Martin C. Nwadiugwu

Background: Alzheimer's disease (AD) is a growing healthcare crisis with limited effective therapies. This study aims to identify new candidate drugs that can be repurposed using key transcriptional regulators (DERs) in AD as therapeutic targets. Methods: Multi‐cohort single‐nucleus RNA sequencing (snRNA‐seq) data from the prefrontal cortex were analysed to identify DERs. Molecular docking and dynamic simulations analysis evaluated interactions between DERs and 2200 Food and Drug Administration‐approved drugs to assess binding stability, whilst pharmacokinetic parameters relevant to blood–brain barrier permeability were evaluated. Results: We identified 20 key DERs associated with AD. Lasmiditan stood out as the most promising drug amongst other drug candidates (Vorapaxar, Bictegravir, Tonaftate, Fluspirilene, Lisuride, Olaparib) interacting with five DERs: ZEB2, APP, PAX6, ETV6, and ST18. Lasmiditan–ETV6 complex showed the best binding stability (RMSD: 2.98 Å, H‐bonds: 68.38) and optimal passive diffusion (Log P 3–4, TPSA 60–75 Å ² ). Discussion: Lasmiditan is a potential AD therapeutic candidate that warrants further preclinical validation. Key points: 20 key transcriptional regulators (DERs) were identified linked to AD in myeloid, and neuronal cell populations. The DERs correlated with Braak stage, APOE genotype, and aging. ETV6 is a potentially viable therapeutic target due to its ability to form stable and strongly interacting complexes across multiple drugs. Lasmiditan showed the strongest binding to ETV6 (RMSD: 2.98 Å, H‐bonds: 68.38) and optimal blood‐brain‐barrier (BBB) penetration (Log P 3–4, TPSA 60–75). Lasmiditan is a potentially promising AD therapeutic candidate that warrants further preclinical validation.

Current treatments for Alzheimer’s disease (AD) focus on slowing memory and cognitive decline, but none offer curative outcomes. This study aims to explore and curate the common properties of active, drug-like molecules that modulate glycogen synthase kinase 3β (GSK-3β), a well-documented kinase with increased activity in tau hyperphosphorylation and neurofibrillary tangles—hallmarks of AD pathology. Leveraging quantitative structure–activity relationship (QSAR) data from the PubChem and ChEMBL databases, we employed seven machine learning models: logistic regression (LogR), k-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB), neural networks (NNs), and ensemble majority voting. Our goal was to correctly predict active and inactive compounds that inhibit GSK-3β activity and identify their key properties. Among the six individual models, the NN demonstrated the highest performance with a 79% AUC-ROC on unbalanced external validation data, while the SVM model was superior in accurately classifying the compounds. The SVM and RF models surpassed NN in terms of Kappa values, and the ensemble majority voting model demonstrated slightly better accuracy to the NN on the external validation data. Feature importance analysis revealed that hydrogen bonds, phenol groups, and specific electronic characteristics are important features of molecular descriptors that positively correlate with active GSK-3β inhibition. Conversely, structural features like imidazole rings, sulfides, and methoxy groups showed a negative correlation. Our study highlights the significance of structural, electronic, and physicochemical descriptors in screening active candidates against GSK-3β. These predictive features could prove useful in therapeutic strategies to understand the important properties of GSK-3β candidate inhibitors that may potentially benefit non-amyloid-based AD treatments targeting neurofibrillary tangles.

The devastating effects of Alzheimer’s disease (AD) are yet to be ameliorated due to the absence of curative treatment options. AD is an aging-related disease that affects cognition, and molecular imbalance is one of its hallmarks. There is a need to identify common causes of molecular imbalance in AD and their potential mechanisms for continuing research. A narrative synthesis of molecular mechanisms in AD from primary studies that employed single-cell sequencing (scRNA-seq) or spatial genomics was conducted using Embase and PubMed databases. We found that differences in molecular mechanisms in AD could be grouped into four key categories: sex-specific features, early-onset features, aging, and immune system pathways. The reported causes of molecular imbalance were alterations in bile acid (BA) synthesis, PITRM1, TREM2, olfactory mucosa (OM) cells, cholesterol catabolism, NFkB, double-strand break (DSB) neuronal damage, P65KD silencing, tau and APOE expression. What changed from previous findings in contrast to results obtained were explored to find potential factors for AD-modifying investigations.

The Fast Healthcare Interoperability Resources (FHIR) standard is increasingly being adopted for healthcare data exchange in the United States and globally, but an overall picture of the applications (apps) that implement the standard is not well known. This study aimed to provide a preliminary assessment of real-world FHIR apps’ clinical, technical, and implementation characteristics. To achieve this aim, we (1) searched digital repositories and libraries containing FHIR apps, (2) extracted the app name, source, and developer contact information, and (3) collected information about the apps via an electronic survey of FHIR app developers and implementers. Respondents reported a variety of health domains, terminologies, FHIR specifications, and types of developing organizations for the 112 apps about which we received information. Apps were increasingly introduced from 2012 to 2022, and most focused on clinical care (n = 74) or research (n = 45). The majority were stand-alone web-based (n = 67) or embedded within an electronic health record (n = 51). Of the many health domains covered, cardiovascular care was the most common (n = 28). Half (n = 56) were implemented across multiple health settings, highlighting FHIR’s substitutable nature. Overall, this study demonstrates the momentum around FHIR, the diversity of FHIR apps, and the need for a robust global FHIR app repository.

The underlying state of alterations in adipose tissue is hypothesized to be as a result of age-related changes. Young and aged mice have been documented to show distinct gene expression and distinct macrophage-specific adipose tissue regulation. However, more biological understanding is required to know the processes associated with these conditions in relation to the aging process. Transcriptional profiling with RNA-seq analysis was used to determine differentially expressed genes in young (2 months old) and aged (20 months old) mice macrophage-enriched phagocytic stromal vascular fractions of pooled epididymal white adipose tissue using data obtained from gene expression omnibus. Results showed distinct differentially expressed genes in young and aged mice with a p value cutoff of 0.05 and dissimilarities in the young and aged epididymal white adipose tissue phagocytic cells. Functional enrichment showed activation of cytokine–cytokine receptor interaction pathways, phosphorus metabolic processes and inflammatory pathways such as IL-17, TNF, NF-kappa B, and TGF-β, while AMPK, PPAR and oxidative phosphorylation were suppressed. The analysis showed that aging is linked with phagocytic cell decline, accumulated cellular damages, inflammation, immunosenescence and increased phosphorus metabolism. Interventions that reduce phosphate-containing compound could improve phosphorus metabolism in old age to prolong lifespan and better health.

Fortifying our preparedness to cope with biological threats by identifying and targeting virulence factors may be a preventative strategy for curtailing infectious disease outbreak. Virulence factors evoke successful pathogenic invasion, and the science and technology of genomics offers a way of identifying them, their agents and evolutionary ancestor. Genomics offers the possibility of deciphering if the release of a pathogen was intentional or natural by observing sequence and annotated data of the causative agent, and evidence of genetic engineering such as cloned vectors at restriction sites. However, to leverage and maximise the application of genomics to strengthen global interception system for real-time biothreat diagnostics, a complete genomic library of pathogenic and non-pathogenic agents will create a robust reference assembly that can be used to screen, characterise, track and trace new and existing strains. Encouraging ethical research sequencing pathogens found in animals and the environment, as well as creating a global space for collaboration will lead to effective global regulation and biosurveillance.

Glycemic variability (GV) is an obstacle to effective blood glucose control and an autonomous risk factor for diabetes complications. We, therefore, explored sample data of patients with diabetes mellitus who maintained better amplitude of glycemic fluctuations and compared their disease outcomes with groups having poor control. A retrospective study was conducted using electronic data of patients having hemoglobin A1C (HbA1c) values with five recent time points from Think Whole Person Healthcare (TWPH). The control variability grid analysis (CVGA) plot and coefficient of variability (CV) were used to identify and cluster glycemic fluctuation. We selected important variables using LASSO. Chi-Square, Fisher’s exact test, Bonferroni chi-Square adjusted residual analysis, and multivariate Kruskal–Wallis tests were used to evaluate eventual disease outcomes. Patients with very high CV were strongly associated (p < 0.05) with disorders of lipoprotein (p = 0.0014), fluid, electrolyte, and acid–base balance (p = 0.0032), while those with low CV were statistically significant for factors influencing health status such as screening for other disorders (p = 0.0137), long-term (current) drug therapy (p = 0.0019), and screening for malignant neoplasms (p = 0.0072). Reducing glycemic variability may balance alterations in electrolytes and reduce differences in lipid profiles, which may assist in strategies for managing patients with diabetes mellitus.

As social media influence become increasingly popular, understanding why some posts are highly followed than others, especially from the perspective of those leading the discussion allows us to gain insight on how followership is being influenced. A qualitative study of eight participants leading active discussions on Quora was conducted using semi-structured in-depth interviews, followed by thematic analysis. The open coding method was used to iteratively code related answers to develop themes. Results suggest that copyright tactics, controversial answers and sharing new information are some of the mechanisms for influencing followership. These mechanisms are built overtime through conscious strong engagement and by writing a consistently well-thought-out answer. The motivation for leading and writing answers on Quora were more intrinsic than extrinsic, and most participants believed influencing followership should not be a concern if one has the right message.

Background: Diabetes is a long-term condition that can be treated and controlled but do not yet have a cure; it could be induced by inflammation and the goal of managing it is to prevent additional co-morbidities and reduce glycemic fluctuations. There is a need to examine inflammatory activities in diabetes-related angiopathies and explore interventions that could reduce the risk for future outcome or ameliorate its effects to provide insights for improved care and management strategies.Method: The study was conducted in Embase (1946–2020), Ovid Medline (1950–2020), and PubMed databases (1960–2020) using the PICO framework. Primary studies (randomized controlled trials) on type 2 diabetes mellitus and inflammatory activities in diabetes-related angiopathies were included. Terms for the review were retrieved from the Cochrane library and from PROSPERO using its MeSH thesaurus qualifiers. Nine articles out of 454 total hits met the eligibility criteria. The quality assessment for the selected study was done using the Center for Evidence-Based Medicine Critical Appraisal Sheet.Results: Data analysis showed that elevated CRP, TNF-α, and IL-6 were the most commonly found inflammatory indicator in diabetes-related angiopathies, while increased IL-10 and soluble RAGE was an indicator for better outcome. Use of drugs such as salsalate, pioglitazone, simvastatin, and fenofibrate but not glimepiride or benfotiamine reported a significant decrease in inflammatory events. Regular exercise and consumption of dietary supplements such as ginger, hesperidin which have anti-inflammatory properties, and those containing prebiotic fibers (e.g., raspberries) revealed a consistent significant (p < 0.05) reduction in inflammatory activities.Conclusion: Inflammatory activities are implicated in diabetes-related angiopathies; regular exercise, the intake of healthy dietary supplements, and medications with anti-inflammatory properties could result in improved protective risk outcome for diabetes patients by suppressing inflammatory activities and elevating anti-inflammatory events.

There has been increased focus on clinically managing multi-morbidity in the older population, but it can be challenging to find appropriate paradigm that addresses the socio-economic burden and risk for polypharmacy. The Commission on Social Determinants of Health (CSDH) has examined the need for institutional change and the parallel need to address the social causes of poor health. This study explored three potential interventions namely, meaningful information from electronic health records (EHR), social prescribing, and redistributive welfare policies from a person-centered perspective using the CARE (connecting, assessing, responding, and empowering) approach. Economic instruments that immediately redistribute state welfare and reduce income disparity such as direct taxation and conditional cash transfers could be adopted to enable older people with long-term conditions have access to healthcare services. Decreased socioeconomic inequality and unorthodox prescriptive interventions that reduce polypharmacy could mitigate barriers to effectively manage the complexities of multi-morbidity.