Alzheimer's Disease Knowledge Graph Enhances Knowledge Discovery and Disease Prediction.

Background: Alzheimer's disease (AD), a progressive neurodegenerative disorder, continues to increase in prevalence without any effective treatments to date. In this context, knowledge graphs (KGs) have emerged as a pivotal tool in biomedical research, offering new perspectives on drug repurposing and biomarker discovery by analyzing intricate network structures. Our study seeks to build an AD-specific knowledge graph, highlighting interactions among AD, genes, variants, chemicals, drugs, and other diseases. The goal is to shed light on existing treatments, potential targets, and diagnostic methods for AD, thereby aiding in drug repurposing and the identification of biomarkers. Results: We annotated 800 PubMed abstracts and leveraged GPT-4 for text augmentation to enrich our training data for named entity recognition (NER) and relation classification. A comprehensive data mining model, integrating NER and relationship classification, was trained on the annotated corpus. This model was subsequently applied to extract relation triplets from unannotated abstracts. To enhance entity linking, we utilized a suite of reference biomedical databases and refine the linking accuracy through abbreviation resolution. As a result, we successfully identified 3,199,276 entity mentions and 633,733 triplets, elucidating connections between 5,000 unique entities. These connections were pivotal in constructing a comprehensive Alzheimer's Disease Knowledge Graph (ADKG). We also integrated the ADKG constructed after entity linking with other biomedical databases. The ADKG served as a training ground for Knowledge Graph Embedding models with the high-ranking predicted triplets supported by evidence, underscoring the utility of ADKG in generating testable scientific hypotheses. Further application of ADKG in predictive modeling using the UK Biobank data revealed models based on ADKG outperforming others, as evidenced by higher values in the areas under the receiver operating characteristic (ROC) curves. Conclusion: The ADKG is a valuable resource for generating hypotheses and enhancing predictive models, highlighting its potential to advance AD's disease research and treatment strategies.

Development of short forms for screening children's dental caries and urgent treatment needs using item response theory and machine learning methods.

OBJECTIVES: Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children. METHODS: This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations. RESULTS: We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses. CONCLUSIONS: The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Preparation of reversible cross-linked amphiphilic polymeric micelles with pH-responsive behavior for smart drug delivery.

A new type of reversible cross-linked and pH-responsive polymeric micelle (PM), poly[polyethylene glycol methacrylate-co-2-(acetoacetoxy)ethyl methacrylate]-b-poly [2-(dimethylamino)ethyl methacrylate] [P(PEGMA-co-AEMA)-b-PDMAEMA], was synthesized for targeted delivery of curcumin. After reversible cross-linking of the micellar shell, the PMs with a typical core-shell structure exhibited excellent stability against extensive dilution and good reversibility of pH-responsiveness in solutions with different pH values. P(PEGMA9-co-AEMA6)-b-PDMAEMA10 has the lowest critical micelle concentration (CMC) value (0.0041 mg mL-1), the highest loading capacity (13.86%) and entrapment efficiency (97.03%). A slow sustained drug release at pH 7.4 with 12.36% in 108 h, while a fast release (42.36%) was observed at pH 5.0. Furthermore, a dissipative particle dynamics (DPD) simulation method was employed to investigate the self-assembly process and pH-responsive behavior of PMs. The optimal drug-carrier ratio (2%) and fraction of water (92%) were confirmed by analyzing the drug distribution and morphology of micelles during the self-assembly process of the block copolymer. The simulation results were consistent with experimental results, indicating DPD simulation shows potential to study the structure properties of reversible cross-linked micelles. The present findings provide a new method for the development of SDDS with good structural stability and controlled drug release properties.

Adherence to Antiretrovirals and HIV Viral Suppression Under COVID-19 Pandemic Interruption - Findings from a Randomized Clinical Trial Using Ingestible Sensors to Monitor Adherence.

The COVID-19 pandemic had a significant impact on vulnerable populations, including people living with HIV. California implemented a coronavirus lockdown (stay-at-home order) in March 2020, which ended in January 2021. We evaluated the pandemic's impact on both clinical outcomes of HIV RNA viral load (VL) and retention rate in a randomized clinical trial conducted from May 2018 to October 2020. The intervention group took co-encapsulated antiretrovirals (ARVs) with ingestible sensor (IS) pills from baseline through week 16. The IS system has the capacity to monitor adherence in real-time using a sensor patch, a mobile device, and supporting software. Both the IS and usual care (UC) groups were followed monthly for 28 weeks. Longitudinal mixed-effects models with random intercept and slope (RIAS) were used to fit log VL and self-reported adherence. The sample size of the study was 112 (54 in IS). Overall, the retention rate at week 28 was 86%, with 90% before the lockdown and 83% after the lockdown. The lockdown strengthened the associations between adherence and VL. Before the lockdown, a 10% increase in adherence was associated with a 0.2 unit decrease in log VL (ß = -1.88, p = 0.004), while during the lockdown, the association was a 0.41-unit decrease (ß = -2.27, p = 0.03). The pandemic did not have a significant impact on our adherence-focused intervention. Our findings regarding the intervention effect remain valid. TRIAL REGISTRATION NUMBER: NCT02797262. Date registration: September 2015.

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images.

Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is known about the phenotypic and genetic links of heart-brain systems. We quantified heart-brain connections using multiorgan magnetic resonance imaging (MRI) data from more than 40,000 subjects. Heart MRI traits displayed numerous association patterns with brain gray matter morphometry, white matter microstructure, and functional networks. We identified 80 associated genomic loci (P < 6.09 × 10-10) for heart MRI traits, which shared genetic influences with cardiovascular and brain diseases. Genetic correlations were observed between heart MRI traits and brain-related traits and disorders. Mendelian randomization suggests that heart conditions may causally contribute to brain disorders. Our results advance a multiorgan perspective on human health by revealing heart-brain connections and shared genetic influences.

ETS2 promotes cardiomyocyte apoptosis and autophagy in heart failure by regulating lncRNA TUG1/miR-129-5p/ATG7 axis.

Heart failure (HF) is a chronic disease in which the heart is unable to provide enough blood and oxygen to the peripheral tissues. Cardiomyocyte apoptosis and autophagy have been linked to HF progression. However, the underlying mechanism of HF is unknown. In this study, H2 O2 -treated AC16 cells were used as a cell model of HF. The mRNA and protein levels of related genes were examined using RT-qPCR and western blot. Cell viability and apoptosis were assessed using CCK-8 and flow cytometry, respectively. The interactions between ETS2, TUG1, miR-129-5p, and ATG7 were validated by luciferase activity, ChIP, and RNA-Binding protein Immunoprecipitation assays. According to our findings, H2 O2 stimulation increased the expression of ETS2, TUG1, and ATG7 while decreasing the expression of miR-129-5p in AC16 cells. Furthermore, H2 O2 stimulation induced cardiomyocyte apoptosis and autophagy, which were reversed by ETS2 depletion, TUG1 silencing, or miR-129-5p upregulation. Mechanistically, ETS2 promoted TUG1 expression by binding to the TUG1 promoter, and TUG1 sponged miR-129-5p to increase ATG7 expression. Furthermore, TUG1 overexpression reversed ETS2 knockdown-mediated inhibition of cardiomyocyte apoptosis and autophagy and miR-129-5p inhibition abolished TUG1 depletion-mediated suppression of cardiomyocyte apoptosis and autophagy in H2 O2 -induced AC16 cells. As presumed, ATG7 overexpression reversed miR-129-5p mimics-mediated repression of cardiomyocyte apoptosis and autophagy in H2 O2 -induced AC16 cells. Finally, ETS2 silencing reduced cardiomyocyte apoptosis and autophagy to slow HF progression by targeting the ETS2/TUG1/miR-129-5p/ATG7 axis, which may provide new therapeutic targets for HF treatment.

LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures.

Over the past 30 years, magnetic resonance imaging has become a ubiquitous tool for accurately visualizing the change and development of the brain's subcortical structures (e.g., hippocampus). Although subcortical structures act as information hubs of the nervous system, their quantification is still in its infancy due to many challenges in shape extraction, representation, and modeling. Here, we develop a simple and efficient framework of longitudinal elastic shape analysis (LESA) for subcortical structures. Integrating ideas from elastic shape analysis of static surfaces and statistical modeling of sparse longitudinal data, LESA provides a set of tools for systematically quantifying changes of longitudinal subcortical surface shapes from raw structure MRI data. The key novelties of LESA include: (i) it can efficiently represent complex subcortical structures using a small number of basis functions and (ii) it can accurately delineate the spatiotemporal shape changes of the human subcortical structures. We applied LESA to analyze three longitudinal neuroimaging data sets and showcase its wide applications in estimating continuous shape trajectories, building life-span growth patterns, and comparing shape differences among different groups. In particular, with the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we found that the Alzheimer's Disease (AD) can significantly speed the shape change of ventricle and hippocampus from 60 to 75 years old compared with normal aging.

An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank.

Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).

Therapeutic effect of sodium­glucose cotransporter 2 inhibitor and benazepril on diabetic nephropathic rats.

The present study aimed to compare the therapeutic effect of sodium/glucose cotransporter 2 (SGLT2) inhibitor and benazepril on diabetic nephropathy (DN) rats and provide a potential novel agent for the clinical treatment of DN. The DN model was established on rats. Animals were dosed orally with SGLT2 and benazepril daily for 4 weeks. The pathological state of renal tissues were evaluated using hematoxylin and eosin, Masson and periodic acid-Schiff staining. The change in the morphology of renal tissues was observed through transmission electron microscopy. Western blotting was utilized to determine the expression level of TGF-ß, N-terminal fragment of the B-type natriuretic peptide precursor (NT-proBNP) and matrix metalloproteinase-9 (MMP-9). The expression level of endothelin 1 (ET-1), von Willebrand factor (vWF), collagen (col)-I and α smooth muscle actin (α-SMA) in renal tissues was visualized using immunohistochemical assay. Significant pathological changes in the glomerular basement membrane, mesangial membrane, renal tubules, lumen, renal interstitial region and renal tubular epithelial cells were observed in DN rats, accompanied by increased collagen fibers. SGLT2 inhibitor treatment demonstrated more alleviatory effects on the pathological changes of renal tissues compared with benazepril. Compared with control, TGF-ß and NT-proBNP were upregulated in DN rats, accompanied by the downregulation of MMP-9, ET-1, vWF, col-I and α-SMA, which were markedly reversed by treatment with SGLT2 inhibitor and benazepril. Compared with benazepril, the effects of SGLT2 inhibitor on the expression level of TGF-ß, NT-proBNP, MMP-9, ET-1, vWF, col-I and α-SMA were more significant. Overall, SGLT2 inhibitor demonstrated an increased therapeutic effect against DN rats compared with benazepril by regulating cytokines, renal fibrosis and extracellular matrix degradation.

Fagopyrum dibotrys extract alleviates hepatic steatosis and insulin resistance, and alters autophagy and gut microbiota diversity in mouse models of high-fat diet-induced non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is a major global health concern with increasing prevalence, with a lack of currently available effective treatment options; thus, the investigation of novel therapeutic approaches is necessary. The study aimed to investigate the outcomes and mechanisms of action of Fagopyrum dibotrys extract (FDE) in a high-fat diet (HFD)-induced mouse model of obesity. The findings showed that FDE supplementation attenuated glucose tolerance, insulin resistance (IR), hepatic steatosis, and abnormal lipid metabolism. In addition, FDE also promoted autophagic activity and inhibited the phosphorylation of transcription factor EB in HFD-fed mice. Furthermore, gut microbiota characterization via 16S rRNA sequencing revealed that the supplementation of FDE increased Bacteroidetes and Verrucomicrobia populations while decreased Firmicutes, thus modifying the gut microbiome. FDE also increased the relative abundance of Akkermansia. Our findings suggest that FDE may protect against HFD-induced NAFLD by activating autophagy and alleviating dysbiosis in the gut microbiome. FDE may be beneficial as a nutraceutical treatment for NAFLD.

Ingestible sensor system for measuring, monitoring and enhancing adherence to antiretroviral therapy: An open-label, usual care-controlled, randomised trial.

BACKGROUND: Co-encapsulated antiretrovirals (ARVs) with ingestible sensor (IS) has the capacity to monitor adherence in real-time using a sensor patch, a mobile device, and supporting software. We evaluated the acceptability, effectiveness, and sustainability of the IS system with real-time text reminders. METHODS: Participants were recruited from HIV clinics in Los Angeles and were randomised 1:1 to IS or usual care (UC) group. Adherence to ARVs (primary outcome) was measured by IS system (IS group only), plasma ARV concentration, and self-report. IS-measured adherence was clustered by group-based trajectory model and was validated by ARV concentration summarized by integrated pharmacokinetic adherence measure (IPAM) score. HIV RNA viral load (VL) was compared between IS and UC group. FINDINGS: A total of 112 (IS = 54, UC = 58) participants who completed baseline with at least one follow-up data collection were included in analyses. Overall satisfaction rate for the IS system was >90%. The IPAM score was higher (0.018, 95% CI: -0.098-0.134, p = 0.75) and VL decayed faster (-0.020, 95% CI: -0.042-0.002, p = 0.08) in the IS group compared with the UC group. The ingestible sensor system was well tolerated by study participants. INTERPRETATION: The IS system was well accepted by participants and its use was associated with improved adherence and lower HIV RNA VL. The findings provide a potentially effective strategy for improving adherence. FUNDING: This work was supported by grant R01-MH110056 from the National Institute of Mental Health (NIMH)/National Institutes of Health (NIH). Y. Wang was in part supported by the NIMH/NIH award T32MH080634. E. Daar was in part supported by the National Center for Advancing Translational Sciences through UCLACTSI Grant UL1TR001881. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Quantitative data collection approaches in subject-reported oral health research: a scoping review.

BACKGROUND: This scoping review reports on studies that collect survey data using quantitative research to measure self-reported oral health status outcome measures. The objective of this review is to categorize measures used to evaluate self-reported oral health status and oral health quality of life used in surveys of general populations. METHODS: The review is guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) with the search on four online bibliographic databases. The criteria include (1) peer-reviewed articles, (2) papers published between 2011 and 2021, (3) only studies using quantitative methods, and (4) containing outcome measures of self-assessed oral health status, and/or oral health-related quality of life. All survey data collection methods are assessed and papers whose methods employ newer technological approaches are also identified. RESULTS: Of the 2981 unduplicated papers, 239 meet the eligibility criteria. Half of the papers use impact scores such as the OHIP-14; 10% use functional measures, such as the GOHAI, and 26% use two or more measures while 8% use rating scales of oral health status. The review identifies four data collection methods: in-person, mail-in, Internet-based, and telephone surveys. Most (86%) employ in-person surveys, and 39% are conducted in Asia-Pacific and Middle East countries with 8% in North America. Sixty-six percent of the studies recruit participants directly from clinics and schools, where the surveys were carried out. The top three sampling methods are convenience sampling (52%), simple random sampling (12%), and stratified sampling (12%). Among the four data collection methods, in-person surveys have the highest response rate (91%), while the lowest response rate occurs in Internet-based surveys (37%). Telephone surveys are used to cover a wider population compared to other data collection methods. There are two noteworthy approaches: 1) sample selection where researchers employ different platforms to access subjects, and 2) mode of interaction with subjects, with the use of computers to collect self-reported data. CONCLUSION: The study provides an assessment of oral health outcome measures, including subject-reported oral health status and notes newly emerging computer technological approaches recently used in surveys conducted on general populations. These newer applications, though rarely used, hold promise for both researchers and the various populations that use or need oral health care.

Pediatric patients with familially inherited sitosterolemia: Two case reports.

Background: Sitosterolemia is a rare recessive genetic abnormality of hyperlipidemia; it is characterized by increased levels and accumulation of sitosterol in the plasma and local tissues. Case descriptions: The study subjects were two siblings (brother and sister) who had sitosterolemia with systemic multiple xanthomas as the main manifestation. The main clinical manifestations were hypercholesterolemia, premature atherosclerosis, arrhythmia, systemic multiple xanthomas, etc. After genetic testing, it was found that the patients had a compound heterozygous mutation of c.1324+1de1G in exon 7 and exon 9 of chromosome 2p21 of the adenosine triphosphate binding cassette transporter G family member 5(ABCG5) gene; the mutation at c.904+1G>A was of maternal origin, and the mutation at c. 1324+1de1G was of paternal origin. The compound heterozygous mutation of these two genes led to a metabolic disorder of plant sterols in vivo. Conclusion: Sitosterolemia is an autosomal recessive disease that could be effectively controlled after dietary control and oral lipid-lowering therapy with Ezetimibe. Xanthomas, which affects function and appearance, could be surgically removed, and primary wound healing could be achieved.

The ATEAM study: Advances in technology to enhance PrEP adherence monitoring (ATEAM) among young men who have sex with men.

Young age has consistently correlated with lower adherence to pre-exposure prophylaxis (PrEP) in young men who have sex with men (YMSM). Digital medicine, a dynamic healthcare platform of wearable physiological sensors and mobile communication technology that can respond to medication nonadherence rapidly, has the potential in promoting PrEP adherence. We evaluated the feasibility and acceptability of Proteus Discover, a digital monitoring adherence system, to measure PrEP adherence and provide real-time feedback among cisgender YMSM and transgender women. One hundred HIV-negative young men and transgender women ages 16-24 years were enrolled in a 24-week randomized controlled crossover study to tenofovir disoproxil fumarate with emtricitabine (TDF/FTC) coencapsulated with Proteus Discover versus TDF/FTC standard-of-care. Participants in the 12-week Proteus Discover arm received weekly SMS text messages to promote pill taking based on Proteus Discover adherence data. Dried blood spots (DBS) were collected at 4-week intervals for tenofovir diphosphate (TFV-DP) in red blood cells as the referent and questionnaires were completed to assess acceptability, usability, and patterns of use. Linear mixed models analyzed the relationship between 30-day adherence measured by DBS and Proteus Discover. PrEP adherence was high overall. Adherence, as measured by DBS, was correlated with adherence as measured by Proteus Discover (p value = 0.03). Most participants reported that Proteus Discover helped them take their PrEP daily and that the system was easy to use. However, a majority (53.5%-60.5%) disagreed with the statement that wearing the patch was not an issue. There was an incremental increase in TFV-DP in DBS with adherence by Proteus Discover. More research is warranted to explore optimizing PrEP adherence for youth through real-time monitoring.

Investigating Perceptions of Teachers and School Nurses on Child and Adolescent Oral Health in Los Angeles County.

This study reports the results of focus groups with school nurses and teachers from elementary, middle, and high schools to explore their perceptions of child and adolescent oral health. Participants included 14 school nurses and 15 teachers (83% female; 31% Hispanic; 21% White; 21% Asian; 14% African American; and 13% Others). Respondents were recruited from Los Angeles County schools and scheduled by school level for six one-hour focus groups using Zoom. Audio recordings were transcribed, reviewed, and saved with anonymization of speaker identities. NVivo software (QSR International, Melbourne, Australia) was used to facilitate content analysis and identify key themes. The nurses' rate of "Oral Health Education" comments statistically exceeded that of teachers, while teachers had higher rates for "Parental Involvement" and "Mutual Perception" comments. "Need for Care" was perceived to be more prevalent in immigrants to the United States based on student behaviors and complaints. "Access to Care" was seen as primarily the nurses' responsibilities. Strong relationships between community clinics and schools were viewed by some as integral to students achieving good oral health. The results suggest dimensions and questions important to item development for oral health surveys of children and parents to address screening, management, program assessment, and policy planning.

Common variants contribute to intrinsic human brain functional networks.

The human brain forms functional networks of correlated activity, which have been linked with both cognitive and clinical outcomes. However, the genetic variants affecting brain function are largely unknown. Here, we used resting-state functional magnetic resonance images from 47,276 individuals to discover and validate common genetic variants influencing intrinsic brain activity. We identified 45 new genetic regions associated with brain functional signatures (P < 2.8 × 10-11), including associations to the central executive, default mode, and salience networks involved in the triple-network model of psychopathology. A number of brain activity-associated loci colocalized with brain disorders (e.g., the APOE ε4 locus with Alzheimer's disease). Variation in brain function was genetically correlated with brain disorders, such as major depressive disorder and schizophrenia. Together, our study provides a step forward in understanding the genetic architecture of brain functional networks and their genetic links to brain-related complex traits and disorders.

Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7.

BACKGROUND: Dental caries is the most common chronic childhood infectious disease and is a serious public health problem affecting both developing and industrialized countries, yet it is preventable in most cases. This study evaluated the potential of screening for dental caries among children using a machine learning algorithm applied to parent perceptions of their child's oral health assessed by survey. METHODS: The sample consisted of 182 parents/caregivers and their children 2-7 years of age living in Los Angeles County. Random forest (a machine learning algorithm) was used to identify survey items that were predictors of active caries and caries experience. We applied a three-fold cross-validation method. A threshold was determined by maximizing the sum of sensitivity and specificity conditional on the sensitivity of at least 70%. The importance of survey items to classifying active caries and caries experience was measured using mean decreased Gini (MDG) and mean decreased accuracy (MDA) coefficients. RESULTS: Survey items that were strong predictors of active caries included parent's age (MDG = 0.84; MDA = 1.97), unmet needs (MDG = 0.71; MDA = 2.06) and the child being African American (MDG = 0.38; MDA = 1.92). Survey items that were strong predictors of caries experience included parent's age (MDG = 2.97; MDA = 4.74), child had an oral health problem in the past 12 months (MDG = 2.20; MDA = 4.04) and child had a tooth that hurt (MDG = 1.65; MDA = 3.84). CONCLUSION: Our findings demonstrate the potential of screening for active caries and caries experience among children using surveys answered by their parents.

Common genetic variation influencing human white matter microstructure.

Brain regions communicate with each other through tracts of myelinated axons, commonly referred to as white matter. We identified common genetic variants influencing white matter microstructure using diffusion magnetic resonance imaging of 43,802 individuals. Genome-wide association analysis identified 109 associated loci, 30 of which were detected by tract-specific functional principal components analysis. A number of loci colocalized with brain diseases, such as glioma and stroke. Genetic correlations were observed between white matter microstructure and 57 complex traits and diseases. Common variants associated with white matter microstructure altered the function of regulatory elements in glial cells, particularly oligodendrocytes. This large-scale tract-specific study advances the understanding of the genetic architecture of white matter and its genetic links to a wide spectrum of clinical outcomes.

Pandemic velocity: Forecasting COVID-19 in the US with a machine learning & Bayesian time series compartmental model.

Predictions of COVID-19 case growth and mortality are critical to the decisions of political leaders, businesses, and individuals grappling with the pandemic. This predictive task is challenging due to the novelty of the virus, limited data, and dynamic political and societal responses. We embed a Bayesian time series model and a random forest algorithm within an epidemiological compartmental model for empirically grounded COVID-19 predictions. The Bayesian case model fits a location-specific curve to the velocity (first derivative) of the log transformed cumulative case count, borrowing strength across geographic locations and incorporating prior information to obtain a posterior distribution for case trajectories. The compartmental model uses this distribution and predicts deaths using a random forest algorithm trained on COVID-19 data and population-level characteristics, yielding daily projections and interval estimates for cases and deaths in U.S. states. We evaluated the model by training it on progressively longer periods of the pandemic and computing its predictive accuracy over 21-day forecasts. The substantial variation in predicted trajectories and associated uncertainty between states is illustrated by comparing three unique locations: New York, Colorado, and West Virginia. The sophistication and accuracy of this COVID-19 model offer reliable predictions and uncertainty estimates for the current trajectory of the pandemic in the U.S. and provide a platform for future predictions as shifting political and societal responses alter its course.

Toxicity evaluation of mesoporous silica particles Santa Barbara No. 15 amorphous in human umbilical vein endothelial cells: influence of particle morphology.

Morphology plays a vital role in determining the biological effects of silica nanoparticles (NPs), but its influence on the toxicity of silica NPs in endothelial cells (ECs) is still inconclusive. We synthesized five kinds of Santa Barbara 15 amorphous (SBA-15) particles with different shapes and added them to human umbilical vein endothelial cells (HUVEC). After 24 After incubation and treatment with 100 ml, more than 80% of the cells are still alive. The microgram/ml of SBA-15 indicates that SBA-15 has high biocompatibility. Fibrous SBA-15 (5) leads to the highest Si element concentration in HUVEC. No NP reduces the release of NO, and NO is an important signaling molecule in the vascular system. Only the aggregated spherical SBA-15 (3) will moderately reduce the endothelial nitric oxide synthase (eNOS) protein. Regarding transcription factors regulating eNOS, we found that all SBA-15 types significantly increased Kruppel-like factor 2 (KLF2) protein, irregular SBA-15 (1), non-aggregated spherical SBA-15 (2) and aggregation The spherical SBA-15 (3) greatly reduces KLF4 by more than 50%. Overall, our results indicate that SBA-15 with different morphologies can be internalized into HUVEC and only cause moderate cytotoxicity. All silica NPs have the smallest effect on the NO-eNOS pathway, but the irregular spherical SBA-15 reduces the eNOS modifier KLF4. The rod-shaped SBA-15 (4) seems to have higher biocompatibility because they are internalized and have negligible adverse effects on HUVEC. These results provide new evidence for the toxic effects of different forms of silica nanoparticles on HUVEC.