bluuebunny/crossref_metadata_2025_split huggingface dataset:
A bidirectional Mendelian randomization study negates causal effects of Parkinson, Alzheimer on Basal Cell Carcinoma
Authors: Cai Xiaoxuan , Li Sheng , Wang Yuqian , Qiao Jianjun , Fang Hong 
Published: January 2023

Abstract
Basal cell carcinoma is the most common malignant disease of the skin. The relationship between basal cell carcinoma and neurodegenerative diseases including Parkinson’s disease and Alzheimer’s disease has been inconsistent. To determine the causal relationship, a bidirectional two sample mendelian randomization method was used to investigate causal effects. Single-nucleotide polymorphisms (SNPs) at genome-wide significance (P < 5 × 10 − 8) were identified from genome-wide association studies and a European basal cell carcinoma genome-wide association studies (GWAS) including 17,416 cases and 375,455 controls was selected. Inverse-variance weighted (IVW) method was used as the main analyses, with sensitivity analyses using weighted median and MR-PRESSO. As a result, no significance was found in the association between PKD and BCC (IVW, OR = 1.02, 95%CI[0.98–1.06], P = 0.38), neither was in AD and BCC(IVW, OR = 1.01, 95%CI[0.97–1.05], P = 0.77). Reversal estimation found no causal association between BCC and PKD(IVW-MRE, OR = 0.98, 95%CI[0.92–1.04], P = 0.45) or AD(IVW, OR = 0.98, 95%CI[0.95-1.00], P = 0.10). The results remain consistent after outlier correction and sensitivity analyses. In conclusion, PKD and AD do not necessarily reduce the risk of BCC, neither does BCC necessarily reduce the risk of PKD and AD.
Low-carbon design based on conceptual design methods for mechanical and electrical products
Authors: Gao Guohua , Yang Xue , Zhang Zihua , Zhu Zhenjiang 
Published: January 2023

Abstract
This paper presents a conceptual product design method that considers the carbon emission factors of mechanical and electrical products, with the purpose of considering low carbon issues before designing products. Based on a comprehensive analysis of conventional product design procedures, the study extracts design information related to greenhouse gas emissions, itemizes and quantifies the information, and ultimately uncovers the relationship among carbon emissions, function and cost of newly designed products. This paper explains the proposed concepts of carbon efficiency and carbon factor, and combined them with the product design process to present a low-carbon design process of mechanical and electrical products. Furthermore, this paper presents a low-carbon design method of mechanical and electrical products, drawing on the product family design idea, with the GHG efficiency and cost constrained. The potential value of the method is demonstrated in a case study of a tomato picking robot.
Cost Benefit Analysis Origin and Applicability of Its Recent Advances: a Critical Review
Authors: Odek Robert , Oluoch Josephat Oluoch 
Published: January 2023

Abstract
Purpose: This study reviewed a number of empirical pieces of literature on cost-benefit analysis origin, advancements in its methods, and their applicability.
Methodology: This study applied a systematic review by relying on previous publications (20 publications were fully reviewed) in line with this study topic. The collected data was analyzed with the application of narrative synthesis.
Findings: There are mixed ideas on the origin of cost benefit analysis. This study concludes that cost benefit analysis was first practiced in China in the 11th Century at the palace construction site. It then spread to the Bavarian Army. The French engineers embraced this technique in the execution of public works in 1708 before the American National Resource Committee incorporated it. Moreover, cost benefit analysis was authoritatively documented in the United States of America in the green book by a sub-committee on benefits and costs where principles and procedures for determining costs and benefits were clarified for reference. Other countries hence embraced Cost benefit analysis after its documentation in the United States. Advances in cost benefit analysis include; willingness to pay which exhibits the definite intention of clients in regard to how they value what they intend to purchase. That is, it expresses the degree the clients are ready to consume a particular product. On the other hand conjoint analysis aids in determining willingness to pay, such that it offers a client an array of characteristics of a product which enables the client to settle on the most preferred product feature. It is shown that designing a conjoint technique is complex. Conjoint is tested at individual level and the model utilized in collecting data is uniformly applicable assuming that all respondents have a similar modeled preference that does not match the real-life situation. Accordingly, information on product attributes could alternatively be obtained via a questionnaire or interview schedule in determining customers’ preferences and not necessarily through the use of conjoint.
Implications: This review criticizes conjoint analysis as CBA method on the basis of its complexity and thus other data collection methods are offered like questionnaires and interview schedules. The study also confirms that advances in cost benefit analysis can be applied in all sectors of the economy since they have been empirically tested.
Value of the Study: It contributes to the comprehension of the origin of cost-benefit analysis, the advancement in cost-benefit methods, and critique on the methods of cost benefit analysis.
3L, three-Lactobacilli on recovering of microbiome and immune-damage by cyclophosphamide chemotherapy —A pilot experiment—
Authors: Yue Shousong , Zhang Zhenzhong , Bian Fei , Zhang Yan , Chen Gao , Zhu Youfeng , Li Jun , Picimbon Jean-François 
Published: January 2023

Abstract

PurposeWe examined the impact of using a probiotic containing three differentLactobacilli(3L) on the gut microbiome of rats following cyclophosphamide (CTX) treatment. CTX corresponded to chemotherapy which is used for human cancer treatment and known to have adversive effects on the immune system.MethodsWe conducted our experiment with ten rats in five different experimental groups which included control, CTX treated, and then low, medium, and high probiotic treatment with CTX treatment. Of these ten rats in each group, we sequenced the stool of three of them using both ITS and 16S sequencing. We then went on to examine the taxonomic composition of these samples to determine whether probiotic treatment helped the rat’s microbiome return to similar structure as the control rats.ResultsWe used Illumina MiSeq sequencing to generate sequencing data from microbial genomic DNA libraries, which is useful for testing the effects of 3L on bacteria and fungi. Microbiome analysis, phylogenetic and classification reports, and community data have all backed up the experiments and findings that 3L had a significant positive impact on the microbiome. Furthermore, the effect on specific metabolic pathways aids in deriving the study’s conclusion (use of 3L in chemotherapy) to the mode of action, mechanistically by correcting microbiota composition and enhancing specific gut metabolic functions.ConclusionsThrough experimental results using anin vivomodel, we suggested the role of novel natural probiotics 3L, 3 Lactobacilli in the establishment of a strong and sustainable beneficial healthy gut flora, after CTX chemotherapy. We suggested some new adjuvants to chemotherapy as drugs +lactobacillustreament using the rat CTX model (immunosuppression caused by cyclophosphamide). Furthermore, in numerous studies that reported the use of probiotics involvingLactobacillusin post-chemo or post-surgical procedures, we proposed a new probiotic formulation (L.acidophilus+L. casei+L.plantarum) to be further studied and explored in the prevention of health condition loss by alteration of the general immune system.
Mitigation of smart black hole attacks using universal sink detection method in graph theory
Authors: MEKKAOUI Kheireddine , TEGGAR Hamza 
Published: January 2023

Abstract
Nowadays, network security has become a very important aspect due to the increasing number of connected things and the multiple threats that become more and more intelligent. Mobile Ad hoc networks (MANET), known to be non-infrastructure and self-configured peer networks, are subject to multiple types of attacks. For this reason, it is essential to implement an Intrusion Detection System that realizes fast attack detection to alert users by any malicious activity taking place on the network. Black hole is one of the most serious threats in MANETs, witch is the origin of Denial of service attack. This type of threats has been widely studied and many solutions were proposed. Unfortunately these solutions has become inefficient against the new generation of black holes, known also as smart black holes, witch can deceive most of these solutions. To overcome smart black holes, we proposed an Intrusion Detection System based on the early detecting and isolating malicious nodes by exploiting local information shared by neighbors and using universal sink detection method in graph theory. We proved that smart black holes can defeat the sequence number threshold-based detection strategy by using leastsquare method. Simulations in NS2, showed the efficiency of the proposed approach, which can quickly detect and isolate smart black holes, improve the Packet delivery ratio (PDR) and throughput by an average of 97% and 90%, respectively, thus preserving the network performances.
Nutrient Dynamics and Sustainability of Short Rotation Eucalyptus camaldulensis Plantations in Southern India
Authors: Mathew Roby , D.S. Guru Murthy , Varghese Mohan 
Published: January 2023

Abstract
Though awareness of fertilizer application has increased over time, low nutrient use efficiency is still a major limiting factor for eucalyptus plantations in India. A study was carried out to understand the nutrient dynamics under different soil fertility conditions which was created by omission of macro nutrients (alone or in combination) and its comparison with balanced nutrient application (NPK). This study reveals two phases of nutrient accumulation. First, juvenile phase which was characterised by an increase in nutrient uptake till canopy closure followed by a phase when the nutrient demand declined. The nutrient partitioning in different tree components changed with age. The rate of accumulation of N and K decreased in order of Leaves > Bark >Branches > Wood > Underground parts. For P, Ca & Mg the rate of accumulation decreased in the order - Bark > Leaves >Branch>Underground parts > Wood. Balanced application of nutrients produced 44 per cent higher wood yield than trees grown on indigenous soil nutrient (-NPK) supply. This study conceptually and quantitatively compares the wide range of soil fertility regimes and explore the limitation of nutrients on plant and plant-soil-level. It explains the importance of efficient nutrient management for sustainability of plantations and ways to maximizing yield and improving soil nutrient balances at harvest.
Genome-wide Identification and Functional Analysis of Dysregulated Alternative Splicing Profiles in Sepsis
Authors: Tuerdi Baihetinisha , Abuduaini Buzukela , Kang Shaotao , Jiao jinliang , Madeniyati Wolazihan , Tuerdimaimaiti Dilixiati , Xu Sicheng 
Published: January 2023

Abstract
Background: An increasing body of evidence now shows that the long-term mortality of patients with sepsis are associated with various sepsis-related immune cell defects. Alternative splicing (AS), as a sepsis-related immune cell defect, is considered as a potential immunomodulatory therapy target to improve patient outcomes. However, our understanding of the role AS plays in sepsis is currently insufficient.
Aim: This study investigated possible associations between AS and the gene regulatory networks affecting immune cells. We also investigated apoptosis and AS functionality in sepsis pathophysiology.
Methods: In this study, we assessed publicly available mRNA-seq data that was obtained from the NCBI GEO dataset (GSE154918), which included a healthy group (HLTY), a mild infection group (INF1), asepsis group (Seps), and a septic shock group (Shock). A total of 79 samples (excluding significant outliers) were identified by a poly-A capture method to generate RNA-seq data. The variable splicing events and highly correlated RNA binding protein (RBP) genes in each group were then systematically analyzed.
Results: For the first time, we used systematic RNA-seq analysis of sepsis-related AS and identified 1505 variable AS events that differed significantly（p <= 0.01) across the four groups. In the sepsis group, the genes related to significant AS events, such as, SHISA5 and IFI27, were mostly enriched in the cell apoptosis pathway. Furthermore, we identified differential splicing patterns within each of the four groups. Significant differences in the expression of RNA Binding Protein（RBP） genes were observed between the control group and the sepsis group. RBP gene expression was highly correlated with variant splicing events in sepsis, as determined by co-expression analysis; the expression of NOP14 and ILF3 RBPs were significant reduced in sepsis compared to the healthy group. Finally, we constructed an RBP-AS functional network.
Conclusion: Analysis indicated that the RBP-AS functional network serves as a critical post-transcriptional mechanism that regulates the development of sepsis. AS dysregulation is associated with alterations in the regulatory gene expression network that is involved in sepsis. Therefore, the RBP-AS expression network could be useful in refining biomarker predictions in the development of new therapeutic targets for the pathogenesis of sepsis.
A lightweight convolutional neural network to reconstruct deformation in BOS recordings
Authors: Mucignat Claudio , Manickathan Lento , Shah Jiggar , Rösgen Thomas , Lunati Ivan 
Published: January 2023

Abstract
We introduce a Convolutional Neural Network (CNN) that is specificallydesigned and trained to post-process recordings obtained by BackgroundOriented Schlieren (BOS), a popular technique to visualize compressibleand convective flows. To reconstruct BOS image deformation, we deviseda lightweight network (LIMA) that has comparatively fewer parameters totrain than the CNNs that have been previously proposed for optical flow.To train LIMA, we introduce a novel strategy based on the generation of synthetic images from random-irrotational deformation fields, which areintended to mimic those provided by real BOS recordings. This allows us to generate a large number of training examples at minimal compu-tational cost. To assess the accuracy of the reconstructed displacements,we consider test cases consisting of synthetic images with sinusoidal dis-placement as well as images obtained in the experimental studies of a hotplume in air and a flow past and inside a heated hollow hemisphere. By comparing the reconstructed deformation fields using the LIMA or conven-tional post-processing techniques used in Direct Image Correlation (dic)or conventional image cross-correlation, we show that LIMA is more accu-rate and robust in the synthetic test case. When applied to experimentalBOS recordings, all methods provide similar and consistent deformation fields. As LIMA is capable of achieving a comparable or better accuracyat a fraction of the computational costs, it represents a valuable alternative to conventional post-processing techniques for BOS experiments.
ROS-Responsive Sequential Release Systems with Excellent Biofilm Permeability for Enhanced Antibacterial and Regeneration-promoting Therapy in Periodontitis
Authors: Zeng Bairui , Mu Zhixiang , Shen Tianxi , Chen Yuanqi , Jin Ting , Li Lingjie , Huang Chen , Wang Yi , Lei Kezheng , Lu Hongyang , Jiang Zhijie , Cai Xiaojun , Hu Rongdang , Deng Hui 
Published: January 2023

Abstract
Periodontitis is the sixth most common chronic inflammatory disease caused by plaque biofilms and closely related to many systemic diseases. In particular, the problems of deep lesion location and sequential treatment of antibacterial and pro-regenerative abilities need to be addressed. We created a novel ROS responsive system (CHX@PCL-PLG) for efficient therapy of refractory periodontitis based on a “three-birds-with-one-stone” strategy, which integrates the biofilm penetration, nitric oxide (NO) sterilization, and NO-mediated pro-angiogenic property into one system. The above system was fabricated by self-assembling vesicles formed by amphiphilic polymers containing poly-ε-caprolactone and guanidinated-poly-ε-lysine as carriers (PCL-PLG) loaded with chlorhexidine (CHX). CHX@PCL-PLG can efficiently penetrate into biofilm under the action of abundant guanidine groups on the vesicle’s surface. Subsequently, the guanidine groups of vesicles respond to the high level of ROS within the biofilm by releasing NO and CHX in a targeted manner to play a synergistic antibacterial and biofilm scavenging function. More importantly, following effective elimination all bacteria from the periodontal pockets, the residual guanidine groups could further produce trace amounts of NO, which promoted angiogenesis and epithelialization of the wound tissue to significantly facilitating wound healing. In conclusion, this study demonstrates that CHX@PCL-PLG makes full use of the characteristics of guanidine groups to significantly disrupt biofilms and promote tissue regeneration for the effective treatment of periodontitis as well as various biofilm-related diseases.
Pre and Post COVID-19: Qualifications of Medical Students who Matched into Dermatology
Authors: Jacobs Jennifer , Diamond Carrie , Rundle Chandler , Presley Colby L. , Stamey Christopher 
Published: January 2023

Abstract
With a growing number of applicants for dermatologic residencies, M.D. students interested in the specialty are expanding their curriculum vitae, specifically through their research involvement, to be considered competitive for the limited number of spots. However, very little is known about the impact of the COVID-19 pandemic on student participation in research and publication production. In this study, we analyzed data on M.D. students applying into dermatology using the National Resident Matching Program (NRMP) published data for the years of 2016, 2018, 2020, and 2022. We analyzed differences between applicants before and during the COVID-19 pandemic of those who matched and those who did not, in terms of number of research experiences and publications completed. Despite the pandemic, all applicants—regardless of their success in matching—increased the amount of research experiences they completed and the number of publications they obtained prior to their application. Higher research competitiveness, as identified through this study, increases the already present disparities that exist within matching into dermatology and suggests that students will have to forego career exploration and creating a solid foundation of pre-clinical knowledge in the name of increased research. As such, the application process for dermatologic residencies will become less holistic and more biased.
Robustness evaluation of Evolutionary-based complex detection algorithms for protein interaction networks with negative control
Authors: Abbas Mustafa , Attea Bara'a , Broneske David , Saake Gunter 
Published: January 2023

Abstract
Background: One of the most significant areas of current computational biology research is the complex detection in protein-protein interaction (PPI) networks due to their critical importance in understanding life at the cellular level, predicting the functions of as-yet-uncharacterized proteins, and diagnosing diseases. Existing state-of-the-art methods, mainly, evolutionary algorithms (EA), partition PPI networks into complexes either based on the graph properties of PPI networks or on their biological semantics. Unfortunately, up to now little interest has been paid to investigate the robustness of these state-of-the-art EAs in unraveling PPI networks with noisy or missing interactions.
Results: In this paper, we adopted EAs to examine the robustness of three single objective models and two multi-objective models that are used to define the complex detection problem. Two well-known Saccharomyces cerevisiae (yeast) PPI networks and two benchmark sets of complexes were used to investigate the robustness of these EA-based complex detection algorithms. Furthermore, several artificial networks are generated by perturbing the original PPI network with different percentage of noise.
Conclusions: Experimental results show that the multi-objective model achieves a higher level of prediction accuracy than other models. We encourage to extend this work to include biological information (i.e., a gene ontology) and design the objective function and heuristic operator based on these biological data for detecting protein complexes.
Impacts of Mg doping on the Structural Properties and Degradation Mechanisms of a Li and Mn Rich Layered Oxide Cathode for Lithium-ion Batteries
Authors: Kaewmala Songyoot , Kamma Natthapong , Buakeaw Sunisa , Limphirat Wanwisa , Nash Jeffrey , Srilom Sutham , Limthongkul Pimpa , Meethong Nonglak 
Published: January 2023

Abstract
The Li- and Mn-rich layered oxide cathode material class is a promising cathode material type for high energy density lithium-ion batteries. However, this cathode material type suffers from layer to spinel structural transition during electrochemical cycling, resulting in energy density losses during repeated cycling. Thus, improving structural stability is an essential key for developing this cathode material family. Elemental doping is a useful strategy to improve the structural properties of cathode materials. This work examines the influences of Mg doping on the structural characteristics and degradation mechanisms of a Li1.2Mn0.4Co0.4O2 cathode material. The results reveal that the prepared cathode materials are a composite material, exhibiting phase separation of the Li2MnO3 and LiCoO2 components. Li2MnO3 and LiCoO2 domain sizes decreased as Mg content increased, altering the electrochemical mechanisms of the cathode materials. Moreover, Mg doping can retard phase transition, resulting in reduced structural degradation. Li1.2Mn0.36Mg0.04Co0.4O2 with optimal Mg doping demonstrated improved electrochemical performance. The current work provides deeper understanding about the roles of Mg doping on the structural characteristics and degradation mechanisms of Li-and Mn-rich layered oxide cathode materials, which is an insightful guideline for the future development of high energy density cathode material for lithium-ion batteries.