bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regional disparities in Dementia-free Life Expectancy in Japan: an ecological study, using the Japanese long-term care insurance claims database
Authors: Yoshikawa Mikako , Goto Etsu , Shin Jung-ho , Imanaka Yuichi 
Published: December 2022

AbstractBackgroundThe number of people with dementia increases in an aging society; therefore, promoting policies for dementia throughout the community is crucial to creating a dementia-friendly society. Understanding the status of older adults with dementia in each region of Japan will be a helpful indicator. We calculated Dementia-free Life Expectancy and aimed to examine regional disparities and their associated factors.MethodsWe calculated Dementia-free Life Expectancy and Life Expectancy with Dementia for each secondary medical area in Japan based on the Degree of Independence in Daily Living for the Demented Elderly, using data extracted from the Japanese long-term care insurance claims database. We then conducted a partial least squares regression analysis, the objective variables being Dementia-free Life Expectancy and Life Expectancy with Dementia for both sexes at age 65, and explanatory regional-level variables included demographic, socioeconomic, and healthcare resources variables.ResultsThe mean estimated regional-level Dementia-free Life Expectancy at age 65 was 17.33 years (95% confidence interval [CI] 17.27–17.38) for males and 20.05 years (95% CI 19.99–20.11) for females. Three latent components identified by partial least squares regression analysis represented urbanicity, socioeconomic conditions, and health services-related factors of the secondary medical areas. The second component explained the most variation in Dementia-free Life Expectancy of the three, indicating that higher socioeconomic status was associated with longer Dementia-free Life Expectancy.ConclusionsThere were regional disparities in secondary medical area level Dementia-free Life Expectancy. Our results suggest that socioeconomic conditions are more related to Dementia-free Life Expectancy than urbanicity and health services-related factors.
A Semi-Supervised Contrastive Learning Approach to Alzheimer’s Disease Diagnostics using Convolutional Autoencoders
Authors: Jung Edward , Kashyap Anshul , Hsu Brandon , Moreland Mason , Chantaduly Chanon , Chang Peter D. 
Published: December 2022

ABSTRACTPURPOSEAlzheimer’s Disease (AD) is a neurodegenerative disease that progressively deteriorates memory and cognitive abilities. PET 18F-AV45 (florbetapir) is a common imaging modality used to characterize the distribution of beta-amyloid deposits in the brain, however interpretation may be subjective and the misdiagnosis rate of AD ranges from 12-23%. Automated algorithms for PET 18F-AV45 interpretation including those derived from deep learning may facilitate more objective and accurate AD diagnosis.MATERIALS & METHODSA total of 1232 PET AV45 scans (207 - AD; 1025 - normal) were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A semi-supervised deep learning framework was developed to differentiate AD and normal patients. The framework consists of an autoencoder (AE), a contrastive learning loss, and a categorical classification head. A contrastive learning paradigm is used to improve the discriminative properties of latent feature vectors in multidimensional space.RESULTSUpon five-fold cross-validation, the best-performing semi-supervised contrastive model achieved validation accuracy of 82% to 86%. Secondary analysis included visualization of intermediate activations, classification report verification, and principal component analysis (PCA) of latent feature vectors. The training process yielded optimal converging losses for all three loss frameworks.CONCLUSIONA deep learning model can accurately diagnose AD using PET 18F-AV45 scans. Such models require large amounts of labeled data during training. The use of a semi-supervised contrastive learning objective and AE regularizer helps to improve model performance, especially when dataset sizes are constrained. Latent representations extracted by the model are visually clustered strongly with the addition of a contrastive learning mechanism.Summary StatementA semi-supervised contrastive learning deep learning system optimizes latent feature vector representations and yields strong model classification performance for larger data distributions within the Alzheimer’s Disease diagnostics domain.Key PointsA common diagnostic procedure used by trained radiologists in the clinical setting is the visual analysis of PET 18F-AV45 neuroimaging scans to diagnose the different stages of Alzheimer’s Disease in a patient.Contrastive learning is a strategy that allows for the optimization of latent feature representations in multidimensional space through the use of a loss function that maximizes the distance between feature vectors of different classes and minimizes the distance of feature vectors of the same class.A semi-supervised contrastive learning approach can lead to improved performance and generalization of deep learning models optimized using small training datasets as encountered in Alzheimer’s Disease and other neurodegenerative conditions.
Multimodal neuroimaging data from a 5-week heart rate variability biofeedback randomized clinical trial
Authors: Yoo Hyun Joo , Nashiro Kaoru , Min Jungwon , Cho Christine , Mercer Noah , Bachman Shelby L. , Nasseri Padideh , Dutt Shubir , Porat Shai , Choi Paul , Zhang Yong , Grigoryan Vardui , Feng Tiantian , Thayer Julian F. , Lehrer Paul , Chang Catie , Stanley Jeffrey A. , Marmarelis Vasilis Z. , Narayanan Shrikanth , Nation Daniel A. , Wisnowski Jessica , Mather Mara 
Published: December 2022

AbstractWe present data from the Heart Rate Variability and Emotion Regulation (HRV-ER) randomized clinical trial testing effects of HRV biofeedback. Younger (N = 121, ages 18-31, 61 female) and older (N = 72, ages 55-80, 45 female) participants completed baseline magnetic resonance imaging (MRI) including T1-weighted, functional MRI (fMRI), pulsed continuous arterial spin labeling (PCASL), and proton magnetic resonance spectroscopy (1H MRS). They also completed an emotion regulation task during fMRI. During fMRI scans, physiological measures (blood pressure, pulse, respiration, and end-tidal CO2) were continuously acquired. Participants were randomized to either increase heart rate oscillations or decrease heart rate oscillations during daily sessions. After 5 weeks of HRV biofeedback, they repeated the baseline measurements in addition to a few new measures (ultimatum game fMRI, training mimicking during blood oxygen level dependent (BOLD) and PCASL fMRI). Participants also wore a wristband sensor to estimate sleep time. Psychological assessment comprised three cognitive tests as well as ten questionnaires related to emotional well-being. Data is publicly available via the OpenNeuro data sharing platform.
Characterizing gun violence by time, day of the week, and holidays in six US cities 2015-2021
Authors: Klerman Elizabeth B. , Affouf Mahmoud , Robbins Rebecca , Iyer Jay , Masiakos Peter T. , Sacks Chana A. 
Published: December 2022

AbstractDeveloping interventions to prevent firearm-related violence and to address its consequences requires an improved understanding of when these violent events are most likely to occur. We explored gunshot events by time of day, day of week, and holiday/non-holiday in six major US cities. We utilized publicly available police department datasets that report the date and time of day of gunshot events from six major US cities. In these cities, shootings occurred most often at night and on holidays and weekends, with significant interaction effects. Primary prevention efforts should consider this differential risk.
Outcomes After Percutaneous Tracheostomy in Patients with COVID-19: A Single-Center Series of 377 Cases
Authors: Alshukry Abdullah , Alhindi Abdulrazzaq , Alzuabi Majdah , Husain Seema , Tarakmeh Mohammad , Al Qattan Shaima , Al Bader Abdullah , Al Habib Ali , Ali Yaseen , Al-Mulla Fahd , Ali Hamad , Bu Abbas Mohammad 
Published: December 2022

ABSTRACTIntroductionThe COVID 19 pandemic was highlighted by a rise in hospital admissions secondary to respiratory decompensation. This was accompanied by an increase in ICU admissions, endotracheal intubation and mechanical ventilation. As a consequence, tracheostomies became essential in preventing complications of prolonged intubation and to facilitate weaning from sedation and mechanical ventilation. With the lack of international consensus on tracheostomy technique and optimal timing, we present our experience with 377 percutaneous tracheostomies performed on critically ill COVID 19 patients.ObjectiveTo report the outcomes of critically ill patients with COVID-19 who underwent percutaneous tracheostomy during a period of 24 months.MethodsA retrospective single-center electronic chart review was performed on all ICU patients who underwent percutaneous tracheostomy after respiratory failure secondary to COVID-19 between March 2020 to March 2022.ResultsA total of 377 percutaneous tracheostomies were performed. The mean duration between intubation and percutaneous tracheostomy was 17.4 days (3-61). The study included 222 males (59%) and 155 females (41%).The mean age of patients was 56.2 years (17-94), with a mean BMI was 31.3 (14-68).The commonest comorbidities among patients were diabetes mellitus (50%) and hypertension (48%).Complications were encountered in 85 cases (23%), with the commonest overall complication being minor bleeding.203 patients (54%) were weaned from sedation. The mean duration between tracheostomy and weaning from sedation was 7.5 days (1 – 47 days). 156 patients (41%) were weaned from MV. The mean duration between tracheostomy and weaning from MV was 12.9 days (1 – 58 days). There was a total of 236 (63%) deaths reported during the period of this study.No deaths were attributable to the surgical procedure.ConclusionPercutaneous tracheostomy can be safely performed in patients with COVID-19. With lack of conclusive objective data regarding the optimal timing for tracheostomy, we recommend that tracheostomy be performed as soon as possible after the 7thday endotracheal intubation.
Chronic pain gene expression changes in the brain and relationships with clinical traits
Authors: Johnston Keira JA , Cote Alanna C. , Hicks Emily , Johnson Jessica , Huckins Laura M. 
Published: December 2022

AbstractBackgroundChronic pain is a common, poorly-understood condition. Genetic studies including genome wide association studies (GWAS) identify many relevant variants, which have yet to be translated into full understanding of chronic pain. Transcriptome wide association study using transcriptomic imputation (TI) methods such as S-PrediXcan can help bridge this genotype-phenotype gap.MethodsWe carried out TI using S-PrediXcan to identify genetically regulated gene expression (GREX) in thirteen brain tissues and whole blood associated with Multisite Chronic Pain (MCP). We then imputed GREX for over 31,000 Mount Sinai BioMe™ participants and performed phenome-wide association study (PheWAS) to investigate clinical relationships in chronic pain associated gene expression changes.ResultsWe identified 95 experiment-wide significant gene-tissue associations (p<7.97×10−7), including 35 unique genes, and an additional 134 gene-tissue associations reaching within-tissue significance, including 53 additional unique genes. Of 89 unique genes total, 59 were novel for MCP and 18 are established drug targets. Chronic pain GREX for 10 unique genes was significantly associated with cardiac dysrhythmia, metabolic syndrome, disc disorders/ dorsopathies, joint/ligament sprain, anemias, and neurological disorder phecodes. PheWAS analyses adjusting for mean painscore showed associations were not driven by mean painscore.ConclusionsWe carried out the largest TWAS of any chronic pain trait to date. Results highlight potential causal genes in chronic pain development, and tissue and direction of effect. Several gene results were also drug targets. PheWAS results showed significant association for phecodes including cardiac dysrhythmia and metabolic syndrome, indicating potential shared mechanisms.
A Statistical Analysis on COVID-19 Pandemic in the City of Toronto
Authors: Kaazempur-Mofrad Ali R. 
Published: December 2022

AbstractAs with many viruses, a main topic of concern that has arisen during the COVID-19 pandemic is the nature of the virus’ spread and the impact it presents for varying age groups. Using statistical methods and numerical summaries, I analysed the impact that age has on the incubation period, death rates, and case outcomes of COVID-19 cases in the city of Toronto. The results of this study illustrate that the elderly have shorter incubation periods, higher death rates, and a higher count of cases which result in fatality. The analysis concludes that the impact of COVID-19 is most felt by the elderly.
The kinetics of humoral and cellular responses after the booster dose of COVID-19 vaccine in inflammatory arthritis patients
Authors: Wroński Jakub , Jaszczyk Bożena , Roszkowski Leszek , Felis-Giemza Anna , Bonek Krzysztof , Kornatka Anna , Plebańczyk Magdalena , Burakowski Tomasz , Lisowska Barbara , Kwiatkowska Brygida , Maśliński Włodzimierz , Wisłowska Małgorzata , Massalska Magdalena , Kuca-Warnawin Ewa , Ciechomska Marzena 
Published: December 2022

AbstractIntroductionImpaired immunogenicity of COVID-19 vaccinations in inflammatory arthritis (IA) patients results in diminished immunity. However, optimal booster vaccination regimens are still unknown, due to not unstudied kinetics of the immune response after booster vaccinations. Therefore, this study aimed to assess the kinetics of humoral and cellular responses in IA patients after the COVID-19 booster.Patients and MethodsIn 29 IA patients and 16 healthy controls (HC) humoral responses (level of IgG antibodies) and cellular responses (IFN-γ production) were assessed before (T0), after 4 weeks (T1), and after more than 6 months (T2) from the booster vaccination with BNT162b2.ResultsIA patients, but not HC, showed lower anti-S-IgG concentration and IGRA fold change at T2 compared to T1 (p=0.026 and p=0.031). Furthermore, in IA patients the level of cellular response at T2 returned to the pre-booster level (T0). All immunomodulatory drugs, except IL-6 and IL-17 inhibitors for the humoral and IL-17 inhibitors for the cellular response, impaired the immunogenicity of the booster dose at T2. However, none of the immunomodulatory drugs affected the kinetics of both humoral and cellular responses (measured as the difference between response rates at T1 and T2).ConclusionOur study showed impaired kinetics of both humoral and cellular responses after the booster dose of the COVID-19 vaccine in IA patients, which, in the case of cellular response, did not allow the vaccination effect to be maintained for more than 6 months. Repetitive vaccination with subsequent booster doses seems to be necessary for IA patients.
Mass Spectrometry-Based Proteomic Profiling of Sonicate Fluid DifferentiatesStaphylococcus aureusPeriprosthetic Joint Infection from Non-Infectious Failure: A pilot study
Authors: Fisher Cody R. , Mangalaparthi Kiran K. , Greenwood-Quaintance Kerryl E. , Abdel Matthew P. , Pandey Akhilesh , Patel Robin 
Published: December 2022

ABSTRACTPurposeThis study aims to use proteomic profiling of sonicate fluid samples to compare host response duringStaphylococcus aureus-associated periprosthetic joint infection (PJI) and non-infected arthroplasty failure (NIAF) and investigate novel biomarkers to increase diagnostic accuracy.Experimental DesignIn this pilot study, eight sonicate fluid samples (four from NIAF and four fromStaphylococcus aureusPJI) were studied. Samples were reduced, alkylated and trypsinized overnight, followed by analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a high-resolution Orbitrap Eclipse mass spectrometer. MaxQuant software suite was used for protein identification, filtering, and label-free quantitation.ResultsPrincipal component analysis of the identified proteins clearly separatedS. aureusPJI and NIAF samples. Overall, 810 proteins were quantified in any three samples from each group and 35 statistically significant differentially abundant proteins (DAPs) were found (2-sample t-test p-values ≤0.05 and log2fold-change values ≥2 or ≤-2). Gene ontology pathway analysis found that microbial defense responses, specifically those related to neutrophil activation, were increased inS. aureusPJI compared to NIAF samples.Conclusion and Clinical RelevanceProteomic profiling of sonicate fluid using LC-MS/MS, alone or in combination with complementary protein analyses, differentiatedS. aureusPJI and NIAF in this pilot study.
Association between recent COVID-19 diagnosis on depression and anxiety symptoms among slum residents in Kampala, Uganda
Authors: Wafula Solomon T. , Ninsiima Lesley L. , Mendoza Hilbert , Ssempebwa John C. , Walter Florian , Musoke David 
Published: December 2022

AbstractBackgroundAn increase in mental health problems has been reported since the beginning of the COVID-19 pandemic. However, little is known about the prevalence of depressive and anxiety disorders, and how recent COVID-19 diagnosis may influence risk of these conditions especially in low-income settings. In this study, we assessed the association between recent COVID-19 diagnosis and depressive and anxiety symptoms among residents in an urban slum setting in Uganda.MethodsA cross-sectional study was conducted among 284 individuals in a slum settlement in Kampala, Uganda between April and May 2022. We assessed generalized anxiety and depression symptoms using two validated questionnaires. We collected data on sociodemographic characteristics, and self-reported recent COVID-19 diagnosis (in the previous 30 days). Using a modified Poisson regression, adjusted for age, sex, gender and household income, we separately provided prevalence ratios and 95% confidence intervals for the associations between recent COVID-19 diagnosis and depressive and anxiety symptoms.ResultsOverall, 33.8% and 13.4% of the participants met the depression and generalized anxiety screening criteria respectively. People with recent COVID-19 diagnosis were more likely to be depressed (53.1%) than those with no recent diagnosis (31.4%). Participants who were recently diagnosed with COVID-19 reported higher prevalence of anxiety (34.4%) compared to those with no recent diagnosis of COVID-19 (10.7%). After adjusting for confounding, recent diagnosis with COVID-19 was associated with depression (PR= 1.60, 95% CI 1.09 – 2.34) and anxiety (PR = 2.83, 95% CI 1.50 – 5.31).ConclusionThis study suggests an increased risk of depressive symptoms and GAD in adults following a COVID-19 diagnosis. We recommend additional mental health support for recently diagnosed persons. The long-term of COVID-19 on mental health effects also need to be investigated.
Modulatory effect of Human immunodeficiency virus on serum miR-21, miR-125b and p53 gene: Any prognostic implication?
Authors: Okoye Jude Ogechukwu , Ngokere Anthony Ajuluchukwu , Onyenekwe Charles Chinedum , Omotuyi Olaposi Idowu , Ogenyi Samuel Ifedioranma , Obi Chioma Maureen , Fasogbon Samuel Ayobami 
Published: December 2022

AbstractIntroductionIdentifying individuals at a high risk of developing cervical cancer remains a major challenge, especially among individuals living with HIV. This study evaluated the levels of normally downregulated oncomirs (miR-21, miR-146a, miR-155, miR-182, and miR-200c) and normally upregulated tumor suppressors (miR-let-7b, miR-125b, miR-143, miR-145, and p53 expression) associated with cervical cancer in the serum of women living with and without HIV.MethodsThis case-control study was carried out between the months of May (2017) and April (2019). It included 173 women without abnormal Pap smears and negative for Human papillomavirus and Epstein-Barr virus; confirmed HIV seropositive women (HIV+; n= 103) and HIV seronegative women (HIV-; n= 70). Relative expressions of miRNAs, and the p53 gene in serum were determined using reverse transcriptase PCR and gel electrophoresis. T-test and Pearson’s correlation analyses were carried out on the generated data. Statistical significance was set atp≤ 0.05 and 0.01.ResultsA significantly higher level of miR-21 and lower levels of miR-125b and p53 gene were observed among HIV+ women compared with their HIV-counterparts at p= 0.028, 0.050, and 0.049, respectively. Among HIV+ women, significant direct correlations were observed between miR-21 and other oncomirs, including miR-145 (p< 0.05) while a significant inverse correlation was observed between miR-21 and miR-let-7b level (p= 0.013).ConclusionThis study suggests that a high circulating level of miR-21 and a low circulating level of miR-125b could be used as biomarkers for identifying individuals at risk of developing cervical cancer, especially among HAART-naïve women who are living with HIV.
Quality of life and its associated factors among epileptic patients on treatment follow up in North Shoa administration, Amhara National State, Ethiopia
Authors: Guday Esubalew , Engdaye Getabalew , Tekleyohannes Belachew , Alemnew Nigus , Eshete Akne , Sewale Yihenew 
Published: December 2022

AbstractBackgroundEpilepsy is a common condition worldwide and has been observed to affect quality of life. Epilepsy patients have a lower quality of life than the general population as well as many other chronic disease patients. However, aside from focusing on symptom reduction, no attention is paid to the quality of life of those with epilepsy. This study aims to evaluate quality of life and associated characteristics among epilepsy patients who visited North Shoa zone hospitals in Ethiopia.MethodsAn institution-based cross-sectional study design was conducted from April -May 2021 at North Shoa zone hospitals. A systematic random sampling technique was used to get a total number of 472 samples. Data on quality of life was assessed through interviews using the World Health Organization Quality of Life—Brief (WHOQOLBREF) Version. The collected data were coded, entered into Epi Data 3.1, and analyzed by using SPSS version 25. Simple and multiple linear regression analysis models were fitted and the unstandardized β coefficient at 95% confidence interval was employed. The statistical significance was accepted atp-value <0.05.ResultsFrom a total of 472 participants the response rate was 98%. The mean score of quality of life was 57.2±12.3. Age (β=5, 95% CI: 2.301, 7.699), marital status (β=-6.914, 95%CI: -8.867, - 4.961),seizure frequency (β=-.2.307, 95%CI: -4.795, .020), Anti-epileptic drug non-adherence (β=-.11.016, 95%CI: -13.642, -8.389), anxiety (β-4.062, 95%CI: (−6.503, -1.621), poor social support (β=-6.220, 95%CI: (−8.422, -4.017) and moderate social support (β=-5.58, 95%CI: -7.792, -3.368) were significantly associated with quality of life.ConclusionThe mean quality of life of people living with epilepsy in this study was low. Age, marital status, seizure frequency, concomitant anxiety, antiepileptic drug non-adherence, number of anti-epileptic drugs/day, moderate and poor social support were all found to be predictors of quality of life in this study. As a suggestion, the patient treatment plan should include a quality of life assessment that addresses psychosocial concerns; professional counseling on how to cope with psychological, environmental, and social difficulties should be increased.
Direct Detection and Identification of Viruses in Saliva Using a SpecID™ Ionization Modified Mass Spectrometer
Authors: Alusta Pierre , Parades Angel , Azevedo Marli , Mullis Lisa , Buzatu Dan 
Published: December 2022

DisclaimerThe authors have withdrawn their manuscript because their institution requires the obtention of additional clearances. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.