bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Precision Deep Drawing Technology of Electro-Permanent Magnet
Authors: Zhang Jiacheng , Qin Siji , He Sicheng , Liu Zhicheng , Xu Zhongrui , Sun Yonggen 
Published: October 2024

Abstract

Deep drawing technology is widely used in industrial production. With the continuous improvement of industrial technology and the increasing demands of people's lives, more and more process products have put forward higher requirements for deep drawing forming accuracy. In order to improve the accuracy of deep drawing, it is essential to study the springback of deep drawing. Electro-permanent magnet technology can provide a green and environmentally friendly way to apply blankholder force in deep drawing processes. During one deep drawing process, it only needs to apply two pulse currents during magnetization and demagnetization. This article studies how to achieve the goal of predicting the springback of deep drawing using electro-permanent magnet technology to provide blank holder force through finite element analysis and data processing. The feed rate of the punch during the deep drawing process can be calculated based on the required product drawing height, and the forming accuracy can be controlled within the error range of 0.1mm. Therefore, it is feasible to achieve low-cost, high-precision forming of deep-drawn components with flanges.
Reporting gaps in shockwave-assisted orthodontic tooth movement and tooth mobility studies
Authors: Khorram Arsalan 
Published: October 2024

Abstract

Introduction: To date, studies exploring shockwave-assisted orthodontic tooth movement and tooth mobility have produced inconclusive results, largely attributable to varying methodologies and a lack of standardized reporting. This inconsistency hinders the ability to compare findings across studies and draw definitive conclusions.
Objective: The aim of this review is reporting the gaps in shockwave and orthodontic tooth movement/tooth mobility studies and the future opportunities.
Methods: Our search was conducted using PubMed, Scopus, Embase, and Web of Science up to August 2024. Searches were performed without restrictions on year, publication status, or language.
Results: Upon reviewing the full texts of the articles, only six related studies were found, including four animal studies and two human studies. Key parameters, such as shockwave system characteristics (e.g., type of shockwave system, energy flux density, pulse frequency, focal area, focal distance), patient characteristics (e.g., facial soft tissue thickness, pulpal blood flow changes, salivary gland secretion changes), and study characteristics (e.g., long-term follow-up, tooth movement/mobility measurement tools and their error, number of shockwave episodes, distance of the shockwave system from the face, distance of the shockwave system from the target tooth, the phase during which shockwave is applied), are often not thoroughly described.
Conclusions: This review emphasizes the need for standardized methodologies and comprehensive reporting in future studies to enable meaningful comparisons and reliable conclusions.
Plasma GFAP, NfL, and p-tau181 levels as early biomarkers of dementia in Chinese adults: Shenzhen community cohort study
Authors: Liang Chunhua , Yan Xueqing , Tian Jing , Yang Yunzhu , Xiao Xiaohua , Huang Yaohui , Wang Tianfu 
Published: October 2024

Abstract

Background
Although blood-based biomarkers can be used to detect early Alzheimer’s disease (AD), population differences affect their clinical value in early diagnosis of the disease spectrum.
Aims
To examine the potential of plasma biomarkers to detect different stages along the AD continuum in a Chinese population
Methods
We enrolled 113 adults from the Shenzhen community (53 cognitively unimpaired [CU], 45 with mild cognitive impairment [MCI], and 15 with AD). We used the single-molecule array technique to detect the levels of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and phosphorylated-tau181 (p-tau181), and performed APOE genotyping. We assessed the association between plasma biomarkers and cognitive scores, and used receiver operating characteristic curves to measure performance for early AD diagnosis.
Results
The plasma GFAP, NfL, and p-tau181 levels increased significantly in AD and were slightly higher in MCI than in CU (GFAP p = 0.811, NfL p = 0.909, p-tau181 p = 0.696). The plasma GFAP and p-tau181 levels negatively correlated with cognitive scores. Blood markers demonstrated higher performance in identifying AD than CU or MCI. Plasma p-tau181 displayed the highest diagnostic value for AD. Predictions of cognitive impairment were more robust when blood markers were combined with clinical indicators for AD (age, sex, body mass index, years of education, and APOE ε4 carrier status).
Discussion
The expression of plasma GFAP, NfL, and p-tau181 increased in the AD continuum. Importantly, plasma p-tau181 could identify individuals with AD from the general population, with superior predictive performance when combined with age or sex.
Conclusions
Plasma biomarkers are useful screening indicators for early AD in Chinese adults.
Multiplex quantification of endocrine proteins in volumetric dried blood spot specimens
Authors: Stauch William Lindgren , Olausson Johan , Bendes Annika , Beck Olof , Schwenk Jochen M 
Published: October 2024

Abstract

Background:
Circulating proteins are routinely quantified from liquid biopsies to deduce health and disease. Among these are endocrine protein hormones, which regulate human growth, development, metabolism, and reproduction. Most commonly, these proteins are analyzed in plasma or serum prepared from venous blood draws. Recently, devices for quantitative capillary sampling from a finger prick have emerged, but their utility for clinical testing remains to be explored.
Methods:
To study the analytical capabilities of quantitative dried blood spots (qDBS), we quantified the luteinizing hormone (LHB), follicle-stimulating hormone (FSHB), thyroid-stimulating hormone (TSHB), prolactin (PRL), and growth hormone (GH1) by multiplexed immunoassays. We determined the performance of the endocrine hormone assays in paired qDBS and EDTA plasma samples from 100 donors (90% females) aged 4 to 78. Lastly, we compared the protein levels with those from an accredited clinical chemistry laboratory.
Results:
The multiplexed analysis showed precise protein quantifications in qDBS (mean CV = 8.3%), high concordance with plasma levels (r = 0.88 to 0.99), and accuracy being matrix- and protein-dependent (recovery: 80–225%). Using the current protocol and sample dilutions, reported protein concentrations were 1.2 to 7.5 times higher in plasma than in qDBS eluates. Concentrations from multiplexed plasma assays agreed with the clinical data (r = 0.87 to 0.99) and decreased slightly when comparing clinical plasma data with multiplexed qDBS assays (r = 0.76 to 0.98). Significant increases in age-related FSHB and LHB levels were observed in females in all specimens and assays (p < 0.01).
Conclusions:
This study shows the suitability of modern qDBS devices for quantifying clinically informative proteins in multiplexed assays and highlights the need for future work on specimen-specific optimization and standards. Volumetric DBS sampling offers new routines for accurate protein quantification for precision medicine.
Omilayers: a Python package for efficient data management to support multi-omic analysis
Authors: Kioroglou Dimitrios 
Published: October 2024

Abstract

Multi-omic integration involves the management of diverse omic datasets. Conducting an effective analysis of these datasets necessitates a data management system that meets a specific set of requirements, such as rapid storage and retrieval of data with varying numbers of features and mixed data-types, ensurance of reliable and secure database transactions, extension of stored data row and column-wise and facilitation of data distribution. SQLite and DuckDB are embedded databases that fulfil these requirements. However, they utilize the structured query language (SQL) that hinders their implementation by the uninitiated user, and complicates their use in repetitive tasks due to the necessity of writing SQL queries. This study offers Omilayers, a Python package that encapsulates these two databases and exposes a subset of their functionality that is geared towards frequent and repetitive analytical procedures. Synthetic data were used to demonstrate the use of Omilayers and compare the performance of SQLite and DuckDB.
Real-Time and Low Latency DynamicComputational Offloading Deep Neural NetworkTechnique in the Internet of Vehicles (IoV)
Authors: Amar Amar Nayak , Sanju Sanjay Agrawal 
Published: October 2024

Abstract

Recently, a new computing paradigm, edge computing, has gained attention because of high-throughput and short-delay task offloading for large-scale Internet-of-Things (IoT) applications. Computational task offloading in the IoT faces significant challenges relatedto energy consumption, performance, security, and latency. Traditionalmachine-learning cloud-based approaches may not meet the real-timetask offloading and processing requirements of IoT applications. To de-termine the potential of fully connected vehicles, the Internet of Vehicles(IoV) requires high-bandwidth and low-latency services. IoT devices inIoV networks have limited resources to perform large and complex op-erations. This issue of limited resources can be solved by dynamic task offloading using cloud and edge computing to improve IoV performance.This paper proposes an innovative Deep Neural Network (DNN) basedReal-Time and Low Latency dynamic computational offloading alloca-tion method that combines the strengths of Cloud and Edge computingwith low-latency computational offloading for IoT applications, such asIoV, Intelligent Transportation Systems, and smart cities. The proposedDNN model is trained to make decisions about where and when to offloadcomputational tasks dynamically based on input features like availableresources, vehicle network conditions, and speed. Finally, for implement-ing and evaluating the performances of proposed low latency, real-timedynamic computational offloading real traffic data are used to build upthe simulation scenarios. Experimental results indicate that our methodachieves improved performance in terms of latency, dynamic efficient re-source allocation, and computational task offloading compared to thetraditional machine learning cloud-based task offloading method.
Development of a novel person-centered question prompt list to pharmacists in Japanese community pharmacies: Focus Group and Delphi Method
Authors: Hayakawa Masayo , Kizaki Hayato , Yanagisawa Yuki , Suzuki Nobuyuki , Kagawa Yumi , Sayama Kyoko , Imai Shungo , Hori Satoko 
Published: October 2024

Abstract

Background
The concept of shifting from patient-centered to person-centered approach in pharmacy practice has been proposed. This shift requires smooth communication between the patients and pharmacists. Although there exists a question prompt list (QPL) for patients and doctors, the same is not available for pharmacists focused on a person-centered approach. This study aimed to develop a novel question prompt list to pharmacists (QPLP) focusing on a person-centered approach to facilitate communication between patients and pharmacists.
Methods
This study aimed to develop the QPLP in three steps. In the first step, six medical pharmaceutical researchers with pharmacist qualifications and two experienced representatives from patient associations prepared an initial draft of the QPLP, referencing existing QPLs used by patients to prepare questions for doctors before consultation. Next, a focus group interview was conducted with eight patients, and a QPLP was drafted. Finally, a modified Delphi method was used to evaluate and collect opinions, and the QPLP was finalized.
Results
A QPLP comprising 16 questions was developed with patient participation in a three-step process. The content was categorized into five sections: “Medicines,” “How to Take/Use Medicines,” “Daily Life,” “Treatment,” and “Consumer Health Information.” The questions covered concerns regarding medicines, difficulties in using medicines, issues in daily life during treatment, treatment-related problems, authenticity of health information, and community health and exercise information.
Conclusion
In this study, we developed a novel QPLP to enhance communication between patients and pharmacists, focusing on a person-centered approach with active patient involvement. Future studies should investigate the contribution of the developed QPLP in improving patient–pharmacist communication. These questions may encourage healthy people and patients to seek health advice from pharmacists.
Exploring the Association between Plasma Proteins and Frailty Based on Mendelian Randomization and Network Pharmacology
Authors: Chen Shuhui , Pan Hejing , Xu Yaling , Mao Yingying , Huang Lin 
Published: October 2024

Abstract

Background
Frailty is an emerging global burden of disease, characterized as an age-related clinical syndrome. Recent studies have suggested a potential link between plasma protein levels and the onset of frailty. This study aims to analyze the potential causal relationship between plasma proteins and frailty using a Mendelian Randomization (MR) study design.
Methods
Associations between plasma proteins and frailty were assessed using inverse variance weighted (IVW), MR-Egger regression, weighted median, maximum-likelihood method, and MR-PRESSO test. Protein-protein interaction network construction and gene ontology functional enrichment analysis were conducted on MR-identified target proteins.
Results
After FDR correction, MR analysis identified five plasma proteins, including BIRC2 [OR = 0.978, 95%CI(0.967–0.990)] and PSME1 [OR = 0.936, 95%CI(0.909–0.965)], as protective factors against frailty, and 49 proteins, including APOB [OR = 1.053, 95%CI(1.037–1.069)] and CYP3A4 [OR = 1.098, 95%CI(1.068,1.128)], as risk factors. Network pharmacology suggested BIRC2, PSME1, APOE, and CTNNB1 as key intervention targets.
Conclusion
This study employed MR design integrated with network pharmacology analysis to investigate the association between circulating plasma proteins and frailty, identified 5 plasma proteins negatively associated with frailty risk and 49 plasma proteins positively associated with frailty.
Impact of Surgical Timing on Mortality in Patients with Fragility Hip Fracture: Protocol for a Systematic Review and Meta-Analysis
Authors: Fu Hairui , Li Feixiong , Cheng Caitong , Shi Xianfeng 
Published: October 2024

Abstract

Background
It is important to improve outcomes and reduce mortality in fragility hip fracture patients. There is conflicting evidence on the prognostic role of surgery timing, and previous studies have been riddled with methodological flaws; therefore, further investigation is warranted. This review seeks to elucidate the prognostic significance of surgery timing for mortality risk among this patient population.
Methods
In accordance with the PRISMA-P 2015 guidelines, the MEDLINE, Embase, CENTRAL, and Google Scholar databases will be searched up to October 13, 2024, without language restrictions. EndNote and EPPI-Reviewer software will be utilized for the study selection, data extraction, and quality assessment processes. The primary outcome will be all-cause mortality. The secondary outcomes will be postoperative complications, readmission rates, and length of hospital stay. Meta-analysis will be performed when feasible, and subgroup and sensitivity analyses will be planned to explore the effects of variations in study design and bias assessment methods.
Discussion
This systematic review aims to synthesize existing evidence regarding the prognostic impact of surgery timing on mortality risk in fragility hip fracture patients. Additionally, this systematic review will investigate how different definitions of early surgery and varying follow-up durations may influence these outcomes, thus providing valuable guidance for clinical decision-making.
Trial registration:
Clinical trial number: not applicable
Predictors of weaning success from prolonged mechanical ventilation: A protocol study
Authors: Bartal Amir , Mai Ofri , shira Turgeman , Peles Ido , Paran Nave , Bartal Carmi 
Published: October 2024

Abstract

Objectives
To describe the outcomes of a large cohort of patients who have been on ventilation for > 14 days (extended prolonged ventilation) and identify unique predictors of weaning success within this group. We also aimed to examine the impact of diuretic therapy before weaning on the likelihood of successful weaning.
Design:
A retrospective study.
Setting:
The computerized database of Soroka University Medical Center, a tertiary 1191-bed medical center serving a population of 1.2 million residents.
Participants:
Overall, 88 patients were included in our study cohort. Forty patients (45%) were successfully weaned off mechanical ventilation and subsequently discharged either to rehabilitation facilities or directly to their homes.
Main outcome measures:
We analyzed the weaning success rate from extended prolonged mechanical ventilation and explored potential predictors for success using multivariate logistic regression.
Results
The in-hospital mortality rate was 28% (25 patients). All-cause mortality within 1 month and 1 year of discharge was 11% (10 patients) and 28% (20 patients), respectively. Hypoalbuminemia was the only significant predictor of weaning failure, with an odds ratio of 7.27. However, demographic factors such as age, comorbidities, reasons for mechanical ventilation, clinical and laboratory data at the time of admission, and diuretics treatment a few days before the initiation of weaning were not significant predictors of weaning success.
Conclusions
As patients stabilize and recover from the acute phase of illness that necessitates mechanical ventilation, rapid weaning success predictors may become less relevant in patients on long-term ventilation. Hypoalbuminemia has multiple potential mechanisms that may cause weaning failure in cases of prolonged ventilation. Therefore, interventions aimed at correcting hypoalbuminemia by improving the metabolic state may potentially enhance weaning success rates.
Cardiopulmonary exercise testing combined with stress echocardiography for the evaluation of myocardial dysfunction in children at risk
Authors: Schöffl Isabelle , Trager Eva , Kessler Lennart , Paech Christian , Weigelt Annika , Dittrich Sven , Wällisch Wolfgang 
Published: October 2024

Abstract

Aims
In paediatric cardiology stress echocardiography is rarely used, even though it is an established tool for investigating myocardial insufficiency which represents a threat in children after arterial switch operation (ASO) or Kawasaki disease (KD). This study combines stress echocardiography with cardiopulmonary exercise testing (CPET) for evaluating these children.
Methods:
We recruited former patients from our database after ASO or KD. All undertook a CPET either on a tilt-recline ergometer or on a treadmill with intermittent echocardiography with strain measurements. In addition to the standard cardiopulmonary exercise parameters the behaviour of the O2pulse before and after the end of exercise was evaluated.
Results:
43 children, adolescents and adults (21 ASO mean age 14.7, 10 KD aged 15.0, and 13 controls aged 15.3 years) participated in this study. The patients after ASO showed a significantly lower peak cardiopulmonary function (\(\:\dot{V}{O}_{2}peak\): 39.6 vs 45.9 ml/kg/min) as well as a lower first ventilatory threshold (VT1) in percent of \(\:\dot{V}{O}_{2}peak\) (45.7 vs. 54%). The only other significant difference was a slower decline of the O2pulse following the end of exercise. The strain values were normal. The patients undertook significantly less sport.
Conclusion:
The lower \(\:\dot{V}{O}_{2}peak\) in combination with the lower VT1 observed in the ASO group point to a lower cardiopulmonary function with poor endurance. In combination with the slower recovery of the O2pulse after exercise this could point to an impairment in cardiac output. Interestingly this was not true for the KD patients even when giant aneurysms were present.
Isolation and characterization of Salmonella enteritidis bacteriophage Salmp-p7 isolated from slaughterhouse effluent and its application in food
Authors: Chen Mengge , Yu Tong , Cao Xiangyu , Pu Jiaqi , Wang Deshu , Deng Hongkuan 
Published: October 2024

Abstract

Salmonella enteritidis is one of the most common pathogens that cause foodborne outbreaks and food spoilage, which seriously threatens human health. In this study, Salmonella enteritidis bacteriophage Salmp-p7 was isolated and characterized from slaughterhouse wastewater. Transmission electron microscopy (TEM) analysis showed that Salmp-p7 belonged to the Siphoviridae family and was active against Salmonella enteritidis and Escherichia coli. Whole genome sequence analysis showed that Salmp-p7 was a lytic bacteriophage with a total length of 60066 bp. In vitro, antimicrobial curves and inhibition of biofilm removal experiments showed that Salmp-p7 could effectively inhibit and eliminate Salmonella enteritidis. The application of Salmp-p7 to the whole liquid of infected eggs resulted in a significant reduction of viable bacteria in the egg liquid. In conclusion, the bacteriophage Salmp-p7 has high stability and lytic activity and has the potential to become a new biological control agent for Salmonella enteritidis in eggs.
Causal relationship between drug target genes of LDL-cholesterol and coronary artery disease: Drug Target Mendelian Randomization Study
Authors: Jee Yongho , Shin Jong Won , Ryu Mikyung , Song Tae-Jin 
Published: October 2024

Abstract

Background
High LDL-cholesterol (LDL-C) is a well-known risk factor for coronary artery disease (CAD). PCSK9, HMGCR, NPC1L1, ACLY, and LDLR gene have been reported as lipid lowering drug genes related to LDL-C lowering. However relevant Asian studies were rare.
Methods
We examined the causality between LDL-c drug target genes and CAD using Korean and Japanese data using the two sample Mendelian Randomization (MR) method. We conducted two-sample MR analysis of LDL-c lowering drug target genes (7 Single-nucleotide polymorphisms (SNP) in PCSK9, 6 SNPs in HMGCR, 5 SNPs in NPC1L1, 9 SNPs in ACLY, 3 SNPs in LDLR) and CAD. We used summary statistics data from the Korean Genome Epidemiology Study (KOGES) for LDL-C data, and Biobank of Japan (BBJ) for CAD data.
Results
For every 10 mg/dl decrease in LDL-C determined by four significant SNPs in the PCSK9 gene, the risk of CAD decreased by approximately 20% (OR = 0.80, 95% CI: 0.75–0.86). The risk of CAD decreased by 10% for every 10 mg/dl decrease in LDL-C due to the six significant SNPs in the HMGCR gene (OR = 0.90, 95% CI: 0.86–0.94). Due to the two significant SNPs in the gene LDLR, the risk of CAD decreased by approximately 26% for every 10 mg/dl decrease in LDL-C (OR = 0.74, 95% CI: 0.66–0.82). The combined effect on CAD showed the largest effect size for the PCSK9 gene and LDLR gene, and the reduced CAD risk induced by these two genes together was OR = 0.78 (95%CI, 0.74–0.83). Finally, the combined effect of all three genes (PCSK9, HMGCR, and LDLR) was OR = 0.85 (95%CI, 0.79–0.91) (Fig. 3D).
Conclusion
LDL-C reduction estimated by SNPs in LDL-C lowering drug target genes significantly reduced the risk of CAD. We found the potential of using of proxy research design for clinical trials using LDL-C lowering drugs.