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In managing the fish environment and underwater ecosystem, there's been a big shift from old-generational schoolings, hands-on methods to high-technologies, automatic ways of doing things, because of some clever computer technology, using a type of Artificial Intelligence smartness known as Convolutional Neural Networks, or CNNs in short. These smart systems help deal with the tricky task of keeping tabs on where fish stay out in deeper underwater, particularly when it's hard to see underwater and when the fish are all over the place. There are some pretty good tools and techniques already out there, like DPANet and a few others with names like PIFS-Net, EFS-Net, and MFAS-Net, which have been helping a bunch of researches and developments for underwater ecosystem. But Deeper water environment still needs a newer and better way to get the tasks done. So, to answer this major question, this hybrid architecture rolls out a new combination that takes the best bits of transformer architecture known as Swin Transformer and another mechanism known as ConvMixer, making it in a form of SwinUNet Architecture. This Swin Transformer is well defined at picking up on the spatial information from underwater deeper images in our case, which is a key point to be highlighted in really getting the fish's niche turf and enquiring their ecosystem. And when the underwater turns misty, the specialized implementation of ConvMixer modules incorporated with Swin Transformer increases its ability to sort out the fish from the rest of the underwater world. And this makes it to perform even more better compared with the existing state of arts model, even under Modern Underwater Machine Vision System conditions. This model even over takes to utilization of Few-Shot Learning model for training it in this lesser Underwater Images, with its capability of identifying the patterns and differentiations in both larger and smaller class objects in the given ground truth image. In this new approach, the paper combines the smart focusing methods with a way to blend different signals to better mIoU score, making it super useful for having a deeper understanding on fish-ecosystem and also their underwater ecosystem. While comparing it with the pre-existing state of arts model and the booming Image Segmentation models (YOLO v8, Pix 2 Pix GAN model, Auto Encoders, UNet), the hybrid approach outperformed the existing model results on this Semantic Segmentation for Underwater Imagery (SUIM) dataset, which is been disclosed in the further sections below.

Purpose: The goal of Electronic Medical Records and Genomics (eMERGE) Phase III Network was to return actionable sequence variants to 25,084 consenting participants from 10 different health care institutions across the United States. The purpose of this study was to evaluate system-based issues relating to the return of results (RoR) disclosure process for clinical grade research genomic tests to eMERGE3 participants., Methods: RoR processes were developed and approved by each eMERGE institution's internal review board. Investigators at each eMERGE3 site were surveyed for RoR processes related to the participant's disclosure of pathogenic or likely pathogenic variants and engagement with genetic counseling. Standard statistical analysis was performed., Results: Of the 25,084 eMERGE participants, 1444 had a pathogenic or likely pathogenic variant identified on the eMERGEseq panel of 67 genes and 14 single nucleotide variants. Of these, 1077 (74.6%) participants had results disclosed, with 562 (38.9%) participants provided with variant-specific genetic counseling. Site-specific processes that either offered or required genetic counseling in their RoR process had an effect on whether a participant ultimately engaged with genetic counseling (P = .0052)., Conclusion: The real-life experience of the multiarm eMERGE3 RoR study for returning actionable genomic results to consented research participants showed the impact of consent, method of disclosure, and genetic counseling on RoR., Competing Interests: Conflicts of Interest R.C.G. receives compensation for advising AIA, Applied Therapeutics, Humanity, and Verily and is a cofounder of Genome Medical, Inc, a technology and services company providing genetics expertise to patients, providers, employers, and care systems. All other authors declare no conflicts of interest., (Copyright © 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Etiologies of HIV disparities are multifaceted; anti-LGBTQ stigma and social marginalization are contributory factors. A city health department developed a program, #ProjectPresence, exhibiting professional photos of Black LGBTQ persons in public spaces. An academic partner explored the relationship of the program to visibility, anti-LGBTQ stigma and social marginalization of Black LGBTQ persons, i.e. models, directly involved in the program and their perceptions of these relationships more broadly for community members. Brief self-administered surveys and semi-structured, in-depth interviews with #ProjectPresence models (n = 15) were conducted after the program to gather their experiences before, during and after the program. Descriptive analyses of survey responses were conducted using Stata 15.1. Interviews were audio-recorded, transcribed and analyzed in NVivo10 using categorical analysis. Surveys indicated prevalent experiences of enacted stigma (73 %) and perceptions of poor local acceptance of LGBTQ people (53 %). Interviews suggested that the program may have influenced positive individual- and community-level changes by increasing visibility of LGBTQ communities and improving acceptance among non-LGBTQ persons, inspiring personal growth and self-acceptance among models, and providing opportunities to foster new connections among LGBTQ subpopulations. Our findings suggest similar programs may present promising approaches for the reduction of stigma and social marginalization affecting LGBTQ persons and communities., (Copyright © 2021. Published by Elsevier Ltd.)

Objective: With its increasingly widespread adoption, electronic health records (EHR) have enabled phenotypic information extraction at an unprecedented granularity and scale. However, often a medical concept (e.g. diagnosis, prescription, symptom) is described in various synonyms across different EHR systems, hindering data integration for signal enhancement and complicating dimensionality reduction for knowledge discovery. Despite existing ontologies and hierarchies, tremendous human effort is needed for curation and maintenance - a process that is both unscalable and susceptible to subjective biases. This paper aims to develop a data-driven approach to automate grouping medical terms into clinically relevant concepts by combining multiple up-to-date data sources in an unbiased manner., Methods: We present a novel data-driven grouping approach - multi-view banded spectral clustering (mvBSC) combining summary data from multiple healthcare systems. The proposed method consists of a banding step that leverages the prior knowledge from the existing coding hierarchy, and a combining step that performs spectral clustering on an optimally weighted matrix., Results: We apply the proposed method to group ICD-9 and ICD-10-CM codes together by integrating data from two healthcare systems. We show grouping results and hierarchies for 13 representative disease categories. Individual grouping qualities were evaluated using normalized mutual information, adjusted Rand index, and F 1 -measure, and were found to consistently exhibit great similarity to the existing manual grouping counterpart. The resulting ICD groupings also enjoy comparable interpretability and are well aligned with the current ICD hierarchy., Conclusion: The proposed approach, by systematically leveraging multiple data sources, is able to overcome bias while maximizing consensus to achieve generalizability. It has the advantage of being efficient, scalable, and adaptive to the evolving human knowledge reflected in the data, showing a significant step toward automating medical knowledge integration., (Copyright © 2019. Published by Elsevier Inc.)

Background: There is an urgent need for biomarkers to better stratify patients with idiopathic pulmonary fibrosis by risk for lung transplantation allocation who have the same clinical presentation. We aimed to investigate whether a specific immune cell type from patients with idiopathic pulmonary fibrosis could identify those at higher risk of poor outcomes. We then sought to validate our findings using cytometry and electronic health records., Methods: We first did a discovery analysis with transcriptome data from the Gene Expression Omnibus at the National Center for Biotechnology Information for 120 peripheral blood mononuclear cell (PBMC) samples of patients with idiopathic pulmonary fibrosis. We estimated percentages of 13 immune cell types using statistical deconvolution, and investigated the association of these cell types with transplant-free survival. We validated these results using PBMC samples from patients with idiopathic pulmonary fibrosis in two independent cohorts (COMET and Yale). COMET profiled monocyte counts in 45 patients with idiopathic pulmonary fibrosis from March 12, 2010, to March 10, 2011, using flow cytometry; we tested if increased monocyte count was associated with the primary outcome of disease progression. In the Yale cohort, 15 patients with idiopathic pulmonary fibrosis (with five healthy controls) were classed as high risk or low risk from April 28, 2014, to Aug 20, 2015, using a 52-gene signature, and we assessed whether monocyte percentage (measured by cytometry by time of flight) was higher in high-risk patients. We then examined complete blood count values in the electronic health records (EHR) of 45 068 patients with idiopathic pulmonary fibrosis, systemic sclerosis, hypertrophic cardiomyopathy, or myelofibrosis from Stanford (Jan 01, 2008, to Dec 31, 2015), Northwestern (Feb 15, 2001 to July 31, 2017), Vanderbilt (Jan 01, 2008, to Dec 31, 2016), and Optum Clinformatics DataMart (Jan 01, 2004, to Dec 31, 2016) cohorts, and examined whether absolute monocyte counts of 0·95 K/μL or greater were associated with all-cause mortality in these patients., Findings: In the discovery analysis, estimated CD14+ classical monocyte percentages above the mean were associated with shorter transplant-free survival times (hazard ratio [HR] 1·82, 95% CI 1·05-3·14), whereas higher percentages of T cells and B cells were not (0·97, 0·59-1·66; and 0·78, 0·45-1·34 respectively). In two validation cohorts (COMET trial and the Yale cohort), patients with higher monocyte counts were at higher risk for poor outcomes (COMET Wilcoxon p=0·025; Yale Wilcoxon p=0·049). Monocyte counts of 0·95 K/μL or greater were associated with mortality after adjusting for forced vital capacity (HR 2·47, 95% CI 1·48-4·15; p=0·0063), and the gender, age, and physiology index (HR 2·06, 95% CI 1·22-3·47; p=0·0068) across the COMET, Stanford, and Northwestern datasets). Analysis of medical records of 7459 patients with idiopathic pulmonary fibrosis showed that patients with monocyte counts of 0·95 K/μL or greater were at increased risk of mortality with lung transplantation as a censoring event, after adjusting for age at diagnosis and sex (Stanford HR=2·30, 95% CI 0·94-5·63; Vanderbilt 1·52, 1·21-1·89; Optum 1·74, 1·33-2·27). Likewise, higher absolute monocyte count was associated with shortened survival in patients with hypertrophic cardiomyopathy across all three cohorts, and in patients with systemic sclerosis or myelofibrosis in two of the three cohorts., Interpretation: Monocyte count could be incorporated into the clinical assessment of patients with idiopathic pulmonary fibrosis and other fibrotic disorders. Further investigation into the mechanistic role of monocytes in fibrosis might lead to insights that assist the development of new therapies., Funding: Bill & Melinda Gates Foundation, US National Institute of Allergy and Infectious Diseases, and US National Library of Medicine., (Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objective: Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to (1) infer phenotypic topics within patient populations and (2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems., Methods: We adapt a generative topic modeling strategy, based on latent Dirichlet allocation, to infer phenotypic topics. We utilize a variance analysis to assess the projection of a patient population from one healthcare system onto the topics learned from another system. The consistency of learned phenotypic topics was evaluated using (1) the similarity of topics, (2) the stability of a patient population across topics, and (3) the transferability of a topic across sites. We evaluated our approaches using four months of inpatient data from two geographically distinct healthcare systems: (1) Northwestern Memorial Hospital (NMH) and (2) Vanderbilt University Medical Center (VUMC)., Results: The method learned 25 phenotypic topics from each healthcare system. The average cosine similarity between matched topics across the two sites was 0.39, a remarkably high value given the very high dimensionality of the feature space. The average stability of VUMC and NMH patients across the topics of two sites was 0.988 and 0.812, respectively, as measured by the Pearson correlation coefficient. Also the VUMC and NMH topics have smaller variance of characterizing patient population of two sites than standard clinical terminologies (e.g., ICD9), suggesting they may be more reliably transferred across hospital systems., Conclusions: Phenotypic topics learned from EHR data can be more stable and transferable than billing codes for characterizing the general status of a patient population. This suggests that EHR-based research may be able to leverage such phenotypic topics as variables when pooling patient populations in predictive models., (Copyright © 2015 Elsevier Inc. All rights reserved.)

This Phase III randomized trial examined efficacy and safety of a novel once-daily extended-release tacrolimus formulation (LCP-Tacro [LCPT]) versus twice-daily tacrolimus in de novo kidney transplantation. Primary efficacy end point was proportion of patients with treatment failure (death, graft failure, biopsy-proven acute rejection or lost to follow-up) within 12 months. Starting doses were, LCPT: 0.17 mg/kg/day and tacrolimus twice-daily: 0.1 mg/kg/day; 543 patients were randomized, LCPT: n = 268; tacrolimus twice-daily: n = 275. At 12 months treatment failure was LCPT: 18.3% and tacrolimus twice-daily: 19.6%; the upper 95% CI of the treatment difference was +5.27%, below the predefined +10% noninferiority criteria. There were no significant differences in the incidence of individual efficacy events or adverse events. Target tacrolimus trough levels were more rapidly achieved in the LCPT group. Following initial dose, 36.6% of patients in the LCPT group had rapidly attained trough levels within 6-11 ng/mL versus 18.5% of tacrolimus twice-daily patients; majority of tacrolimus twice-daily patients (74.7%) had troughs <6 ng/mL compared with 33.5% in the LCPT group. Overall, cumulative study dose was 14% lower for LCPT. Results suggest that use of once-daily LCPT in de novo kidney transplantation is efficacious and safe. Lower LCPT dose reflects the improved absorption provided by the novel formulation., (© Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.)

In the Lao People's Democratic Republic (PDR), mumps is not a notifiable disease and mumps vaccine is currently not included in the routine childhood immunization programme. In order to assess the burden of disease, we investigated the seroprevalence of mumps-specific IgG antibodies across four provinces. In addition, we genetically characterized mumps viruses from the past 3 years from several outbreaks and single cases. Blood and/or throat swabs from suspected cases were investigated for specific IgM antibodies or viral RNA. Mumps cases occurred between March and November in 2011-2013 and 5- to 15-year-olds were most affected. Four sequences from an outbreak in the north of Lao PDR in 2011 were identical and belonged to genotype G. Eight sequences from two outbreaks and two individual cases from 2012 and 2013 belonged to genotype J. In addition, sera collected from 2379 healthy infants and school pupils aged between 9 months and 19 years and from pregnant women aged between 16 and 46 years were investigated for mumps-specific IgG. Overall, 58.2% were positive, 39.5% were negative and the remaining 2.3% were equivocal. The seropositivity increased with age, with the lowest percentage found in <1-year-old infants (9.1%) and the highest in the cohort of pregnant women (69.2%). More female subjects than male subjects were seropositive (60.4 vs. 54.9%). There were some differences between the locations. Mumps should be a notifiable disease in Lao PDR in order to get more accurate case numbers and cost estimates for public health-care, and vaccination of children and high-risk groups should be considered., (© 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.)

Resonance patterns observed in 2D PISEMA (polarization inversion spin exchange at magic angle) spectra from a transmembrane alpha-helix have been demonstrated to yield structural details of the protein. This paper presents a mathematical discussion of the PISEMA powder spectrum as the image in the frequency plane of a quadratic function from the sphere of unit vectors. The simplicity of this function allows easy calculation of the powder spectrum. Based on this analysis of powder patterns, four degeneracies are discussed which arise in determining possible orientations associated with PISA spectra. This paper also gives parametric equations for PISA wheels, which are specific patterns observed in PISEMA spectra of oriented peptides. These wheels are useful both in assigning the resonances and in determining the orientation of the helix with respect to the magnetic field. The union of these PISA wheels gives the entire powder spectrum., (Copyright 2001 Academic Press.)

Resonance patterns have been observed in 2D solid-state NMR spectra of the transmembrane segment of M2 protein from Influenza A virus in oriented samples reflecting the helical wheel of this alpha-helix. The center of this pattern uniquely defines the helical tilt with respect to the bilayer normal without a need for resonance assignments. The distribution of resonances from amino acid specific labels around the "PISA wheel" defines the rotational orientation of the helix and yields preliminary site-specific assignments. With assignments high-resolution structural detail, such as differences in tilt and rotational orientation along the helical axis leading to an assessment of helical coiling, can be obtained., (Copyright 2000 Academic Press.)

Solid-state NMR has been used to study the influence of lipid bilayer hydrophobic thickness on the tilt of a peptide (M2-TMP) representing the transmembrane portion of the M2 protein from influenza A. Using anisotropic (15)N chemical shifts as orientational constraints, single-site isotopically labeled M2-TMPs were studied in hydrated dioleoylphosphatidylcholine (DOPC) and dimyristoylphosphatidylcholine (DMPC) lipid bilayers oriented between thin glass plates. These chemical shifts provide orientational information for the molecular frame with respect to the magnetic field in the laboratory frame. When modeled as a uniform ideal alpha-helix, M2-TMP has a tilt of 37(+/-3) degrees in DMPC and 33(+/-3) degrees in DOPC with respect to the bilayer normal in these lipid environments. The difference in helix tilt between the two environments appears to be small. This lack of a substantial change in tilt further suggests that significant interactions occur between the helices, as in an oligomeric state, to prevent a change in tilt in thicker lipid bilayers., (Copyright 2000 Academic Press.)

Results of a previous study showed that angiotensin II (AII) inhibited the induction of long-term potentiation (LTP) in hippocampal granule cells in response to dorsomedial perforant path stimulation in urethane-anesthetized rats. The results of present experiments demonstrate a dose-dependent inhibition of LTP induction under the same conditions due to ethanol (EtOH) administered by stomach tube and diazepam (DZ) injected IP. The inhibition of LTP induction by EtOH and DZ can be blocked by saralasin (SAR) applied directly to the dorsal hippocampus and by lorsartan (DuP 753) administered IP. Lorsartan or a metabolite crosses the blood-brain barrier because it also blocks the inhibition of LTP induction due to AII administration directly into the dorsal hippocampus. Lorsartan is a competitive antagonist of the AT1 subtype AII receptor. Therefore, the AII and the EtOH and DZ inhibition of LTP induction are mediated by the AII subtype receptor AT1. AIII and the AT2 antagonist PD123319 did not produce any significant effects. These in vivo effects can be reproduced in brain slices and therefore cannot be attributed to other factors, such as the urethane. In addition, electrical stimulation of the lateral hypothalamus (LH) inhibits LTP induction, and the inhibition can be blocked by SAR. These data on LH stimulation indicate that LH AII-containing neurons send axons into the hippocampus that inhibit the induction of LTP. These results not only provide new information on a neurotransmitter involved in the amnesic effects of benzodiazepines and ethanol-induced memory blackouts, but also testable hypotheses concerning recent observations that angiotensin converting enzyme (ACE) inhibitors elevate mood and improve certain cognitive processes in the elderly.