MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Management of Small Papillary Thyroid Cancers.

Thyroid cancer is the most common endocrine malignancy. With increasing imaging utilization, there has been an increase in the recognition of small, indolent cancers that would otherwise go undiagnosed. Historically, the surgical recommendation for all patients with thyroid cancer was a total thyroidectomy. However, over the last 20 years, there have been numerous studies evaluating the de-escalation of interventions for low-risk thyroid cancers, transitioning from total thyroidectomy to thyroid lobectomy or active surveillance when indicated. Here, we review the current literature and recommendations with each of these treatment options.

Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a clinically and biologically heterogenous disease with currently unpredictable progression and relapse. After the development and success of neurofilament as a cerebrospinal fluid (CSF) biomarker, there is reinvigorated interest in identifying other markers of or contributors to disease. The objective of this study is to probe the predictive potential of a panel of brain-enriched proteins on MS disease progression and subtype. METHODS: This study includes 40 individuals with MS and 14 headache controls. The MS cohort consists of 20 relapsing remitting (RR) and 20 primary progressive (PP) patients. The CSF of all individuals was analyzed for 63 brain enriched proteins using a method of liquid-chromatography tandem mass spectrometry. Wilcoxon rank sum test, Kruskal-Wallis one-way ANOVA, logistic regression, and Pearson correlation were used to refine the list of candidates by comparing relative protein concentrations as well as relation to known imaging and molecular biomarkers. RESULTS: We report 30 proteins with some relevance to disease, clinical subtype, or severity. Strikingly, we observed widespread protein depletion in the disease CSF as compared to control. We identified numerous markers of relapsing disease, including KLK6 (kallikrein 6, OR = 0.367, p < 0.05), which may be driven by active disease as defined by MRI enhancing lesions. Other oligodendrocyte-enriched proteins also appeared at reduced levels in relapsing disease, namely CNDP1 (carnosine dipeptidase 1), LINGO1 (leucine rich repeat and Immunoglobin-like domain-containing protein 1), MAG (myelin associated glycoprotein), and MOG (myelin oligodendrocyte glycoprotein). Finally, we identified three proteins-CNDP1, APLP1 (amyloid beta precursor like protein 1), and OLFM1 (olfactomedin 1)-that were statistically different in relapsing vs. progressive disease raising the potential for use as an early biomarker to discriminate clinical subtype. CONCLUSIONS: We illustrate the utility of targeted mass spectrometry in generating potential targets for future biomarker studies and highlight reductions in brain-enriched proteins as markers of the relapsing remitting disease stage.

Measuring Urease and Phospholipase Secretion in Cryptococcus neoformans.

Urease and phospholipase are enzymes that are important virulence factors for Cryptococcus neoformans. These are two of the most studied enzymes involved in how C. neoformans breaches the blood-brain barrier. Additionally, phospholipase secretion also supports dissemination from the lungs. This chapter describes the methods used to measure the secretion of these enzymes, which may be used to characterize strain invasiveness and virulence.

Outcome in dogs with invasive adrenal gland tumors that did not pursue adrenalectomy.

OBJECTIVE: To report the survival times in dogs diagnosed with adrenal tumors with vascular or soft tissue invasion that did not undergo adrenalectomy. ANIMALS: Retrospective case series of 32 client-owned dogs. METHODS: The medical records of a referral veterinary hospital were reviewed to identify dogs that were diagnosed with an invasive adrenal mass and did not undergo adrenalectomy between January 2013 and December 2022. Data collected included signalment, examination findings, and diagnostic results from the initial presentation. Descriptive statistics were calculated to summarize dog signalment information, and Kaplan-Meier survival analysis was performed for calculation of median survival time. RESULTS: Most dogs (n = 28) had vascular invasion, primarily into the caudal vena cava. Surgery was offered but not pursued due to perceived risk of sudden death (n = 5), risk of hemorrhage (4), or concurrent diagnosis of disseminated intravascular coagulation (1). Only 1 dog pursued stereotactic body radiation therapy, and 1 was prescribed toceranib phosphate (Palladia). Of these 32 dogs, 30 (93.8%) died or were euthanized and 2 (6.2%) dogs survived. The median follow-up time was 49 days (range, 0 to 1,910 days). The median survival time was 50 days (95% CI, 4 to 194 days). The most common cause of death or euthanasia was hemoabdomen (n = 8). CLINICAL RELEVANCE: Nonsurgical management of invasive adrenal tumors was associated with short survival times in this case series.

Global field collection data confirm an affinity of brown rot fungi for coniferous habitats and substrates.

Unlike 'white rot' (WR) wood-decomposing fungi that remove lignin to access cellulosic sugars, 'brown rot' (BR) fungi selectively extract sugars and leave lignin behind. The relative frequency and distribution of these fungal types (decay modes) have not been thoroughly assessed at a global scale; thus, the fate of one-third of Earth's aboveground carbon, wood lignin, remains unclear. Using c. 1.5 million fungal sporocarp and c. 30 million tree records from publicly accessible databases, we mapped and compared decay mode and tree type (conifer vs angiosperm) distributions. Additionally, we mined fungal record metadata to assess substrate specificity per decay mode. The global average for BR fungi proportion (BR/(BR + WR records)) was 13% and geographic variation was positively correlated (R2 = 0.45) with conifer trees proportion (conifer/(conifer + angiosperm records)). Most BR species (61%) were conifer, rather than angiosperm (22%), specialists. The reverse was true for WR (conifer: 19%; angiosperm: 62%). Global BR proportion patterns were predicted with greater accuracy using the relative distributions of individual tree species (R2 = 0.82), rather than tree type. Fungal decay mode distributions can be explained by tree type and, more importantly, tree species distributions, which our data suggest is due to strong substrate specificities.

Predictors of follow-up care for critically-ill patients with seizures and epileptiform abnormalities on EEG monitoring.

OBJECTIVE: Post-hospitalization follow-up visits are crucial for preventing long-term complications. Patients with electrographic epileptiform abnormalities (EA) including seizures and periodic and rhythmic patterns are especially in need of follow-up for long-term seizure risk stratification and medication management. We sought to identify predictors of follow-up. METHODS: This is a retrospective cohort study of all patients (age ≥ 18 years) admitted to intensive care units that underwent continuous EEG (cEEG) monitoring at a single center between 01/2016-12/2019. Patients with EAs were included. Clinical and demographic variables were recorded. Follow-up status was determined using visit records 6-month post discharge, and visits were stratified as outpatient follow-up, neurology follow-up, and inpatient readmission. Lasso feature selection analysis was performed. RESULTS: 723 patients (53 % female, mean (std) age of 62.3 (16.4) years) were identified from cEEG records with 575 (79 %) surviving to discharge. Of those discharged, 450 (78 %) had outpatient follow-up, 316 (55 %) had a neurology follow-up, and 288 (50 %) were readmitted during the 6-month period. Discharge on antiseizure medications (ASM), younger age, admission to neurosurgery, and proximity to the hospital were predictors of neurology follow-up visits. Discharge on ASMs, along with longer length of stay, younger age, emergency admissions, and higher illness severity were predictors of readmission. SIGNIFICANCE: ASMs at discharge, demographics (age, address), hospital care teams, and illness severity determine probability of follow-up. Parameters identified in this study may help healthcare systems develop interventions to improve care transitions for critically-ill patients with seizures and other EA.

Tracing the origin of SARS-CoV-2 omicron-like spike sequences detected in an urban sewershed: a targeted, longitudinal surveillance study of a cryptic wastewater lineage.

BACKGROUND: The origin of novel SARS-CoV-2 spike sequences found in wastewater, without corresponding detection in clinical specimens, remains unclear. We sought to determine the origin of one such cryptic wastewater lineage by tracking and characterising its persistence and genomic evolution over time. METHODS: We first detected a cryptic lineage, WI-CL-001, in municipal wastewater in Wisconsin, USA, in January, 2022. To determine the source of WI-CL-001, we systematically sampled wastewater from targeted sub-sewershed lines and maintenance holes using compositing autosamplers. Viral concentrations in wastewater samples over time were measured by RT digital PCR. In addition to using metagenomic 12s rRNA sequencing to determine the virus's host species, we also sequenced SARS-CoV-2 spike receptor binding domains, and, where possible, whole viral genomes to identify and characterise the evolution of this lineage. FINDINGS: We traced WI-CL-001 to its source at a single commercial building. There we detected the cryptic lineage at concentrations as high as 2·7 × 109 genome copies per L. The majority of 12s rRNA sequences detected in wastewater leaving the identified source building were human. Additionally, we generated over 100 viral receptor binding domain and whole-genome sequences from wastewater samples containing the cryptic lineage collected over the 13 consecutive months this virus was detectable (January, 2022, to January, 2023). These sequences contained a combination of fixed nucleotide substitutions characteristic of Pango lineage B.1.234, which circulated in humans in Wisconsin at low levels from October, 2020, to February, 2021. Despite this, mutations in the spike gene and elsewhere resembled those subsequently found in omicron variants. INTERPRETATION: We propose that prolonged detection of WI-CL-001 in wastewater indicates persistent shedding of SARS-CoV-2 from a single human initially infected by an ancestral B.1.234 virus. The accumulation of convergent omicron-like mutations in WI-CL-001's ancestral B.1.234 genome probably reflects persistent infection and extensive within-host evolution. People who shed cryptic lineages could be an important source of highly divergent viruses that sporadically emerge and spread. FUNDING: The Rockefeller Foundation, Wisconsin Department of Health Services, Centers for Disease Control and Prevention, National Institute on Drug Abuse, and the Center for Research on Influenza Pathogenesis and Transmission.

Optic nerve sheath diameter and its association with brain swelling in pediatric cerebral malaria: a retrospective study.

Introduction: Mortality in pediatric cerebral malaria (CM) in low- and middle-income countries (LMICs) is associated with brain swelling on magnetic resonance imaging (MRI); however, MRI is unavailable in most LMICs. Optic nerve sheath diameter (ONSD) measurement is an inexpensive method of detecting increased intracranial pressure compared with the invasive opening pressure (OP). Our primary objective was to determine if increased ONSD correlated with brain swelling on MRI in pediatric CM. Our secondary objective was to determine if increased ONSD correlated with increased OP and/or poor neurological outcome in pediatric CM. We hypothesized that increased ONSD would correlate with brain swelling on MRI and increased OP and that ONSD would be higher in survivors with sequelae and non-survivors. Methods: We performed a retrospective chart review of children aged 0-12 years in Blantyre, Malawi, from 2013 to 2022 with CM as defined by the World Health Organization. Brain swelling on admission MRI was characterized by brain volume scores (BVS); severe swelling was scored as 7-8, mild-to-moderate as 4-6, normal as 3. The admission ONSD was measured via ultrasound; it was defined as abnormal if it was >4.5 mm in children >1 year and >4 mm in children <1 year. Favorable outcome was defined as a normal neurological exam on discharge in survivors. The primary and secondary objectives were evaluated using Spearman's correlation; and the demographics were compared using chi-square and the Kruskal-Wallis test (Stata, College Station, TX, USA). Results: Median age of the 207-patients cohort was 50 months [interquartile range (IQR) 35-75]; 49% (n = 102) were female. Of those, 73% (n = 152) had a favorable outcome, and 14% (n = 30) died. Twenty-nine (14%) had a normal BVS, 134 (65%) had mild-to-moderate swelling, and 44 (21%) had severe swelling. ONSD was elevated in 86% (n = 178) of patients, while 12% of patients had increased OP. There was a weakly positive correlation between BVS and ONSD (r = 0.14, p = 0.05). The median ONSD was not significantly different compared by discharge outcome (p = 0.11) or by BVS (p = 0.18). Conclusion: ONSD was not a reliable tool to correlate with BVS, neurological outcome, or OP in children with CM. Future studies to identify alternative methods of early identification of CM patients at highest risk for morbidity and mortality are urgently needed.

Musculoskeletal model degrees of Freedom: Frontal plane constraints are hindering our understanding of human movement.

Induced acceleration analyses have expanded our understanding on the contributions of muscle forces to center of mass and segmental kinematics during a myriad of tasks. While these techniques have identified a subset of major muscle that contribute to locomotion, most analyses have included models with only one frontal plane degree of freedom (dof) actuated by the hip joint. The purpose of this study was to define the impact of including knee and subtalar joint frontal plane dof on model superposition accuracy and muscle specific contributions to mediolateral accelerations. Induced acceleration analyses were performed using OpenSim with the Lai model on a freely available dataset of one subject running at 4 m/s. Analyses were performed on four models (standard, with subtalar joint, with frontal plane knee, and combined frontal plane knee with subtalar) with the kinematic constraint and perturbation analyses. Root mean square error and correlations were computed against experimental kinematics. Adding frontal plane dofs improved mediolateral acceleration correlations on average by > 0.25 while only minimally impacting errors. The constraints method performed better than the perturbation method for mediolateral accelerations. Including frontal plane knee dof resulted in muscle and method specific responses. All muscles presented with a complete flip of polarity for constraint method, imparted by allowing the medial/lateral muscles to contribute according to their anatomical function. Only the gluteus medius flipped for the perturbation method. This study provides significant support for the inclusion of frontal plane knee and subtalar dof and the need for reevaluation of muscle contributions via induced acceleration.

Assessment of the Cutaneous Hormone Landscapes and Microbiomes in Vulvar Lichen Sclerosus.

Vulvar lichen sclerosus (VLS) is a progressive skin disease of unknown etiology. In this longitudinal case-control exploratory study, we evaluated the hormonal and microbial landscapes in 18 postmenopausal females (mean [SD] age: 64.4 [8.4] years) with VLS and controls. We reevaluated the patients with VLS after 10-14 weeks of daily topical class I steroid. We found that groin cutaneous estrone was lower in VLS than in controls (-22.33, 95% confidence interval [CI] = -36.96 to -7.70; P = .006); cutaneous progesterone was higher (5.73, 95% CI = 3.74-7.73; P < .0001). Forehead 11-deoxycortisol (-0.24, 95% CI = -0.42 to -0.06; P = .01) and testosterone (-7.22, 95% CI = -12.83 to -1.62; P = .02) were lower in disease. With treatment, cutaneous estrone (-7.88, 95% CI = -44.07 to 28.31; P = .62), progesterone (2.02, 95% CI = -2.08 to 6.11; P = .29), and 11-deoxycortisol (-0.13, 95% CI = -0.32 to 0.05; P = .15) normalized; testosterone remained suppressed (-7.41, 95% CI = -13.38 to -1.43; P = .02). 16S ribosomal RNA V1-V3 and ITS1 amplicon sequencing revealed bacterial and fungal microbiome alterations in disease. Findings suggest that cutaneous sex hormone and bacterial microbiome alterations may be associated with VLS in postmenopausal females.

Predicting Knee Joint Contact Forces During Normal Walking Using Kinematic Inputs With a Long-Short Term Neural Network.

Knee joint contact forces are commonly estimated via surrogate measures (i.e., external knee adduction moments or musculoskeletal modeling). Despite its capabilities, modeling is not optimal for clinicians or persons with limited experience. The purpose of this study was to design a novel prediction method for knee joint contact forces that is simplistic in terms of required inputs. This study included marker trajectories and instrumented knee forces during normal walking from the "Grand Challenge" (n = 6) and "CAMS" (n = 2) datasets. Inverse kinematics were used to derive stance phase hip (sagittal, frontal, transverse), knee (sagittal, frontal), ankle (sagittal), and trunk (frontal) kinematics. A long-short term memory network (LSTM) was created using matlab to predict medial and lateral knee force waveforms using combinations of the kinematics. The Grand Challenge and CAMS datasets trained and tested the network, respectively. Musculoskeletal modeling forces were derived using static optimization and joint reaction tools in OpenSim. Waveform accuracy was determined as the proportion of variance and root-mean-square error between network predictions and in vivo data. The LSTM network was highly accurate for medial forces (R2 = 0.77, RMSE = 0.27 BW) and required only frontal hip and knee and sagittal hip and ankle kinematics. Modeled medial force predictions were excellent (R2 = 0.77, RMSE = 0.33 BW). Lateral force predictions were poor for both methods (LSTM R2 = 0.18, RMSE = 0.08 BW; modeling R2 = 0.21, RMSE = 0.54 BW). The designed LSTM network outperformed most reports of musculoskeletal modeling, including those reached in this study, revealing knee joint forces can accurately be predicted by using only kinematic input variables.

Rotation sequences for the calculation of shoulder kinematics of the volleyball attack.

Calculating upper extremity kinematics during overhead movements presents with problems typically not seen for the lower extremity due to the large range of motion. Due to these unique issues, different rotation sequences have been suggested to circumvent challenges due to gimbal lock (GL) and angle coherence (AC). The purpose of this study is to determine the most appropriate rotation sequence for shoulder angle calculation during a volleyball attack. METHODS: 15 healthy experienced volleyball players (women = 8) performed 5 attacks off a stationary ball. A 12-camera 3D motion capture system was utilized to record trunk and arm kinematics to compare joint angles calculated using the YXY, ZXY, XZY, YXZ, ZYX, and XYZ rotation sequences. Instances of GL and AC inconsistences were marked for each trial. The last 3 trials were used for analysis. RESULTS: The YXY and XYZ sequences presented with the least total number of errors (12 and 5, respectively). 5 instances of GL were present in the XYZ sequence while none were recorded for the YXY sequence. All other sequences returned incoherent angles that greatly exceeded known ranges of motion. CONCLUSION: When performing kinematic analyses during a volleyball attack, researchers should adhere to ISB recommendations and employ the Eulerian YXY sequence for calculations. If greater anatomical understanding is desired, the XYZ sequence may be utilized for most subjects.

SUMMIT-FA: a new resource for improved transcriptome imputation using functional annotations.

Transcriptome-wide association studies (TWAS) integrate gene expression prediction models and genome-wide association studies (GWAS) to identify gene-trait associations. The power of TWAS is determined by the sample size of GWAS and the accuracy of the expression prediction model. Here, we present a new method, the Summary-level Unified Method for Modeling Integrated Transcriptome using Functional Annotations (SUMMIT-FA), which improves gene expression prediction accuracy by leveraging functional annotation resources and a large expression quantitative trait loci (eQTL) summary-level dataset. We build gene expression prediction models in whole blood using SUMMIT-FA with the comprehensive functional database MACIE and eQTL summary-level data from the eQTLGen consortium. We apply these models to GWAS for 24 complex traits and show that SUMMIT-FA identifies significantly more gene-trait associations and improves predictive power for identifying "silver standard" genes compared to several benchmark methods. We further conduct a simulation study to demonstrate the effectiveness of SUMMIT-FA.

Characterization of an N-Allylglyoxylamide-Based Bioorthogonal Nitrone Trap.

Aldehydes are attractive bioorthogonal coupling partners. The ease of manipulation of aldehydes and their orthogonality to other classes of bioorthogonal reactions have inspired the exploration of chemistries, which generate irreversible conjugates. Similarly, nitrones have been shown to be potent 1,3-dipoles in bioorthogonal reactions when paired with strained alkynes. Here, we combine the reactivity of nitrones with the simplicity of aldehydes using an N-allylglyoxylamide, in a cascade reaction with an N-alkylhydroxylamine to produce a bicyclic isoxazolidine. The reaction is found to be catalyzed by 5-methoxyanthranilic acid and proceeds at pH 7 with favorable kinetics. Using the HaloTag7 protein bearing an N-alkylhydroxylamine, we show the reaction to be bioorthogonal in a complex cell lysate and to proceed well at the surface of a HEK293 cell. Furthermore, the reaction is compatible with a typical strain-promoted alkyne-azide click reaction. The characteristics of this reaction suggest it will be a useful addition to the pallet of bioorthogonal reactions that have revolutionized chemical biology.

The Impact of SIV-Induced Immunodeficiency on Clinical Manifestation, Immune Response, and Viral Dynamics in SARS-CoV-2 Coinfection.

Persistent and uncontrolled SARS-CoV-2 replication in immunocompromised individuals has been observed and may be a contributing source of novel viral variants that continue to drive the pandemic. Importantly, the effects of immunodeficiency associated with chronic HIV infection on COVID-19 disease and viral persistence have not been directly addressed in a controlled setting. Here we conducted a pilot study wherein two pigtail macaques (PTM) chronically infected with SIVmac239 were exposed to SARS-CoV-2 and monitored for six weeks for clinical disease, viral replication, and viral evolution, and compared to our previously published cohort of SIV-naïve PTM infected with SARS-CoV-2. At the time of SARS-CoV-2 infection, one PTM had minimal to no detectable CD4+ T cells in gut, blood, or bronchoalveolar lavage (BAL), while the other PTM harbored a small population of CD4+ T cells in all compartments. Clinical signs were not observed in either PTM; however, the more immunocompromised PTM exhibited a progressive increase in pulmonary infiltrating monocytes throughout SARS-CoV-2 infection. Single-cell RNA sequencing (scRNAseq) of the infiltrating monocytes revealed a less activated/inert phenotype. Neither SIV-infected PTM mounted detectable anti-SARS-CoV-2 T cell responses in blood or BAL, nor anti-SARS-CoV-2 neutralizing antibodies. Interestingly, despite the diminished cellular and humoral immune responses, SARS-CoV-2 viral kinetics and evolution were indistinguishable from SIV-naïve PTM in all sampled mucosal sites (nasal, oral, and rectal), with clearance of virus by 3-4 weeks post infection. SIV-induced immunodeficiency significantly impacted immune responses to SARS-CoV-2 but did not alter disease progression, viral kinetics or evolution in the PTM model. SIV-induced immunodeficiency alone may not be sufficient to drive the emergence of novel viral variants.

Improving Neurology Clinical Care With Natural Language Processing Tools.

The integration of natural language processing (NLP) tools into neurology workflows has the potential to significantly enhance clinical care. However, it is important to address the limitations and risks associated with integrating this new technology. Recent advances in transformer-based NLP algorithms (e.g., GPT, BERT) could augment neurology clinical care by summarizing patient health information, suggesting care options, and assisting research involving large datasets. However, these NLP platforms have potential risks including fabricated facts and data security and substantial barriers for implementation. Although these risks and barriers need to be considered, the benefits for providers, patients, and communities are substantial. With these systems achieving greater functionality and the pace of medical need increasing, integrating these tools into clinical care may prove not only beneficial but necessary. Further investigation is needed to design implementation strategies, mitigate risks, and overcome barriers.