bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Fetal Growth Restriction on Postnatal Gut Microbiota in a Rat Model
Authors: Arai Yoshiteru , Shoji Hiromichi , Santosa Irena , Awata Kentaro , Tokita Kazuhide , Shimizu Toshiaki 
Published: May 2023

Objective:
Fetal growth restriction (FGR) indicates increased risks of lifestyle-related diseases in adulthood. Previous studies showed the association between human gut dysbiosis and various diseases. However, reports examining the relationship between FGR and gut microbiota are scarce. Herein, we hypothesized that FGR may cause gut dysbiosis and analyzed the gut microbiota in a FGR rat model by restricting maternal protein intake during pregnancy.

Methods:
The FGR group was developed by feeding pregnant Sprague Dawley rats a diet containing 7% protein until birth. Control rats were fed 21% protein. Fecal samples of 2–11-week-old pups were collected weekly. DNA was extracted from each sample and subjected to polymerase chain reaction (PCR) amplification and sequencing. Additionally, short-chain fatty acids in the cecum were analyzed at 2 weeks of age, when there were differences in the occupancy of the gut microbiota.

Results:
Comparative analysis of the gut microbiota showed differences only at 2 weeks of age. Verrucomicrobia was significantly more abundant in the control group (q < 0.1), whereas pathogenic bacteria, including Enterococcus and Enterobacteriaceae, tended to increase in the FGR group. The abundance of acetic and butyric acid-producing bacteria also differed between groups. Acetic acid in the cecum was considerably decreased in the FGR group, while butyric acid was increased compared to that in the control group.

Conclusions:
Normalizing the alteration of FGR on postnatal gut microbiota may have beneficial effects for the host, since the FGR group caused gut dysbiosis.
Monitoring the battleground: Antimicrobial resistance, antibiofilm patterns, and virulence factors of wound bacterial isolates from patients in hospital system.
Authors: Awuor Silas Onyango , Omwenga Eric O. , Mariita Richard M. , Musyoki Stanslaus , Musila Jonathan 
Published: May 2023

Extensive use of antibiotics in the treatment of bacterial infections has led to a challenge of antibiotic resistance, contributing to morbidity and mortality. Herein, evaluation of bacterial isolates from patients with wound discharge was performed and drug susceptibility patterns examined, with a goal of deciphering antibacterial resistance. A cross-sectional study was conducted between May to August 2022, in which samples were collected from patients with chronic wounds and were inoculated into appropriate media for identification and characterization. The bacterial pathogens were identified using standard microbiological methods. The majority of wound isolates showed positive growth in microbial analysis with high prevalence in male candidates. Further, Staphylococcus aureus 28 (20.7%) was identified as the most predominant pathogen followed by Klebsiella spp. 20 (14.8%), P. aeruginosa spp. 10 (14.8%) and lastly E. coli 6 (4.4%) bacteria in the wound isolates while cotrimoxazole 13 (48.1%) followed by clindamycin 7 (25.9%) and erythromycin 7 (25.9%) were the most antibacterial resistant drugs to both Gram positive and Gram-negative bacteria. Out of the four isolates, 3 (75%) isolates were able to produce the haemolysin and protease and 2 (50%) isolates were able to produce the lipase and phospholipase. The findings herein form a clinical basis for identification of antimicrobial resistance in chronic wounds that can be applied in responsible use of antibacterial in chronic wound management and as an illumination in development of more potent antibiotics for chronic wound treatment.
Demographic Influence on the Effectiveness of England’s SARS-CoV-2 Policies
Authors: Dhada Maharshi , Montes Jazmin Labra 
Published: May 2023

ABSTRACTHealth data is key for the development of medicinal drugs, treatments, and policy-planning to control the spread of infectious diseases. However, the collection, curation, and interpretation of health data is often biased. This paper discusses England-wide impact of public policies to control the spread of SARS-CoV-2 (Covid-19) infections, based on the recorded per-capita infection cases between July 2020 to January 2023. The analysis presented herewith highlights the disparities across the upper local tier authorities, in the number of Covid-19 cases recorded in response to the policies. This paper further presents the correlation between the Covid-19 cases count and demographic factors, thus highlighting the key factors determining the effectiveness of the NHS policies, and therefore the need for incorporating demographic imbalance in the policy planning process. It is concluded that the upper local tier authorities comprise of three clusters of low, mid, and high prevalence of Covid-19 infections. Where the regions with high prevalence of Covid-19 cases are also the ones with higher proportions of Black/ Mixed racial groups, amongst a mid-range and low internal Migrations.
Spike ripples localize the epileptogenic zone better than other leading biomarkers: a multicenter intracranial study
Authors: Shi Wen , Shaw Dana , Walsh Katherine G. , Han Xue , Eden Uri T. , Richardson Robert M. , Gliske Stephen V. , Jacobs Julia , Brinkmann Benjamin H. , Worrell Gregory A. , Stacey William C. , Kramer Mark A. , Chu Catherine J. 
Published: May 2023

AbstractObjectiveWe evaluated whether the combination of epileptiform spikes and ripples (spike ripples) outperformed other leading biomarkers in identifying the epileptogenic zone across subjects in a multicenter international study.MethodsWe validated and applied an automated spike ripple detector on intracranial EEG recordings in subjects from 4 centers who subsequently underwent surgical resection with known 1-year seizure outcomes. We evaluated the spike ripple rate in subjects cured after resection (ILAE 1 outcome) and those with persistent seizures (ILAE 2-5) across sites and recording types. We also evaluated spike, wideband HFO (80-500 Hz), fast ripple (250-500 Hz), and ripple (80-250 Hz) rates using validated automated detectors. The proportion of resected events was computed and compared across subject outcomes and biomarkers.Results109 subjects were included. The majority of spike ripples were removed in subjects with ILAE 1 outcome (p = 1e-6), and this was qualitatively observed across the four sites (p = 0.032, p = 0.092, p = 0.0005, p = 0.003) and the two electrode types (p = 0.01, p = 7e-6). A higher proportion of spike ripples were removed in subjects with ILAE 1 outcomes compared to ILAE 2-5 outcomes (p = 0.02). Among ILAE 1 subjects, the proportion of spike ripples removed was higher than the proportion of spikes (p = 0.0004), wideband HFOs (p = 0.0004), fast ripples (p = 0.008), and ripples (p = 0.008) removed. At the individual level, more subjects with ILAE 1 outcome had the majority of spike ripples removed (40/48, 83%) than spikes (69%, p = 0.04), wideband HFOs (63%, p = 0.009), fast ripples (36%, p = 2e-5), or ripples (45%, p = 0.0007) removed.InterpretationWhen surgical resection was successful, the majority of spike ripples were removed. Automatically detected spike ripples have improved specificity for epileptogenic tissue compared to spikes, wideband HFOs, fast ripples, and ripples.
Plasma soluble triggering receptor expressed on myeloid cells 2 is associated with depression after acute ischemic stroke
Authors: Huang Tiansheng , Zhu Yinwei , Lu Yaling , Zhang Qi , Fang Chongquan , Ju Zhong , He Jiang , Zhang Yonghong , Xu Tan , Zhong Chongke 
Published: May 2023

AbstractBackgroundPrevious studies suggested that elevated levels of plasma soluble triggering receptor expressed on myeloid cells 2 (sTREM2) was related to increased risk of death, cardiovascular events and cognitive impairment after stroke. We aimed to prospectively investigate the association between plasma sTREM2 levels and post-stroke depression (PSD).MethodsWe measured plasma sTREM2 levels in 590 ischemic stroke patients from the China Antihypertensive Trial in Acute Ischemic Stroke. The 24-item Hamilton Rating Scale for Depression was used to assess depression at 3 months after ischemic stroke onset, and PSD was defined as a score of ≥8. Logistic regression analysis was performed to evaluate the risk of PSD associated with plasma sTREM2 levels, and net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to assess the predictive value of sTREM2.ResultsOf the 590 participants, 229 (38.8%) patients experienced PSD. The risk of PSD elevated significantly with plasma sTREM2 levels (Pfor trend=0.034). After adjusting for several covariates, the odds ratio for the highest quartile of sTREM2 compared with the lowest quartile was 2.41 (95% CI=1.35-4.31) for PSD. Multiple adjusted spline regression analysis further confirmed the linear dose-response relationship between sTREM2 levels and PSD (Pfor linearity=0.024). The addition of sTREM2 to a conventional model notably improved the risk prediction for PSD (category-free NRI=21.50%, 95% CI=5.92%-37.07%,P=0.011; IDI=1.43%, 95% CI=0.45%-2.42%,P=0.005).ConclusionsThe present study demonstrated that elevated plasma sTREM2 levels were associated with increased risk of PSD, suggesting that sTREM2 may be a promising prognostic biomarker for PSD.RegistrationURL:https://www.clinicaltrials.gov; Unique identifier:NCT01840072.
The impact of atypical intrahospital transfers on patient outcomes: a mixed methods study
Authors: Mendelsohn Estera , Honeyford Kate , Brittin Andy , Mercuri Luca , Klaber Robert Edward , Expert Paul , Costelloe Céire 
Published: May 2023

ABSTRACTBackgroundThe architectural design of hospitals worldwide is centred around individual departments, which require the movement of patients between wards. However, patients do not always take the simplest route from admission to discharge, but can experience convoluted movement patterns, particularly when bed availability is low. Few studies have explored the impact of these rarer, atypical trajectories.MethodsUsing a mixed-method explanatory sequential study design, we firstly used three continuous years of electronic health record data prior to the Covid-19 pandemic, from 55,152 patients admitted to a London hospital network to define the ward specialities by patient type using the Herfindahl-Hirschman index. We explored the impact of ‘regular transfers’ between pairs of wards with shared specialities, ‘atypical transfers’ between pairs of wards with no shared specialities and ‘site transfers’ between pairs of wards in different hospital site locations, on length of stay, 30-day readmission and mortality. Secondly, to understand the possible reasons behind atypical transfers we conducted three focus groups and three interviews with site nurse practitioners and bed managers within the same hospital network.ResultsWe found that at least one atypical transfer was experienced by 12.9% of patients. Each atypical transfer is associated with a larger increase in length of stay, 2.84 days (95%CI: 2.56-3.12), compared to regular transfers, 1.92 days (95%CI: 1.82-2.03). No association was found between odds of mortality, or 30-day readmission and atypical transfers after adjusting for confounders. Atypical transfers appear to be driven by complex patient conditions, a lack of hospital capacity, the need to reach specific services and facilities, and more exceptionally, rare events such as major incidents.ConclusionOur work provides an important first step in identifying unusual patient movement and its impacts on key patient outcomes using a system-wide, data-driven approach. The broader impact of moving patients between hospital wards, and possible downstream effects should be considered in hospital policy and service planning.
Factors associated with excess skin after bariatric surgery: A mixed method study
Authors: Baillot Aurélie , Brunet Jennifer , Lemelin Lucie , Gabriel Shaina A. , Langlois Marie-France , Tchernof André , Biertho Laurent , Rabasa-Lhoret Rémi , Garneau Pierre Y. , Aimé Annie , Bouchard Stéphane , Romain Ahmed J. , Bernard Paquito 
Published: May 2023

AbstractIntroductionAfter metabolic and bariatric surgery (MBS), many patients have excess skin (ES), which can cause inconveniences. Identifying factors related to ES quantity and inconveniences is crucial to inform interventions. The aim of this study was to identify sociodemographic, physical, psychosocial, and behavioral factors associated with ES quantity and inconveniences.MethodsA mixed-method study with a sequential explanatory design was conducted with 124 adults (92% women, Mage46.5±9.9 years, Mtimepost-MBS34.2±27.6 months). During Phase I, ES quantity (arms, abdomen, thighs) and inconveniences, sociodemographic, anthropometric, clinical and behavioral outcomes were assessed. In Phase II, 7 focus groups were performed with 37 participants from Phase I. A triangulation protocol was completed to identify convergences, complementarities, and dissonances from quantitative and qualitative data.ResultsQuantitative data indicate only ES quantity on arms was associated with ES inconveniences on arms (r=.36, p<.01). Total ES quantity was associated with maximal body mass index (BMI) reached pre-MBS (r=.48, p<.05) and current BMI (r=.35, p<.05). Greater ES inconveniences was associated with higher social physique anxiety and age (R2=.50, p<.01). Qualitative data were summarized into 4 themes: psychosocial experiences living with ES, physical ailments due to ES, essential support and unmet needs, and beliefs of ES quantity causes.ConclusionsMeasured ES quantity is related to higher BMI, but not reported inconveniences. Greater self-reported ES quantity and inconveniences were associated with body image concerns.
The potential benefits of delaying seasonal flu vaccine selections: a retrospective modeling study
Authors: Lee Kyueun , Williams Katherine , Englund Janet 
Published: May 2023

AbstractBackgrounds and PurposeAntigenic match between selected vaccine virus and circulating virus crucial to achieve high vaccine effectiveness for seasonal flu. Due to the time-consuming process of producing eggs, vaccine candidate viruses are currently selected 5-6 months ahead of the flu season. New non-egg-based vaccine production technologies have emerged with the potential to improve production efficiency and to revise current vaccine formulation schedules. In this study, we aim to 1) identify the past flu seasons where the opportunity to improve vaccine decision existed if rapid vaccine production were available and to 2) quantify the impact of revising the current vaccine decision schedule, where new vaccine production technologies allow more time for specimen collection prior to vaccine virus selection.MethodsWe extracted the trend in the viral activity of season-predominant strain in three data points: when vaccine decision was made, in between vaccine decision and season starts, and after season starts. Between 2012 and 2020, we first identified the past flu seasons where the season-dominant strains presented increasing activity only after vaccine decisions had already been made in February for the Northern Hemisphere. Using an epidemiological model (SEIR) of season flu in the US, we evaluated the impact of updating vaccine decisions on the epidemic size and the number of flu hospitalizations in the United States.ResultsIn the past flu seasons between 2012 and 2020, the timing when the clades or subclades that predominantly circulated during flu season emerged varied by season. In particular, in 2013/14, season-dominant H3N2 subclade emerged after vaccine decisions were made, contributing to the mismatch between vaccine and circulating virus. If the H3N2 component of the vaccine were updated given the additional viral activity data collected after February, our simulation model showed that the updated vaccine could have averted 5,000-65,000 flu hospitalizations, depending on how much vaccine effectiveness could improve with matching vaccine virus. On the other hand, updating the B/Victoria vaccine component did not yield substantial change in flu burden in the 2019/20 season.ConclusionsWith rapid vaccine production, revising the timeline for vaccine selection can result in substantial epidemiological benefits, particularly at times when additional data help improve the vaccine effectiveness through better match between vaccine and circulating viruses.
Phenotyping and prediction of paediatric abdominal pain: A machine learning approach
Authors: Takahashi Kazuya , Lubiatowska Michalina , Shehwana Huma , Ruffle James K. , Williams John A , Acharjee Animesh , Terai Shuji , Gkoutos Georgios V , Satti Humayoon , Aziz Qasim 
Published: May 2023

AbstractDue to patient heterogeneity, the exact mechanisms of paediatric abdominal pain (AP) remain unknown. We sought to resolve this by identifying paediatric AP phenotypes and developing predictive models to determine their associated factors. In 13,790 children from a large birth cohort, the frequencies of paediatric and maternal demographics and comorbidities were catalogued from general practitioner records. Unsupervised machine learning clustering was used to identify phenotypes of paediatric AP with shared characteristics. Predictive paediatric AP models were constructed using paediatric and maternal demographics and comorbidities.1,274 children experienced AP (9.2 %) (average age: 8.4 ± 1.1 years old, male/female: 615/659), who clustered into 3 distinct phenotypes: phenotype 1 with an allergic predisposition (n = 137), phenotype 2 with maternal comorbidities (n = 676), and phenotype 3 with minimal other comorbidities (n = 340). As the number of allergic diseases or maternal comorbidities increased, so did the frequency of AP, with 17.6% of children with ≥ 3 allergic diseases and 25.6% of children with ≥ 3 maternal comorbidities. Furthermore, in high-risk children who met both ≥ 3 allergic diseases and ≥ 3 maternal comorbidities, 30.8% had AP. Predictive models demonstrated modest fidelity in predicting paediatric AP (AUC 0.66), showing that a child’s ethnicity and paediatric/maternal comorbidities were strongly predictive factors. Our findings reveal distinct phenotypes and associated factors of paediatric AP, suggesting targets for future research to elucidate the exact mechanisms of paediatric AP related to allergic diseases, ethnicity, and maternal comorbidities.
Associations between early in-hospital medications and the development of delirium in patients with stroke
Authors: Ryan Sophia L. , Liu Xiu , McKenna Vanessa , Ghanta Manohar , Muniz Carlos , Renwick Rachel , Westover M. Brandon , Kimchi Eyal Y. 
Published: May 2023

ABSTRACTObjectivesPatients hospitalized with stroke develop delirium at higher rates than general hospitalized patients. While several medications are associated with existing delirium, it is unknown whether early medication exposures are associated with subsequent delirium in patients with stroke. Additionally, it is unknown whether delirium identification is associated with changes in the prescription of these medications.Materials and MethodsWe conducted a retrospective cohort study of patients admitted to a comprehensive stroke center, who were assessed for delirium by trained nursing staff during clinical care. We analyzed exposures to multiple medication classes in the first 48 hours of admission, and compared them between patients who developed delirium >48 hours after admission and those who never developed delirium. Statistical analysis was performed using univariate testing and multivariable logistic regression.Results1,710 unique patients were included in the cohort, of whom 471 (27.5%) developed delirium >48 hours after admission. Delirium was associated with prior exposure to antipsychotics, sedatives, opiates, and antimicrobials, even after accounting for several clinical covariates. Usage of these medications decreased in the 48 hours following delirium identification, except for atypical antipsychotics, whose use increased. Other medication classes such as steroids, benzodiazepines, and sleep aids were not initially associated with subsequent delirium, but prescription patterns still changed after delirium identification.ConclusionsEarly exposure to multiple medication classes is associated with the subsequent development of delirium in patients with stroke. Additionally, prescription patterns changed following delirium identification, suggesting that these medication classes may be modifiable targets for future delirium prevention strategies.140-character messageEarly exposure to specific medication classes is associated with delirium in patients with stroke & may be targets for future prevention.@SophiaLRyan, @ekimchi, @MGHNeurology, @MSHSNeurology, @NMNeurology
Dengue in Cambodia 2002-2020: Cases, Characteristics and Capture by National Surveillance
Authors: Yek Christina , Li Yimei , Pacheco Andrea R. , Lon Chanthap , Duong Veasna , Dussart Philippe , Chea Sophana , Lay Sreyngim , Man Somnang , Kimsan Souv , Huch Chea , Leang Rithea , Huy Rekol , Brook Cara E. , Manning Jessica E. 
Published: May 2023

AbstractObjectiveData from 19 years of national dengue surveillance in Cambodia (2002-2020) were analyzed to describe trends in dengue case characteristics and incidence.MethodsGeneralized additive models were fitted to dengue case incidence and characteristics (mean age, case phenotype, fatality) over time. Dengue incidence in a pediatric cohort study (2018-2020) was compared to national data during the same period to evaluate disease under-estimation by national surveillance.FindingsDuring 2002-2020, there were 353,270 cases of dengue (average age-adjusted incidence 1.75 cases/ 1,000 persons/ year) recorded in Cambodia, with an estimated 2.1-fold increase in case incidence between 2002 and 2020 (slope = 0.0058, SE = 0.0021, p = 0.006). Mean age of infected individuals increased from 5.8 years in 2002 to 9.1 years in 2020 (slope = 0.18, SE = 0.088, p <0.001); case fatality rates decreased from 1.77% in 2002 to 0.10% in 2020 (slope = - 0.16, SE = 0.0050, p <0.001). When compared to cohort data, national data under-estimated clinically apparent dengue case incidence by 5.0-fold (95% CI 0.2 – 26.5), and overall dengue case incidence (both apparent and inapparent cases) by 33.6-fold (range: 18.7-53.6).ConclusionDengue incidence in Cambodia is increasing and disease is shifting to older pediatric populations. National surveillance continues to under-estimate case numbers. Future interventions should account for disease under-estimation and shifting demographics for scaling and to target appropriate age groups.
Understanding ethnic diversity in open dementia neuroimaging datasets
Authors: Heng Nicholas , Rittman Timothy 
Published: May 2023

AbstractIntroductionEthnic differences in dementia are increasingly recognised in epidemiological measures and diagnostic biomarkers. Nonetheless, ethnic diversity remains limited in many study populations Here we provide insights into ethnic diversity in open access neuroimaging dementia datasets.MethodsDatasets comprising dementia populations who underwent neuroimaging assessment with available data on ethnicity were included. Statistical analyses of sample and effect sizes were based on the Cochrane Handbook.Results14 databases were included, with 12 studies of healthy and MCI groups, and 11 of dementia groups. Combining all studies, the largest ethnic group was Caucasian (21,512 participants) with the next most common being Afro-Caribbean (1,960), followed by Asian (780). The smallest effect size detectable within the Caucasian group was 0.03, compared to Afro-Caribbean (0.1) and Asian (0.16).DiscussionOur findings quantify the lack of ethnic diversity in openly available neuroimaging dementia datasets. More representative data would facilitate the development and validation of neuroimaging biomarkers relevant across ethnicities.