bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shadow Economy and Economic Growth Nexus in Developing Countries: What is the Role of Financial Inclusion?
Authors: Waqar Ahmad , Babar Hussain , Khalid Muhammad Waqas , Lambarraa-Lehnhardt Fatima , Umair Muhammad 
Published: December 2024

Abstract

Shadow economy (SE) creates a significant barrier to economic progress in developing economies, whereas financial inclusion (FINI) plays a crucial role in boosting economic performance. This study examines the impact of the SE on economic growth (ECOG) and explores how this relationship is moderated by FINI. We use two key dimensions of FINI including financial market development (FMD) and financial institution development (FID). We apply system GMM and difference GMM techniques on a dataset of 120 selected developing economies worldwide, spanning the years 2002 to 2020. The estimation results reveal that a sizeable SE significantly hampers ECOG, while higher levels of FINI improve it. Additionally, financial inclusion, particularly through the development of financial markets and institutions, moderates the adverse effects of the SE on ECOG, suggesting a significant substitutability between the SE and FINI. This indicates that increasing FINI can reduce the shadow economy's size and mitigate its harmful effect on ECOG. These results remain robust when using an alternative measure of the SE. Based on the findings; we recommend that governments promote financial inclusion initiatives, such as expanding banking services, advancing mobile banking, and increasing financial literacy.
Analysis of Gene mutation types and clinical characteristics of patients with familial hypercholesterolemia in Shijiazhuang
Authors: Hu Xitian , Wei Zeqian , Geng Shuchen , Wang Shuo , Chen Liyuan 
Published: December 2024

Abstract

Objective This study aimed to investigate the incidence, types of gene mutations, and clinical characteristics of familial hypercholesterolemia (FH) in Shijiazhuang, while evaluating the effectiveness of targeted sequencing combined with high-risk population screening for FH. Methods A cross-sectional study was conducted involving 941 randomly selected normal individuals and 83 high-risk individuals. All participants underwent targeted sequencing for Low Density Lipoprotein Receptor (LDLR), Proprotein Convertase Subtilisin/kexin Type 9 (PCSK9), and Apolipoprotein B (APOB). Logistic regression and ROC curves were used to analyze predictive factors for gene mutations. Results The mutation rate of LDLR in the general population is 0.318%, while the mutation rate of PCSK9 is 0.106%. In contrast, among high-risk groups, the LDLR mutation rate increases significantly to 18.072%, and the mutation rate of APOB is 1.204%. Predictive factors for carrying mutated genes were TG (odds ratio [OR] = 0.328, 95% confidence interval [CI] = 0.164–0.893, p = 0.026), incidence of fatty liver (OR = 0.274, 95%, CI = 0.081–0.924, p = 0.037), body mass index (BMI) (OR = 0.775, 95% CI = 0.637–0.944, p = 0.011), incidence of fatty corneal arch (OR = 3.375, 95% CI = 1.124–10.131, p = 0.030), DLCN score (OR = 2.075, 95% CI = 1.433–2.951, p < 0.050), respectively. The areas under the ROC curves of TG, DLCN scores, and BMI were 0.757 (cutoff value, 1.420), 0.854 (cutoff value, 5.500), and 0.734 (cutoff value, 24.950) respectively. Conclusions Targeted sequencing of LDLR, PCSK9, and APOB effectively identifies FH-related mutations, especially in high-risk populations, enhancing detection rates while reducing costs.
Identification and Validation of a Novel Machine Learning Model for Predicting Severe Pelvic Endometriosis: A Retrospective Study
Authors: Cao Siqi , Li Xingzhe , Zheng Xin , Zhang Jiaxin , Ji Ziyao , liu yanjun 
Published: December 2024

Abstract

Background
Severe endometriosis significantly impacts the quality of life, particularly in women of reproductive age. Though numerous studies have conducted predictive models with preoperative clinical data for endometriosis, most risk models focus on diagnosis rather than disease staging. This study aimed to explore potential factors for endometriosis severity and to develop a classification model to assess the accuracy of predicting the risk of severe endometriosis.
Methods
A total of 308 patients with endometriosis were retrospectively analyzed. The stage of endometriosis was classified according to the scoring system of the revised American Society for Reproductive Medicine (rASRM) system, through surgical visualization,which is the most widely used staging system globally. All patients underwent preoperative transabdominal and transvaginal ultrasound, based on four steps screening approach proposed by The International Deep Endometriosis Analysis (IDEA) consensus. We randomly divided these data into training and testing datasets at a ratio of 8:2. Least absolute shrinkage and selection operator (LASSO) was performed to identify the potential risk factors for severe endometriosis. Then, we used 7 machine learning(ML) models to construct the predictive models. The area under the receiver-operating-characteristics curve (AUC) and accuracy were used to evaluate and determine the most effective model. Finally, SHapley Additive exPlanations (SHAP) interpretation was calculated to evaluate each parameter's contribution to risk prediction.
Results
In this retrospective study, about 59.2% (183/308) of endometriosis patients were diagnosed with severe endometriosis. The predictors of severe endometriosis occurrence were found to be compliance of 18 factors such as the negative sliding sign, pelvic fluid, bilateral OE, serum CA125 level and severe dysmenorrhea according to LASSO. The random forest (RF) model performed best in discriminative ability among the 7 ML models. After reducing features according to feature importance rank, an explainable final RF model was established with 6 features. The final model could accurately predict severe endometriosis with the area under curve (AUC) of 0.744 and an accuracy of 0.667 in the test set. From the SHAP map, it was found that the negative sliding sign had the greatest impact on the diagnostic performance of the RF model.
Conclusions
We constructed a predictive model based on the ML model, and the RF model showed a better performance. we also provided a personalized risk assessment for the development of stage IV in endometriosis patients explained by SHAP. This can help clinicians to treat severe endometriosis.
Prediction of Epileptic Seizure Using Deep Learning Techniques
Authors: Krosuri Lakshmi Revathi , Gundam Siddartha Reddy , Datti Mounika Lakshmi 
Published: December 2024

Abstract

Epilepsy, a widespread neurological condition affecting more than 65 million individuals globally, poses a significant challenge for over 30% of cases resistant to conventional medical or surgical interventions. This addresses the need for effective seizure prediction to counter the consequences of epilepsy through early detection of seizures. They occur in four primary states: the preictal phase, signaling occurrence of seizures earlier; ictal, the active seizure period; postictal state ensues after the seizure; and interictal, the baseline between seizure. In this proposal, a novel deep learning based epileptic seizure prediction approach using EEG signals has been introduced. It begins with the preprocessing of scalp EEG signals, followed by the automated extraction of features utilizing convolutional neural networks. Utilizing Bi-LSTM facilitates the classification process in the proposed methodology. The classification process is facilitated by Bi-LSTM, achieving a remarkable accuracy of 99.61% and specificity of 0.9961. This approach holds promise for improving quality of life by effectively mitigating the impact of seizures through timely intervention and accurate classification.
Comparison of three different protocols for the preparation of dental implant drilling sequences (Conventional, Undersized surgical technique and Expander-osteotome): Ex-vivo study
Authors: Ferreira Anderson Jara , Cáceres-Barreno Andrés , Gaêta-Araujo Hugo , Haiter-Neto Francisco , Guimarães Camila Coelho , Dias-Ribeiro Eduardo , Asprino Luciana 
Published: December 2024

Abstract

Objective: To compare the effect of three types of surgical site preparation protocols on the primary stability of dental implants installed in poor quality bone. Material and methods: After analysis by X-ray microtomography, thirty bone blocks with poor bone quality were chosen and divided into three groups (N = 10). Control: Conventional; Undersized surgical technique and Expander-osteotome. The final insertion torque and the implant stability quotient were recorded. Statistical analysis included the Shapiro-Wilk test, One-way ANOVA, with Tukey's post-hoc and Pearson's correlation coefficient with a significance level of 5%. Results: The undersized surgical technique obtained higher final insertion torque values (p <0.05) and better results in terms of resonance frequency analysis values (p <0.05). Pearson's correlation test showed a strong correlation between the variables (p < 0.05). Conclusions: According to the methodology used, the undersized surgical technique proved to be more advantageous in regions of low bone quality.
Comprehensive analysis of the nasopharyngeal microbiome and host transcriptome in children with varying severity of respiratory syncytial virus infection
Authors: Wang leying , Li Haiyan , Liu Zhenwei , Weng tingting , chen Xiaofang , Liu Peining , Dong lin 
Published: December 2024

Abstract

Background: The majority of children hospitalized with severe respiratory syncytial virus (RSV) infection do not exhibit conventional identifiable risk factors. The composition of the respiratory microbiota, in conjunction with host factors, significantly influences the initiation and progression of respiratory tract infections. We hypothesized that the severity of RSV infection in children is influenced by the interplay between host immune response regulation and the respiratory microbiota.
Methods: 16S rRNA sequencing was conducted on nasopharyngeal aspirate samples from pediatric RSV-infected patients (n = 129) and healthy controls (HCs; n = 21). Leukocyte transcriptomics was conducted using whole blood samples from 75 RSV-infected children and 40 age-matched HCs. Patients were grouped by severity of illness. To identify pathologic regulatory mechanisms, advanced computational methods were employed to analyze and integrate these datasets.
Results: Compared with HCs, RSV-infected children exhibited decreased microbial diversity, and higher relative abundances of the genera Pseudomonas, Achromobacter, and Variovorax that were positively correlated with the severity of infection. Transcriptomics uncovered 1,016 differentially expressed genes (DEGs) in the mild-, moderate-, and severe-infection groups versus the HC group. Of these, the 169 DEGs were common to all three infection groups were mainly enriched in processes related to hydrogen peroxide catabolic precursors, host entry mechanisms, response to lipopolysaccharide, and receptor-mediated endocytosis of viruses by host cells.Integrated microbiome and transcriptome analyses revealed strong correlations between two characteristic genera and two genes.
Conclusions: The respiratory microbiota is useful to distinguish severity of infection. Specifically, interactions between RSV and nasal microbes may regulate the host immune response, potentially affecting the severity of clinical diseases.
Impact of Lipid-Lowering Therapy on Pancreatic Health: Insights from Mendelian Randomization
Authors: Yang Ge , Feng Yizhuo , Ou Yanjiao , Zhang Hong , Tang Can-E , Chen Yongchuan 
Published: December 2024

Abstract

Pancreatic diseases, usually including various pancreatitis, pancreatic cancer and pancreatic cysts, present great challenges to the global health care system. Abnormal lipid profiles are common in these pancreatic diseases, suggesting the lipid-lowering medications may have potential effects on them. However, given the current evidence, the effects of lipid-lowering drugs on pancreatic diseases are inconsistent. Therefore, this study employs drug-targeted Mendelian randomization to investigate the causal relationships between hypocholesterolemic drugs (statins, ezetimibe and PCSK9 inhibitors) and various pancreatic diseases. The findings of our results indicate significant associations between the genetically proxied inhibition of HMGCR and decreased risks of chronic pancreatitis and pancreatic cysts, while PCSK9 inhibition is associated with an increased risk of alcoholic chronic pancreatitis. In addition, NPC1L1 inhibition is linked to an increased risk of pancreatic cysts and benign pancreatic tumors. These results provide insights for screening personalized medications for pancreatic diseases, highlighting the potential benefits of statins in pancreatitis and its complication and the need for caution when prescribing specific lipid-lowering drugs to patients predisposed to pancreatic conditions.
Assessment of Submandibular Fossa Depth and Diameter of Mandibular Canal Using Cone Beam Computed Tomography: A Comparative Study
Authors: Livingstone Shilpa , . Shivaprasad , Ayoob Aneesa , Shetty Devika , M Shruthi 
Published: December 2024

Abstract

Introduction
The submandibular fossa (SF) is a depression on the lingual surface of the mandible, extending from the distal of the mental foramen to the mandibular third molars. It houses the submandibular salivary gland, influencing its depth and shape. Accurate knowledge of SF and mandibular canal (MC) anatomy is crucial for preventing complications during oral surgeries, such as dental implant placement and extractions. This study aims to assess the SF depth, MC diameter, and concavity angles between males and females.
Methodology
The study included 160 patients (80 females and 80 males) aged 18–35 years who underwent CBCT imaging of the mandible. The images were analysed using NNT viewer software, focusing on the interradicular regions of the first and second molars. SF depth was categorized into three types: Type I (< 2 mm), Type II (2–3 mm), and Type III (> 3 mm). Measurements of MC diameter and concavity angles were also taken. Statistical analysis was performed using the unpaired t-test and Chi-square test, with significance set at p < 0.05.
Results
Type I SF depth was the most prevalent in both genders, with 70% of females and 60% of males exhibiting this type. However, males generally exhibited greater SF depth, averaging 2.0 mm compared to 1.7 mm in females, and larger concavity angles, with an average of 39° in males and 35° in females. Significant gender differences were observed in MC diameter, which was larger in males, averaging 2.9 mm compared to 2.7 mm in females, particularly on the right side. The SF depth was greater on the left side for both genders, with an average of 1.8 mm on the left side compared to 1.6 mm on the right side.
Conclusion
This study emphasizes the significance of anatomical variations, highlighting the necessity of detailed preoperative imaging for dental implant placement. Such imaging ensures an accurate assessment of bone morphology and dimensions, thereby minimizing surgical risks and improving patient outcomes.
Nonlinear association of the visceral adiposity index with migraine among the U.S adults from NHANES: a cross-sectional study
Authors: Lan Yang , Zijian Tang , Chen Qiwei , Yang Lu , Junqiang Chen. 
Published: December 2024

Abstract

Background
As a primary headache disorder impacting the neurovascular system, migraine has been linked to a higher risk in obese individuals relative to those with normal weight. Nonetheless, data regarding the association between central obesity and migraine are limited. The Visceral Adiposity Index (VAI) serves as an indicator of abdominal fat distribution and the functionality of adipose tissue. This study aims to examine the association between VAI and the risk of migraine in the adult U.S. population.
Methods
This research utilized data gathered from adult subjects during the 1999–2004 phase of the NHANES. Weighted multivariable logistic regression and smoothed curve fitting analyses were conducted to explore the potential associations between VAI and migraine. In addition, two-piecewise logistics regression models were used to calculate inflection points, we also conducted subgroup analysis, interaction tests to determine the consistency of findings.
Results
A total of 4503 participants(weighted mean age 46.35 years; 49.28% male) in this study, 868(19.28%) had a self-reported history of migraine. In the fully adjusted model, there is a 19% increased chance of getting migraine for every unit increase in the VAI after ln transformation(OR = 1.19, 95%CI:1.04–1.36). When VAI was converted from continuous variable into tertiles, participants in the highest VAI tertiles(T3) had a significantly 32% increased risk of migraine compared with those in the lowest tertile (OR = 1.32, 95%CI: 1.02–1.71). Furthermore,the multivariate smooth splines analysis demonstrated a non-linear relationship between VAI after Ln transformation and migraine (P for nonlinearity < 0.05), with an inflection point of roughly 0.64. The subgroup analyses, adjusted for all covariates, were in line with the overall population findings, and also revealed interactions between stroke and the outcome within the subgroups.
Conclusion
The study revealed a non-linear relationship, suggesting that VAI, being a noninvasive measure of visceral adiposity, might be utilized for a straightforward assessment of migraine risk, thereby serving as an innovative marker.
Estimation of Informal Economy in Pakistan Through Monetary Approach
Authors: Jehan Yasir , Khan Rohina 
Published: December 2024

Abstract

This study purposes to estimate Pakistan’s informal economy by monetary methods. The other objective of the study is to find that if tax evasion is playing a major role in the informal economy. Ordinary least square is used for estimation. From the monetary approach, we conclude that informal economy is increasing. In our study, particular implications of the informal economy are identified and conferred to accomplish and achieve the goal of continuous growth and progression of a country. The estimated result shows that informal economy grew rapidly to 13541.4 billion in 2017. On the other side, tax evasion grew rapidly from 2005 to 76184.1 billion and increases to 1886700.0 billion. The informal economy plays a main role in income inequality and reducing the poverty. It limits the implementation of the operative public policy. The government should make such policies to control the informal economy and increase tax evasion.
Challenges of getting to B (Briefing / Preoperative goal setting) in the BID model
Authors: Poola V. Prasad , Boehler Margaret , Roberts Nicole K 
Published: December 2024

Abstract

Purpose:
Implementing effective operative teaching models such as Briefing, Intra-operative teaching, and De- briefing (BID model) begins with establishing pre-operative teaching goals. However, the practice of setting pre-operative teaching goals is not widespread. This study aims to investigate the benefits, barriers, and facilitators of pre-operative goal setting as perceived by faculty surgeons.
Methods:
This qualitative study involved interviews with faculty members from our general surgery residency program, utilizing a standardized questionnaire. The interviews were recorded and transcribed. Qualitative analysis software (ATLAS.ti.9) was used to analyze the transcripts. We report the themes and relational networks.
Results:
All eight participants agreed that preoperative goal setting enhances teaching and improves resident satisfaction. However, individual and systemic barriers prevent this from being routinely practiced. These barriers include a belief that non-deliberate teaching is effective, administrative burdens that lead to organizational challenges and faculty burnout, workflow designs that hinder the alignment of faculty and residents for operative teaching, and a lack of clear expectations. Facilitators of incorporating preoperative goal setting into routine teaching practice include educating both faculty and residents, establishing realistic expectations, and aligning educational goals in the operating room. Faculty should be able to express their preferences for how and when to set preoperative goals. Cultivating a culture that considers preoperative goal setting as integral to operative teaching is essential for sustaining this practice.
Conclusions:
Despite recognizing its benefits, preoperative goal setting is not consistently practiced. This study identifies both individual and systemic barriers, as well as facilitators, that can guide efforts to promote and enhance the practice of preoperative goal setting.
Inflections in Learner Sentiment on the Culture of Surgery
Authors: Wagner Justin P. , Huang Ivy A. , Chen Formosa , Wu James , Tillou Areti , MacQueen Ian T. , Chen David C. , Rogers David A. 
Published: December 2024

Abstract

Purpose
Students’ preconceptions about workplace culture may influence the learning environment in the Surgery clerkship; however, the time at which students develop these sentiments is unclear. We aimed to identify inflections in students’ preconceptions of the culture of surgery, which are relevant to the timing of interventions targeting the surgical learning environment.
Methods
Cohorts of students at multiple levels received surveys between July 2021-September 2023 soliciting words associated with, “Culture of Surgery.” We analyzed entries using a Bag-of-Words method, with each word representing a unique token, and determined the most prevalent words. In sentiment analysis, 2 raters independently assigned a positive, neutral, or negative valence to each word, and valence agreement was assessed. We compared proportions of valences and rater agreement among cohorts with Fisher exact tests and determined inflections in sentiment along the learning continuum.
Results
Participants included 50 undergraduates, 111 first-year medical students, and 216 clerks beginning Surgery rotations. “Intense” was the most common word associated with “Culture of Surgery” at all levels. Sentiment analysis comparing pre-medical undergraduate students and first-year medical students revealed profound differences in proportions of words with positive (58.9 vs 13.3%, p<0.001) and negative (20.0 vs 57.0%, p<0.001) valences. Non-pre-medical undergraduate students’ word valences were even more frequently positive (71.6%) and less frequently negative (7.1%). Sentiments did not change appreciably among medical students at all levels. The range of rater agreements was 62.3-78.6%.
Conclusions
Prior to medical school, students have predominantly positive sentiments about surgical culture, while negative preconceptions predominate early in medical school and persist into clerkships. Interventions should be designed to encourage surgeons’ contributions to all aspects of undergraduate medical education culture.
Anti-GluK2 Antibody-Positive Autoimmune Encephalitis Concurrent with Multiple Myeloma: A Case Report
Authors: Cheng Zheng ping , Song Yang , Zhao Shuqi , Sui Xiaowen , Xie Lili , Zhao Hongling , Pan Xin , Cui Li , Huang Xinran , Ma Shubei 
Published: December 2024

Abstract

Background It is the first reported instance of GluK2 antibody-associated autoimmune encephalitis with involuntary movement.
Case presentation A 60-year-old woman who experienced involuntary movements of her lower limbs and facial muscle for two years，sometimes accompanied with hysterical shouting. Ater the treatment for multiple myeloma, bone marrow examinations showed that the proportion of myeloma cells have a sustained decline which indicated the treatment worked, meanwhile, all the symptoms disappeared and the concentrations of anti-GluK2 antibody IgG decreased sharply.
Conclusions This case revealed that the involuntary movements and the emotion is a new phenotype of Anti-GluK2 Antibody-Positive Autoimmune Encephalitis.