bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of water-mediated interaction effects on the stability and transmission of Omicron
Authors: Zaman Naila , Parvaiz Nousheen , Gul Fouzia , Yousaf Rimsha , Gul Kainat , Azam Syed Sikander 
Published: November 2023

AbstractSARS-Cov-2 Omicron variant and its highly transmissible sublineages amidst news of emerging hybrid variants strengthen the evidence of its ability to rapidly spread and evolve giving rise to unprecedented future waves. Owing to the presence of isolated RBD, monomeric and trimeric Cryo-EM structures of spike protein in complex with ACE2 receptor, comparative analysis of Alpha, Beta, Gamma, Delta, and Omicron assist in a rational assessment of their probability to evolve as new or hybrid variants in future. This study proposes the role of hydration forces in mediating Omicron function and dynamics based on a stronger interplay between protein and solvent with each Covid wave. Mutations of multiple hydrophobic residues into hydrophilic residues underwent concerted interactions with water leading to variations in charge distribution in Delta and Omicron during molecular dynamics simulations. Moreover, comparative analysis of interacting moieties characterized a large number of mutations lying at RBD into constrained, homologous and low-affinity groups referred to as mutational drivers inferring that the probability of future mutations relies on their function. Furthermore, the computational findings reveal a significant difference in angular distances among variants of concern due 3 amino acid insertion (EPE) in Omicron variant that not only facilitates tight domain organization but also seems requisite for characterization of mutational processes. The outcome of this work signifies the possible relation between hydration forces, their impact on conformation and binding affinities, and viral fitness that will significantly aid in understanding dynamics of drug targets for Covid-19 countermeasures. The emerging scenario is that hydration forces and hydrophobic interactions are crucial variables to probe in mutational analysis to explore conformational landscape of macromolecules and reveal the molecular origins of protein behaviors.
Semaglutide and Tirzepatide reduce alcohol consumption in individuals with obesity
Authors: Quddos Fatima , Hubshman Zachary , Tegge Allison , Sane Daniel , Marti Erin , Kablinger Anita S. , Gatchalian Kirstin M. , Kelly Amber L. , DiFeliceantonio Alexandra G. , Bickel Warren K. 
Published: November 2023

AbstractAlcohol Use Disorder (AUD) contributes significantly to global mortality. GLP-1 (Glucagon-like peptide-1) and GLP-1/GIP (Glucose-dependent Insulinotropic Polypeptide) agonists, FDA-approved for managing type 2 diabetes and obesity, where the former has shown to effectively reduce the consumption of alcohol in animal models but no reports exist on the latter. In this report, we conducted two studies. In the first study, we conducted an analysis of abundant social media texts. Specifically, a machine-learning based attribution mapping of ~ 68,250 posts related to GLP-1 or GLP-1/GIP agonists on the Reddit platform. Secondly, we recruited participants (n = 153; current alcohol drinkers; BMI ≥ 30) who self-reported either taking Semaglutide (GLP-1 agonist), Tirzepatide (the GLP-1/GIP combination) for ≥ 30 days or, as a control group; no medication to manage diabetes or weight loss for a within and between subject remote study. In the social media study, we report 8 major themes including effects of medications (30%); diabetes (21%); and Weight loss and obesity (19%). Among the alcohol-related posts (n = 1580), 71% were identified as craving reduction, decreased desire to drink, and other negative effects. In the remote study, we observe a significantly lower self-reported intake of alcohol, drinks per drinking episode, binge drinking odds, Alcohol Use Disorders Identification Test (AUDIT) scores, and stimulating, and sedative effects in the Semaglutide or Tirzepatide group when compared to prior to starting medication timepoint (within-subjects) and the control group (between-subjects). In summary, we provide initial real-world evidence of reduced alcohol consumption in people with obesity taking Semaglutide or Tirzepatide medications, suggesting potential efficacy for treatment in AUD comorbid with obesity.
Association of early bedtime at 3 years of age with higher academic performance and better non-cognitive skills in elementary school
Authors: Nishiyama Masahiro , Kyono Yuki , Yamaguchi Hiroshi , Kawamura Aoi , Oikawa Shizuka , Tokumoto Shoichi , Tomioka Kazumi , Nozu Kandai , Nagase Hiroaki 
Published: November 2023

AbstractThis study investigated the relationship between sleep habits in early childhood and academic performance and non-cognitive skills in the first grade. We retrospectively analyzed a longitudinal population-based cohort from birth through early childhood, up to elementary school, in Amagasaki City, Japan. The primary outcome was academic performance in the first grade. Other outcomes were self-reported non-cognitive skills. Overall, 4395 children were enrolled. Mean national language scores for children with bedtimes at 18:00–20:00, 21:00, 22:00, and ≥ 23:00 were 71.2 ± 19.7, 69.3 ± 19.4, 68.3 ± 20.1, and 62.5 ± 21.3, respectively. Multiple regression analysis identified bedtime at 3 years as a significant factor associated with academic performance. However, sleep duration was not significantly associated with academic performance. Bedtime at 3 years also affected non-cognitive skills in the first grade. Diligence decreased with a later bedtime (21:00 vs. 18:00–20:00; odds ratio [OR]: 1.98, 95% confidence interval [CI] 1.27–3.09; 22:00 vs. 18:00–20:00; OR: 2.15, 95% CI 1.37–3.38; ≥ 23:00 vs. 18:00–20:00; OR: 2.33, 95% CI 1.29–4.20). Thus, early bedtime at 3 years may be associated with a higher academic performance and better non-cognitive skills in the first grade. Optimum early-childhood sleep habits may positively impact academic future.
Young basketball players have better manual dexterity performance than sportsmen and non-sportsmen of the same age: a cross-sectional study
Authors: Amato Alessandra , Giustino Valerio , Patti Antonino , Proia Patrizia , Trivic Tatjana , Drid Patrik , Obradovic Anja , Manojlovic Marko , Mondoni Maurizio , Paoli Antonio , Bianco Antonino 
Published: November 2023

AbstractManual dexterity is a key skill in motor development. There are conflicting studies on the influence of sports practice on this skill and on which type of sport trains this ability the most in youth. Manual dexterity is usually assessed with expensive and time-consuming tools not easily available to facilities such as schools or sports clubs. The aim of this study was to assess differences in manual dexterity performance between young basketball players, sportsmen, and non-sportsmen. A further aim was to analyze whether the coin rotation task was a reliable tool for assessing manual dexterity. Based on the characteristics of the sport, we hypothesized that basketball players had better manual dexterity performances. Seventy-eight participants were included in the study and categorized into “basketball”, “sports”, and “non-sports” groups. Manual dexterity was assessed with the grooved pegboard, the coin rotation task, and the handgrip tests. The basketball group showed better performance in all tests. Significant differences were found between the basketball group and sports group and between the basketball group and non-sport group in the grooved pegboard (p < 0.05) and in the handgrip (p < 0.05) tests. Test–retest reliability of the coin rotation task scores was moderate in the basketball group (ICC2,1 0.63–0.6). Basketball practice could positively influence manual dexterity. The coin rotation task showed an acceptable construct of validity.
Platelet-to-lymphocyte ratio and serum hsCRP levels in third trimester and adverse pregnancy outcomes in women with gestational diabetes mellitus
Authors: Tao Jun , Huang Yun , Li Yan , Dai Wen 
Published: November 2023

AbstractGestational diabetes mellitus (GDM) is a major complication of pregnancy. GDM is associated with a higher risk of adverse pregnancy outcomes (APO). The purpose of this study was to assess the association between third-trimester platelet to lymphocyte ratio (PLR) and high-sensitivity C-reactive protein (hsCRP) concentration and the risk of APO in GDM pregnant women. This study selected 406 non-elderly gestational diabetes patients diagnosed in the Renmin Hospital of Wuhan University from May 2021 to February 2023 as the research objects. According to the presence or absence of APO, they were divided into an APO group (n = 171) and a non-APO group (n = 235). Logistic regression model to evaluate the correlation between PLR and hsCRP and APO in women with GDM; Restricted cubic spline analyses was used to explore nonlinear correlations between PLR or hsCRP and the risk of APO; ROC curve analysis of the diagnostic performance of PLR and hsCRP for APO in women with GDM. APO occurred in 171 of the 406 included participants. Compared with the non-APO group, patients in the APO group had higher PLR and hsCRP levels. The incidence of APO was positively associated with PLR and the hsCRP level in each logistic regression model (P < 0.05). After adjusting for all the risk factors included in this study, restricted cubic spline analyses found that the PLR and the hsCRP level were positively associated with the risk of APO. The levels of PLR and hsCRP in the third trimester are related to the occurrence of APO in women with GDM, and high levels of PLR and hsCRP may indicate the occurrence of APO.
Branched chain amino acids harbor distinct and often opposing effects on health and disease
Authors: Avery Christy L. , Howard Annie Green , Lee Harold H. , Downie Carolina G. , Lee Moa P. , Koenigsberg Sarah H. , Ballou Anna F. , Preuss Michael H. , Raffield Laura M. , Yarosh Rina A. , North Kari E. , Gordon-Larsen Penny , Graff Mariaelisa 
Published: November 2023

Abstract
Background
The branched chain amino acids (BCAA) leucine, isoleucine, and valine are essential nutrients that have been associated with diabetes, cancers, and cardiovascular diseases. Observational studies suggest that BCAAs exert homogeneous phenotypic effects, but these findings are inconsistent with results from experimental human and animal studies.

Methods
Hypothesizing that inconsistencies between observational and experimental BCAA studies reflect bias from shared lifestyle and genetic factors in observational studies, we used data from the UK Biobank and applied multivariable Mendelian randomization causal inference methods designed to address these biases.

Results
In n = 97,469 participants of European ancestry (mean age = 56.7 years; 54.1% female), we estimate distinct and often opposing total causal effects for each BCAA. For example, of the 117 phenotypes with evidence of a statistically significant total causal effect for at least one BCAA, almost half (44%, n = 52) are associated with only one BCAA. These 52 associations include total causal effects of valine on diabetic eye disease [odds ratio = 1.51, 95% confidence interval (CI) = 1.31, 1.76], valine on albuminuria (odds ratio = 1.14, 95% CI = 1.08, 1.20), and isoleucine on angina (odds ratio = 1.17, 95% CI = 1.31, 1.76).

Conclusions
Our results suggest that the observational literature provides a flawed picture of BCAA phenotypic effects that is inconsistent with experimental studies and could mislead efforts developing novel therapeutics. More broadly, these findings motivate the development and application of causal inference approaches that enable ‘omics studies conducted in observational settings to account for the biasing effects of shared genetic and lifestyle factors.
AAV-mediated editing of PMP22 rescues Charcot-Marie-Tooth disease type 1A features in patient-derived iPS Schwann cells
Authors: Yoshioka Yuki , Taniguchi Juliana Bosso , Homma Hidenori , Tamura Takuya , Fujita Kyota , Inotsume Maiko , Tagawa Kazuhiko , Misawa Kazuharu , Matsumoto Naomichi , Nakagawa Masanori , Inoue Haruhisa , Tanaka Hikari , Okazawa Hitoshi 
Published: November 2023

Abstract
Background
Charcot-Marie-Tooth disease type 1A (CMT1A) is one of the most common hereditary peripheral neuropathies caused by duplication of 1.5 Mb genome region including PMP22 gene. We aimed to correct the duplication in human CMT1A patient-derived iPS cells (CMT1A-iPSCs) by genome editing and intended to analyze the effect on Schwann cells differentiated from CMT1A-iPSCs.

Methods
We designed multiple gRNAs targeting a unique sequence present at two sites that sandwich only a single copy of duplicated peripheral myelin protein 22 (PMP22) genes, and selected one of them (gRNA3) from screening their efficiencies by T7E1 mismatch detection assay. AAV2-hSaCas9-gRNAedit was generated by subcloning gRNA3 into pX601-AAV-CMV plasmid, and the genome editing AAV vector was infected to CMT1A-iPSCs or CMT1A-iPSC-derived Schwann cell precursors. The effect of the genome editing AAV vector on myelination was evaluated by co-immunostaining of myelin basic protein (MBP), a marker of mature myelin, and microtubule-associated protein 2(MAP2), a marker of neurites or by electron microscopy.

Results
Here we show that infection of CMT1A-iPS cells (iPSCs) with AAV2-hSaCas9-gRNAedit expressing both hSaCas9 and gRNA targeting the tandem repeat sequence decreased PMP22 gene duplication by 20–40%. Infection of CMT1A-iPSC-derived Schwann cell precursors with AAV2-hSaCas9-gRNAedit normalized PMP22 mRNA and PMP22 protein expression levels, and also ameliorated increased apoptosis and impaired myelination in CMT1A-iPSC-derived Schwann cells.

Conclusions
In vivo transfer of AAV2-hSaCas9-gRNAedit to peripheral nerves could be a potential therapeutic modality for CMT1A patient after careful examinations of toxicity including off-target mutations.
Modelling Alzheimer’s disease in a dish: dissecting amyloid-β metabolism in human neurons
Authors: Hill Elizabeth , Cunningham Thomas J. 
Published: November 2023

Abstract
This scientific commentary refers to ‘Inhibition of insulin-degrading enzyme in human neurons promotes amyloid-β deposition’ by Rowland et al. (https://doi.org/10.1042/NS20230016). Insulin-degrading enzyme (IDE) and neprilysin (NEP) have been proposed as two Aβ-degrading enzymes supported by human genetics and in vivo data. Rowland et al. provide complementary evidence of a key role for IDE in Aβ metabolism in human-induced pluripotent stem cell (iPSC)-derived cortical neurons.
Fault detection of fractional‐order system based on finite frequency H−/H∞${{H}_{-}}/{{H}_{\infty }}$ unknown input observer
Authors: Li He , Li Jie , Fan Quan‐Yong 
Published: November 2023

AbstractThis study is about fault detection observer design in finite frequency domain for fractional‐order systems with unknown input disturbances. In order to make the generated residuals fault‐sensitive, robust to the non‐decoupling parts of unknown input disturbances, and guarantee the stability requirements of fractional‐order error systems, the authors derive the fault detection conditions of unknown input observers. First, using the condition of observer, the unknown input is decomposed into decoupling part and non‐decoupling part, and the decoupling part is eliminated from the estimation error. Second, the residuals generator of the unknown input observer is designed by using the finite frequency performance indicator, so that the residuals are robust to the non‐decoupling part of the unknown input and sensitive to fault signals. In particular, variable linearization methods are introduced to convert design conditions into a series of LMIs. Finally, the simulation results show the effectiveness of the designed method.
Online estimation of PID controllers and plant dynamics via multi‐recursive least squares estimation from closed‐loop I/O data
Authors: Zaman Amirreza , Birk Wolfgang 
Published: November 2023

AbstractThis article proposes an online solution to address the problem of closed‐loop system identification using multiple recursive least squares estimation protocols. Some control systems cannot be analysed in an open‐loop form for stability reasons or the requirement for online control system operation. So, it is necessary to identify plant dynamics and controller parameters based on input–output data from the feedback structure. The presented method identifies real‐time parameters of plant dynamics and controller parameters by utilising a series of recursive least square estimation algorithms that estimate open‐loop data from noisy input–output data measured from the closed‐loop feedback structure. The proposed method can effectively identify abrupt variations in both the controller parameters and plant dynamics. This capability makes it valuable for deployment as a supervisory component, enabling the detection of any faults that may arise in operating systems. Mathematical formulations and theorems are developed, and two numerical case studies are presented to examine the feasibility and performance of the presented closed‐loop system identification protocol.
Fueling the seaport of the future: Investments in low‐carbon energy technologies for operational resilience in seaport multi‐energy systems
Authors: Xie Chengzhi , Dehghanian Payman , Estebsari Abouzar 
Published: November 2023

AbstractThe ability to withstand and recover from disruptions is essential for seaport energy systems, and in light of the growing push for decarbonization, incorporating clean energy sources has become increasingly imperative to ensure resilience. This paper proposes a resilience enhancement planning strategy for a seaport multi‐energy system that integrates various energy modalities and sources, including heating, cooling, hydrogen, solar, and wind power. The planning strategy aims to ensure the reliable operation of the system during contingency events, such as power outages, equipment failures, or extreme weather incidents. The proposed optimization model is designed as a mixed‐integer nonlinear programming formulation, in which McCormick inequalities and other linearization techniques are utilized to tackle the model nonlinearities. The model allocates fuel cell electric trucks (FCETs), renewable energy sources, hydrogen refueling stations, and remote control switches such that the system resilience is enhanced while incorporating natural‐gas‐powered combined cooling, heating, and power system to minimize the operation and unserved demand costs. The model considers various factors such as the availability of renewable energy sources, the demand for heating, cooling, electricity, and hydrogen, the operation of remote control switches to help system reconfiguration, the travel behaviour of FCETs, and the power output of FCETs via vehicle‐to‐grid interface. The numerical results demonstrate that the proposed strategy can significantly improve the resilience of the seaport multi‐energy system and reduce the risk of service disruptions during contingency scenarios.
Contrastive learning for traffic flow forecasting based on multi graph convolution network
Authors: Guo Kan , Tian Daxin , Hu Yongli , Sun Yanfeng , Qian Zhen (Sean) , Zhou Jianshan , Gao Junbin , Yin Baocai 
Published: November 2023

AbstractContrastive learning is an increasingly important research direction and has attracted considerable attention in the field of computer vision. It can greatly improve the representativeness of image features through data augmentation, unsupervised learning, and pre‐trained models. However, in the field of traffic flow forecasting, most graph‐based models focus on the construct of spatial–temporal relationships between road segments and ignore the use of temporal data augmentation and pre‐trained models, which can improve the representation ability of the forecasting model. Therefore, in this work, contrastive learning are used to expand the distribution of sequence samples and improve the quality and generalization of forecasting models. Based on this, a novel forecasting model called contrastive learning based on multi graph convolution network (CLMGCN) is proposed, which is combined with four components: multi graph convolution network, which learns the spatial–temporal feature of the input traffic data; temporal data augmentation, which obtains the augmentation data of the input traffic data; contrastive learning, which achieves the pre‐training phase and improve the quality of output feature of multi graph convolution network; output block, which utilizes the enhanced output feature of multi graph convolution network for predicting the future traffic data. Finally, by the experimental results of four public traffic flow datasets, it can be shown that CLMGCN achieves higher traffic forecasting accuracy with lower model complexity.
Voltage profile analysis at planning and operational stages with allowable PV hosting capacity
Authors: Yadav Anju , Kishor Nand , Negi Richa 
Published: November 2023

AbstractHigh level of photovoltaic (PV) integration into the distribution network (DN) may have a negative impact in terms of voltage variations across the limits. As such thorough analysis is required to ensure voltage within limits, mainly at feeder‐end buses. In this study, the PV integration problem is addressed in a more comprehensive way, considering the unbalance DN, impedance characteristic, and interaction of load against available PV output. The approach applies to both the planning and operational stage in the assessment of allowable PV hosting capacity (HC). In the planning stage, the local impedance index is computed at constant load and power factor conditions. The entire network is partitioned into areas and the most suitable area for PV integration is determined, which can allow maximum PV integration, without/minimum voltage violations. In the operation stage for allowable PV hosting capacity, further voltage analysis is performed, wherein peakness of PV output and load conditions do not match each other. Towards, voltage regulation via PV inverter, the power factor profile is adjusted as a function of PV output. The study is demonstrated for transient solar radiation, with emphasis on maintaining the voltage at feeder‐end buses. The simulation is carried out on interfacing GridPV in MATLAB and OpenDSS toolbox. The proposed scheme for allowable HC and further voltage regulation in the network using PV inverter is also compared with those approaches, applying optimised and centralised placement of PVs.
Editorial
Authors: Becker Claus 
Published: November 2023

Liebe Kolleginnen und Kollegen,Fort- und Weiterbildung sind zentrale Themen im Leben und im Beruf. Auch - oder
gerade wegen - unserer neuen Berufsbezeichnung „Medizinische Technologinnen
und Technologen für Radiologie“ ist die Verantwortung und die
Erwartungen an uns gestiegen.