bluuebunny/crossref_metadata_2025_split huggingface dataset:
Provision of digital health interventions for young people with ADHD in primary care: findings from a national survey and scoping review
Authors: Gudka Rebecca , Becker Kieran , Newlove-Delgado Tamsin , Price Anna 
Published: November 2023

Abstract
Background
People with attention-deficit hyperactivity disorder (ADHD) are at risk of negative health outcomes, with risks reduced through evidence-based treatments. Therefore, ensuring continued access to treatment for young people with ADHD, especially as they transition from child to adult services, is a priority. Currently many young people with ADHD are unable to access adequate care, with negative consequences for patients and their communities. Preliminary evidence suggests digital health interventions (DHIs) may act as an effective adjunct to usual care, helping overcome barriers to access, and improving outcomes by increasing understanding of ADHD as a long-term condition. The aim of this mixed methods study is to explore the healthcare information preferences of people with lived experience of ADHD in the primary care context and considers these in the light of the emerging body of literature on DHIs for ADHD.
Methods
A cross-sectional survey on used and preferred healthcare information resources for people with ADHD was disseminated via research networks, national organisations, and social media. A scoping review of evidence on DHIs for people with ADHD aged 16–25 was conducted, with synthesis of evidence on barriers and facilitators to implementation. A descriptive summary of survey responses was compared and discussed in the context of DHIs identified in the scoping review.
Results
Digital apps, followed by support groups, were deemed the most useful information resource types by survey respondents, but were the least currently used/provided. Over 40% participants indicated a preference for signposting to all resource types by their general practitioner (GP), suggesting that GPs are credible sources for ADHD healthcare information. The scoping review identified 10 studies of DHI for ADHD, consisting of games, symptom monitoring, psychoeducation, and medication reminders, with limited evidence of effectiveness/implementation.
Conclusions
People with ADHD state a preference for digital apps as an adjunct to usual care. However, these are currently the least provided information resource in primary care, indicating a key area for future development. The limited evidence base on DHIs for ADHD suggests combining digital apps and support networks, and utilising multimodal delivery methods may also enhance the delivery of healthcare information.
The inflammation score predicts the prognosis of gastric cancer patients undergoing Da Vinci robot surgery
Authors: chen xihao , zhang yichao , liu zhiyu , song jiawei , li jipeng 
Published: November 2023

Abstract

Purpose
Neutrophil-to-lymphocyte ratio (NLR), calculated from peripheral blood immune-inflammatory cell counts, is considered a predictor of survival in various cancers. Nevertheless, there is a lack of research into the predictive value of NLR specifically in gastric cancer patients following surgery using the Da Vinci robot. Investigate the objectives of this research, confirm the positive predictive value of NLR in the prognosis of gastric cancer patients undergoing Da Vinci robotic-assisted surgery by comparing its prognostic ability with other inflammation markers and tumor biomarkers.
Methods
In this retrospective analysis, information from 128 individuals diagnosed with gastric cancer and treated with da Vinci robot-assisted surgery was examined. The study examined various markers in the peripheral blood, including neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), systemic immune-inflammatory index (SII) prognostic nutrition index (PNI), cancer antigen 125 (CA125), carbohydrate antigen 19 − 9 (CA19-9), carbohydrate antigen 72 − 4 (CA72-4), carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP).To ascertain the prognostic ability and optimal cutoff values of each parameter, operating characteristic curves and the area under the curve were utilized in the analysis. For evaluation of independent prognostic factors, we utilized Kaplan-Meier curves and multifactorial COX analysis. The variables from the multifactorial Cox analysis were used to construct a nomogram.
Results
NLR, LMR, CEA, AFP, primary location, largest tumor size and TNM stage were all found to be significant predictive elements for overall survival (OS). Multivariate Cox identified NLR (P = 0.005), LMR (P = 0.03) and AFP (P = 0.007) as the only separate predictive variables among hematological indicators. The nomogram built using NLR demonstrates excellent predictive performance at 1-year (AUC = 0.778),3-years (AUC = 0.773), and 5-years (AUC = 0.781). Cross-validation demonstrates that this model has favorable predictive performance and discriminative ability.
Conclusion
NLR is an uncomplicated yet potent marker for forecasting the survival result of individuals with gastric cancer following da Vinci robotic surgery, and it possesses considerable predictive significance. The nomogram based on NLR provides patients with a visual and accurate prognosis prediction.
Toxic element enrichment and potential ecological risks from asbestos-bearing mine wastes
Authors: Schapira Jessica , Bolhar Robert , Master Sharad 
Published: November 2023

Abstract
In developing countries, such as those in Africa, the existence of empirical data characterising the chemical composition and ecological and health risks of solid mine wastes, such as asbestos, is extremely limited. While the geological properties and carcinogenic risks of asbestos fibres have been long-known and well-researched, the potential ecological impacts of exposed asbestos mine wastes and asbestos-bearing geological deposits have largely been ignored. In this study a preliminary assessment of heavy metal pollution from asbestos-mine wastes is presented using different pollution indices in the context of source contamination. The quantitative contamination indices (enrichment factor, geo-accumulation index (Igeo), contamination factor (Cf), degree of contamination (Cdegree) and pollution load index (PLI)), ecological risks and hazards quotient (HQ) were determined for chrysotile, amosite, crocidolite and anthophyllite mine waste types. The results indicate that the asbestos mine wastes contain high concentrations of heavy metals, greater than their respective background levels, with significant implications for ecological and human health risks.
Characterization of Argonaute Nucleases from Mesophilic Bacteria Pseudobutyrivibrio ruminis
Authors: Xu Xiaoyi , Yang Hao , Dong Huarong , Li Xiao , Liu Qian , Feng Yan 
Published: November 2023

Abstract
Mesophilic Argonautes (Agos) from microbial resources have garnered significant attention due to their potential applications in genome editing and molecular diagnostics. This study characterizes a novel Ago from Pseudobutyrivibrio ruminis (PrAgo) that exhibits strict DNA-guided cleavage for single-stranded DNA. PrAgo can effectively cleave DNA using 5'-phosphate guide DNA, with both Mn2+ and Mg2+ ions, and functions optimally across a wide range of pH values and temperatures. Additionally, PrAgo displays efficient cleavage even in the presence of a single- nucleotide mismatch in the guide DNA, and continuous double-nucleotide mismatches may reduce cleavage efficiency. Notably, PrAgo also demonstrates programmable cleavage of double-stranded DNA at 65°C. Molecular dynamic simulations suggest interactions between the PAZ domain and different guide DNAs strongly influence cleavage efficiency. These findings expand our understanding of mesophilic Agos and their potential applications in biotechnology.
Flexible superconducting wiring for integration with low temperature detector and readout fabrication
Authors: O'Neil Galen , Doriese William Bertrand , Keller Mark , Mates John , Morgan Kelsey , Schmidt Dan , Singh Robinjeet , Swetz Daniel , Vale Leila , Vissers Michael , Weber Joel , Ullom Joel 
Published: November 2023

Abstract

We present a method of creating high-density superconducting flexible wiring on flexible thin silicon substrates. The flexible wiring, called SOI flex, is created by depositing superconducting wiring on a silicon on insulator (SOI) wafer, selectively etching away the thicker silicon section handle layer, and bending the thinner silicon device layer. We show measurements of superconducting transition temperature and critical current for Mo, Nb, and Al on SOI flex. We discuss the expected advantages of SOI flex for low-temperature detector applications, as well as the role of stress and strain in bent silicon and niobium.
The Function Number Method: Generalization
Authors: YANDZA Marcel Julmard ONGOUMAKA , GOMAT Landry Jean Pierre 
Published: November 2023

Abstract

Many mathematical methods have been created to solve mathematical problems such as integral calculus, derivatives and differential equations. Among them, there is the Function Number Method (FNM). A Function Number is a real number which represents a variable function in a set. The calculus is done by the application of some properties detailed in the corps of this article. This real number, representing the function, can also be transformed to a variable function. By this way, many mathematical problems are solved easily. The FNM can be used for all orders of the derivatives. In the precedent publication on the FNM, the methodology presented was focused only on the resolution of the derivatives of the first and second orders. To solve the high orders of the derivatives of the functions with many variables, a general method is necessary. So, in this article, the generalization of the FNM is presented. The method will help mathematicians, physicists and many others scientists in their researches.
Thermodynamic Equilibrium State Prediction By Deep Learning Method
Authors: Okano Yu , Kaneshita Takeshi , Okuno Katsuki , Takemoto Shimpei , Okuno Yoshishige 
Published: November 2023

Abstract
The method of calculation of phase diagrams (CALPHAD) is a calculation method that searches for a state of providing minimal Gibbs energy as an equilibrium state. To perform a thermodynamic equilibrium calculation for a single material composition and to predict a phase diagram, we can complete the CALPHAD method calculation within a realistic time. However, screening many material compositions associated with predicting the corresponding phase diagrams takes much time. For alloy materials, for example, it would take 161 hours to calculate phase diagrams of all alloy compositions to screen 10,000 sets of explanatory variables, i.e., compositions and manufacturing conditions, since it takes 58 seconds to calculate each set. The present study aims to provide a calculation device, method, and program for quickly predicting the thermodynamic equilibrium state. We developed a deep learning model based on the Transformer architecture to achieve this objective, primarily used for various natural language processing tasks, such as machine translation, text summarization, question answering, and sentiment analysis. The encoder part of our developed model extracts the necessary features for phase diagram prediction from the inputted alloying elements. In contrast, the decoder part predicts a phase diagram for each temperature based on the results from the encoder. We calculated 800,000 species using the CALPHAD method and employed these data to train our developed model. Our trained model can calculate thermodynamic equilibrium states more than 100 times faster than the CALPHAD method and correctly reproduce the phase diagrams of ground truths. Based on the present result, we could invent a calculation device, a calculation method, and a calculation program for predicting the thermodynamic equilibrium state in a short time.
Symptoms of anxiety and depression and health-related quality of life in women with severe obesity and polycystic ovary syndrome and the effect of a one year weight loss intervention
Authors: Kataoka Josefin , Olsson Marie , Lindgren Eva , Larsson Ingrid , Schmidt Johanna , Benrick Anna , Stener-Victorin Elisabet 
Published: November 2023

Abstract
Background
Polycystic ovary syndrome (PCOS) is a common endocrine disorder among women, with more reported symptoms of anxiety, depression and lower health related quality of life (HRQoL). PCOS is associated with, and increases with obesity, which per se could lead to symptoms of anxiety and depression and lower HRQoL. First line treatment for PCOS is weight loss through life-style intervention. Studies on mental health and quality of life in women with PCOS and severe obesity are lacking. The aim of this study was to investigate symptoms of anxiety and depression and HRQoL in women with severe obesity with and without PCOS, and to define the effect of a one-year weight loss intervention.
Methods
In total 246 women with severe obesity with (n = 63), and without (n = 183) PCOS were included. Comprehensive Psychopathological Rating Scale Self-rating Scale for affective symptoms, and the generic short form-36 were used to assess symptoms of anxiety and depression and HRQoL. At one year, 72 women had completed a one-year weight loss intervention and were followed up with baseline data.
Results
There were no differences in symptoms of anxiety and depression and HRQoL between women with and without PCOS at baseline. Clinically relevant symptoms of anxiety were present in 71.3% (PCOS) respectively 65.6% (non-PCOS), and symptoms of depression were present in 56.4% (PCOS), respectively 52.2%, (non-PCOS). Significant weight reduction improved physical HRQoL for all women, but decreased symptoms of anxiety and depression only in women without PCOS.
Conclusions
In women with severe obesity, weight loss improves symptoms of anxiety and depression only in women without PCOS.
Trial registration number:
Clinical trial.gov: NCT01319162, March 18, 2011. Date of registration and enrolment of the first subject September 2011.
Study on the mechanism of action of probucol in the treatment of coronary artery disease based on network pharmacology and molecular docking technology
Authors: dan liangxing , Pan Ye , zhao Zunlan , feng Wenting , liu Zhihui , shi Weili , Wang Liuyi 
Published: November 2023

Abstract
Objective
The latest studies have shown that the combined use of aggressive lipid-lowering and inflammation-reducing therapies might reduce atherosclerotic risk. Probucol has hypolipidemic, antioxidative, and anti-inflammatory effects. Through network pharmacology and molecular docking, the core genes, biological function, and signalling pathways of Probucol in coronary artery disease/coronary heart disease were revealed.
Methods
Pharmacological targets of probucol were screened using the SuperPred, Similarity ensemble approach (SEA), and STITCH databases. Similarly, the pathological targets of CAD/CHD were obtained through the DisGeNET, National Center for Biotechnology Information (NCBI), and GeneCard databases. Then, all common targets of probucol against CAD/CHD were screened by an online platform. Seven core targets were obtained through six algorithms of the CytoHubba plugin of Cytoscape and the online platform Jvenn. Finally, the core genes were analysed by GO and KEGG enrichment analyses and molecular docking technology was utilized to verify the core gene prediction and further confirm the target and mechanism of probucol in CAD/CHD.
Results
By screening the targets of probucol and CAD/CHD, 121 pharmacological targets, 11403 pathological targets, and 84 common targets were obtained; furthermore, seven core targets were identified. These core targets were SCARB1, APOE, VCAM1, NF-кB, HIF1A, PTPN11 and SLC2A1. In addition, the enrichment analysis results indicated that probucol might treat CAD/CHD by regulating cholesterol imbalance and anti-inflammatory and antioxidant activities. The molecular docking results showed that probucol binds well to the core targets associated with CAD/CHD.
Conclusion
Probucol might be involved in regulating cholesterol imbalance and anti-inflammatory and antioxidant activities based on its regulation of SCARB1, APOE, VCAM1, NF-кB, HIF1A, PTPN11 and SLC2A1. Strategies targeting these biotargets may be used to treat CAD/CHD in future clinical practice.
DeepSipred: A deep-learning-based approach on siRNA inhibition prediction
Authors: Liu Bin , Huang Huiya , Liao Weixi , Pan Xiaoyong , Jin Cheng , Yuan Ye 
Published: November 2023

Abstract
Motivation: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has become a widespread molecular tool for gene function study and new drug identification. Although the pathway of RNAi to mediate gene expression has been widely investigated, the selection of hyperfunctional siRNA with high inhibition remains challenging.
Results: In this study, we build a deep-learning-based approach on siRNA inhibition prediction, named DeepSipred. It combines features from sequence context, thermodynamic property, and other expert knowledge together to predict the inhibition more accurately than existing methods. The sequence features from siRNA and local target mRNA are generated via one-hot encoding and pretrained RNA-FM encoding. The convolution layers with multiple kernels in DeepSipred can detect various decisive motifs, which will determine the actual inhibition of siRNA. The thermodynamic features are calculated from Gibbs Free Energy. In addition, the expert knowledge includes those design criteria from previous studies. Benchmarked on large available public datasets, the 10-fold cross-validation results indicate that our predictor achieving the state-of-the-art performance.
Cytotoxic effect of DEBIO 1143 on Triple Negative Mouse Breast Cancer Cell Lines by Non-Apoptosis Death Mechanisms
Authors: Tuğrul Berrin , Alp Meral , Balcan Erdal 
Published: November 2023

Abstract
Background
Triple negative breast cancer (TNBC) is a lethal cancer lacking therapeutic targets. In this project, we aimed to investigate the cytotoxic effect of DEBIO 1143, a SMAC mimetic, on 4T1 and 4T1-HER2 mouse TNBC cell lines and the cell death pathway through which this effect is mediated.
Methods and results
MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) test was used to determine cell viability, flow cytometry analysis was performed to determine apoptosis, and MDC (monodansylcadaverine) was used to determine autophagic vesicles. In addition, LC3II, Beclin 1, RIP3 and cIAP1 proteins were analyzed by western blot. In both cell lines, it was determined that DEBIO 1143 IC50 doses caused predominantly non-apoptotic cell death in the 48-h drug-treated group. In western blot analysis, LC3II level was significantly increased in 4T1-HER2 cells treated with DEBIO 1143 for 24 and 48 hours compared to control. Beclin 1 expression was significantly elevated in the drug treatment groups of both cell lines. The expression level of RIP3 in 4T1 cells was relatively increased after 24 and 48 h treatment of DEBIO 1143 compared to control. cIAP1 protein bands were detected in both control and 24- h treatment groups of both cell lines, but not in 48- h treatment groups.
Conclusions
Our findings revealed that DEBIO 1143 showed a time-dependent cytotoxic effect in mouse TNBC cell lines. This effect may be predominantly mediated through non-apoptosis cell death mechanisms such as autophagy and necrosis. Further research is recommended to clarify the issue fully.
Evaluation of the Seasonal Variation on the Hydrogeochemical Parameters and Quality Assessment of the Springs in Nelliyampathy; Kerala- Southern Western Ghats India: The Contribution of Natural and Anthropogenic Factors
Authors: G Rijulal , KM Athul Gabriel , TM Vishnu Maya , A Krishnakumar , K Anoop Krishnan 
Published: November 2023

Abstract

Groundwater is a life-sustaining resource that plays a central part in irrigated agriculture and influences the health of many ecosystems. For fresh water supplies, groundwater in the form of springs has been the traditional and conventional source for the rural communities as well as for peri-urban and urban areas of Indian subcontinent. The springs originate from the underground aquifers which are recharged with rainwater. To assess natural and anthropogenic impacts on spring water chemistry, seasonal and spatial hydrochemical changes in 13 springs water samples were studied in the high land of Nelliyampathy region of western Ghats Kerala. The analyses investigated major cation, anion, and trace element concentrations. Moreover, water temperature, electrical conductivity, and pH were measured in the field. The irrigation quality parameters such as sodium adsorption ratio, %Na, residual sodium carbonate, residual sodium bicarbonate, Kelley’s index, potential salinity, magnesium hazard, Mg/Ca ratio and permeability index were calculated and discussed. Hydrochemical interpretation suggests two main groups of samples. Furthermore, groundwater chemistry was found mainly influenced by evaporation–crystallization in Gibbs variation diagram. This study suggested that spring water is unsafe for drinking purpose without purification and quality measures should be considered while cropping in its irrigation use.
Laser-Induced Graphene Electrochemical Sensor for Quantitative Detection of Phytotoxic Aluminum Ions (Al 3+ ) in Soils Extracts
Authors: Loaiza Vanessa Reyes , Roche Jhonattan De La , Renjifo Erick Hernandez , Idárraga Orlando , Silva Mayesse Da , Valencia Drochss Pettri , Ghneim-Herrera Thaura , Jaramillo-Botero Andres 
Published: November 2023

Abstract
Aluminum in its Al3+ form is a metal that inhibits plant growth, especially in acidic soils (pH < 5.5). Rapid and accurate quantitative detection of Al3+ in agricultural soils is critical for the timely implementation of remediation strategies. However, detecting metal ions requires time-consuming preparation of samples, using expensive instrumentation and non-portable spectroscopic techniques. As an alternative, electrochemical sensors offer a cost-effective and minimally invasive approach for in situ quantification of metal ions. Here, we developed and validated an electrochemical sensor based on bismuth-modified laser-induced graphene (LIG) electrodes for Al3+ quantitative detection in a range relevant to agriculture (1 to 300 ppm). Our results show a linear Al3+ detection range of 1.07–300 ppm with a variation coefficient of 5.3%, even in the presence of other metal ions (Pb2+, Cd2+, and Cu2+). The sensor offers a limit of detection (LOD) of 0.34 ppm and a limit of quantification (LOQ) of 1.07 ppm. We compared its accuracy for soil samples with pH < 4.8 to within 89–98% of spectroscopic methods (ICP-OES) and potentiometric titration. This technology's portability, easy to use, and cost-effectiveness make it a promising candidate for in situ quantification and remediation of Al3+ in agricultural soils and other complex matrices.