taking only 20 s, while the FEM model required 5 h. However, the physical model provided higher interpretability and the ability to predict the dynamic response of the entire structure. These findings help to promote the further integration of these two approaches to obtain an accurate and comprehensive dual-driven approach for predicting the structural dynamic response of large-span bridge structures affected by strong wind loading.

Cognitive entailments among "the true, the good, the beautiful": a mainland Chinese sample.

Philosophers and cognitive scientists have long debated about the entailments among "the true, the good, the beautiful" (TGB hereafter). In the current article, we directly probed mainland Chinese subjects' cognitive entailment among TGB. Using 1-7 (Experiment 1) and 1-6 (Experiment 2) Likert scales, we convergently observed that mainland Chinese subjects tend to think that the beautiful is not the true, and that the good is the beautiful. Additionally, Experiment 1 also revealed that mainland Chinese subjects tend to think that the true is not the beautiful. Some of these results may reflect anthropological universals, and some others may reflect cultural specifics. Experiment 3 revealed that the most popular translation of TGB in Chinese into English is rather "the true, the kind, the beautiful", suggesting that the three concepts mapped to TGB in Chinese is not one-to-one mapped to the three concepts mapped to TGB in English. Therefore, caution should be exercised when making cross-linguistic or cross-cultural comparisons about TGB in the future.

Progress on CRISPR/Cas9 system in the genetic improvement of livestock and poultry.

CRISPR/Cas9 gene editing technology, as a highly efficient genome editing method, has been extensively employed in the realm of animal husbandry for genetic improvement. With its remarkable efficiency and precision, this technology has revolutionized the field of animal husbandry. Currently, CRISPR/Cas9-based gene knockout, gene knock-in and gene modification techniques are widely employed to achieve precise enhancements in crucial production traits of livestock and poultry species. In this review, we summarize the operational principle and development history of CRISPR/Cas9 technology. Additionally, we highlight the research advancements utilizing this technology in muscle growth and development, fiber growth, milk quality composition, disease resistance breeding, and animal welfare within the livestock and poultry sectors. Our aim is to provide a more comprehensive understanding of the application of CRISPR/Cas9 technology in gene editing for livestock and poultry.

JrWRKY21 interacts with JrPTI5L to activate the expression of JrPR5L for resistance to Colletotrichum gloeosporioides in walnut.

Walnut (Juglans regia L.) anthracnose, induced by Colletotrichum gloeosporioides, is a catastrophic disease impacting the walnut industry in China. Although WRKY transcription factors play a key role in plant immunity, the function of the WRKY gene family in walnut resistance to C. gloeosporioides is not clear. Here, through transcriptome sequencing and quantitative real-time polymerase chain reaction (qRT-PCR), we identified a differentially expressed gene, JrWRKY21, that was significantly upregulated upon C. gloeosporioides infection in walnut. JrWRKY21 positively regulated walnut resistance to C. gloeosporioides, as demonstrated by virus-induced gene silencing and transient gene overexpression. Additionally, JrWRKY21 directly interacted with the transcriptional activator of the pathogenesis-related (PR) gene JrPTI5L in vitro and in vivo, and could bind to the W-box in the JrPTI5L promoter for transcriptional activation. Moreover, JrPTI5L could induce the expression of the PR gene JrPR5L through binding to the GCCGAC motif in the promoter. Our data support that JrWRKY21 can indirectly activate the expression of the JrPR5L gene via the WRKY21-PTI5L protein complex to promote resistance against C. gloeosporioides in walnut. The results will enhance our understanding of the mechanism behind walnut disease resistance and facilitate the genetic improvement of walnut by molecular breeding for anthracnose-resistant varieties.

lncRNA ANRIL accelerates wound healing in diabetic foot ulcers via modulating HIF1A/VEGFA signaling through interacting with FUS.

BACKGROUND: Diabetic foot ulcer (DFU) is a frequently diagnosed complication of diabetes, and remains a heathcare burden worldwide. However, the pathogenesis of DFU is still largely unclear. The objective of this study is to delineate the function and underlying mechanism of lncRNA antisense non coding RNA in the INK4 locus (ANRIL) in endothelial progenitor cells (EPCs) and DFU mice. METHODS: The DFU mouse model was established, and EPCs were subjected to high glucose (HG) treatment to mimic diabetes. qRT-PCR or western blot was employed to detected the expression of ANRIL, HIF1A, FUS and VEGFA. CCK-8 and Annexin V/PI staining were used to monitor cell proliferation and apoptosis. Wound healing, Transwell invasion and tube formation assays were conducted to assess cell migration, invasion and angiogenesis, respectively. The association between ANRIL and FUS was verified by RNA pull-down and RIP assays. Luciferase and ChIP assays were employed to investigate HIF1A-mediated transcriptional regulation of VEGFA and ANRIL. The histological alterations of DFU wound healing were observed by H&E and Masson staining. RESULTS: ANRIL was downregulated in peripheral blood samples of DFU patients, DFU mice and HG-treated EPCs. Mechanistically, ANRIL regulated HIFA mRNA stability via recruiting FUS. VEGFA and ANRIL were transcriptionally regulated by HIF1A. Functional experiments revealed that HG suppressed EPC proliferation, migration, invasion and tube formation, but promoted apoptosis via ANRIL/HIF1A axis. ANRIL accelerated DFU wound healing via modulating HIF1A expression in vivo. CONCLUSION: ANRIL accelerated wound healing in DFU via modulating HIF1A/VEGFA signaling in a FUS-dependent manner.

Identifying Proliferative Hepatocellular Carcinoma at Pretreatment CT: Implications for Therapeutic Outcomes after Transarterial Chemoembolization.

Background Hepatocellular carcinomas (HCCs) can be divided into proliferative and nonproliferative types, which may have implications for outcomes after conventional transarterial chemoembolization (cTACE). Biopsy to identify proliferative HCC is not routinely performed before cTACE. Purpose To develop and validate a predictive model for identifying proliferative HCCs using CT imaging features and to compare therapeutic outcomes between predicted proliferative and nonproliferative HCCs after cTACE according to this model. Materials and Methods This retrospective multicenter study included adults with HCC who underwent liver resection or cTACE between August 2013 and December 2020. A CT-based predictive model for identifying proliferative HCCs was developed and externally validated in a cohort that underwent resection. Diagnostic performance was calculated for the model. Thereafter, patients in the cTACE cohort were stratified into groups with predicted proliferative or nonproliferative HCCs according to the model. The primary outcome was overall survival (OS), and the secondary outcomes were tumor response rate and progression-free survival (PFS). These were compared between the two groups with use of the χ2 test and the log-rank test. Results A total of 1194 patients (1021 men; mean age, 54 years ± 12 [SD]; median follow-up time, 29.1 months) were included. The predictive model, named the SMARS score, incorporated lobulated shape, mosaic architecture, α-fetoprotein levels, rim arterial phase hyperenhancement, and satellite lesions. The area under the receiver operating characteristic curve for the SMARS score was 0.83 for the training cohort and 0.80 for the validation cohort. According to the SMARS score, patients with predicted proliferative HCCs (n = 114) had lower tumor response rate (48% vs 71%; P < .001) and worse PFS (6.6 months vs 12.4 months; P < .001) and OS (14.4 months vs 38.7 months; P < .001) than those with nonproliferative HCCs (n = 263). Conclusion The predictive model demonstrated good performance for identifying proliferative HCCs. According to the SMARS score, patients with predicted proliferative HCCs have worse prognosis than those with predicted nonproliferative HCCs after cTACE. © RSNA, 2023 Supplemental material is available for this article.

Fotagliptin monotherapy with alogliptin as an active comparator in patients with uncontrolled type 2 diabetes mellitus: a randomized, multicenter, double-blind, placebo-controlled, phase 3 trial.

BACKGROUND: Dipeptidyl peptidase-4 inhibitors (DPP-4i) have become firmly established in treatment algorithms and national guidelines for improving glycemic control in type 2 diabetes mellitus (T2DM).To report the findings from a multicenter, randomized, double-blind, placebo-controlled phase 3 clinical trial, which was designed to assess the efficacy and safety of a novel DPP-4 inhibitor fotagliptin in treatment-naive patients with T2DM. METHODS: Patients with T2DM were randomized to receive fotagliptin (n = 230), alogliptin (n = 113) or placebo (n = 115) at a 2:1:1 ratio for 24 weeks of double-blind treatment period, followed by an open-label treatment period, making up a total of 52 weeks. The primary efficacy endpoint was to determine the superiority of fotagliptin over placebo in the change of HbA1c from baseline to Week 24. All serious or significant adverse events were recorded. RESULTS: After 24 weeks, mean decreases in HbA1c from baseline were -0.70% for fotagliptin, -0.72% for alogliptin and -0.26% for placebo. Estimated mean treatment differences in HbA1c were -0.44% (95% confidence interval [CI]: -0.62% to -0.27%) for fotagliptin versus placebo, and -0.46% (95% CI: -0.67% to -0.26%) for alogliptin versus placebo, and 0.02% (95%CI: -0.16% to 0.19%; upper limit of 95%CI < margin of 0.4%) for fotagliptin versus alogliptin. So fotagliptin was non-inferior to alogliptin. Compared with subjects with placebo (15.5%), significantly more patients with fotagliptin (37.0%) and alogliptin (35.5%) achieved HbA1c < 7.0% after 24 weeks of treatment. During the whole 52 weeks of treatment, the overall incidence of hypoglycemia was low for both of the fotagliptin and alogliptin groups (1.0% each). No drug-related serious adverse events were observed in any treatment group. CONCLUSIONS: In summary, the study demonstrated improvement in glycemic control and a favorable safety profile for fotagliptin in treatment-naive patients with T2DM. TRIAL REGISTRATION: ClinicalTrail.gov NCT05782192.

An Integrated Liver Function, Systemic Inflammation, and Tumor Characteristic Score Predicts Prognosis in Hepatocellular Carcinoma After Curative Resection.

BACKGROUND: Several scoring systems are currently used to predict prognosis of hepatocellular carcinoma (HCC), but none of them integrates liver function, systemic inflammation, and tumor characteristics in a unified model. The current study aimed to develop and validate a novel prognostic score that integrates liver function, systemic inflammation, and tumor characteristics in a unified model to predict the prognosis of HCC after curative resection. METHODS: Patients with HCC who underwent curative liver resection were included in a training set (n = 1027). Multivariate Cox regression was performed to determine the risk factors for a poor prognosis. A prognostic score was developed by assigning points for risk factors in proportion to beta coefficients in a Cox multivariable model. Predictive performance and distinction ability of the prognostic score were further evaluated in two independent validation cohorts treated with either curative resection (n = 281) or transarterial chemoembolization (TACE) (n = 404) and compared with 16 other models. RESULTS: The prognostic predictive system, named the function-inflammation-burden-alpha-fetoprotein (FIBA) score, was derived by assigning points for six independent predictors including albumin, total bilirubin, lymphocyte count, diameter of the largest tumor, number of tumors, and alpha-fetoprotein (AFP). The FIBA score showed an outperformed predictive value compared with other systems in both training and validation cohorts by giving the highest C-index, likelihood ratio chi-square values, and Wald test values as well as the lowest Akaike information criterion. CONCLUSION: The FIBA score can be used to stratify HCC patients treated with curative resection. Meanwhile, the FIBA score performs well against other prognostic scoring systems and is potentially broadly applicable to a TACE-treated patient cohort.

A systematic review and meta-analysis on the prevalence of stigma in infectious diseases, including COVID-19: a call to action.

Infectious diseases, including COVID-19, are crucial public health issues and may lead to considerable fear among the general public and stigmatization of, and discrimination against, specific populations. This meta-analysis aimed to estimate the pooled prevalence of stigma in infectious disease epidemics. We systematically searched PubMed, PsycINFO, Embase, MEDLINE, Web of Science, and Cochrane databases since inception to June 08, 2021, and reported the prevalence of stigma towards people with infectious diseases including SARS, H1N1, MERS, Zika, Ebola, and COVID-19. A total of 50 eligible articles were included that contributed 51 estimates of prevalence in 92722 participants. The overall pooled prevalence of stigma across all populations was 34% [95% CI: 28-40%], including enacted stigma (36% [95% CI: 28-44%]) and perceived stigma (31% [95% CI: 22-40%]). The prevalence of stigma in patients, community population, and health care workers, was 38% [95% CI: 12- 65%], 36% [95% CI: 28-45%], and 30% [95% CI: 20-40%], respectively. The prevalence of stigma in participants from low- and middle-income countries was 37% [95% CI: 29-45%], which is higher than that from high-income countries (27% [95% CI: 18-36%]) though this difference was not statistically significant. A similar trend of prevalence of stigma was also observed in individuals with lower education (47% [95% CI: 23-71%]) compared to higher education level (33% [95% CI: 23-4%]). These findings indicate that stigma is a significant public health concern, and effective and comprehensive interventions are needed to counteract the damaging effects of the infodemics during infectious disease epidemics, including COVID-19, and reduce infectious disease-related stigma.

A systematic review and meta-analysis on prevalence of and risk factors associated with depression, anxiety and insomnia in infectious diseases, including COVID-19: a call to action.

Infectious disease epidemics have become more frequent and more complex during the 21st century, posing a health threat to the general public and leading to psychological symptoms. The current study was designed to investigate the prevalence of and risk factors associated with depression, anxiety and insomnia symptoms during epidemic outbreaks, including COVID-19. We systematically searched the PubMed, Embase, Web of Science, OVID, Medline, Cochrane databases, bioRxiv and medRxiv to identify studies that reported the prevalence of depression, anxiety or insomnia during infectious disease epidemics, up to August 14th, 2020. Prevalence of mental symptoms among different populations including the general public, health workers, university students, older adults, infected patients, survivors of infection, and pregnant women across all types of epidemics was pooled. In addition, prevalence of mental symptoms during COVID-19 was estimated by time using meta-regression analysis. A total of 17,506 papers were initially retrieved, and a final of 283 studies met the inclusion criteria, representing a total of 948,882 individuals. The pooled prevalence of depression ranged from 23.1%, 95% confidential intervals (95% CI: [13.9-32.2]) in survivors to 43.3% (95% CI: [27.1-59.6]) in university students, the pooled prevalence of anxiety ranged from 25.0% (95% CI: [12.0-38.0]) in older adults to 43.3% (95% CI: [23.3-63.3]) in pregnant women, and insomnia symptoms ranged from 29.7% (95% CI: [24.4-34.9]) in the general public to 58.4% (95% CI: [28.1-88.6]) in university students. Prevalence of moderate-to-severe mental symptoms was lower but had substantial variation across different populations. The prevalence of mental problems increased over time during the COVID-19 pandemic among the general public, health workers and university students, and decreased among infected patients. Factors associated with increased prevalence for all three mental health symptoms included female sex, and having physical disorders, psychiatric disorders, COVID infection, colleagues or family members infected, experience of frontline work, close contact with infected patients, high exposure risk, quarantine experience and high concern about epidemics. Frequent exercise and good social support were associated with lower risk for these three mental symptoms. In conclusion, mental symptoms are common during epidemics with substantial variation across populations. The population-specific psychological crisis management are needed to decrease the burden of psychological problem and improve the mental wellbeing during epidemic.

Binding of Tetrabromobisphenol A and S to Human Serum Albumin Is Weakened by Coexisting Nanoplastics and Environmental Kosmotropes.

Human serum albumin (HSA) was used as a model protein to explore the effects of brominated flame retardant (BFR) binding and the corona formation on polystyrene nanoplastics (PNs). Under physiological conditions, HSA helped to disperse PNs but promoted the formation of aggregates in the presence of tetrabromobisphenol A (TBBPA, ΔDh = 135 nm) and S (TBBPS, ΔDh = 256 nm) at pH 7. At pH 4, these aggregates became larger with fewer electrostatic repulsion effects (ΔDh = 920 and 691 nm for TBBPA and TBBPS, respectively). However, such promotion effects as well as BFR binding are different due to structural differences of tetrabromobisphenol A and S. Environmental kosmotropes efficiently stabilized the structure of HSA and inhibited BFR binding, while the chaotropes favored bioconjugated aggregate formation. Such effects were also verified in natural seawater. The newly gained knowledge may help us anticipate the behavior and fate of plastic particles and small molecular pollutants in both physiological and natural aqueous systems.