Gcap14 is a microtubule plus-end-tracking protein coordinating microtubule-actin crosstalk during neurodevelopment.

Regulation of microtubule dynamics is required to properly control various steps of neurodevelopment. In this study, we identified granule cell antiserum-positive 14 (Gcap14) as a microtubule plus-end-tracking protein and as a regulator of microtubule dynamics during neurodevelopment. Gcap14 knockout mice exhibited impaired cortical lamination. Gcap14 deficiency resulted in defective neuronal migration. Moreover, nuclear distribution element nudE-like 1 (Ndel1), an interacting partner of Gcap14, effectively corrected the downregulation of microtubule dynamics and the defects in neuronal migration caused by Gcap14 deficiency. Finally, we found that the Gcap14-Ndel1 complex participates in the functional link between microtubule and actin filament, thereby regulating their crosstalks in the growth cones of cortical neurons. Taken together, we propose that the Gcap14-Ndel1 complex is fundamental for cytoskeletal remodeling during neurodevelopmental processes such as neuronal processes elongation and neuronal migration.

Genome-wide kinase-MAM interactome screening reveals the role of CK2A1 in MAM Ca2+ dynamics linked to DEE66.

The endoplasmic reticulum (ER) and mitochondria form a unique subcellular compartment called mitochondria-associated ER membranes (MAMs). Disruption of MAMs impairs Ca2+ homeostasis, triggering pleiotropic effects in the neuronal system. Genome-wide kinase-MAM interactome screening identifies casein kinase 2 alpha 1 (CK2A1) as a regulator of composition and Ca2+ transport of MAMs. CK2A1-mediated phosphorylation of PACS2 at Ser207/208/213 facilitates MAM localization of the CK2A1-PACS2-PKD2 complex, regulating PKD2-dependent mitochondrial Ca2+ influx. We further reveal that mutations of PACS2 (E209K and E211K) associated with developmental and epileptic encephalopathy-66 (DEE66) impair MAM integrity through the disturbance of PACS2 phosphorylation at Ser207/208/213. This, in turn, causes the reduction of mitochondrial Ca2+ uptake and the dramatic increase of the cytosolic Ca2+ level, thereby, inducing neurotransmitter release at the axon boutons of glutamatergic neurons. In conclusion, our findings suggest a molecular mechanism that MAM alterations induced by pathological PACS2 mutations modulate Ca2+-dependent neurotransmitter release.

Schizophrenia-associated Mitotic Arrest Deficient-1 (MAD1) regulates the polarity of migrating neurons in the developing neocortex.

Although large-scale genome-wide association studies (GWAS) have identified an association between MAD1L1 (Mitotic Arrest Deficient-1 Like 1) and the pathology of schizophrenia, the molecular mechanisms underlying this association remain unclear. In the present study, we aimed to address these mechanisms by examining the role of MAD1 (the gene product of MAD1L1) in key neurodevelopmental processes in mice and human organoids. Our findings indicated that MAD1 is highly expressed during active cortical development and that MAD1 deficiency leads to impairments in neuronal migration and neurite outgrowth. We also observed that MAD1 is localized to the Golgi apparatus and regulates vesicular trafficking from the Golgi apparatus to the plasma membrane, which is required for the growth and polarity of migrating neurons. In this process, MAD1 physically interacts and collaborates with the kinesin-like protein KIFC3 (kinesin family member C3) to regulate the morphology of the Golgi apparatus and neuronal polarity, thereby ensuring proper neuronal migration and differentiation. Consequently, our findings indicate that MAD1 is an essential regulator of neuronal development and that alterations in MAD1 may underlie schizophrenia pathobiology.

Improving the accuracy of automated gout flare ascertainment using natural language processing of electronic health records and linked Medicare claims data.

BACKGROUND: We aimed to determine whether integrating concepts from the notes from the electronic health record (EHR) data using natural language processing (NLP) could improve the identification of gout flares. METHODS: Using Medicare claims linked with EHR, we selected gout patients who initiated the urate-lowering therapy (ULT). Patients' 12-month baseline period and on-treatment follow-up were segmented into 1-month units. We retrieved EHR notes for months with gout diagnosis codes and processed notes for NLP concepts. We selected a random sample of 500 patients and reviewed each of their notes for the presence of a physician-documented gout flare. Months containing at least 1 note mentioning gout flares were considered months with events. We used 60% of patients to train predictive models with LASSO. We evaluated the models by the area under the curve (AUC) in the validation data and examined positive/negative predictive values (P/NPV). RESULTS: We extracted and labeled 839 months of follow-up (280 with gout flares). The claims-only model selected 20 variables (AUC = 0.69). The NLP concept-only model selected 15 (AUC = 0.69). The combined model selected 32 claims variables and 13 NLP concepts (AUC = 0.73). The claims-only model had a PPV of 0.64 [0.50, 0.77] and an NPV of 0.71 [0.65, 0.76], whereas the combined model had a PPV of 0.76 [0.61, 0.88] and an NPV of 0.71 [0.65, 0.76]. CONCLUSION: Adding NLP concept variables to claims variables resulted in a small improvement in the identification of gout flares. Our data-driven claims-only model and our combined claims/NLP-concept model outperformed existing rule-based claims algorithms reliant on medication use, diagnosis, and procedure codes.

Comparative Safety Analysis of Oral Antipsychotics for In-Hospital Adverse Clinical Events in Older Adults After Major Surgery : A Nationwide Cohort Study.

BACKGROUND: Antipsychotics are commonly used to manage postoperative delirium. Recent studies reported that haloperidol use has declined, and atypical antipsychotic use has increased over time. OBJECTIVE: To compare the risk for in-hospital adverse events associated with oral haloperidol, olanzapine, quetiapine, and risperidone in older patients after major surgery. DESIGN: Retrospective cohort study. SETTING: U.S. hospitals in the Premier Healthcare Database. PATIENTS: 17 115 patients aged 65 years and older without psychiatric disorders who were prescribed an oral antipsychotic drug after major surgery from 2009 to 2018. INTERVENTIONS: Haloperidol (≤4 mg on the day of initiation), olanzapine (≤10 mg), quetiapine (≤150 mg), and risperidone (≤4 mg). MEASUREMENTS: The risk ratios (RRs) for in-hospital death, cardiac arrhythmia events, pneumonia, and stroke or transient ischemic attack (TIA) were estimated after propensity score overlap weighting. RESULTS: The weighted population had a mean age of 79.6 years, was 60.5% female, and had in-hospital death of 3.1%. Among the 4 antipsychotics, quetiapine was the most prescribed (53.0% of total exposure). There was no statistically significant difference in the risk for in-hospital death among patients treated with haloperidol (3.7%, reference group), olanzapine (2.8%; RR, 0.74 [95% CI, 0.42 to 1.27]), quetiapine (2.6%; RR, 0.70 [CI, 0.47 to 1.04]), and risperidone (3.3%; RR, 0.90 [CI, 0.53 to 1.41]). The risk for nonfatal clinical events ranged from 2.0% to 2.6% for a cardiac arrhythmia event, 4.2% to 4.6% for pneumonia, and 0.6% to 1.2% for stroke or TIA, with no statistically significant differences by treatment group. LIMITATION: Residual confounding by delirium severity; lack of untreated group; restriction to oral low-to-moderate dose treatment. CONCLUSION: These results suggest that atypical antipsychotics and haloperidol have similar rates of in-hospital adverse clinical events in older patients with postoperative delirium who receive an oral low-to-moderate dose antipsychotic drug. PRIMARY FUNDING SOURCE: National Institute on Aging.

Identifying Functional Status Impairment in People Living With Dementia Through Natural Language Processing of Clinical Documents: Cross-Sectional Study.

BACKGROUND: Assessment of activities of daily living (ADLs) and instrumental ADLs (iADLs) is key to determining the severity of dementia and care needs among older adults. However, such information is often only documented in free-text clinical notes within the electronic health record and can be challenging to find. OBJECTIVE: This study aims to develop and validate machine learning models to determine the status of ADL and iADL impairments based on clinical notes. METHODS: This cross-sectional study leveraged electronic health record clinical notes from Mass General Brigham's Research Patient Data Repository linked with Medicare fee-for-service claims data from 2007 to 2017 to identify individuals aged 65 years or older with at least 1 diagnosis of dementia. Notes for encounters both 180 days before and after the first date of dementia diagnosis were randomly sampled. Models were trained and validated using note sentences filtered by expert-curated keywords (filtered cohort) and further evaluated using unfiltered sentences (unfiltered cohort). The model's performance was compared using area under the receiver operating characteristic curve and area under the precision-recall curve (AUPRC). RESULTS: The study included 10,000 key-term-filtered sentences representing 441 people (n=283, 64.2% women; mean age 82.7, SD 7.9 years) and 1000 unfiltered sentences representing 80 people (n=56, 70% women; mean age 82.8, SD 7.5 years). Area under the receiver operating characteristic curve was high for the best-performing ADL and iADL models on both cohorts (>0.97). For ADL impairment identification, the random forest model achieved the best AUPRC (0.89, 95% CI 0.86-0.91) on the filtered cohort; the support vector machine model achieved the highest AUPRC (0.82, 95% CI 0.75-0.89) for the unfiltered cohort. For iADL impairment, the Bio+Clinical bidirectional encoder representations from transformers (BERT) model had the highest AUPRC (filtered: 0.76, 95% CI 0.68-0.82; unfiltered: 0.58, 95% CI 0.001-1.0). Compared with a keyword-search approach on the unfiltered cohort, machine learning reduced false-positive rates from 4.5% to 0.2% for ADL and 1.8% to 0.1% for iADL. CONCLUSIONS: In this study, we demonstrated the ability of machine learning models to accurately identify ADL and iADL impairment based on free-text clinical notes, which could be useful in determining the severity of dementia.

The convergent application of metabolites from Avena sativa and gut microbiota to ameliorate non-alcoholic fatty liver disease: a network pharmacology study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue globally, currently, the treatment of NAFLD lies still in the labyrinth. In the inchoate stage, the combinatorial application of food regimen and favorable gut microbiota (GM) are considered as an alternative therapeutic. Accordingly, we integrated secondary metabolites (SMs) from GM and Avena sativa (AS) known as potent dietary grain to identify the combinatorial efficacy through network pharmacology. METHODS: We browsed the SMs of AS via Natural Product Activity & Species Source (NPASS) database and SMs of GM were retrieved by gutMGene database. Then, specific intersecting targets were identified from targets related to SMs of AS and GM. The final targets were selected on NAFLD-related targets, which was considered as crucial targets. The protein-protein interaction (PPI) networks and bubble chart analysis to identify a hub target and a key signaling pathway were conducted, respectively. In parallel, we analyzed the relationship of GM or AS─a key signaling pathway─targets─SMs (GASTM) by merging the five components via RPackage. We identified key SMs on a key signaling pathway via molecular docking assay (MDA). Finally, the identified key SMs were verified the physicochemical properties and toxicity in silico platform. RESULTS: The final 16 targets were regarded as critical proteins against NAFLD, and Vascular Endothelial Growth Factor A (VEGFA) was a key target in PPI network analysis. The PI3K-Akt signaling pathway was the uppermost mechanism associated with VEGFA as an antagonistic mode. GASTM networks represented 122 nodes (60 GM, AS, PI3K-Akt signaling pathway, 4 targets, and 56 SMs) and 154 edges. The VEGFA-myricetin, or quercetin, GSK3B-myricetin, IL2-diosgenin complexes formed the most stable conformation, the three ligands were derived from GM. Conversely, NR4A1-vestitol formed stable conformation with the highest affinity, and the vestitol was obtained from AS. The given four SMs were no hurdles to develop into drugs devoid of its toxicity. CONCLUSION: In conclusion, we show that combinatorial application of AS and GM might be exerted to the potent synergistic effects against NAFLD, dampening PI3K-Akt signaling pathway. This work provides the importance of dietary strategy and beneficial GM on NAFLD, a data mining basis for further explicating the SMs and pharmacological mechanisms of combinatorial application (AS and GM) against NAFLD.

Validation of serostatus of rheumatoid arthritis using ICD-10 codes in administrative claims data.

PURPOSE: To determine the accuracy of International Classification of Diseases- Tenth Revision (ICD-10) diagnosis codes for rheumatoid arthritis (RA) serostatus using a U.S. claims database (Optum Clinformatics Data Mart, Optum) and to compare the results to a previous validation study performed in IBM Marketscan Research Database (sensitivity 73%, positive predictive value, PPV, 84%). METHODS: In Optum (01/01/2016-03/31/2020) linked with laboratory results, we selected RA patients based on ≥2 ICD-10 diagnosis codes for RA (M05 or M06) and at least one dispensing of RA treatments. We included individuals with at least one laboratory result for rheumatoid factor (RF) or anti-cyclic citrullinated peptide (CCP) performed 365 days prior to and including the cohort entry date. An individual was "seropositive" if at least one of the 2 diagnosis codes used to define RA status was M05. "Seronegative" patients were required to have only M06. Secondary analyses were performed using subsets of M05 and M06 diagnosis codes. We calculated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and kappa of M05 and M06 against the prespecified reference standard laboratory data. RESULTS: We identified 14 490 adult RA patients who had at least 1 RF or anti-CCP result. The number of patients identified for each reference standard definition ranged from 3315 (reference standard definition: high + anti-CCP) to 13 636 (any + RF). PPV for seropositive RA, M05, was 77.1%. The PPV of M06 for seronegative RA was 61.6%. When we applied more restricted definitions of M05 and M06, the PPV for seropositive RA increased to 79.2%. The PPV for seronegative RA also notably increased to 89.5%. CONCLUSION: ICD-10 codes (M05 and M06) can help identify RA serostatus in claims data, but their limitations should be acknowledged. The PPVs for seropositive and seronegative RA found in the Optum database were lower than those found in MarketScan, perhaps related to database variability or differing patient characteristics and clinical practice. When more restricted definitions of M05 and M06 were used, the PPVs for seropositive and seronegative RA improved to 79.2% and 89.5%, respectively.

Treatment Failure and Adverse Events After Amoxicillin-Clavulanate vs Amoxicillin for Pediatric Acute Sinusitis.

Importance: Acute sinusitis is one of the most common indications for antibiotic prescribing in children, with an estimated 4.9 million such prescriptions in the US annually. Consensus does not exist regarding the optimal empirical antibiotic. Objective: To compare amoxicillin-clavulanate vs amoxicillin for the treatment of acute sinusitis in outpatient children. Design, Setting, and Participants: Cohort study of children and adolescents aged 17 years or younger with a new outpatient diagnosis of acute sinusitis and a same-day new prescription dispensation of amoxicillin-clavulanate or amoxicillin in a nationwide health care utilization database. Propensity score matching was used to mitigate confounding. Exposure: A new prescription dispensation of amoxicillin-clavulanate or amoxicillin. Main Outcomes and Measures: Treatment failure, defined as an aggregate of a new antibiotic dispensation, emergency department or inpatient encounter for acute sinusitis, or inpatient encounter for a sinusitis complication, was assessed 1 to 14 days after cohort enrollment. Adverse events were evaluated, including gastrointestinal symptoms, hypersensitivity and skin reactions, acute kidney injury, and secondary infections. Results: The cohort included 320 141 patients. After propensity score matching, there were 198 942 patients (99 471 patients per group), including 100 340 (50.4%) who were female, 101 726 (51.1%) adolescents aged 12 to 17 years, 52 149 (26.2%) children aged 6 to 11 years, and 45 067 (22.7%) children aged 0 to 5 years. Treatment failure occurred in 1.7% overall; 0.01% had serious failure (an emergency department or inpatient encounter). There was no difference in the risk of treatment failure between the amoxicillin-clavulanate and amoxicillin groups (relative risk [RR], 0.98 [95% CI, 0.92-1.05]). The risk of gastrointestinal symptoms (RR, 1.15 [95% CI, 1.05-1.25]) and yeast infections (RR, 1.33 [95% CI, 1.16-1.54]) was higher with amoxicillin-clavulanate. After patients were stratified by age, the risk of treatment failure after amoxicillin-clavulanate was an RR of 0.98 (95% CI, 0.86-1.12) for ages 0 to 5 years; RR was 1.06 (95% CI, 0.92-1.21) for 6 to 11 years; and RR was 0.87 (95% CI, 0.79-0.95) for 12 to 17 years. The age-stratified risk of adverse events after amoxicillin-clavulanate was an RR of 1.23 (95% CI, 1.10-1.37) for ages 0 to 5 years; RR was 1.19 (95% CI, 1.04-1.35) for 6 to 11 years; and RR was 1.04 (95% CI, 0.95-1.14) for 12 to 17 years. Conclusions and Relevance: In children with acute sinusitis who were treated as outpatients, there was no difference in the risk of treatment failure between those who received amoxicillin-clavulanate compared with amoxicillin, but amoxicillin-clavulanate was associated with a higher risk of gastrointestinal symptoms and yeast infections. These findings may help inform decisions for empirical antibiotic selection in acute sinusitis.

Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials.

Importance: Nonrandomized studies using insurance claims databases can be analyzed to produce real-world evidence on the effectiveness of medical products. Given the lack of baseline randomization and measurement issues, concerns exist about whether such studies produce unbiased treatment effect estimates. Objective: To emulate the design of 30 completed and 2 ongoing randomized clinical trials (RCTs) of medications with database studies using observational analogues of the RCT design parameters (population, intervention, comparator, outcome, time [PICOT]) and to quantify agreement in RCT-database study pairs. Design, Setting, and Participants: New-user cohort studies with propensity score matching using 3 US claims databases (Optum Clinformatics, MarketScan, and Medicare). Inclusion-exclusion criteria for each database study were prespecified to emulate the corresponding RCT. RCTs were explicitly selected based on feasibility, including power, key confounders, and end points more likely to be emulated with real-world data. All 32 protocols were registered on ClinicalTrials.gov before conducting analyses. Emulations were conducted from 2017 through 2022. Exposures: Therapies for multiple clinical conditions were included. Main Outcomes and Measures: Database study emulations focused on the primary outcome of the corresponding RCT. Findings of database studies were compared with RCTs using predefined metrics, including Pearson correlation coefficients and binary metrics based on statistical significance agreement, estimate agreement, and standardized difference. Results: In these highly selected RCTs, the overall observed agreement between the RCT and the database emulation results was a Pearson correlation of 0.82 (95% CI, 0.64-0.91), with 75% meeting statistical significance, 66% estimate agreement, and 75% standardized difference agreement. In a post hoc analysis limited to 16 RCTs with closer emulation of trial design and measurements, concordance was higher (Pearson r, 0.93; 95% CI, 0.79-0.97; 94% meeting statistical significance, 88% estimate agreement, 88% standardized difference agreement). Weaker concordance occurred among 16 RCTs for which close emulation of certain design elements that define the research question (PICOT) with data from insurance claims was not possible (Pearson r, 0.53; 95% CI, 0.00-0.83; 56% meeting statistical significance, 50% estimate agreement, 69% standardized difference agreement). Conclusions and Relevance: Real-world evidence studies can reach similar conclusions as RCTs when design and measurements can be closely emulated, but this may be difficult to achieve. Concordance in results varied depending on the agreement metric. Emulation differences, chance, and residual confounding can contribute to divergence in results and are difficult to disentangle.

Identification of Gut Microbiome Metabolites via Network Pharmacology Analysis in Treating Alcoholic Liver Disease.

Alcoholic liver disease (ALD) is linked to a broad spectrum of diseases, including diabetes, hypertension, atherosclerosis, and even liver carcinoma. The ALD spectrum includes alcoholic fatty liver disease (AFLD), alcoholic hepatitis, and cirrhosis. Most recently, some reports demonstrated that the pathogenesis of ALD is strongly associated with metabolites of human microbiota. AFLD was the onset of disease among ALDs, the initial cause of which is alcohol consumption. Thus, we analyzed the significant metabolites of microbiota against AFLD via the network pharmacology concept. The metabolites from microbiota were retrieved by the gutMGene database; sequentially, AFLD targets were identified by public databases (DisGeNET, OMIM). The final targets were utilized for protein-protein interaction (PPI) networks and signaling pathway analyses. Then, we performed a molecular docking test (MDT) to verify the affinity between metabolite(s) and target(s) utilizing the Autodock 1.5.6 tool. From a holistic viewpoint, we integrated the relationships of microbiota-signaling pathways-targets-metabolites (MSTM) using the R Package. We identified the uppermost six key targets (TLR4, RELA, IL6, PPARG, COX-2, and CYP1A2) against AFLD. The PPI network analysis revealed that TLR4, RELA, IL6, PPARG, and COX-2 had equivalent degrees of value (4); however, CYP1A2 had no associations with the other targets. The bubble chart showed that the PI3K-Akt signaling pathway in nine signaling pathways might be the most significant mechanism with antagonistic functions in the treatment of AFLD. The MDT confirmed that Icaritin is a promising agent to bind stably to RELA (known as NF-Κb). In parallel, Bacterium MRG-PMF-1, the PI3K-Akt signaling pathway, RELA, and Icaritin were the most significant components against AFLD in MSTM networks. In conclusion, we showed that the Icaritin-RELA complex on the PI3K-Akt signaling pathway by bacterial MRG-PMF-1 might have promising therapeutic effects against AFLD, providing crucial evidence for further research.

Tofacitinib and risk of cardiovascular outcomes: results from the Safety of TofAcitinib in Routine care patients with Rheumatoid Arthritis (STAR-RA) study.

OBJECTIVES: Recent results from 'ORAL Surveillance' trial have raised concerns regarding the cardiovascular safety of tofacitinib in patients with rheumatoid arthritis (RA). We further examined this safety concern in the real-world setting. METHODS: We created two cohorts of patients with RA initiating treatment with tofacitinib or tumour necrosis factor inhibitors (TNFI) using deidentified data from Optum Clinformatics (2012-2020), IBM MarketScan (2012-2018) and Medicare (parts A, B and D, 2012-2017) claims databases: (1) A 'real-world evidence (RWE) cohort' consisting of routine care patients and (2) A 'randomised controlled trial (RCT)-duplicate cohort' mimicking inclusion and exclusion criteria of the ORAL surveillance trial to calibrate results against the trial findings. Cox proportional hazards models with propensity score fine stratification weighting were used to estimate HR and 95% CIs for composite outcome of myocardial infarction and stroke and accounting for 76 potential confounders. Database-specific effect estimates were pooled using fixed effects models with inverse-variance weighting. RESULTS: In the RWE cohort, 102 263 patients were identified of whom 12 852 (12.6%) initiated tofacitinib. The pooled weighted HR (95% CI) comparing tofacitinib with TNFI was 1.01 (0.83 to 1.23) in RWE cohort and 1.24 (0.90 to 1.69) in RCT-duplicate cohort which aligned closely with ORAL-surveillance results (HR: 1.33, 95% CI 0.91 to 1.94). CONCLUSIONS: We did not find evidence for an increased risk of cardiovascular outcomes with tofacitinib in patients with RA treated in the real-world setting; however, tofacitinib was associated with an increased risk of cardiovascular outcomes, although statistically non-significant, in patients with RA with cardiovascular risk factors. TRIAL REGISTRATION NUMBER: NCT04772248.

The Link between Gut Microbiota and Hepatic Encephalopathy.

Hepatic encephalopathy (HE) is a serious complication of cirrhosis that causes neuropsychiatric problems, such as cognitive dysfunction and movement disorders. The link between the microbiota and the host plays a key role in the pathogenesis of HE. The link between the gut microbiome and disease can be positively utilized not only in the diagnosis area of HE but also in the treatment area. Probiotics and prebiotics aim to resolve gut dysbiosis and increase beneficial microbial taxa, while fecal microbiota transplantation aims to address gut dysbiosis through transplantation (FMT) of the gut microbiome from healthy donors. Antibiotics, such as rifaximin, aim to improve cognitive function and hyperammonemia by targeting harmful taxa. Current treatment regimens for HE have achieved some success in treatment by targeting the gut microbiota, however, are still accompanied by limitations and problems. A focused approach should be placed on the establishment of personalized trial designs and therapies for the improvement of future care. This narrative review identifies factors negatively influencing the gut-hepatic-brain axis leading to HE in cirrhosis and explores their relationship with the gut microbiome. We also focused on the evaluation of reported clinical studies on the management and improvement of HE patients with a particular focus on microbiome-targeted therapy.

Microbiome-Based Metabolic Therapeutic Approaches in Alcoholic Liver Disease.

Alcohol consumption is a global healthcare problem. Chronic alcohol consumption generates a wide spectrum of hepatic lesions, the most characteristic of which are steatosis, hepatitis, fibrosis, and cirrhosis. Alcoholic liver diseases (ALD) refer to liver damage and metabolomic changes caused by excessive alcohol intake. ALD present several clinical stages of severity found in liver metabolisms. With increased alcohol consumption, the gut microbiome promotes a leaky gut, metabolic dysfunction, oxidative stress, liver inflammation, and hepatocellular injury. Much attention has focused on ALD, such as alcoholic fatty liver (AFL), alcoholic steatohepatitis (ASH), alcoholic cirrhosis (AC), hepatocellular carcinoma (HCC), a partnership that reflects the metabolomic significance. Here, we report on the global function of inflammation, inhibition, oxidative stress, and reactive oxygen species (ROS) mechanisms in the liver biology framework. In this tutorial review, we hypothetically revisit therapeutic gut microbiota-derived alcoholic oxidative stress, liver inflammation, inflammatory cytokines, and metabolic regulation. We summarize the perspective of microbial therapy of genes, gut microbes, and metabolic role in ALD. The end stage is liver transplantation or death. This review may inspire a summary of the gut microbial genes, critical inflammatory molecules, oxidative stress, and metabolic routes, which will offer future promising therapeutic compounds in ALD.

New insight of chemical constituents in Persea americana fruit against obesity via integrated pharmacology.

Persea americana fruit (PAF) is a favorable nutraceutical resource that comprises diverse unsaturated fatty acids (UFAs). UFAs are significant dietary supplementation, as they relieve metabolic disorders, including obesity (OB). In another aspect, this study was focused on the anti-OB efficacy of the non-fatty acids (NFAs) in PAF through network pharmacology (NP). Natural product activity & species source (NPASS), SwissADME, similarity ensemble approach (SEA), Swiss target prediction (STP), DisGeNET, and online Mendelian inheritance in man (OMIM) were utilized to gather significant molecules and its targets. The crucial targets were adopted to construct certain networks: protein-protein interaction (PPI), PAF-signaling pathways-targets-compounds (PSTC) networks, a bubble chart, molecular docking assay (MDA), and density function theory (DFT). Finally, the toxicities of the key compounds were validated by ADMETlab 2.0 platform. All 41 compounds in PAF conformed to Lipinski's rule, and the key 31 targets were identified between OB and PAF. On the bubble chart, PPAR signaling pathway had the highest rich factor, suggesting that the pathway might be an agonism for anti-OB. Conversely, estrogen signaling pathway had the lowest rich factor, indicating that the mechanism might be antagonism against OB. Likewise, the PSTC network represented that AKT1 had the greatest degree value. The MDA results showed that AKT1-gamma-tocopherol, PPARA-fucosterol, PPARD-stigmasterol, (PPARG)-fucosterol, (NR1H3)-campesterol, and ILK-alpha-tocopherol formed the most stable conformers. The DFT represented that the five molecules might be promising agents via multicomponent targeting. Overall, this study suggests that the NFAs in PAF might play important roles against OB.

How Do Risk Evaluation and Mitigation Strategies Impact Clinical Practice? A National Survey of Physicians.

The US Food and Drug Administration can require risk evaluation and mitigation strategy (REMS) programs for prescription drugs to ensure the benefits of use outweigh the risks. We conducted a national survey of physicians' experiences prescribing eight REMS-covered drugs: (1) ambrisentan; (2) bosentan; (3) clozapine; (4) isotretinoin; (5-7) the multiple myeloma (MM) drugs lenalidomide, pomalidomide, thalidomide; and (8) sodium oxybate. Between May 2022 and January 2023, we surveyed 5,331 physician prescribers of these drugs, and 1,295 (24%) returned surveys (range: 149 for bosentan to 226 for MM drugs). Although 765 (68%) respondents thought the certification process provided useful drug information, 757 (67%) wanted materials to include benefit data and 944 (84%) non-REMS-related risk data. A majority (704, 63%) thought the safe use requirements facilitated discussion with patients, but a similar number (637, 57%) attributed delayed medication access to these requirements. In multivariable modeling, MM drug and isotretinoin respondents were less likely than sodium oxybate respondents to agree that the certification process provided useful drug information (MM drug: odds ratio (OR) = 0.37, 95% confidence interval (CI) = 0.25-0.55; isotretinoin: OR = 0.39, 95% CI = 0.25-0.61), and isotretinoin, clozapine, and bosetan respondents were more likely than sodium oxybate respondents to agree that the safe use requirements often delayed medication access (isotretinoin: OR = 5.83, 95% CI = 3.70-9.19; clozapine: OR = 1.65, 95% CI = 1.08-2.54; bosentan: OR = 1.78, 95% CI = 1.12-2.85). Most physicians believe REMS programs convey useful drug safety information and facilitate discussion with patients but also seek information on benefits and non-REMS-related risks and better integration of REMS processes into clinical workflows.

Trends in Use and Evidence of Adherence to Risk Evaluation and Mitigation Strategy Pregnancy Testing Requirements for Thalidomide, Lenalidomide, and Pomalidomide in the USA, 2000-2020.

INTRODUCTION: Lenalidomide, pomalidomide, and thalidomide are effective treatments for multiple myeloma but are teratogenic. To mitigate this risk, the US Food and Drug Administration (FDA) required risk evaluation and mitigation strategy (REMS) programs for these drugs, which include pregnancy testing among women of childbearing potential-twice before initiation, weekly in the first month on treatment, and every 2-4 weeks thereafter. OBJECTIVE: We evaluated dispensing trends of lenalidomide, pomalidomide, and thalidomide and assessed adherence to REMS pregnancy testing requirements among at-risk patients taking these drugs. METHODS: Using three US health insurance claims databases (Optum Clinformatics® [2004-2020], Merative Marketscan [2003-2019], and Medicaid [2000-2018]), we assessed monthly use of the drugs, patient characteristics and treatment persistence among drug initiators, and claims-based evidence for adherence to pregnancy testing requirements among initiators with child-bearing potential. RESULTS: Lenalidomide was the most prescribed agent following its approval in 2006 and through the end of the study period. A total of 48,311 lenalidomide (mean age = 59 years [standard deviation (SD) = 16]), 17,550 thalidomide (mean age = 65 years [SD = 12]), and 6560 pomalidomide initiators (mean age = 65 years [SD = 11]) were identified; 45% of initiators of each drug were women. Among initiators under follow-up on day 90, 70% were still on therapy. Initiators of childbearing potential comprised 3% (N = 1,920) of all initiators; among this cohort, 12% had evidence in claims data of two pregnancy tests before initiation, and 9% with at least 33 days of follow-up of four tests during the first month of treatment. By contrast, 52% who received a refill had claims-based evidence of a pregnancy test within 7 days of dispensing. CONCLUSION: Although most patients who initiated lenalidomide, pomalidomide, and thalidomide were not of child-bearing potential, further investigation into actual non-adherence to pregnancy testing is needed.

A consortium of Hordeum vulgare and gut microbiota against non-alcoholic fatty liver disease via data-driven analysis.

Despite many recent studies on non-alcoholic fatty liver disease (NAFLD) therapeutics, the optimal treatment has yet to be determined. In this unfinished project, we combined secondary metabolites (SMs) from the gut microbiota (GM) and Hordeum vulgare (HV) to investigate their combinatorial effects via network pharmacology (NP). Additionally, we analyzed GM or barley - signalling pathways - targets - metabolites (GBSTMs) in combinatorial perspectives (HV, and GM). A total of 31 key targets were analysed via a protein-protein interaction (PPI) network, and JUN was identified as the uppermost target in NAFLD. On a bubble plot, we revealed that apelin signalling pathway, which had the lowest enrichment factor antagonize NAFLD. Holistically, we scrutinized GBSTM to identify key components (GM, signalling pathways, targets, and metabolites) associated with the Apelin signalling pathway. Consequently, we found that the primary GMs (Eubacterium limosum, Eggerthella sp. SDG-2, Alistipes indistinctus YIT 12060, Odoribacter laneus YIT 12061, Paraprevotella clara YIT 11840, Paraprevotella xylaniphila YIT 11841) to ameliorate NAFLD. The molecular docking test (MDT) suggested that tryptanthrin-JUN is an agonist, conversely, dihydroglycitein-HDAC5, 1,3-diphenylpropan-2-ol-NOS1, and (10[(Acetyloxy)methyl]-9-anthryl)methyl acetate-NOS2, which are antagonistic conformers in the apelin signalling pathway. Overall, these results suggest that combination therapy could be an effective strategy for treating NAFLD.

Investigating the ability to adhere to cardiometabolic medications with different properties: a retrospective cohort study of >500 000 patients in the USA.

OBJECTIVE: Poor medication adherence remains highly prevalent and adversely affects health outcomes. Patients frequently describe properties of the pills themselves, like size and shape, as barriers, but this has not been evaluated objectively. We sought to determine the extent to which oral medication properties thought to be influential translate into lower objectively-measured adherence. DESIGN: Retrospective cohort study. SETTING: US nationwide commercial claims database, 2016-2019. PARTICIPANTS: Among patients initiating first-line hypertension, diabetes or hyperlipidaemia treatment based on clinical guidelines, we measured pill size, shape, colour and flavouring, number of pills/day and fixed-dose combination status as properties. OUTCOME MEASURES: Outcomes included discontinuation after the first fill (ie, never filling again over a minimum of 1-year follow-up) and long-term non-adherence (1-year proportion of days covered <0.80). We estimated associations between each property and outcomes, by therapeutic class (eg, statins), with multivariable logistic regression. RESULTS: Across 604 323 patients, 14.6% discontinued after filling once (ie, were non-persistent), and 54.0% were non-adherent over 1-year follow-up. Large pill size was associated with non-adherence, except for thiazides (eg, metformin adjusted OR (aOR): 1.12, 95% CI: 1.06 to 1.18). Greater pill burden was associated with a higher risk of non-adherence across all classes (eg, metformin aOR: 1.58, 95% CI: 1.53 to 1.64 for two pills/day). Taking less than one pill/day was also associated with higher risk of non-adherence and non-persistence (eg, non-persistence statin aOR: 1.29, 95% CI: 1.20 to 1.38). Pill shape, colour, flavouring and combination status were associated with mixed effects across classes. CONCLUSIONS: Pill burden and pill size are key properties affecting adherence for almost all classes; others, like size and combination, could modestly affect medication adherence. Clinical interventions could screen patients for potential intolerance to medication and potentially implement more convenient dosing schedules.

Utilization of P2Y12 Inhibitors in Older Adults With ST-Elevation Myocardial Infarction and Frailty.

Choosing optimal P2Y12 inhibitor in frail older adults is challenging because they are at increased risk of both ischemic and bleeding events. We conducted a retrospective cohort study of Medicare Advantage Plan beneficiaries who were prescribed clopidogrel, prasugrel, or ticagrelor after percutaneous coronary intervention-treated ST-elevation myocardial infarction from January 1, 2010 to December 31, 2020. Frailty was defined using claims-based frailty index ≥0.25. We conducted multivariable logistic regression to identify factors associated with using potent P2Y12 inhibitors and multivariable-adjusted competing risk analyses to compare the rate of discontinuation of potent P2Y12 inhibitors in frail versus non-frail patients. There were 11,239 patients (mean age 74 years, 39% women). The prevalence of cardiovascular and geriatric co-morbidities was as follows: 32% chronic kidney disease, 28% heart failure, 10% previous myocardial infarction, 6% dementia, 20% anemia, and 12% frailty. The proportion of patients receiving clopidogrel decreased from 78.3% in 2010 to 2013 to 42.1% in 2018 to 2020, with a concurrent increase in those receiving potent P2Y12 inhibitors (mostly ticagrelor) from 21.7% to 57.9%. Frailty was independently associated with reduced odds of initiation (odds ratio 0.78, 95% confidence interval 0.67 to 0.90) but not with discontinuation of potent P2Y12 inhibitors (subdistribution hazard ratio 1.09, 95% confidence interval 0.98 to 1.22). In conclusion, frail older adults are less likely to receive potent P2Y12 inhibitors after percutaneous coronary intervention-treated ST-elevation myocardial infarction, but they are as likely as non-frail patients to continue with the prescribed P2Y12 inhibitor.