bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunization with different recombinant West Nile virus envelope proteins induces varying levels of serological cross-reactivity and protection from infection
Authors: Weiß Rebecca , Issmail Leila , Rockstroh Alexandra , Grunwald Thomas , Fertey Jasmin , Ulbert Sebastian 
Published: November 2023

IntroductionWest Nile Virus (WNV) is a zoonotic flavivirus transmitted by mosquitoes. Especially in the elderly or in immunocompromised individuals an infection with WNV can lead to severe neurological symptoms. To date, no human vaccine against WNV is available. The Envelope (E) protein, located at the surface of flaviviruses, is involved in the invasion into host cells and is the major target for neutralizing antibodies and therefore central to vaccine development. Due to their close genetic and structural relationship, flaviviruses share highly conserved epitopes, such as the fusion loop domain (FL) in the E protein, that are recognized by cross-reactive antibodies. These antibodies can lead to enhancement of infection with heterologous flaviviruses, which is a major concern for potential vaccines in areas with co-circulation of different flaviviruses, e.g. Dengue or Zika viruses.MaterialTo reduce the potential of inducing cross-reactive antibodies, we performed an immunization study in mice using WNV E proteins with either wild type sequence or a mutated FL, and WNV E domain III which does not contain the FL at all.Results and discussionOur data show that all antigens induce high levels of WNV-binding antibodies. However, the level of protection against WNV varied, with the wildtype E protein inducing full, the other antigens only partial protection. On the other hand, serological cross-reactivity to heterologous flaviviruses was significantly reduced after immunization with the mutated E protein or domain III as compared to the wild type version. These results have indications for choosing antigens with the optimal specificity and efficacy in WNV vaccine development.
Reality bites: highlighting the potential discrepancies between multisensory taste perception in extended and physical reality
Authors: Dawes Christopher , Beganovic Sabina , Schwalk Matti , Mai Michaela , Pawlizak Steve , Zhang Jingxin , Nelles Gabriele , Krasteva Nadejda , Obrist Marianna 
Published: November 2023

IntroductionWhen we taste, we take in a variety of sensory information that can be completely independent from the properties of the food itself: the ambient lighting and environmental sounds can all influence our taste perception and affective responses. However, current multisensory research is mixed as to whether these In Real Life (IRL) findings also apply to Extended Reality (XR) environments. A potential reason for this may be the limited realism of some XR scenarios, which this study aimed to overcome through an immersive Virtual Reality experience (VR, chosen for its greater realism relative to other XR applications) whilst also expanding the scope to flavour perception.MethodsA total of 34 participants rated food samples under neutral, red, and green ambient lighting in VR. Participants ate either lime flavoured, strawberry flavoured, or “Neutral” (no added flavour) samples.ResultsWhile participants were equally immersed in all three environments, they rated the red and green lighting environments as substantially less natural than the neutral lighting environment. Interestingly, while participants associated sweetness and sourness with red lighting and green lighting respectively, this minimally extended to their behavioural ratings, when sampling the stimuli in VR. Samples eaten under red lighting were rated as significantly sweeter than those eaten under neutral lighting. However, neither red nor green lighting affected sample sourness nor the intensity of strawberry or lime flavour.DiscussionThis study found limited evidence of multisensory integration in XR, wherein taste expectations do not extend to taste experiences. We discuss these results in light of prior works on crossmodal associations and raise a reflection on why multisensory integration of taste may not apply to XR in our study. While there is much excitement about the opportunities XR can offer, we argue that we are only at the beginning of understanding the experiences on the reality-virtuality continuum and that we need to establish a richer understanding of participants' experiences, expectations, and taste/flavour perceptions between IRL and XR.
Distance learning and face-to-face learning in a pathophysiology problem-based learning course during a pandemic
Authors: Chen Fang-Hsu , Wu Po-Jen , Chi Chih-Hsien 
Published: November 2023

IntroductionDuring the past 2 years of the COVID-19 pandemic, education methods adjusted from conventional in-person classes to distance learning. Most classes were lectures that could go well if the participants were familiar with the online operation and had a stable network connection. However, problem-based learning (PBL) classes, which rely on the ability to engage in discussions, still had communication and group development limitations.MethodsHere, we surveyed the learning effects of face-to-face (FF) and distance learning (DL) in a medical PBL course for two classes. Tutors and students were requested to give grades for five key areas (participation, communication, preparation, critical thinking, and group skills).Results and discussionsA questionnaire found reduced participation, communication, and group skills in DL classes in comparison to FF classes. The tutors’ perspective regarded participation and communication ability as reduced in DL. Nevertheless, one of the two classes showed no difference in group skills.ConclusionOur research shows the experience of a PBL class focusing on discussion and communication. In the post-pandemic era, whether FF or DL, classes should be appropriately adjusted to facilitate effective student communication.
Integrative bioinformatics analysis of biomarkers and pathways for exploring the mechanisms and molecular targets associated with pyroptosis in type 2 diabetes mellitus
Authors: Wang Wei , Wang Yao 
Published: November 2023

IntroductionResearch has shown that pyroptosis contributes greatly to the progression of diabetes and its complications. However, the exact relationship between this particular cell death process and the pathology of type 2 diabetes mellitus (T2DM) remains unclear. In this study, we used bioinformatic tools to identify the pyroptosis-related genes (PRGs) associated with T2DM and to analyze their roles in the disease pathology.MethodsTwo microarray datasets, GSE7014 and GSE25724, were obtained from the GEO database and assessed for differentially expressed genes (DEGs). The T2DM-associated DEGs that overlapped with differentially expressed PRGs were noted as T2DM-PRGs. Subsequently, 25 T2DM-PRGs were validated and subjected to functional enrichment analysis through Gene Ontology annotation analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and gene set enrichment analysis (GSEA). The diagnostic and predictive value of the T2DM-PRGs was evaluated using receiver operating characteristic curves (ROC). Additionally, a single-sample GSEA algorithm was applied to study immune infiltration in T2DM and assess immune infiltration levels.ResultsWe identified 25 T2DM-PRGs that were significantly enriched in the nuclear factor-kappa B signaling and prostate cancer pathways. The top five differentially expressed prognostic T2DM-PRGs targeted by miRNAs were PTEN, BRD4, HSP90AB1, VIM, and PKN2. The top five differentially expressed T2DM-PRGs associated with transcription factors were HSP90AB1, VIM, PLCG1, SCAF11, and PTEN. The genes PLCG1, PTEN, TP63, CHI3L1, SDHB, DPP8, BCL2, SERPINB1, ACE2, DRD2, DDX58, and BTK showed excellent diagnostic performance. The immune infiltration analysis revealed notable differences in immune cells between T2DM and normal tissues in both datasets. These findings suggest that T2DM-PRGs play a crucial role in the development and progression of T2DM and could be used as potential diagnostic biomarkers and therapeutic targets.DiscussionInvestigating the mechanisms and biomarkers associated with pyroptosis may offer valuable insights into the pathophysiology of T2DM and lead to novel therapeutic approaches to treat the disease.
A prediction model for high ovarian response in the GnRH antagonist protocol
Authors: Jiang Yilin , Cui Chenchen , Guo Jiayu , Wang Ting , Zhang Cuilian 
Published: November 2023

BackgroundsThe present study was designed to establish and validate a prediction model for high ovarian response (HOR) in the GnRH antagonist protocol.MethodsIn this retrospective study, the data of 4160 cycles were analyzed following the in vitro fertilization (IVF) at our reproductive medical center from June 2018 to May 2022. The cycles were divided into a training cohort (n=3121) and a validation cohort (n=1039) using a random sampling method. Univariate and multivariate logistic regression analyses were used to screen out the risk factors for HOR, and the nomogram was established based on the regression coefficient of the relevant variables. The area under the receiver operating characteristic curve (AUC), the calibration curve, and the decision curve analysis were used to evaluate the performance of the prediction model.ResultsMultivariate logistic regression analysis revealed that age, body mass index (BMI), follicle-stimulating hormone (FSH), antral follicle count (AFC), and anti-mullerian hormone (AMH) were independent risk factors for HOR (all P&lt; 0.05). The prediction model for HOR was constructed based on these factors. The AUC of the training cohort was 0.884 (95% CI: 0.869–0.899), and the AUC of the validation cohort was 0.884 (95% CI:0.863–0.905).ConclusionThe prediction model can predict the probability of high ovarian response prior to IVF treatment, enabling clinicians to better predict the risk of HOR and guide treatment strategies.
Gut microbiome and blood glucose control in type 1 diabetes: a systematic review
Authors: Abuqwider Jumana , Corrado Alessandra , Scidà Giuseppe , Lupoli Roberta , Costabile Giuseppina , Mauriello Gianluigi , Bozzetto Lutgarda 
Published: November 2023

ObjectiveThe risk of developing micro- and macrovascular complications is higher for individuals with type 1 diabetes (T1D). Numerous studies have indicated variations in gut microbial composition between healthy individuals and those with T1D. These changes in the gut ecosystem may lead to inflammation, modifications in intestinal permeability, and alterations in metabolites. Such effects can collectively impact the metabolic regulation system, thereby influencing blood glucose control. This review aims to explore the relationship between the gut microbiome, inflammation, and blood glucose parameters in patients with T1D.MethodsGoogle Scholar, PubMed, and Web of Science were systematically searched from 2003 to 2023 using the following keywords: “gut microbiota,” “gut microbiome,” “bacteria,” “T1D,” “type 1 diabetes,” “autoimmune diabetes,” “glycemic control,” “glucose control,” “HbA1c,” “inflammation,” “inflammatory,” and “cytokine.” The examination has shown 18,680 articles with relevant keywords. After the exclusion of irrelevant articles, seven observational papers showed a distinct gut microbial signature in T1D patients.ResultsThis review shows that, in T1D patients, HbA1c level was negatively correlated with abundance of Prevotella, Faecalibacterium, and Ruminococcaceae and positively correlated with abundance of Dorea formicigenerans, Bacteroidetes, Lactobacillales, and Bacteriodes. Instead, Bifidobacteria was negatively correlated with fasting blood glucose. In addition, there was a positive correlation between Clostridiaceae and time in range. Furthermore, a positive correlation between inflammatory parameters and gut dysbiosis was revealed in T1D patients.ConclusionWe draw the conclusion that the gut microbiome profiles of T1D patients and healthy controls differ. Patients with T1D may experience leaky gut, bacterial translocation, inflammation, and poor glucose management due to microbiome dysbiosis. Direct manipulation of the gut microbiome in humans and its effects on gut permeability and glycemic control, however, have not been thoroughly investigated. Future research should therefore thoroughly examine other potential pathophysiological mechanisms in larger studies.
Anomalies and major cluster-based grouping of electricity users for improving the forecasting performance of deep learning models
Authors: Aurangzeb Khursheed 
Published: November 2023

Analyzing and understanding the electricity consumption of end users, especially the anomalies (outliers), are vital for the planning, operation, and management of the power grid. It will help separate the group of users with unpredictable consumption behavior and then develop and train specialized deep learning models for power load forecasting or regular and non-regular users. The aim of the current work is to divide electricity customers into numerous groups based on anomalies in consumption behavior and major clusters. Successful separation of such groups of customers will provide us with two advantages. One is the increase in the accuracy of load forecasting of other users or groups of users due to their predictable consumption behavior. The second is the opportunity to develop and train specialized deep learning models for customers with highly unpredictable behaviors. The novelty of the work is the segregation of anomalous electricity users from normal/regular users based on outliers in their past power consumption behavior over a period of 92 days. Results indicate that almost 85 percent of the users in the selected residential community attribute one major cluster in their consumption behavior over a period of 3 months of data (92 days). It is also evident from the results that only a small proportion of customers, i.e., 10 out of 69 customers (15 percent), have either more than one cluster or attribute no cluster (zero clusters), which is highly important and indicates that these are the possible users who cause higher variations in power consumption of the residential community.
Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users
Authors: Diehl Peter Udo , Zilly Hannes , Sattler Felix , Singer Yosef , Kepp Kevin , Berry Mark , Hasemann Henning , Zippel Marlene , Kaya Müge , Meyer-Rachner Paul , Pudszuhn Annett , Hofmann Veit M. , Vormann Matthias , Sprengel Elias 
Published: November 2023

The hearing loss of almost half a billion people is commonly treated with hearing aids. However, current hearing aids often do not work well in real-world noisy environments. We present a deep learning based denoising system that runs in real time on iPhone 7 and Samsung Galaxy S10 (25 ms algorithmic latency). The denoised audio is streamed to the hearing aid, resulting in a total delay of around 65–75 ms, depending on the phone. In tests with hearing aid users having moderate to severe hearing loss, our denoising system improves audio across three tests: 1) listening for subjective audio ratings, 2) listening for objective speech intelligibility, and 3) live conversations in a noisy environment for subjective ratings. Subjective ratings increase by more than 40%, for both the listening test and the live conversation compared to a fitted hearing aid as a baseline. Speech reception thresholds, measuring speech understanding in noise, improve by 1.6 dB SRT. Ours is the first denoising system that is implemented on a mobile device, streamed directly to users’ hearing aids using only a single channel as audio input while improving user satisfaction on all tested aspects, including speech intelligibility. This includes overall preference of the denoised and streamed signal over the hearing aid, thereby accepting the higher latency for the significant improvement in speech understanding.
iTRAQ-based quantitative proteomic analysis of the antibacterial mechanism of silver nanoparticles against multidrug-resistant Streptococcus suis
Authors: Liu Baoling , Liu Dingyu , Chen Tianbao , Wang Xiaohu , Xiang Hua , Wang Gang , Cai Rujian 
Published: November 2023

BackgroundThe increase in antibiotic resistance of bacteria has become a major concern in clinical treatment. Silver nanoparticles (AgNPs) have significant antibacterial effects against Streptococcus suis. Therefore, this study aimed to investigate the antibacterial activity and mechanism of action of AgNPs against multidrug-resistant S. suis.MethodsThe effect of AgNPs on the morphology of multidrug-resistant S. suis was observed using scanning electron microscopy (SEM). Differentially expressed proteins were analyzed by iTRAQ quantitative proteomics, and the production of reactive oxygen species (ROS) was assayed by H2DCF-DA staining.ResultsSEM showed that AgNPs disrupted the normal morphology of multidrug-resistant S. suis and the integrity of the biofilm structure. Quantitative proteomic analysis revealed that a large number of cell wall synthesis-related proteins, such as penicillin-binding protein and some cell cycle proteins, such as the cell division protein FtsZ and chromosomal replication initiator protein DnaA, were downregulated after treatment with 25 μg/mL AgNPs. Significant changes were also observed in the expression of the antioxidant enzymes glutathione reductase, alkyl hydroperoxides-like protein, α/β superfamily hydrolases/acyltransferases, and glutathione disulfide reductases. ROS production in S. suis positively correlated with AgNP concentration.ConclusionThe potential antibacterial mechanism of AgNPs may involve disrupting the normal morphology of bacteria by inhibiting the synthesis of cell wall peptidoglycans and inhibiting the growth of bacteria by inhibiting the cell division protein FtsZ and Chromosomal replication initiator protein DnaA. High oxidative stress may be a significant cause of bacterial death. The potential mechanism by which AgNPs inhibit S. suis biofilm formation may involve affecting bacterial adhesion and interfering with the quorum sensing system.
Efficacy and safety of acupuncture treatment for fatigue after COVID-19 infection: study protocol for a pilot randomized sham-controlled trial
Authors: Kim Sung-A. , Lee Ji-Su , Kim Taegon , Kim Tae-Hun , Kwon Sunoh , Kang Jung Won 
Published: November 2023

BackgroundAs the coronavirus disease 2019 (COVID-19) pandemic has spread globally, its sequelae, called Long COVID, have persisted, troubling patients worldwide. Although fatigue is known to be the most frequent among Long COVID symptoms, its mechanism and treatment have not been clearly demonstrated. In 2022, we conducted a preliminary prospective case series and found that acupuncture and moxibustion were feasible interventions for fatigue. This study is a pilot patient-assessor-blinded randomized sham-controlled trial to evaluate the efficacy and safety of acupuncture treatment for patients with fatigue that has persisted for at least 4 weeks after recovery from COVID-19.MethodsThirty patients will be recruited and randomly assigned to either the acupuncture or sham acupuncture treatment groups. Treatment will be conducted thrice a week for both groups during 4 weeks. The primary outcome will be the efficacy and safety of acupuncture, including numeric rating scale (NRS), brief fatigue inventory (BFI), fatigue severity scale (FSS), and adverse event evaluation. Secondary outcomes will be evaluation of improvement in the comorbid symptoms of fatigue and feasibility variables. Outcome variables will be assessed before treatment, 4 weeks after treatment, and 8 weeks after treatment completion.DiscussionThe results of this study will be used to clarify the efficacy and safety of acupuncture treatment for persistent fatigue in patients with Long COVID. Additionally, the feasibility of the study design was validated to provide evidence for future full-scale randomized controlled trials.Clinical trial registration: identifier: KCT0008656 https://cris.nih.go.kr/cris/search/detailSearch.do?seq=24785&amp;search_page=L.
Quantitative study of bioinformatics analysis on glioma: a bibliometric analysis
Authors: Yang Xiaobing , Man Dulegeqi , Zhao Peng , Li Xingang 
Published: November 2023

BackgroundThe bioinformatics analysis on glioma has been a hot point recently. The purpose of this study was to provide an overview of the research in this field using a bibliometric method.MethodsThe Web of Science Core Collection (WOSCC) database was used to search for literature related to the bioinformatics analysis of gliomas. Countries, institutions, authors, references, and keywords were analyzed using VOSviewer, CiteSpace, and Microsoft Excel software.ResultChina was the most productive country, while the USA was the most cited. Capital Medical University had the largest number of publications and citations. Institutions tend to collaborate more with other institutions in their countries rather than foreign ones. The most productive and most cited author was Jiang Tao. Two citation paths were identified, with literature in basic research journals often cited in clinical journals. Immune-related vocabularies appeared frequently in recent studies.ConclusionGlioma bioinformatics analyses spanned a wide range of fields. The international communication in this field urgently needs to be strengthened. Glioma bioinformatics approaches are developing from basic research to clinical applications. Recently, immune-related research has become a focus.
The advantage of point-of-care ultrasound in central venous catheterization and related pericardial effusion in infants in the NICU
Authors: Zhang Yahui , Yan Aijing , Liu Yunfeng 
Published: November 2023

BackgroundCentral venous catheterization (CVC) is broadly used in neonatal intensive care units (NICUs) for efficient vascular access; however, its establishment and maintenance are associated with numerous risks and complications. Here, we focus on investigating the value of point-of-care ultrasound (POCUS) in the early diagnosis and treatment of pericardial effusion associated with CVC and compare the differences in ultrasound and radiography in CVC localization and monitoring in the NICU.MethodsTwenty-five infants with CVC-associated pericardial effusion (PCE) who were hospitalized in the NICU of Peking University Third Hospital between January 2013 and March 2023 were retrospectively selected for the study. Data concerning their catheterization characteristics, CVC tip position, clinical and imaging manifestations of PCE, treatments, and prognoses were analyzed.ResultsThe mean gestational age of our cohort was 29.3 ± 3.1 weeks, and the mean birth weight was 1,211 ± 237 g. The incidence of CVC-associated PCE was 0.65%, and 80% of PCE cases occurred within 4 days of CVC. After PCE, the most common symptoms were tachypnea (44%) and tachycardia (64%). Chest radiographs revealed cardiothoracic enlargement, and only 2 cases (9.10%) showed a “flask heart”. Cardiac ultrasound showed that the catheter tip extended deep into the heart in 72% of infants with PCE. Cardiac insufficiency was observed in 12 cases (48%). Overall, 8 infants (32%) had pericardial tamponade, 7 (87.5%) of whom underwent pericardiocentesis. Overall, 2 (8%) infants died, and the remaining 23 (92%) were cured.ConclusionCVC-associated PCE mostly occurs in the early post-catheterization stages (within 4 days) in infants. Some cases may have critical clinical manifestations and progress rapidly, with some even developing pericardial tamponade. A CVC tip being deep into the heart cavity is an important cause of PCE. Compared with chest radiography, point-of-care ultrasound is more accurate for CVC tip positioning and can detect PCE more quickly. Furthermore, it is more advantageous for locating and monitoring CVC-associated PCE. Early identification and diagnosis can effectively reduce fatality rates and improve the prognosis of infants with CVC-associated PCE.