bluuebunny/crossref_metadata_2025 huggingface dataset:
Preventing Adolescent Suicide: Feasibility and Preliminary Outcome Evaluation of a Theatre-Based Gatekeeper Training for Teachers
Authors: Davico Chiara , Graziano Federica , Rossi Ghiglione Alessandra , Amianto Federico , Begotti Tatiana , Calandri Emanuela , Copetto Giorgia , Di Franco Francesca , Lonardelli Elena , Marcotulli Daniele , Olcuire Linda , Ricci Federica , Vitiello Benedetto
Published: December 2024

Improving teachers’ knowledge and skills in dealing with adolescent suicidality may be important for prevention. We evaluated the feasibility and acceptability of a theatre-based gatekeeper teacher training for adolescent suicide prevention (SPES project). Self-reported changes in knowledge and self-efficacy were also investigated. Based on a quasi-experimental repeated measures design, secondary schools were invited to participate in one of two intervention groups (theatre workshop or attending a theatre performance) or a control group (no intervention). Assessments were conducted prior to the intervention, shortly following it and 3 months later. Attendance and retention were indicators of feasibility. Knowledge and self-efficacy were assessed longitudinally using anonymous questionnaires. Data were analyzed using linear mixed models. 191 teachers (84.3% women; Mage = 46.8, SD = 9.8) participated in the study (63 workshop, 66 performance and 62 control group). Attendance was 92% in the workshop group and 94% in the performance group. The retention rate after three months was 51% in the workshop group and 53% in the performance group. Teachers in both groups reported greater knowledge of adolescent suicide (p < 0.001) and higher gatekeeper self-efficacy (p < 0.05) than the control group. The SPES project was found to be feasible and acceptable. Both the workshop and the performance viewing may improve teachers’ knowledge and self-efficacy in recognizing signs of suicide risk in adolescents.
Raising Awareness for Sustainable Faecal Treatment Using Augmented Reality
Authors: Otaki Yurina , Honda Hidehito , Onuki Yutaro , Shinohara Gen , Otaki Masahiro , Chaminda Tushara
Published: December 2024

Pit latrines—the simplest on-site sanitation system—have been extensively used in developing countries in Asia for a long time. However, pit latrines are pollution and health risk hotspots that can cause widespread contamination. It is preferable to upgrade them to septic tanks, which are more advanced, effective, and simple alternatives. This study encourages the transition from pit latrines to septic tanks by making people aware of the health and environmental risks associated with the use of pit latrines. As decisions about sanitation technologies are mostly made by individual households, it is important to find communication tools for the average household to understand the basic information to make informed decisions. To this end, this study used augmented reality as a communication tool. A survey was conducted with Sri Lankan households that use pit latrines, and experiments were carried out in a university laboratory in Japan. The use of augmented reality increased people’s understanding of the environmental and health risks of pit latrines. This understanding was retained for some time because people found the use of augmented reality ‘enjoyable’. Hence, our findings contribute to the promotion of the transition from pit latrines to septic tanks in low- and middle-income countries.
Assessing the Polarising Impacts of Low-Traffic Neighbourhoods: A Community Perspective from Birmingham, UK
Authors: Whelan Isabelle , Luiu Carlo , Pope Francis D.
Published: December 2024

Globally, the transport sector is a major contributor to air pollution. Currently, in the UK, vehicle emissions contribute significant amounts of nitrogen oxide (NOx) and particulate matter (PM) pollution in urban areas. Low-emission-zone policies have been used as an intervention to tackle air pollution, and in this context, the UK launched the Low-Traffic Neighbourhood scheme. This study investigates the impacts of the Low-Traffic Neighbourhood in Kings Heath, Birmingham, UK, to evaluate its impact in reducing air pollution and local community perspectives about the scheme and perceived impacts on health and well-being. This study employs a mixed-method approach comprising an air-quality-monitoring assessment and a survey questionnaire involving 210 residents. The findings reveal an increase in active travel and a reduction in air pollution levels in the years after the implementation of the scheme, although the area is still non-compliant with the 2021 WHO air quality guidelines. Nonetheless, the scheme has a polarising effect and created a division within the local community about the overall scheme acceptance and spatial distribution of the scheme’s benefits. This study underscores the importance of comprehensive baseline data, long-term community engagement, and integration with broader urban planning initiatives to enhance the success of future Low-Neighbourhood Traffic schemes.
More Quality, Less Trust?
Authors: Dreyfuss Michael , Giat Yahel , Manes Eran
Published: December 2024

This study investigates how an increase in the quality of business ventures, measured as their success probability, affects trust and return on investment (ROI) in situations where the investor–entrepreneur interaction is affected by moral hazard and asymmetric information. We model a repeated trust problem between investors and entrepreneurs, featuring moral hazard and adverse selection. Hidden Markov techniques and computer simulations are used to derive the main results. We find that trust and ROI may decline as quality improves. Although lenders tend to reduce the requirements for granting initial credit, they nevertheless become less tolerant of current borrowers who fail to pay back. Additionally, we demonstrate a novel substitution effect, where lenders prefer new borrowers over existing borrowers that experienced early failures. The main conclusions of our study are that while impressing early on is effective in gaining first access to credit, it may nevertheless hurt the cause of getting credit in subsequent periods, following an early failure. In business environments plagued with ex post moral hazard, entrepreneurs might do better by gaining trust first and impressing later. Furthermore, our results imply that in a thriving economy, not only are bad loans made, but good loans are lost as well.
Genomic Prediction of Semen Traits in Boars Incorporating Biological Interactions
Authors: Chen Yantong , Yang Fang , Yang Yanda , Hu Yulong , Meng Yang , Zhang Yuebo , Ran Maoliang , He Jun , Yin Yulong , Gao Ning
Published: December 2024

In the context of modern pig farming, the central role of boars is underscored by large-scale centralized breeding and the widespread application of artificial insemination techniques. However, previous studies and breeding programs have focused mainly on product efficiency traits, such as growth rate, lean meat yield, and litter size, often neglecting boar semen traits. In this study, we estimated the genetic parameters and assessed the genomic prediction accuracy of boar semen traits with phenotypes evaluated from 274,332 ejections in a large population consisting of 2467 Duroc boars. Heritability of sperm morphological abnormality rate (ABN), fresh semen volume (VOL), sperm concentration (DEN), and motility (MOT) were estimated to be 0.43, 0.22, 0.23, and 0.16, respectively. GBLUP achieved a moderate predictive ability of semen traits, with a range of 0.32–0.50. Incorporating gene interactions indicated by the KEGG pathways (biBLUP) significantly improved predictive accuracy over the classical additive model (GBLUP) and epistatic model (RKHS). Moreover, biBLUP showed an improvement from 9.50% to 20.10% among the studied traits compared with GBLUP, with the greatest improvement (0.40 vs. 0.48) observed in sperm morphological abnormality rate. In conclusion, moderate to low heritability was estimated for the Duroc boar semen traits. Genomic prediction was able to achieve moderate accuracy, with a range from 0.32 to 0.56, for the studied traits. Considering gene interactions within KEGG pathways enhanced the predictive ability of boar semen traits.
Unveiling the Role of β-Glucosidase Genes in Bletilla striata’s Secondary Metabolism: A Genome-Wide Analysis
Authors: Xu Mengwei , Li Hongwei , Luo Hongyuan , Liu Jingyi , Li Kunqian , Li Qingqing , Yang Ning , Xu Delin
Published: December 2024

β-glucosidases (BGLUs) are abundant enzymes in plants that play pivotal roles in cell wall modification, hormone signal transduction, secondary metabolism, defense against herbivores, and volatile compound release. Bletilla striata, a perennial herb revered for its therapeutic properties, lacks a comprehensive analysis of its BGLU gene family despite the critical role these genes play in plant secondary metabolism. This study aims to perform a genome-wide analysis of the BGLU gene family in B. striata (BsBGLU) to elucidate their functions and regulatory mechanisms in secondary metabolite biosynthesis. We conducted a genome-wide screening to identify BsBGLU, followed by phylogenetic analysis to classify these genes into groups. Sequence characteristics were analyzed to predict functional roles. Simple sequence repeat (SSR) markers were examined to assess conservation and polymorphism among different landraces. Expression profiles of BsBGLUs were evaluated under sodium acetate and salicylic acid elicitor treatments and across different tissues. The accumulation of phylogenetic metabolites in different treatments and tissues was also analyzed by HPLC and LCMS detection to explore the correlation between gene expression and metabolite accumulation. A total of 23 BsBGLU genes were identified and classified into eight distinct groups. Sequence analysis suggested diverse functions related to hormone responses, secondary metabolism, and stress resistance. BsBGLUs with SSR sequences were conserved yet showed polymorphism among different B. striata landraces. Under elicitor treatments, expression profiling revealed that BsBGLUs significantly modulate the synthesis of secondary metabolites such as dactylorhin A and militarine. Tissue-specific expression analysis indicated that BsBGLU15 and BsBGLU28 were highly expressed in tubers compared to other tissues, suggesting their central role and a potential negative regulatory effect in metabolite accumulation. The elicitor NaAc can regulate metabolite synthesis by modulating the expression of BsBGLUs. The BsBGLU gene family in B. striata is integral to the modulation of secondary metabolite biosynthesis and accumulation and can respond to elicitors to promote the synthesis of militarine. These findings provide a theoretical foundation for the further exploration of BsBGLU gene functions and their regulatory mechanisms, advancing the production of medicinally active compounds in B. striata.
Discovery of a Small Molecule with an Inhibitory Role for RAB11
Authors: Lempicki Camille , Milosavljevic Julian , Laggner Christian , Tealdi Simone , Meyer Charlotte , Walz Gerd , Lang Konrad , Campa Carlo Cosimo , Hermle Tobias
Published: December 2024

RAB11, a pivotal RabGTPase, regulates essential cellular processes such as endocytic recycling, exocytosis, and autophagy. The protein was implicated in various human diseases, including cancer, neurodegenerative disorders, viral infections, and podocytopathies. However, a small-molecular inhibitor is lacking. The complexity and workload associated with potential assays make conducting large-scale screening for RAB11 challenging. We employed a tiered approach for drug discovery, utilizing deep learning-based computational screening to preselect compounds targeting a specific pocket of RAB11 protein with experimental validation by an in vitro platform reflecting RAB11 activity through the exocytosis of GFP. Further validation included the exposure of Drosophila by drug feeding. In silico pre-screening identified 94 candidates, of which 9 were confirmed using our in vitro platform for Rab11 activity. Focusing on compounds with high potency, we assessed autophagy, which independently requires RAB11, and validated three of these compounds. We further analyzed the dose–response relationship, observing a biphasic, potentially hormetic effect. Two candidate compounds specifically caused a shift in Rab11 vesicles to the cell periphery, without significant impact on Rab5 or Rab7. Drosophila larvae exposed to another candidate compound with predicted oral bioavailability exhibited minimal toxicity, subcellular dispersal of endogenous Rab11, and a decrease in RAB11-dependent nephrocyte function, further supporting an inhibitory role. Taken together, the combination of computational screening and experimental validation allowed the identification of small molecules that modify the function of Rab11. This discovery may further open avenues for treating RAB11-associated disorders.
Contribution of Sex Differences to Development of Cardiovascular Disease in Metabolic-Associated Steatotic Liver Disease (MASLD)
Authors: Taylor Lucy C. , Arthur Gertrude , de Carvalho Cruz Marcella , Stec David E. , Badmus Olufunto O.
Published: December 2024

Sex differences are a complex and crucial variable in developing and progressing metabolic and cardiovascular disease pathophysiology and clinical outcomes. The female sex, compared to the male sex, is protected from metabolic disturbances and their resulting cardiovascular events. However, the peculiar life phases associated with females, such as puberty, pregnancy, and premenopausal and menopausal stages, are all associated with different risks for the development of cardiovascular disease (CVD). Metabolic dysfunction-associated steatotic liver disease (MASLD), a condition of hepatic steatosis, and at least one feature of metabolic syndrome is associated with an increased risk of cardiovascular events. The risk of MASLD and its progression to the development of CVD differs between men and women. Differences in several factors, including formyl peptide receptor (FPR) 2, adipose tissue distribution, liver pyruvate kinase (LPK), and ketone body production, may underlie the sex differences in the risk of development of MASLD-induced CVD. Understanding the specific risk factors involved in the development and progression of MASLD between the sexes is crucial. This knowledge will provide important insights into the mechanisms responsible for its cardiovascular complications and can potentially lead to therapeutics targeted explicitly for each sex, offering new hope in the fight against MASLD-induced CVD.
Model Optimization and Dynamic Analysis of Inventory Management in Manufacturing Enterprises
Authors: Lei Tengfei , Li Rita Yi Man , Deeprasert Jirawan
Published: December 2024

This study investigates inventory management systems using a sample of listed manufacturing companies in China from 2019 to 2023. By constructing a static mathematical model, the impact of inventory management on corporate performance was empirically tested. Additionally, based on a classical inventory management dynamical model and considering inventory delay characteristics, a new class of two-dimensional inventory management systems was reconstructed. The system’s periodic and chaotic nonlinear characteristics were verified using 0-1 tests, bifurcation diagrams, Lyapunov exponents, and system eigenvalue plots. Furthermore, MATLAB simulations were employed to examine the effect of resource transfer rates on the nonlinear dynamic behavior of the inventory management system. The results from both static mathematical models and dynamical models provide a theoretical basis for inventory management and safety stock level predictions in the manufacturing industry.
Evolving Strategies in Machine Learning: A Systematic Review of Concept Drift Detection
Authors: Hovakimyan Gurgen , Bravo Jorge Miguel
Published: December 2024

In this comprehensive literature review, we rigorously adhere to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for our process and reporting. This review employs an innovative method integrating the advanced natural language processing model T5 (Text-to-Text Transfer Transformer) to enhance the accuracy and efficiency of screening and data extraction processes. We assess strategies for handling the concept drift in machine learning using high-impact publications from notable databases that were made accessible via the IEEE and Science Direct APIs. The chronological analysis covering the past two decades provides a historical perspective on methodological advancements, recognizing their strengths and weaknesses through citation metrics and rankings. This review aims to trace the growth and evolution of concept drift mitigation strategies and to provide a valuable resource that guides future research and deepens our understanding of this rapidly changing field. Key findings highlight the effectiveness of diverse methodologies such as drift detection methods, window-based methods, unsupervised statistical methods, and neural network techniques. However, challenges remain, particularly with imbalanced data, computational efficiency, and the application of concept drift detection to non-tabular data like images. This review aims to trace the growth and evolution of concept drift mitigation strategies and provide a valuable resource that guides future research and deepens our understanding of this rapidly changing field.
Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia
Authors: Ilyas Mahwish , Bilal Muhammad , Malik Nadia , Khan Hikmat Ullah , Ramzan Muhammad , Naz Anam
Published: December 2024

Medical diagnosis plays a critical role in the early detection and treatment of diseases by examining symptoms and supporting findings through advanced laboratory testing. Early and accurate diagnosis is essential for detecting medical problems and then prescribing the most effective treatment strategies, especially in life-threatening diseases such as leukemia. Leukemia, a blood malignancy, is one of the most prevalent cancer types affecting both adults and children. It is caused by the rapid and uncontrolled growth of abnormal white blood cells in the bone marrow. This accumulation interferes with the production of normal blood cells, leading to a weakened immune deficiency, anemia, and bleeding disorders. Conventional leukemia diagnostic methods are time-consuming, manually intensive, and inefficient. This research study proposes an automatic diagnostics prediction of leukemia by analyzing blood images according to the shape of the blast cells using digital image processing and machine learning. The purpose of blood cell detection is to precisely identify and classify diverse blood cells, detecting anomalies associated with blood cancers like leukemia. This supports early diagnosis and monitoring, which leads to more effective treatments and improved results for cancer patients. To accomplish this task, we use digital image processing techniques and then apply the convolutional neural network (CNN) deep learning algorithm to blood sample images. This research employs a multi-stage methodology, including data preparation, data preprocessing, feature extraction, and then classification. While our model is built on a typical CNN architecture, we make significant advances by using preprocessing techniques and hyperparameter tuning. We have modified its layers combination to include convolutional, pooling, and fully connected layers that are optimized for image characteristics. These layers are fine-tuned for better feature extraction and classification accuracy. This study showed that blood cell detection for diagnosing acute leukemia based on images had 99% accuracy and outperformed other advanced models, including DenseNet121, ResNet-50, Incep-tionv3, MobileNet, and EfficientNet. The comprehensive analysis of the results reveals the highest accuracy of leukemia detection as compared to existing studies in the relevant literature.
Application of ResUNet-CBAM in Thin-Section Image Segmentation of Rocks
Authors: Zhao Ling , Zhang Huili , Sun Xianda , Ouyang Zhaozhuo , Xu Chengwu , Qin Xudong
Published: December 2024

The convolutional neural network (CNN) algorithm in deep learning has been widely applied in petroleum geology research both domestically and internationally. Automated and accurate segmentation of thin-section images of rocks is foundational for in-depth analysis. However, traditional segmentation methods for reservoir rock thin sections often suffer from low accuracy and high cost. To address these issues, this paper proposes a novel segmentation algorithm based on an improved UNet network, integrating residual networks and the CBAM attention mechanism. By incorporating residual modules, the network depth is expanded, and the CBAM attention mechanism enhances the feature weighting capability during learning. Experimental results demonstrate that this method outperforms traditional approaches in both segmentation accuracy and efficiency, representing significant advancements in reservoir rock thin-section image segmentation.
A Yoga Pose Difficulty Level Estimation Method Using OpenPose for Self-Practice System to Yoga Beginners
Authors: Shih Cheng-Liang , Liu Jun-You , Anggraini Irin Tri , Xiao Yanqi , Funabiki Nobuo , Fan Chih-Peng
Published: December 2024

Yoga is an exercise preferable for various users at different ages to enhance physical and mental health. To help beginner yoga self-practitioners avoid getting injured by selecting difficult yoga poses, the information of the difficulty level of yoga poses is very important to provide an objective metric to assist yoga self-practitioners in selecting appropriate exercises on the basis of their skill level by using the yoga self-practice system. To enhance the developed yoga self-practice system, the yoga difficulty level estimation function will enable users to clearly understand whether the selected yoga poses are suitable for them. In this paper, the newest difficulty level estimation method of yoga poses is proposed by using and analyzing OpenPose two-dimensional (2D) human body keypoints. The proposed method effectively uses the selected six keypoints areas of the upper and lower body, body support types, center of gravity calculations, and body tilt angles and slopes to produce estimations. Firstly, the method calculates the weighted centers of the upper and lower human body for each pose by using keypoints. Secondly, it refers the slope of the centroid line between the two centers and infers the body’s balance state. Lastly, the system estimates the difficulty level by additionally considering the keypoints of the body to contact the ground. For evaluations of the proposal, more than one hundred yoga poses are collected from the Internet and applied to classify them into five difficulty levels. Through comparisons with subjective levels from one instructor and 10 users, the validity of the estimation results is confirmed, a comparison is performed with existing designs, and it is implemented in embedded systems.
The Introduction of a New Mobile Driving Unit for a Ventricular Assist Device in a Pediatric Patient (EXCOR Active)
Authors: Ünesen Nuri , Balmer Christian , Schweiger Martin
Published: December 2024

Pediatric patients supported by extracorporeal ventricular assist devices traditionally require long-term stationary inpatient settings. Limited mobility and permanent hospitalization significantly reduce their quality of life. Berlin Heart address this with their novel mobile driving unit, EXCOR® Active. This case report presents its first application outside of Germany, where it was developed, focusing on staff education and safety measures leading to a successful switch of driving units.
Hands-On Robotic Microsurgery: Robotic-Assisted Free Flap Reconstruction of the Upper Extremity
Authors: Struebing Felix , Bigdeli Amir Khosrow , Boecker Arne , Weigel Jonathan , Kneser Ulrich , Gazyakan Emre
Published: December 2024

Background/Objectives: Robot-assisted microsurgery (RAMS) has been introduced into the field of plastic surgery in recent years. It potentially offers enhanced precision and control compared to traditional methods, which is crucial for complex microvascular tasks in free flap reconstructions. We aim to analyze our experiences with robotic-assisted microsurgery in the field of upper extremity free flap reconstruction. Methods: This prospective study evaluated the efficacy and safety of the Symani Surgical System for free flap reconstructions in 16 patients with upper extremity defects at our institution from February 2023 to March 2024. Operating times were compared to a matched, historical cohort. We collected data on surgical outcomes, operative times, and complication rates, following strict adherence to the Declaration of Helsinki. Results: Our cohort primarily involved male patients (81%) with defects mostly located on the hand (81%). The anterolateral thigh flap was the most commonly used free flap (14/16, 88%). The average operative time was 368 ± 89 min (range: 216–550 min). No complete or partial flap losses were observed, but one flap required revision surgery due to arterial thrombosis. Major complications occurred in 13% of the cases. The average anastomosis time was 31 ± 12 min (range: 20–35 min) for arterial end-to-end anastomoses and 33 ± 13 min (range: 20–60 min) for arterial end-to-side anastomoses. Venous anastomoses required, on average, 20 ± 6 min. Operating times were not significantly longer when compared to the historical cohort (p = 0.67). Conclusions: We were able to show comparable outcomes to conventional microsurgery, while requiring more time for the microsurgical anastomoses. The study highlights the need for larger, controlled trials to better understand the benefits and limitations of robotic assistance in microsurgical reconstruction of the upper extremity.
There Is Significant Within-Subject Variation in the Time from Light Stimulus to Maximum Pupil Constriction Among Healthy Controls
Authors: Kamal Abdulkadir , Kim Yohan , Salter Amber , Gunna Shripal , Nairon Emerson B. , Olson DaiWai M.
Published: December 2024

Background: Handheld quantitative pupilometers (QPs) measure each phase of the pupillary light reflex (PLR) and provide a summary score based on these values. One phase of the PLR is the period of time from the onset of light exposure to the maximum constriction of the pupil, also known as time to maximum constriction (tMC). Although tMC has been found to vary significantly among patients with neurological injury, there are no studies reporting tMC in healthy controls. This study addresses this gap. Methods: Subjects in this prospective observational study were healthy controls who provided paired (left and right eye) QP readings during four separate observations over the course of 2 days. The tMC was derived by determining the smallest observed pupil size during videos filmed at 30 frames per second, and we assessed within-subject variability using the coefficient of variance and intraclass correlation coefficient (ICC). Results: Fifty subjects provided 380 QP readings (190 left eye and 190 right eye). Subjects primarily identified as female (80%), non-Hispanic (86%), white (62%), and <40 years old (74%). The mean tMC was 1.0 (0.14) seconds (s) for the left eye and 1.0 (0.17) s for the right eye; the coefficient of variance ranged from 11.6% to 18.8% and the ICC ranged from 0.25 to 0.40. For the between-subject comparisons across the four observation periods, the left and right eye mean differences ranged from 0.001 to 0.063 and the ICC ranged from 0.12 to 0.52. Conclusions: The tMC values vary significantly in healthy controls. Changes in pupil function as a clinical biomarker of intracranial pathology are not fully understood. Identifying clinical correlations of tMC variation may provide insight for the prognostication and treatment of neurocritically ill patients.
Comparing Prescribing Behaviors and Clinician Experiences Between Multiplex PCR/Pooled Antibiotic Susceptibility Testing and Standard Urine Culture in Complicated UTI Cases
Authors: Haley Emery , Luke Natalie , Korman Howard , Rao Ganesh Srinvas , Baunoch David , Chen Xiaofei , Havrilla Jim , Mathur Mohit
Published: December 2024

Background/Objectives: We aimed to compare the prescribing behavior and clinical experience of urology providers when using the combined multiplex polymerase chain reaction (M-PCR)/Pooled Antibiotic Susceptibility Testing (P-AST) diagnostic test versus the standard urine culture (SUC) in the same set of patients previously reported to have improved clinical outcomes with M-PCR/P-AST. Methods: We conducted a multi-centered, prospective, observational study (clinical trial registration: NCT05091931) with Western Institutional Review Board (IRB) approval (20214705). Adult subjects were split between the M-PCR/P-AST (n = 250) and SUC arms (n = 135). Treatment details were determined by clinician and subject surveys. Differences in prescribed antibiotics were compared using the Chi-square or Fisher’s exact test. Results: There was no significant difference in the overall use of “access” antibiotics (p = 1.0) or first-line drugs (p = 0.4483) between M-PCR/P-AST and SUC. Nitrofurantoin (p = 0.0172) and metronidazole (p = 0.0309) were more frequently used with M-PCR/P-AST, while amoxicillin/clavulanate (p = 0.0008), cefuroxime (p = 0.0378), and ertapenem (p = 0.0378) were more frequently used with SUC. Conclusions: The use of M-PCR/P-AST to guide complicated UTI management was not associated with the increased use of non-first-line antibiotics, such as carbapenems, compared to SUC. Combined with the prior reported evidence of improved patient outcomes in this same set of patients, this test should be considered for utilization when managing complicated UTI cases.
Levels of Anxiety, Depression, Self-Esteem, and Guilt in Women with High-Risk Pregnancies
Authors: Tuncer Can Sevim , Yildiz Sevler , Torun Raziye , Omeroglu Ibrahim , Golbasi Hakan
Published: December 2024

Objectives: Pregnancy is an inherently delicate process characterized by physiological and psychological changes, even in the absence of any health complications. This study compares the levels of anxiety, depression, self-esteem, and guilt in women diagnosed with high-risk pregnancies to those in a control group consisting of women with healthy pregnancies. Methods: A total of 172 women participated in the study, 108 of whom had high-risk pregnancies, and 64 had healthy pregnancies. All participants were administered a semi-structured Sociodemographic Data Form, Beck Depression Inventory (BDI), Beck Anxiety Scale (BAI), Rosenberg Self-Esteem Scale (RSES), and Guilt Inventory (GI). The findings were statistically analyzed and compared. Results: Women with high-risk pregnancies had significantly higher scores on the BAI (p = 0.002), BDI (p = 0.035), and GI (p = 0.001) compared to the control group. In the logistic regression analysis for calculating the risk of high-risk pregnancy, the multivariate analysis revealed that living in rural areas posed 3.5 times higher risk for high-risk pregnancy compared to urban living (OR = 3.500, 95% CI = 1.484–8.254). Additionally, for every one-point increase in the GI score, the risk of high-risk pregnancy increased by 1.064 times (OR = 1.064, 95% CI = 1.017–1.114). In the patient group, significant positive correlations were found between the BAI score and BDI, RSES, and GI scores, while a significant negative correlation was observed between BAI and parity. There were also significant positive correlations between the BDI and RSES as well as the GI scores. Additionally, a positive significant correlation was found between the RSES and GI scores. Conclusions: Our findings may help in identifying the psychological states of women with high-risk pregnancies and
Bedside Assessment of the Respiratory System During Invasive Mechanical Ventilation
Authors: Giosa Lorenzo , Collins Patrick D. , Shetty Sridevi , Lubian Marta , Del Signore Riccardo , Chioccola Mara , Pugliese Francesca , Camporota Luigi
Published: December 2024

Assessing the respiratory system of a patient receiving mechanical ventilation is complex. We provide an overview of an approach at the bedside underpinned by physiology. We discuss the importance of distinguishing between extensive and intensive ventilatory variables. We outline methods to evaluate both passive patients and those making spontaneous respiratory efforts during assisted ventilation. We believe a comprehensive assessment can influence setting mechanical ventilatory support to achieve lung and diaphragm protective ventilation.
Biochemical Sensors for Personalized Therapy in Parkinson’s Disease: Where We Stand
Authors: Ciarrocchi Davide , Pecoraro Pasquale Maria , Zompanti Alessandro , Pennazza Giorgio , Santonico Marco , di Biase Lazzaro
Published: December 2024

Since its first introduction, levodopa has remained the cornerstone treatment for Parkinson’s disease. However, as the disease advances, the therapeutic window for levodopa narrows, leading to motor complications like fluctuations and dyskinesias. Clinicians face challenges in optimizing daily therapeutic regimens, particularly in advanced stages, due to the lack of quantitative biomarkers for continuous motor monitoring. Biochemical sensing of levodopa offers a promising approach for real-time therapeutic feedback, potentially sustaining an optimal motor state throughout the day. These sensors vary in invasiveness, encompassing techniques like microdialysis, electrochemical non-enzymatic sensing, and enzymatic approaches. Electrochemical sensing, including wearable solutions that utilize reverse iontophoresis and microneedles, is notable for its potential in non-invasive or minimally invasive monitoring. Point-of-care devices and standard electrochemical cells demonstrate superior performance compared to wearable solutions; however, this comes at the cost of wearability. As a result, they are better suited for clinical use. The integration of nanomaterials such as carbon nanotubes, metal–organic frameworks, and graphene has significantly enhanced sensor sensitivity, selectivity, and detection performance. This framework paves the way for accurate, continuous monitoring of levodopa and its metabolites in biofluids such as sweat and interstitial fluid, aiding real-time motor performance assessment in Parkinson’s disease. This review highlights recent advancements in biochemical sensing for levodopa and catecholamine monitoring, exploring emerging technologies and their potential role in developing closed-loop therapy for Parkinson’s disease.
Size Does Matter: Mastectomy Flap Thickness as an Independent Decisional Factor for the Peri-Prosthetic Device Choice in Prepectoral Breast Reconstruction
Authors: Kaciulyte Juste , Sordi Silvia , Luridiana Gianluigi , Marcasciano Marco , Lo Torto Federico , Cavalieri Enrico , Codolini Luca , Cuomo Roberto , Rozen Warren Matthew , Seth Ishith , Ribuffo Diego , Casella Donato
Published: December 2024

Background. In alloplastic breast reconstruction, the choice of implant positioning and the selection of periprosthetic devices is a critical and challenging decision. Surgeons must navigate between various biologic and synthetic meshes, including acellular dermal matrices (ADM). This study aimed to propose a simple selection tool for periprosthetic devices in prepectoral breast reconstruction. Methods. Patients scheduled for mastectomy followed by implant-based breast reconstruction between September 2019 and December 2023 were included. Preoperative risk assessments were performed using the Pre-Bra Score, and only those deemed suitable for prepectoral implant placement were selected. Mastectomy flap thickness was used as an independent criterion, and only cases with flap thicknesses less than 1 cm were included. Results. A total of 70 cases with an average flap thickness of 0.7 cm (range, 0.4–0.9 cm), as measured by preoperative contrast-enhanced spectral mammography (CESM), underwent prepectoral reconstruction with ADM covering the implant. Of these, 25 patients (35%) received direct-to-implant reconstruction, while 45 (65%) underwent two-stage reconstruction with a temporary tissue expander. Postoperative complications were recorded during a minimum follow-up period of 6 months. Over an average follow-up duration of 17.5 months (range 6–36 months), no major complications were observed. Minor complications occurred in seven patients: infection (1.28%), seroma (3.85%), and superficial skin necrosis (1.28%). Additionally, 21 patients (30%) experienced rippling, and secondary lipofilling was scheduled. Conclusions. The incidence of rippling was reduced by 40% through ADM in this patient subgroup, reducing the need for secondary aesthetic refinements.
Analysing Digital Engagement Patterns: A Machine Learning Investigation into Social Anxiety Among Adolescents with ADHD
Authors: Șipoș Roxana , Văidean Tudor , Răpciuc Andreea-Marlena , Poetar Costina-Ruxandra , Predescu Elena
Published: December 2024

Background: The relationship between screen time and mental health among adolescents, particularly those identified as “digital natives”, has become increasingly pertinent, especially in the context of heightened digital engagement during the COVID-19 pandemic. This study aims to examine the associations between digital engagement patterns, ADHD severity, and anxiety symptoms in adolescents aged 11–18. Methods: A cross-sectional observational study was conducted with a sample of 97 adolescents diagnosed with ADHD. Participants completed validated questionnaires assessing daily digital activities and anxiety symptoms while caregivers provided additional contextual information. Data were analyzed using Random Forest regression to identify relationships between screen time, ADHD severity, and anxiety symptoms. Results: The findings indicate an average screen time of 6.6 h on weekdays and 8.1 h on weekends, with social media emerging as the primary activity, particularly among female participants. Notable gender differences were identified, with family dynamics influencing digital engagement; family disputes had a more significant impact on girls than boys. Furthermore, specific anxiety traits, i.e., physical symptoms and harm avoidance, significantly predicted time spent on social media across all genders considered in the study, while others, namely social anxiety and separation anxiety, were less valuable. Conclusions: This study highlights the complex interplay between screen time, ADHD, and anxiety symptoms in adolescents. These findings underscore the importance of tailored interventions that address the nuanced relationships between digital engagement and mental health in this population, warranting further research to develop effective management strategies.
Nationwide Cross-Sectional Analysis of Mortality Trends in Patients with Sarcoidosis and Non-Ischemic Cardiovascular Disease—The Impact of Gender, Ethnicity, Geographical Location, and COVID-19 Pandemic
Authors: Ahmed Raheel , Ahmed Mushood , Khlidj Yehya , Rehman Obaid Ur , Al-Mukhtar Laith , Abou Khater Noha , Khurram Mustaq Gardezi Syed , Rashid Muhammad , Collins Peter , Jain Hritvik , Ramphul Kamleshun , Baig Mudassar , Chahal Anwar , Kouranos Vasilis , Behary Paray Nitish , Sharma Rakesh
Published: December 2024

Background and Objectives: The epidemiological data regarding mortality rates of adults with sarcoidosis and non-ischemic cardiovascular disease (CVD) are limited. A retrospective observational analysis was conducted to identify trends and disparities related to sarcoidosis and non-ischemic cardiovascular disease mortality among the adult US population from 1999 to 2022. Methods: We used the Centers for Disease Control and Prevention (CDC) WONDER database to extract death certificate data for the adult US population (≥25 years). The age-adjusted mortality rates (AAMRs) per 100,000 persons were calculated, and annual percent changes (APCs) were determined using Joinpoint. Results: Between 1999 and 2022, 23,642 deaths were identified related to non-ischemic CVD + sarcoidosis. The overall AAMR increased from 0.2 (95% CI, 0.2 to 0.3) in 1999 to 0.5 (95% CI, 0.5 to 0.6) in 2022. Females had a higher AAMR than males (0.6 vs. 0.5). Non-Hispanic (NH) blacks had the highest AAMR, followed by NH whites and Hispanic or Latinos. The southern region had the highest AAMR (0.7: 95% CI, 0.6–0.7), followed by the Midwest (0.6, 95% CI, 0.54–0.669), the Northeast (0.5, 95% CI, 0.5 to 0.6), and the West (0.4; 95% CI, 0.3–0.4). Urban and rural areas had comparable mortality rates (0.5 vs. 0.6). People aged 65+ had the highest AAMRs. Conclusions: The overall mortality rates for non-ischemic CVD and sarcoidosis have increased in the US from 1999 to 2022. Females and NH blacks had higher AAMRs, while a minimal variation was observed based on geographical regions. Early diagnosis and prompt management are the keys to reducing the mortality burden of non-ischemic CVD plus sarcoidosis.
Rapunzel Syndrome: Clinical, Diagnostic and Forensic Aspects in Related Deaths—A Review of the Literature
Authors: Sacco Matteo Antonio , Gualtieri Saverio , Princi Aurora , Tarda Lucia , Tarallo Alessandro Pasquale , Calanna Luca , Lombardo Stefano , Calafiore Jasmine , Gratteri Santo , Aquila Isabella
Published: December 2024

Background: Rapunzel syndrome is a rare and severe form of trichobezoar, characterized by the presence of hair masses in the stomach that often extend into the bowel, resembling the legendary “Rapunzel’s” long hair. Methods: This review examines the clinical, diagnostic, forensic, and post-mortem aspects associated with Rapunzel syndrome, with a focus on cases resulting in mortality or those at high risk of death due to complications. In particular, the review systematically analyzes the existing literature on fatal cases of Rapunzel syndrome, emphasizing insights into risk factors, clinical manifestations, diagnostic methods, autopsy findings, and preventive measures to provide a focused understanding of these critical aspects. Results: The syndrome predominantly affects young females with a history of trichotillomania (hair-pulling) and trichophagia (hair-eating), often associated with underlying psychiatric conditions. Clinically, Rapunzel syndrome presents with non-specific gastrointestinal symptoms, including abdominal pain, vomiting, and malnutrition, which may complicate timely diagnosis. Diagnosis typically involves imaging techniques such as ultrasound, CT scans, and endoscopy, but cases often go unrecognized until complications like intestinal obstruction, perforation, or even fatal outcomes occur. Forensically, Rapunzel syndrome presents unique challenges, as misdiagnosis or delayed intervention can lead to fatalities that may raise questions in medico-legal investigations. Post-mortem investigations, particularly autopsies, have proven instrumental in elucidating rare complications and advancing understanding of the syndrome’s long-term effects. Conclusions: Increased awareness, timely diagnosis, and comprehensive evaluation, including autopsy studies, are essential to improve patient outcomes and reduce the potential for life-threatening complications in this rare yet serious condition.
Implications of Preoperative C-Reactive Protein Levels in Heart Transplant Patients—A Single-Center Retrospective Study
Authors: Huma Laurentiu , Suciu Horatiu , Avram Calin , Suteu Radu-Adrian , Danilesco Alina , Baba Dragos-Florin , Moldovan Diana-Andreea , Sin Anca-Ileana
Published: December 2024

Background: Heart transplant is the final therapeutic option for end-stage heart failure patients. It has been used with increasing success as a surgical procedure, greatly influenced by advances in diagnostic and prognostic tools. The aim of this paper was to study potential implications of C-reactive protein (CRP) in patients who underwent heart transplants. Methods: Our cohort included 43 adult patients from the Emergency Institute for Cardiovascular Diseases and Transplant of Târgu Mureș who underwent heart transplants in our center between 2011 and 2023. Correlations between CRP levels and different characteristics of the patients were investigated, and the optimal cut-off value for CRP levels in relation to the 6-month mortality rate was determined. The central tendencies of the baseline characteristics of patients who had a CRP value lower than the cut-off and those with a value higher than it were compared using parametric or nonparametric tests. Results: Significant correlations between the preoperative CRP levels and 6-month mortality rate (r = 0.35; 95%CI: 0.05–0.60; p = 0.02), as well as previous cardiac resynchronization therapy (CRT) and preoperative CRP levels (r = −0.37; 95%CI: −0.61–−0.07, p = 0.01) were highlighted. A value for CRP > 1.66 mg/dL was found to be associated with 6-month mortality (OR = 18.00; 95%CI: 1.90–170.33, p < 0.01). Moreover, the patients who received CRT before transplantation had significantly lower levels of CRP when compared to those who did not receive CRT (p = 0.01). Conclusions: Preoperative CRP levels could represent a valuable asset in the follow-up algorithm of heart transplant patients. The lower levels of CRP in patients who benefited from CRT before transplantation highlights the importance of understanding the complex mechanisms of inflammation and increasing focus on device therapy for future transplant recipients. Further prospective studies with larger cohorts are needed for validation.
Association Between Obesity and Intra-Abdominal Solid Organ Damage in Patients with Blunt Abdominal Trauma: A Cross-Sectional Study
Authors: Chung Jae Sik , An Sanghyun , Moon Hyeun Eui , Kim Yonsu , Chung Tae-Ha
Published: December 2024

Background/Objectives: The global prevalence of obesity continues to rise. However, whether obesity affects the degree of intra-abdominal solid organ damage following blunt trauma remains unclear. This study aimed to investigate the correlation between obesity and intra-abdominal solid organ damage. Methods: This cross-sectional study was conducted at a regional trauma center in the Republic of Korea from January 2018 to December 2022 and included 582 patients aged 18–98 years with blunt abdominal trauma. Patients were categorized into four groups—underweight, normal weight, overweight, and obesity—based on their body mass index (BMI). Odds ratios (ORs), beta coefficients, and 95% confidence intervals (CIs) for intra-abdominal organ damage were calculated across BMI categories using multiple logistic regression analysis after adjusting for the confounding variables. Results: The obesity group exhibited a significant decrease in the prevalence of liver injury (OR: 0.553, CI: 0.316 to 0.966) and a reduction in liver injury severity (β: −0.214, CI: −0.391 to −0.037) compared with the normal-weight group after adjusting for the confounding factors. However, no significant association was observed between the BMI and injuries to other solid organs, such as the spleen, pancreas, and kidneys. Additionally, the younger obesity group (participants aged < 45 years) exhibited a significant negative association with both liver injury and injury grade. However, the older obesity group (participants aged > 65 years) exhibited a statistically significant association only with the liver injury grade compared with the normal-weight group. Conclusions: Obesity can serve as a predictive factor for the presence and severity of liver damage caused by blunt abdominal trauma.