bluuebunny/crossref_metadata_2025_split huggingface dataset:
A cross-sectional study of the prevalence of lameness and digital dermatitis in dairy cattle herds in Egypt
Authors: Salem Shebl E. , Mesalam Ayman , Monir Ahmed 
Published: November 2022

Abstract
Background
lameness is a significant problem of the dairy industry worldwide. No previous studies have evaluated the prevalence of lameness or digital dermatitis (DD) in dairy cattle herds in Egypt. A total of 16,098 dairy cows from 55 dairy herds in 11 Egyptian Governorates underwent visual locomotion scoring using a 4-point scoring system. Cows that had a lameness score ≥ 2 were considered clinically lame. Following manure removal with water and using a flashlight, the cows’ hid feet were examined in the milking parlour to identify and M-score DD lesions. Furthermore, each cow was assigned a hock score (a 3-point scale) and a hygiene score (a 4-point scale). The cow-level, within-and between-herd prevalence of lameness and digital dermatitis and associated 95% confidence intervals (CI) were calculated. The prevalence of hock lesions and poor cow hygiene was also calculated.
Results
Of the examined cows, 6,883 cows were found to be clinical lame (42.8%, 95% CI = 42–43.5%). The average within-herd prevalence of lameness was 43.1% (95% CI = 35.9–50.3%). None of the dairy herds recruited into the study was found to be free from clinical lameness. The average within-herd prevalence of DD was 6.4% (95% CI = 4.9–8%). The herd-level prevalence of DD was 92.7% (95% CI = 85.9–99.6%). Active DD lesions (M1, M2, M4.1) were identified in 464 cows (2.9%) while inactive lesions (M3, M4) were identified in 559 cows (3.5%). The within-herd prevalence of hock lesions (score 2 or 3) was 12.6% (95% CI = 4.03–21.1%) while a severe hock lesion had within-herd prevalence of 0.31% (95% CI = 0.12–0.51%). Cow-level prevalence of hock lesions was 6.2% (n = 847, 95% CI = 5.8–6.2%). Majority of examined cows had a hygiene score 4 (n = 10,814, prevalence = 70.3%, 95% CI = 69.5–71%).
Conclusions
The prevalence of lameness was higher than reported prevalence estimates in other countries which could be due to differing management and/or environmental factors. DD was identified at lower prevalence in most herds. Poor cow hygiene was notable in most herds. There should be measures to reduce the prevalence of lameness and to improve cow hygiene in dairy cattle herds in Egypt.
A long-duration gamma-ray burst of dynamical origin from the nucleus of an ancient galaxy
Authors: Levan Andrew , Malesani Daniele , Gompertz Benjamin , Nugent Anya , Nicholl Matt , Oates Samantha , Perley Daniel , Rastinejad Jillian , Metzger Brian , Schulze Steve , Stanway Elizabeth , Inkenhaag Anne , Fernández José Feliciano Agüí , Chrimes Ashley , Bhirombhakdi Kornpob , Postigo Antonio de Ugarte , Fong Wen-fai , Fruchter Andrew , Fragione Giacomo , Fynbo Johan , Gaspari Nicola , Heintz Kasper , Hjorth Jens , Jakobsson Pall , Jonker Peter , Lamb Gavin , Mandel Ilya , Ravasio Maria , Sollerman Jesper , Tanvir Nial 
Published: November 2022

Abstract
The majority of long-duration (>2s) gamma-ray bursts (GRBs) are believed to arise from the collapse of massive stars (Hjorth et al. 2003) with a small proportion created from the merger of compact objects (Rastinejad et al. 2022, Yang et al. 2022, Troja et al. 2022). Most of these systems are likely formed via standard stellar evolution pathways. However, it has long been thought that a fraction of GRBs may instead be an outcome of dynamical interactions in dense environments (Grindlay et al. 2006, Fragione et al. 2019, McKernan et al. 2020), channels which could also contribute significantly to the samples of compact object mergers detected as gravitational wave sources (O’Leary et al. 2016). Here we report the case of GRB 191019A, a long GRB (T_90 = 64.4 +/- 4.5 s) which we pinpoint close (< 100 pc projected) to the nucleus of an ancient (>1 Gyr old) host galaxy at z=0.248. The lack of evidence for star formation and deep limits on any supernova emission makes a massive star origin difficult to reconcile with observations, while the timescales of the emission rule out direct interaction with the supermassive black hole in the nucleus of the galaxy, We suggest that the most likely route for progenitor formation is via dynamical interactions in the dense nucleus of the host, consistent with the centres of such galaxies exhibiting interaction rates up to two orders of magnitude larger than typical field galaxies (French et al. 2014, Stone et al. 2016). The burst properties could naturally be explained via compact object mergers involving white dwarfs (WD), neutron stars (NS), or black holes (BH). These may form dynamically in dense stellar clusters, or originate in a gaseous disc around the supermassive black hole (Perna et al. 2021, Lazzati et al. 2022). Future electromagnetic and gravitational-wave observations in tandem thus offer a route to probe the dynamical fraction and the details of dynamical interactions in galactic nuclei and other high-density stellar systems.
Inferring the effects of protein variants on protein–protein interactions with an interpretable deep-learning model
Authors: Liu Zhe , Qian Wei , Cai Wenxiang , Song Weichen , Wang Weidi , Maharjan Dhruba , Cheng Wenhong , Chen Jue , Xu Fei , Wang Han , Xu Dong , Lin Guan 
Published: November 2022

AbstractIdentifying pathogenetic variants and inferring their impact on protein–protein interactions sheds light on their functional consequences on diseases. Limited by the availability of experimental data on the consequences on protein interaction, most existing methods focus on building models to predict changes in protein binding affinity. Here, we introduced MIPPI, an end-to-end, interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from IMEx. We trained MIPPI to determine the types of variant impact (increasing, decreasing, disrupting, and no effect) on protein-protein interactions, and demonstrated its accuracy and interpreted the learned attention weights, which correlate with the amino acids interacting with the variant. We further showed the utility of MIPPI in prioritizingde novomutations associated with complex neurodevelopmental disorders and the potential in determining the pathogenic and driving mutations. Finally, we experimentally validated the functional impact of several variants identified in patients with such disorders. Overall, MIPPI is a versatile, robust, and interpretable model suitable for prediction tasks for mutation impact on protein–protein interaction and the discovery of clinically actionable variants. A webserver for MIPPI is available from https://www.psymukb.net/MIPPI.
Significance of modern antihistamines in the treatment of patients with allergic rhinitis
Authors: Starostina S. V. , Toldanov A. V. 
Published: November 2022

Allergic rhinitis (AR) is one of the most common diseases in the world, which is based on immunoglobulin E (IgE) – mediated inflammation that develops after contact with various allergens. About 40 % of people suffer from various allergic diseases, every 3 rd inhabitant of the Earth has symptoms of allergic rhinitis and every 10 th has bronchial asthma. The early phase of allergen binding to IgE antibodies occurs within a few minutes after contact, the late phase develops after 4–6 hours. In addition to the airborne pathway of penetration, contact with the allergen is possible through the skin and mucous membranes, gastrointestinal tract, with parenteral administration of drugs. Taking into account the etiotropic factor, there are year-round allergic rhinitis (CAR) and seasonal (SAR). By the nature of the course, intermittent and persistent allergic rhinitis are distinguished. The most basic symptoms of allergic rhinitis include: sneezing, rhinorrhea, nasal congestion, itching, decreased sense of smell. Treatment includes antihistamines, intranasal steroids, leukotriene receptor antagonists and immunotherapy. To date, antihistamines of the second generation are recommended and widely used for the treatment of patients with allergic rhinitis, the main representative of which is levocetirizine (levocetirizine dihydrochloride). The purpose of the work is an analytical review of the results of clinical trials of levocetirizine for allergic rhinitis. The article discusses in detail the prevalence, etiology and pathogenesis, classification of the disease, treatment regimens for patients with allergic rhinitis, and provides two own clinical observations. Based on the data of a number of studies, the advantages of using antihistamines of the second generation in allergic rhinitis have been demonstrated, expanding not only the possibilities of treating patients, but also preventing the transition of the disease into a chronic process.
Hydrological simulation and prediction of soil erosion using the SWAT model in a mountainous watershed: a case study of Murat River Basin, Turkey
Authors: Karakoyun Erkan , Kaya Nihat 
Published: November 2022

Abstract
The Euphrates-Tigris basin in Turkey suffers from sedimentation and erosion problems. The purpose of this study was to estimate streamflow, sediment yield, and identification of soil erosion-prone areas for the Murat River Basin which is the headwater of Euphrates River, with Soil and Water Assessment Tool (SWAT). The model was calibrated and validated with observed streamflow and sediment yield data obtained from two gauging stations. The statistical model performance was evaluated by using NSE, R2, and PBIAS. NSE values were calculated as 0.57, 0.50 and 0.77, 0.75 for the stations E21A074 and E21A077, respectively, in the monthly streamflow calibration and validation periods. Monthly sediment yield generated the NSE values for stations E21A074 and E21A077 were 0.54, 0.69 and 0.62, 0.35 in the calibration and validation periods, respectively. Spatial analysis indicates that 3.9% of the basin is under very severe (&gt;20 t/ha/y), and 21.3% is under severe (&gt;10 t/ha/y) soil erosion conditions. Most of the soil erosion occurs at the barren land use and in the sub-watersheds with a slope greater than 25%. Overall, the SWAT model satisfactorily simulated the streamflow and sediment yield, and identified the erosion-prone areas at the sub-watershed scale at the Murat River Basin for water resource management.
A neural network approach for short-term water demand forecasting based on a sparse autoencoder
Authors: Huang Haidong , Lin Zhenliang , Liu Shitong , Zhang Zhixiong 
Published: November 2022

Abstract
This paper presents a backpropagation neural network (BPNN) approach based on the sparse autoencoder (SAE) for short-term water demand forecasting. In this method, the SAE is used as a feature learning method to extract useful information from hourly water demand data in an unsupervised manner. After that, the extracted information is employed to optimize the initial weights and thresholds of the BPNN. In addition, to enhance the effectiveness of the proposed method, data reconstruction is implemented to create suitable samples for the BPNN, and the early stopping method is employed to overcome the BPNN overfitting problem. Data collected from a real-world water distribution system are used to verify the effectiveness of the proposed method, and a comparison with the BPNN and other BPNN-based methods which integrate the BPNN with particle swarm optimization (PSO) and the mind evolutionary algorithm (MEA), respectively, is conducted. The results show that the proposed method can achieve fairly accurate and stable forecasts with a 2.31% mean absolute percentage error (MAPE) and 320 m3/h root mean squared error (RMSE). Compared with the BPNN, PSO–BPNN and MEA–BPNN models, the proposed method gains MAPE improvements of 5.80, 3.33 and 3.89%, respectively. In terms of the RMSE, promising improvements (i.e., 5.27, 2.73 and 3.33%, respectively) can be obtained.
Flood forecasting and uncertainty analysis based on the combination of improved adaptive noise learning model and density estimation
Authors: Liu Yang , Du Shuaibing , Wang Lihu 
Published: November 2022

AbstractThe strong randomness exhibited by runoff series means the accuracy of flood forecasting still needs to be improved. Mode mixing can be dealt with using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the endpoint effect of CEEMDAN can be successfully dealt with using the mutual information criterion. To increase the computational effectiveness of broad learning (BL), orthogonal triangular matrix decomposition (QR) was used. A novel improved coupled CEEMDAN-QRBL flood forecasting model was created and applied to the prediction of daily runoff in Xiaolangdi Reservoir based on the benefit of quick calculation by the model output layer. The findings indicate that the enhanced QRBL is 28.92% more computationally efficient than the BL model, and that the reconstruction error of CEEMDAN has been decreased by 48.22%. The MAE of the improved CEEMDAN-QRBL model is reduced by 12.36% and 16.31%, and the Ens is improved by 8.81% and 3.96%, respectively, when compared with the EMD-LSTM and CEEMDAN-GRU models. The predicted values of the CEEMDAN-QRBL model have a suitable fluctuation range thanks to the use of nonparametric kernel density estimation (NPKDE), which might serve as a useful benchmark for the distribution of regional water resources.
Effect of the sampling interval on the measurement accuracy of electronic water meters under real consumption conditions
Authors: Borchling Alexander , Kroner Corinna , Tränckner Jens 
Published: November 2022

Abstract
The share of electronic water meters installed in households has increased sharply in recent years. However, the current regulations are in large parts still tailored to traditional mechanical water meters. Electronic meters have already been included in the common standards, but reviews and various adaptions are still missing. An important point to be reviewed is the impact of the sampling interval of the electronic water meters on the measurement accuracy of the captured water volume. In this study, the error caused by the sampling interval is investigated by using measured data sets and stochastic water consumption data. It is shown that the error caused by sampling depends on the starting point of the sampling and the observation period. The studies show that for a billing period of one year, which is common in Germany, the sampling interval should be 14 s or less to always ensure a sampling-related error of less than 0.5%. Based on the results, input for further regulations is derived.
Understanding the Role of Free Radicals and Antioxidant Enzymes in Human Diseases
Authors: Chaudhary Nidhee , Roy Zinal , Bansal Raveena , Siddiqui Lubna 
Published: November 2022

Abstract:Antioxidant enzymes being an integral part of the defense mechanism have a crucial role in cellular metabolism, essential for healthy growth and living of the cells. The main function is to scavenge and degrade the free radicals, reactive oxygen species (ROS), and reactive nitrogen species (RNS). Endogenous antioxidant enzymes present in mitochondria, cytosol, and other cellular parts participate in capturing and repairing the oxidative damage to the system. Superoxide dismutase, catalase, and glutathione are antioxidant enzymes considered to be part of the first line of defense and are especially important in scavenging reactive oxygen species such as superoxide anion and hydrogen peroxide. Numerous studies in humans, as well as animal models, are correlated and reported about elevation in the enzymatic activity being involved in inhibiting oxidative damage and controlling the disease progression. Similarly, alterations due to enzymatic damage increase oxidative damage and have a key role in disease progression in diseases like cancer, atherosclerotic diseases, neurodegenerative diseases like Parkinson’s, Alzheimer’s, viral diseases, age-related ailments, etc. However, information about antioxidant enzymes, their specificity, free radicals involved in different diseases, and the oxidation process needs to be explored to a greater extent. This review focuses on our current understanding of the role of free radicals and the potential of various antioxidant enzymes, and their great scope in therapeutics against many dreadful diseases.
Current Progress on Neuroinflammation-mediated Postoperative Cognitive Dysfunction: An Update
Authors: Peng Wenyong , Lu Wei , Jiang Xiaofeng , Xiong Chang , Chai Hua , Cai Libin , Lan Zhijian 
Published: November 2022

Abstract:Postoperative cognitive dysfunction (POCD) is a common complication of the central nervous system (CNS) in elderly patients after surgery, showing cognitive changes such as decreased learning and memory ability, impaired concentration, and even personality changes and decreased social behavior ability in severe cases. POCD may appear days or weeks after surgery and persist or even evolve into Alzheimer's disease (AD), exerting a significant impact on patients’ health. There are many risk factors for the occurrence of POCD, including age, surgical trauma, anesthesia, neurological diseases, etc. The level of circulating inflammatory markers increases with age, and elderly patients often have more risk factors for cardiovascular diseases, resulting in an increase in POCD incidence in elderly patients after stress responses such as surgical trauma and anesthesia. The current diagnostic rate of POCD is relatively low, which affects the prognosis and increases postoperative complications and mortality. The pathophysiological mechanism of POCD is still unclear, however, central nervous inflammation is thought to play a critical role in it. The current review summarizes the related studies on neuroinflammation-mediated POCD, such as the involvement of key central nervous cells such as microglia and astrocytes, proinflammatory cytokines such as TNF-α and IL-1β, inflammatory signaling pathways such as PI3K/Akt/mTOR and NF-κB. In addition, multiple predictive and diagnostic biomarkers for POCD, the risk factors, and the positive effects of anti-inflammatory therapy in the prevention and treatment of POCD have also been reviewed. The exploration of POCD pathogenesis is helpful for its early diagnosis and long-term treatment, and the intervention strategies targeting central nervous inflammation of POCD are of great significance for the prevention and treatment of POCD.
Antimalarials Targeting the Malaria Parasite Cation ATPase P. falciparum
ATP4 (PfATP4)
Authors: Zagórska Agnieszka , Jaromin Anna 
Published: November 2022

Abstract:
Malaria, caused by parasites of the Plasmodium species and transmitted through the bites of infected female Anopheles mosquitoes, is still a fatal and dangerous disease in mainly tropical and subtropical regions. The widespread resistance of P. falciparum to antimalarial drugs forces the search for new molecules with activity against this parasite. While a large number of compounds can inhibit P. falciparum growth in vitro, unfortunately, only a limited number of targets have been identified so far. One of the most promising approaches has been the identification of effective in-hibitors of P-type cation-transporter ATPase 4 (PfATP4) in P. falciparum. PfATP4 is a Na+ efflux pump that maintains a low cytosolic Na+ in the parasite. Thus, upon treatment with PfATP4 inhibi-tors, the parasites rapidly accumulate Na+, which triggers processes leading to parasite death. PfATP4 is present in the parasite plasma membrane but is absent in mammals; its exclusivity thus makes it a good antimalarial drug target.
The current review presents PfATP4 function in the context of the pharmacological influence of its inhibitors. In addition, compounds with inhibitory activities belonging to spiroindolones, dihydroi-soquinolones, aminopyrazoles, pyrazoleamides, and 4-cyano-3-methylisoquinolines, are also re-viewed. Particular emphasis is placed on the results of preclinical and clinical studies in which their effectiveness was tested. PfATP4-associated antimalarials rapidly cleared parasites in mouse mod-els and preliminary human trials. These findings highlight a fundamental biochemical mechanism sensitive to pharmacological intervention that can form a medicinal chemistry approach for antima-larial drug design to create new molecules with potent PfATP4 inhibitory activity.
Early Efficacy of Antipsychotic Medications at Week 2 Predicts Subsequent
Responses at Week 6 in a Large-scale Randomized Controlled Trial
Authors: Tang Yiguo , Wu Yulu , Li Xiaojing , Hao QinJian , Deng Wei , Yue Weihua , Yan Hao , Zhang Yamin , Tan Liwen , Chen Qi , Yang Guigang , Lu Tianlan , Wang Lifang , Yang Fude , Zhang Fuquan , Yang Jianli , Li Keqing , Lv Luxian , Tan Qingrong , Zhang Hongyan , Ma Xin , Li Lingjiang , Wang Chuanyue , Ma Xiaohong , Zhang Dai , Yu Hao , Zhao Liansheng , Ren Hongyan , Wang Yingcheng , Zhang Guangya , Li Chuanwei , Du Xiangdong , Hu Xun , Li Tao , Wang Qiang 
Published: November 2022

Background:
Since the early clinical efficacy of antipsychotics has not yet been well perceived,
this study sought to decide whether the efficacy of antipsychotics at week 2 can predict subsequent
responses at week 6 and identify how such predictive capacities vary among different antipsychotics
and psychotic symptoms.

Methods:
A total of 3010 patients with schizophrenia enrolled in a randomized controlled trial (RCT)
and received a 6-week treatment with one antipsychotic drug randomly chosen from five atypical antipsychotics
(risperidone 2-6 mg/d, olanzapine 5-20 mg/d, quetiapine 400-750 mg/d, aripiprazole 10-30
mg/d, and ziprasidone 80-160 mg/d) and two typical antipsychotics (perphenazine 20-60 mg/d and
haloperidol 6-20 mg/d). Early efficacy was defined as the reduction rate using the Positive and Negative
Syndrome Scale (PANSS) total score at week 2. With cut-offs at 50% reduction, logistic regression,
receiver operating characteristic (ROC) and random forests were adopted.

Results:
The reduction rate of PANSS total score and improvement of psychotic symptoms at week 2
enabled subsequent responses to 7 antipsychotics to be predicted, in which improvements in delusions,
lack of judgment and insight, unusual thought content, and suspiciousness/ persecution were endowed
with the greatest weight.

Conclusions:
It is robust enough to clinically predict treatment responses to antipsychotics at week 6
using the reduction rate of PANSS total score and symptom relief at week 2. Psychiatric clinicians had
better determine whether to switch the treatment plan by the first 2 weeks.

Clinical Trial Registration Number:
This RCT was registered at the Chinese Clinical Trials Registry
Identifier: ChiCTR-TRC-10000934).