bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Geospatial Analysis of salmonellosis and its association with socioeconomic status in Texas
Authors: Gourishankar Anand 
Published: May 2021

AbstractObjectiveThe study’s objective was to find the association between salmonellosis and socioeconomic status (SES) in hot spot areas and statewide counties.DesignA retrospective cohort study.SettingThe data was recorded regarding salmonellosis in 2017 from the Texas surveillance database. It included assessment of hot spot analysis and SES association with salmonellosis at the county level.ParticipantsPatients with salmonellosis of all age groups in Texas.ResultsThere were a total of 5113 salmonelloses from 254 counties with an unadjusted crude rate of 18 per 100,000 Person-year. Nine SES risk factors in the hot spot counties were as follows: low values of the severe housing problem, unemployment, African American, and high values of college education, social association rate, fast food/full-service restaurant use, Hispanic, and senior low access-to-store (P < 0.05). A 12% difference existed between local health departments in hot (25%) and cold spot (37%) counties (χ2 [1, n = 108] = 0.5, P = 0.81). Statewide independent risk factors were severe housing problem (IRR = 1.1; CI:1.05-1.14), social association rate (IRR = 0.89; CI:0.87-0.92), college education (IRR = 1.05; CI: 1.04-1.07), and non-Hispanic senior local access-to-store (IRR = 1.98; CI: 1.26-3.11). The severe housing problem predicted zero occurrences of infection in a county (OR = 0.51; CI: 0.28-0.95).ConclusionsDisparity exists in salmonellosis and socioeconomic status. Attention to unmet needs will decrease salmonellosis. Severe housing problem is a notable risk.
Biologic Therapies for the Treatment of Post Ileal Pouch Anal Anastomosis Surgery Chronic Inflammatory Disorders: Systematic Review and Meta-analysis
Authors: Shehab Mohammad , Alrashed Fatema , Charabaty Aline , Bessissow Talat 
Published: May 2021

AbstractBackgroundChronic inflammatory disorders after ileal pouch-anal anastomosis (IPAA) surgery are common. These include chronic pouchitis, Crohn’s disease of the pouch, prepouch ileitis, and rectal cuff inflammation. The aim of this study was to evaluate the efficacy of biologic therapies in treating these disorders.MethodSystematic review of all published studies from inception to April 1st, 2021 was performed to investigate the efficacy of biologic therapies for post IPAA chronic inflammatory disorders. The primary outcome was the efficacy of biologic therapies in achieving complete response or remission. A subgroup analysis was performed for each disorder separately.ResultsA total of 24 studies were identified including 682 patients. Using a random effect model, the overall pooled efficacy of biologic therapies in achieving complete response or remission in patients with post IPAA surgery chronic inflammatory disorders was 60% (95% Confidence Interval (CI), 56 - 64). Specifically, the pooled efficacy of ustekinumab was 75% (95% CI, 64 - 85, p = 0.007), whereas the efficacy of vedolizumab was 60% (95% CI, 52 - 68, p = 0.172). In addition, the efficacy infliximab and adalimumab were 59% (95% CI, 53 - 64, p <0.01) and 51% (95% CI, 42 - 60, p = 0.452) respectively.ConclusionUstekinumab, infliximab, vedolizumab and adalimumab are effective in achieving complete response or remission in post IPAA surgery chronic inflammatory disorders. There is also a clear trend toward higher efficacy in patients with Crohn’s disease of the pouch compared to chronic pouchitis. More studies are needed to determine the efficacy of biologics in cuffitis.SummaryChronic inflammatory disorders after ileal pouch-anal anastomosis surgery are common. These include chronic pouchitis, Crohn’s disease of the pouch, prepouch ileitis, and rectal cuff inflammation. This study aimed to evaluate the efficacy of biologic therapies in achieving complete response or remission in these disorders.
Symptoms of common mental disorders and adherence to antiretroviral therapy among adults living with HIV in rural Zimbabwe: a cross-sectional study
Authors: Haas Andreas D , Kunzekwenyika Cordelia , Hossmann Stefanie , Manzero Josphat , van Dijk Janneke H , Manhibi Ronald , Verhey Ruth , Limacher Andreas , von Groote Per , Manda Ethel , Hobbins Michael , Chibanda Dixon , Egger Matthias ,   for IeDEA Southern Africa
Published: May 2021

AbstractObjectivesTo examine the proportion of people living with HIV who screen positive for common mental disorders (CMD) and the associations between CMD and self-reported adherence to antiretroviral therapy (ART).SettingSixteen government-funded health facilities in the rural Bikita district of Zimbabwe.DesignCross-sectional survey.ParticipantsHIV-positive non-pregnant adults, aged 18 years or older, who lived in Bikita district and had received ART for at least six months.Outcome measuresThe primary outcome was the proportion of participants screening positive for CMD defined as a Shona Symptoms Questionnaire (SSQ-14) score of 9 or greater. Secondary outcomes were the proportion of participants reporting suicidal ideation, perceptual symptoms, and suboptimal ART adherence and adjusted prevalence ratios (aPR) for factors associated with CMD, suicidal ideation, perceptual symptoms, and suboptimal ART adherence.ResultsOut of 3,480 adults, 18.8% (95% confidence interval [CI] 14.8-23.7) screened positive for CMD, 2.7% (95% CI 1.5-4.7) reported suicidal ideations, and 1.5% (95% 0.9-2.6) reported perceptual symptoms. Positive CMD screens were more common in women (adjusted prevalence ratio [aPR] 1.67, 95% CI 1.19-2.35) than in men and were more common in adults aged 40-49 years (aPR 1.47 95% CI 1.16-1.85) or aged 50-59 years (20.3%; aPR 1.51 95% CI 1.05-2.17) than in those 60 years or older. Positive CMD screen was associated with suboptimal adherence (aPR 1.53; 95% CI 1.37-1.70).ConclusionsA substantial proportion of people living with HIV in rural Zimbabwe are affected by CMD. There is a need to integrate mental health services and HIV programs in rural Zimbabwe.Strengths and limitations of this studyInclusion of a large sample of people living with HIV recruited at 16 government-funded primary and secondary care facilities in a rural district of Zimbabwe.Use of a locally developed screening tool that showed good psychometric properties for detecting common mental disorders in Zimbabwe in HIV-positive urban populations.The screening tool was not validated for the rural setting, and the cutoff score was selected based on data from the urban setting.Adherence to antiretroviral therapy was self-reported.
ENRICHing Medical Imaging Training Sets Enables More Efficient Machine Learning
Authors: Chinn Erin , Arora Rohit , Arnaout Ramy , Arnaout Rima 
Published: May 2021

AbstractObjectiveDeep learning (DL) has been applied in proofs of concept across biomedical imaging, including across modalities and medical specialties1–17. Labeled data is critical to training and testing DL models, but human expert labelers are limited. In addition, DL traditionally requires copious training data, which is computationally expensive to process and iterate over. Consequently, it is useful to prioritize using those images that are most likely to improve a model’s performance, a practice known as instance selection. The challenge is determining how best to prioritize. It is natural to prefer straightforward, robust, quantitative metrics as the basis for prioritization for instance selection. However, in current practice such metrics are not tailored to, and almost never used for, image datasets.MethodsTo address this problem, we introduce ENRICH—EliminateNoise andRedundancy for ImagingChallenges—a customizable method that prioritizes images based on how much diversity each image adds to the training set.ResultsFirst, we show that medical datasets are special in that in general each image adds less diversity than in non-medical datasets. Next, we demonstrate that ENRICH achieves nearly maximal performance on classification and segmentation tasks on several medical image datasets using only a fraction of the available images and outperforms random image selection, the negative control. Finally, we show that ENRICH can also be used to identify errors and outliers in imaging datasets.ConclusionENRICH is a simple, computationally efficient method for prioritizing images for expert labeling and use in DL.
The Telomere Length Landscape of Prostate Cancer
Authors: Livingstone Julie , Shiah Yu-Jia , Yamaguchi Takafumi N. , Heisler Lawrence E. , Huang Vincent , Lesurf Robert , Gebo Tsumugi , Carlin Benjamin , Eng Stefan , Drysdale Erik , Green Jeffrey , van der Kwast Theodorus , Bristow Robert G. , Fraser Michael , Boutros Paul C. 
Published: May 2021

AbstractReplicative immortality is a hallmark of cancer, and can be achieved through telomere lengthening and maintenance. We report telomere lengths (TLs) of 392 localized prostate cancer tumours and characterize their relationship to genomic, transcriptomic and proteomic features. Shorter tumour TLs were associated with elevated genomic instability, including single-nucleotide variants, indels and structural variants. Genes involved in cell proliferation and signaling were correlated with tumour TL at all levels of the central dogma. TL was also associated with multiple clinical features of a tumour. Longer TLs in non-tumour samples were associated with a lower rate of biochemical relapse after definitive local therapy. Our analysis integrates multi-omics data to illuminate the relationship of specific genomic alterations in a tumour and TL in prostate cancer. Although the role of telomere length in cancer has been well studied, its association to genomic features is less well known. We describe the multi-level integration of telomere length, genomics, transcriptomics and proteomics in localized prostate cancer. Patient Summary We examined the association between telomere length and multiple omics-level data in prostate cancer. We observed that traditional telomere mutations are rare in prostate cancer and that telomere length is associated with multiple measure of genomic instability.
A note on decoding elicited and self-generated inner speech
Authors: Jones Oiwi Parker , Voets Natalie L. 
Published: May 2021

AbstractA recent result shows that inner speech can, with proper care, be decoded to the same high-level of accuracy as articulated speech. This relies, however, on neural data obtained while subjects performelicitedtasks, such as covert reading and repeating, whereas a neural speech prosthetic will require the decoding of inner speech that isself-generated. Prior work has, moreover, emphasised differences between these two kinds of inner speech, raising the question of how well a decoder optimised for one will generalise to the other. In this study, we trained phoneme-level decoders on an atypically large, elicited inner speech dataset, previously acquired using 7T fMRI in a single subject. We then acquired a second self-generated inner speech dataset in the same subject. Although the decoders were trained exclusively on neural recordings obtained during elicited inner speech, they predicted unseen phonemes accurately in both elicited and selfgenerated test conditions, illustrating the viability ofzero-shot task transfer. This has significant practical importance for the development of a neural speech prosthetic, as labelled data is far easier to acquire at scale for elicited than for self-generated inner speech. Indeed, elicited tasks may be the only option for acquiring labelled data in critical patient populations who cannot control their vocal articulators.
Correlated Drug Action as a Baseline Model for Combination Therapy in Patient Cohorts and Cell Cultures
Authors: Arun Adith S. , Kim Sung-Cheol , Ahsen Mehmet Eren , Stolovitzky Gustavo 
Published: May 2021

AbstractIdentifying and characterizing the effect of combination therapies is of paramount importance in various diseases, including cancer. Various competing null models have been proposed to serve as baselines against which to compare the effect of drug combinations. In this work, we introduce Correlated Drug Action (CDA), a baseline model for the study of drug combinations in both cell cultures and in patient populations. CDA assumes that the efficacy of pairs of drugs to be used in a combination may be correlated, that is, if the efficacy of a drug in a given patient or cell is high (low), then the efficacy of the other drug may also be high (low) in the same patient or cell. Our model can be used in the temporal domain (temporal CDA or tCDA) to explain survival curves in patient populations, and in the dose domain (dose CDA or dCDA), to explain dose-response curves in cell cultures. At the level of clinical trials, we demonstrate tCDA’s utility in identifying possibly synergistic combinations and cases where the combination can be explained in terms of the monotherapies. At the level of cells in culture, dCDA generalizes null models such as Bliss independence, the Highest Single Agent model, the dose equivalence principle, and is consistent with what should be expected in sham combinations. We demonstrate the applicability of dCDA in assessing combinations in experimental MCF7 cell-line data by introducing a new metric, the Excess over CDA (EOCDA).
Business as Un-usual: Access to mental health and primary care services for people with severe mental illness during the COVID-19 restrictions
Authors: Newbronner Elizabeth , Spanakis Panagiotis , Wadman Ruth , Crossland Suzanne , Heron Paul , Johnston Gordon , Walker Lauren , Gilbody Simon , Peckham Emily 
Published: May 2021

AbstractAimsTo explore: how satisfied people with severe mental illness (SMI) are with the support received during the pandemic; understand any difficulties encountered when accessing both mental health and primary care services; consider ways to mitigate these difficulties; and assess the perceived need for future support from mental health services.Materials and MethodsA representative sample was drawn from a large transdiagnostic clinical cohort of people with SMI, which was recruited between April 2016 and March 2020. The sample was re-surveyed a few months after the beginning of the restrictions. Descriptive frequency statistics were used to analyse the quantitative data. The free text responses were analysed thematically.Results367 participants responded to the survey. Two thirds were receiving support from mental health services with the rest supported in primary care or self-managing. A quarter thought they would need more mental health support in the coming year. Half had needed to used community mental health services during the pandemic and the majority had been able to get support. A minority reported that their mental health had deteriorated but they had either not got the supported they wanted or had not sought help. The biggest service change was the reduction in face-to-face appointments and increasing use of phone and video call support. Nearly half of those using mental health services found this change acceptable or even preferred it; acceptability was influenced by several factors. Participants were more likely to be satisfied with support received when seen in person.DiscussionAlthough most participants were satisfied with the mental health support they had received, a minority were not. This, couple with findings on future need for mental health support has implications for post pandemic demand on services. Remote care has brought benefits but also risks that it could increase inequalities in access to services.
Dengue transmission risk in a changing climate: Bangladesh could experience a longer dengue fever season in the future
Authors: Paul Kishor K , Macadam Ian , Green Donna , Regan David G , Gray Richard T 
Published: May 2021

AbstractOur changing climate is already affecting the transmission of vector borne diseases such as dengue fever. This issue presents a significant public health concern for some nations, such as Bangladesh, which already experience regular seasonal outbreaks of dengue fever under present day conditions. To provide guidance for proactive public health planning to potentially mitigate future infections, we explore the impact of climate change on dengue infections by calculating the change in vectorial capacity of Aedes aegypti mosquito at a seasonal level for all regions in Bangladesh under two scenarios for future atmospheric greenhouse gas concentrations. For each of the four climate models used, and for both scenarios, our analysis reveals that the annual vectorial capacity remains at a level that would enable potential dengue epidemic transmission in all regions in Bangladesh. We found a slight decline in vectorial capacity in half of the regions examined during the last two decades of the 21st Century for the lower-concentration scenario, with a pronounced decline in vectorial capacity in all geographic regions beginning in 2060 for the higher-concentration scenario. The likely reason is that in many regions, warming is leading to sub-optimal mosquito breeding temperatures. However, seasonal differences in vectorial capacity dissipates as the climate warms, to the point that there is almost no observable seasonality for the higher-concentration scenario during the last two decades of this century. This finding suggests there is the potential for the dengue season to extend all year, with outbreaks occurring at any time. Consequently, disease surveillance and control activities would need to be geographically and temporally adapted to mitigate dengue epidemic risk in response to climate change.
Integrative functional analysis uncovers metabolic differences between Candida species
Authors: Begum Neelu , Lee Sunjae , Pellon Aize , Nasab Shervin Sadeghi , Nieslen Jens , Uhlen Mathias , Moyes David , Shoaie Saeed 
Published: May 2021

AbstractCandida species are a dominant constituent of the human mycobiome and a better understanding of their metabolism from a fungal perspective can provide key insights into their ability to cause pathogenesis. Here, we have developed the BioFung database – a fungal specific tool for functional annotation using the KEGG database that provides an efficient method for annotation of protein-encoding gene. Analysis of carbohydrate-active enzyme (CAZymes) and BioFung, uncovered core and accessory features across Candida species demonstrating plasticity, adaptation to the environment and acquired features. Integerative functional analysis revealed that all Candida species can employ amino acid metabolism. However, metabolomics revealed that only a specific cluster of species (AGAu species - C. albicans, C. glabrata and C. auris) utilised amino acid metabolism. We identified critical metabolic pathways in the AGAu clusters with biomarkers and anti-fungal target potential in the CAZyme profile, polyamine, choline and fatty acid biosynthesis pathways. This study, combining genomic analysis, metabolomics and gene expression validation, highlights the metabolic diversity within AGAu species that underlies their remarkable ability to dominate the mycobiome and cause disease.
Language barriers in global bird conservation
Authors: Negret Pablo Jose , Atkinson Scott C. , Woodworth Bradley K. , Tor Marina Corella , Allan James R. , Fuller Richard A. , Amano Tatsuya 
Published: May 2021

AbstractMultiple languages being spoken within a species’ distribution can impede communication among conservation stakeholders, the compilation of scientific information, and the development of effective conservation actions. Here, we investigate the number of official languages spoken within the distributions of 10,863 bird species to identify which ones might be particularly affected by consequences of language barriers. We show that 1587 species have 10 languages or more spoken within their distributions. Threatened, migratory and wide-ranging species have especially many languages spoken within their distribution. Particularly high numbers of species with many languages within their distribution are found in Eastern Europe, Russia and central and western Asia. Global conservation efforts would benefit from implementing guidelines to overcome language barriers, especially in regions with high species and language diversity.
Modeling the effects of Aedes aegypti’s larval environment on adult body mass at emergence
Authors: Walker Melody , Chandrasegaran Karthikeyan , Vinauger Clément , Robert Michael A , Childs Lauren M 
Published: May 2021

AbstractMosquitoes vector harmful pathogens that infect millions of people every year, and developing approaches to effectively control mosquitoes is a topic of great interest. However, the success of many control measures is highly dependent upon ecological, physiological, and life history traits of the mosquito species. The behavior of mosquitoes and their potential to vector pathogens can also be impacted by these traits. One trait of interest is mosquito body mass, which depends upon many factors associated with the environment in which juvenile mosquitoes develop. Our experiments examined the impact of larval density on the body mass of Aedes aegypti mosquitoes, which are important vectors of dengue, Zika, yellow fever, and other pathogens. To investigate the interactions between the larval environment and mosquito body mass, we built a discrete time mathematical model that incorporates body mass, larval density, and food availability and fit the model to our experimental data. We considered three categories of model complexity informed by data, and selected the best model within each category using Akaike’s Information Criterion. We found that the larval environment is an important determinant of the body mass of mosquitoes upon emergence. Furthermore, we found that larval density has greater impact on body mass of adults at emergence than on development time, and that inclusion of density dependence in the survival of female aquatic stages in models is important. We discuss the implications of our results for the control of Aedes mosquitoes and on their potential to spread disease.Author summaryIn this work we examined how the environment in which young mosquitoes develop affects their adult body size as measured by adult body mass. Adult size has potential impacts on mosquito behavior and the ability of mosquitoes to transmit disease. We used a combination of experimental work and mathematical modeling to determine important factors affecting adult mosquito body size. In our model, we incorporated potentially interacting aspects of the mosquito life cycle and traits that affect mosquito growth as juveniles. These aspects include body mass, density of the population, and level of available resource. We compared different models to determine the one that best describes the data. As mass at emergence is linked to the success of adult mosquitoes to produce offspring and to their ability transmit pathogens, we discuss how important influences on development and survival of young mosquitoes affect mosquito control and disease spread.