bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dosimetry Comparison of 3D Conformal Radiotherapy and Intensity-modulated Radiotherapy for the Treatment of Brain Tumors: A Meta-Analysis
Authors: Barman Ashima , Roy Sagor Kumar , Mahamud Sujan , Karmaker Nupur , Islam Md. Nurul 
Published: October 2024

Background:
This study aimed to evaluate IMRT and 3D-CRT in the therapy of brain
tumor (BT) in relation to dose-volume histograms (DVHs) parameters, such as Heterogeneity Index
(HI), Conformity index (CI), Equivalent Uniform Dose (EUD), and mean dose (Dmean) outcomes,
including the program for the tumors of the brain and estimate whether a favored procedure
can be found through the features of the pretreatment.

Method:
A search of the PubMed, Cochrane Library, and Embase datasets from their beginnings
from January 2006 to September 2022 was conducted. The authors separately selected and evaluated
studies for qualifying criteria and bias risk.

Result:
Seven studies in total were included. Of them, a total of 387 patients were integrated for
the Heterogeneity index (HI), Conformity Index (CI), Equivalent Uniform Dose (EUD), and mean
dose (Dmean) comparison analysis, which showed 3D-CRT & IMRT with odd ratio (OR) =1.93;
95% confidence interval (95% CI) =1.63, 2.22; and P value=0.00. For brain tumor patients, CI
was higher in IMRT than 3D-CRT with OR= 0.72; 95% CI =0.41, 1.03; p value <0.001. EUD was
higher in IMRT than 3D-CRT, resulting in an increased overall survival with OR=-0.86; 95% CI
=-1.30, 0.42; and p value<0.001. However, no statistically significant variance was perceived in
Dmean between 3D-CRT and IMRT.

Conclusion:
Our records suggested that IMRT with conventional linacs results in a meaningfully
lower regular percentage of brain tumor volumes compared to 3D-CRT. Finally, this meta-analysis
indicated that IMRT is better than 3D-CRT and decreases the average percent irradiated
amount of the brain.
Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Tumor Immune Infiltration in Bladder Cancer
Authors: Liu Gao-Lei , Luo Hao , Liang Dan-Dan , Zhong Li , Dai Nan , Lan Wei-Hua 
Published: October 2024

Background:
Bladder cancer exhibits substantial heterogeneity encompassing genetic
expressions and histological features. This heterogeneity is predominantly attributed to alternative
splicing (AS) and AS-regulated splicing factors (SFs), which, in turn, influence bladder
cancer development, progression, and response to treatment.

Objective:
This study aimed to explore the immune landscape of aberrant AS in bladder cancer
and establish the prognostic signatures for survival prediction.

Methods:
Bladder cancer-related RNA-Seq, transcriptome, and corresponding clinical information
were downloaded from The Cancer Genome Atlas (TCGA). Gene set enrichment analysis
(GSEA) was used to identify significantly enriched pathways of cancer-related AS events.
The underlying interactions among differentially expressed genes (DEGs) and cancer-related
AS events were assessed by a protein-protein interaction network. Univariate and multivariate
Cox regression analyses were performed to identify crucial prognostic DEGs that co-occurred
with cancer-related AS events (DEGAS) for overall survival. The area under the curve (AUC)
of receiver operating characteristic (ROC) curves was used to assess the efficiency of the prognostic
signatures. The CIBERSORT algorithm was used to explore the abundance of immune
infiltrating cells.

Results:
A total of 3755 cancer-related AS events and 3110 DEGs in bladder cancer were identified.
Among them, 379 DEGs co-occurred with cancer-related AS events (DEGAS), of which
102 DEGAS were associated with 14 dysregulated SFs. GSEA and KEGG analysis showed that
cancer-related AS events were predominantly enriched in pathways related to immunity, tumorigenesis,
and treatment difficulties of bladder cancer. Multivariate Cox regression analysis identified
8 DEGAS (CABP1, KCNN2, TNFRSF13B, PCDH7, SNRPA1, APOLD1, CX3CL1, and
DENND5A) significantly associated with OS, and they were further integrated into the prediction
model with good AUCs at 3-year, 5-year and 7-year ROC curves (all>0.7). Immune infiltration
analysis revealed the significant enrichment of three immune cell types (B cells naïve,
dendritic cells resting, and dendritic cell activated) in high-risk bladder cancer patients.

Conclusion:
This study not only unveiled comprehensive prognostic signatures of AS events in
bladder cancer but also established a robust prognostic model based on survival-related DEGAS.
These aberrant AS events, dysregulated SFs, and the identified 8 DEGAS may have significant
clinical potential as therapeutic targets for bladder cancer.
Investigation of Apoptotic and Anticancer Effects of 2-substituted Benzothiazoles in Breast Cancer Cell Lines: EGFR Modulation and Mechanistic Insights
Authors: Uremis Muhammed Mehdi , Ceylan Mustafa , Turkoz Yusuf 
Published: October 2024

Background and Objective:
Benzothiazole derivatives, a class of heterocyclic compounds, exhibited
diverse biological activities influenced by substituents in the thiazole ring. This study aimed to synthesize these
compounds with two functional groups to investigate their potential as anticancer agents, particularly against
breast cancer. While previous research demonstrated the efficacy of 2-substituted benzothiazoles against glioma
and cervical and pancreatic cancer cells, there is a gap in studies targeting breast cancer.

Methods:
The synthesized compounds were tested in vitro using MCF-7, MDA-MB-231, and MCF-10A cell
lines, with Doxorubicin as the positive control. Various assays were conducted, including Annexin V/PI, cell
cycle analysis, wound healing, and measurement of mitochondrial membrane potential. Protein expression of
EGFR and transcription levels of apoptosis-related genes (Bax and Bcl-xL) and cancer progression-related genes
(JAK, STAT3, ERK, AKT, mTOR) were analyzed. Additionally, the balance between antioxidants and oxidants
was evaluated by measuring TAS and TOS levels.

Results:
Our findings revealed that benzothiazole compounds significantly inhibited breast cancer cell growth by
reducing cell motility, disrupting mitochondrial membrane potential, and inducing cell cycle arrest in the sub-G1
phase. These compounds increased reactive oxygen species accumulation, leading to cell death. Furthermore,
they decreased EGFR protein levels, increased Bax gene transcription, and downregulated the expression of
genes such as JAK, STAT3, ERK, AKT, and mTOR.

Conclusion:
In conclusion, benzothiazole derivatives exhibited potent inhibitory effects on breast cancer in vitro
by promoting apoptosis, downregulating EGFR activity, and modulating key signaling pathways, including
JAK/STAT, ERK/MAPK, and PI3K/Akt/mTOR. These results highlighted the potential of benzothiazole derivatives
as novel therapeutic agents for breast cancer treatment.
Acute Febrile Illness in India: An Epidemiological Retrospective Study
Authors: Kumar Kaushalendra , Tripathi Amit Kumar , Sharma Vikash Kumar , Mishra Sunil Kumar , Patnaik Ranjana 
Published: October 2024

Introduction:
Acute febrile illness (AFI) is a frequent occurrence in India, often com-plicated by a multitude of pathogenic and etiological factors. In this context, it is important to analyze the biochemical, hematological, and epidemiological clinical parameters of AFI patients in the North Indian population.

Methods:
This study included 1,819 patients of various ages who presented with new-onset acute febrile illness (AFI) between 2017 and 2021. Among these patients, 211, with a median age of 40 years (ranging from 2 to 85 years), were selected for further analysis. At enrollment, clinical examination involved collecting respiratory tract specimens, blood, and urine samples for bio-chemical analysis, with subsequent data analysis conducted using statistical methods.

Results and Discussion:
The following biochemical parameters were analyzed: C-reactive pro-tein (CRP), alkaline phosphatase (ALP), serum glutamate-pyruvate transaminase (SGPT), serum glutamic oxaloacetic transaminase (SGOT), gamma-glutamyl transpeptidase (GGT), and total protein serum. The hematological parameters included total leukocyte count (TLC), lymphocyte count, monocyte count, eosinophil count, red blood cell count (RBCs), packed cell volume (PCV), erythrocyte sedimentation rate (ESR), hematocrit value, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH). Additionally, clinical parameters such as phosphorus, urea, calcium, sodium, uric acid, bilirubin, and potassium were measured. Specific values observed were: SGPT (~113 IU/L in 2018), SGOT (~81 U/L in 2019), GGT (~148 g/L in 2018), and total protein serum (~7 g/L in 2020). The hematological parameters (TLC, lympho-cyte, monocyte, RBCs, PCV, ESR, MCV, and MCH). The regression analysis was conducted to explore the temperature recorded at the time of admission, the duration of hospital stays, and biochemical as well as hematological variables of patients suffering from AFI. Karl-Pearson's correlation coefficient and variance inflation factor for each variable mentioned above.

Conclusion:
Biochemical and hematological parameters were analyzed over different years of intake in patients with Acute Febrile Illness (AFI). Further investigation is required to explore the mechanistic pathways of infection, and preventive measures will be implemented using nat-ural products and other therapeutic interventions. Our data will offer the first systematic assess-ment of the etiological factors, along with regression analysis and the Karl-Pearson correlation coefficient for each variable in AFI patients.
The Effect of Nutritional Mobile Apps on Populations With Cancer: Systematic Review
Authors: Ng Krystal Lu Shin , Munisamy Murallitharan , Lim Joanne Bee Yin , Alshagga Mustafa 
Published: October 2024

Background
Limited access to nutrition support among populations with cancer is a major barrier to sustainable and quality cancer care. Increasing use of mobile health in health care has raised concerns about its validity and health impacts.

Objective
This systematic review aimed to determine the effectiveness of commercial or cancer-specific nutritional mobile apps among people living with cancer.

Methods
A systematic search of the CENTRAL, Embase, PubMed (MEDLINE), and Scopus databases was carried out in May 2024. All types of intervention studies were included, except observational studies, gray literature, and reference lists of key systematic reviews. Studies were eligible for inclusion if they involved (1) patients with or survivors of cancer and (2) nutrition-related mobile apps. Studies were excluded if the nutrition intervention was not delivered via mobile app or the app intervention was accompanied by dietary counseling. The review process was conducted based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The Risk of Bias 2 and Risk of Bias in Nonrandomized Studies tools were used to assess the study quality. The Cochrane Review Manager (version 5.4) software was used to synthesize the results of the bias assessment.

Results
A total of 13 interventions were included, comprising 783 adults or teenagers with cancer. Most studies focused on breast cancer (6/13, 46%), overweight (6/13, 46%), and survivors (9/13, 69%). Data on anthropometry and body composition (7/13, 54%; 387 participants), nutritional status (3/13, 23%; 249 participants), dietary intake (7/13, 54%; 352 participants), and quality of life (6/13, 46%; 384 participants) were gathered. Experimental groups were more likely to report significant improvements in body weight or composition, dietary compliance, nutritional status, and quality of life than control groups.

Conclusions
Although mobile app platforms are used to deliver nutrition interventions, the evidence for long-term efficacy, particularly in populations with cancer, remains elusive. More robust randomized controlled trials with larger sample sizes, as well as more homogeneous population characteristics and outcome measures, are warranted.

Trial Registration
PROSPERO CRD42023330575; https://tinyurl.com/55v56yaj
Sensors for Smoking Detection in Epidemiological Research: Scoping Review
Authors: Favara Giuliana , Barchitta Martina , Maugeri Andrea , Magnano San Lio Roberta , Agodi Antonella 
Published: October 2024

Background
The use of wearable sensors is being explored as a challenging way to accurately identify smoking behaviors by measuring physiological and environmental factors in real-life settings. Although they hold potential benefits for aiding smoking cessation, no single wearable device currently achieves high accuracy in detecting smoking events. Furthermore, it is crucial to emphasize that this area of study is dynamic and requires ongoing updates.

Objective
This scoping review aims to map the scientific literature for identifying the main sensors developed or used for tobacco smoke detection, with a specific focus on wearable sensors, as well as describe their key features and categorize them by type.

Methods
According to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) protocol, an electronic search was conducted on the PubMed, MEDLINE, and Web of Science databases, using the following keywords: (“biosensors” OR “biosensor” OR “sensors” OR “sensor” OR “wearable”) AND (“smoking” OR “smoke”).

Results
Among a total of 37 studies included in this scoping review published between 2012 and March 2024, 16 described sensors based on wearable bands, 15 described multisensory systems, and 6 described other strategies to detect tobacco smoke exposure. Included studies provided details about the design or application of wearable sensors based on an elastic band to detect different aspects of tobacco smoke exposure (eg, arm, wrist, and finger movements, and lighting events). Some studies proposed a system composed of different sensor modalities (eg, Personal Automatic Cigarette Tracker [PACT], PACT 2.0, and AutoSense).

Conclusions
Our scoping review has revealed both the obstacles and opportunities linked to wearable devices, offering valuable insights for future research initiatives. Tackling the recognized challenges and delving into potential avenues for enhancement could elevate wearable devices into even more effective tools for aiding smoking cessation. In this context, continuous research is essential to fine-tune and optimize these devices, guaranteeing their practicality and reliability in real-world applications.
Discriminant Power of Smartphone-Derived Keystroke Dynamics for Mild Cognitive Impairment Compared to a Neuropsychological Screening Test: Cross-Sectional Study
Authors: Park Jin-Hyuck 
Published: October 2024

Background
Conventional neuropsychological screening tools for mild cognitive impairment (MCI) face challenges in terms of accuracy and practicality. Digital health solutions, such as unobtrusively capturing smartphone interaction data, offer a promising alternative. However, the potential of digital biomarkers as a surrogate for MCI screening remains unclear, with few comparisons between smartphone interactions and existing screening tools.

Objective
This study aimed to investigate the effectiveness of smartphone-derived keystroke dynamics, captured via the Neurokeys keyboard app, in distinguishing patients with MCI from healthy controls (HCs). This study also compared the discriminant performance of these digital biomarkers against the Korean version of the Montreal Cognitive Assessment (MoCA-K), which is widely used for MCI detection in clinical settings.

Methods
A total of 64 HCs and 47 patients with MCI were recruited. Over a 1-month period, participants generated 3530 typing sessions, with 2740 (77.6%) analyzed for this study. Keystroke metrics, including hold time and flight time, were extracted. Receiver operating characteristics analysis was used to assess the sensitivity and specificity of keystroke dynamics in discriminating between HCs and patients with MCI. This study also explored the correlation between keystroke dynamics and MoCA-K scores.

Results
Patients with MCI had significantly higher keystroke latency than HCs (P<.001). In particular, latency between key presses resulted in the highest sensitivity (97.9%) and specificity (96.9%). In addition, keystroke dynamics were significantly correlated with the MoCA-K (hold time: r=–.468; P<.001; flight time: r=–.497; P<.001), further supporting the validity of these digital biomarkers.

Conclusions
These findings highlight the potential of smartphone-derived keystroke dynamics as an effective and ecologically valid tool for screening MCI. With higher sensitivity and specificity than the MoCA-K, particularly in measuring flight time, keystroke dynamics can serve as a noninvasive, scalable, and continuous method for early cognitive impairment detection. This novel approach could revolutionize MCI screening, offering a practical alternative to traditional tools in everyday settings.

Trial Registration
Thai Clinical Trials Registry TCTR20220415002; https://www.thaiclinicaltrials.org/show/TCTR20220415002
Improvement of Motor Imagination and Manual Ability Through Virtual Reality and Selective and Nonselective Functional Electrical Stimulation: Protocol for a Randomized Controlled Trial
Authors: Santamaría-Vázquez Montserrat , Ortiz-Huerta J Hilario , Martín-Odriozola Aitor , Saiz-Vazquez Olalla 
Published: October 2024

Background
Motor imagery (MI) is a cognitive process that has been shown to be useful in the rehabilitation process after brain injury. Moreover, functional electrical stimulation (FES) and virtual reality (VR) have also been shown to be effective interventions in many parameters, and there is some evidence of their contribution to the improvement of MI capacity.

Objective
This study aimed to compare the improvements in MI parameters, grip strength, and manual dexterity obtained using VR, FES, and selective FES based on multifield electrodes in healthy people.

Methods
This clinical randomized controlled trial (RCT)with 4 branches will involve 80 healthy university students, with blinded third-party assessment. Participants will be divided into 4 groups: control (no intervention), selective FES (Fesia Grasp), traditional FES (Globus Elite), and Virtual Rehab Hands (Leap Motion sensor). Each group will receive 5 daily sessions, and assessments will be conducted at baseline, postintervention, and follow-up. The Movement Imagery Questionnaire-Revised (MIQ-RS) and chronometry will be used to assess MI, strength will be measured with a digital dynamometer, and manual dexterity will be evaluated with the Nine Hole Peg Test (NHPT) and the Box and Block Test (BBT). Statistical analyses will include 2-way repeated-measures ANOVA with post hoc Bonferroni correction to compare group differences over time, with nonparametric tests (eg, Kruskal-Wallis) being used if normality or variance assumptions are violated. The study will be organized into 3 phases: preparation, data collection, and analysis. The preparation phase will involve finalizing project protocols and obtaining ethical approvals. The data collection phase will consist of recruiting participants, randomizing them into 4 intervention groups, and conducting baseline assessments, followed by intervention sessions. Finally, the analysis phase will focus on evaluating the data collected from all groups and compiling the results for presentation.

Results
The study received approval in July 2023, with recruitment and data collection starting in September 2023. The recruitment phase was expected to conclude by July 2024, and the entire study, including the 2-week follow-up, was set to finish in September 2024. As of July 2024, we had enrolled 100% of the sample (N=80 students). We plan to publish the study findings by the end of 2024.

Conclusions
Improvements in MI and upper limb functionality are expected, particularly in the selective FES group. This RCT will identify which intervention is most effective in enhancing these skills, with potential benefits for patients with neurological motor disorders.

Trial Registration
ClinicalTrials.gov NCT06109025; https://clinicaltrials.gov/study/NCT06109025

International Registered Report Identifier (IRRID)
DERR1-10.2196/63329
Support vector machine classification of patients with depression based on resting-state electroencephalography
Authors: Yang Chia-Yen , Chen Yin-Zhen 
Published: October 2024

Abstract

Background
Depression is one of the most common mental disorders. Although depression is typically diagnosed by identifying specific symptoms and through history, no recognized standard for depression diagnosis exists. This assures the development of objective diagnostic tools for depression.

Objectives
We investigated the differences in the resting-state electroencephalograms (EEGs) of patients with depression and healthy controls (HCs) to distinguish patients from HCs by using a support vector machine (SVM) classifier with the following two feature selection approaches: t test and receiver operating characteristic analysis.

Methods
We used the EEG data from the Patient Repository of EEG Data + Computational Tools; this study included 21 patients with depressive disorder (MDD) and 21 HCs. The relative frequency power, alpha interhemispheric asymmetry, left–right coherence, strength, clustering coefficient (CC), shortest path length, sample entropy (SampEn), multiscale entropy (MSE), and detrended fluctuation analysis (DFA) data were extracted to determine candidate EEG features associated with depression.

Results
With the t-test selection, the SVM classifier demonstrated the highest performance with the accuracy, sensitivity, and specificity of 96.66%, 95.93%, and 97.550% for the eye-open condition and 91.33%, 90.59%, and 91.81% for the eye-closed condition, respectively. For comparisons of features in the 2 selection approaches, the most influential features were relative frequency power and left–right coherence.

Conclusion
Using this information to distinguish patients with MDD from HC subjects with the SVM classifier resulted in a mean accuracy over 90%. Although this result may not be robust enough for clinical applications, further exploration is necessary given the simplicity, objectivity, and efficiency of the classifier.
The Influence of a Practical Remediation Medium on the Relationship of Exchange Reaction in Soil to Hazardous Lead and Inorganic Forms of Nitrogen
Authors: Urminská Jana , Prokeinová Renáta Benda , Musilová Janette , Urminská Dana , Tančinová Dana , Mašková Zuzana , Barboráková Zuzana 
Published: October 2024

Abstract
The objective of this research was to analyse soil and garden compost as a remediation medium at the foothill´s locality of the Tribeč Mountains, Southwestern Slovakia, to determine the pH/KCl, Pb, NO3
−-N, NH4
+-N contents in soil and soil affected by compost (the ratio 1 : 1), to evaluate the statistical significance of pH/KCl in relation to Pb and inorganic forms of nitrogen, and to find whether garden compost affects the monitored parameters. The analyses were carried out using Atomic Absorption Spectrometry, and Colorimetric and Potentiometric methods. Ascertained values of exchange reactions in soil ranged from 5.74 to 6.83 and exchange reactions in soil affected by garden compost ranged from 6.78 to 7.98. According to the calculated indices of dependencies, the development of pH/KCl values can be evaluated as moderately dynamic. The obtained results were evaluated statistically using the SAS 9.4 software method by the Spearman‘s correlation coefficient. The results in the observed three-year period showed that NO3
−-N contents in soil had reached 14.73 mg.kg−1, NH4
+-N 9.50 mg.kg−1, Nin 23.05 mg.kg−1, Pb 67.38 mg.kg−1, soil affecting by remediation medium – garden compost (the ratio 1 : 1) showed that NO3
−-N contents had reached 23.93 mg.kg−1, NH4
+-N 26.42 mg.kg−1, Nin 42.63 mg.kg−1, Pb 64.71 mg.kg−1 dry matter. Statistical dependence was high (P <0.01), which was demonstrated for soil pH : soil + compost Pb, soil + compost pH : soil + compost Pb. The garden compost influenced pH/KCl, reduced Pb levels, and increased the proportion of inorganic forms of nitrogen in soil.