bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Reliable Routing Algorithm Based on Path Satisfaction in Energy Internet
Authors: Wei Xiangqian , Hu Haifeng , Yu Peng , Shi Lei , Liu Baoju , Sun Zejun 
Published: June 2024

Abstract

Energy Internet (EI) is the trend of smart grids evolution. Since there are large number of services with different performance requirements in the EI. To ensure its smooth operation, it is necessary to design reliable routing algorithms. However, the existing routing strategies in the IP layer place more emphasis on algorithm robustness but neglect resource use in the optical layer as well as characteristic of EI network structure. Actually, resources status of the optical layer affects the availability of the routing algorithm. In view of this, we propose a cross-layer reliable service routing approach, which comprehensively service characteristics in the application layer, link satisfaction and spectrum resources status in the optical layer. The final objective is to satisfy service QoS requirements and ensure services evenly distributed in the network. To reduce the computational complexity, a heuristic algorithm is designed. Extensive experiments are carried out, and the simulation results reflect that the proposed algorithm is superior to the existing algorithms according to the service blocking ratio(SBR) and service distribution fairness index.
Effects of glucocorticoid treatment and survival duration on symptom scores and biomarkers
Authors: Sackmann Valerie , Fransson Karin , Jakobsson Maria , Karlsson Marit , Nilsberth Camilla 
Published: June 2024

Abstract

Patients with cancer experience several severe symptoms that can affect quality of life. The present study investigated how symptoms evolve during the disease and how biomarkers in the blood change during the course of the disease. The effects of glucocorticoid treatment on symptoms and biomarkers were also studied. Forty-eight patients who died within 3 months of inclusion were compared to 62 patients who survived more than 3 months after inclusion. In addition, analysis was performed by comparing the 61 patients who received glucocorticoid treatment to the 49 patients who did not. Symptom scores were assessed by the EORTC QLQ-C15-PAL questionnaire, and CRP, procalcitonin, LDH, albumin and cytokines were measured in the blood. Patients at the end-stage of the disease scored higher on the physical functioning, appetite and dyspnea scores. CRP, procalcitonin, LDH and the cytokines IL-1RA, IL-6, IL-7, IL-8, IL-10, IL-17A, IP10 and TNF-RII were increased, whereas albumin was significantly decreased. The glucocorticoid-treated group displayed higher (worse) symptom scores for physical functioning. In addition, the levels of several cytokines (IL-1RA, IL-10, and TNF-RII) and LDH were significantly greater in the glucocorticoid-treated group. Patients at the end stage of the disease experience more debilitating symptoms, which can be explained by greater inflammatory activity. Patients receiving glucocorticoid treatment also reported higher symptom scores associated with higher levels of biomarkers in the blood. Further studies are required to clarify whether these results are because patients on glucocorticoid treatment are more affected by the tumor or if there may be another explanation.
Identification key genes involved in lignin and flavonoid accumulation during Tilia tuan seed maturation
Authors: Liu Lei , Long Cui , Hao Xuri , Zhang Rui , Li Chenqi , Song Yuepeng 
Published: June 2024

Abstract

Tilia tuan Szyszyl. (T. tuan) is a timber tree species with important ecological and commercial value. However, its highly lignified pericarp results in a low seed germination rate and a long dormancy period. In addition, it is unknown whether there is an interaction between the biosynthesis of flavonoids and lignin as products of the phenylpropanoid pathway during seed development. To explore the molecular regulatory mechanism of lignin and flavonoid biosynthesis, T. tuan seeds were harvested at five stages (30, 60, 90, 120, and 150 days after pollination) for lignin and flavonoid analyses. The results showed that lignin accumulated rapidly in the early and middle stages (S1, S3, and S4), and rapid accumulation of flavonoids during the early and late stages (S1 and S5). High-throughput RNA sequencing analysis of developing seeds identified 50,553 transcripts., including 223 phenylpropanoid biosynthetic pathway genes involved in lignin accumulation grouped into three clusters, and 106 flavonoid biosynthetic pathway genes (FBPGs) grouped into two clusters. Subsequent WGCNA and time-ordered gene co-expression network (TO-GCN) analysis revealed that 24 TFs (e.g., TtARF2and TtWRKY15) were involved in lignin and flavonoid biosynthesis regulation. The transcriptome data were validated by qRT-PCR to analyze the expression profiles of key enzyme-coding genes. This study revealed that there existed a competitive relationship between the flavonoid biosynthesis pathway and the lignin biosynthesis pathway, both of which are downstream pathways of phenylpropane that provide a foundation for the further exploration of molecular mechanisms underlying lignin and flavonoid accumulation in T. tuanseeds.
Accuracy of RENOVO Predictions on Genetic Variants Reclassified Over Time
Authors: Bonetti Emanuele , Tini Giulia , Mazzarella Luca 
Published: June 2024

Abstract

Background
Interpreting the clinical consequences of genetic variants is the central problem in modern clinical genomics, for both hereditary diseases and oncology. However, clinical validation lags behind the pace of discovery, leading to distressing uncertainty for patients, physicians and researchers. This “interpretation gap” changes over time as evidence accumulates, and variants initially deemed of uncertain (VUS) significance may be subsequently reclassified in pathogenic/benign. We previously developed RENOVO, a random forest-based tool able to predict variant pathogenicity based on publicly available information, and tested on variants that have changed their classification status over time. Here, we comprehensively evaluated the accuracy of RENOVO predictions on variants that have been reclassified over the last four years.
Methods
we retrieved 16 retrospective instances of the ClinVar database, every 3 months since March 2020 to March 2024, and analyzed time trends of variant classifications. We identified variants that changed their status over time and compared RENOVO predictions generated in 2020 with the actual reclassifications.
Results
VUS have become the dominant class in ClinVar (44.97% vs 9.75% (likely) pathogenic and 40,33% (likely) benign). The rate of VUS/CIP reclassification is linear and slow compared to the rate of VUS/CIP reporting, exponential and currently ~ 30x faster, creating a growing divide between what can be sequenced vs what can be interpreted. Out of 10,196 VUS/CIP variants in January 2020 that have undergone a clinically meaningful reclassification to march 2024, RENOVO correctly classified 82.6% in 2020. In addition, RENOVO correctly identified the majority of the few variants that switched clinically meaningful classes (e.g., from benign to pathogenic and vice versa). We highlight variant classes and clinically relevant genes for which RENOVO provides particularly accurate estimates. In particularly, genes characterized by dominant prevalence of high- or low-impact mutations (e.g., POLE, NOTCH1, FANCM etc.). Suboptimal RENOVO predictions mostly concern genes validated through dedicated consortia (e.g., BRCA1/2), in which RENOVO would anyway have a limited impact.
Conclusions
Time trend analysis demonstrates that the current model of variant interpretation cannot keep up with variant discovery. Machine learning-based tools like RENOVO confirm high accuracy that can aid in clinical practice and research.
Early-life tobacco exposure is causally implicated in aberrant RAG-mediated recombination in childhood acute lymphoblastic leukemia
Authors: Liu Tanxin , Xu Keren , Pardeshi Anmol , Myint Swe Swe , Kang Alice , Morimoto Libby , Lieber Michael , Wiemels Joseph , Kogan Scott , Metayer Catherine , de Smith Adam J. 
Published: June 2024

Abstract

Acute lymphoblastic leukemia (ALL) is the most common cancer in children, yet few environmental risk factors have been identified. We previously found an association between early-life tobacco smoke exposure and frequency of somatic deletions of 8 leukemia driver genes among childhood ALL patients in the California Childhood Leukemia Study. To expand analysis genome-wide and examine potential mechanisms, we conducted tumor whole-genome sequencing in 35 ALL patients, including 18 with high prenatal tobacco exposure and 17 with low exposure as determined by established epigenetic biomarkers. High tobacco exposure patients had significantly more structural variants (P < .001) and deletions (P = .001) genome-wide than low exposure patients. Investigation of off-target RAG recombination revealed that 41% of deletions in the high tobacco exposure patients were putatively RAG-mediated (full RAG motif identified at one or both breakpoints) compared with only 21% in the low exposure group (P = .001). In a multilevel model, deletions in high tobacco exposure patients were 2.44-fold (95% CI:1.13–5.38) more likely to be putatively RAG-mediated than deletions in low exposure patients. No point mutational signatures were associated with prenatal tobacco exposure. Our findings suggest that early-life tobacco smoke exposure may promote leukemogenesis by driving development of somatic deletions in pre-leukemic lymphocytes via off-target RAG recombination.
Elicitation of callus cultures of the medicinally important plant Embelia ribes Burm f. using biotic and abiotic elicitors for enhanced production of embelin
Authors: Kamble Vidya V. , Rather Shabir A. , Razaq Mohsin , Phukela Banisha , Gaikwad Nikhil B. 
Published: June 2024

Abstract

The berries of Embelia ribes Burm f. are a rich source of embelin, a compound known for its anthelmintic, antidiabetic, and anticancer activity. Due to over-exploitation, the natural habitat of Embelia ribes is now considered vulnerable. Traditional propagation methods are insufficient to meet current demands, necessitating alternative production methods. This study was designed to explore in vitro culture as a viable alternative for the production of embelin. While numerous studies have focused on extracting embelin from callus cultures, there is a lack of research on enhancing the embelin content in both organogenic and embryogenic callus cultures. The objective of this study was to enhance embelin production in callus cultures by using both biotic and abiotic elicitors. Additionally, efforts were made to optimize rapid in vitro shoot induction. We achieved the best response rate for the induction of organogenic and embryogenic calli using MS basal medium supplemented with TDZ. Among the various elicitors tested, chitosan at 200 mg/L was the most effective, yielding the highest embelin content, at 6.44% in embryogenic calli and 5.72% in organogenic calli. Subsequent subculturing enabled successful differentiation of callus cultures into shoot buds on MS medium supplemented with a combination of BAP (6-benzylaminopurine) and IAA (indole-3-acetic acid) at concentrations of 2.0 mg/l and 0.1 mg/l, respectively. An effective protocol has been developed for obtaining the highest embelin content from embryogenic and organogenic callus cultures, coupled with a high frequency of shoot multiplication. The protocol can be instrumental for large-scale embelin production, ex-situ conservation, sustainable utilization, and industrial applications.
Unveiling Optimal Molecular Features for hERG Insights with Automatic Machine Learning
Authors: Xu Congying , Xu Youjun , Hu Ziang , Pei Jianfeng 
Published: June 2024

Abstract

We have developed MaxQsaring, a novel universal framework integrating molecular descriptors, fingerprints, and deep-learning pretrained representations, to predict the properties of compounds. Applied to a case study of hERG (human Ether-à-go-go-Related Gene) blockage prediction, MaxQsaring achieved state-of-the-art performance on two external challenging datasets through automatic optimal feature combinations, and successfully identified top 10 important interpretable features that could be used to model a high-accuracy decision tree. The models’ predictions could well align with empirical hERG optimization strategies, demonstrating their interpretability for practical utilities. Deep-learning-pretrained representations can moderately improve the performance of the models, but contribute less to improve models’ generalizability for compounds with novel scaffolds. MaxQsaring excelled in the Therapeutics Data Commons benchmark, ranking first in 19 out of 22 tasks, showcasing its potential for universal accurate compound property prediction to facilitate high success rate of early drug discovery, which is still a formidable challenge.
New Bounded Unit Weibull Model: Applications with Quantile Regression
Authors: Sapkota Laxmi Prasad , Bam Nirajan , Kumar Vijay 
Published: June 2024

Abstract

In practical scenarios, data measurements like ratios and proportions often fall within the 0 to 1 range. Analyzing such bounded data introduces unique modeling challenges, prompting statisticians to explore new distributions that can effectively handle this context. Although beta and Kumaraswamy distributions, along with their related regression models, have gained popularity for examining the relationship between bounded response variables and covariates, several alternative models have shown superior performance compared to these two. However, there is still no agreement on the most effective alternative models. Consequently, this paper introduces a novel bounded probability distribution derived from transforming the Weibull distribution. Our investigation has revealed several interesting properties, including various moments and their generating function, entropies, quantile function, and a linear form of the proposed model. Additionally, we have developed the sequential probability ratio test (SPRT) for the proposed model. The maximum likelihood estimation method was employed to estimate the model parameters. A Monte Carlo simulation was conducted to evaluate the performance of parameter estimation for the model. Finally, we formulated a quantile regression model and applied it to data sets related to risk assessment and educational attainment, demonstrating its superior performance over alternative regression models. These results highlight the importance of our contributions to enhancing the statistical toolkit for analyzing bounded variables across different scientific fields.
Can ChatGPT, Bing, and Bard save lives? Evaluation of correctness and reliability of chatbots in teaching bystanders to help victims
Authors: Aqavil-Jahromi Saeed , Eftekhari Mohammad , Mirfazaelian Hadi , Akbari Hamideh , Aligholi-Zahraie Mehrnoosh 
Published: June 2024

Abstract

Background: Timely recognition and initiation of basic life support (BLS) before emergency medical services (EMS) arrives significantly improves survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sources, chatbots powered by generative artificial intelligence (AI) are emerging as potential tools for providing immediate health-related guidance. This study investigates the reliability of AI chatbots, specifically GPT-3.5, GPT-4, Bard, and Bing, in responding to BLS scenarios. Methods: A cross-sectional study was conducted using six scenarios adapted from the BLS Objective Structured Clinical Examination (OSCE) by United Medical Education. These scenarios encompassed adult, pediatric, and infant emergencies and were presented to each chatbot on two occasions, one week apart. Responses were evaluated by a board-certified emergency medicine professor from Tehran University of Medical Sciences, using a checklist based on BLS-OSCE standards. Correctness was assessed, and reliability was measured using Cohen's kappa coefficient. Results: GPT4 demonstrated the highest correctness in adult scenarios (85% correct responses), while Bard showed 60% correctness. GPT3.5 and Bing performed poorly across all scenarios. Bard had a correctness rate of 52.17% in pediatric scenarios, but all chatbots scored below 44% in infant scenarios. Cohen's kappa indicated substantial reliability for GPT-4 (k=0.649) and GPT3.5 (k=0.645), moderate reliability for Bing (k=0.503), and fair reliability for Bard (k=0.357). Conclusion: GPT4 showed acceptable performance and substantial reliability in adult BLS scenarios. However, the overall limited correctness and reliability of all chatbots across different scenarios indicate that current AI chatbots are unsuitable for providing life-saving instructions in critical medical emergencies.
Endoscopic Screening for Identification of Signet Ring Cell Gastric Cancer Foci in Carriers of Germline Pathogenic Variants in CDH1
Authors: Perez Lady Katherine Mejia , O’Malley Margaret , Chatterjee Arjun , Lyu Ruishen , Yang Qijun , Cruise Michael W. , LaGuardia Lisa , Liska David , Macaron Carole , Walsh R. Matthew , Burke Carol A 
Published: June 2024

Abstract

Objective: To determine the preoperative detection of signet ring cancer cells (SRC) on upper endoscopy (EGD) in patients with CDH1 pathogenic variant (PV) undergoing gastrectomy. To evaluate the development of advanced diffuse gastric cancer (DGC) in patients choosing surveillance.
Summary Background Data: Guidelines recommend prophylactic total gastrectomy (pTG) in CDH1PV carriers with family history of DGC between 18-40 years. Annual EGD with biopsies according to established protocols is recommended in carriers with no SRC and no family history of DGC, with consideration of pTG.
Methods:Retrospective analysis of asymptomatic patients with CDH1 PVs with ≥ 1 surveillance EGD. Outcomes included pre-operative EGD detection of SRC, surgical stage, and progression to advanced DGC in those electing surveillance with EGD.
Results: 48 patients with CDH1 PVs who had ≥ 1 EGD were included. 24/ 48 (50%) underwent gastrectomy, including pTG in 7 patients. SRCC were detected on gastrectomy specimen in 21/24 (87.5%). SRCs were identified by EGD in 17/21 patients who had SRCC on gastrectomy specimens (sensitivity 81%, 17/21). All cancers were stage pT1a. The remaining 17 patients (50% with a family history of gastric cancer) continue in annual EGD surveillance with a median follow-up of 34.6 months. No SRCC or advanced DGC have been diagnosed.
Conclusions: No CDH1PV carriers without SRCC on random biopsies followed in an endoscopic program developed advanced DGC over a median follow up of 3 years. In the short term, EGD surveillance appears a safe alternative to immediate pTG in patients with CDH1PV.
3D-printed aberration-free terahertz metalens for ultra-broadband achromatic super-resolution wide-angle imaging with high numerical aperture
Authors: Huang Shaoxing , Chen Jin , Chan Ka Fai , Wu Geng-Bo , Chan Chi Hou 
Published: June 2024

Abstract

Terahertz lens constitutes a vital component in terahertz systems, enabling high-resolution biosensing, biological imaging, and the detection of concealed details. Metasurfaces have been extensively employed in designing terahertz metalenses to mitigate the constraints of traditional bulky refractive lenses, owing to their adaptability and compact nature. Nevertheless, the high phase dispersion of their constituent units severely limits their applicability due to chromatic/spherical aberration, while the diffraction limit constrains the achievable imaging resolution. Consequently, the realization of achromatic super-resolution terahertz metalenses with a wide field of view (FOV) presents a challenging and urgently needed endeavor. In this study, we propose an innovative method for designing terahertz metalenses. The required phase distribution of the metalens is translated into a refractive index (RI) profile with a specific thickness, achieved through meticulously designed gradient metamaterials. Our designed terahertz metalens can realize achromatic super-resolution focusing with a high numerical aperture (NA) of 0.57 across the 0.2 to 0.9 THz range and is fabricated using 3D printing technology. Submillimeter features separated by approximately 0.2 mm can be resolved with high precision, such as epoxy-resin-impregnated woven glass fabric within FR4 panels and fibrous tissue on leaves, with a corresponding FOV of 900. Our approach offers a feasible and cost-effective means to obtain super-resolution achromatic terahertz metalens with a large FOV, which holds great potential for applications in non-destructive testing, biomedical imaging, and the realization of various terahertz metadevices.
Study on the efficacy and prognostic value of minimal residual disease in locally advanced cervical cancer based on plasma HPV-ctDNA protocol
Authors: Zhang Cui , Jiang Jia , Li Libo , Yang Can , Dai Yunmeng , Chen Yanping , Huang Yisidan , Xie Lu , Zhu Xiong , Xiang Yang , Yuan Jia , Luo Xiaoqing , Zeng Yuting , Liu Yuncong , Zhang Hanqun , Li Yong 
Published: June 2024

Abstract

Background
The recurrence and/or distant metastasis rate of locally advanced cervical cancer is still high after treatment. Current methods commonly used in clinical follow-up surveillance of cervical cancer still have some limitations. Important advances have been made in liquid biopsy-based circulating tumor DNA (ctDNA) for the assessment of microscopic residual disease (MRD) (ctNDA/MRD), and recent studies have found that human papillomavirus (HPV)-ctDNA-based assessment of MRD status is perhaps even more advantageous (HPV/MRD). However, it remains uncertain whether plasma HPV-ctDNA-based assessment of locally advanced cervical cancer efficacy and monitoring of prognosis is accurate and effective.
Methods
This study was a prospective, observational, single-center study to explore the predictive significance of monitoring HPV/MRD and ctDNA/MRD status on the efficacy and recurrence risk of cervical cancer after concurrent chemoradiotherapy. Patients with locally advanced cervical cancer who were treated in Guizhou Provincial People's Hospital were collected for tissue and blood samples for HPV testing and liquid biopsy HPV-ctDNA. The primary study endpoint is to detect the changes in MRD expression level before and after simultaneous radiotherapy for cervical cancer and to evaluate the efficacy and recurrence risk after simultaneous radiotherapy for cervical cancer. The secondary study endpoint is to analyze the role of MRD detection and imaging in predicting tumor recurrence and metastasis. The target sample size was 30 patients.
Discussion
This is a prospective study to explore the role of MRD based on HPV-ctDNA assessment in the efficacy and prognosis monitoring of concurrent chemoradiotherapy for locally advanced cervical cancer. It aims to provide important theoretical and practical significance for the evaluation of the efficacy and prognosis of locally advanced cervical cancer after concurrent chemoradiotherapy and to provide new methods for intervention in the recurrence of potential cervical cancer after treatment.
Trial registration
This trial is registered at the ClinicalTrials.gov (NCT05950087) on 18th July 2023, https://www.clinicaltrials.gov/ct2/show/NCT05950087.