bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blockchain Consensus Algorithm for Supply Chain Information Security Sharing Based on Convolutional Neural Networks
Authors: Cai Lu , Liu Aijun , Yan Yongcai 
Published: August 2024

Abstract

To solve the problems of data silos and information asymmetry in traditional supply chain information security sharing, this article combines Convolutional Neural Networks (CNN) and blockchain consensus algorithms, analyzes data and uses blockchain for secure sharing, so that all parties can obtain and verify data in real time, improve the overall operational efficiency of the supply chain, and promote information transparency and sharing efficiency. CNN can be used to analyze data in the supply chain. Training on real digital images ensures data privacy and improves the accuracy and efficiency of data processing. Blockchain technology can be introduced into supply chain information sharing to ensure the immutability and transparency of data. This article introduces a federated learning (FL) mechanism to improve consensus algorithms, which improves the efficiency of model training. Among them, each link in the FL process is rigorously verified and recorded through the consensus mechanism of blockchain, ensuring the security and reliability of the entire process. This article adopts an improved consensus algorithm, PoDaS (Proof of Data Sharing), whose core idea is to use the computational consumption generated during FL as proof of workload. The specific steps include: local model training and uploading, model update verification shield, and model update aggregation. The PoDaS algorithm combines the advantages of PoW (Proof of Work) and PoS (Proof of Stack) to ensure the fairness of the consensus mechanism and reduce the waste of computing resources. By comparing and analyzing the block time and model accuracy of three algorithms, the superiority of PoDaS algorithm in block time and model accuracy was verified. The experimental results show that the PoDaS algorithm is significantly better than the PoW algorithm in terms of block generation time, and slightly better than the PoS algorithm. In terms of model accuracy, the PoDaS algorithm is significantly superior to traditional PoW and PoS algorithms. Its model accuracy reaches 96.00%, reflecting the effectiveness and practicality of the PoDaS consensus algorithm in the sharing of supply chain information security.
Transfemoral hepatic vein access in double vein embolization – initial experience and feasibility
Authors: Carling Ulrik , Berger Sigurd , Gjønnæss Eyvind , Røsok Bård , Yaqub Sheraz , Lassen Kristoffer , Fretland Åsmund Avdem , Dorenberg Eric 
Published: August 2024

Abstract

Background: Hepatic vein embolization in double vein embolization (DVE) can be performed with transhepatic, transjugular or transfemoral access. This study evaluates the feasibility of using a transfemoral access for the hepatic vein embolization in patients undergoing preoperative to induce hypertrophy of the future liver remnant (FLR), in a cohort with very small FLR.
Material and Methods: Retrospective analysis of single center cohort including 17 consecutive patients. The baseline standardized FLR was 18.2 % (range 14.7-24.9). Portal vein embolization was performed with vascular plugs and glue through an ipsilateral transhepatic access. Hepatic vein embolization was performed using vascular plugs. Access for the hepatic vein was either transhepatic, transjugular or transfemoral. Technical success, number of hepatic veins embolized and complications were registered. In addition, volumetric data including degree of hypertrophy (DH) and kinetic growth rate (KGR), and resection data were registered.
Results: Seven of the 17 patients had transfemoral hepatic vein embolization, with 100% technical success. No severe complications were registered. In the whole cohort, the median number of hepatic veins embolized was 2 (1-6). DH was 8.6 % (3.0-19.4) and KGR was 3.6 %/week (1.4-7.4), without significant differences between the patients having transfemoral versus transhepatic /transjugular access (p= 0.48 and 0.54 respectively). Time from DVE to surgery was median 4.8 weeks (2.6-33.9) for the whole cohort, with one patient declining surgery, two having explorative laparotomy and one patient having change of surgical strategy due to insufficient growth.
Conclusion: Transfemoral access is a feasible option for hepatic vein embolization in patients with small future liver remnants needing DVE.
Diet and Feeding Strategy of Northern Pike, Esox lucius L., 1758 Inhabiting A Deep Dam Lake from Located Central Anatolia, TÜRKİYE
Authors: YAZICIOĞLU Okan , YAZICI Ramazan , YAĞCI Abdülkadir , YILMAZ Mahmut 
Published: August 2024

Abstract

Fish samples were collected monthly from Dam Lake from September 2015 to August 2016 and a total of 133 northern pike, Esox lucius individuals were examined for this study. The feeding intensity showed the highest value during summer (FI = 1.59) while the lowest value was during winter (FI = 0.51). Temperature was identified as the most critical environmental variable influencing feeding intensity. The high similarity in the diet of northern pike was observed between seasons. Stomach content analysis indicated that this species consumed only prey fishes. The most eaten of prey fishes were the Tinca tinca contributing 44.83% by number and 56.16% by frequency of occurrence. There was little variation in feeding features between seasons. The northern pike more specialized on T.tinca and Atherina. boyeri. According to the findings of the study, Esox lucius was a primary predator and showed a specialist feeding behavior, feeding only on fish (mainly T. tinca and A. boyeri). Environmental prey abundance did not affect the prey selection of this fish species in Sıddıklı Dam Lake.
Retroperitoneal pancreas transplantation with a Roux-en-Y duodenojejunostomy for exocrine drainage
Authors: Khubutiya Mogeli , Dmitriev Ilya , Zhuravel Nikita , Balkarov Aslan , Storozhev Roman , Anisimov Yuri , Kondrashkin Alexander , Shmarina Nonna 
Published: August 2024

Abstract

Background
Pancreatic transplantation is the only definitive surgical treatment for diabetes mellitus. Currently, most transplant centers use enteric exocrine drainage of pancreatic secretions; however, experts disagree on which part of the gastrointestinal tract is preferable for enteric anastomosis. We analyzed the outcomes of retroperitoneal pancreatic transplantation with enteric drainage of pancreatic secretions.
Materials and Methods
We evaluated the outcomes of 60 simultaneous retroperitoneal pancreas-kidney transplantations. Based on the type of enteric anastomosis, the patients were divided into two groups: the study group consisted of 10 patients who underwent enteric drainage via Roux-en-Y duodenojejunostomy, and the control group included 50 patients who underwent exocrine drainage via duodenoduodenal anastomosis. No statistically significant differences were observed between the groups in terms of the main parameters.
Results
The rate of surgical complications did not differ significantly between the groups (p > 0.05). Clavien IVb complications occurred only in the control group (n = 4.8%). The in-hospital pancreatic graft survival rate in both groups was 80%, whereas the recipient survival rates were 90% and 84%, in the study and control groups, respectively (p < 0.05).
Conclusion
Retroperitoneal pancreatic transplantation with exocrine drainage via a Roux-en-Y duodenojejunostomy is an effective alternative technique that reduces the rate of severe surgical complications.
A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques
Authors: Pope Francis , Baruah Arunik , Bousiotis Dimitrios , Damayanti Seny , Bigi Alessandro , Ghermandi Grazia , Ghaffarpasand Omid , Harrison Roy 
Published: August 2024

Abstract

Particulate Matter (PM) air pollution poses significant threats to public health. Existing models for predicting PM levels range from Chemical Transport Models to statistical approaches, with Machine Learning (ML) tools showing superior performance due to their ability to capture highly non-linear atmospheric responses. This research introduces a novel methodology leveraging ML tools to predict PM2.5 levels at a fine spatial resolution of 30 metres and temporal scale of 10 seconds. The methodology aims to demonstrate its proficiency in estimating missing PM2.5 measurements in urban areas that lack direct observational data. A hybrid dataset was curated from an intensive aerosol campaign in Selly Oak, Birmingham, UK, utilizing citizen scientists and low-cost Optical Particle Counters (OPCs) strategically placed in both static and mobile settings. Spatially resolved proxy variables, meteorological parameters, and aerosol properties were integrated, enabling a fine-grained analysis of PM2.5 distribution along road segments. Calibration involved three approaches: Standard Random Forest Regression, Sensor Transferability Evaluation, and Road Transferability Evaluation. Results demonstrated high predictive accuracy (R2 = 0.85, MAE = 1.60 µg m−³) for the standard RF model. Sensor and road transferability evaluations exhibited robust generalization capabilities across different sensors (best R2 = 0.65, MAE = 2.76 µg m−³) and road types (R2 = 0.71, MAE = 2.46 µg m−³), respectively. This methodology has the potential to significantly enhance spatial resolution beyond regulatory monitoring infrastructure, thereby refining air quality predictions and improving exposure assessments. The findings underscore the importance of ML-based approaches in advancing our understanding of PM2.5 dynamics and their implications for public health. The paper has important implications for citizen science initiatives, as it suggests that the contributions of a small number of participants can significantly enhance our understanding of local air quality patterns for many 1000s of residents.
Prognostic value of laboratory markers in patients with acute pulmonary embolism
Authors: Ahmed Yousef Ahmed Yousef , Elfadl Abd-Elazim Ahmed Abo , Houssein Abeer , Abdelrahman Amal Abdallah , Shehata Khaled Mohamed Ali , Omar Amany Omar Mohamed 
Published: August 2024

Abstract

Background
Acute pulmonary embolism (APE) is a serious illness. Identifying prognostic factors for APE may help in the management of those patients. This study's objective was to evaluate the prognostic value of laboratory markers in predicting right ventricular dysfunction (RVD) and 30-day mortality in pulmonary embolism patients.
Methods
Eighty patients with APE were enrolled and followed up for 30-day. Detailed echocardiography was done to evaluate RVD. All patients were subjected to arterial blood gas analysis, complete blood count (CBC), plasma concentration of C-reactive protein (CRP), serum D-dimer level, and serum troponin I level, and the following ratio were calculated: Neutrophil to lymphocytic ratio (NLR), Platelet to lymphocytic ratio (PLR), Red cell distribution width (RDW), Mean platelet volume (MPV) and alveolar to arterial gradient.
Results
Our results analysis revealed significantly elevated levels of median NLR, PLR, CRP, D-dimer, and troponin in both the RVD and non-survivor groups (P value < 0.001). The blood markers that showed the highest predictive ability for right ventricular dysfunction (RVD) and 30-day mortality, as determined by receiver operating characteristic (ROC) analysis and logistic regression, were A-a O2 gradient, serum troponin, CRP, D-dimer, NLR, and PLR (P value < 0.001).
Conclusion
Evaluation of different serum markers including NLR, PLR, RDW, CRP, D-dimer, troponin and A-a O2 gradient are simple and available markers for predicting right ventricular dysfunction (RVD) and 30- day mortality in patients with APE.
Trial registration:
ClinicalTrials.gov ID: NCT04237974.
Identification and Analysis of Autophagy-Related Genes as Diagnostic Markers and Potential Therapeutic Targets for Tuberculosis Through Bioinformatics
Authors: Luo Tingting , Shen Shijie , Sun Yufei , El-Ashram Saeed , Zhang Xia , Liu Keyu , Deng Siqi , Cao Chengzhang , Alajmi Reem Atalla , Wu Jiangdong , Zhang Wanjiang 
Published: August 2024

Abstract

Background: According to the World Health Organization, Mycobacterium tuberculosis (Mtb) infections affect approximately 25% of the world's population. There is mounting evidence linking autophagy and immunological dysregulation to TB, according to many research. As a result, this research set out to discover TB-related autophagy-related biomarkers, gene regulatory networks, and prospective treatment targets.
Methods: We used five autophagy databases to get genes linked to autophagy and GEO databases to get genes connected to TB. Then, functional modules associated with autophagy were obtained by analyzing them using weighted gene coexpression network analysis (WGCNA). Both GO and KEGG were used to examine the ATGs of important modules. Limma, an R tool, was used to identify differentially expressed ATGs, and the external datasets of GSE19435 were used to further confirm their identification. We used DE-ATGs and a protein-protein interaction (PPI) network to search the hub genes. CIBERSORT was used to estimate the kinds and amounts of immune cells. After that, we built a drug-gene interaction network and a network that included messenger RNA, small RNA, DNA, and ceRNA. At last, the differential expression of hub ATGs was confirmed by RT-qPCR, Immunohistochemistry (IHC), and Western blotting (WB). The diagnostic usefulness of hub ATGs was evaluated using receiver operating characteristic (ROC) curve analysis.
Results: Including 508 ATGs, four of the nine modules strongly linked with TB were deemed essential. Three hub genes—IL1B, CAPS1, and STAT1—were identified by intersection out of twenty-two DE-ATGs discovered by differential expression analysis. Research into immune cell infiltration found that TB patients had an increased proportion of plasma cells, CD8 T cells, and M0 macrophages. A competitive endogenous RNA (ceRNA) network utilized 10 long non-coding RNAs (lncRNAs) and 2 miRNAs. Then, the IL1B-targeted drug CANAKINUMAB was assessed using this network. During bioinformatics analysis, three hub genes—IL1B, CAPS1, and STAT1—were validated using WB/RT-qPCR/IHC in mouse and macrophage infection models. In most cases, the new findings corroborated the old ones.
Conclusion: We found that IL1B, CASP1, and STAT1 are important biomarkers for TB. As a result, these crucial hub genes may hold promise as TB treatment targets.
Early withdrawal immunosuppression improved mixed chimerism in hematopoietic stem cell transplantation for pediatric aplastic anemia
Authors: Wang Xinan , Qin Xia , Luo Chengjuan , Luo Changying , Wang Jianmin , Huang Xiaohang , Mi Qiang , Lin Yuchen , Chen Jing 
Published: August 2024

Abstract

Mixed chimerism (MC) occurs frequently with the risk of graft reject (GR) for aplastic anemia (AA) patients undergoing matched sibling donor (MSD) hematopoietic stem cell transplantation (HSCT). So far, no one knows how to adjust immunosuppression (IS) during MC. We retrospectively analyzed 87 consecutive pediatric patients. Early withdrawal (EW) IS and donor lymphocyte infusion (DLI) were attempted to reverse MC. The rate of MC was 26% (n = 23). Low dose cyclophosphamide (CY) (120–150 mg/kg) is an independent risk factor for MC (P = 0.0002) and increase dosage of Fludarabine (FLU) cannot eliminated it. Patients receiving 200 mg/kg CY had the lowest MC rate (8%) and best 3-year graft-versus-host disease (GVHD)/failure free survival (GFFS; 95%). Chimerism in T cells is more sensitive than that in whole blood (P = 0.001). In 17 patients with early-onset MC (ratio of DLI: 83% versus 82%), EW IS strategy is helpful to improving complete chimerism (CC) (63 vs. 295 days, P = 0.008). Our study shows that FLU is necessary to intensify CY + ATG conditioning to maintain the engraftment and 200 mg/kg CY + 150 mg/m2 FLU is recommended as a basic conditioning regimen. EW IS strategy should be considered as an important option to improve donor chimerism in early-onset MC.
Biomarkers to predict the need for renal replacement therapy in severe acute kidney injury: an ancillary analysis of a multicenter randomized controlled trial
Authors: CHAIBI Khalil , PICOD Adrien , BOUBAYA Marouane , Tubiana Sarah , JULLIEN Vincent , MAGREAULT Sophie , Placier Sandrine , Mallet Jérémie , LOUIS Guillaume , Lefevre Laurent Martin , TITECA-BEAUPORT Dimitri , COMBE Béatrice LA , BESSET Sébastien , Badie Julio , Chevrel Guillaume , Chudeau Nicolas , Barbar Saber , Vinsonneau Christophe , Forel Jean-Marie , Thevenin Didier , LACAVE Guillaume , NSEIR Saad , Oziel Johanna , Mayaux Julien , Klouche Kada , Reignier Jean , RICARD Jean-Damien , Quenot Jean-Pierre , Mebazaa Alexandre , Azibani Feriel , Dreyfuss Didier , Gaudry Stephane 
Published: August 2024

Abstract

Introduction
Predicting the need for renal replacement therapy (RRT) in acute kidney injury (AKI) remains challenging. The utility of biomarkers was explored during previous studies which were biased as RRT indications relied on clinician opinion rather than evidence. Those studies preceded trials that clarified RRT initiation criteria. We aimed to assess biomarkers in predicting criteria for RRT initiation in severe AKI patients.
Material and methods
This is an ancillary study of the AKIKI2 trial. Patients with severe AKI (stage 3) receiving invasive mechanical ventilation and/or vasopressors were included. Blood and urine samples were collected within 12 hours after the occurrence of severe AKI. The primary endpoint was the onset of rigorous criteria for RRT initiation within 72 hours after severe AKI. We analyzed routine serum biomarkers (pH, serum potassium, serum creatinine) and novel urinary and serum biomarkers (CCL14, KIM1, nicotinamide and its metabolites, cDPP3, plasma proenkephalin A 119–159).
Results
Among the 256 patients, 101 (39%) met at least one criterion for RRT initiation or died within 72 hours. No biomarker demonstrated satisfactory predictive performance for the primary endpoint. Urinary CCL14 showed potential interest in toxic-induced AKI (AUC 0.74 [0.57–0.90]). No novel biomarker was significantly associated with the occurrence of MAKE60. In multivariate analysis, ‘SAPSIII’ and ‘Serum potassium level at D0’ were significantly associated with the occurrence of MAKE60.
Conclusion
Neither routine nor novel biomarkers demonstrated conclusive predictive accuracy for the need for RRT in severe AKI patients. Given evidence-based criteria for initiating RRT, the tested biomarkers may not effectively guide RRT initiation.
Tesla Autopilot Through Constructions: Investigating the Effect of On-Road Partially-Automated Driving through Construction Zones
Authors: Biondi Francesco , Sahoo Praneet , Jajo Noor 
Published: August 2024

Abstract

Partially-automated driving systems are designed to control the vehicle’s speed and acceleration without input from the human driver on the condition that the driver maintains alertness. These systems are promised to make driving safer especially when driving in road sections exhibiting a higher risk of collisions like construction zones. Despite this, little knowledge is available on how these systems are used in these accident-prone areas and the effect they may have on drivers’ workload and glance allocation. This study aims to fill this gap by having participants drive a Tesla vehicle in Autopilot and manual mode through three road sections: pre-construction, construction, and post-construction. Results show no differences in cognitive workload by driving mode or construction zone. An increase in glances directed away from the forward roadway toward the vehicle’s touchscreen was observed during partially-automated driving in the pre-construction zone, a pattern that, notably, continued on when driving throughout the construction zone. These findings adds to the literature on the human factors of partial automation. More importantly, because drivers failed to increase the amount of time looking at the forward roadway when entering the construction zone, they show the perniciousness of partially-automated driving and the detrimental effect these systems may have on safety.
Assessing Buprenorphine Treatment Utilization and SAMHSA DATA Waiver Provider Distribution in 2021: A Real-World Analysis in California
Authors: Wang Yun , Hu Tao , Roosan Moom , Chang Chih-Hung , Heshmatipour Matthew , Guo Jeff Jianfei , Miotto Karen A. 
Published: August 2024

Abstract

Qualified clinicians must obtain a practitioner waiver (i.e., “DATA-waiver”) to offer buprenorphine, a medication for opioid use disorder (OUD). However, many counties experience fewer buprenorphine prescriptions due to factors such as “DATA-waiver” providers underutilizing their buprenorphine prescribing ability. Our study aimed to compare the availability of active buprenorphine-prescribing clinicians in California to the Substance Abuse and Mental Health Services Administration (SAMSHA)-listed DATA waived prescribers under each 5-digit ZIP Code. This study utilized the buprenorphine prescription record data in 2021 from California’s Controlled Substance Utilization Review and Evaluation System (CURES). The list of the locators for all X-waiver clinicians was obtained from the SAMHSA webpage. Among 1,600 ZIP Codes where patients resided, 62.1% housed DATA-waived physicians, and 57.8% had active buprenorphine-prescribing clinicians. A disproportional distribution between buprenorphine-prescribing clinicians and DATA-waived physicians was evident. Among physicians listed in the SAMHSA roster, not all were actively prescribing buprenorphine. Significant disparities in access to active prescribers and DATA waiver prescribers persist between rural and urban areas in California. Addressing these issues requires resource allocation and inter-professional collaboration. The 2022 Omnibus bill's policy changes hold promise, necessitating further effort into OUD-based policy changes.
Clinical Application of Hip Joint Anatomical CT Digital Measurement and Correlation Analysis
Authors: Wu Chao , Su Ning , Liu XiaoLin , Chen GuoQiang , Li Wei , Bai XiuXiong , Liu HaiBin , Ou WenJing 
Published: August 2024

Abstract

Purpose
This study employed CT multi-planar reconstruction and cinematic rendering techniques to measure anatomical parameters of the hip joint. It aimed to compare the differences in hip joint anatomical parameters among adults of different age groups and analyze their correlations with baseline data such as height, weight, and BMI.
Methods
A total of 156 cases, comprising 312 hips, were included and divided into six groups based on 10-year age intervals. The following parameters of both hip joints were measured: acetabular anteversion angle, center-edge angle, acetabular coverage rate, acetabular depth, neck shaft angle, femoral offset distance, center-edge angle, anterior and posterior acetabular sector angles, and acetabular anteversion angle. Data were analysed and processed using SPSS statistical software.
Results
When comparing the different age groups, the values of Acetabular coverage, Acetabular depth and other hip parameters were lower in the young adult group than in the older group, but the Sharp angle was greater than in the older group. There was no statistically significant correlation between the innovative and traditional measures of Acetabular coverage and Acetabular depth (r = 0.76, 0.95, P < 0.01). Sharp angle also showed correlation with body mass index and other hip parameter indices.
Conclusion
There are significant differences in hip joint anatomical parameters among different genders and age groups, and significant correlations exist between various anatomical parameters. There is a close relationship between some anatomical parameters and the mechanism of hip arthroplasty, hip dislocation and femoroacetabular impingement, which plays a crucial role in clinical management.