bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the mechanical properties of stainless steel foams produced by dissolving spherical urea particles as a space holder
Authors: sahraei Masood , Naserian-Nik Ali Mohammad , Sazegaran Hamid 
Published: November 2023

Abstract

Foam materials are a family of new and advanced materials that, due to their unique characteristics, will have a lot of potential for development in the coming years. The family of foam materials is divided into three categories: metal foams, ceramic foams, and polymer foams. Compared to ceramic and polymer foams, metal foams are newer and their properties and applications are being developed So, it seems that a bright future is waiting for these materials. The current research deals with the production of metal foams made of 316L stainless steel, which has a relatively wide application in the medical industry, especially the construction of implants. For this purpose, the method of dissolving spherical urea particles in water has been used as a spacer. In order to study the effect of porosity and production pressure on the mechanical behavior of 316L stainless steel, a standard pressure test was performed on foam samples produced under different production pressures and porosity percentages and their mechanical properties were investigated. In addition to conducting experimental tests, foam finite element models with zero and 30 percent porosity were created and pressure tests were simulated for them.
Spin-reorientation driven emergent phases and unconventional magnetotransport in quasi-2D vdW ferromagnet Fe4GeTe2
Authors: Pal Atindra , Pal Riju , Pal Buddhadeb , Mondal Suchanda , Sharma Rajesh , Das Tanmoy , Mandal Prabhat 
Published: November 2023

Abstract
Nontrivial spin textures driven by strong exchange interaction, magneto-crystalline anisotropy and electron correlation in a low-dimensional magnetic material often lead to unusual electronic transitions. Through a combination of transport experiments and first principle calculations, we unravel the new electronic phases in quasi-2D van der Waals ferromagnet, Fe4GeTe2, possessing ferromagnetic TC ∼ 270 K, along with a spin reorientation transition (TSR ∼ 120 K) with the change of magnetic easy axis. Two electronic transitions are identified. The first transition near TSR exhibits a sharp fall in resistivity, followed by a sign change in the ordinary Hall coefficient (RH), together with, maximum negative magnetoresistance (MR) and anomalous Hall conductivity. Another unusual electronic transition, hitherto unknown, is observed near ∼ 38 K (TQ), where RH further changes sign and below which, the resistivity shows a quadratic temperature dependence and MR becomes positive. An analysis of the experimental data further uncovers the role of competing inelastic scattering processes in anomalous magnetotransport behavior. A DFT-based first-principle calculations unveil two possible magnetic phases, followed by a low-energy model Hamiltonian which captures the essence of these phases as well as explains the observed magnetotransport behavior. Thus, we demonstrate an interplay between magnetism and band topology and its consequence on electron transport in Fe4GeTe2, important for spintronic applications.
Screening of Akt and Wnt Pathways for the Early Diagnosis and Treatment of Alzheimer's Disease
Authors: Wang Yahan , Li Hai-Tao , Zhang Kai-Xin , Wu Hong-Yun , Cui Wen-Qiang , Xu Xiang-Qing , Zhi Hong-Wei , Zhang Ji-Wei 
Published: November 2023

Abstract
Background
Alzheimer's disease is a neurodegenerative disease that is difficult to reverse. Akt and Wnt play a role in complex cellular signaling, which is important for studying the onset of AD. This study aimed to screen key genes of the Akt and Wnt pathways as potential biomarkers for the early diagnosis and treatment of AD.
Methods
We searched for differentially expressed genes in the GEO database, constructed candidate gene protein-protein interaction (PPI) networks, and used least absolute shrinkage and selection operator (LASSO) regression analysis and the support vector machine-recursive feature elimination (SVM-RFE) algorithm to screen for key genes. Correlation and functional similarity analyses of key genes, immune infiltration analysis, ceRNA network construction, and drug prediction of key genes were performed. We further validated the expression of key genes in streptozotocin (STZ)-treated AD mice using quantitative reverse transcription (RT-q) PCR.
Results
Bioinformatic analysis identified five key genes in AD, including PRKACA, CDH3, ATP6V0C, DLL1, and CELSR2. Step-down tests, immunohistochemistry, and silver plate staining confirmed the success of STZ-induced AD in mice. RT-PCR showed that the relative expression of DLL1 mNRA in the AD group was higher than that in the control group, whereas the relative expression of ATP6V0C and PRKACA mRNA in the AD group was lower than the control group, which was consistent with the results of the bioinformatic analysis.
Conclusions
This study provides a basis for a more comprehensive understanding of the underlying mechanisms of AD. Furthermore, DLL1, ATP6V0C, and PRKACA may be potential intervention targets for AD.
Potential Therapy for Multiple Sclerosis (MS): Investigating the effects of 1,25-dihydroxycholecalciferol on T regulatory cells in Patients with MS
Authors: Arab Fahimeh Lavi , Khorasani Sahar , Naderi-Meshkin Hojjat , Mirahmadi Mahdi , Dana Hassan , Nikkhah Karim , Rajabian Arezoo , Nikkhah Ali , Yousefi Forouzan , Faraji Fatemeh , Tabasi Nafiseh Sadat , Mahmoudi Mahmoud 
Published: November 2023

Abstract
The active form of 1,25-dihydroxycholecalciferol and mesenchymal stem cells (MSCs) have immunomodulatory effects on the immune system and could be helpful for regenerative therapeutic application in neurodegenerative diseases. The MSCs were isolated from adipose tissue and characterized using surface CD markers pattern and differentiation capacity into adipose and osteocyte lineages. After that, the confirmed MSCs were cultured in the presence of different concentrations of 1,25-dihydroxycholecalciferol (6, 12, 25, 50, 100 nM and 0 as control). Finally, the MSCs proliferation and apoptosis were evaluated by 3-(4,5-dimethylthiazohl-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and flow cytometry tests, respectively. The gene expression of inflammatory and anti-inflammatory cytokines was measured by real-time PCR and regulatory T cells (Tregs) population using flow cytometry techniques. Also, anti-oxidant parameters including NO, MDA, and SOD activity were measured. Our findings indicated that 6, 12, 25 and 50 nM concentrations of 1,25-dihydroxycholecalciferol significantly increased AT-MSCs viability, protecting them against apoptosis and also expanded Tregs proportion. Furthermore, 1,25-dihydroxycholecalciferol induced higher expression levels of anti-inflammatory markers, while 1,25-dihydroxycholecalciferol decreased the expression of inflammatory cytokines. In addition, the 1,25-dihydroxycholecalciferol at concentrations of 100 nM decreased nitrite oxide content. This study demonstrated that 1,25-dihydroxycholecalciferol is effective in the AT-MSCs by inducing regulatory, anti-oxidant, and anti-apoptosis effects. The main conclusion of this study is that 1,25-dihydroxyvitamin D3 can act as a beneficial synergistic factor in treating patients undergoing stem cell therapy.
A SuperLearner approach to predicting diabetic kidney disease upon the initial diagnosis of T2DM in hospital
Authors: Lin Xiaomeng , Liu Chao , Wang Huaiyu , Fan Xiaohui , Li Linfeng , Xu Jiming , Li Changlin , Wang Yao , Cai Xudong , Peng Xin 
Published: November 2023

Abstract

Background Diabetic kidney disease (DKD) is a serious complication of diabetic mellitus (DM) and is asymptomatic until the advanced stage. We developed and validated a predictive model for DKD in patients with an initial diagnosis of type 2 Diabetes Mellitus (T2DM) based on real-world data. Methods Data from 3,291 patients (1740 men, 1551 women) newly diagnosed with T2DM at Ningbo Municipal Hospital of Traditional Chinese Medicine (2011–2023) were retrospectively collected. Data were randomly divided into training and validation cohorts. Forty-six readily available medical characteristics at initial diagnosis of T2DM from the electronic medical record (EMR) were used to develop prediction models based on linear, non-linear, and SuperLearner approaches. Model performance was evaluated using the area under the curve (AUC). Shapley additive explanation (SHAP) was used to interpret the best-performing models. Results Of the 3291 participants, 563 (17.1%) were diagnosed with DKD during a median follow-up of 2.53 years. The SuperLearner model had the highest AUC (0.7138, 95% CI [0.673, 0.7546]) for the holdout internal validation set in predicting any DKD stage. Top-ranked features were WBC_Cnt*, Neut_Cnt, Hct, and Hb. High WBC_Cnt, low Neut_Cnt, high Hct, and low Hb levels were associated with an increased risk of developing DKD. Conclusions We developed and validated a DKD risk prediction model for patients with newly diagnosed T2DM. Using routinely available clinical measurements, the SuperLearner model can predict DKD during hospital visits. Prediction accuracy and SHAP-based model interpretability may help improve early detection, targeted interventions, and prognosis of patients with DM.
Utilizing Incoherent Feedforward Loops for Enhanced Response Stability and Coordination of Microbial Consortia-Based Biosensors
Authors: Daniel Ramez , Kravchik Valeriia , Geva-Zatorsky Naama 
Published: November 2023

Abstract
Synthetic multicellular systems can accomplish complex tasks. However, their asynchronous design requires precise adjustments, often resulting in undesired output variations. Here, we created bacterial consortia designed for multi-marker detection, achieving member coordination by activating an array of AND logic gates controlled by a shared quorum sensing signal. Our experimental results demonstrate that successful coordination was achieved when the shared signal was generated by an incoherent feedforward loop (IFFL), leading to a low-level signal that maintains a consistent response across 20 cell generations. These characteristics provide a stable relationship in molecule synthesis and prevent amplitude amplification during signal processing, enabling the IFFL to coordinate the asynchronous activities among consortium members effectively. We examined the consortia-based biosensor by monitoring Lactate and Heme in humanized fecal samples for 40 hours. Our findings provide insights into the IFFL system's dynamic response and long-term stability, making them valuable for biotechnological applications e.g., scaling up synthetic multicellular systems.
Optimal immobilization position for conservative treatment of proximal humerus fractures by fracture type: A biomechanical cadaveric study
Authors: Jin Seokhwan , Lim Joon-Ryul , Yoon Tae-Hwan , Choi Yun-Rak , Chun Yong-Min 
Published: November 2023

Abstract

In conservative treatment for proximal humerus fractures (PHFs), the immobilization position of the affected arm should not be determined uniformly. The aim of this study is to investigate the optimal immobilization position for conservative treatment of different types of PHFs. PHF models involving either the surgical neck (SN) or greater tuberosity (GT) were created using 12 fresh-frozen cadaveric shoulders. In the SN model, the deforming forces on the pectoralis major muscle were measured in full adduction by increasing external rotation. In the GT model, the deforming force of the supraspinatus muscle was measured in neutral rotation by decreasing abduction, and the deforming force of the infraspinatus muscle was measured in full adduction by increasing internal rotation, respectively. In the SN model, the deforming force of the pectoralis major muscle increased significantly with external rotation from full internal rotation to neutral rotation (P=0.006), indicating that the arm should be placed in full internal rotation. In the GT model, the deforming force of the supraspinatus muscle increased significantly with adduction from 45° of abduction to full adduction (P=0.006); the deforming force of the infraspinatus muscle increased significantly with internal rotation from neutral rotation to full internal rotation (P=0.006). These findings should be considered when placing the arm in a brace so as to minimize the deforming force by either the supra or infraspinatus muscle. In conservative treatment for PHFs, the affected arm should be placed in a position that minimizes the deforming force on the fracture components involved.
The Machining Characteristics of Drilling Multidirectional CFRP Using Wire Electrical Discharge Machining
Authors: Hasan Ali , Abdallah Ramy 
Published: November 2023

Abstract
This paper examines the feasibility of wire electrical discharge machining (WEDM) on drilling multidirectional carbon-fibre-reinforced plastic (CFRP) composite laminates using high-performance wire electrodes. A full factorial experimental array of 8 (23) tests was employed to evaluate the effect of varying the machining parameters including pulse-on time (0.6 and 0.9 µs), pulse-off time (4 and 6 µs), and wire type (Compeed and Topas Plus D) on the material removal rate (MRR), top and bottom delamination factor (DFT and DFB) and surface integrity. The results revealed that the MRR varied between 1.35 and 2.9 mm3/min and increased by high pulse on time and low pulse off time as a result of the higher discharge energy generated. Despite, none of the parameters having a significant effect on MRR, the pulse-off time was found to have the largest percentage contribution ratio (PCR), with a value of 71.8%. The Topas Plus D wire exhibited a higher MRR (up to 21%) under the same cutting conditions compared to the Compeed wire electrode. Regarding the delamination, the top and bottom factors ranged from 1.06 to 1.20 and 1.08 to 1.25 respectively. The pulse-on time and its interaction with the pulse-off time had the highest PCR on DFT, with values of 26.86% and 38.21%, respectively, according to ANOVA, which showed that none of the parameters had a significant impact on delamination. Optical micrographs of the workpiece revealed the presence of defects in terms of poor hole quality/roundness error, frayed fibres, excessive delamination, and adhered debris (including wire electrode contaminants) on both the top and bottom surfaces. These defects tended to be more noticeable in experiments using the Compeed wire electrode, probably as a result of the higher discharge energies.
Systematic Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma
Authors: Zhang Long , Xiong Yajun , Zhang Jie , Feng Yuying , Xu Aiguo 
Published: November 2023

Abstract
Background
Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer and the leading cause of cancer-related deaths. Identifying novel drug targets for LUAD is essential, with the proteome serving as a major source of therapeutic targets. We performed proteomo-wide Mendelian randomization (MR) and colocalization analyses to identify potential targets for LUAD.
Methods
Data summarizing 1394 plasma proteins were extracted from an extensive study on protein quantitative trait loci, including 4907 individuals. Genetic associations with LUAD were sourced from the Transdisciplinary Research in Cancer of the Lung, involving 11245 cases and 54619 controls. MR analysis was conducted to assess the associations between proteins and LUAD risk. Bayesian colocalization anslysis was used to ascertain shared causal variants between the identified proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of the effect of risk factors mediated by proteins on LUAD. Finally, a protein-protein interaction (PPI) analysis was employed to unveil potential links between proteins and current LUAD medications.
Results
Mendelian randomization analysis identified nine plasma proteins. MDGA2 (OR, 1.13; 95% CI, 1.08–1.19), NTM (OR, 1.12; 95% CI, 1.09–1.16) , PMM2 (OR, 1.35; 95% CI, 1.18–1.53), RNASET2 (OR, 1.15; 95% CI, 1.08–1.21), and TFPI (OR, 4.58; 95% CI, 3.02–6.94) increased the risk of LUAD, while ALAD (OR, 0.79; 95% CI, 0.72–0.87), FLT1 (OR, 0.39; 95% CI, 0.28–0.55) , ICAM5 (OR, 0.91; 95% CI, 0.88–0.95), and VWC2 (OR, 0.85; 95% CI, 0.79–0.92) decreased the risk. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. NTM and FLT1 interacted with target proteins of current LUAD medications. Furthermore, two therapeutics are presently under evaluation, three are druggable and four are future breakthrough points.
Conclusions
Our proteome-wide MR analysis revealed nine proteins associated with the risk of LUAD. RNASET2, TFPI, VWC2, NTM, and FLT1 might be promising drug targets for LUAD and deserve further clinical investigation.
Layer reconstruction, collapse and metallization of van der Waals bonded ZrS2 under high pressure
Authors: Hu Qingyang , Yang Linfei , Li Junwei , Zhang Dongzhou , Liu Yuegao 
Published: November 2023

Abstract

In contrast to two-dimensional (2D) monolayer materials, van der Waals layered transition metal dichalcogenides exhibit rich polymorphism, making them promising candidates for novel superconductors, topological insulators, and high-performance electrochemical catalysts. Here, we combine Raman scattering, electrical conductivity, and synchrotron X-ray diffraction measurements to reveal a series of phase transitions in van der Waals layered ZrS2, driven by the formation of a distorted metastable structure under pressure. Unlike layered sliding observed in archetypal MoS2, ZrS2 undergoes a dramatic structural reconstruction, rearranging the original ZrS6 octahedra into ZrS8 cuboids at 5.5 GPa, leading to an abrupt 8.8% volume reduction. The unique cuboids coordination of Zr atoms in the single-layer is thermodynamically metastable and collapses to a partially disordered phase at 17.4 GPa, and ultimately metallize above 30.0 GPa. Decompressing metallic ZrS2 restores its semiconductor properties. These complex structural transitions present the highly tunable electronic properties of compressed ZrS2 with possible implications for optoelectronic devices.
Semisupervised adaptive learning models for IDH1 mutation status prediction
Authors: Zhao Yulin , Liang Fengning , Xu Jinhui , Xu Kai , Zhu Hong 
Published: November 2023

Abstract
The mutation status of isocitrate dehydrogenase1 (IDH1) in glioma is critical information for the diagnosis, treatment, and prognosis. Accurately determining such information from MRI data has become an important research problem in recent years. Existing techniques for this problem often suffer from various limitations, such as the data waste and instability issues. To address such issues, we present a semisupervised adaptive deep learning model based on radiomics and rough sets for predicting the mutation status of IDH1 from MRI data. Our model first uses a rough set algorithm to remove the redundant medical image features extracted by radiomics, and adds pseudo-labels to those non-label data with the help of statistical T-test. This helps us address the commonly encountered issue of insufficient datasets in medical imaging analysis. Then, it applies a Sand Cat Swarm Optimization (SCSO) algorithm to optimize the weight of pseudo-label data. Finally, our model adopts UNet and CRNN to construct a semisupervised classification model UCNet to classify the IDH1 mutation status. To validate our models, we use a preoperative MRI dataset with 316 glioma patients to evaluate the performance. Our study suggests that the prediction accuracy of glioma IDH1 mutation status reaches 95.63%. Our experimental results suggest that the study can effectively improve the utilization of glioma imaging data and the accuracy of intelligent diagnosis of glioma IDH1 mutation status.
Association of Dietary Diabetes Risk Reduction Score and Macronutrient Quality Index with Metabolic Syndrome
Authors: Namkhah Zahra , Irankhah Kiyavash , Sarviha Sina , Sobhani Seyyed Reza 
Published: November 2023

Abstract

Background: Metabolic syndrome (MetS) is a cluster of cardiovascular risk factors affecting a quarter of the global population, with diet playing a significant role in its progression. The aim of this study is to compare the effectiveness of Dietary diabetes risk reduction score (DDRRS) and Macronutrient Quality Index (MQI) scoring systems in assessing diet-related metabolic syndrome risk.Methods: In this cross-sectional study, data of 7431 individuals aged between 30 and 70 years from the Mashhad Cohort Study were used to evaluate metabolic syndrome risk factors. A valid semi-quantitative food frequency questionnaire assessed participants' dietary intake. The MQI was calculated based on carbohydrate, fat, and healthy protein components. The DDRRS was also computed. Anthropometric measurements and blood samples were taken to determine metabolic syndrome. Logistic regression analyses were performed to assess the association between MQI and DDRRS with metabolic syndrome and its components.Results: According to the crude model, we found that the odds of MetS were lower in the highest quartile of DDRRS and MQI when compared to the lowest quartile (P-trend < 0.001). The trend persisted in the full adjusted models, with odds ratios of 0.399 (95% CI: 0.319-0.500) and 0.597 (95% CI: 0.476-0.749) for DDRRS and MQI respectively. After controlling for all potential confounders, lower odds of central obesity in the highest quartile of MQI (OR: 0.818, 95%CI: 0.676-0.989, P-trend= 0.027) was observed. Moreover, we found that the odds of high triglyceride levels were lower in the highest quartile of DDRRS compared to the lowest quartile (OR: 0.633, 95% CI: 0.521, 0.770, P-trend< 0.001).Conclusion: In conclusion, our study suggests that higher adherence to both DDRRS and MQI is associated with reduced risk of metabolic syndrome and its components. These findings have important implications for public health and personalized nutrition strategies