The photoactivated antifungal activity and possible mode of action of sodium pheophorbide a on Diaporthe mahothocarpus causing leaf spot blight in Camellia oleifera.

Introduction: Sodium pheophorbide a (SPA) is a natural plant-derived photosensitizer, with high photoactivated antifungal activity against some phytopathogenic fungi. However, its fungicidal effect on Diaporthe mahothocarpus, a novel pathogen that causes Camellia oleifera leaf spot blight, is unclear. Methods: In the present study, we explored its inhibitory effects on spore germination and mycelial growth of D. mahothocarpus. Then we determined its effects on the cell membrane, mycelial morphology, redox homeostasis, and cell death through bioassay. Finally, RNA-seq was used further to elucidate its mode of action at the transcriptional level. Results: We found that SPA effectively inhibited the growth of D. mahothocarpus, with half-maximal effective concentrations to inhibit mycelial growth and spore germination of 1.059 and 2.287 mg/mL, respectively. After 1.0 mg/mL SPA treatment, the conductivity and malondialdehyde content of D. mahothocarpus were significantly increased. Scanning electron microscopy and transmission electron microscopy indicated that SPA significantly affected the morphology and ultrastructure of D. mahothocarpus hyphae, revealing that SPA can destroy the mycelial morphology and cell structure, especially the cell membrane of D. mahothocarpus. Furthermore, transcriptome analysis revealed that SPA significantly suppressed the expression of genes involved in morphology, cell membrane permeability, and oxidative stress. Then, we also found that SPA significantly promoted the accumulation of reactive oxygen species (ROS) in of D. mahothocarpus, while it decreased the content of reduced glutathione, inhibited the enzyme activities of superoxide dismutase and catalase, and exacerbated DNA damage. Annexin V-FITC/PI staining also confirmed that 1.0 mg/mL SPA could significantly induce apoptosis and necrosis. Discussion: Generally, SPA can induce ROS-mediated oxidative stress and cell death, thus destroying the cell membrane and hyphal morphology, and ultimately inhibiting mycelial growth, which indicates that SPA has multiple modes of action, providing a scientific basis for the use of SPA as an alternative plant-derived photoactivated fungicide against C. oleifera leaf spot blight.

Circulating Metabolite Biomarkers of Glycemic Control in Youth-Onset Type 2 Diabetes.

OBJECTIVE: We aimed to identify metabolites associated with loss of glycemic control in youth-onset type 2 diabetes. RESEARCH DESIGN AND METHODS: We measured 480 metabolites in fasting plasma samples from the TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth) study. Participants (N = 393; age 10-17 years) were randomly assigned to metformin, metformin plus rosiglitazone, or metformin plus lifestyle intervention. Additional metabolomic measurements after 36 months were obtained in 304 participants. Cox models were used to assess baseline metabolites, interaction of metabolites and treatment group, and change in metabolites (0-36 months), with loss of glycemic control adjusted for age, sex, race, treatment group, and BMI. Metabolite prediction models of glycemic failure were generated using elastic net regression and compared with clinical risk factors. RESULTS: Loss of glycemic control (HbA1c ≥8% or insulin therapy) occurred in 179 of 393 participants (mean 12.4 months). Baseline levels of 33 metabolites were associated with loss of glycemic control (q < 0.05). Associations of hexose and xanthurenic acid with treatment failure differed by treatment randomization; youths with higher baseline levels of these two compounds had a lower risk of treatment failure with metformin alone. For three metabolites, changes from 0 to 36 months were associated with loss of glycemic control (q < 0.05). Changes in d-gluconic acid and 1,5-AG/1-deoxyglucose, but not baseline levels of measured metabolites, predicted treatment failure better than changes in HbA1c or measures of ß-cell function. CONCLUSIONS: Metabolomics provides insight into circulating small molecules associated with loss of glycemic control and may highlight metabolic pathways contributing to treatment failure in youth-onset diabetes.

Metal-containing nanoparticles in road dust from a Chinese megacity over the last decade: Spatiotemporal variation and driving factors.

As a crucial sink of metal-containing nanoparticles (MNPs), road dust can record their spatiotemporal variations in urban environments. In this study, taking Shanghai as a representative megacity in China, a total of 272 dust samples were collected in the winter and summer of 2013 and 2021/2022 to understand the spatiotemporal variations and driving factors of MNPs. The number concentrations of Fe-, Ti-, and Zn-containing NPs were 3.8 × 106 - 8.4 × 108, 2.3 × 106-1.4 × 108, and 6.0 × 105-2.3 × 108 particles/mg, respectively, according to single particle (sp)ICP-MS analysis. These MNPs showed significantly higher number concentrations in summer than in winter. Hotspots of Fe-containing NPs were more concentrated in industrial and traffic areas, Zn-containing NPs were mainly distributed in the central urban areas, while Ti-containing NPs were abundant in areas receiving high rainfall. The structural equation model results indicates that substantial rainfall in summer can help remove MNPs from atmospheric PM2.5 into dust, while in winter industrial and traffic activities were the primary contributors for MNPs. Moreover, the contribution of traffic emissions to MNPs has surpassed industrial one over the last decade, highlighting the urgency to control traffic-sourced MNPs, especially those from non-exhaust emissions by electric vehicles.

TIR8 protects against nonalcoholic steatohepatitis by antagonizing lipotoxicity-induced PPARα downregulation and reducing the sensitivity of hepatocytes to LPS.

In up to one-third of nonalcoholic fatty liver disease (NAFLD) patients, simple steatosis progresses to its more severe form, nonalcoholic steatohepatitis (NASH), but the precise mechanisms underlying this transition are not fully understood. Toll/interleukin-1 receptor 8 (TIR8), a conventional innate immune regulator highly expressed in hepatic tissue, has shown potential for ameliorating various inflammation-related disorders. However, its role in NASH pathogenesis, especially its regulatory effects on lipid metabolism and inflammatory responses, is still unclear. Here, using a TIR8 knockout (TIR8KO) mouse model and mass spectrometry analyses, we found that TIR8KO mice displayed aggravated hepatic steatosis and inflammation, whereas TIR8 overexpression attenuated these adverse effects. Ectopic TIR8 expression counteracts free fatty acid (FFA)-induced PPARα inhibition and downstream signaling. A decrease in TIR8 levels in hepatocytes heightened lipopolysaccharide (LPS) sensitivity. Notably, FFA stimulation led to a direct interaction between TIR8 and proteasome subunit alpha type 4 (PSMA4), facilitating TIR8 degradation. These results revealed that TIR8 safeguards PPARα-regulated lipid metabolism and mitigates inflammation induced by external factors during NASH progression. Our study highlights TIR8 as a promising target for NASH therapy, indicating the potential of TIR8 agonists in treatment strategies.

Obscured Contribution of Oxygenated Intermediate-Volatility Organic Compounds to Secondary Organic Aerosol Formation from Gasoline Vehicle Emissions.

Secondary organic aerosol (SOA) formation from gasoline vehicles spanning a wide range of emission types was investigated using an oxidation flow reactor (OFR) by conducting chassis dynamometer tests. Aided by advanced mass spectrometric techniques, SOA precursors, including volatile organic compounds (VOCs) and intermediate/semivolatile organic compounds (I/SVOCs), were comprehensively characterized. The reconstructed SOA produced from the speciated VOCs and I/SVOCs can explain 69% of the SOA measured downstream of an OFR upon 0.5-3 days' OH exposure. While VOCs can only explain 10% of total SOA production, the contribution from I/SVOCs is 59%, with oxygenated I/SVOCs (O-I/SVOCs) taking up 20% of that contribution. O-I/SVOCs (e.g., benzylic or aliphatic aldehydes and ketones), as an obscured source, account for 16% of total nonmethane organic gas (NMOG) emission. More importantly, with the improvement in emission standards, the NMOG is effectively mitigated by 35% from China 4 to China 6, which is predominantly attributed to the decrease of VOCs. Real-time measurements of different NMOG components as well as SOA production further reveal that the current emission control measures, such as advances in engine and three-way catalytic converter (TWC) techniques, are effective in reducing the "light" SOA precursors (i.e., single-ring aromatics) but not for the I/SVOC emissions. Our results also highlight greater effects of O-I/SVOCs to SOA formation than previously observed and the urgent need for further investigation into their origins, i.e., incomplete combustion, lubricating oil, etc., which requires improvements in real-time molecular-level characterization of I/SVOC molecules and in turn will benefit the future design of control measures.

To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice.

OBJECTIVES: To develop recommendations regarding the use of weights to reduce selection bias for commonly performed analyses using electronic health record (EHR)-linked biobank data. MATERIALS AND METHODS: We mapped diagnosis (ICD code) data to standardized phecodes from 3 EHR-linked biobanks with varying recruitment strategies: All of Us (AOU; n = 244 071), Michigan Genomics Initiative (MGI; n = 81 243), and UK Biobank (UKB; n = 401 167). Using 2019 National Health Interview Survey data, we constructed selection weights for AOU and MGI to represent the US adult population more. We used weights previously developed for UKB to represent the UKB-eligible population. We conducted 4 common analyses comparing unweighted and weighted results. RESULTS: For AOU and MGI, estimated phecode prevalences decreased after weighting (weighted-unweighted median phecode prevalence ratio [MPR]: 0.82 and 0.61), while UKB estimates increased (MPR: 1.06). Weighting minimally impacted latent phenome dimensionality estimation. Comparing weighted versus unweighted phenome-wide association study for colorectal cancer, the strongest associations remained unaltered, with considerable overlap in significant hits. Weighting affected the estimated log-odds ratio for sex and colorectal cancer to align more closely with national registry-based estimates. DISCUSSION: Weighting had a limited impact on dimensionality estimation and large-scale hypothesis testing but impacted prevalence and association estimation. When interested in estimating effect size, specific signals from untargeted association analyses should be followed up by weighted analysis. CONCLUSION: EHR-linked biobanks should report recruitment and selection mechanisms and provide selection weights with defined target populations. Researchers should consider their intended estimands, specify source and target populations, and weight EHR-linked biobank analyses accordingly.

Doubly robust proximal synthetic controls.

To infer the treatment effect for a single treated unit using panel data, synthetic control (SC) methods construct a linear combination of control units' outcomes that mimics the treated unit's pre-treatment outcome trajectory. This linear combination is subsequently used to impute the counterfactual outcomes of the treated unit had it not been treated in the post-treatment period, and used to estimate the treatment effect. Existing SC methods rely on correctly modeling certain aspects of the counterfactual outcome generating mechanism and may require near-perfect matching of the pre-treatment trajectory. Inspired by proximal causal inference, we obtain two novel nonparametric identifying formulas for the average treatment effect for the treated unit: one is based on weighting, and the other combines models for the counterfactual outcome and the weighting function. We introduce the concept of covariate shift to SCs to obtain these identification results conditional on the treatment assignment. We also develop two treatment effect estimators based on these two formulas and generalized method of moments. One new estimator is doubly robust: it is consistent and asymptotically normal if at least one of the outcome and weighting models is correctly specified. We demonstrate the performance of the methods via simulations and apply them to evaluate the effectiveness of a pneumococcal conjugate vaccine on the risk of all-cause pneumonia in Brazil.

Disseminated Talaromyces marneffei infection initially presenting as cutaneous and subcutaneous lesion in an HIV-Negative renal transplant recipient: a case report and literature review.

BACKGROUND: The incidence of Talaromyces marneffei (T. marneffei) infection has increased in recent years with the development of organ transplantation and the widespread use of immunosuppressive agents. However, the lack of clinical suspicion leading to delay or misdiagnosis is an important reason for the high mortality rate in non-human immunodeficiency virus (HIV) and non-endemic population. Herein, we report a case of disseminated T. marneffei infection in a non-HIV and non-endemic recipient after renal transplant, who initially presented with skin rashes and subcutaneous nodules and developed gastrointestinal bleeding. CASE PRESENTATION: We describe a 54-year-old renal transplantation recipient presented with scattered rashes, subcutaneous nodules and ulcerations on the head, face, abdomen, and right upper limb. The HIV antibody test was negative. The patient had no obvious symptoms such as fever, cough, etc. Histopathological result of the skin lesion sites showed chronic suppurative inflammation with a large number of fungal spores. Subsequent fungal culture suggested T. marneffei infection. Amphotericin B deoxycholate was given for antifungal treatment, and there was no deterioration in the parameters of liver and kidney function. Unfortunately, the patient was soon diagnosed with gastrointestinal bleeding, gastrointestinal perforation and acute peritonitis. Then he rapidly developed multiple organ dysfunction syndrome and abandoned treatment. CONCLUSIONS: The risk of fatal gastrointestinal bleeding can be significantly increased in kidney transplant patients with T. marneffei infection because of the long-term side effects of post-transplant medications. Strengthening clinical awareness and using mNGS or mass spectrometry technologies to improve the detection rate and early diagnosis of T. marneffei are crucial for clinical treatment in non-HIV and non-endemic population.

Conditional reprogrammed human limbal epithelial cell model for anti-SARS-CoV-2 drug screening.

To minimize the global pandemic COVID-19 spread, understanding the possible transmission routes of SARS-CoV-2 and discovery of novel antiviral drugs are necessary. We describe here that the virus can infect ocular surface limbal epithelial, but not other regions. Limbal supports wild type and mutant SARS-CoV-2 entry and replication depending on ACE2, TMPRSS2 and possibly other receptors, resulting in slight CPE and arising IL-6 secretion, which symbolizes conjunctivitis in clinical symptoms. With this limbal model, we have screened two natural product libraries and discovered several unreported drugs. Our data reveal important commonalities between COVID-19 and ocular infection with SARS-CoV-2, and establish an ideal cell model for drug screening and mechanism research.

Online causal inference with application to near real-time post-market vaccine safety surveillance.

Streaming data routinely generated by social networks, mobile or web applications, e-commerce, and electronic health records present new opportunities to monitor the impact of an intervention on an outcome via causal inference methods. However, most existing causal inference methods have been focused on and applied to static data, that is, a fixed data set in which observations are pooled and stored before performing statistical analysis. There is thus a pressing need to turn static causal inference into online causal learning to support near real-time monitoring of treatment effects. In this paper, we present a framework for online estimation and inference of treatment effects that can incorporate new information as it becomes available without revisiting prior observations. We show that, under mild regularity conditions, the proposed online estimator is asymptotically equivalent to the offline oracle estimator obtained by pooling all data. Our proposal is motivated by the need for near real-time vaccine effectiveness and safety monitoring, and our proposed method is applied to a case study on COVID-19 vaccine safety surveillance.

BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis.

Brown adipose tissue (BAT) is best known for thermogenesis. Rodent studies demonstrated that enhanced BAT thermogenesis is tightly associated with increased energy expenditure, reduced body weight, and improved glucose homeostasis. However, human BAT is protective against type 2 diabetes, independent of body weight. The mechanism underlying this dissociation remains unclear. Here, we report that impaired mitochondrial catabolism of branched-chain amino acids (BCAAs) in BAT, by deleting mitochondrial BCAA carriers (MBCs), caused systemic insulin resistance without affecting energy expenditure and body weight. Brown adipocytes catabolized BCAA in the mitochondria as nitrogen donors for the biosynthesis of non-essential amino acids and glutathione. Impaired mitochondrial BCAA-nitrogen flux in BAT resulted in increased oxidative stress, decreased hepatic insulin signaling, and decreased circulating BCAA-derived metabolites. A high-fat diet attenuated BCAA-nitrogen flux and metabolite synthesis in BAT, whereas cold-activated BAT enhanced the synthesis. This work uncovers a metabolite-mediated pathway through which BAT controls metabolic health beyond thermogenesis.

Identification of immune-associated biomarker for predicting lung adenocarcinoma: bioinformatics analysis and experiment verification of PTK6.

BACKGROUND: Abnormal expression of protein tyrosine kinase 6 (PTK6) has been proven to be involved in the development of gynecological tumors. However, its immune-related carcinogenic mechanism in other tumors remains unclear. OBJECTIVE: The aim of this study was to identify PTK6 as a novel prognostic biomarker in pan-cancer, especially in lung adenocarcinoma (LUAD), which is correlated with immune infiltration, and to clarify its clinicopathological and prognostic significance. METHODS: The prognostic value and immune relevance of PTK6 were investigated by using bio-informatics in this study. PTK6 expression was validated in vitro experiments (lung cancer cell lines PC9, NCI-H1975, and HCC827; human normal lung epithelial cells BEAS-2B). Western blot (WB) revealed the PTK6 protein expression in lung cancer cell lines. PTK6 expression was inhibited by Tilfrinib. Colony formation and the Cell Counting Kit-8 (CCK-8) assay were used to detect cell proliferation. The wound healing and trans-well were performed to analyze the cell migration capacity. Then flow cytometry was conducted to evaluate the cell apoptosis. Eventually, the relationship between PTK6 and immune checkpoints was examined. WB was used to estimate the PD-L1 expression at different Tilfrinib doses. RESULTS: PTK6 was an independent predictive factor for LUAD and was substantially expressed in LUAD. Pathological stage was significantly correlated with increased PTK6 expression. In accordance with survival analysis, poor survival rate in LUAD was associated with a high expression level of PTK6. Functional enrichment of the cell cycle and TGF-ß signaling pathway was demonstrated by KEGG and GSEA analysis. Moreover, PTK6 expression considerably associated with immune infiltration in LUAD, as determined by immune analysis. Thus, the result of vitro experiments indicated that cell proliferation and migration were inhibited by the elimination of PTK6. Additionally, PTK6 suppression induced cell apoptosis. Obviously, PD-L1 protein expression level up-regulated while PTK6 was suppressed. CONCLUSION: PTK6 has predictive value for LUAD prognosis, and could up regulated PD-L1.

Association between sleep-disordered breathing and post-stroke fatigue in patients with ischemic stroke.

OBJECTIVES: Post-stroke fatigue (PSF) is common and often disabling. Sleep-disordered breathing (SDB) is highly prevalent among stroke survivors and can cause fatigue. We explored the relationship between SDB and PSF over time. MATERIALS AND METHODS: Ischemic stroke (IS) patients within the BASIC project were offered SDB screening with a well-validated cardiopulmonary sleep apnea test at 0, 3-, 6-, and 12-months post-stroke. The primary exposure was the respiratory event index (REI; sum of apneas plus hypopneas per hour). The primary outcome was PSF, measured by the SF-36 vitality scale. Associations between REI and PSF were evaluated using linear regression including time-by-REI interactions, allowing the effect of REI to vary over time. RESULTS: Of the 411 IS patients who completed at least one outcome interview, 44 % were female, 61 % Mexican American (MA), 26 % non-Hispanic white, with a mean age of 64 (SD 10). Averaged across timepoints, REI was not associated with PSF. In a time-varying model, higher REI was associated with greater PSF at 3-months (ß = 1.75, CI = 0.08, 3.43), but not at 6- or 12-months. Across timepoints, female sex, depressive symptoms, and comorbidity burden were associated with greater PSF, whereas MA ethnicity was associated with less PSF. CONCLUSIONS: Higher REI was associated with modestly greater PSF in the early post-stroke period, but no association was observed at 6 months and beyond. SDB may be a modest modifiable risk factor for early PSF, but its treatment is unlikely to have a substantial impact on long-term PSF. MA ethnicity seems to be protective against PSF.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy.

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Mechanisms of electroacupuncture relieves uterine smooth muscle spasm in dysmenorrhea rats based on Rho/ROCK signaling pathway. / 基于Rho/ROCKä¿¡å·é€šè·¯æŽ¢è®¨ç”µé’ˆä»»è„‰ã€ç£è„‰ç»ç©´ç¼“è§£ç±»ç—›ç»æ¨¡åž‹å¤§é¼ å­å®«å¹³æ»‘è‚Œç—‰æŒ›çš„æœºåˆ¶.

OBJECTIVES: To investigate the effect of electroacupuncture (EA) on Rho/Rho-associated coiled-coil-forming kinases (ROCK) signaling pathway of uterus tissue in rats with dysmenorrhea, so as to explore the underlying mechanism of EA treating primary dysmenorrhea (PD) and uterine smooth muscle spasm, and to observe whether there is a difference in the effect of meridian acupoints in Conception Vessel (CV) and Governer Vessel (GV). METHODS: Sixty female SD rats were randomly divided into saline, model, CV, GV, and non-acupoint groups, with 12 rats in each group. The dysmenorrhea model was established by subcutaneous injection of estradiol diphenhydrate combined with intraperitoneal injection of oxytocin (OT). EA (2 Hz) was applied to "Qihai" (CV6) and "Zhongji" (CV3) for CV group, "Mingmen" (GV4) and "Yaoshu" (GV2) for GV group, "non-acupoint 1" and "non-acupoint 3" on the left side for non-acupoint group, and manual acupuncture was applied to "Guanyuan" (CV4) for CV group, "Yaoyangguan" (GV3) for GV group, "non-acupoint 2" on the left side for non-acupoint group. The treatment was conducted for 20 min each time, once daily for 10 days. The writhing score was evaluated. The smooth myoelectric signals of rats' uterus in vivo were recorded by multi-channel physiological recorder. The uterine histopathological changes were observed by HE staining. The contents of prostaglandin F2α (PGF2α), OT and calcium ion (Ca2+) in uterine tissue of rats were detected by ELISA. The protein and mRNA expression levels of smooth muscle 22-α (SM22-α), RhoA and ROCKⅡ in uterine tissue were detected by Western blot and fluorescence quantitative PCR, respectively. RESULTS: Compared with the saline group, the writhing score of rats in the model group was increased (P<0.01), the amplitude voltage of uterine smooth muscle in vivo was elevated (P<0.01), the contents of PGF2α, OT and Ca2+, the protein and mRNA expression of SM22-α, RhoA and ROCK Ⅱ in uterine tissue were all increased (P<0.01). Compared with the model and the non-acupoint groups, the writhing scores of the CV and the GV groups were decreased (P<0.01, P<0.05), the amplitude voltage of uterine smooth muscle was decreased (P<0.01), the contents of PGF2α, OT and Ca2+ in uterine tissue were decreased (P<0.01, P<0.05), and the protein expression and mRNA expression of SM22-α, RhoA and ROCKⅡ in uterine tissue were decreased (P<0.01, P<0.05). HE staining showed extensive exfoliation of uterine intima with severe edema and increased glandular secretion in the model group, which was alleviated in the CV and GV groups. CONCLUSIONS: EA at acupoints of CV and GV can significantly reduce the writhing score, uterine smooth muscle amplitude voltage, pathological injury degree of uterus, and relieve spasm of uterine smooth muscle in dysmenorrhea rats, which may be related to its effect in regulating PGF2α and OT contents, inhibiting the Rho/ROCK signaling pathway, and reducing the SM22-α, RhoA, ROCKⅡ protein and mRNA expression, and Ca2+ content in uterine tissue.

Combined exposure of emamectin benzoate and microplastics induces tight junction disorder, immune disorder and inflammation in carp midgut via lysosome/ROS/ferroptosis pathway.

Pesticides and plastics bring convenience to agriculture and life, but also bring residual pollution in the environment. Emamectin benzoate (EMB) is the most popular pesticide at present. The harm of microplastics (MPs) to water and aquatic organisms is gradually increasing, and the possibility that it appears synchronously with various pesticides increases. However, the damage of EMB and MPs to the carp midgut and its mechanism have not been clarified. Therefore, based on the EMB or/and MPs exposure models, this study explored the mechanism of midgut injury through transcriptomics, immunofluorescence, western blot methods, and so on. Studies in vivo and in vitro showed that EMB or MPs exposure caused cilia shortening, lysosome damage, and ROS overproduction, which led to Fe2+ content increase, GSH/GSSG system disorder, lipid peroxidation, and ferroptosis. This process further led to the down-regulation of Cx43, Occludin, Claudin, and ZO-1, which further caused barrier damage, immune-related genes (immunoglobulin, IFN-γ) decrease and inflammation-related genes (TNF-α, IL-1ß) increase. Combined exposure was more significant than that of single exposure, and the addition of EN6 and NAC proved that lysosome/ROS/ferroptosis regulated these midgut damages. In conclusion, EMB or/and MPs exposure induce tight junction disorder, immune disorder and inflammation in carp midgut through the lysosome/ROS/ferroptosis pathway.

Lac-Phe mediates the effects of metformin on food intake and body weight.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. There is ongoing debate about the mechanisms that mediate metformin's effects on energy balance. Here, we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite N-lactoyl-phenylalanine (Lac-Phe) in cells, in mice and two independent human cohorts. Metformin drives Lac-Phe biosynthesis through the inhibition of complex I, increased glycolytic flux and intracellular lactate mass action. Intestinal epithelial CNDP2+ cells, not macrophages, are the principal in vivo source of basal and metformin-inducible Lac-Phe. Genetic ablation of Lac-Phe biosynthesis in male mice renders animals resistant to the effects of metformin on food intake and body weight. Lastly, mediation analyses support a role for Lac-Phe as a downstream effector of metformin's effects on body mass index in participants of a large population-based observational cohort, the Multi-Ethnic Study of Atherosclerosis. Together, these data establish Lac-Phe as a critical mediator of the body weight-lowering effects of metformin.

Targeted Learning with an Undersmoothed Lasso Propensity Score Model for Large-Scale Covariate Adjustment in Healthcare Database Studies.

Lasso regression is widely used for large-scale propensity score (PS) estimation in healthcare database studies. In these settings, previous work has shown that undersmoothing (overfitting) Lasso PS models can improve confounding control, but it can also cause problems of non-overlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale Lasso PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed Lasso PS-models, the use of cross-fitting was important for avoiding non-overlap in covariate distributions and reducing bias in causal estimates.

Collaborative inference for treatment effect with distributed data-sharing management in multicenter studies.

Data sharing barriers present paramount challenges arising from multicenter clinical studies where multiple data sources are stored and managed in a distributed fashion at different local study sites. Merging such data sources into a common data storage for a centralized statistical analysis requires a data use agreement, which is often time-consuming. Data merging may become more burdensome when propensity score modeling is involved in the analysis because combining many confounding variables, and systematic incorporation of this additional modeling in a meta-analysis has not been thoroughly investigated in the literature. Motivated from a multicenter clinical trial of basal insulin treatment for reducing the risk of post-transplantation diabetes mellitus, we propose a new inference framework that avoids the merging of subject-level raw data from multiple sites at a centralized facility but needs only the sharing of summary statistics. Unlike the architecture of federated learning, the proposed collaborative inference does not need a center site to combine local results and thus enjoys maximal protection of data privacy and minimal sensitivity to unbalanced data distributions across data sources. We show theoretically and numerically that the new distributed inference approach has little loss of statistical power compared to the centralized method that requires merging the entire data. We present large-sample properties and algorithms for the proposed method. We illustrate its performance by simulation experiments and the motivating example on the differential average treatment effect of basal insulin to lower risk of diabetes among kidney-transplant patients compared to the standard-of-care.