Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach.

Enhancement of cellulolytic enzyme production from intrageneric protoplast fusion of Aspergillus species and evaluating the hydrolysate scavenging activity.

BACKGROUND: Lignocellulosic biomass provides a great starting point for the production of energy, chemicals, and fuels. The major component of lignocellulosic biomass is cellulose, the employment of highly effective enzymatic cocktails, which can be produced by a variety of microorganisms including species of the genus Aspergillus, is necessary for its utilization in a more productive manner. In this regard, molecular biology techniques should be utilized to promote the economics of enzyme production, whereas strategies like protoplast fusion could be employed to improve the efficacy of the hydrolytic process. RESULTS: The current study focuses on cellulase production in Aspergillus species using intrageneric protoplast fusion, statistical optimization of growth parameters, and determination of antioxidant activity of fermentation hydrolysate. Protoplast fusion was conducted between A. flavus X A. terreus (PFFT), A. nidulans X A. tamarii (PFNT) and A. oryzae X A. tubingensis (PFOT), and the resultant fusant PFNT revealed higher activity level compared with the other fusants. Thus, this study aimed to optimize lignocellulosic wastes-based medium for cellulase production by Aspergillus spp. fusant (PFNT) and studying the antioxidant effect of fermentation hydrolysate. The experimental strategy Plackett-Burman (PBD) was used to assess how culture conditions affected cellulase output, the best level of the three major variables namely, SCB, pH, and incubation temperature were then determined using Box-Behnken design (BBD). Consequently, by utilizing an optimized medium instead of a basal medium, cellulase activity increased from 3.11 U/ml to 7.689 U/ml CMCase. The following medium composition was thought to be ideal based on this optimization: sugarcane bagasse (SCB), 6.82 gm; wheat bran (WB), 4; Moisture, 80%; pH, 4; inoculum size, (3 × 106 spores/ml); and incubation Temp. 31.8 °C for 4 days and the fermentation hydrolysate has 28.13% scavenging activities. CONCLUSION: The results obtained in this study demonstrated the significant activity of the selected fusant and the higher sugar yield from cellulose hydrolysis over its parental strains, suggesting the possibility of enhancing cellulase activity by protoplast fusion using an experimental strategy and the fermentation hydrolysate showed antioxidant activity.

Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network.

In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasible to fit or produce low prediction accuracy due to overfitting. To address this issue, the focus has shifted towards introducing a novel approaches for feature selection and survival prediction. In this article, we propose a new hybrid feature selection approach that handles high-dimensional bioinformatics datasets for improved survival prediction. This study explores the efficacy of four distinct variable selection techniques: LASSO, RSF-vs, SCAD, and CoxBoost, in the context of non-parametric biomedical survival prediction. Leveraging these methods, we conducted comprehensive variable selection processes. Subsequently, survival analysis models-specifically CoxPH, RSF, and DeepHit NN-were employed to construct predictive models based on the selected variables. Furthermore, we introduce a novel approach wherein only variables consistently selected by a majority of the aforementioned feature selection techniques are considered. This innovative strategy, referred to as the proposed method, aims to enhance the reliability and robustness of variable selection, subsequently improving the predictive performance of the survival analysis models. To evaluate the effectiveness of the proposed method, we compare the performance of the proposed approach with the existing LASSO, RSF-vs, SCAD, and CoxBoost techniques using various performance metrics including integrated brier score (IBS), concordance index (C-Index) and integrated absolute error (IAE) for numerous high-dimensional survival datasets. The real data applications reveal that the proposed method outperforms the competing methods in terms of survival prediction accuracy.

Hesperetin protects against rotenone-induced motor disability and neurotoxicity via the regulation of SIRT1/NLRP3 signaling.

Rotenone is a pesticide that causes complex I inhibition and is widely known to induce motor disability and experimental Parkinson's disease (PD) in rodents. Evidence suggests a crucial role for sirtuin/nuclear factor-kappaB/nod-like receptor family, pyrin domain-containing 3 (SIRT1/NFκB/NLRP3) signaling and inflammation in PD and rotenone neurotoxicity. Hesperetin (C16H14O6) is a citrus flavonoid with documented anti-inflammatory activity. We investigated the value of hesperetin in delaying rotenone-induced PD in mice and the possible modulation of inflammatory burden. PD was induced in mice via rotenone injections. Groups were assigned as a vehicle, PD, or PD + hesperetin (50 or 100 mg/kg) and compared for the motor function, protein level (by ELISA), and gene expression (by real-time PCR) of the target proteins, histopathology, and immunohistochemistry for tyrosine hydroxylase enzyme. Hesperetin (50 or 100 mg/kg) alleviated the motor disability and the striatal dopamine level and decreased the expression of NLRP3 and NF-κB but increased SIRT1 expression (p < 0.05). Further, it enhanced the neural viability and significantly decreased neural degeneration in the substantia nigra, hippocampus, and cerebral cortex (p < 0.05). Taken together, we propose that hesperetin mediates its neuroprotective function via alleviating modulation of the SIRT1/NFκB/NLRP3 pathway. Therefore, hesperetin might delay the PD progression.

Trajectories of dietary patterns from pregnancy to 12 years post-pregnancy and associated maternal characteristics: evidence from the Avon Longitudinal Study of Parents and Children.

PURPOSE: Dietary patterns (DPs) during pregnancy have been well researched. However, little is known about maternal diet after pregnancy. The aim of the study was to explore maternal DPs longitudinally, examine trajectories over 12 years after pregnancy and identify associated factors. METHODS: Of 14,541 pregnant women enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) complete dietary information was available for 5336 women. Principal components analysis (PCA) was used to derive DPs. DP scores at each time point were used to create DP trajectories using group-based trajectory modelling (GBTM). Multinomial logistic regression assessed the association with maternal factors. RESULTS: A total of six distinct DPs were identified over time with different numbers of DPs at each time point. The "healthy" and "processed" DPs persisted over the 12-year post-pregnancy. Three trajectories of "healthy" and "processed" DPs were identified from GBTM. Half the women were on the moderately healthy DP trajectory with 37% on the lower trajectory and 9% on the higher healthy DP trajectory. 59% of women were on the lower processed DP trajectory with 38% on the moderate trajectory and 3.3% on the higher processed DP trajectory. Low educational attainment, low social class and smoking in pregnancy were independently associated with being on a less favourable DP trajectory over the 12 years. CONCLUSION: Health professionals should provide support on smoking cessation along with healthy eating advice during ante-natal counselling. Continued support on eating healthily after pregnancy would be beneficial for mothers and families.

A Review of the Impact of Pharmacogenetics and Metabolomics on the Efficacy of Metformin in Type 2 Diabetes.

Metformin is the most often prescribed drug for people with type 2 diabetes (T2D). More than 120 million patients with T2D use metformin worldwide. However, monotherapy fails to achieve glycemic control in a third of the treated patients. Genetics contribute to some of the inter-individual variations in glycemic response to metformin. Numerous pharmacogenetic studies have demonstrated that variations in genes related to pharmacokinetics and pharmacodynamics of metformin's encoding transporters are mainly associated with metformin response. The goal of this review is to evaluate the current state of metformin pharmacogenetics and metabolomics research, discuss the clinical and scientific issues that need to be resolved in order to increase our knowledge of patient response variability to metformin, and how to improve patient outcomes. Metformin's hydrophilic nature and absorption as well as its action mechanism and effectiveness on T2D initiation are discussed. The impacts of variations associated with various genes are analysed to identify and evaluate the effect of genetic polymorphisms on the therapeutic activity of metformin. The metabolic pattern of T2D and metformin is also indicated. This is to emphasise that studies of pharmacogenetics and metabolomics could expand our knowledge of metformin response in T2D.

Time trends, projections, and spatial distribution of low birthweight in Australia, 2009-2030: Evidence from the National Perinatal Data Collection.

INTRODUCTION: Infants with low birthweight (LBW, birthweight <2500 g) have increased in many high-resource countries over the past two decades. This study aimed to investigate the time trends, projections, and spatial distribution of LBW in Australia, 2009-2030. METHODS: We used standard aggregate data on 3 346 808 births from 2009 to 2019 from Australia's National Perinatal Data Collection. Bayesian linear regression model was used to estimate the trends in the prevalence of LBW in Australia. RESULTS: Wefound that the prevalence of LBW was 6.18% in 2009, which has increased to 6.64% in 2019 (average annual rate of change, AARC = +0.76%). If the national trend remains the same, the projected prevalence of LBW in Australia will increase to 7.34% (95% uncertainty interval, UI = 6.99, 7.68) in 2030. Observing AARC across different subpopulations, the trend of LBW was stable among Indigenous mothers, whereas it increased among non-Indigenous mothers (AARC = +0.81%). There is also an increase among the most disadvantaged mothers (AARC = +1.08%), birthing people in either of two extreme age groups (AARC = +1.99% and +1.53% for <20 years and ≥40 years, respectively), and mothers who smoked during pregnancy (AARC = +1.52%). Spatiotemporal maps showed that some of the Statistical Area level 3 (SA3) in Northern Territory and Queensland had consistently higher prevalence for LBW than the national average from 2014 to 2019. CONCLUSION: Overall, the prevalence of LBW has increased in Australia during 2009-2019; however, the trends vary across different subpopulations. If trends persist, Australia will not achieve the Sustainable Development Goals (SDGs) target of a 30% reduction in LBW by 2030. Centering and supporting the most vulnerable subpopulations is vital to progress the SDGs and improves perinatal and infant health in Australia.

Chronic Kidney Disease is Associated With Attenuated Plasma Metabolome Response to Oral Glucose Tolerance Testing.

OBJECTIVE: Chronic kidney disease (CKD) is associated with decreased anabolic response to insulin contributing to protein-energy wasting. Targeted metabolic profiling of oral glucose tolerance testing (OGTT) may help identify metabolic pathways contributing to disruptions to insulin response in CKD. METHODS: Using targeted metabolic profiling, we studied the plasma metabolome response in 41 moderate-to-severe nondiabetic CKD patients and 20 healthy controls at fasting and 2 hours after an oral glucose load. We used linear mixed modeling with random intercepts, adjusting for age, gender, race/ethnicity, body weight, and batch to assess heterogeneity in response to OGTT by CKD status. RESULTS: Mean estimated glomerular filtration rate among CKD participants was 38.9 ± 12.7 mL/min per 1.73 m2 compared to 87.2 ± 17.7 mL/min per 1.73 m2 among controls. Glucose ingestion induced an anabolic response resulting in increased glycolysis products and a reduction in a wide range of metabolites including amino acids, tricarboxylic acid cycle intermediates, and purine nucleotides compared to fasting. Participants with CKD demonstrated a blunted anabolic response to OGTT evidenced by significant changes in 13 metabolites compared to controls. The attenuated metabolome response predominant involved mitochondrial energy metabolism, vitamin B family, and purine nucleotides. Compared to controls, CKD participants had elevated lactate:pyruvate (L:P) ratio and decreased guanosine diphosphate:guanosine triphosphate ratio during OGTT. CONCLUSION: Metabolic profiling of OGTT response suggests a broad disruption of mitochondrial energy metabolism in CKD patients. These findings motivate further investigation into the impact of insulin sensitizers and mitochondrial targeted therapeutics on energy metabolism in patients with nondiabetic CKD.

Time trends and projections in the prevalence of gestational diabetes mellitus in Queensland, Australia, 2009-2030: Evidence from the Queensland Perinatal Data Collection.

BACKGROUND: Gestational diabetes mellitus (GDM) is the fastest-growing type of diabetes in Australia. We aimed to assess the time trends during 2009-2018 and projections of GDM in Queensland, Australia up to 2030. MATERIALS AND METHODS: The study data were from the Queensland Perinatal Data Collection (QPDC) and included data on 606 662 birth events with the births reported from at least 20 weeks gestational age or birth weight at least 400 g. Bayesian regression model was used to assess the trends in the prevalence of GDM. RESULTS: The prevalence of GDM increased from 5.47 to 13.62% from 2009 to 2018 (average annual rate of change, AARC = +10.71%). If the trend remains the same, the projected prevalence will increase to 42.04% (95% uncertainty interval = 34.77-48.96) by 2030. Observing AARC across different subpopulations, we found that the trend of GDM increased markedly among women living in inner regional areas (AARC = +12.49%), were non-Indigenous (AARC = +10.93%), most disadvantaged (AARC = +11.84%), aged either of two age groups (AARC = +18.45% and + 15.17% for <20 years and 20-24 years, respectively), were with obesity (AARC = +11.05%) and smoked during pregnancy (AARC = +12.26%). CONCLUSIONS: Overall, the prevalence of GDM has sharply increased in Queensland, and if this trend continues, about 42% of pregnant women will experience GDM by 2030. The trends vary across different subpopulations. Therefore, targeting the most vulnerable subpopulations is vital to prevent the development of GDM.

Cationic Surfactant-Modified Tetraselmis sp. for the Removal of Organic Dyes from Aqueous Solution.

The modification of the Tetraselmis sp. algae material (Tetra-Alg) with surfactant Cethyltrimethylammonium Bromide (CTAB) yielded adsorbent Tetra-Alg-CTAB as an adsorbent of methyl orange (MO) and methylene blue (MB) solutions. The characterization of the adsorbent used an infrared (IR) spectrometer to identify functional groups and Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDX FEI Inspect-S50, Midland, ON, Canada) to determine the surface morphology and elemental composition. Methyl orange and methylene blue adsorption on the adsorbent Tetra-Alg, Tetraselmis sp. algae-modified Na+ ions (Tetra-Alg-Na), and Tetra-Alg-CTAB were studied, including variations in pH, contact time, concentration, and reuse of adsorbents. The adsorption of MO and MB by Tetra-Alg-CTAB at pH 10, during a contact time of 90 min, and at a concentration of 250 mg L-1 resulted in MO and MB being absorbed in the amounts of 128.369 and 51.013 mg g-1, respectively. The adsorption kinetics and adsorption isotherms of MO and MB and Tetra-Alg, Tetra-Alg-Na, and Tetra-Alg-CTAB tend to follow pseudo-second-order kinetics models and Freundlich adsorption isotherms with each correlation coefficient value (R2) approaching 1. Due to the modification with the cationic surfactant CTAB, anionic dyes can be strongly sorbed in alkaline pH due to strong electrostatic attraction, while MB is more likely to involve cation exchange and hydrogen bonding. The reuse of Tetra-Alg-CTAB was carried out four times with adsorption percent > 70%, and the adsorbent was very effective in the adsorption of anionic dyes such as MO.

The Cost-Effectiveness of Intermediate-Acting, Long-Acting, Ultralong-Acting, and Biosimilar Insulins for Type 1 Diabetes Mellitus: A Systematic Review.

OBJECTIVES: The incidence of type 1 diabetes mellitus is increasing every year requiring substantial expenditure on treatment and complications. A systematic review was conducted on the cost-effectiveness of insulin formulations, including ultralong-, long-, or intermediate-acting insulin, and their biosimilar insulin equivalents. METHODS: MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, HTA, and NHS EED were searched from inception to June 11, 2021. Cost-effectiveness and cost-utility analyses were included if insulin formulations in adults (≥ 16 years) with type 1 diabetes mellitus were evaluated. Two reviewers independently screened titles, abstracts, and full-text articles, extracted study data, and appraised their quality using the Drummond 10-item checklist. Costs were converted to 2020 US dollars adjusting for inflation and purchasing power parity across currencies. RESULTS: A total of 27 studies were included. Incremental cost-effectiveness ratios ranged widely across the studies. All pairwise comparisons (11 of 11, 100%) found that ultralong-acting insulin was cost-effective compared with other long-acting insulins, including a long-acting biosimilar. Most pairwise comparisons (24 of 27, 89%) concluded that long-acting insulin was cost-effective compared with intermediate-acting insulin. Few studies compared long-acting insulins with one another. CONCLUSIONS: Long-acting insulin may be cost-effective compared with intermediate-acting insulin. Future studies should directly compare biosimilar options and long-acting insulin options and evaluate the long-term consequences of ultralong-acting insulins.

Sleep and health-related quality of life in women following a cancer diagnosis: results from the Women's Wellness after Cancer Program in Australia.

PURPOSE: Sleep disturbance after cancer treatment could compromise recovery. This paper examined the associations between post-treatment sleep problems and health-related quality of life (HRQoL), and the effectiveness of an e-enabled lifestyle intervention on sleep outcomes. METHODS: The Women's Wellness after Cancer Program (WWACP) was examined in a single blinded, multi-centre randomised controlled trial. Data were collected from 351 women (Mage = 53.2, SD = 8.8; intervention n = 175, control group n = 176) who had completed surgery, chemotherapy and/or radiotherapy for breast, gynaecological or blood cancers within the previous 24 months. Participants completed the Pittsburgh Sleep Quality Index (PSQI) at baseline (prior to intervention randomisation), and at 12 and 24 weeks later. Sociodemographic information, menopausal symptoms (Greene Climacteric Scale) and HRQoL (36-Item Short Form Health Survey; SF-36) were also collected. Linear panel regression was used to examine the association between sleep variables and SF36 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. A difference-in-difference regression model approach was used to examine the intervention effect on the sleep outcomes. RESULTS: After adjustment for potential confounders, the sleep variables (except sleep duration) significantly predicted physical, but not mental, HRQoL. There was no statistically significant effect of the intervention on sleep outcomes at 12 or 24 weeks. CONCLUSION: Women who have completed treatment for cancer experience sleep problems that are associated with decreased physical HRQoL. Improving sleep through targeted interventions should improve their physical HRQoL. Improved targeting of the sleep components of the WWACP should be explored.

Anthropometric indices of obesity as predictors of high blood pressure among school children.

BACKGROUND: Hypertension is related to increased body fat, which can be evaluated by anthropometric indicators. The aim of this study was to determine the predictive power of anthropometric indicators and to establish their cutoff points as discriminators of high blood pressure. METHODS: A cross-sectional study was conducted on 793 schoolchildren aged 10-14 years. Six anthropometric indices were used: body mass index-z-score (BMI-z-score), waist circumference (WC), waist-toheight ratio (WHtR), a body shape index (ABSI), body roundness index (BRI) and conicity index (CI). Elevated blood pressure (EBP) and hypertension (HTN) were characterized by values ≥ 90th and <95th percentile and ≥ 95th percentile for systolic and/or diastolic blood pressure, respectively. The predictive power of anthropometric indices was analyzed by sex using the receiver operating characteristic curve (ROC). RESULTS: The prevalence of EBP and HTN was 11.0% and 14.8%, respectively. According to the analyses of the ROC curve, WC provided the largest area under the curve (AUC) value, while CI showed the lowest AUC value in predicting elevated blood pressure in the total sample. The BMI z-score provided the largest area under the curve (AUC) value (0.722), followed by WHtR (0.709) and BRI (0.709), in predicting hypertension in boys. CONCLUSIONS: BMI z-score and WC may be the best predictors of EBP and BMI z-score for HTN among Jordanian schoolchildren.

Deployment Optimization Algorithms in Wireless Sensor Networks for Smart Cities: A Systematic Mapping Study.

In recent years, different types of monitoring systems have been designed for various applications, in order to turn the urban environments into smart cities. Most of these systems consist of wireless sensor networks (WSN)s, and the designing of these systems has faced many problems. The first and most important problem is sensor node deployment. The main function of WSNs is to gather the required information, process it, and send it to remote places. A large number of sensor nodes were deployed in the monitored area, so finding the best deployment algorithm that achieves maximum coverage and connectivity with the minimum number of sensor nodes is the significant point of the research. This paper provides a systematic mapping study that includes the latest recent studies, which are focused on solving the deployment problem using optimization algorithms, especially heuristic and meta-heuristic algorithms in the period (2015-2022). It was found that 35% of these studies updated the swarm optimization algorithms to solve the deployment problem. This paper will be helpful for the practitioners and researchers, in order to work out new algorithms and seek objectives for the sensor deployment. A comparison table is provided, and the basic concepts of a smart city and WSNs are presented. Finally, an overview of the challenges and open issues are illustrated.

Antibacterial Activity of Dental Composite with Ciprofloxacin Loaded Silver Nanoparticles.

Resin composites have been widely used in dental restoration. However, polymerization shrinkage and resultant bacterial microleakage are major limitations that may lead to secondary caries. To overcome this, a new type of antibacterial resin composite containing ciprofloxacin-loaded silver nanoparticles (CIP-AgNPs) were synthesized. The chemical reduction approach successfully produced CIP-AgNPs, as demonstrated by FTIR, zeta potential, scanning electron microscopy, and ultraviolet-visible (UV-vis) spectroscopy. CIP-AgNPs were added to resin composites and the antibacterial activity of the dental composite discs were realized against Enterococcus faecalis, Streptococcus mutans, and the Saliva microcosm. The biocompatibility of modified resin composites was assessed and mechanical testing of modified dental composites was also performed. The results indicated that the antibacterial activity and compressive strength of resin composites containing CIP-AgNPs were enhanced compared to the control group. They were also biocompatible when compared to resin composites containing AgNPs. In short, these results established strong ground application for CIP-AgNP-modified dental composite resins.

Hepatic transcriptional profile reveals the role of diet and genetic backgrounds on metabolic traits in female progenitor strains of the Collaborative Cross.

Mice have provided critical mechanistic understandings of clinical traits underlying metabolic syndrome (MetSyn) and susceptibility to MetSyn in mice is known to vary among inbred strains. We investigated the diet- and strain-dependent effects on metabolic traits in the eight Collaborative Cross (CC) founder strains (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Liver transcriptomics analysis showed that both atherogenic diet and host genetics have profound effects on the liver transcriptome, which may be related to differences in metabolic traits observed between strains. We found strain differences in circulating trimethylamine N-oxide (TMAO) concentration and liver triglyceride content, both of which are traits associated with metabolic diseases. Using a network approach, we identified a module of transcripts associated with TMAO and liver triglyceride content, which was enriched in functional pathways. Interrogation of the module related to metabolic traits identified NADPH oxidase 4 (Nox4), a gene for a key enzyme in the production of reactive oxygen species, which showed a strong association with plasma TMAO and liver triglyceride. Interestingly, Nox4 was identified as the highest expressed in the C57BL/6J and NZO/HILtJ strains and the lowest expressed in the CAST/EiJ strain. Based on these results, we suggest that there may be genetic variation in the contribution of Nox4 to the regulation of plasma TMAO and liver triglyceride content. In summary, we show that liver transcriptomic analysis identified diet- or strain-specific pathways for metabolic traits in the Collaborative Cross (CC) founder strains.

Comparative Efficacy and Safety of Ultra-Long-Acting, Long-Acting, Intermediate-Acting, and Biosimilar Insulins for Type 1 Diabetes Mellitus: a Systematic Review and Network Meta-Analysis.

BACKGROUND: Increasing availability of competing biosimilar alternatives makes it challenging to make treatment decisions. The purpose of this review is to evaluate the comparative efficacy and safety of ultra-long-/long-/intermediate-acting insulin products and biosimilar insulin compared to human/animal insulin in adults with type 1 diabetes mellitus (T1DM). METHODS: MEDLINE, EMBASE, CENTRAL, and grey literature were searched from inception to March 27, 2019. Randomized controlled trials (RCTs), quasi-experimental studies, and cohort studies of adults with T1DM receiving ultra-long-/long-/intermediate-acting insulin, compared to each other, as well as biosimilar insulin compared to human/animal insulin were eligible for inclusion. Two reviewers independently screened studies, abstracted data, and appraised risk-of-bias. Pairwise meta-analyses and network meta-analyses (NMA) were conducted. Summary effect measures were mean differences (MD) and odds ratios (OR). RESULTS: We included 65 unique studies examining 14,200 patients with T1DM. Both ultra-long-acting and long-acting insulin were superior to intermediate-acting insulin in reducing A1c, FPG, weight gain, and the incidence of major, serious, or nocturnal hypoglycemia. For fasting blood glucose, long-acting once a day (od) was superior to long-acting twice a day (bid) (MD - 0.44, 95% CI: - 0.81 to - 0.06) and ultra-long-acting od was superior to long-acting bid (MD - 0.73, 95% CI - 1.36 to - 0.11). For weight change, long-acting od was inferior to long-acting bid (MD 0.58, 95% CI: 0.05 to 1.10) and long-acting bid was superior to long-action biosimilar od (MD - 0.90, 95% CI: - 1.67 to - 0.12). CONCLUSIONS: Our results can be used to tailor insulin treatment according to the desired results of patients and clinicians and inform strategies to establish a competitive clinical market, address systemic barriers, expand the pool of potential suppliers, and favor insulin price reduction. PROSPERO REGISTRATION: CRD42017077051.

Use of Multiphase CT Protocols in 18 Countries: Appropriateness and Radiation Doses.

PURPOSE: To assess the frequency, appropriateness, and radiation doses associated with multiphase computed tomography (CT) protocols for routine chest and abdomen-pelvis examinations in 18 countries. MATERIALS AND METHODS: In collaboration with the International Atomic Energy Agency, multi-institutional data on clinical indications, number of scan phases, scan parameters, and radiation dose descriptors (CT dose-index volume; dose-length product [DLP]) were collected for routine chest (n = 1706 patients) and abdomen-pelvis (n = 426 patients) CT from 18 institutions in Asia, Africa, and Europe. Two radiologists scored the need for each phase based on clinical indications (1 = not indicated, 2 = probably indicated, 3 = indicated). We surveyed 11 institutions for their practice regarding single-phase and multiphase CT examinations. Data were analyzed with the Student t test. RESULTS: Most institutions use multiphase protocols for routine chest (10/18 institutions) and routine abdomen-pelvis (10/11 institutions that supplied data for abdomen-pelvis) CT examinations. Most institutions (10/11) do not modify scan parameters between different scan phases. Respective total DLP for 1-, 2-, and 3-phase routine chest CT was 272, 518, and 820 mGy·cm, respectively. Corresponding values for 1- to 5-phase routine abdomen-pelvis CT were 400, 726, 1218, 1214, and 1458 mGy cm, respectively. For multiphase CT protocols, there were no differences in scan parameters and radiation doses between different phases for either chest or abdomen-pelvis CT (P = 0.40-0.99). Multiphase CT examinations were unnecessary in 100% of routine chest CT and in 63% of routine abdomen-pelvis CT examinations. CONCLUSIONS: Multiphase scan protocols for the routine chest and abdomen-pelvis CT examinations are unnecessary, and their use increases radiation dose.

A New Generator of Probability Models: The Exponentiated Sine-G Family for Lifetime Studies.

In this article, we propose the exponentiated sine-generated family of distributions. Some important properties are demonstrated, such as the series representation of the probability density function, quantile function, moments, stress-strength reliability, and Rényi entropy. A particular member, called the exponentiated sine Weibull distribution, is highlighted; we analyze its skewness and kurtosis, moments, quantile function, residual mean and reversed mean residual life functions, order statistics, and extreme value distributions. Maximum likelihood estimation and Bayes estimation under the square error loss function are considered. Simulation studies are used to assess the techniques, and their performance gives satisfactory results as discussed by the mean square error, confidence intervals, and coverage probabilities of the estimates. The stress-strength reliability parameter of the exponentiated sine Weibull model is derived and estimated by the maximum likelihood estimation method. Also, nonparametric bootstrap techniques are used to approximate the confidence interval of the reliability parameter. A simulation is conducted to examine the mean square error, standard deviations, confidence intervals, and coverage probabilities of the reliability parameter. Finally, three real applications of the exponentiated sine Weibull model are provided. One of them considers stress-strength data.

Indole-3-lactic acid associated with Bifidobacterium-dominated microbiota significantly decreases inflammation in intestinal epithelial cells.

BACKGROUND: Bifidobacterium longum subsp. infantis (B. infantis) is a commensal bacterium that colonizes the gastrointestinal tract of breast-fed infants. B. infantis can efficiently utilize the abundant supply of oligosaccharides found in human milk (HMO) to help establish residence. We hypothesized that metabolites from B. infantis grown on HMO produce a beneficial effect on the host. RESULTS: In a previous study, we demonstrated that B. infantis routinely dominated the fecal microbiota of a breast fed Bangladeshi infant cohort (1). Characterization of the fecal metabolome of binned samples representing high and low B. infantis populations from this cohort revealed higher amounts of the tryptophan metabolite indole-3-lactic acid (ILA) in feces with high levels of B. infantis. Further in vitro analysis confirmed that B. infantis produced significantly greater quantities of the ILA when grown on HMO versus lactose, suggesting a growth substrate relationship to ILA production. The direct effects of ILA were assessed in a macrophage cell line and intestinal epithelial cell lines. ILA (1-10 mM) significantly attenuated lipopolysaccharide (LPS)-induced activation of NF-kB in macrophages. ILA significantly attenuated TNF-α- and LPS-induced increase in the pro-inflammatory cytokine IL-8 in intestinal epithelial cells. ILA increased mRNA expression of the aryl hydrogen receptor (AhR)-target gene CYP1A1 and nuclear factor erythroid 2-related factor 2 (Nrf2)-targeted genes glutathione reductase 2 (GPX2), superoxide dismutase 2 (SOD2), and NAD(P) H dehydrogenase (NQO1). Pretreatment with either the AhR antagonist or Nrf-2 antagonist inhibited the response of ILA on downstream effectors. CONCLUSIONS: These findings suggest that ILA, a predominant metabolite from B. infantis grown on HMO and elevated in infant stool high in B. infantis, and protects gut epithelial cells in culture via activation of the AhR and Nrf2 pathway.