Integrating metabolomics, bionics, and culturomics to study probiotics-driven drug metabolism

Many drugs have been shown to be metabolized by the human gut microbiome, but probiotic-driven drug-metabolizing capacity is rarely explored. Here, we developed an integrated metabolomics, culturomics, and bionics framework for systematically studying probiotics-driven drug metabolism. We discovered that 75% (27/36 of the assayed drugs) were metabolized by five selected probiotics, and drugs containing nitro or azo groups were more readily metabolized. As proof-of-principle experiments, we showed that Lacticaseibacillus casei Zhang (LCZ) could metabolize racecadotril to its active products, S-acetylthiorphan and thiorphan, in monoculture, in a near-real simulated human digestion system, and in an ex vivo fecal co-culture system. However, a personalized effect was observed in the racecadotril-metabolizing activity of L. casei Zhang, depending on the individual’s host gut microbiome composition. Based on data generated by our workflow, we proposed a possible mechanism of interactions among L. casei Zhang, racecadotril, and host gut microbiome, providing practical guidance for probiotic-drug co-treatment and novel insights into precision probiotics

Neural network models for seabed stability: a deep learning approach to wave-induced pore pressure prediction

Wave cyclic loading in submarine sediments can lead to pore pressure accumulation, causing geohazards and compromising seabed stability. Accurate prediction of long-term wave-induced pore pressure is essential for disaster prevention. Although numerical simulations have contributed to understanding wave-induced pore pressure response, traditional methods lack the ability to simulate long-term and real oceanic conditions. This study proposes the use of recurrent neural network (RNN) models to predict wave-induced pore pressure based on in-situ monitoring data. Three RNN models (RNN, LSTM, and GRU) are compared, considering different seabed depths, and input parameters. The results demonstrate that all three RNN models can accurately predict wave-induced pore pressure data, with the GRU model exhibiting the highest accuracy (absolute error less than 2 kPa). Pore pressure at the previous time step and water depth are highly correlated with prediction, while wave height, wind speed, and wind direction show a secondary correlation. This study contributes to the development of wave-induced liquefaction early warning systems and offers insights for utilizing RNNs in geological time series analysis

Risk Prediction of Second Primary Malignancies in Primary Early-Stage Ovarian Cancer Survivors: A SEER-Based National Population-Based Cohort Study

Purpose: This study aimed to characterize the clinical features of early-stage ovarian cancer (OC) survivors with second primary malignancies (SPMs) and provided a prediction tool for individualized risk of developing SPMs. Methods: Data were obtained from the Surveillance, Epidemiology and End Results (SEER) database during 1998–2013. Considering non-SPM death as a competing event, the Fine and Gray model and the corresponding nomogram were used to identify the risk factors for SPMs and predict the SPM probabilities after the initial OC diagnosis. The decision curve analysis (DCA) was performed to evaluate the clinical utility of our proposed model. Results: A total of 14,314 qualified patients were enrolled. The diagnosis rate and the cumulative incidence of SPMs were 7.9% and 13.6% [95% confidence interval (CI) = 13.5% to 13.6%], respectively, during the median follow-up of 8.6 years. The multivariable competing risk analysis suggested that older age at initial cancer diagnosis, white race, epithelial histologic subtypes of OC (serous, endometrioid, mucinous, and Brenner tumor), number of lymph nodes examined (<12), and radiotherapy were significantly associated with an elevated SPM risk. The DCA revealed that the net benefit obtained by our proposed model was higher than the all-screening or no-screening scenarios within a wide range of risk thresholds (1% to 23%). Conclusion: The competing risk nomogram can be potentially helpful for assisting physicians in identifying patients with different risks of SPMs and scheduling risk-adapted clinical management. More comprehensive data on treatment regimens and patient characteristics may help improve the predictability of the risk model for SPMs

Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China:the PLANS (platelet lymphocyte age neutrophil sex) model

Background Previous published prognostic models for COVID-19 patients have been suggested to be prone to bias due to unrepresentativeness of patient population, lack of external validation, inappropriate statistical analyses, or poor reporting. A high-quality and easy-to-use prognostic model to predict in-hospital mortality for COVID-19 patients could support physicians to make better clinical decisions. Methods Fine-Gray models were used to derive a prognostic model to predict in-hospital mortality (treating discharged alive from hospital as the competing event) in COVID-19 patients using two retrospective cohorts (n = 1008) in Wuhan, China from January 1 to February 10, 2020. The proposed model was internally evaluated by bootstrap approach and externally evaluated in an external cohort (n = 1031). Results The derivation cohort was a case-mix of mild-to-severe hospitalized COVID-19 patients (43.6% females, median age 55). The final model (PLANS), including five predictor variables of platelet count, lymphocyte count, age, neutrophil count, and sex, had an excellent predictive performance (optimism-adjusted C-index: 0.85, 95% CI: 0.83 to 0.87; averaged calibration slope: 0.95, 95% CI: 0.82 to 1.08). Internal validation showed little overfitting. External validation using an independent cohort (47.8% female, median age 63) demonstrated excellent predictive performance (C-index: 0.87, 95% CI: 0.85 to 0.89; calibration slope: 1.02, 95% CI: 0.92 to 1.12). The averaged predicted cumulative incidence curves were close to the observed cumulative incidence curves in patients with different risk profiles. Conclusions The PLANS model based on five routinely collected predictors would assist clinicians in better triaging patients and allocating healthcare resources to reduce COVID-19 fatality

Inhibition of ERK-DLP1 signaling and mitochondrial division alleviates mitochondrial dysfunction in Alzheimer's disease cybrid cell

Mitochondrial dysfunction is an early pathological feature of Alzheimer’s disease (AD). The underlying mechanisms and strategies to repair it remain unclear. Here, we demonstrate for the first time the direct consequences and potential mechanisms of mitochondrial functional defects associated with abnormal mitochondrial dynamics in AD. Using cytoplasmic hybrid (cybrid) neurons with incorporated platelet mitochondria from AD and age-matched non-AD human subjects into mitochondrial DNA (mtDNA)-depleted neuronal cells, we observed that AD cybrid cells had significant changes in morphology and function; such changes associate with altered expression and distribution of dynamin-like protein (DLP1) and mitofusin 2 (Mfn2). Treatment with antioxidant protects against AD mitochondria-induced extracellular signal-regulated kinase (ERK) activation and mitochondrial fission-fusion imbalances. Notably, inhibition of ERK activation not only attenuates aberrant mitochondrial morphology and function but also restores the mitochondrial fission and fusion balance. These effects suggest a role of oxidative stress-mediated ERK signal transduction in modulation of mitochondrial fission and fusion events. Further, blockade of the mitochondrial fission protein DLP1 by a genetic manipulation with a dominant negative DLP1 (DLP1K38A), its expression with siRNA-DLP1, or inhibition of mitochondrial division with mdivi-1 attenuates mitochondrial functional defects observed in AD cybrid cells. Our results provide new insights into mitochondrial dysfunction resulting from changes in the ERK-fission/fusion (DLP1) machinery and signaling pathway. The protective effect of mdivi-1 and inhibition of ERK signaling on maintenance of normal mitochondrial structure and function holds promise as a potential novel therapeutic strategy for AD

Inhibition of ERK-DLP1 signaling and mitochondrial division alleviates mitochondrial dysfunction in Alzheimer's disease cybrid cell

Mitochondrial dysfunction is an early pathological feature of Alzheimer’s disease (AD). The underlying mechanisms and strategies to repair it remain unclear. Here, we demonstrate for the first time the direct consequences and potential mechanisms of mitochondrial functional defects associated with abnormal mitochondrial dynamics in AD. Using cytoplasmic hybrid (cybrid) neurons with incorporated platelet mitochondria from AD and age-matched non-AD human subjects into mitochondrial DNA (mtDNA)-depleted neuronal cells, we observed that AD cybrid cells had significant changes in morphology and function; such changes associate with altered expression and distribution of dynamin-like protein (DLP1) and mitofusin 2 (Mfn2). Treatment with antioxidant protects against AD mitochondria-induced extracellular signal-regulated kinase (ERK) activation and mitochondrial fission-fusion imbalances. Notably, inhibition of ERK activation not only attenuates aberrant mitochondrial morphology and function but also restores the mitochondrial fission and fusion balance. These effects suggest a role of oxidative stress-mediated ERK signal transduction in modulation of mitochondrial fission and fusion events. Further, blockade of the mitochondrial fission protein DLP1 by a genetic manipulation with a dominant negative DLP1 (DLP1K38A), its expression with siRNA-DLP1, or inhibition of mitochondrial division with mdivi-1 attenuates mitochondrial functional defects observed in AD cybrid cells. Our results provide new insights into mitochondrial dysfunction resulting from changes in the ERK-fission/fusion (DLP1) machinery and signaling pathway. The protective effect of mdivi-1 and inhibition of ERK signaling on maintenance of normal mitochondrial structure and function holds promise as a potential novel therapeutic strategy for AD

Maternal hypertensive disorders and neurodevelopmental disorders in offspring: a population-based cohort in two Nordic countries

Maternal hypertensive disorders during pregnancy (HDP) have been associated with neuropsychiatric problems in offspring. We aim to investigate the associations between specific types of maternal HDP and offspring neurodevelopmental disorders and further examine whether the timing of onset and severity of HDP would affect these associations. The study population consisted of 4,489,044 live-born singletons in Denmark during 1978-2012 and Sweden during 1987-2010. Maternal HDP was categorized into chronic hypertension, gestational hypertension, and pre-eclampsia; pre-eclampsia was further stratified according to timing (early-onset, late-onset), or severity (moderate, severe) of the disease. Neurodevelopmental disorders, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and intellectual disability (ID), were defined by ICD-coded register diagnosis. Cox regression was used to calculate hazard ratios (HR) while adjusting for potential confounders, and sibling analyses assessed the influence of unmeasured shared familial factors. Maternal HDP was associated with increased risks of ADHD (HR, 1.24; 95% confidence interval [CI], 1.20-1.28), ASD (1.29 [1.24-1.34]), and ID (1.58 [1.50-1.66]) in offspring, respectively, which was mostly driven by pre-eclampsia. The strongest associations were observed for early-onset and severe pre-eclampsia, and the corresponding HRs for ADHD, ASD and ID were 1.93 [1.73-2.16], 1.86 [1.61-2.15], and 3.99 [3.42-4.65], respectively. The results were similar in the sibling analyses. The associations between maternal HDP and offspring neurodevelopmental disorders were consistent across the subgroups of sex, preterm status, parity, maternal age and psychiatric disorders. Maternal HDP, especially early-onset pre-eclampsia, are associated with increased risks of ADHD, ASD, and ID in particular, independent of shared familial factors

Mendelian randomization and clinical trial evidence supports TYK2 inhibition as a therapeutic target for autoimmune diseases

Background: To explore the associations of genetically proxied TYK2 inhibition with a wide range of disease outcomes and biomarkers to identify therapeutic repurposing opportunities, adverse effects, and biomarkers of efficacy. Methods: The loss-of-function missense variant rs34536443 in TYK2 gene was used as a genetic instrument to proxy the effect of TYK2 inhibition. A phenome-wide Mendelian randomization (MR) study was conducted to explore the associations of genetically-proxied TYK2 inhibition with 1473 disease outcomes in UK Biobank (N = 339,197). Identified associations were examined for replication in FinnGen (N = 260,405). We further performed tissue -specific gene expression MR, colocalization analyses, and MR with 247 blood biomarkers. A systematic review of randomized controlled trials (RCTs) on TYK2 inhibitor was performed to complement the genetic evidence. Findings: PheWAS-MR found that genetically-proxied TYK2 inhibition was associated with lower risk of a wide range of autoimmune diseases. The associations with hypothyroidism and psoriasis were confirmed in MR analysis of tissue-specific TYK2 gene expression and the associations with systemic lupus erythematosus, psoriasis, and rheumatoid arthritis were observed in colocalization analysis. There were nominal associations of genetically-proxied TYK2 inhibition with increased risk of prostate and breast cancer but not in tissue-specific expression MR or colocalization analyses. Thirty-seven blood biomarkers were associated with the TYK2 loss-of-function mutation. Evidence from RCTs confirmed the effectiveness of TYK2 inhibitors on plaque psoriasis and reported several adverse effects. Interpretation: This study supports TYK2 inhibitor as a potential treatment for psoriasis and several other autoim-mune diseases. Increased pharmacovigilance is warranted in relation to the potential adverse effects.De två första författarna delar förstaförfattarskapet.De tre sista författarna delar sistaförfattarskapet.</p