Background: Olanzapine and clozapine are atypical antipsychotics (AAPs) with the greatest risk of weight gain, and changes in feeding behavior are among the most important underlying mechanisms. However, few studies have investigated the role of diet-alone interventions in improving individuals' weight gain by taking AAPs. In closed management mental hospitals of China, family members are allowed to bring food to patients regularly, causing patients to have caloric intake added to their 3 daily meals. However, during the global pandemic of coronavirus disease 2019 (COVID-19), bringing food to the hospital was temporarily prohibited in mental health institutions in China to prevent the spread of the virus. This study sought to compare the body weight and body mass index (BMI) changes of patients taking olanzapine or clozapine undergoing diet-alone interventions caused by this prohibition.Methods: A retrospective self-controlled study was conducted on 90 patients with schizophrenia from a single-center treated with olanzapine or clozapine monotherapy, or combined with aripiprazole or ziprasidone which has a small metabolic impact. A paired-samples t-test was used to compare the changes in body weight and BMI before and after the 3-month prohibition, and general linear regression was used to analyze the effects of gender, age, disease course, duration of drug exposure, and equivalent dose on the BMI improvement. Also, the percentage of people who lost weight and that of individuals who lost 5% of their pre-prohibition body weight were calculated.Results: Paired-samples t-test showed that after 3-month prohibition, the patients' body weight (71.68±6.83 vs. 66.91±7.03, P<0.001) and BMI (26.43±2.11 vs. 24.63±1.81, P<0.001) decreased significantly. Weight loss rate accounted for 99.1%, and weight loss of 5% from the pre-prohibition body weight accounted for 71.8%. General linear regression showed that the duration of drug exposure (β =−0.678, P<0.001) was significantly and negatively correlated with the BMI changes. No significant correlation of gender, age, disease course, or equivalent dose with BMI changes was found.Conclusions: Diet-alone interventions facilitate weight loss in chronically hospitalized schizophrenia patients taking AAPs. Conduction of dietary intervention in the early stages of medication may yield greater benefits.
Antipsychotics are known to be associated with metabolic syndromes (MetS). Chlorpromazine (CPZ) and Clozapine (CLZ) are currently the most commonly used antipsychotics in low-income districts of China. However, potential differences in the long-term effects of CPZ and CLZ on MetS in schizophrenia inpatients are not well understood. Here, we aimed to identify any MetS profile differences between long-term schizophrenia patients who were prescribed either CPZ or CLZ at a primary psychiatric hospital.We recruited a total of 204 male schizophrenia patients who received either CPZ or CLZ. We measured their weight, height, body mass index (BMI), waist circumference (WC), diastolic blood pressure (DBP), and systolic blood pressure (SBP), as well as their biochemical indicators, including fasting blood glucose (FBS), triglycerides (TG), cholesterol (TC), high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c).The MetS prevalence in the CPZ and CLZ groups was 31% and 37.5%, respectively. The CLZ group had significantly higher DBP levels and a higher incidence of dyslipidemia (HDL-c) but lower HDL-c and TC levels than the CPZ group. We also determined that smoking history, BMI, and duration of hospitalisation were risk factors for the development of MetS. Moreover, we found that CPZ and CLZ were correlated with the same risk for developing MetS and that BMI was a vital risk factor of MetS for both the CPZ and CLZ groups.Long-term CPZ and CLZ prescriptions were associated with similar profiles for developing MetS of schizophrenia patients.
Summary The type III secretion system ( T3SS ) is a major virulence factor in many G ram‐negative bacterial pathogens and represents a particularly appealing target for antimicrobial agents. Previous studies have shown that the plant phenolic compound p ‐coumaric acid ( PCA ) plays a role in the inhibition of T3SS expression of the phytopathogen D ickeya dadantii 3937. This study screened a series of derivatives of plant phenolic compounds and identified that trans ‐4‐hydroxycinnamohydroxamic acid ( TS 103) has an eight‐fold higher inhibitory potency than PCA on the T3SS of D . dadantii . The effect of TS 103 on regulatory components of the T3SS was further elucidated. Our results suggest that TS103 inhibits HrpY phosphorylation and leads to reduced levels of hrp S and hrp L transcripts. In addition, through a reduction in the RNA levels of the regulatory small RNA RsmB , TS103 also inhibits hrp L at the post‐transcriptional level via the rsm B ‐ RsmA regulatory pathway. Finally, TS 103 inhibits hrp L transcription and mRNA stability, which leads to reduced expression of HrpL regulon genes, such as hrp A and hrp N . To our knowledge, this is the first inhibitor to affect the T3SS through both the transcriptional and post‐transcriptional pathways in the soft‐rot phytopathogen D . dadantii 3937.
Aims/hypothesis It is widely thought that the intestinal microbiota plays a significant role in the pathogenesis of metabolic disorders. However, the gut microbiota composition and characteristics of schizophrenia patients with metabolic syndrome (MetS) have been largely understudied. Herein, we investigated the association between the metabolic status of mainland Chinese schizophrenia patients with MetS and the intestinal microbiome. Methods Fecal microbiota communities from 115 male schizophrenia patients (57 with MetS and 58 without MetS) were assessed by 16S ribosomal RNA gene sequencing. We assessed the variations of gut microbiome between both groups and explored potential associations between intestinal microbiota and parameters of MetS. In addition, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) based on the KEGG database was used to predict the function of intestinal microbiota. We also conducted Decision Tree Analysis to develop a diagnostic model for the MetS in patients with schizophrenia based on the composition of intestinal microbiota. Results The fecal microbial diversity significantly differed between groups with or without MetS (α-diversity (Shannon index and Simpson index): p=0.0155, p=0.0089; β-diversity: p=0.001). Moreover, the microbial composition was significantly different between the two groups, involving five phyla and 38 genera (p<0.05). In addition, a significant correlation was observed between the metabolic-related parameters and abundance of altered microbiota including HDL-c (r2 = 0.203, p=0.0005), GLU (r2 = 0.286, p=0.0005) and WC (r2 = 0.061, p=0.037). Furthermore, KEGG pathway analysis showed that 16 signaling pathways were significantly enriched between the two groups (p<0.05). Importantly, our diagnostic model based on five microorganisms established by decision tree analysis could effectively distinguish between patients with and without MetS (AUC = 0.94). Conclusions/interpretation Our study established the compositional and functional characteristics of intestinal microbiota in schizophrenia patients with MetS. These new findings provide novel insights into a better understanding of this disease and provide the theoretical basis for implementing new interventional therapies in clinical practice.
Terrestrial evapotranspiration (ET) is an important control factor for water cycling and energy transport, serving as a crucial link between ecological and hydrological processes. Accurate estimation of ET is essential for enhancing efficient utilization of water resources, improving agricultural productivity, preserving ecosystems, and advancing climate change research. Despite its significance, high spatiotemporal resolution continuous ET datasets remain scarce. In ET estimation, machine learning methods have been widely adopted, with tree-based machine learning models gaining increasing attention due to their computational efficiency and reliability accuracy. However, research comparing the performance of these models remains relatively limited. In this study, we use data from flux observation sites and various remote sensing sources to explore the performance of four tree-based machine learning models in ET estimation across the Contiguous United States (CONUS). Our findings demonstrate the proficient performance of all four models in estimating terrestrial ET across CONUS. Particularly noteworthy is the outstanding performance of the extremely randomized trees (ERT) model, showing a high correlation (R2 = 0.84), low bias (BIAS = −0.0003 mm/d), and low root mean square error (RMSE = 0.72 mm/d) with flux observation site data. Using this model, we successfully obtained a seamless terrestrial ET dataset (ERT_ET) with a spatial resolution of 1 km and multiple temporal resolutions (daily, 8-day, monthly, and seasonal) from 2008 to 2018 across the CONUS. Compared to the MOD16 ET product, the ERT_ET outperforms with a higher R2 by 0.40 and lower RMSE by 5.31 mm/8d, providing better performance in capturing detailed features. Moreover, our ERT_ET product is comparable to other widely used ET products (MOD16, PML-V2, and ETMonitor), further highlighting its reliability. These findings will contribute to studies in various fields, including global climate change, hydrological cycles, and drought monitoring.
Abstract: Antipsychotics with a prominent anti-serotoninergic profile have risks of obsessive-compulsive symptoms (OCS). These types of OCS are remain mostly intractable to existing treatments because of the dilemma between the antipsychotic effects and the OCS adverse effects, both of which brought by serotoninergic-blocking profile. This state forced us to seek non-serotonergic system pharmaceuticals. Memantine, as a glutamatergic drug, is the adjunctive agent most consistently showing an effective impact in primary OCD, however its benefit in antipsychotics-associated OCS has not been reported. Herein, we presented a case of a 34-year-old male schizophrenia patient who experienced antipsychotics-associated OCS which could not be relieved by routine managements. He had fallen into dilemma of either aggravated OCS or poorly controlled schizophrenia. Eventually his condition got significant relief by individualized utilization of antipsychotics to control psychosis and by memantine to deal with his OCS. This is the first case to report the benefit of memantine in SGAs-associated OCS. It suggests that memantine is a worth considering approach, especially when the OCS are resistant to routine managements. Moreover, this case would be helpful for clinicians to know the etiology of SGAs-associated OCS, as indicated by the interesting changes after every adjustment of antipsychotics in the whole therapeutic course.
A considerable number of patients suffer from adverse metabolic reactions caused by atypical antipsychotics (AAPs), however, current management strategies are disappointing to clinicians. Preclinical studies have consistently demonstrated that intermittent fasting (IF) has robust disease-modifying efficacy in animal models in a wide range of pathological conditions, especially obesity and diabetes. However, it is unclear what role IF can play in addressing AAPs-induced metabolic disturbances. In our study, we found that a 5:2 IF regimen significantly ameliorated the metabolic disturbances induced by olanzapine (a drug representative of AAPs) in animal models. Meanwhile, our research suggests that IF altering food intake during the refeeding phase may account for the metabolic benefit. This study provides supporting evidence regarding a potentially cost-effective intervention strategy for AAPs-induced metabolic disturbances.
Background: Many studies have indicated that autophagy plays an important role in multiple cancers, including hepatocellular carcinoma (HCC). This study aimed to establish a prognostic signature for HCC based on autophagy-related genes (ARGs) to predict the prognosis of patients.
Background: Hepatocellular carcinomas (HCCs) occur frequently in the digestive system and are associated with high mortality. This current study examined the regulatory relationship between interleukin (IL)-1 receptor-associated kinase 1 (IRAK1), NLR family pyrin domain-containing 3 (NLRP3) inflammasomes, and tumor-associated macrophages (TAMs) in the growth and metastasis of HCC. Methods: The expression of IRAK1 and NLRP3 was assessed in tissues and cells via quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis. Immunohistology was performed to detect the macrophage markers CD68, CD163, and CD168 in tumor tissues. Small interfering (si)RNA targeting IRAK1 (si-IRAK1) was designed to silence IRAK1 expression. Following si-IRAK1 transfection and/or co-culture with TAMs, HCC cell viability, proliferation, migration, and invasion, as well as the expression of NLRP3 and pro-inflammatory cytokines IL-1 β, IL-18, and monocyte chemotactic protein 1 (MCP-1) were assessed. Results: HCC tissues showed elevated expression of IRAK1 and NLRP3, as well as increased expression of the macrophage markers CD68, CD163, and CD168, compared to adjacent healthy tissues. Silencing of IRAK1 expression in HepG2 and Huh7 cells resulted in suppression of cell proliferation, migration, and invasion, and also reduced expression of NLRP3 and the pro-inflammatory cytokines IL-1β, IL-18, and MCP-1. Moreover, TAMs promoted HepG2 and Huh7 cell proliferation, migration, and invasion, and elevated the expression of NLRP3, IL-1β, IL-18, and MCP-1. Furthermore, IRAK1 silencing reversed the effects of TAMs on HepG2 and Huh7 cells. Conclusions: The expression of IRAK1 was associated with HCC growth and metastasis, as well as NLRP3 inflammasome activation. The ability of TAMs to promote HCC growth and metastasis may be activated by NLRP3 inflammasomes and regulated by IRAK1.
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