bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive evolutionary modelling for influenza virus by site-based dynamics of mutations
Authors: Lou Jingzhi , Liang Weiwen , Cao Lirong , Zhao Shi , Chen Zigui , Yi Chan Renee Wan , Hang Cheung Peter Pak , Zheng Hong , Liu Caiqi , Li Qi , Chun Chong Marc Ka , Zhang Yexian , Yeoh Eng-kiong , Chan Paul Kay-Sheung , Ying Zee Benny Chung , Pun Mok Chris Ka , Wang Maggie Haitian 
Published: August 2023

AbstractA predictive evolutionary model was developed to forecast representative influenza viral strains and select vaccine strains for upcoming epidemic seasons. Influenza virus continuously evolves to escape human adaptive immunity and generates seasonal epidemics. A computational approach beth-1 that models site-wise mutation dynamics demonstrated remarkable matching of predicted strains to the circulating viruses in subsequent seasons for the influenza A(H1N1)pdm09 and A(H3N2) viruses in both retrospective and prospective validations. The method offers a promising and ready-to-use tool to facilitate vaccine strain selection for the influenza virus, achieved by capturing heterogeneous evolutionary dynamics over genome space-time and linking molecular variants to population immune response.One-Sentence SummaryA computational model predicts virus evolution and facilitates vaccine strain selection for the influenza virus
Red cabbage juice-mediated gut microbiota modulation improves intestinal epithelial homeostasis and ameliorates colitis
Authors: Jean Wilson Emily , Sirpu Natesh Nagabhishek , Ghadermazi Parsa , Pothuraju Ramesh , Shanmugam Marudhupandiyan , Prajapati Dipakkumar R. , Pandey Sanjit , Kaifi Jussuf T. , Dodam John R. , Bryan Jeffrey , Lorson Christian L. , Watrelot Aude A. , Foster Jason M. , Mansel Thomas J. , Joshua Chan Siu Hung , Batra Surinder K. , Subbiah Jeyamkondan , Rachagani Satyanarayana 
Published: August 2023

ABSTRACTGut microbiota plays a crucial role in inflammatory bowel disease (IBD) and has therapeutic benefits. Thus, targeting the gut microbiota is a promising therapeutic approach for IBD treatment. We recently found that red cabbage juice (RCJ) ameliorates dextran sulfate sodium (DSS)-induced colitis in mice. However, the underlying mechanisms remain unknown. The current study investigated the modulation of gut microbiota in response to treatment with RCJ to ameliorate the DSS colitis. The initial results demonstrated that mice treated with DSS + RCJ showed increased body weight and decreased diarrhea and blood in feces compared to the DSS alone group. RCJ ameliorated colitis by regulating the intestinal barrier function by reducing the number of apoptotic cells, improving colonic protective mucin, and increasing tight junction protein in RCJ + DSS groups compared to the DSS group. Short-gun metagenomic analysis revealed significant enrichment of short-chain fatty acid (SCFAs)-producing bacteria(Butyrivibrio, Ruminococcaceae, Acetatifactor muris, Rosburia Sp.CAG:303, Dorea Sp.5-2) increased PPAR-© activation, leading to repression of the nuclear factor κB (NFκB) signaling pathway, thus decreasing the production of crucial inflammatory cytokines and chemokines in the RCJ + DSS groups compared to the DSS group. Pathway abundance analysis showed an increased abundance of the SCFA pathway, reduced histidine degradation (Bacteroides sartorii, and Bacteroides caecimuris), and LCFA production in the RCJ+DSS treated group, suggesting the promotion of good colonic health. Furthermore, increased T-reg (FOXP3+) cells in the colon were due to SCFAs produced by the gut microbiota, which was corroborated by an increase in IL-10, a vital anti-inflammatory cytokine. Thus, our study provides the first evidence that RCJ ameliorates colonic inflammation by modulating the gut microbiota.
Respiration recording for fMRI: breathing belt versus spine coil sensor
Authors: Wilding Marilena , Ischebeck Anja , Zaretskaya Natalia 
Published: August 2023

AbstractPhysiological signals such as pulse and respiration strongly contribute to non-neuronal signal change of the blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI). This has been observed not only during task-based but also during resting-state fMRI measurements, where the confounding influence of physiological signals is most pronounced. Over the last decades, a variety of techniques evolved, aiming at detecting and removing physiological artifacts in fMRI time series. These follow either a solely data-driven approach or rely on externally recorded physiological data. To record cardiac and respiratory signals, typically pulse oximetry or electrocardiography (ECG) and a respiration belt are used, respectively. New technologies allow to capture respiratory signal directly with a sensor placed within the spine coil in the patient table, eliminating the need of a respiration belt, which considerably increases participants’ comfort. However, little is known about the effectiveness of these new technologies and how they compare to the standard respiration belt recording. In the current study, we compared the two devices, respiration belt and spine coil sensor, in their suitability for physiological noise removal during a visual perception task and during rest. We did not find any differences in resting-state functional connectivity (RSFC) or stimulus-related activity between data corrected with the two recording devices. However, we did find reduced residual noise in the time series corrected with spine coil-derived respiration signals compared to belt-based corrected data in the task dataset. Our results show that spine coil-derived respiration recordings are slightly superior to belt respiration recordings for physiological noise removal in task-induced activity, with spine coil recordings having an additional advantage in terms of subject comfort.
Disparities in adherence to antiretroviral therapy of the selected subpopulations among adults living with HIV/AIDS in Tanzania. Analysis of a population-based survey 2016-17
Authors: Adam Dayani , Balan Ramkumar T. , Ismail Abbas 
Published: August 2023

AbstractAdherence is a critical component of successful HIV treatment among people living with HIV/AIDS. It is essential for achieving and maintaining viral suppression, which is the primary goal of HIV care and treatment. The objective of this study was to assess the disparity of the treatment adherence of selected subpopulations among HIV adult patients in Tanzania. The study used a cross-sectional survey of 792 adults living with HIV/AIDS from 31 regions in Tanzania. A two-stage stratified cluster design was used in this survey and included jackknife replicate sampling weights. Frequency tables displaying frequencies, weighted proportions, and confidence intervals were employed to depict socio-demographics by treatment adherence. Treatment adherence was calculated by subtracting missed doses from prescribed doses, dividing the result by the prescribed dosage, and multiplying by 100 to establish a percentage. Rao-Scott chi-square was used to produce the weighted proportions of the adherence within subpopulations. Also, the Adjusted Wald Test was used to examine whether or not the subpopulations are similar to or different in terms of their level of treatment adherence. The results showed that there was a significant difference in treatment adherence between the selected subpopulations. The majority of the selected subpopulations, including those based on age, sex, marital status, and level of education, were found to have disparities in the level of treatment adherence. However, the study also revealed no disparities in treatment adherence between urban and rural settings, married and widowed, age groups of 25 to 34, and those of 55 and over. The study’s findings revealed considerable disparities in treatment adherence between various subpopulations, emphasizing the necessity for specifically developed interventions to address these disparities to attain better health outcomes among adults living with HIV/AIDS.
Prevalence of Modifiable Risk Factors for Cardiovascular Disease among School-going Children and Adolescents in Eldoret, Kenya
Authors: Magutah Karani , Mbuthia Grace Wambura , Osengo Gilbert , Odhiambo Dancun , Meiring Rebecca 
Published: August 2023

AbstractCardiovascular disease (CVD) prevalence in Kenya is rising. Overweight, pre-hypertension and physical inactivity in younger ages is contributory. These risk factors are inadequately documented among Kenyan children and adolescents, hampering CVD prevention.This cross-sectional study randomly sampled 384 school children and adolescents. After obtaining assent and consent, global physical activity (PA) questionnaire was used to assess PA. Body mass index (BMI), Waist-Hip Ratio (WHR) and Waist-Height Ratio (WHtR) were determined. Blood pressure (BP) was also measured.Participants were 14.6±2.7 years, and 62.6% were female. Overall BMI was 19.8±3.9 kg/m2with 8% having ≥25.0 kg/m2, 87% of whom were in secondary schools. Using SBP, 27.9% were at risk of CVD. For age ≥13 years old, males and females proportions were 42.5% and 20% respectively while that for <13 years old, it was 26.5% and 27% respectively. For DBP, 12.8% had elevated- to-hypertensive BP. For ages ≥ 13 years old, this was 13.2% and 8.3% for males and females respectively and for the <13 years old, the respective percentages were 11.8 and 25.4. Combining SBP and DBP, 8.1% of participants, mostly males, had elevated-to-hypertensive BP. Thirty-one percent of boys and 15.6% of girls were at CVD risk using respective WHR cutoffs of 0.90 and 0.85 (males, 0.93±0.02; females, 0.89±0.03). For WHtR, 39.6% of boys had values >0.463 cut-off (0.493±0.02), with 52.6% in secondary schools against 32.4% for girls having >0.469 cut-off (0.517±0.05), 69.7% being in secondary schools. Overall, 45% of participants were sports-inactive and 77.2% did minimal PA.Among school-going children and adolescents in Eldoret, Kenya, prevalence of CVD risk-factors was high especially among boys and in high schools. Large proportions had elevated BP, BMI, WHR and WHtR, and, further, were sedentary, posing high CVD risk. Lifestyle interventions to mitigate this public health concern among children and adolescent are urgently needed.
Improving diagnosis of non-malarial fevers in Senegal:Borreliaand the contribution of tick-borne bacteria
Authors: Levine Zoë C. , Sene Aita , Mkandawire Winnie , Deme Awa B. , Ndiaye Tolla , Sy Mouhamad , Gaye Amy , Diedhiou Younouss , Mbaye Amadou M. , Ndiaye Ibrahima , Gomis Jules , Ndiop Médoune , Sene Doudou , Paye Marietou Faye , MacInnis Bronwyn , Schaffner Stephen F. , Park Daniel J. , Badiane Aida S. , Colubri Andres , Ndiaye Mouhamadou , Sy Ngayo , Sabeti Pardis C. , Ndiaye Daouda , Siddle Katherine J. 
Published: August 2023

AbstractThe worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata from febrile patients and healthy controls in a low malaria burden area. Using 16S and unbiased sequencing, we detected viral, bacterial, or eukaryotic pathogens in 29% of NMFI cases. Bacteria were the most common, with relapsing feverBorreliaand spotted feverRickettsiafound in 15% and 3.7% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosedPlasmodium, including one putativeP. ovaleinfection. We developed a logistic regression model to distinguishBorreliafrom NMFIs with similar presentation based on symptoms and vital signs. These results highlight the challenge and importance of improved diagnostics, especially forBorrelia, to support diagnosis and surveillance.
Breast cancer epidemiology in women from colombian caribbean region during 2018-2021
Authors: Pérez Bravo Valentina Vanessa , Vásquez Serge Valentina Alexandra , Norwood Lobo George , Alcocer Olaciregui Adalgisa , Vargas Moranth Rusvelt 
Published: August 2023

ABSTRACTBackgroundBreast cancer is a global public health problem, representing a significant burden at the personal, collective, economic and quality of life level. It is necessary to consider the incidence, prevalence and mortality of this disease with a regional approach, so the objective of this work is to describe the epidemiological behavior of this tumor in the departments of the Colombian Caribbean Region during the period 2018 to 2021.MethodologyDescriptive, retrospective study. Data from a secondary source (Cuenta de Alto Costo) was taken through the Higia platform. Rates x 100,000 of proportion of new cases reported, prevalence and incidence, by departments are analyzed. Data was imported from a downloadable.csv file into Excel and then into SPSS V22.ResultsThe indicators analyzed showed a heterogeneous behavior in the 8 departments of the Region. Atlántico and Bolívar were the departments with similar and higher figures in the 4 years observed than those of the country and there were atypical values in San Andrés. La Guajira was the only department with a sustained tendency to increase in incidence, prevalence and mortality.
Nutritional traits in the prodromal phase of Parkinson’s disease in community-dwelling older adults in Japan
Authors: Yamaguchi Takashi , Nozaki Ryota , Taguchi Keita , Suzuki Yoshio , Takahashi Kai , Takahashi Kenta , Iwaoka Kazuhiro , Sato Yuriko , Terauchi Takahiro , Akasaka Hiroshi , Ishizuka Naoki , Uchida Kazuhiro , Ninomiya Toshiharu , Maeda Tetsuya 
Published: August 2023

AbstractThe growing aging population means that increasing numbers of people are living with Parkinson’s disease (PD). Although dopamine replacement is effective, there are currently no curative or disease-modifying treatments. Nutrition is a well-known environmental risk factor of PD. This study aimed to clarify the relationship between nutritional traits and the prodromal phase of PD.Subjects were enrolled from community-dwelling older adults. To identify individuals with prodromal PD (PPD), probability of PPD (PPP) and mild parkinsonian sign (MPS) assessments were used. Nutritional status was evaluated using a self-administered food frequency questionnaire form. Intakes of total energy, the three major nutrients (fat, protein, and carbohydrate), B vitamins, water, and dietary fiber were calculated. Nutrient intake in PPD was analyzed using analysis of covariance with age and sex as covariates.We enrolled 305 subjects. The prevalence of older adults living with PPD was 4.1% by PPP ≥ 0.3 and 21.0% by MPS criteria. Compared with subjects without PPD, individuals with PPP ≥ 0.3 had significantly higher fat intake (33.4 ± 8.8 vs. 29.3 ± 6.7 g/1000 kcal/day, p=0.037) and lower carbohydrate intake (121.4 ± 19.0 vs. 132.1 ± 17.7 g/1000 kcal/day, p=0.039), and MPS-positive subjects had significantly lower total energy intake (1817.5 ± 384.7 vs. 1933.7 ± 433.7 kcal/day, p=0.012).In this community-based cross-sectional study, nutritional traits differed between older individuals with and without PPD; these differences were more pronounced when the PPP was used to evaluate PPD. Nutrition and diet may thus modify PD incidence.
Personalized Machine Learning using Passive Sensing and Ecological Momentary Assessments for Meth Users in Hawaii: A Research Protocol
Authors: Washington Peter 
Published: August 2023

AbstractBackgroundArtificial intelligence (AI)-powered digital therapies which detect meth cravings delivered on consumer devices have the potential to reduce these disparities by providing remote and accessible care solutions to Native Hawaiians, Filipinos, and Pacific Islanders (NHFPI) communities with limited care solutions. However, NHFPI are fully understudied with respect to digital therapeutics and AI health sensing despite using technology at the same rates as other races.ObjectiveWe seek to fulfill two research aims: (1) Understand the feasibility of continuous remote digital monitoring and ecological momentary assessments (EMAs) in NHFPI in Hawaii by curating a novel dataset of longitudinal FitBit biosignals with corresponding craving and substance use labels. (2) Develop personalized AI models which predict meth craving events in real time using wearable sensor data.MethodsWe will develop personalized AI/ML (artificial intelligence/machine learning) models for meth use and craving prediction in 40 NHFPI individuals by curating a novel dataset of real-time FitBit biosensor readings and corresponding participant annotations (i.e., raw self-reported substance use data) of their meth use and cravings. In the process of collecting this dataset, we will glean insights about cultural and other human factors which can challenge the proper acquisition of precise annotations. With the resulting dataset, we will employ self-supervised learning (SSL) AI approaches, which are a new family of ML methods that allow a neural network to be trained without labels by being optimized to make predictions about the data itself. The inputs to the proposed AI models are FitBit biosensor readings and the outputs are predictions of meth use or craving. This paradigm is gaining increased attention in AI for healthcare.ConclusionsWe expect to develop models which significantly outperform traditional supervised methods by fine-tuning to an individual subject’s data. Such methods will enable AI solutions which work with the limited data available from NHFPI populations and which are inherently unbiased due to their personalized nature. Such models can support future AI-powered digital therapeutics for substance abuse.
Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models
Authors: Ye Jiancheng , Hai Jiarui , Song Jiacheng , Wang Zidan 
Published: August 2023

ABSTRACTObjectiveTo propose a novel approach for enhancing clinical prediction models by combining structured and unstructured data with multimodal data fusion.MethodsWe presented a comprehensive framework that integrated multimodal data sources, including textual clinical notes, structured electronic health records (EHRs), and relevant clinical data from National Electronic Injury Surveillance System (NEISS) datasets. We proposed a novel hybrid fusion method, which incorporated state-of-the-art pre-trained language model, to integrate unstructured clinical text with structured EHR data and other multimodal sources, thereby capturing a more comprehensive representation of patient information.ResultsThe experimental results demonstrated that the hybrid fusion approach significantly improved the performance of clinical prediction models compared to traditional fusion frameworks and unimodal models that rely solely on structured data or text information alone. The proposed hybrid fusion system with RoBERTa language encoder achieved the best prediction of the Top 1 injury with an accuracy of 75.00% and Top 3 injuries with an accuracy of 93.54%.ConclusionOur study highlights the potential of integrating natural language processing (NLP) techniques with multimodal data fusion for enhancing clinical prediction models’ performances. By leveraging the rich information present in clinical text and combining it with structured EHR data, the proposed approach can improve the accuracy and robustness of predictive models. The approach has the potential to advance clinical decision support systems, enable personalized medicine, and facilitate evidence-based health care practices. Future research can further explore the application of this hybrid fusion approach in real-world clinical settings and investigate its impact on improving patient outcomes.
Protozoan predation enhances stress resistance and antibiotic tolerance in the opportunistic pathogenBurkholderia cenocepaciaby triggering the SOS response
Authors: Morón Álvaro , Belinchón Iván , Tarhouchi Alaa E. , Valenzuela Juan M. , de Francisco Patricia , Martín-González Ana , Amaro Francisco 
Published: August 2023

AbstractBacterivorous protists are thought to serve as training grounds for bacterial pathogens by subjecting them to the same hostile conditions that they will encounter in the human host. Bacteria that survive intracellular digestion exhibit enhanced virulence and stress resistance after successful passage through protozoa but the underlying mechanisms remain to be clarified. Here we show that the opportunistic pathogenBurkholderia cenocepaciasurvives phagocytosis by ciliates found in domestic and hospital sink drains, and viable bacteria are expelled packaged in respirable membrane vesicles with enhanced resistance to oxidative stress, desiccation and antibiotics, thereby contributing to bacterial dissemination in the environment. By using diverse methodological approaches, we demonstrate that reactive oxygen species generated within the protozoan phagosome promote the formation of persisters tolerant to ciprofloxacin by activating the bacterial SOS response. Besides, we show that genes encoding antioxidant enzymes are upregulated during passage through ciliates increasing bacterial resistance to oxidative radicals. We prove that suppression of the SOS response impairs bacterial intracellular survival and persister formation within protists. This study highlights the significance of protozoan food vacuoles as niches that foster bacterial adaptation in natural and built environments and suggests that persister switch within phagosomes may be a widespread phenomenon in bacteria surviving intracellular digestion.
Age and obesity-driven changes in the extracellular matrix of the primary tumor and metastatic site influence tumor invasion and metastatic outgrowth
Authors: Conner Sydney J. , Guarin Justinne R. , Borges Hannah B. , Salhany Kenneth J. , Mensah Diamond N. , Hamilton Grace A. , Le Giang H. , Oudin Madeleine J. 
Published: August 2023

AbstractYounger age and obesity increase the incidence and metastasis of triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer. The extracellular matrix (ECM) promotes tumor invasion and metastasis. We characterized the effect of age and obesity on the ECM of mammary fat pads, lungs, and liver using a diet-induced obesity (DIO) model. At 4 week intervals, we either injected the mammary fat pads with allograft tumor cells to characterize tumor growth and metastasis or isolated the mammary fat pads and livers to characterize the ECM. Age had no effect on tumor growth but increased lung and liver metastasis after 16 weeks. Obesity increased tumor growth starting at 12 weeks, increased liver metastasis only at 4 weeks, and weight gain correlated to increased lung but not liver metastasis. Utilizing whole decellularized ECM coupled with proteomics, we found that early stages of obesity were sufficient to induce changes in the ECM composition and invasive potential of mammary fat pads with increased abundance of pro-invasive ECM proteins Collagen IV and Collagen VI. We identified cells of stromal vascular fraction and adipose stem and progenitor cells as primarily responsible for secreting Collagen IV and VI, not adipocytes. We characterized the changes in ECM in the lungs and liver, and determined that older age decreases the metastatic potential of lung and liver ECM while later-stage obesity increases the metastatic potential. These data implicate ECM changes in the primary tumor and metastatic microenvironment as mechanisms by which age and obesity contribute to breast cancer progression.SignificanceYounger age and obesity increase the incidence and metastasis of triple-negative breast cancer. Our data suggest that changes in the breast, lung and liver ECM are driving some of these effects.