Identification and validation of supervariants reveal novel loci associated with human white matter microstructure.

As an essential part of the central nervous system, white matter coordinates communications between different brain regions and is related to a wide range of neurodegenerative and neuropsychiatric disorders. Previous genome-wide association studies (GWASs) have uncovered loci associated with white matter microstructure. However, GWASs suffer from limited reproducibility and difficulties in detecting multi-single-nucleotide polymorphism (multi-SNP) and epistatic effects. In this study, we adopt the concept of supervariants, a combination of alleles in multiple loci, to account for potential multi-SNP effects. We perform supervariant identification and validation to identify loci associated with 22 white matter fractional anisotropy phenotypes derived from diffusion tensor imaging. To increase reproducibility, we use United Kingdom (UK) Biobank White British (n = 30,842) data for discovery and internal validation, and UK Biobank White but non-British (n = 1927) data, Europeans from the Adolescent Brain Cognitive Development study (n = 4399) data, and Europeans from the Human Connectome Project (n = 319) data for external validation. We identify 23 novel loci on the discovery set that have not been reported in the previous GWASs on white matter microstructure. Among them, three supervariants on genomic regions 5q35.1, 8p21.2, and 19q13.32 have P-values lower than 0.05 in the meta-analysis of the three independent validation data sets. These supervariants contain genetic variants located in genes that have been related to brain structures, cognitive functions, and neuropsychiatric diseases. Our findings provide a better understanding of the genetic architecture underlying white matter microstructure.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10-9 ) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10-8 ) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

Live Birth with or without Preimplantation Genetic Testing for Aneuploidy.

BACKGROUND: Embryo selection with preimplantation genetic testing for aneuploidy (PGT-A) may improve pregnancy outcomes after initial embryo transfer. However, it remains uncertain whether PGT-A improves the cumulative live-birth rate as compared with conventional in vitro fertilization (IVF). METHODS: In this multicenter, randomized, controlled trial, we randomly assigned subfertile women with three or more good-quality blastocysts to undergo either PGT-A or conventional IVF; all the women were between 20 and 37 years of age. Three blastocysts were screened by next-generation sequencing in the PGT-A group or were chosen by morphologic criteria in the conventional-IVF group and then were successively transferred one by one. The primary outcome was the cumulative live-birth rate after up to three embryo-transfer procedures within 1 year after randomization. We hypothesized that the use of PGT-A would result in a cumulative live-birth rate that was no more than 7 percentage points higher than the rate after conventional IVF, which would constitute the noninferiority margin for conventional IVF as compared with PGT-A. RESULTS: A total of 1212 patients underwent randomization, and 606 were assigned to each trial group. Live births occurred in 468 women (77.2%) in the PGT-A group and in 496 (81.8%) in the conventional-IVF group (absolute difference, -4.6 percentage points; 95% confidence interval [CI], -9.2 to -0.0; P<0.001). The cumulative frequency of clinical pregnancy loss was 8.7% and 12.6%, respectively (absolute difference, -3.9 percentage points; 95% CI, -7.5 to -0.2). The incidences of obstetrical or neonatal complications and other adverse events were similar in the two groups. CONCLUSIONS: Among women with three or more good-quality blastocysts, conventional IVF resulted in a cumulative live-birth rate that was noninferior to the rate with PGT-A. (Funded by the National Natural Science Foundation of China and others; ClinicalTrials.gov number, NCT03118141.).

iProbiotics: a machine learning platform for rapid identification of probiotic properties from whole-genome primary sequences.

Lactic acid bacteria consortia are commonly present in food, and some of these bacteria possess probiotic properties. However, discovery and experimental validation of probiotics require extensive time and effort. Therefore, it is of great interest to develop effective screening methods for identifying probiotics. Advances in sequencing technology have generated massive genomic data, enabling us to create a machine learning-based platform for such purpose in this work. This study first selected a comprehensive probiotics genome dataset from the probiotic database (PROBIO) and literature surveys. Then, k-mer (from 2 to 8) compositional analysis was performed, revealing diverse oligonucleotide composition in strain genomes and apparently more probiotic (P-) features in probiotic genomes than non-probiotic genomes. To reduce noise and improve computational efficiency, 87 376 k-mers were refined by an incremental feature selection (IFS) method, and the model achieved the maximum accuracy level at 184 core features, with a high prediction accuracy (97.77%) and area under the curve (98.00%). Functional genomic analysis using annotations from gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Rapid Annotation using Subsystem Technology (RAST) databases, as well as analysis of genes associated with host gastrointestinal survival/settlement, carbohydrate utilization, drug resistance and virulence factors, revealed that the distribution of P-features was biased toward genes/pathways related to probiotic function. Our results suggest that the role of probiotics is not determined by a single gene, but by a combination of k-mer genomic components, providing new insights into the identification and underlying mechanisms of probiotics. This work created a novel and free online bioinformatic tool, iProbiotics, which would facilitate rapid screening for probiotics.

Evaluating the probiotic effects of spraying lactiplantibacillus plantarum P-8 in neonatal piglets.

BACKGROUND: Gut microbes play an important role in the growth and health of neonatal piglets. Probiotics can promote the healthy growth of neonatal piglets by regulating their gut microbes. The study investigated the effects of spraying Lactiplantibacillus plantarum P-8 (L. plantarum P-8) fermentation broth on the growth performance and gut microbes of neonatal piglets. RESULTS: The animals were randomly divided into probiotics groups (109 neonatal piglets) and control groups (113 neonatal piglets). The probiotics group was sprayed with L. plantarum P-8 fermented liquid from 3 day before the expected date of the sow to the 7-day-old of piglets, while the control group was sprayed with equal dose of PBS. Average daily gain (ADG), immune and antioxidant status and metagenome sequencing were used to assess the changes in growth performance and gut microbiota of neonatal piglets. The results showed that L. plantarum P-8 treatment significantly improved the average daily gain (P < 0.05) of neonatal piglets. L. plantarum P-8 increased the activities of CAT and SOD but reduced the levels of IL-2 and IL-6, effectively regulating the antioxidant capacity and immunity in neonatal piglets. L. plantarum P-8 adjusted the overall structure of gut microflora improving gut homeostasis to a certain extent, and significantly increased the relative abundance of gut beneficial bacteria such as L. mucosae and L. plantarum. CONCLUSION: Spraying L. plantarum P-8 can be a feasible and effective probiotic intervention not only improving the growth of neonatal piglets, regulating the antioxidant capacity and immunity of neonatal piglets, but also improving the gut homeostasis to a certain extent.

Effects of toothpaste containing inactivated Lacticaseibacillus paracasei Probio-01 on plaque-induced gingivitis and dental plaque microbiota.

Plaque-induced gingivitis is an inflammatory response in gingival tissues resulting from bacterial plaque accumulation at the gingival margin. Postbiotics can promote the proliferation of beneficial bacteria and optimise the state of microbiota in the oral cavity. In this study, we investigated the effect of inactivated Lacticaseibacillus paracasei Probio-01 on plaque-induced gingivitis and the dental plaque microbiota. A total of 32 healthy gingival participants (Group N, using blank toothpaste for 3 months) and 60 patients with plaque-induced gingivitis (30 in Group F, using inactivated Probio-01 toothpaste for 3 months, and 30 in Group B, using blank toothpaste for 3 months, respectively) were recruited. Clinical indices, which included bleeding on probing (BOP), gingival index (GI), and plaque index (PI), were used to assess the severity of gingivitis. Furthermore, 16SrDNA amplicon sequencing was used to explore changes in the gingival state and dental plaque microbiota in patients with plaque-induced gingivitis. The results showed that inactivated Probio-01 significantly reduced clinical indices of gingivitis, including BOP, GI, and PI, in participants with plaque-induced gingivitis and effectively relieved gingival inflammation, compared with that observed in the control group (group B). Inactivated Probio-01 did not significantly influence the diversity of dental plaque microbiota, but increased the relative abundance of dental plaque core bacteria, such as Leptotrichia and Fusobacterium (P < 0.05). Strong correlations were observed between the indices and abundance of dental plaque microbiota. Overall, the inactivated Probio-01 significantly reduced the clinical indices of gingivitis and effectively improved gingival inflammation in patients with plaque-induced gingivitis. The activity of inactivated Probio-01 against plaque-induced gingivitis was possibly mediated by its ability to regulate the dental plaque microbiota, as indicated by the close correlation between the plaque microbiota and clinical indices of gingivitis.

Cost-effectiveness analysis of expectant vs active management for treatment of persistent pregnancies of unknown location.

BACKGROUND: Persistent pregnancies of unknown location are defined by abnormally trending serum human chorionic gonadotropin with nondiagnostic ultrasound. There is no consensus on optimal management. OBJECTIVE: This study aimed to assess the cost-effectiveness of 3 primary management strategies for persistent pregnancies of unknown location: (1) expectant management, (2) empirical 2-dose methotrexate, and (3) uterine evacuation followed by methotrexate, if indicated. STUDY DESIGN: This was a prospective economic evaluation performed concurrently with the Expectant versus Active Management for Treatment of Persistent Pregnancies of Unknown Location multicenter randomized trial that was conducted from July 2014 to June 2019. Participants were randomized 1:1:1 to expectant management, 2-dose methotrexate, or uterine evacuation. The analysis was from the healthcare sector perspective with a 6-week time horizon after randomization. Costs were expressed in 2018 US dollars. Effectiveness was measured in quality-adjusted life years and the rate of salpingectomy. Incremental cost-effectiveness ratios and cost-effectiveness acceptability curves were generated. Sensitivity analyses were performed to assess the robustness of the analysis. RESULTS: Methotrexate had the lowest mean cost ($875), followed by expectant management ($1085) and uterine evacuation ($1902) (P=.001). Expectant management had the highest mean quality-adjusted life years (0.1043), followed by methotrexate (0.1031) and uterine evacuation (0.0992) (P=.0001). The salpingectomy rate was higher for expectant management than for methotrexate (9.4% vs 1.2%, respectively; P=.02) and for expectant management than for uterine evacuation (9.4% vs 8.1%, respectively; P=.04). Uterine evacuation, with the highest costs and the lowest quality-adjusted life years, was dominated by both expectant management and methotrexate. In the base case analysis, expectant management was not cost-effective compared with methotrexate at a willingness to pay of $150,000 per quality-adjusted life year given an incremental cost-effectiveness ratio of $175,083 per quality-adjusted life year gained (95% confidence interval, -$1,666,825 to $2,676,375). Threshold analysis demonstrated that methotrexate administration would have to cost $214 (an increase of $16 or 8%) to favor expectant management. Moreover, expectant management would be favorable in lower-risk patient populations with rates of laparoscopic surgical management for ectopic pregnancy not exceeding 4% of pregnancies of unknown location. Based on the cost-effectiveness acceptability curves, the probability of expectant management being cost-effective compared with methotrexate at a willingness to pay of $150,000 per quality-adjusted life year gained was 50%. The results were dependent on the cost of surgical intervention and the expected rate of methotrexate failure. CONCLUSION: The management of pregnancies of unknown location with a 2-dose methotrexate protocol may be cost-effective compared with expectant management and uterine evacuation. Although uterine evacuation was dominated, expectant management vs methotrexate results were sensitive to modest changes in treatment costs of both methotrexate and surgical management.

Association of cognitive impairment with the interaction between chronic kidney disease and depression: findings from NHANES 2011-2014.

BACKGROUND: Cognitive impairment (CoI), chronic kidney disease (CKD), and depression are prevalent among older adults and are interrelated, imposing a significant disease burden. This study evaluates the association of CKD and depression with CoI and explores their potential interactions. METHOD: Data for this study were sourced from the 2011-2014 National Health and Nutritional Examination Survey (NHANES). Multiple binary logistic regression models assessed the relationship between CKD, depression, and CoI while controlling for confounders. The interactions were measured using the relative excess risk of interaction (RERI), the attributable proportion of interaction (AP), and the synergy index (S). RESULTS: A total of 2,666 participants (weighted n = 49,251,515) were included in the study, of which 700 (16.00%) had CoI. After adjusting for confounding factors, the risk of CoI was higher in patients with CKD compared to non-CKD participants (odds ratio [OR] = 1.49, 95% confidence interval [CI]:1.12-1.99). The risk of CoI was significantly increased in patients with depression compared to those without (OR = 2.29, 95% CI: 1.73-3.03). Furthermore, there was a significant additive interaction between CKD and depression in terms of the increased risk of CoI (adjusted RERI = 2.01, [95% CI: 0.31-3.71], adjusted AP = 0.50 [95% CI: 0.25-0.75], adjusted S = 2.97 [95% CI: 1.27-6.92]). CONCLUSION: CKD and depression synergistically affect CoI, particularly when moderate-to-severe depression co-occurs with CKD. Clinicians should be mindful of the combined impact on patients with CoI. Further research is needed to elucidate the underlying mechanisms and assess the effects specific to different CKD stages.

Development and validation of a LASSO prediction model for cisplatin induced nephrotoxicity: a case-control study in China.

BACKGROUND: Early identification of high-risk individuals with cisplatin-induced nephrotoxicity (CIN) is crucial for avoiding CIN and improving prognosis. In this study, we developed and validated a CIN prediction model based on general clinical data, laboratory indications, and genetic features of lung cancer patients before chemotherapy. METHODS: We retrospectively included 696 lung cancer patients using platinum chemotherapy regimens from June 2019 to June 2021 as the traing set to construct a predictive model using Absolute shrinkage and selection operator (LASSO) regression, cross validation, and Akaike's information criterion (AIC) to select important variables. We prospectively selected 283 independent lung cancer patients from July 2021 to December 2022 as the test set to evaluate the model's performance. RESULTS: The prediction model showed good discrimination and calibration, with AUCs of 0.9217 and 0.8288, sensitivity of 79.89% and 45.07%, specificity of 94.48% and 94.81%, in the training and test sets respectively. Clinical decision curve analysis suggested that the model has value for clinical use when the risk threshold ranges between 0.1 and 0.9. Precision-Recall (PR) curve shown in recall interval from 0.5 to 0.75: precision gradually declines with increasing Recall, up to 0.9. CONCLUSIONS: Predictive models based on laboratory and demographic variables can serve as a beneficial complementary tool for identifying high-risk populations with CIN.

Probiotic Bifidobacterium animalis ssp. lactis Probio-M8 improves the fermentation and probiotic properties of fermented milk.

Probiotics are increasingly used as starter cultures to produce fermented dairy products; however, few studies have investigated the role of probiotics in milk fermentation metabolism. The current study aimed to investigate whether adding Bifidobacterium animalis ssp. lactis Probio-M8 (Probio-M8) as a starter culture strain could improve milk fermentation by comparing the physicochemical characteristics and metabolomes of fermented milks produced by a commercial starter culture with and without Probio-M8. Our results showed that adding Probio-M8 shortened the milk fermentation time and improved the fermented milk texture and stability. Metabolomics analyses revealed that adding Probio-M8 affected mostly organic acid, AA, and fatty acid metabolism in milk fermentation. Targeted quantitative analyses revealed significant increases in various metabolites related to the sensory quality, nutritive value, and health benefits of the probiotic fermented milk, including 5 organic acids (acetic acid, lactic acid, citric acid, succinic acid, and tartaric acid), 5 EAA (valine, arginine, leucine, isoleucine, and lysine), glutamic acid, and 2 essential fatty acids (α-linolenic acid and docosahexaenoic acid). Thus, applying probiotics in milk fermentation is desirable. This study has generated useful information for developing novel functional dairy products.

Shotgun metagenomic analysis of microbiota dynamics during long-term backslopping fermentation of traditional fermented milk in a controlled laboratory environment.

Traditional fermented milks are produced through an inoculation process that involves the deliberate introduction of microorganisms that have been adapted and perpetuated across successive generations. However, the changes in the microbiota of traditional fermented milk during long-term inoculation fermentation in a laboratory environment remain unclear. In this study, we collected 5 samples of traditional fermented milk samples from 5 different counties in Tibet (3 kurut products) and Xinjiang (2 tarag products) of China, which served as starter cultures for a 9-mo continuous inoculation fermentation experiment. We analyzed the inter- and intra-population variations in the microbial communities of the collected samples, representing their macrodiversity and microdiversity, using shotgun metagenomic sequencing. Across all samples, we obtained a total of 186 high-quality metagenomic-assembled genomes, including 7 genera and 13 species with a relative abundance of more than 1%. The majority of these genomes were annotated as Lactobacillus helveticus (60.46%), Enterococcus durans (9.52%), and Limosilactobacillus fermentum (6.23%). We observed significant differences in species composition and abundance among the 5 initial inoculants. During the long-term inoculation fermentation, we found an overall increasing trend in species diversity, composition, and abundances of carbohydrate metabolism module-encoding genes in the fermented milk bacterial metagenome, while the fermented milk virome exhibited a relatively narrow range of variation. Lactobacillus helveticus, a dominant species in traditional fermented milk, displayed high stability during the long-term inoculation fermentation. Our study provides valuable insights for the industrial production of traditional fermented milk.

Dynamic Changes of the Gut Microbiota and Its Functional Metagenomic Potential during the Development of Non-Small Cell Lung Cancer.

The gut microbiota plays a significant role in tumor pathogenesis by regulating the host metabolism and immune response, and there are few studies focused on tracking changes in the gut microbiota from the onset of lung cancer. Therefore, the aim of our study is combining preclinical and clinical research to thoroughly analyze the signatures of fecal microbiota in lung cancer, which will be useful for early diagnosis and predicting the therapeutic efficacy of lung cancer. The first part of this study analyzed the fecal metagenomic differences between patients with non-small cell lung cancer and healthy subjects, and the second part of this work constructed a murine lung cancer model to monitor changes in mouse fecal metagenomics and T cell immunology during lung cancer progression. We found that the fecal microbiota was altered in both humans and mice with lung cancer, characterized by a significantly reduced microbial diversity and number of beneficial microbes, with increases in potential pathogens. The fecal level of Akkermansia muciniphila and the gut metabolic module of the secondary bile acid metabolism were diminished in both humans and mice with lung cancer compared with healthy subjects. Splenomegaly was observed in the lung cancer mice. Flow cytometer analysis of the splenocytes revealed substantial alterations in the proportions of T cell subsets in the lung cancer mice, characterized by significant increases in CD4+Foxp3+CD25+ T regulatory cells (p < 0.05) while significant decreases in CD3+ T cells (p < 0.001), CD4+ T cells (p < 0.001), and the CD4+/CD8+ ratio (p < 0.01). Vertical and longitudinal analyses of the fecal microbiota of the two mouse groups identified some lung cancer biomarkers (including Acutalibacter timonensis, Lachnospiraceae bacterium NSJ-38 sp014337195, etc.). The fecal microbiota of the lung cancer mice had a reduced metagenomic potential for neurotransmitters (melatonin, γ-aminobutyric acid, and histamine) compared with healthy mice. In summary, this study found that the diversity, structure, and composition of gut microbiota vary between cancer and healthy conditions, ultimately leading to changes in the potential for functional metagenomics.

High intestinal isoleucine is a potential risk factor for food allergy by regulating the mTOR/AKT pathway in dendritic cells.

Food allergy is a global food safety problem with a growing prevalence. People in industrial regions are more susceptible to allergy, but the mechanisms behind this are not fully understood. In this study, the probiotic Lactobacillus casei Zhang (LcZ) was administered to allergic individuals and the impact on allergy-related factors were determined. LcZ alleviated allergenic responses, and there was a significant correlation between the intestinal isoleucine content and IgE concentration. Metagenomics results suggest that the metabolism of the gut microbiota is a source of isoleucine. In a mouse model of food allergy, a high isoleucine diet exacerbated allergic responses and increased the activity of allergenic dendritic cell. In a dendritic cell model, a protein array revealed that the mTOR/AKT pathway mediated the function of isoleucine, and molecular docking suggested that Sestrin2 could be the potential receptor. Overall, this study revealed the role of isoleucine in promoting food allergy, elucidated the underlying mechanisms, and suggested that a high intake of isoleucine could be a potential risk factor for food allergy.

Depth importance in precision medicine (DIPM): a tree- and forest-based method for right-censored survival outcomes.

Many clinical trials have been conducted to compare right-censored survival outcomes between interventions. Such comparisons are typically made on the basis of the entire group receiving one intervention versus the others. In order to identify subgroups for which the preferential treatment may differ from the overall group, we propose the depth importance in precision medicine (DIPM) method for such data within the precision medicine framework. The approach first modifies the split criteria of the traditional classification tree to fit the precision medicine setting. Then, a random forest of trees is constructed at each node. The forest is used to calculate depth variable importance scores for each candidate split variable. The variable with the highest score is identified as the best variable to split the node. The importance score is a flexible and simply constructed measure that makes use of the observation that more important variables tend to be selected closer to the root nodes of trees. The DIPM method is primarily designed for the analysis of clinical data with two treatment groups. We also present the extension to the case of more than two treatment groups. We use simulation studies to demonstrate the accuracy of our method and provide the results of applications to two real-world data sets. In the case of one data set, the DIPM method outperforms an existing method, and a primary motivation of this article is the ability of the DIPM method to address the shortcomings of this existing method. Altogether, the DIPM method yields promising results that demonstrate its capacity to guide personalized treatment decisions in cases with right-censored survival outcomes.

TRPA1 promotes cisplatin-induced acute kidney injury via regulating the endoplasmic reticulum stress-mitochondrial damage.

BACKGROUND: Cisplatin is a widely used and effective chemotherapeutic agent against cancer. However, nephrotoxicity is one of the most common side effects of cisplatin, and it can proceed to acute kidney injury (AKI). Studies have reported that activation of transient receptor potential ankyrin-1 (TRPA1) mediates cisplatin-induced renal tubular cytotoxic injury. The aim of this study was to investigate the mechanism of TRPA1 in promoting cisplatin-induced AKI through modulation of the endoplasmic reticulum stress (ERS)-mitochondrial damage. METHODS: A cisplatin-induced HK-2 cell model in vitro and mouse model in vivo were established. The mechanism of TRPA1 promotes AKI was elucidated by H&E staining, TUNEL staining, transmission electron microscope (TEM), immunofluorescence, CCK-8 viability assays, flow cytometry, Western blotting, JC-1 assay, and enzyme linked immunosorbent assay (ELISA). RESULT: In vivo and in vitro, HC-030031 reduced cisplatin-induced Scr and BUN level elevations; improved cisplatin-induced renal tissue injury, apoptosis, and mitochondrial dysfunction; elevated the reduced ERS-associated proteins glucose-regulated protein 78 (GRP78), glucose-regulated protein 75 (GRP75), and C/EBP homologous protein (CHOP) levels induced by cisplatin; reduced the elevated optic atrophy 1 (OPA1), mito-fusion 1 (MFN1), and mito-fusion 2 (MFN2) protein levels, and elevated phospho-dynamin-related protein 1 (p-DRP1) and mitochondrial fission factor (MFF) protein levels. HC-030031 also reduced the mitochondria-associated endoplasmic reticulum membrane (MAM) structure. In addition, TRPA1 agonists also decreased cell proliferation, increased apoptosis, and triggered mitochondrial dysfunction and calcium overload in HK-2 cells via modulation of MAM. ERS inhibitors and GRP75 inhibitors reversed these changes caused by TRPA1 agonists. CONCLUSION: Our findings suggest that TRPA1 enhances cisplatin-induced AKI via modulation of ERS and mitochondrial damage.

Genetic polymorphisms of CYP2B6 is a risk of metabolic associated fatty liver disease in Chinese population.

BACKGROUND: The expression and activity of cytochrome P450 2B6 (CYP2B6) may be related to the metabolic associated fat liver disease (MAFLD). Since constitutive androstane receptor (CAR) is a classic transcriptional regulator of CYP2B6, and the single nucleotide polymorphisms (SNPs) of CYP2B6 and CAR are both associated with adverse reactions of efavirenz, we hypothesized that genetic polymorphisms of CAR might also result in additional interindividual variability in CYP2B6. This study was devoted to explore the association between CYP2B6 and CAR SNPs and susceptibility to MAFLD. MATERIALS AND METHODS: A total of 590 objects of study (118 with MAFLD and 472 healthy control) between December 2014 and April 2018 were retrospectively enrolled. Twenty-two selected SNPs in CYP2B6 and CAR were genotyped with a custom-designed 48-plex SNP Scan TM® Kit. The frequencies of the alleles, genotypes and genetic models of the variants were compared between the two groups. The odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were calculated. RESULTS: The T allele of rs3745274 in CYP2B6 was associated with a decreased risk for MAFLD (OR 0.610; 95% CI: 0.451-0.825, p = 0.001) which was still statistically significant after adjusting with Bonferroni method(p = 0.014) The allele, genotype and genetic model frequencies were similar in the two groups for the other twenty-one SNPs (all P > 0.05). There were no multiplicative or additive interactions between the SNPs. CONCLUSION: Our study revealed that rs3745274 variants in CYP2B6 is associated with susceptibility to MAFLD in the Han Chinese population.

Effect of the probiotic strain, Lactiplantibacillus plantarum P9, on chronic constipation: A randomized, double-blind, placebo-controlled study.

Chronic constipation (CC) is a common gastrointestinal condition associated with intestinal inflammation, and the condition considerably impairs patients' quality of life. We conducted a large-scale 42-day randomized, double-blind, placebo-controlled trial to investigate the effect of probiotics in alleviating CC. 163 patients diagnosed with CC (following Rome IV criteria) were randomly divided into probiotic (n = 78; received Lactiplantibacillus plantarum P9 [P9]; 1 ×1011 CFU/day) and placebo (n = 85; received placebo material) groups. Ingesting P9 significantly improved the weekly mean frequency of complete spontaneous bowel movements (CSBMs) and spontaneous bowel movements (SBMs), while significantly reducing the level of worries and concerns (WO; P < 0.05). Comparing with the placebo group, P9 group was significantly enriched in potentially beneficial bacteria (Lactiplantibacillus plantarum and Ruminococcus_B gnavus), while depriving of several bacterial and phage taxa (Oscillospiraceae sp., Lachnospiraceae sp., and Herelleviridae; P < 0.05). Interesting significant correlations were also observed between some clinical parameters and subjects' gut microbiome, including: negative correlation between Oscillospiraceae sp. and SBMs; positive correlation between WO and Oscillospiraceae sp., Lachnospiraceae sp. Additionally, P9 group had significantly (P < 0.05) more predicted gut microbial bioactive potential involved in the metabolism of amino acids (L-asparagine, L-pipecolinic acid), short-/medium-chain fatty acids (valeric acid and caprylic acid). Furthermore, several metabolites (p-cresol, methylamine, trimethylamine) related to the intestinal barrier and transit decreased significantly after P9 administration (P < 0.05). In short, the constipation relief effect of P9 intervention was accompanied by desirable changes in the fecal metagenome and metabolome. Our findings support the notion of applying probiotics in managing CC.

Bifidobacterium lactis Probio-M8 improves bone metabolism in patients with postmenopausal osteoporosis, possibly by modulating the gut microbiota.

PURPOSE: Postmenopausal osteoporosis (PMO) is usually managed by conventional drug treatment. However, prolonged use of these drugs cause side effects. Gut microbiota may be a potential target for treatment of PMO. This work was a three-month intervention trial aiming to evaluate the added effect of probiotics as adjunctive treatment for PMO. METHODS: Forty patients with PMO were randomized into probiotic (n = 20; received Bifidobacterium animalis subsp. lactis Probio-M8 [Probio-M8], calcium, calcitriol) and placebo (n = 20; received placebo material, calcium, calcitriol) groups. The bone mineral density of patients was measured at month 0 (0 M; baseline) and month 3 (3 M; after three-month intervention). Blood and fecal samples were collected 0 M and 3 M. Only 15 and 12 patients from Probio-M8 and placebo groups, respectively, provided complete fecal samples for gut microbiota analysis. RESULTS: No significant change was observed in the bone mineral density of patients at 3 M. Co-administering Probio-M8 improved the bone metabolism, reflected by an increased vitamin D3 level and decreased PTH and procalcitonin levels in serum at 3 M. Fecal metagenomic analysis revealed modest changes in the gut microbiome in both groups at 3 M. Interestingly, Probio-M8 co-administration affected the gut microbial interactive correlation network, particularly the short-chain fatty acid-producing bacteria. Probio-M8 co-administration significantly increased genes encoding some carbohydrate metabolism pathways (including ABC transporters, the phosphotransferase system, and fructose and mannose metabolism) and a choline-phosphate cytidylyltransferase. CONCLUSIONS: Co-administering Probio-M8 with conventional drugs/supplements was more efficacious than conventional drugs/supplements alone in managing PMO. Our study shed insights into the beneficial mechanism of probiotic adjunctive treatment. REGISTRATION NUMBER OF CLINICAL TRIAL: Chinese Clinical Trial Registry (identifier number: ChiCTR1800019268).

Downregulated calmodulin expression contributes to endothelial cell impairment in diabetes.

Endothelial dysfunction, a central hallmark of cardiovascular pathogenesis in diabetes mellitus, is characterized by impaired endothelial nitric oxide synthase (eNOS) and NO bioavailability. However, the underlying mechanisms remain unclear. Here in this study, we aimed to identify the role of calmodulin (CaM) in diabetic eNOS dysfunction. Human umbilical vein endothelial cells and murine endothelial progenitor cells (EPCs) treated with high glucose (HG) exhibited downregulated CaM mRNA/protein and vascular endothelial growth factor (VEGF) expression with impeded eNOS phosphorylation and cell migration/tube formation. These perturbations were reduplicated in CALM1-knockdown cells but prevented in CALM1-overexpressing cells. EPCs from type 2 diabetes animals behaved similarly to HG-treated normal EPCs, which could be rescued by CALM1-gene transduction. Consistently, diabetic animals displayed impaired eNOS phosphorylation, endothelium-dependent dilation, and CaM expression in the aorta, as well as deficient physical interaction of CaM and eNOS in the gastrocnemius. Local CALM1 gene delivery into a diabetic mouse ischemic hindlimb improved the blunted limb blood perfusion and gastrocnemius angiogenesis, and foot injuries. Diabetic patients showed insufficient foot microvascular autoregulation, eNOS phosphorylation, and NO production with downregulated CaM expression in the arterial endothelium, and abnormal CALM1 transcription in genome-wide sequencing analysis. Therefore, our findings demonstrated that downregulated CaM expression is responsible for endothelium dysfunction and angiogenesis impairment in diabetes, and provided a novel mechanism and target to protect against diabetic endothelial injury.

A polynomial algorithm for best-subset selection problem.

Best-subset selection aims to find a small subset of predictors, so that the resulting linear model is expected to have the most desirable prediction accuracy. It is not only important and imperative in regression analysis but also has far-reaching applications in every facet of research, including computer science and medicine. We introduce a polynomial algorithm, which, under mild conditions, solves the problem. This algorithm exploits the idea of sequencing and splicing to reach a stable solution in finite steps when the sparsity level of the model is fixed but unknown. We define an information criterion that helps the algorithm select the true sparsity level with a high probability. We show that when the algorithm produces a stable optimal solution, that solution is the oracle estimator of the true parameters with probability one. We also demonstrate the power of the algorithm in several numerical studies.