Effect of prebiotic fiber on physical function and gut microbiota in adults, mostly women, with knee osteoarthritis and obesity: a randomized controlled trial.

PURPOSE: Obesity is a primary risk factor for knee osteoarthritis (OA). Prebiotics enhance beneficial gut microbes and can reduce body fat and inflammation. Our objective was to examine if a 6-month prebiotic intervention improved physical function in adults with knee osteoarthritis and obesity. We also measured knee pain, body composition, quality of life, gut microbiota, inflammatory markers, and serum metabolomics. METHODS: Adults (n = 54, mostly women) with co-morbid obesity (BMI > 30 kg/m2) and unilateral/bilateral knee OA were randomly assigned to prebiotic (oligofructose-enriched inulin; 16 g/day; n = 31) or isocaloric placebo (maltodextrin; n = 21) for 6 months. Performance based-tests, knee pain, quality of life, serum metabolomics and inflammatory markers, and fecal microbiota and short-chain fatty acids were assessed. RESULTS: Significant between group differences were detected for the change in timed-up-and-go test, 40 m fast paced walk test, and hand grip strength test from baseline that favored prebiotic over placebo. Prebiotic also reduced trunk fat mass (kg) at 6 months and trunk fat (%) at 3 months compared to placebo. There was a trend (p = 0.059) for reduced knee pain at 6 months with prebiotic versus placebo. In gut microbiota analysis, a total of 37 amplicon sequence variants differed between groups. Bifidobacterium abundance was positively correlated with distance walked in the 6-min walk test and hand grip strength. At 6 months, there was a significant separation of serum metabolites between groups with upregulation of phenylalanine and tyrosine metabolism with prebiotic. CONCLUSION: Prebiotics may hold promise for conservative management of knee osteoarthritis in adults with obesity and larger trials are warranted. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov/study/NCT04172688.

The association between blood biological age at rehabilitation admission and physical activity during rehabilitation in geriatric inpatients: RESORT.

Geriatric rehabilitation inpatients have high levels of sedentary behaviour (SB) and low levels of physical activity (PA). Biological age predicted by blood biomarkers is indicative of adverse outcomes. The objective was to determine the association between blood biological age at rehabilitation admission and levels of SB and PA during rehabilitation in geriatric inpatients. Inpatients admitted to geriatric rehabilitation wards at the Royal Melbourne Hospital (Melbourne, Australia) from October 22, 2019, to March 29, 2020, in the REStORing health of acute unwell adulTs (RESORT) observational cohort were included. Blood biological age was predicted using SenoClock-BloodAge, a hematological ageing clock. Patients wore an inertial sensor to measure SB and PA. Logistic regression analyses were conducted. A total of 111 patients (57.7% female) with mean age 83.3 ± 7.5 years were included in the analysis. The mean blood biological age was 82.7 ± 8.4 years. Patients with 1-year higher blood biological age had higher odds of having high SB measured as non-upright time greater than 23 h/day (odds ratio (OR): 1.050, 95% confidence interval (CI): 1.000-1.102). Individuals having 1-year higher age deviation trended towards lower odds of having high levels of PA measured as stepping time greater than 7.4 min/day (OR: 0.916, CI: 0.836-1.005) and as greater than 19.5 sit-to-stand transitions/day (OR: 0.915, CI: 0.836-1.002). In conclusion, higher biological age was associated with higher levels of SB and trended towards lower PA. Incorporating blood biological age could facilitate resource allocation and the development of more tailored rehabilitation plans.

Towards personalized nicotinamide mononucleotide (NMN) supplementation: Nicotinamide adenine dinucleotide (NAD) concentration.

Nicotinamide mononucleotide (NMN) is a precursor of nicotinamide adenine dinucleotide (NAD), which declines with age. Supplementation of NMN has been shown to improve blood NAD concentration. However, the optimal NMN dose remains unclear. This is a post-hoc analysis of a double-blinded clinical trial involving 80 generally healthy adults aged 40-65 years. The participants received a placebo or daily 300 mg, 600 mg, or 900 mg NMN for 60 days. Blood NAD concentration, blood biological age, homeostatic model assessment for insulin resistance, 6-minute walk test, and 36-item short-form survey (SF-36) were measured at baseline and after supplement. A significant dose-dependent increase in NAD concentration change (NADΔ) was observed following NMN supplementation, with a large coefficient of variation (29.2-113.3%) within group. The increase in NADΔ was associated with an improvement in the walking distance of 6-minute walk test and the SF-36 score. The median effect dose of NADΔ for the 6-minute walk test and SF-36 score was 15.7 nmol/L (95% CI: 10.9-20.5 nmol/L) and 13.5 nmol/L (95% CI; 10.5-16.5 nmol/L), respectively. Because of the high interindividual variability of the NADΔ after NMN supplementation, monitoring NAD concentration can provide valuable insights for tailoring personalized dosage regimens and optimizing NMN utilization.

Protocol for nutritional intervention in neonatal rats using the "pup-in-a-cup" artificial rearing system.

Early-life nutrition fundamentally influences newborn development and health. Here, we present a protocol for nutritional intervention in neonatal rats using the "pup-in-a-cup" artificial rearing system. We describe steps for rat milk substitute preparation, cheek cannulation and maintenance, and nutritional manipulation during the suckling period. This protocol enables investigation into the role of nutritional factors in newborns by artificially rearing rats away from the mother with experimental diets starting at postnatal day 4 for up to 18 days. For complete details on the use and execution of this protocol, please refer to Wang et al.,1 Choudhary et al.,2 and Mu et al.3,4.

CK1δ/ε inhibition induces ULK1-mediated autophagy in tumorigenesis.

INTRODUCTION: Autophagy is an important mechanism of cell homeostasis maintenance. As essential serine/threonine-protein kinases, casein kinase I family members affect tumorigenesis by regulating a variety of cellular progression. However, the mechanism by which they regulate autophagy remains unclear. MATERIALS AND METHODS: We silenced CK1δ/ε in cancer cells and observed cell morphology, the expression of autophagy-related genes, and its impact on cancer cell growth and viability. By inhibiting CK1δ/ε-induced upregulation of autophagy genes, we profiled the regulatory mechanism of CK1δ/ε on autophagy and cancer cell growth. The impact of CK1δ/ε inhibition on tumor cell growth was also assessed in vivo. RESULTS: Here, we found that CK1δ/ε played an important role in ULK1-mediated autophagy regulation in both lung cancer and melanoma cells. Mechanically, silencing CK1δ/ε increased ULK1 expression with enhanced autophagic flux and suppressed cancer cell proliferation, while ULK1 knockdown blocked the activation of autophagy caused by CK1δ/ε inhibition. By silencing CK1δ/ε in syngeneic mouse model bearing LLC1 murine lung cancer cells in vivo, we observed tumor growth suppression mediated by CK1δ/ε inhibition. CONCLUSION: Our results provide evidence for the role of CK1δ/ε in the regulation of tumorigenesis via the ULK1-mediated autophagy, and also suggest the impact of CK1δ/ε inhibition on tumor growth and its significance as a potential therapeutic target.

Integrated transcriptomics, proteomics, and functional analysis to characterize the tissue-specific small extracellular vesicle network of breast cancer.

Small extracellular vesicles (sEVs) are essential mediators of intercellular communication within the tumor microenvironment (TME). Although the biological features of sEVs have been characterized based on in vitro culture models, recent evidence indicates significant differences between sEVs derived from tissue and those derived from in vitro models in terms of both content and biological function. However, comprehensive comparisons and functional analyses are still limited. Here, we collected sEVs from breast cancer tissues (T-sEVs), paired normal tissues (N-sEVs), corresponding plasma (B-sEVs), and tumor organoids (O-sEVs) to characterize their transcriptomic and proteomic profiles. We identified the actual cancer-specific sEV signatures characterized by enriched cell adhesion and immunomodulatory molecules. Furthermore, we revealed the significant contribution of cancer-associated fibroblasts in the sEV network within the TME. In vitro model-derived sEVs did not entirely inherit the extracellular matrix- and immunity regulation-related features of T-sEVs. Also, we demonstrated the greater immunostimulatory ability of T-sEVs on macrophages and CD8+ T cells compared to O-sEVs. Moreover, certain sEV biomarkers derived from noncancer cells in the circulation exhibited promising diagnostic potential. This study provides valuable insights into the functional characteristics of tumor tissue-derived sEVs, highlighting their potential as diagnostic markers and therapeutic agents for breast cancer.

Ficus carica polysaccharide extraction via ultrasound-assisted technique: Structure characterization, antioxidant, hypoglycemic and immunomodulatory activities.

In this research, the ultrasound-assisted extraction (UAE) conditions of the water-soluble polysaccharide (FCPS) from Ficus carica fruits were optimized using the response surface methodology. The optimal FCPS yield was 7.97 % achieved by conducting ultrasound-assisted extraction four times at a solid-liquid ratio of 1:20 (g/mL) and an ultrasound temperature of 70 °C. Then, the structure, antioxidant properties, hypoglycemic effects, and immunomodulatory activities of FCPS were evaluated. FCPS was characterized as irregular, rough-surfaced, flaky materials consisting of pyran-type polysaccharides with α- and ß-glycosidic linkages, and composed of multiple monosaccharides and only one homogeneous concentrated polysaccharide component (FCPS1) with a molecular weight of 4.224 × 104 Da. The results suggested FCPS exhibited remarkable antioxidant activity in vitro, as evidenced by improved cell viability and reduced the reactive oxygen species (ROS) levels. Meanwhile, FCPS effectively improved liver-related insulin resistance by promoting glucose consumption in hepatocytes and activated the immune response through activation of murine bone marrow-derived dendritic cells (DCs) and upregulation of interleukin 6 (IL6) and interleukin 12 (IL-12) expression. The findings demonstrate the efficacy of the UAE technique in isolating FCPS with biological functionality and FCPS could potentially serve as a beneficial organic antioxidant source and functional food, carrying important implications for future studies.

Quality variation and biosynthesis of anti-inflammatory compounds for Capparis spinosa based on the metabolome and transcriptome analysis.

Introduction: Capparis spinosa L. fruits as edible and medicinal plant, has anti-inflammatory activities. The different morphological characteristics of C. spinosa fruits from Ili, Turpan, and Karamay may affect their anti-inflammatory components and functions. Methods: The anti-inflammatory activity of C. spinosa fruit was assessed using an LPS-induced inflammatory cell model. Furthermore, the differences in anti-inflammatory compounds were analyzed by metabolome and RNA-seq. Additionally, the anti-inflammatory mechanism was elucidated using network pharmacology. Results: In the study, we found that the 95% ethanol extracts (CSE) obtained from the three kinds of fruits showed remarkable anti-inflammatory effects both in vivo and in vitro. However, the CSE derived from Ili fruits significantly reduced CD86 levels on DCs. As a result of metabolomic analysis, the metabolic profiles of Ili fruits differed significantly from those of the other two habitats, which were consistent with transcriptome analysis. A total of 15 compounds exhibiting anti-inflammatory activity were subjected to screening, revealing a greater accumulation of flavonoids in the Turpan and Karamay districts. Notably, phenolic compounds were identified as the principal anti-inflammatory components in C. spinosa. Conclusion: There were significant differences in the morphology, metabolites, transcriptional levels, and anti-inflammatory activity of C. spinosa from the three districts.

Predicting oral cancer survival-Development and validation of an Asia-Pacific nomogram.

BACKGROUND: Nomograms are graphical calculating devices that predict response to treatment during cancer management. Oral squamous cell carcinoma (OSCC) is a lethal and deforming disease of rising incidence and global significance. The aim of this study was to develop a nomogram to predict individualized OSCC survival using a population-based dataset obtained from Queensland, Australia and externally validated using a cohort of OSCC patients treated in Hong Kong. METHODS: Clinico-pathological data for newly diagnosed OSCC patients, including age, sex, tumour site and grading, were accessed retrospectively from the Queensland Cancer Registry (QCR) in Australia and the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong. Multivariate Cox proportional hazard regression was used to construct overall survival (OS) and cancer-specific survival (CSS) prediction models. Nomograms were internally validated using 10-fold cross validation, and externally validated against the Hong Kong dataset. RESULTS: Data from 9885 OSCC patients in Queensland and 465 patients from Hong Kong were analysed. All clinico-pathological variables significantly influenced survival outcomes. Nomogram calibration curves demonstrated excellent agreement between predicted and actual probability for Queensland patients. External validation in the Hong Kong population demonstrated slightly poorer nomogram performance, but predictive power remained strong. CONCLUSION: Based upon readily available data documenting patient demographic and clinico-pathological variables, predictive nomograms offer pragmatic aid to clinicians in individualized treatment planning and prognosis assessment in contemporary OSCC management.

Deep Learning Identifies Intelligible Predictors of Poor Prognosis in Chronic Kidney Disease.

Early diagnosis and prediction of chronic kidney disease (CKD) progress within a given duration are critical to ensure personalized treatment, which could improve patients' quality of life and prolong survival time. In this study, we explore the intelligibility of machine-learning and deep-learning models on end-stage renal disease (ESRD) prediction, based on readily-accessible clinical and laboratory features of patients suffering from CKD. Eight machine learning models were used to predict whether a patient suffering from CKD would progress to ESRD within three years based on demographics, clinical,and comorbidity information. LASSO, random forest, and XGBoost were used to identify the most significant markers. In addition, we introduced four advanced attribution methods to the deep learning model to enhance model intelligibility. The deep learning model achieved an AUC-ROC of 0.8991, which was significantly higher than that of baseline models. The interpretation generated by deep learning with attribution methods, random forest, and XGBoost was consistent with clinical knowledge, whereas LASSO-based interpretation was inconsistent. Hematuria, proteinuria, potassium, urine albumin to creatinine ratio were positively associated with the progression of CKD, while eGFR and urine creatinine were negatively associated. In conclusion, deep learning with attribution algorithms could identify intelligible features of CKD progression. Our model identified a number of critical, but under-reported features, which may be novel markers for CKD progression. This study provides physicians with solid data-driven evidence for using machine learning for CKD clinical management and treatment.

Characterization of the Glucan-Branching Enzyme GlgB Gene from Swine Intestinal Bacteria.

Starch hydrolysis by gut microbiota involves a diverse range of different enzymatic activities. Glucan-branching enzyme GlgB was identified as the most abundant glycosidase in Firmicutes in the swine intestine. GlgB converts α-(1→4)-linked amylose to form α-(1→4,6) branching points. This study aimed to characterize GlgB cloned from a swine intestinal metagenome and to investigate its potential role in formation of α-(1→4,6)-branched α-glucans from starch. The branching activity of purified GlgB was determined with six different starches and pure amylose by quantification of amylose after treatment. GlgB reduced the amylose content of all 6 starches and amylose by more than 85% and displayed a higher preference towards amylose. The observed activity on raw starch indicated a potential role in the primary starch degradation in the large intestine as an enzyme that solubilizes amylose. The oligosaccharide profile showed an increased concentration of oligosaccharide introduced by GlgB that is not hydrolyzed by intestinal enzymes. This corresponded to a reduced in vitro starch digestibility when compared to untreated starch. The study improves our understanding of colonic starch fermentation and may allow starch conversion to produce food products with reduced digestibility and improved quality.

Characteristics of Maternal Mortality Missed by Vital Statistics in Hong Kong, 2000-2019.

Importance: Reducing maternal mortality is a global objective. The maternal mortality ratio (MMR) is low in Hong Kong, China, but there has been no local confidential enquiry into maternal death, and underreporting is likely. Objective: To determine the causes and timing of maternal death in Hong Kong and identify deaths and their causes that were missed by the Hong Kong vital statistics database. Design, Setting, and Participants: This cross-sectional study was conducted among all 8 public maternity hospitals in Hong Kong. Maternal deaths were identified using prespecified search criteria, including a registered delivery episode between 2000 to 2019 and a registered death episode within 365 days after delivery. Cases as reported by the vital statistics were then compared with the deaths found in the hospital-based cohort. Data were analyzed from June to July 2022. Main Outcomes and Measures: The outcomes of interest were maternal mortality, defined as death during pregnancy or within 42 days after ending the pregnancy, and late maternal death, defined as death more than 42 days but less than 1 year after end of the pregnancy. Results: A total of 173 maternal deaths (median [IQR] age at childbirth, 33 [29-36] years) were found, including 74 maternal mortality events (45 direct deaths and 29 indirect deaths) and 99 late maternal deaths. Of 173 maternal deaths, 66 women (38.2%) of individuals had preexisting medical conditions. For maternal mortality, the MMR ranged from 1.63 to 16.78 deaths per 100 000 live births. Suicide was the leading cause of direct death (15 of 45 deaths [33.3%]). Stroke and cancer deaths were the most common causes of indirect death (8 of 29 deaths [27.6%] each). A total of 63 individuals (85.1%) died during the postpartum period. In the theme-based approach analysis, the leading causes of death were suicide (15 of 74 deaths [20.3%]) and hypertensive disorders (10 of 74 deaths [13.5%]). The vital statistics in Hong Kong missed 67 maternal mortality events (90.5%). All suicides and amniotic fluid embolisms, 90.0% of hypertensive disorders, 50.0% of obstetric hemorrhages, and 96.6% of indirect deaths were missed by the vital statistics. The late maternal death ratio ranged from 0 to 16.36 deaths per 100 000 live births. The leading causes of late maternal death were cancer (40 of 99 deaths [40.4%]) and suicide (22 of 99 deaths [22.2%]). Conclusions and Relevance: In this cross-sectional study of maternal mortality in Hong Kong, suicide and hypertensive disorder were the dominant causes of death. The current vital statistics methods were unable to capture most of the maternal mortality events found in this hospital-based cohort. Adding a pregnancy checkbox to death certificates and setting up a confidential enquiry into maternal death could be possible solutions to reveal the hidden deaths.

HUTNet: An Efficient Convolutional Neural Network for Handwritten Uchen Tibetan Character Recognition.

Recognition of handwritten Uchen Tibetan characters input has been considered an efficient way of acquiring mass data in the digital era. However, it still faces considerable challenges due to seriously touching letters and various morphological features of identical characters. Thus, deeper neural networks are required to achieve decent recognition accuracy, making an efficient, lightweight model design important to balance the inevitable trade-off between accuracy and latency. To reduce the learnable parameters of the network as much as possible and maintain acceptable accuracy, we introduce an efficient model named HUTNet based on the internal relationship between floating-point operations per second (FLOPs) and Memory Access Cost. The proposed network achieves a ResNet-18-level accuracy of 96.86%, with only a tenth of the parameters. The subsequent pruning and knowledge distillation strategies were applied to further reduce the inference latency of the model. Experiments on the test set (Handwritten Uchen Tibetan Data set by Wang [HUTDW]) containing 562 classes of 42,068 samples show that the compressed model achieves a 96.83% accuracy while maintaining lower FLOPs and fewer parameters. To verify the effectiveness of HUTNet, we tested it on the Chinese Handwriting Data sets Handwriting Database 1.1 (HWDB1.1), in which HUTNet achieved an accuracy of 97.24%, higher than that of ResNet-18 and ResNet-34. In general, we conduct extensive experiments on resource and accuracy trade-offs and show a stronger performance compared with other famous models on HUTDW and HWDB1.1. It also unlocks the critical bottleneck for handwritten Uchen Tibetan recognition on low-power computing devices.

Clinical presentation, investigation, underlying causes, and subsequent pregnancy outcomes among different phenotypes of second trimester miscarriage.

AIM: To evaluate the causes of miscarriage and subsequent pregnancy outcomes among different phenotypes of second trimester miscarriage. METHODS: Retrospective analysis of 170 consecutive second trimester miscarriages between 14 + 0 and 23 + 6 weeks recorded in the Clinical Data Analysis and Reporting System from 2012 to 2021. Cases were excluded if miscarriages occurred before 14 + 0 weeks of gestation, data were incomplete, or passage of the fetus happened before the clinical assessment. Cases were classified with a stepwise approach into three phenotypic groups including silent miscarriages (ST-SM), rupture of membranes (ST-ROM), and inevitable miscarriages (ST-IM) depending on the fetal heart pulsation and leakage of liquor at presentation. Clinical investigation of the underlying causes and the outcome of the subsequent pregnancy was then reviewed. RESULTS: There were 97 cases of ST-SM, 21 cases of ST-ROM, and 52 cases of ST-IM. Placental histology and karyotype examination were more likely to yield significant results in the cases of ST-ROM and ST-SM (p < 0.05). The phenotypic examination identified different underlying causes including fetal anomaly, suspected cervical insufficiency, diabetes mellitus, and unknown causes (p < 0.001). Sixty-four cases achieved a subsequent pregnancy. Although women with history of ST-ROM and ST-IM received more cervical length monitoring and cervical cerclage than those with ST-SM (66.7% vs. 44.4% vs. 7.5%, p = 0.0002; and 16.7% vs. 22.2% vs. 2.5%, p = 0.031, respectively), the risk of recurrent second trimester miscarriage was higher in ST-ROM and ST-IM than in ST-SM (16.7% vs. 0%, p = 0.018). CONCLUSION: The classification can differentiate different second trimester miscarriage phenotypes, which offers essential information to guide investigation panels of the underlying cause of miscarriages, and the prognosis and management of subsequent pregnancy. Future researches focused on second trimester miscarriage should report their findings according to different phenotypes.

Predicting Acute Onset of Heart Failure Complicating Acute Coronary Syndrome: An Explainable Machine Learning Approach.

Patients with acute coronary syndrome (ACS) are at high risk of heart failure (HF). Early prediction and management of HF among ACS patients are essential to provide timely and cost-effective care. The aim of this study is to train and evaluate a machine learning model to predict the acute onset of HF subsequent to ACS. A total of 1,028 patients with ACS admitted to Guangdong Second Provincial General Hospital between October 2019 and May 2022 were included in this study. 128 clinical features were ranked using Shapley additive exPlanations (SHAP) values and the top 20% of features were selected for building a balanced random forest (BRF) model. We compared the discriminatory capability of BRF with linear logistic regression (LLR). In the hold-out test set, the BRF model predicted subsequent HF with areas under the curve (AUC) of 0.76 (95% CI: 0.75-0.77), sensitivity of 0.97 (95% CI: 0.96-0.97), positive predictive value (PPV) of 0.73 (95% CI: 0.72-0.74), negative predictive value (NPV) of 0.63 (95% CI: 0.60-0.66), and accuracy of 0.73 (95% CI: 0.72-0.73), respectively. BRF outperforms linear logistic regression by 15.6% in AUC, 3.0% in sensitivity, and 60.8% in NPV. End-to-end machine learning approaches can predict the acute onset of HF following ACS with high prediction accuracy. This proof-of-concept study has the potential to substantially advance the management of ACS patients by utilizing the machine learning model as a triage tool to automatically identify clinically significant patients allowing for prioritization of interventions.

Cistanche tubulosa phenylethanoid glycosides suppressed adipogenesis in 3T3-L1 adipocytes and improved obesity and insulin resistance in high-fat diet induced obese mice.

BACKGROUND: Cistanche tubulosa is an editable and medicinal traditional Chinese herb and phenylethanoid glycosides are its major components, which have shown various beneficial effects such as anti-tumor, anti-oxidant and neuroprotective activities. However, the anti-obesity effect of C. tubulosa phenylethanoid glycosides (CTPG) and their regulatory effect on gut microbiota are still unclear. In the present study, we investigated its anti-obesity effect and regulatory effect on gut microbiota by 3T3-L1 cell model and obesity mouse model. METHODS: 3T3-L1 adipocytes were used to evaluate CTPG effects on adipogenesis and lipids accumulation. Insulin resistant 3T3-L1 cells were induced and used to measure CTPG effects on glucose consumption and insulin sensitivity. High-fat diet (HFD)-induced C57BL/6 obese mice were used to investigate CTPG effects on fat deposition, glucose and lipid metabolism, insulin resistance and intestinal microorganism. RESULTS: In vitro data showed that CTPG significantly decreased the triglyceride (TG) and non-esterified fatty acid (NEFA) contents of the differentiated 3T3-L1 adipocytes in a concentration-dependent manner without cytotoxicity, and high concentration (100 µg/ml) of CTPG treatment dramatically suppressed the level of monocyte chemoattractant protein-1 (MCP-1) in 3T3-L1 mature adipocytes. Meanwhile, CTPG increased glucose consumption and decreased NEFA level in insulin resistant 3T3-L1 cells. We further found that CTPG protected mice from the development of obesity by inhibiting the expansion of adipose tissue and adipocyte hypertrophy, and improved hepatic steatosis by activating AMPKα to reduce hepatic fat accumulation. CTPG ameliorated HFD-induced hyperinsulinemia, hyperglycemia, inflammation and insulin resistance by activating IRS1/Akt/GLUT4 insulin signaling pathway in white adipose tissue. Moreover, gut microbiota structure and metabolic functions in HFD-induced obese mice was changed by CTPG, especially short chain fatty acids-producing bacteria including Blautia, Roseburia, Butyrivibrio and Bacteriodes were significantly increased by CTPG treatment. CONCLUSIONS: CTPG effectively suppressed adipogenesis and lipid accumulation in 3T3-L1 adipocytes and ameliorated HFD-induced obesity and insulin resistance through activating AMPKα and IRS1/AKT/GLUT4 signaling pathway and regulating the composition and metabolic functions of gut microbiota.

[Hepatic Insulin Resistance and Type 2 Diabetes Mellitus].

Insulin resistance (IR) is a pathological reaction of hyperinsulinemia and impaired glucose tolerance caused by decreased sensitivity of target tissues such as liver to insulin.The pathogenesis of IR as a typical pathological feature of type 2 diabetes is the focus of anti-diabetes research.In this paper,we reviewed the molecular mechanisms of glucose and lipid metabolism,oxidative stress,mitochondrial dysfunction,endoplasmic reticulum stress,inflammation,and hepatic IR in the case of type 2 diabetes mellitus,which might provide new ideas and theoretical guidance for the treatment of diabetes mellitus.

Relationship between viral load and pregnancy outcomes among hepatitis B carriers.

OBJECTIVE: Pregnant hepatitis B carriers may have a higher risk of adverse pregnancy outcomes. Current evidences are conflicting regarding the relationship between hepatitis B virus (HBV) and various pregnancy complications, owing to the inclusion of women with different viral activity. This study is to evaluate the relationship between hepatitis B e antigen (HBeAg) status/HBV DNA level and pregnancy outcomes among pregnant hepatitis B carriers in Hong Kong. MATERIALS AND METHODS: This was a retrospective analysis of a prospective multicenter observational study carried out in Hong Kong between 2014 and 2016. Pregnant HBV carriers were recruited. HBeAg was tested. HBV DNA level was quantified at 28-30 weeks of gestation. The rates of gestational diabetes mellitus (GDM), gestational hypertension, pre-eclampsia, preterm prelabour rupture of membranes (PPROM), preterm birth, low birth weight (LBW), macrosomia and mode of delivery were recorded. RESULTS: 679 pregnancies were analyzed. 23.3% of women were seropositive for HBeAg. The mean viral load (SD) at 28-30 weeks of gestation was 3.6 (2.5) log10IU/ml. No statistically significant differences were found in the rates of GDM, gestational hypertension, pre-eclampsia, PPROM, preterm birth, LBW, macrosomia and mode of delivery among women with different viral load levels (≤2 log10IU/ml, 2.01-6 log10IU/ml and >6 log10IU/ml). Positive maternal HBeAg status was not associated with pregnancy complications compared to seronegative women. CONCLUSION: Seropositive HBeAg status or a higher level of HBV DNA during pregnancy did not pose a significant negative impact to the pregnancy outcomes.

Trend and causes of maternal death, stillbirth and neonatal death over seven decades in Hong Kong.

Background: Reducing maternal and perinatal mortality is a global objective. Hong Kong is a city with low maternal and perinatal mortality but little is known about the trend and causes of these deaths in this high-income city. We analyzed the maternal death, stillbirth and neonatal death since 1946 in Hong Kong. Methods: Data were extracted from vital statistics, based on the number of registered deaths and births, provided by the Department of Health, the Government of the HKSAR. The annual change rate of mortality was evaluated by regression analysis. Contextual factors were collected to assess the association with mortality. Findings: Between 1946 and 2017, the stillbirth rate (per 1,000 total births) reduced from 21·5 to 2·4; early and late neonatal deaths (per 1,000 live births) reduced from 14·1 and 18·1 to 0·7 and 0·4 in 2017, respectively. The maternal mortality ratio (per 100,000 live births) declined from 125 to 1·8.The causes of maternal and perinatal deaths were available since 1981 and 1980 respectively. The leading causes of death were thromboembolism (37·0%) and obstetric haemorrhage (30·4%) for maternal death; congenital problem (30·1%) and prematurity (29·0%) for neonatal death. No data on causes of stillbirth were available. No specific shift of pattern was observed in the causes of maternal and neonatal death with time. There were no cases of maternal death due to sepsis and only 2 cases (2·2%) of maternal deaths due to indirect cause. Interpretation: The maternal and perinatal death have reduced significantly in Hong Kong and maintained at the lowest level globally. Indirect maternal death and sepsis were unusual causes of maternal deaths. Use of ICD-PM stillbirth classification, setting up a maternal death confidential enquiry and adding pregnancy checkbox could be the next step to identify and categorize hidden burden. Funding: Nil.

Exercise and Prebiotic Fiber Provide Gut Microbiota-Driven Benefit in a Survivor to Germ-Free Mouse Translational Model of Breast Cancer.

The gut microbiota plays a role in shaping overall host health and response to several cancer treatments. Factors, such as diet, exercise, and chemotherapy, can alter the gut microbiota. In the present study, the Alberta Cancer Exercise (ACE) program was investigated as a strategy to favorably modify the gut microbiota of breast cancer survivors who had received chemotherapy. Subsequently, the ability of post-exercise gut microbiota, alone or with prebiotic fiber supplementation, to influence breast cancer outcomes was interrogated using fecal microbiota transplant (FMT) in germ-free mice. While cancer survivors experienced little gut microbial change following ACE, in the mice, tumor volume trended consistently lower over time in mice colonized with post-exercise compared to pre-exercise microbiota with significant differences on days 16 and 22. Beta diversity analysis revealed that EO771 breast tumor cell injection and Paclitaxel chemotherapy altered the gut microbial communities in mice. Enrichment of potentially protective microbes was found in post-exercise microbiota groups. Tumors of mice colonized with post-exercise microbiota exhibited more favorable cytokine profiles, including decreased vascular endothelial growth factor (VEGF) levels. Beneficial microbial and molecular outcomes were augmented with prebiotic supplementation. Exercise and prebiotic fiber demonstrated adjuvant action, potentially via an enhanced anti-tumor immune response modulated by advantageous gut microbial shifts.