bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global Parkinson’s Genetics Program (GP2) Monogenic Network Protocol: Elucidating causative gene variants in hereditary Parkinson’s disease
Authors: Lange Lara M. , Avenali Micol , Ellis Melina , Illarionova Anastasia , Keller Sarmiento Ignacio J. , Tan Ai-Huey , Madoev Harutyun , Galandra Caterina , Junker Johanna , Roopnarain Karisha , Solle Justin , Wegel Claire , Fang Zih-Hua , Heutink Peter , Kumar Kishore R. , Lim Shen-Yang , Valente Enza Maria , Nalls Mike , Blauwendraat Cornelis , Singleton Andrew , Mencacci Niccolo , Lohmann Katja , Klein Christine ,   the Global Parkinson’s Genetic Program (GP2)
Published: December 2022

AbstractThe Monogenic Network of the Global Parkinson’s Genetics Program (GP2) aims to create an efficient infrastructure to accelerate the identification of novel genetic causes of Parkinson’s disease (PD) and to improve our understanding of already identified genetic causes, such as reduced penetrance and variable clinical expressivity of known disease-causing variants. We aim to perform short- and long-read whole-genome sequencing for up to 10,000 patients with parkinsonism.
Are we really targeting and stimulating DLPFC by placing transcranial electrical stimulation (tES) electrodes over F3/F4?
Authors: Soleimani Ghazaleh , Kuplicki Rayus , Camchong Jazmin , Opitz Alexander , Paulus Martin P , Lim Kelvin O , Ekhtiari Hamed 
Published: December 2022

AbstractBackgroundIn many clinical trials involving transcranial electrical stimulation (tES), target electrodes are typically placed over DLPFC with the assumption that this will primarily stimulate the underlying brain region. However, our study aimed to evaluate the electric fields (EF) that are actually delivered and identify prefrontal regions that may be inadvertently targeted in DLPFC tES.MethodsHead models were generated from Human Connectome Project database’s T1+T2-weighted MRIs of 80 healthy adults. Two common DLPFC montages were simulated; symmetric-F4/F3, and asymmetric-F4/Fp1. Averaged EF was extracted from (1) the center of target electrode (F4), and (2) the top 1% of voxels showing the strongest EF in individualized EF maps. Inter-individual variabilities were quantified with standard deviation of EF peak location/value. Similar steps were repeated with 66 participants with methamphetamine use disorder (MUDs) as an independent clinical population.ResultsIn healthy adults, the group-level location of EF peaks was situated in the medial-frontopolar, and the individualized EF peaks were positioned in a cube with a volume of 29cm3/46cm3 (symmetric/asymmetric montages). EFs in frontopolar area were significantly higher than EF “under” the target electrode in both symmetric (peak:0.41±0.06, F4:0.22±0.04) and asymmetric (peak:0.38±0.04, F4:0.2±0.04) montages (Heges’g>0.7). Similar results with slight between-group differences were found in MUDs.ConclusionsWe highlighted that in common DLPFC tES montages, in addition to inter-individual/inter-group variability, the frontopolar received the highest EFs rather than DLPFC as the main target. We specifically recommended considering the potential involvement of the frontopolar area as a mechanism underlying the effectiveness of DLPFC tES protocols.HighlightsThere are many published tES studies assuming targeting DLPFC with DLPFC tES montagesIn DLPFC tES montages, electric field peaks are not located under the electrodesThe electric field peak in DLPFC montages is located in the medial frontopolar areaAn independent population showed between-group similarities and variations in electric fieldThere is a large interindividual variation in both location and strength of the electric field peak
A rapid evidence map of what evidence is available on the effectiveness of community diagnostic centres
Authors: Wale Alesha , Okolie Chukwudi , Everitt Jordan , Hookway Amy , Shaw Hannah , Little Kirsty , Lewis Ruth , Cooper Alison , Edwards Adrian 
Published: December 2022

AbstractThe COVID-19 pandemic has resulted in increased demand and delays to diagnostic services. Community diagnostic centres (which are generally referred to as Regional Diagnostic Hubs in Wales) aim to reduce this backlog and the waiting times for patients by providing a broad range of elective diagnostic services in the community, away from acute hospital facilities. As diagnostic services account for over 85% of clinical pathways and cost the National Health Service (NHS) over six billion pounds a year (NHS 2022), community diagnostic centres across a broader range of diagnostic services may be an effective, efficient, and cost-effective introduction to the UK health sector. This Rapid Evidence Map aimed to identify, describe, and map the available evidence on the effectiveness of diagnostic centres. 50 primary studies were identified. Studies were published between 1995 and 2021: A wide range of study designs were used, and studies were conducted in a range of countries including the UK. 30 studies were specific to cancer diagnosis, whilst the remaining 20 studies focused on diagnosis associated with: anaemia, autism, cerebral palsy, intellectual disability, multiple sclerosis, respiratory conditions, shoulder pain, and unexplained fever Eleven studies reported information on multi-condition diagnostic centres, rather than a specific condition.The majority of studies were conducted within hospital settings. Two studies evaluated diagnostic centres within a community setting. The diagnostic centres offered a wide range of diagnostic tests and incorporated different staff and facilities. Participants were mainly referred by GPs, primary care centres and emergency departments. However, referrals were also made from outpatient clinics located within the same hospital as the diagnostic centre.Over 100 different outcomes were reported covering: patient data and referral outcomes, clinical outcomes, performance outcomes, economic outcomes, and patient and physician-reported outcomes.The findings of this rapid evidence map were used to select a substantive focus for a subsequent rapid review on community diagnostic centres that can be accessed by primary care teams.
Changes in Children’s Fitness and Health Status Over the Course of the COVID-19 Pandemic: A 34-month Longitudinal Study of 331 Primary School Children (September 2019 to June 2022)
Authors: Jarnig Gerald , Kerbl Reinhold , van Poppel Mireille N.M. 
Published: December 2022

ABSTRACTBackgroundPrevious studies have shown that coronavirus disease 2019 (COVID-19) mitigation measures lead to reductions in health status and health-related fitness in children, whereas no data are currently available on the development of children after the removal of these mitigation measures. Therefore, we aimed to investigate the influence of different stringent measures, during and after COVID-19, on the longitudinal development of fitness and health status of primary school children.METHODSA longitudinal cohort study of 331 primary school children in Austria aged 7.7 ± 0.4 years at the start of the observation period was conducted. Before (Sept 2019), and during (June 2020, Sept 2020) and after (March 2021, June 2021, Sept 2021, and June 2022) the COVID-19 mitigation measures, fitness tests were carried out and anthropometric data of the children were collected. Age- and sex-specific standard deviation scores (SDSs) were calculated for seven individual fitness tests of the AUT FIT [1] test battery, body mass index, and waist-to-height ratio. In addition, children were classified into different fitness categories based on the AUT FIT summary score.ResultsAfter the implementation of COVID-19 mitigation measures, cardiorespiratory fitness and action speed decreased dramatically, and the number of children with overweight or obesity increased. At the last measurement after the COVID-19 mitigation measures (June 2022), significant improvements in cardiorespiratory fitness and weight status were observed. However, pre-COVID fitness levels were not achieved and BMI was still higher compared to Sept 2019.InterpretationOur study showed a trend reversal, in that the negative indirect effects of the COVID-19 measures on fitness and health parameters of children were followed by significant improvements in these parameters after the removal of those mitigation measures. At the end of the observation period, a positive trend in the development of fitness and health status was observed, although pre-COVID levels were not reached. Collaborative efforts are needed to reinforce the observed positive trend, and to continue to improve the level of fitness and health status of primary school children, and to mitigate the long-term negative health consequences of the COVID-19 pandemic.FundingAustrian Federal Ministry of Arts, Culture, Public Service and Sports (GZ2021-0.361.671).
Mpox (monkeypox) knowledge, concern, willingness to change behaviour, and seek vaccination: Results of a national cross-sectional survey
Authors: MacGibbon James , Cornelisse Vincent , Smith Anthony K J , Broady Timothy R , Hammoud Mohamed A , Bavinton Benjamin R , Paynter Heath , Vaughan Matthew , Wright Edwina J , Holt Martin 
Published: December 2022

ABSTRACTBackgroundWe assessed knowledge and concern about mpox, acceptability of behavioural changes to reduce transmission risk, and willingness to be vaccinated among gay, bisexual and queer-identifying men and non-binary people.MethodsWe conducted a national, online cross-sectional survey with a convenience sample between August and September 2022. Participants were recruited through community organisation promotions, online advertising, and direct email invitations. Eligible participants were gay, bisexual or queer; identified as male (cisgender or transgender) or non-binary; aged 16 years or older; and lived in Australia. The main outcome measures were: knowledge and concern about mpox; recognition of mpox symptoms and transmission routes; vaccination history; acceptability of behavioural changes to reduce mpox risk, and willingness to be vaccinated.ResultsOf 2287 participants, most participants were male (2189/2287; 95.71%) and gay (1894/2287; 82.82%). Nearly all had heard about mpox (2255/2287; 98.60%), and the majority were concerned about acquiring it (1461/2287; 64.42%). Most of the 2268 participants not previously diagnosed with mpox identified skin lesions (2087; 92.02%), rash (1977; 87.17%), and fever (1647; 72.62%) as potential symptoms, and prolonged and brief skin-to-skin contact as potential ways to acquire mpox (2124, 93.65%; and 1860, 82.01% respectively). The most acceptable behavioural changes were reducing or avoiding attendance at sex parties (1494; 65.87%) and sex-on-premises venues (1503; 66.40%), and having fewer sexual partners (1466; 64.64%). Most unvaccinated and undiagnosed participants were willing to be vaccinated (1457/1733; 84.07%).ConclusionsPeople at risk of mpox should be supported to adopt acceptable risk reduction strategies during outbreaks and seek vaccination.
A machine learning model to explore individual risk factors for tuberculosis treatment non-adherence in Mukono district
Authors: Gichuhi Haron W. , Magumba Mark , Kumar Manish , Mayega Roy William 
Published: December 2022

AbstractDespite the availability and implementation of well-known efficacious interventions for Tuberculosis (TB) prevention and treatment by the Ministry of Health, Uganda (MoH), treatment non-adherence persists. Moreover, identifying a specific patient at risk of non-adherence is still a challenge. Thus, this study set out to utilize machine learning modeling to explore individual risk factors predictive of tuberculosis treatment non-adherence in the Mukono district.This was a retrospective study based on a record review of 838 TB patients enrolled in six health facilities (3 government, 3 private-not-for-profit) in the Mukono district. We developed five machine learning algorithms (Logistic regression (LR), artificial neural networks (ANN), support vector machines (SVM), Random Forest (RF), and AdaBoost) to explore the individual risk factors for tuberculosis treatment non-adherence. Also, we evaluated their accuracy by computing the positive predictive value (PPV) and negative predictive value (NPV) through the aid of a confusion matrix.Of the five developed and evaluated models, SVM performed the best with an accuracy of 91.28 % compared to RF (89.97%), LR (88.30%), ANN (88.30%), and AdaBoost (91.05%) respectively. Individual risk factors predictive of non-adherence included; TB type, GeneXpert results, sub-country, ART status, contacts below 5 years, health facility ownership, sputum test results at 2 months, treatment supporter, CPT Dapson status, risk group, patient age, gender, middle and upper arm circumference, referral, positive sputum test at 5 months and 6 months.This study shows that classification machine learning techniques can identify patient factors predictive of treatment non-adherence and accurately differentiate between adherent and non-adherent patients. Thus, TB program management should consider adopting the machine learning techniques evaluated in this study as a screening tool for both identity and target-suited interventions for these patients.
Role ofSTING/TMEM173mutation in systemic lupus erythematosus: from animal model to intrinsic human genetics
Authors: Vejvisithsakul Pichpisith Pierre , Wanachate Satima , Ngamjanyaporn Pintip , Thumarat Chisanu , Suangtamai Thanitta , Leelahavanichkul Asada , Hirankan Nattiya , Pisitkun Trairak , Paludan Soren Riis , Pisitkun Prapaporn 
Published: December 2022

AbstractObjectiveWe aim to confirm the function ofSting/Tmem173in pristane-induced lupus and identify the role ofSTING/TMEM173variants in SLE susceptibility.MethodsPristane-induced lupus model was introduced in theSting-deficient mice (ENU-induced Goldenticket mutant mice). Autoantibody, histopathology, and immunophenotypes were analyzed after pristane injection for six months. Isolated DNA from 302 SLE patients and 173 healthy donors were tested for STING genotyping. We calculated the Odd Ratios of each STING variant and the inheritance patterns that significantly increased SLE susceptibility. Then, we analyzed the associations between STING genotypes and lupus phenotypes.ResultsThe absence of STING signaling in the Goldenticket mutant mice reduced the autoantibody production and severity of glomerulonephritis in pristane-induced lupus. The humanSTINGmutation at p.R284S (gain-of-function) significantly increased the SLE risk in autosomal dominant pattern [OR = 64.0860 (95%CI = 22.8605-179.6555), p < 0.0001], while the mutation at p.R232H (loss of function) reduced the SLE risk in autosomal recessive pattern [OR = 0.2515 (95%CI = 0.1648-0.3836), p < 0.0001]. The combination of STING variants in a specific inheritance pattern increased the higher OR than a single variant. The patient who had p.R284S with p.R232H showed milder disease activity than those who had p.R284S alone at the time of diagnosis.ConclusionThe inhibition of STING rescued autoimmune phenotypes in pristane-induced lupus. Gain-of-function STING mutation increased SLE susceptibility and severity of the disease. These data suggested the critical function via STING-mediated signaling in SLE. Targeted at STING may provide a favorable outcome in SLE patients.
Impact of COVID-19 Vaccinations in India - A Statewise Analysis
Authors: Adhikary Abhigayan , Pal Manoranjan , Maiti Raju , Ghosh Palash 
Published: December 2022

AbstractObjectiveThe COVID-19 vaccination program in India started after the first wave of infections had almost subsided. In this work, the objective is to perform a statewise analysis to assess the impact of vaccination during the second COVID-19 wave in India. A total of 21 states are chosen for the analysis encompassing 97% of the Indian population.MethodsWe use the generalized Gompertz curve to study the COVID-19 outbreak. The generalized Gompertz model is then modified to study the impact of vaccination. The modified model considers the cumulative daily number of individuals having the first and second shots of the vaccine in each state as explanatory variables.ResultsWe observe that, out of 21 states, 16 states show the effectiveness of vaccines in curbing the spread of COVID-19. However, in states like Telangana, West Bengal, Tamil Nadu, Rajasthan, and Kerala, we do not conclusively observe the impact of vaccination during the study period.ConclusionsThe effectiveness of COVID-19 vaccine depends on many factors. Some of them are not directly measurable. Using only COVID-19 infection cases and the vaccination data, we conclude that overall the vaccination program was effective in curbing the spread of COVID-19 in India.
Computational simulation of virtual patients reduces dataset bias and improves machine learning-based detection of ARDS from noisy heterogeneous ICU datasets
Authors: Sharafutdinov Konstantin , Fritsch Sebastian Johannes , Iravani Mina , Ghalati Pejman Farhadi , Saffaran Sina , Bates Declan G. , Hardman Jonathan G. , Polzin Richard , Mayer Hannah , Marx Gernot , Bickenbach Johannes , Schuppert Andreas 
Published: December 2022

ABSTRACTGoalMachine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their unproven performance in real-world settings, remain significant constraints to their widespread adoption in clinical practice. One approach to tackle this issue is to base learning on large multi-center datasets. However, such heterogeneous datasets can introduce further biases driven by data origin, as data structures and patient cohorts may differ between hospitals.MethodsIn this paper, we demonstrate how mechanistic virtual patient (VP) modeling can be used to capture specific features of patients’ states and dynamics, while reducing biases introduced by heterogeneous datasets. We show how VP modeling can be used to extract relevant medical information on individual patients with suspected acute respiratory distress syndrome (ARDS) from observational data of mixed origin. We compare the results of an unsupervised learning method (clustering) in two cases: where the learning is based on original patient data and on data ‘filtered’ through a VP model.ResultsMore robust cluster configurations were observed in clustering using the VP model-based filtered data. VP model-based clustering also reduced biases introduced by the inclusion of data from different hospitals and was able to discover an additional cluster with significant ARDS enrichment.ConclusionsOur results indicate that mechanistic VP modeling can be used as a filter to significantly reduce biases introduced by learning from heterogeneous datasets and to allow improved discovery of patient cohorts driven exclusively by medical conditions.IMPACT STATEMENTMechanistic virtual patient modeling can be used as a filter to extract relevant medical information on individual patients, significantly reducing biases introduced by learning from heterogeneous datasets and allowing improved discovery of patient cohorts driven exclusively by medical conditions.
ythdf2(ch200)and its role in development of the early zebrafish embryo
Authors: Beadell Alana V. 
Published: December 2022

SummaryWe appreciate the well-presented data and focus on mechanism in the paper titled, “Ythdf m6A Readers Function Redundantly during Zebrafish Development” by Konturet al. December 29, 20201[DOI:https://doi.org/10.1016/j.celrep.2020.108598]. However, we would like to suggest several alternative conclusions regarding the role of Ythdf2 in maternal RNA clearance and the phenotypic consequences of theythdf2(ch200)mutation as described in Zhaoet al. 2017, “m6A-dependent maternal mRNA clearance facilitates zebrafish maternal-to-zygotic transition”2[DOI:https://doi.org/10.1038/nature21355], along with caveats regarding the interpretation of Ythdf2’s roles in mRNA metabolism in the early embryo.
New insights into the structure of Comirnaty Covid-19 vaccine: A theory on soft nanoparticles with mRNA-lipid supercoils stabilized by hydrogen bonds
Authors: Szebeni János , Kiss Bálint , Bozó Tamás , Turjeman Keren , Levi-Kalisman Yael , Barenholz Yechezkel , Kellermayer Miklós 
Published: December 2022

AbstractDespite the worldwide success of mRNA-LNP Covid-19 vaccines, the nanoscale structure of these formulations is still poorly understood. To fill this gap, we used a combination of atomic force microscopy (AFM), dynamic light scattering (DLS), transmission electron microscopy (TEM), cryogenic transmission electron microscopy (cryo-TEM) and the determination of LNP pH gradient to analyze the nanoparticles (NPs) in BNT162b2 (Comirnaty), comparing it with the well characterized pegylated liposomal doxorubicin (Doxil). Comirnaty NPs had similar size to Doxil, however, unlike Doxil liposomes, wherein the stable ammonium and pH gradient enables accumulation of14C-methylamine in the intraliposomal aqueous phase, Comirnaty LNPs lack such pH gradient in spite of the fact that the pH 4, at which LNPs are prepared, is raised to pH 7.2 after loading of the mRNA. Mechanical manipulation of Comirnaty NPs with AFM revealed soft, compliant structures. The sawtooth-like force transitions seen during cantilever retraction implies that molecular strands, corresponding to mRNA, can be pulled out of NPs, and the process is accompanied by stepwise rupture of mRNA-lipid bonds. Unlike Doxil, cryo-TEM of Comirnaty NPs revealed a granular, solid core enclosed by mono- and bilayers. Negative staining TEM shows 2-5 nm electron-dense spots in the liposom’s interior that are aligned into strings, semicircles, or labyrinth-like networks, which may imply crosslink-stabilized supercoils. The neutral intra-LNP core questions the dominance of ionic interactions holding together this scaffold, raising the alternative possibility of hydrogen bonding between the mRNA and the lipids. Such interaction, described previously for another mRNA/lipid complex, is consistent with the steric structure of ionizable lipid in Comirnaty, ALC-0315, displaying free =O and -OH groups. It is hypothesized that the latter groups can get into steric positions that enable hydrogen bonding with the nitrogenous bases in the mRNA. These newly recognized structural features of mRNA-LNP may be important for the vaccine’s efficacy.