Utility of a bone health clinic in bridging the osteoporosis care gap: Prescribing habit review at an academic institution.

OBJECTIVE: To analyze osteoporosis medication prescribing trends across specialties in the context of a Bone Health Clinic. INTRODUCTION: Osteoporosis affects over 10 million adults in the US, taking a significant toll on patients and the healthcare system. Although screening methods and treatments are improving, the disease remains underdiagnosed and undertreated. This study aims to evaluate the prescribing trends of osteoporosis medication among department specialties to delineate the benefits of a bone health clinic. METHODS: Retrospective data collection identified and analyzed patients within the Penn State Health system prescribed one of the following osteoporosis medications: Bisphosphonate, denosumab, romosozumab, teriparatide, abaloparatide, or raloxifene. Date range: 4/18/2016 to 4/14/2021. Data collection identified the specialty origin of prescriptions for osteoporosis medications across various medical specialties (e.g., orthopaedics, family medicine, and internal medicine). RESULTS: 10,736 prescription orders were issued to patients with an average age of 68 years. Non-Hispanic Caucasian patients received 88.6% of prescriptions, followed by Asian (3.4%) and African American (2.2%). Female patients accounted for 87.8% of all prescriptions. The Bone Health Clinic under two orthopaedic providers wrote 3,619 prescriptions, averaging 361.9 prescriptions per provider per year-marking the highest rate among specialties. The clinic prescriptions constituted 33.7% of all prescriptions across specialties. Orthopaedic surgery prescribed the most denosumab, romosozumab, teriparatide, and abaloparatide prescriptions, and had the highest number of male osteoporosis patients compared to other specialties (15.6%), consequently prescribing the most male prescriptions (578). CONCLUSION: Establishing a bone health clinic dedicated to osteoporosis management leads to significantly higher prescription rates per provider, increased utilization of anabolic therapies compared to other specialties, and more male patients being treated-an often-neglected population in osteoporosis.

Gaps in our understanding of how vagal afferents to the small intestinal mucosa detect luminal stimuli.

Vagal afferents to the gastrointestinal tract are crucial for regulation of food intake, signaling negative feedback that contributes to satiation and positive feedback that produces appetition and reward. Vagal afferents to the small intestinal mucosa contribute to this regulation by sensing luminal stimuli and reporting this information to the brain. These afferents respond to mechanical, chemical, thermal, pH, and osmolar stimuli and to bacterial products and immunogens. Surprisingly little is known about how these stimuli are transduced by vagal mucosal afferents, or how their transduction is organized among these afferents' terminals. Further, the effects of stimulus concentration ranges or physiological stimuli on vagal activity have not been examined for some of these stimuli. And, detection of luminal stimuli has rarely been examined in rodents, which are most frequently employed for studying small intestinal innervation. Here we review what is known about stimulus detection by vagal mucosal afferents and illustrate the complexity of this detection using nutrients as an exemplar. The accepted model proposes nutrients bind to taste receptors on enteroendocrine cells (EECs), which excites them, causing release of hormones that stimulate vagal mucosal afferents. Evidence is reviewed that suggests while this model accounts for many aspects of vagal signaling about nutrients, it cannot account for all aspects. A major goal of this review therefore is to evaluate what is known about nutrient absorption and detection and based on this evaluation to identify candidate mucosal cells and structures that could cooperate with EECs and vagal mucosal afferents in stimulus detection.

A pathologist-AI collaboration framework for enhancing diagnostic accuracies and efficiencies.

In pathology, the deployment of artificial intelligence (AI) in clinical settings is constrained by limitations in data collection and in model transparency and interpretability. Here we describe a digital pathology framework, nuclei.io, that incorporates active learning and human-in-the-loop real-time feedback for the rapid creation of diverse datasets and models. We validate the effectiveness of the framework via two crossover user studies that leveraged collaboration between the AI and the pathologist, including the identification of plasma cells in endometrial biopsies and the detection of colorectal cancer metastasis in lymph nodes. In both studies, nuclei.io yielded considerable diagnostic performance improvements. Collaboration between clinicians and AI will aid digital pathology by enhancing accuracies and efficiencies.

Mapping medically relevant RNA isoform diversity in the aged human frontal cortex with deep long-read RNA-seq.

Determining whether the RNA isoforms from medically relevant genes have distinct functions could facilitate direct targeting of RNA isoforms for disease treatment. Here, as a step toward this goal for neurological diseases, we sequenced 12 postmortem, aged human frontal cortices (6 Alzheimer disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. We identified 1,917 medically relevant genes expressing multiple isoforms in the frontal cortex where 1,018 had multiple isoforms with different protein-coding sequences. Of these 1,018 genes, 57 are implicated in brain-related diseases including major depression, schizophrenia, Parkinson's disease and Alzheimer disease. Our study also uncovered 53 new RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. We also reported on five mitochondrially encoded, spliced RNA isoforms. We found 99 differentially expressed RNA isoforms between cases with Alzheimer disease and controls.

Large-scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity.

Introduction: Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups. Methods: Dorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS). Results: As a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals. Discussion: This comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

Proteomic changes in the human cerebrovasculature in Alzheimer's disease and related tauopathies linked to peripheral biomarkers in plasma and cerebrospinal fluid.

INTRODUCTION: Cerebrovascular dysfunction is a pathological hallmark of Alzheimer's disease (AD). Nevertheless, detecting cerebrovascular changes within bulk tissues has limited our ability to characterize proteomic alterations from less abundant cell types. METHODS: We conducted quantitative proteomics on bulk brain tissues and isolated cerebrovasculature from the same individuals, encompassing control (N = 28), progressive supranuclear palsy (PSP) (N = 18), and AD (N = 21) cases. RESULTS: Protein co-expression network analysis identified unique cerebrovascular modules significantly correlated with amyloid plaques, cerebrovascular amyloid angiopathy (CAA), and/or tau pathology. The protein products within AD genetic risk loci were concentrated within cerebrovascular modules. The overlap between differentially abundant proteins in AD cerebrospinal fluid (CSF) and plasma with cerebrovascular network highlighted a significant increase of matrisome proteins, SMOC1 and SMOC2, in CSF, plasma, and brain. DISCUSSION: These findings enhance our understanding of cerebrovascular deficits in AD, shedding light on potential biomarkers associated with CAA and vascular dysfunction in neurodegenerative diseases.

Physical Rehabilitation and Mobilization in Patients Receiving Extracorporeal Life Support: A Systematic Review.

OBJECTIVES: We planned to synthesize evidence examining the potential efficacy and safety of performing physical rehabilitation and/or mobilization (PR&M) in adult patients receiving extracorporeal life support (ECLS). DATA SOURCES: We included any study that compared PR&M to no PR&M or among different PR&M strategies in adult patients receiving any ECLS for any indication and any cannulation. We searched seven electronic databases with no language limitations. STUDY SELECTION AND DATA EXTRACTION: Two reviewers, independently and in duplicate, screened all citations for eligibility. We used the Cochrane Risk of Bias 2 and Cochrane Risk Of Bias In Non-randomized Studies of Interventions tools to assess individual study risk of bias. Although we had planned for meta-analysis, this was not possible due to insufficient data, so we used narrative and tabular data summaries for presenting results. We assessed the overall certainty of the evidence for each outcome using the Grading of Recommendations Assessment, Development, and Evaluation framework. DATA SYNTHESIS: We included 17 studies that enrolled 996 patients. Most studies examined venovenous extracorporeal membrane oxygenation (ECMO) and/or venoarterial ECMO as a bridge to recovery in the ICU. We found an uncertain effect of high-intensity/active PR&M on mortality, duration of mechanical ventilation, ICU length of stay, hospital length of stay, or quality of life compared with low-intensity/passive PR&M in patients receiving ECLS (very low certainty due to very serious imprecision). There was similarly an uncertain effect on safety events including clinically important bleeding, spontaneous intracerebral hemorrhage, limb ischemia, accidental decannulation, or ECLS circuit dysfunction (very low certainty due to very serious risk of bias and imprecision). CONCLUSIONS: Based on the currently available summary of evidence, there is an uncertain effect of high-intensity/active PR&M on patient important outcomes or safety in patients receiving ECLS. Despite indirect data from other populations suggesting potential benefit of high-intensity PR&M in the ICU; further high-quality randomized trials evaluating the benefits and risks of physical therapy and/or mobilization in this population are needed.

Bridging the Gap: Multi-Omics Profiling of Brain Tissue in Alzheimer's Disease and Older Controls in Multi-Ethnic Populations.

INTRODUCTION: Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS: To bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors. RESULTS: We generated multi-omics data and curated and harmonized phenotypic data from AA (n=306), LA (n=326), or AA and LA (n=4) brain donors plus Non-Hispanic White (n=252) and other (n=20) ethnic groups, to establish a foundational dataset enriched for AA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION: Inclusion of traditionally underrepresented groups in multi-omics studies is essential to discover the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.

Heparin-enriched plasma proteome is significantly altered in Alzheimer's Disease.

Introduction: Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to ß-amyloid (Aß) and tau pathology in Alzheimer's disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches. Methods: We employed heparin affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to capture and enrich HBPs in plasma obtained from AD (n=62) and control (n=47) samples. These profiles were then correlated to a consensus AD brain proteome, as well as with Aß, tau and phosphorylated tau (pTau) CSF biomarkers from the same individuals. We then leveraged published human postmortem brain proteome datasets to assess the overlap with the heparin-enriched plasma proteome. Results: Heparin-enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundance proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude were detectable. Utilizing a consensus AD brain protein co-expression network, we observed that specific plasma HBPs exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes highlighting the complex interplay between the two compartments. Elevated HBPs in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate within Aß deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and APOE. Additionally, heparin enriched plasma proteins demonstrated significant correlations with conventional AD CSF biomarkers, including Aß, total tau, pTau, and plasma pTau from the same individuals. Conclusion: These findings support the utility of a heparin-affinity approach for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.

Draft genome sequences of two Micromonospora strains isolated from the root nodules of Alnus glutinosa.

In this paper, the draft genomes of Micromonospora RTGN7 and RTP1Z1, derived from Alnus glutinosa root nodules, are reported. The assembly of RTGN7 is 6.6 Mbp, composed of 59 contigs, with an N50 of 321,872. RTP1Z1's assembly is 6.3 Mbp, composed of 151 contigs, with an N50 of 76,442 bp.

Persistence of microbiological hazards in food and feed production and processing environments.

Listeria monocytogenes (in the meat, fish and seafood, dairy and fruit and vegetable sectors), Salmonella enterica (in the feed, meat, egg and low moisture food sectors) and Cronobacter sakazakii (in the low moisture food sector) were identified as the bacterial food safety hazards most relevant to public health that are associated with persistence in the food and feed processing environment (FFPE). There is a wide range of subtypes of these hazards involved in persistence in the FFPE. While some specific subtypes are more commonly reported as persistent, it is currently not possible to identify universal markers (i.e. genetic determinants) for this trait. Common risk factors for persistence in the FFPE are inadequate zoning and hygiene barriers; lack of hygienic design of equipment and machines; and inadequate cleaning and disinfection. A well-designed environmental sampling and testing programme is the most effective strategy to identify contamination sources and detect potentially persistent hazards. The establishment of hygienic barriers and measures within the food safety management system, during implementation of hazard analysis and critical control points, is key to prevent and/or control bacterial persistence in the FFPE. Once persistence is suspected in a plant, a 'seek-and-destroy' approach is frequently recommended, including intensified monitoring, the introduction of control measures and the continuation of the intensified monitoring. Successful actions triggered by persistence of L. monocytogenes are described, as well as interventions with direct bactericidal activity. These interventions could be efficient if properly validated, correctly applied and verified under industrial conditions. Perspectives are provided for performing a risk assessment for relevant combinations of hazard and food sector to assess the relative public health risk that can be associated with persistence, based on bottom-up and top-down approaches. Knowledge gaps related to bacterial food safety hazards associated with persistence in the FFPE and priorities for future research are provided.

Draft genome sequences of five Mycobacterium strains, isolated from Alnus glutinosa root nodules.

Mycobacterium is a clinically relevant genus of bacteria, with this paper reporting draft genomes of five Mycobacterium strains derived from Alnus glutinosa root nodules. The genome sizes of the isolates ranged from 6.1 to 6.9 Mbp, composed of 22-59 contigs. The N50 values ranged from 303,875 to 865,751 bp, presenting a GC% of 66.07%-66.96%.

Proteomic Changes in the Human Cerebrovasculature in Alzheimer's Disease and Related Tauopathies Linked to Peripheral Biomarkers in Plasma and Cerebrospinal Fluid.

Dysfunction of the neurovascular unit stands as a significant pathological hallmark of Alzheimer's disease (AD) and age-related neurodegenerative diseases. Nevertheless, detecting vascular changes in the brain within bulk tissues has proven challenging, limiting our ability to characterize proteomic alterations from less abundant cell types. To address this challenge, we conducted quantitative proteomic analyses on both bulk brain tissues and cerebrovascular-enriched fractions from the same individuals, encompassing cognitively unimpaired control, progressive supranuclear palsy (PSP), and AD cases. Protein co-expression network analysis identified modules unique to the cerebrovascular fractions, specifically enriched with pericytes, endothelial cells, and smooth muscle cells. Many of these modules also exhibited significant correlations with amyloid plaques, cerebral amyloid angiopathy (CAA), and/or tau pathology in the brain. Notably, the protein products within AD genetic risk loci were found concentrated within modules unique to the vascular fractions, consistent with a role of cerebrovascular deficits in the etiology of AD. To prioritize peripheral AD biomarkers associated with vascular dysfunction, we assessed the overlap between differentially abundant proteins in AD cerebrospinal fluid (CSF) and plasma with a vascular-enriched network modules in the brain. This analysis highlighted matrisome proteins, SMOC1 and SMOC2, as being increased in CSF, plasma, and brain. Immunohistochemical analysis revealed SMOC1 deposition in both parenchymal plaques and CAA in the AD brain, whereas SMOC2 was predominantly localized to CAA. Collectively, these findings significantly enhance our understanding of the involvement of cerebrovascular abnormalities in AD, shedding light on potential biomarkers and molecular pathways associated with CAA and vascular dysfunction in neurodegenerative diseases.

The correlation between altmetric score and traditional measures of article impact for studies published within the Surgeon Journal.

Alternative metrics, or altmetrics, have emerged as a promising tool for measuring the social impact of research, which is increasingly important in today's digital and social media-driven world. Altmetric Attention Score (AAS) is a weighted count of all the online attention garnered by a study, and it is currently unclear whether a relationship with traditional bibliometrics exists. The purpose of this article was to retrospectively review articles published in the Surgeon Journal from 2003 to 2020 to compare AAS with bibliometric parameters using an Independent t-test and Pearson's correlation analysis. There were statistically significant weakly positive relationships between AAS and sample size, number of reads, and number of citations. There was no statistically significant relationship between AAS and number of authors, H-index, or level of evidence. This study highlights the potential value of altmetrics by measuring the social impact of research as altmetrics can provide valuable information not captured by traditional metrics. It is currently unclear what the optimal balance of social and academic impact is in evaluating research impact and how altmetrics can be integrated into existing research frameworks.

Draft genome sequence of Streptomyces poriferorum RTGN2, a bacterial endophyte isolated from Alnus glutinosa root nodules.

Herein is reported the draft genome sequence of Streptomyces poriferum RTGN2, a bacterial isolate of Alnus glutinosa root nodules, collected from Saltwell Park, Gateshead, United Kingdom. The assembly is 9.5 Mbp in size, composed of 187 contigs, with a N50 of 189,630 bp, presenting a GC content of 71.2%.

Draft genome sequence of Amycolatopsis camponoti RTGN1, a bacterial endophyte isolated from Alnus glutinosa root nodules.

Here, we report the draft genome sequence of Amycolatopsis camponoti RTGN1, a bacterial endophyte of Alnus glutinosa root nodules, collected from Saltwell Park, United Kingdom. The genome is 11.9 Mbp in size, composed of 147 contigs, with an N50 of 179,211 bp and presenting a GC content of 70.9%.

Unveiling Resilience to Alzheimer's Disease: Insights From Brain Regional Proteomic Markers.

Studying proteomics data of the human brain could offer numerous insights into unraveling the signature of resilience to Alzheimer's disease. In our previous study with rigorous cohort selection criteria that excluded 4 common comorbidities, we harnessed multiple brain regions from 43 research participants with 12 of them displaying cognitive resilience to Alzheimer's disease. Based on the previous findings, this work focuses on 6 proteins out of the 33 differentially expressed proteins associated with resilience to Alzheimer's disease. These proteins are used to construct a decision tree classifier, enabling the differentiation of 3 groups: (i) healthy control, (ii) resilience to Alzheimer's disease, and (iii) Alzheimer's disease with dementia. Our analysis unveiled 2 important regional proteomic markers: Aß peptides in the hippocampus and PA1B3 in the inferior parietal lobule. These findings underscore the potential of using distinct regional proteomic markers as signatures in characterizing the resilience to Alzheimer's disease.

Polygenic scores, and the genome-wide association studies they derive from, will have difficulty identifying genes that predispose one to develop a social behavioral trait.

Polygenic scores (PGSs) have several limitations. They are confounded with environmental effects on behavior and cannot be used to study how mutations affect brain function and behavior. For this, mutations with large effects, which often arise in only one geographical population are needed. Genome-wide association studies (GWASs), commonly used for identifying mutations, have difficulty detecting these mutations. A strategy that overcomes this challenge is discussed.

Using deep long-read RNAseq in Alzheimer's disease brain to assess medical relevance of RNA isoform diversity.

Due to alternative splicing, human protein-coding genes average over eight RNA isoforms, resulting in nearly four distinct protein coding sequences per gene. Long-read RNAseq (IsoSeq) enables more accurate quantification of isoforms, shedding light on their specific roles. To assess the medical relevance of measuring RNA isoform expression, we sequenced 12 aged human frontal cortices (6 Alzheimer's disease cases and 6 controls; 50% female) using one Oxford Nanopore PromethION flow cell per sample. Our study uncovered 53 new high-confidence RNA isoforms in medically relevant genes, including several where the new isoform was one of the most highly expressed for that gene. Specific examples include WDR4 (61%; microcephaly), MYL3 (44%; hypertrophic cardiomyopathy), and MTHFS (25%; major depression, schizophrenia, bipolar disorder). Other notable genes with new high-confidence isoforms include CPLX2 (10%; schizophrenia, epilepsy) and MAOB (9%; targeted for Parkinson's disease treatment). We identified 1,917 medically relevant genes expressing multiple isoforms in human frontal cortex, where 1,018 had multiple isoforms with different protein coding sequences, demonstrating the need to better understand how individual isoforms from a single gene body are involved in human health and disease, if at all. Exactly 98 of the 1,917 genes are implicated in brain-related diseases, including Alzheimer's disease genes such as APP (Aß precursor protein; five), MAPT (tau protein; four), and BIN1 (eight). As proof of concept, we also found 99 differentially expressed RNA isoforms between Alzheimer's cases and controls, despite the genes themselves not exhibiting differential expression. Our findings highlight the significant knowledge gaps in RNA isoform diversity and their medical relevance. Deep long-read RNA sequencing will be necessary going forward to fully comprehend the medical relevance of individual isoforms for a "single" gene.

Whole genome deconvolution unveils Alzheimer's resilient epigenetic signature.

Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) accurately depicts the chromatin regulatory state and altered mechanisms guiding gene expression in disease. However, bulk sequencing entangles information from different cell types and obscures cellular heterogeneity. To address this, we developed Cellformer, a deep learning method that deconvolutes bulk ATAC-seq into cell type-specific expression across the whole genome. Cellformer enables cost-effective cell type-specific open chromatin profiling in large cohorts. Applied to 191 bulk samples from 3 brain regions, Cellformer identifies cell type-specific gene regulatory mechanisms involved in resilience to Alzheimer's disease, an uncommon group of cognitively healthy individuals that harbor a high pathological load of Alzheimer's disease. Cell type-resolved chromatin profiling unveils cell type-specific pathways and nominates potential epigenetic mediators underlying resilience that may illuminate therapeutic opportunities to limit the cognitive impact of the disease. Cellformer is freely available to facilitate future investigations using high-throughput bulk ATAC-seq data.