Discovery of Hypoxanthine and Inosine as Robust Biomarkers for Predicting the Preanalytical Quality of Human Plasma and Serum for Metabolomics.

In cold human blood, the anomalous dynamics of adenosine triphosphate (ATP) result in the progressive accumulation of adenosine diphosphate (ADP), adenosine monophosphate (AMP), inosine monophosphate (IMP), inosine, and hypoxanthine. While the ATP, ADP, AMP, and IMP are confined to red blood cells (RBCs), inosine and hypoxanthine are excreted into plasma/serum. The plasma/serum levels of inosine and hypoxanthine depend on the temperature of blood and the plasma/serum contact time with the RBCs, and hence they represent robust biomarkers for evaluating the preanalytical quality of plasma/serum. These biomarkers are highly specific since they are generally absent or at very low levels in fresh plasma/serum and are highly sensitive since they are derived from ATP, one of the most abundant metabolites in blood. Further, whether blood was kept at room temperature or on ice could be predicted based on inosine levels. An analysis of >2000 plasma/serum samples processed for metabolomics-centric analyses showed alarmingly high levels of inosine and hypoxanthine. The results highlight the gravity of sample quality challenges with high risk of grossly inaccurate measurements and incorrect study outcomes. The discovery of these robust biomarkers provides new ways to address the longstanding and underappreciated preanalytical sample quality challenges in the blood metabolomics field.

Multi-output prediction of dose-response curves enables drug repositioning and biomarker discovery.

Drug response prediction is hampered by uncertainty in the measures of response and selection of doses. In this study, we propose a probabilistic multi-output model to simultaneously predict all dose-responses and uncover their biomarkers. By describing the relationship between genomic features and chemical properties to every response at every dose, our multi-output Gaussian Process (MOGP) models enable assessment of drug efficacy using any dose-response metric. This approach was tested across two drug screening studies and ten cancer types. Kullback-leibler divergence measured the importance of each feature and identified EZH2 gene as a novel biomarker of BRAF inhibitor response. We demonstrate the effectiveness of our MOGP models in accurately predicting dose-responses in different cancer types and when there is a limited number of drug screening experiments for training. Our findings highlight the potential of MOGP models in enhancing drug development pipelines by reducing data requirements and improving precision in dose-response predictions.

Cluster of Influenza A(H5) Cases Associated with Poultry Exposure at Two Facilities - Colorado, July 2024.

Persons who work in close contact with dairy cattle and poultry that are infected with highly pathogenic avian influenza (HPAI) A(H5N1) virus are at increased risk for infection. In July 2024, the Colorado Department of Public Health & Environment responded to two poultry facilities with HPAI A(H5N1) virus detections in poultry. Across the two facilities, 663 workers assisting with poultry depopulation (i.e., euthanasia) received screening for illness; 109 (16.4%) reported symptoms and consented to testing. Among those who received testing, nine (8.3%) received a positive influenza A(H5) virus test result, and 19 (17.4%) received a positive SARS-CoV-2 test result. All nine workers who received positive influenza A(H5) test results had conjunctivitis, experienced mild illness, and received oseltamivir. This poultry exposure-associated cluster of human cases of influenza A(H5) is the first reported in the United States. The identification of these cases highlights the ongoing risk to persons who work in close contact with infected animals. Early response to each facility using multidisciplinary, multilingual teams facilitated case-finding, worker screening, and treatment. As the prevalence of HPAI A(H5N1) virus clade 2.3.4.4b genotype B3.13 increases, U.S. public health agencies should prepare to rapidly investigate and respond to illness in agricultural workers, including workers with limited access to health care.

Omada: robust clustering of transcriptomes through multiple testing.

BACKGROUND: Cohort studies increasingly collect biosamples for molecular profiling and are observing molecular heterogeneity. High-throughput RNA sequencing is providing large datasets capable of reflecting disease mechanisms. Clustering approaches have produced a number of tools to help dissect complex heterogeneous datasets, but selecting the appropriate method and parameters to perform exploratory clustering analysis of transcriptomic data requires deep understanding of machine learning and extensive computational experimentation. Tools that assist with such decisions without prior field knowledge are nonexistent. To address this, we have developed Omada, a suite of tools aiming to automate these processes and make robust unsupervised clustering of transcriptomic data more accessible through automated machine learning-based functions. FINDINGS: The efficiency of each tool was tested with 7 datasets characterized by different expression signal strengths to capture a wide spectrum of RNA expression datasets. Our toolkit's decisions reflected the real number of stable partitions in datasets where the subgroups are discernible. Within datasets with less clear biological distinctions, our tools either formed stable subgroups with different expression profiles and robust clinical associations or revealed signs of problematic data such as biased measurements. CONCLUSIONS: In conclusion, Omada successfully automates the robust unsupervised clustering of transcriptomic data, making advanced analysis accessible and reliable even for those without extensive machine learning expertise. Implementation of Omada is available at http://bioconductor.org/packages/omada/.

Dapagliflozin reduces systemic inflammation in patients with type 2 diabetes without known heart failure.

OBJECTIVE: Sodium glucose cotransporter 2 (SGLT2) inhibitors significantly improve cardiovascular outcomes in diabetic patients; however, the mechanism is unclear. We hypothesized that dapagliflozin improves cardiac outcomes via beneficial effects on systemic and cardiac inflammation and cardiac fibrosis. RESEARCH AND DESIGN METHODS: This randomized placebo-controlled clinical trial enrolled 62 adult patients (mean age 62, 17% female) with type 2 diabetes (T2D) without known heart failure. Subjects were randomized to 12 months of daily 10 mg dapagliflozin or placebo. For all patients, blood/plasma samples and cardiac magnetic resonance imaging (CMRI) were obtained at time of randomization and at the end of 12 months. Systemic inflammation was assessed by plasma IL-1B, TNFα, IL-6 and ketone levels and PBMC mitochondrial respiration, an emerging marker of sterile inflammation. Global myocardial strain was assessed by feature tracking; cardiac fibrosis was assessed by T1 mapping to calculate extracellular volume fraction (ECV); and cardiac tissue inflammation was assessed by T2 mapping. RESULTS: Between the baseline and 12-month time point, plasma IL-1B was reduced (- 1.8 pg/mL, P = 0.003) while ketones were increased (0.26 mM, P = 0.0001) in patients randomized to dapagliflozin. PBMC maximal oxygen consumption rate (OCR) decreased over the 12-month period in the placebo group but did not change in patients receiving dapagliflozin (- 158.9 pmole/min/106 cells, P = 0.0497 vs. - 5.2 pmole/min/106 cells, P = 0.41), a finding consistent with an anti-inflammatory effect of SGLT2i. Global myocardial strain, ECV and T2 relaxation time did not change in both study groups. GOV REGISTRATION: NCT03782259.

DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy.

Drug-drug interaction (DDI) may result in clinical toxicity or treatment failure of antiretroviral therapy (ARV) or comedications. Despite the high number of possible drug combinations, only a limited number of clinical DDI studies are conducted. Computational prediction of DDIs could provide key evidence for the rational management of complex therapies. Our study aimed to assess the potential of deep learning approaches to predict DDIs of clinical relevance between ARVs and comedications. DDI severity grading between 30,142 drug pairs was extracted from the Liverpool HIV Drug Interaction database. Two feature construction techniques were employed: 1) drug similarity profiles by comparing Morgan fingerprints, and 2) embeddings from SMILES of each drug via ChemBERTa, a transformer-based model. We developed DeepARV-Sim and DeepARV-ChemBERTa to predict four categories of DDI: i) Red: drugs should not be co-administered, ii) Amber: interaction of potential clinical relevance manageable by monitoring/dose adjustment, iii) Yellow: interaction of weak relevance and iv) Green: no expected interaction. The imbalance in the distribution of DDI severity grades was addressed by undersampling and applying ensemble learning. DeepARV-Sim and DeepARV-ChemBERTa predicted clinically relevant DDI between ARVs and comedications with a weighted mean balanced accuracy of 0.729 ± 0.012 and 0.776 ± 0.011, respectively. DeepARV-Sim and DeepARV-ChemBERTa have the potential to leverage molecular structures associated with DDI risks and reduce DDI class imbalance, effectively increasing the predictive ability on clinically relevant DDIs. This approach could be developed for identifying high-risk pairing of drugs, enhancing the screening process, and targeting DDIs to study in clinical drug development.

Measles Outbreak Associated with a Migrant Shelter - Chicago, Illinois, February-May 2024.

Measles, a highly contagious respiratory virus with the potential to cause severe complications, hospitalization, and death, was declared eliminated from the United States in 2000; however, with ongoing global transmission, infections in the United States still occur. On March 7, 2024, the Chicago Department of Public Health (CDPH) confirmed a case of measles in a male aged 1 year residing in a temporary shelter for migrants in Chicago. Given the congregate nature of the setting, high transmissibility of measles, and low measles vaccination coverage among shelter residents, measles virus had the potential to spread rapidly among approximately 2,100 presumed exposed shelter residents. CDPH immediately instituted outbreak investigation and response activities in collaboration with state and local health departments, health care facilities, city agencies, and shelters. On March 8, CDPH implemented active case-finding and coordinated a mass vaccination campaign at the affected shelter (shelter A), including vaccinating 882 residents and verifying previous vaccination for 784 residents over 3 days. These activities resulted in 93% measles vaccination coverage (defined as receipt of ≥1 recorded measles vaccine dose) by March 11. By May 13, a total of 57 confirmed measles cases associated with residing in or having contact with persons from shelter A had been reported. Most cases (41; 72%) were among persons who did not have documentation of measles vaccination and were considered unvaccinated. In addition, 16 cases of measles occurred among persons who had received ≥1 measles vaccine dose ≥21 days before first known exposure. This outbreak underscores the need to ensure high vaccination coverage among communities residing in congregate settings.

Dapagliflozin Reduces Systemic Inflammation in Patients with Type 2 Diabetes Without Known Heart Failure.

Objective: Sodium glucose cotransporter 2 (SGLT2) inhibitors significantly improve cardiovascular outcomes in diabetic patients; however, the mechanism is unclear. We hypothesized that dapagliflozin improves cardiac outcomes via beneficial effects on systemic and cardiac inflammation and cardiac fibrosis. Research and Design Methods: This randomized placebo-controlled clinical trial enrolled 62 adult patients (mean age 62, 17% female) with type 2 diabetes (T2D) without known heart failure. Subjects were randomized to 12 months of daily 10 mg dapagliflozin or placebo. For all patients, blood/plasma samples and cardiac magnetic resonance imaging (CMRI) were obtained at time of randomization and at the end of 12 months. Systemic inflammation was assessed by plasma IL-1B, TNFα, IL-6 and ketone levels and PBMC mitochondrial respiration, an emerging marker of sterile inflammation. Cardiac fibrosis was assessed by T1 mapping to calculate extracellular volume fraction (ECV); cardiac tissue inflammation was assessed by T2 mapping. Results: Between the baseline and 12-month time point, plasma IL-1B was reduced (-1.8 pg/mL, P=0.003) while ketones were increased (0.26 mM, P=0.0001) in patients randomized to dapagliflozin. PBMC maximal oxygen consumption rate (OCR) decreased over the 12-month period in the placebo group but did not change in patients receiving dapagliflozin (-158.9 pmole/min/106cells, P=0.0497 vs -45.2 pmole/min/106cells, P=0.41), a finding consistent with an anti-inflammatory effect of SGLT2i. ECV and T2 relaxation time did not change in both study groups. Conclusion: This study demonstrates that 12 months of dapagliflozin reduces IL-1B mediated systemic inflammation but affect cardiac fibrosis in T2D. Clinical Trialgov Registration: NCT03782259.

Transcatheter Edge-to-Edge Mitral Valve Repair in a Patient With Anderson-Fabry Disease.

Severe degenerative mitral regurgitation (DMR) is one cardiac manifestation of the multiorgan metabolic enzyme disorder Anderson-Fabry Disease (AFD). Although DMR is normally managed surgically, many patients with AFD are unsuitable for this. We present the first case of mitral transcatheter edge-to-edge repair in a patient with AFD.

Inpatient Screening, Brief Intervention, and Referral to Treatment for Alcohol Use Disorder in Patients Admitted with Alcohol-associated Liver Disease Is Not Universally Implemented in Practice, But Can Reduce Readmissions for Alcohol-associated Hepatitis.

Introduction: The management of alcohol-related liver disease requires a multidisciplinary approach to treat alcohol use disorder. We aimed to determine the proportion of actively drinking patients admitted for alcohol-associated hepatitis (AAH) or decompensated alcohol-related cirrhosis (DARLC) who were offered or underwent screening, brief intervention, and referral to treatment (SBIRT) for alcohol use disorder during admission and if inpatient SBIRT is associated with reduced readmissions for alcohol-related liver disease. Methods: We conducted a retrospective cohort study of actively drinking patients admitted to our institution from January 2017 to December 2021 with AAH or DARLC. Logistic regression was used to identify factors, such as conducting SBIRT, that were associated with 30-day and 90-day readmissions for recurrent AAH or DARLC. Results: There were 120 AAH admissions (mean age 47.7 ± 13.6 years), and 177 DARLC admissions (mean age 58.2 ± 9.5 years). SBIRT was conducted in only 51.7% of AAH admissions, and 23.7% of DARLC admissions. For AAH, conducting SBIRT was associated with significantly reduced 30-day (OR 0.098, P = 0.001, 95% CI 0.024-0.408) and 90-day (OR 0.166, P = 0.003, 95% CI 0.052-0.534) readmissions. For DARLC, there was no association between conducting SBIRT and 30-day or 90-day readmissions. Conclusion: SBIRT was conducted with actively drinking patients in only 51.7% of AAH admissions and 23.7% of DARLC admissions. Patients admitted for AAH who received inpatient SBIRT had decreased 30-day and 90-day readmission rates for AAH or DARLC.

Mendelian Randomization Study With Clinical Follow-Up Links Metabolites to Risk and Severity of Pulmonary Arterial Hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) exhibits phenotypic heterogeneity and variable response to therapy. The metabolome has been implicated in the pathogenesis of PAH, but previous works have lacked power to implicate specific metabolites. Mendelian randomization (MR) is a method for causal inference between exposures and outcomes. METHODS AND RESULTS: Using genome-wide association study summary statistics, we implemented MR analysis to test for potential causal relationships between serum concentration of 575 metabolites and PAH. Five metabolites were causally associated with the risk of PAH after multiple testing correction. Next, we measured serum concentration of candidate metabolites in an independent clinical cohort of 449 patients with PAH to check whether metabolite concentrations are correlated with markers of disease severity. Of the 5 candidates nominated by our MR work, serine was negatively associated and homostachydrine was positively associated with clinical severity of PAH via direct measurement in this independent clinical cohort. Finally we used conditional and orthogonal approaches to explore the biology underlying our lead metabolites. Rare variant burden testing was carried out using whole exome sequencing data from 578 PAH cases and 361 675 controls. Multivariable MR is an extension of MR that uses a single set of instrumental single-nucleotide polymorphisms to measure multiple exposures; multivariable MR is used to determine interdependence between the effects of different exposures on a single outcome. Rare variant analysis demonstrated that loss-of-function mutations within activating transcription factor 4, a transcription factor responsible for upregulation of serine synthesis under conditions of serine starvation, are associated with higher risk for PAH. Homostachydrine is a xenobiotic metabolite that is structurally related to l-proline betaine, which has previously been linked to modulation of inflammation and tissue remodeling in PAH. Our multivariable MR analysis suggests that the effect of l-proline betaine is actually mediated indirectly via homostachydrine. CONCLUSIONS: Our data present a method for study of the metabolome in the context of PAH, and suggests several candidates for further evaluation and translational research.

Ranking and filtering of neuropathology features in the machine learning evaluation of dementia studies.

Early diagnosis of dementia diseases, such as Alzheimer's disease, is difficult because of the time and resources needed to perform neuropsychological and pathological assessments. Given the increasing use of machine learning methods to evaluate neuropathology features in the brains of dementia patients, it is important to investigate how the selection of features may be impacted and which features are most important for the classification of dementia. We objectively assessed neuropathology features using machine learning techniques for filtering features in two independent ageing cohorts, the Cognitive Function and Aging Studies (CFAS) and Alzheimer's Disease Neuroimaging Initiative (ADNI). The reliefF and least loss methods were most consistent with their rankings between ADNI and CFAS; however, reliefF was most biassed by feature-feature correlations. Braak stage was consistently the highest ranked feature and its ranking was not correlated with other features, highlighting its unique importance. Using a smaller set of highly ranked features, rather than all features, can achieve a similar or better dementia classification performance in CFAS (60%-70% accuracy with Naïve Bayes). This study showed that specific neuropathology features can be prioritised by feature filtering methods, but they are impacted by feature-feature correlations and their results can vary between cohort studies. By understanding these biases, we can reduce discrepancies in feature ranking and identify a minimal set of features needed for accurate classification of dementia.

Unsupervised machine learning to investigate trajectory patterns of COVID-19 symptoms and physical activity measured via the MyHeart Counts App and smart devices.

Previous studies have associated COVID-19 symptoms severity with levels of physical activity. We therefore investigated longitudinal trajectories of COVID-19 symptoms in a cohort of healthcare workers (HCWs) with non-hospitalised COVID-19 and their real-world physical activity. 121 HCWs with a history of COVID-19 infection who had symptoms monitored through at least two research clinic visits, and via smartphone were examined. HCWs with a compatible smartphone were provided with an Apple Watch Series 4 and were asked to install the MyHeart Counts Study App to collect COVID-19 symptom data and multiple physical activity parameters. Unsupervised classification analysis of symptoms identified two trajectory patterns of long and short symptom duration. The prevalence for longitudinal persistence of any COVID-19 symptom was 36% with fatigue and loss of smell being the two most prevalent individual symptom trajectories (24.8% and 21.5%, respectively). 8 physical activity features obtained via the MyHeart Counts App identified two groups of trajectories for high and low activity. Of these 8 parameters only 'distance moved walking or running' was associated with COVID-19 symptom trajectories. We report a high prevalence of long-term symptoms of COVID-19 in a non-hospitalised cohort of HCWs, a method to identify physical activity trends, and investigate their association. These data highlight the importance of tracking symptoms from onset to recovery even in non-hospitalised COVID-19 individuals. The increasing ease in collecting real-world physical activity data non-invasively from wearable devices provides opportunity to investigate the association of physical activity to symptoms of COVID-19 and other cardio-respiratory diseases.

Role of dopamine in the pathophysiology of Parkinson's disease.

A pathological feature of Parkinson's disease (PD) is the progressive loss of dopaminergic neurons and decreased dopamine (DA) content in the substantia nigra pars compacta in PD brains. DA is the neurotransmitter of dopaminergic neurons. Accumulating evidence suggests that DA interacts with environmental and genetic factors to contribute to PD pathophysiology. Disturbances of DA synthesis, storage, transportation and metabolism have been shown to promote neurodegeneration of dopaminergic neurons in various PD models. DA is unstable and can undergo oxidation and metabolism to produce multiple reactive and toxic by-products, including reactive oxygen species, DA quinones, and 3,4-dihydroxyphenylacetaldehyde. Here we summarize and highlight recent discoveries on DA-linked pathophysiologic pathways, and discuss the potential protective and therapeutic strategies to mitigate the complications associated with DA.

Civilian Medical Responder Perspectives to a Federal Military Medical Deployment in New York City during the COVID-19 Pandemic.

OBJECTIVES: This study aims to describe the civilian experience and perceptions of the patient coordination and management at the interface of the New York City (NYC) civilian and the military health systems during a large-scale public health emergency. METHODS: A qualitative study design was implemented with interviews conducted using a basic descriptive approach. Purposive sampling was used to recruit participants with experience working during the first wave of COVID-19 in NYC. Inclusion criteria were civilians who worked at the Javits Center, the USNS Comfort, or NYC hospitals, who interfaced with patient transfer and military personnel during the city-wide medical response to COVID-19. Semi-structured video interviews were conducted between July 20, 2021 and March 11, 2022. RESULTS: Civilian responders working in the clinical and transfer operations of patients to military facilities in NYC during March and April of 2020 described initial confusion, as well as logistical (patient selection, transfer logistics, patient tracking), communication, and leadership challenges. While the military deployment was felt to be necessary to address the surge capacity in hospitals, the lack of clarity about military medical resources and frameworks for response resulted in confusion about what was being offered by the military deployment. This was balanced by the positive impression of working with military members and the resources that they brought to the response more generally. The need for future trainings and exercises were highlighted. CONCLUSIONS: Initial challenges with civilian-military roles and responsibilities, regional needs assessment, patient selection, and logistics were ultimately resolved through adaptation of civilian and military leadership. Improvements in patient tracking, medical records, and standard hospital admission and discharge functions for patients in military alternative care facilities were identified as areas for improvement. Civilian government, health care, and military leaders should consider these ideas when planning for future military deployments in support of a domestic medical response.

Hemorrhage From Left Hepatic Artery Pseudoaneurysm as a Complication of Acute Pancreatitis in a Patient With Fibromuscular Dysplasia.

Hepatic artery pseudoaneurysms are a rare complication of pancreatitis, and their rupture and bleeding cause high mortality. We present the case of a 76-year-old woman with fibromuscular dysplasia who developed a new left hepatic artery pseudoaneurysm within a week of her first episode of acute pancreatitis and later suffered an acute pseudoaneurysm bleed successfully treated with transcatheter coil embolization. To the best of our knowledge, this is the first case reported of a patient with fibromuscular dysplasia with pancreatitis-related pseudoaneurysm formation. One must consider pseudoaneurysms and associated bleeding as complications of acute pancreatitis because prompt recognition can lead to timely management.

Role of mitochondria in the myopathy of juvenile dermatomyositis and implications for skeletal muscle calcinosis.

OBJECTIVES: To elucidate mechanisms contributing to skeletal muscle calcinosis in patients with juvenile dermatomyositis. METHODS: A well-characterized cohorts of JDM (n = 68), disease controls (polymyositis, n = 7; juvenile SLE, n = 10, and RNP + overlap syndrome, n = 12), and age-matched health controls (n = 17) were analyzed for circulating levels of mitochondrial (mt) markers including mtDNA, mt-nd6, and anti-mitochondrial antibodies (AMAs) using standard qPCR, ELISA, and novel-in-house assays, respectively. Mitochondrial calcification of affected tissue biopsies was confirmed using electron microscopy and energy dispersive X-ray analysis. A human skeletal muscle cell line, RH30, was used to generate an in vitro calcification model. Intracellular calcification is measured by flow cytometry and microscopy. Mitochondria were assessed for mtROS production and membrane potential by flow cytometry and real-time oxygen consumption rate by Seahorse bioanalyzer. Inflammation (interferon-stimulated genes) was measured by qPCR. RESULTS: In the current study, patients with JDM exhibited elevated levels of mitochondrial markers associated with muscle damage and calcinosis. Of particular interest are AMAs predictive of calcinosis. Human skeletal muscle cells undergo time- and dose-dependent accumulation of calcium phosphate salts with preferential localization to mitochondria. Calcification renders skeletal muscle cells mitochondria stressed, dysfunctional, destabilized, and interferogenic. Further, we report that inflammation induced by interferon-alpha amplifies mitochondrial calcification of human skeletal muscle cells via the generation of mitochondrial reactive oxygen species (mtROS). CONCLUSIONS: Overall, our study demonstrates the mitochondrial involvement in the skeletal muscle pathology and calcinosis of JDM and mtROS as a central player in the calcification of human skeletal muscle cells. Therapeutic targeting of mtROS and/or upstream inducers, such as inflammation, may alleviate mitochondrial dysfunction, leading to calcinosis. AMAs can potentially identify patients with JDM at risk for developing calcinosis.

Bilateral treatment of the masseter with botulinum toxin: Consequences for mastication, muscle force and the mandibular condyle.

BACKGROUND: Clinical use of botulinum neurotoxins (BoNTs) in masticatory muscles is usually bilateral, but most studies on the functional consequences of BoNT treatment have used unilaterally treated animals. OBJECTIVES: To test the hypothesis that bilateral BoNT treatment of the rabbit masseter hampers mastication and to assess its effects on bone density of the mandibular condyles. METHODS: Ten 5-month-old female rabbits received injections of BoNT into both masseter muscles and nine sham animals received saline. Body weight, incisor bite force during masseter tetany, and surface and fine-wire electromyography (EMG) of the masseter and medial pterygoid muscles were assessed at regular intervals. Half the sample was terminated after 4 weeks and the remainder after 12 weeks. Muscles were weighed and mandibular condyles were scanned with microCT to analyse bone density. RESULTS: BoNT rabbits lost weight and required a soft-food diet. Incisor occlusal force plummeted after BoNT injection and remained lower than the shams. The duration of masticatory cycles was increased in the BoNT rabbits for 5 weeks, with most of the increase due to the adductor burst. Masseteric EMG amplitude began to improve at Week 5, but remained low on the working side throughout the experiment. At the 12-week endpoint, masseter muscles were smaller in the BoNT rabbits. Medial pterygoid muscles did not compensate. Condylar bone density was reduced. CONCLUSION: Bilateral treatment of the rabbit masseter by BoNT severely affected chewing performance. Even after a 3-month recovery period, deficits remained in bite force, muscle size and condylar bone density.

Assessment of Alzheimer-related pathologies of dementia using machine learning feature selection.

Although a variety of brain lesions may contribute to the pathological assessment of dementia, the relationship of these lesions to dementia, how they interact and how to quantify them remains uncertain. Systematically assessing neuropathological measures by their degree of association with dementia may lead to better diagnostic systems and treatment targets. This study aims to apply machine learning approaches to feature selection in order to identify critical features of Alzheimer-related pathologies associated with dementia. We applied machine learning techniques for feature ranking and classification to objectively compare neuropathological features and their relationship to dementia status during life using a cohort (n=186) from the Cognitive Function and Ageing Study (CFAS). We first tested Alzheimer's Disease and tau markers and then other neuropathologies associated with dementia. Seven feature ranking methods using different information criteria consistently ranked 22 out of the 34 neuropathology features for importance to dementia classification. Although highly correlated, Braak neurofibrillary tangle stage, beta-amyloid and cerebral amyloid angiopathy features were ranked the highest. The best-performing dementia classifier using the top eight neuropathological features achieved 79% sensitivity, 69% specificity and 75% precision. However, when assessing all seven classifiers and the 22 ranked features, a substantial proportion (40.4%) of dementia cases was consistently misclassified. These results highlight the benefits of using machine learning to identify critical indices of plaque, tangle and cerebral amyloid angiopathy burdens that may be useful for classifying dementia.

Linking autism spectrum disorders and parkinsonism: clinical and genetic association.

BACKGROUND: Autism spectrum disorders (ASD) comprise many complex and clinically distinct neurodevelopmental conditions, with increasing evidence linking them to parkinsonism. METHODS: We searched Medline and Embase from inception to 21 March 2022 and reviewed the bibliographies of relevant articles. Studies were screened and reviewed comprehensively by two independent authors. RESULTS: Of 863 references from our search, we included eight clinical studies, nine genetic studies, and five case reports. Regardless of age group, Parkinson's disease (PD) and parkinsonian syndromes were more frequently observed in patients with ASD, though the evidence for increased rates of parkinsonism is less clear for children and adolescents. Parkinsonian features and hypokinetic behavior were common in Rett syndrome, with prevalence estimates ranging from 40% to 80%. Frequently observed parkinsonian features include bradykinesia, rigidity, hypomimia, and gait freezing. PD gene PARK2 copy number variations appear more frequently in ASD cases than controls. Evidence suggests that RIT2 and CD157/BST1 are implicated in ASD and PD, while the evidence for other PD-related genes (DRD2, GPCR37, the SLC gene family, and SMPD1) is less clear. Rare mutations, such as ATP13A2, CLN3, and WDR45, could result in autistic behavior and concomitant parkinsonism. CONCLUSION: The prevalence of parkinsonism in ASD is substantially greater than in the general population or matched controls. Various PD-associated gene loci, especially PARK2, could confer susceptibility to ASD as well. Important future directions include conducting prospective cohort studies to understand how parkinsonian symptoms may progress, genetic studies to reveal relevant gene loci, and pathophysiologic studies to identify potential therapeutic targets.