bluuebunny/crossref_metadata_2025_split huggingface dataset:
The safety and efficacy of surgery for foot deformity in patients with Charcot-Marie-Tooth disease: a systematic review and meta-analysis
Authors: Song Haibo , Wu Yuanpeng , Zhang Huifang , Liu Zengling , Ren Yuebing 
Published: March 2024

Abstract

Background
The objective of this study is to conduct a comprehensive meta-analysis to assess the safety and effectiveness of surgical treatment in patients with Charcot–Marie–Tooth disease (CMT), the most prevalent inherited peripheral neuropathy. The aim is to assess if surgical interventions improve functional scores in CMT patients, filling literature gaps and guiding evidence-based surgical management.
Methods
We conducted a systematic review and meta-analysis, searching articles in PubMed, Embase, the Cochrane Library databases, and Web of Science from their inception to December 10, 2023. Inclusion criteria involved studies reporting primary data, focusing primarily on surgical treatments for CMT foot deformity, having available full text, and reporting outcomes from more than three patients. Non-surgical treatment studies, review articles, basic research, and cadaveric studies were excluded. Outcomes associated with the surgical management of CMT were obtained using random-effects meta-analysis.
Results
From a total of 572 identified and screened studies, 11 studies (1.9%) comprising 322 feet undergoing surgical procedures for CMT were included. Among them, there were 2 prospective observational studies, 8 retrospective cohort studies, and 1 case report. However, while post-operative ankle function scores showed improvement, patient satisfaction and reintervention rates remained unsatisfactory. Notably, three studies reported significant improvements in the range of motion parameters for tibiotalar flexion with the knee in full extension post-operation. Radiographic examination was conducted to evaluate deformity correction and force lines. Furthermore, complications such as early post-op or subsequent operations, delayed wound healing, blisters, and Ward were monitored in all 11 studies.
Conclusion
Surgical management is effective in improving assessment scores, foot and ankle function, and enabling a faster return to work and sports for patients with CMT. However, caution is needed to minimize complications. Further research, including RCT, is necessary to assess detailed outcomes and identify prognostic factors for treatment decision-making in clinical practice.
A Adaptive Service Deployment Algorithm for Cloud-Edge Collaborative system based on Speedup Weights
Authors: Hu Zhichao , Chen Sheng , Rao Huanle , Hong Chenjie , Huang Ouhan , Xu Xiaobin , Jia Gangyong 
Published: March 2024

Abstract
In the contemporary landscape of edge computing, the deployment of services with stringent real-time requirements on edge devices is increasingly prevalent. However, the challenge of designing an effective service deployment strategy that optimally leverages both cloud and edge resources to deliver high-quality services in production environments persists, primarily due to resource constraints in edge devices. To tackle this issue, we introduce an adaptive service deployment algorithm that utilizes speedup weights for cloud-edge collaborative environments(SWD-AD). This algorithm is crafted by comparing task execution times in both cloud and edge settings and integrating Speedup Weights with resource consumption metrics. During task cluster operations, service-specific task processing data is collected, and cumulative Speedup Weights are computed. Based on this metric, a dynamic service adjustment policy is implemented to facilitate service migration between cloud and edge, optimizing resource allocation. Our performance evaluation experiments reveal that this strategy notably reduces the average response time of tasks by 29.38\% and 25.86\% compared to Swarm and kubernetes (K8s) algorithms, respectively.
Study of The Effect Of Graphene Oxide in Flexible and Moldable Bamboo/Brine Sludge &amp; PDMS-Based Composites for Thermal Applications
Authors: Singhwane Anju , Jaiswal Ayushi , Srivast AK , Verma Sarika 
Published: March 2024

Abstract
The present study introduces a novel approach for developing advanced, adaptable, flexible, and moldable composite using bamboo powder derived from bamboo fiber, graphene oxide (GO), and chlor-alkali waste brine sludge embedded with polydimethylsiloxane (PDMS). The process involves the development of a flexible composite utilizing treated bamboo fiber powder with brine sludge, graphene oxide nanoparticles, and PDMS as a polymer matrix. The study developed three sets of Graphene Oxide GO-reinforced flexible Bamboo composite named TGO 100, TGO 300 and TGO 500. The utilization of this flexible, thermally active bamboo composite holds promise as an alternative in various applications. The developed samples were characterized for their morphological, mechanical, water absorption, and thermal conductivity studies. With the increase in the concentration of graphene oxide (TG0 500 composition) the highest tensile strength is reported to be 0.197 Mpa.The thermal conductivity results demonstrate that the developed flexible material exhibits thermal conductivity properties, with the material achieving excellent values of 0.192, 0.196, and 0.203 W/m·K respectively. Consequently, the bamboo-based flexible composite material possesses outstanding thermal conductive qualities and can find diverse applications across a wide range of fields.
Network pharmacology-based investigation and experimental validation of the mechanism of Metformin in the treatment of acute myeloid leukemia
Authors: Liu Shaoyu , Xu mingming , Yang zhuofan , Li yangzi , Wu Depei , Tang Xiaowen 
Published: March 2024

Abstract
Metformin，a widely used anti-diabetic agent, has shown significant anti-cancer properties as reported in in various cancers, including acute myeloid leukemia. However, the detailed mechanisms by which metformin influences acute myeloid leukemia remain unrevealed. Employing a synergistic approach of network pharmacology and experimental validation, this study systematically identifies and analyses potential Metformin targets and AML-related genes. These findings are then cross-referenced with biomedical databases to construct a target-gene network, providing insights into Metformin's pharmacodynamics in AML treatment. Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses are utilized. Results show Metformin's effectiveness in inhibiting AML cell proliferation and inducing apoptosis through the AKT/HIF1A/PDK1 signaling pathway. This research provides insights into Metformin's clinical application in AML treatment.
Unsupervised metric learning via K-ISOMAP for high-dimensional data clustering
Authors: Mendes Rodrigo de P. , Chavari Gustavo H. , Levada Alexandre L. M. 
Published: March 2024

Abstract
Clustering does not assume the knowledge of the class labels, defining an unsupervised learning paradigm relevant for many pattern recognition and machine learning problems. One of the limitations of clustering is that most algorithms rely heavily in a distance function used to compute a dissimilarity measure between the samples. The usual choice is the Euclidean distance, which is known to have a poor discriminant power in high-dimensional spaces and also is quite sensitive to the presence of outliers. In this paper, we propose to investigate how unsupervised metric learning via the curvature-based ISOMAP algorithm (K-ISOMAP) can influence the clustering performance by means of quantitative evaluation metrics. The computation of the local curvature in the dimensionality reduction process allows the incorporation of an adaptive and intrinsic distance metric function into clustering, making it more aware of the geometry of the underlying data manifold. Computational experiments with real-world datasets indicate that the use of K-ISOMAP prior to a clustering algorithm may produce superior Rand, Calinski-Harabasz and Fowlkes-Mallows indices, in comparison to raw and regular ISOMAP data, suggesting that learning a suitable metric can be a relevant pre-processing step before clustering.
Impact of Pyrazinamide Usage on Serious Adverse Events in Elderly Tuberculosis Patients: A Multicenter Cohort Study
Authors: Yoon Joon Young , Kim Tae-Ok , Kim Ju Sang , Kim Hyung Woo , Lee Eung Gu , Jeong Sung Soo , Oh Jee Youn , Kim Jin Woo , Lee Sang Haak , Kim Seunghoon , Kim Sun-Hyung , Park Yeonhee , Min Jinsoo , Kwon Yong-Soo 
Published: March 2024

Abstract

Background Pyrazinamide (PZA) usage has been associated with adverse drug reactions, prompting its avoidance in treating elderly tuberculosis (TB) patients. This study aims to examine whether the administration of PZA is associated with poor outcomes during TB treatment among elderly individuals. Methods A retrospective analysis was undertaken on data collected from a prospective cohort conducted between July 2019 and June 2023, which involved tuberculosis patients from 18 institutions across the Republic Korea. The study aimed to assess the impact of PZA on the incidence of serious adverse events (SAEs), medication interruptions, and becoming lost to follow-up (LTFU) during standard short courses of TB treatment in elderly (≥ 65 years old) patients. Results PZA was administered to 356 of 390 elderly patients (91.3%), and 98 of the 390 (25.1%) experienced SAEs. Treatment success was significantly lower in patients not treated with PZA compared to those who received PZA (64.7% vs 89.9%, p < 0.001). The incidence of SAEs, medication interruption, or LTFU was higher in patients not given PZA compared those who received PZA (52.9% vs. 27.2%, p = 0.002). A multivariate logistic regression analysis, factoring in covariates such as age, comorbidities, and baseline laboratory data, revealed that PZA was not a risk factor for SAEs, medication interruption, or LTFU in TB treatment (odds ratio [OR] 0.457, 95% confidence interval [CI] 0.201–1.041). Conclusion Treating elderly TB patients with PZA did not increase the incidence of SAEs, medication interruptions, or LTFU during the standard short course of TB treatment. Therefore, considering its potential advantages, incorporating PZA into the treatment regimen for elderly TB patients may be advisable.
Experimental Study on Bearing Characteristics of Single Piles of Different Lengths in Heterogeneous Layered Foundation
Authors: WANG Zhengzhen , HUANG Lei , DAI Guoliang , CAO Chengming , Zhu Wentao 
Published: March 2024

Abstract

In order to study the vertical bearing characteristics of bored piles with different lengths in heterogeneous layered foundation, two single piles with different lengths in layered foundation were tested using BOFDA technique and anchor pile method static load test relying on the pile testing project of Lanzhou Zhongchuan International Airport Phase III expansion project. The pile top settlement, pile axial force, pile side friction resistance and pile-soil relative displacement under vertical load were measured and analyzed. On the other hand, the measured limit lateral resistance value was compared with the recommended value in the geological survey report, and the relationship between pile end resistance and pile end displacement under the influence of sediment was analyzed by using the three-fold line model. The results can provide reference for the design and testing of bored pile in heterogeneous layered foundation.
Optimizing Concrete Performance through Metakaolin and Flyash Incorporation: A Critical Appraisal of Regression Modeling and Design Code Applicability
Authors: MM Saravanan , Ayyadurai Ananthakumar , P Sasikumar 
Published: March 2024

Abstract
An investigation into the use of metakaolin (MK) and fly ash (FA) as partial cement replacements in concrete was conducted to enhance the sustainability of the construction industry. The MK and FA were incorporated into the concrete mix design by weight, replacing a portion of the portland cement content. The replacement percentages varied in two sets: 5%, 7.5%, 10%, 12.5%, and 15% for MK; and 5%, 10%, 15%, 20%, and 25% for FA. Workability of the fresh concrete was evaluated using the slump cone test to identify the optimal replacement level. Subsequently, the mechanical properties of the hardened concrete were investigated using compressive strength (CS), split tensile strength (STS), flexural strength (FS), modulus of elasticity (MoE). The results revealed that incorporating MK improved the mechanical properties: CS increased by 12.06%, STS by 16.84%, and FS by 15.42% compared to the control mix. In comparison, FA substitution resulted in a slightly lower increase: CS by 9.72%, STS by 12.84%, and FS by 8.57%. The study concluded that MK exhibited a superior performance in enhancing the strength properties of concrete compared to FA. Additionally, linear regression analysis was employed to establish correlations between the experimentally determined strength properties and the mix design parameters. This analysis demonstrated a strong correlation between the predicted and experimental values, making it a valuable tool for future concrete mix design optimization.
A Container Optimal Matching Deployment Algorithm based on CN-Graph for Mobile Edge Computing
Authors: Rao Huanle , Chen Sheng , Du Yuxuan , Xu Xiaobin , Chen Haodong , Jia Gangyong 
Published: March 2024

Abstract
The deployment of increasingly diverse services on edge devices is becoming increasingly prevalent. Efficiently deploying functionally heterogeneous services to resource heterogeneous edge nodes while achieving superior user experience is a challenge that every edge system must address. In this paper, we propose a Container-Node Graph (CN-Graph) based container optimal matching deployment algorithm, Edge Kuhn-Munkres Algorithm (EKM) Based on Container-Node Graph, designed for heterogeneous environment to optimize systemperformance. Initially, containers are categorized by functional labels, followed by construction of a CN-Graph model based on the relationship between containers and nodes. Finally, the container deployment problem is transformed into a weighted bipartite graph optimal matching problem. In comparison with the mainstream container deployment algorithms, Swarm, Kubernetes, and the recently emerged ECSched-dp algorithm, the EKM algorithm demonstrates the ability to effectively enhance the average runtime performance of containers to 3.74 times, 4.10 times, and 2.39 times, respectively.
The effects of standardized intravenous Treprostinil in pulmonary arterial hypertension patients after total cavo-pulmonary connection procedure
Authors: Wang Xiaofeng , Wang Shilin , Shen Ruihuan , Lu Zhongyuan , Wang Xu 
Published: March 2024

Abstract

Objective
Total cavo-pulmonary connection (TCPC) is a palliative treatment for single ventricular malformations. For high-risk patients (preoperative mean pulmonary arterial pressure, mPAP > 15 mmHg), between the inhaled and oral targeted medications, the application of intravenous Treprostinil as a bridge therapy to achieve "seamless" management is core postoperative treatment. This study intends to explore the effect of different administration regimens on early postoperative recovery.
Methods
This was a retrospective cohort study. High-risk pediatric patients (age ≤ 14 years) who underwent TCPC procedure in Fu Wai Hospital from 2015 to 2022 were included. Since the regimen of Treprostinil was standardized in our center in 2021, the patients in 2020 and before were included in group 1, patients in 2021 and 2022 were included in group 2. The hemodynamic parameters were compared before and after the maintenance dose of Treprostinil. The differences of demographic characteristics, surgical data and postoperative recovery were compared between the two groups.
Results
A total of 51 pediatric patients was included. The group 1 included 35 patients who received Treprostinil at 1–3 post-operative days and an average dose of 12 ± 4 ng/(kg·min). The group 2 included 16 patients who received Treprostinil within postoperative 1 day and an average dose of 22 ± 7 ng/(kg·min). There were no significant differences between the two groups in terms of age, weight, preoperative percutaneous oxygen saturation and mPAP, heterotaxia syndrome, TCPC procedure type, other concurrent procedure, cardiopulmonary bypass time and aortic cross clamp proportion (p > 0.05). After 24 hours of Treprostinil treatment, the mPAP in group 1 reduced from 17 ± 3 mmHg to 15 ± 2mmHg (p < 0.001), and in group 2 from 17 ± 2 mmHg to 14 ± 2mmHg (p < 0.001), with no difference between groups. In the postoperative recovery, patients in Group 2 exhibited a reduced duration of mechanical ventilation, 19 (11, 25) hours vs 69 (23, 189) hours, p = 0.001; a shorter stay in the ICU, 8 (6,12) days vs 16 (9,26) days, p = 0.006; and a shorter postoperative length of stay, 27 (17,55) days vs 39 (29,58) days, p = 0.032. Patients in group 2 also exhibited a lower incidence of thromboembolic events, 0 (0/26) vs 26% (9/35), p = 0.043; and the need for renal replacement therapy, 0 (0/26) vs 31% (11/35), p = 0.011.
Conclusion
After TCPC procedure, the standardized application of Treprostinil can improve the postoperative recovery, reduce the incidence of important complications and benefit the early postoperative recovery.
Towards the Prediction of Drug Solubility in Binary Solvent Mixtures at Various Temperatures Using Machine Learning
Authors: Bao Zeqing , Tom Gary , Cheng Austin , Aspuru-Guzik Alán , Allen Christine 
Published: March 2024

Abstract

Drug solubility plays an important role in the drug development process. Traditional methods for measuring solubility involve saturating a solvent with the drug and determining the drug concentration thereafter. However, these techniques are tedious and challenging to employ when dealing with expensive drugs or those available in small quantities. To address this, researchers have begun to leverage machine learning (ML) as an alternative approach. ML offers a data-driven strategy that enables the training of models on existing datasets to predict unmeasured solubility. Nonetheless, the majority of existing ML research has focused on the predictions of aqueous solubility and/or solubility at specific temperatures. This restricts the application of these models in pharmaceutical development which often requires insights into drug solubility across various solvents, solvent mixtures, and temperature conditions. To bridge this gap, we compiled an extensive dataset including solubility of small molecules measured in a range of binary solvent mixtures under various temperatures. We trained models on this dataset and subsequently optimized through Bayesian optimization to identify the models and model configurations that deliver optimal performance. The chosen top-performing models were further validated through a prospective study. The results demonstrated the potential of these developed ML models to predict drug solubility, especially for drugs whose features closely align with the small molecules within the dataset. To support future research and facilitate advancements in the field, we have made the dataset and the codes openly available.
Data-Independent Acquisition-Based Mass Spectrometry (DIA-MS) Reveals Exosome Yes1 derived from cancer cells promotes osteosarcoma tumorigenesis via MAPK pathway
Authors: Li Zihua , Chen Qingjing , Zhang Yi , Ye Zhanhui , Song Yixian , Zhang Yiwei , Gu Chenzheng , Tan Jia , Yang Yunfeng , Shang Anquan 
Published: March 2024

Abstract

Background
Osteosarcoma (OS) stands as the predominant primary bone tumor impacting children and young adults. Exosomes, vital for cellular communication, emerge as promising markers for diagnosing and prognosticating tumors. While few proteomic studies have delved into osteosarcoma's exosomal protein secretion, examining the differences in exosomal proteomes from OS cells can unveil insights into bone tumor development and spread.
Methods This investigation employed Data-Independent Acquisition-Based Mass Spectrometry to analyze the exosomal proteomes of osteoblast and osteosarcoma cells. Exosomal YES1, belonging to the proto-oncogene tyrosine-protein kinase Src family kinases and linked with cancer genesis, tumor environments, and patient survival across various cancers, especially osteosarcoma, was a focal point. The study's experimental approach included in vitro functional assays (Edu, wound healing, transwell assays, flow cytometry) and in vivo experiments to assess the effects of exosomes on the malignant traits of OS cells. Immunohistochemistry was used to compare YES1 expression in human osteosarcoma tissues against normal tissues, complemented by bioinformatic analyses correlating YES1 expression levels with patient survival and prognosis.
Results The research found that exosomal YES1 from osteosarcoma cells is integral to the immune microenvironment and cancer-promoting activities in OS through the MAPK pathway. It was observed that YES1 expression was notably higher in osteosarcoma tissues compared to normal ones, aligning with bioinformatics findings that linked elevated YES1 expression with lower overall survival rates and poorer prognoses in patients.
Conclusions This study highlighted the critical role of osteosarcoma-derived exosomal YES1 in tumor immunology and oncogenesis via the MAPK pathway, presenting new perspectives on the function of exosomal proteins in osteosarcoma tumorigenesis. It also suggests the potential of exosomal YES1 as a biomarker for osteosarcoma therapy, emphasizing its importance in understanding tumor behavior and improving patient outcomes.