bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of shear wave elastography in early prediction of response to neaodjuvant chemotherapy in cases of breast cancer
Authors: Elmoghazy Alaa Mohamed Ahmed Elmosselhy , Nada Omina Mokhtar , Beshir Manal Mohamed Refaat , Elhakim Rehab Ahmed Elbadri , Hashem Tarek Mohamed , Mansour Osman Mohamed , Radwan Amira Hamed 
Published: July 2023

Abstract
Background
Breast cancer is the most common malignant tumor and the commonest cause of death in female between 35 and 55 years of age. Neoadjuvant chemotherapy (NACT) is used in large scale nowadays in management of breast cancer. Recent studies propose that shear wave elastography (SWE) can early predict tumor therapy response during NACT for invasive breast cancer.

Aim of work
To study the ability of SWE to predict pathological complete response (pCR) during NACT as early as first cycle.

Subjects and methods
The study analyzed data of 48 patients breast cancer who were scheduled for receiving NACT before surgery. During treatment, SWE examination was done at first four cycles.

Results
Forty-eight breast cancer cases were included in the study with one hundred and ninety two examinations done. The cutoff point of stiffness ratio percent change post-first cycle in differentiating pCR and npCR groups was − 20% (AUC 0.755, sensitivity 81.8%, specificity 61.5%). The cutoff point of stiffness ratio percent change post-second cycle in differentiating pCR and npCR groups was − 49% (AUC 0.741, sensitivity 72.7%, specificity 76.9%). The stiffness ratio could predict pCR in early cycles of NACT.

Conclusions
US using shear wave elastography is an available, cheap, non-contrast, non-ionizing radiation method that predicts pCR in cases of breast cancer at neoadjuvant setting as early as first cycle.
Adaptive IIR model identification using chaotic opposition-based whale optimization algorithm
Authors: Dey Souvik , Roy Provas Kumar , Sarkar Angsuman 
Published: July 2023

AbstractInfinite impulse response (IIR) filter system recognition is a serious issue nowadays as it has many applications on a diversity of platforms. The whale optimization algorithm (WOA) is a novel nature-motivated population-based meta-heuristic algorithm where the hunting techniques of humpback whales are implemented to solve many optimization problems. But the main disadvantage of WOA is its stagnant convergence rate. As the algorithm is population based, the initialization process is very important in finding the best result and to enhance the convergence rate. In this paper, a novel chaotic oppositional-based initialization process is nominated before the start of conventional WOA to improve the performance. To effectively cover the entire search region, a chaotic-based logistic population map consists of both the actual numbers and its corresponding opposite numbers are incorporated into this opposition-based initialization process. When checked out with some classic model of examples, simulation performance authorizes chaotic oppositional-based whale optimization algorithm (COWOA) as a more convenient contender compared to the other evolutionary techniques in terms of accuracy and convergence speed. Convergence profile and mean square error are the performance specifications that are needed to inspect the performance of our recommended algorithm.
Transformer faults in tanzanian electrical distribution networks: indicators, types, and causes
Authors: Mbembati Hadija , Bakiri Hussein A. 
Published: July 2023

AbstractTransformers are essential and costly components of electrical secondary distribution networks (ESDNs). Distribution transformers provide electricity to low-voltage consumers that need a consistent power supply for their daily tasks. Transformer faults have an impact on ESDN power reliability. Even though several studies have attempted to investigate fault parameters; types, causes, and indicators in transformers, it is still difficult to generalize these criteria based on diversifications. These diversifications are caused by the architecture of the ESDN itself, transformer type, and insulation materials. Therefore, this paper investigates fault types, causes, and indicators specifically on oil-based transformers in Tanzania’s ESDN using the oil analysis technique and the Dissolved Gas Analysis (DGA) tool based on descriptive statistical analysis. Results show that cellulose deterioration accounted for 33.2% of all faults, and the leading causes are overload, aging, and moisture content. Despite cellulose deterioration issues, the arcing fault is 26.2% caused by trippings, short circuits, and flashovers. The outcome of this work may help the utility implement a more advanced monitoring tool and maintenance mechanisms to enhance power reliability and reduce transformer faults in ESDN.
Retrospective study of congenital airway malformations detected by flexible fiberoptic bronchoscopy in Alexandria University Children’s Hospital
Authors: Abdellah Lina Mortada , Faseeh Nader Abdelmoneim , Abougabal Mohamed Saeed , Farag Marwa Mohamed 
Published: July 2023

Abstract
Background
Congenital airway malformations affect the quality of life and increase the family burden. The care of children who have these lesions requires considerable expenditures of time and other resources within a tertiary care center.

Aim
This work aims to determine the incidence of congenital airway malformations in children with airway-related manifestations detected by flexible fiberoptic bronchoscopy at the bronchoscopy unit of Alexandria University Children Hospital during the period from 1st of January 2019 to 31st of December 2019.

Patients and methods
This retrospective study includes symptomatic children who underwent flexible fiberoptic bronchoscopy from 1st of January 2019 to 31st of December 2019.

Results
The incidence of congenital airway malformations in the studied population was 32%. The mean age of patients at time of diagnosis was 7 months and the most common congenital anomaly was laryngomalacia.

Conclusion
We concluded that congenital airway malformations are not uncommon in newborns and their early detection can be beneficial for optimum management.
Afghan mental health and psychosocial well-being: thematic review of four decades of research and interventions
Authors: Alemi Qais , Panter-Brick Catherine , Oriya Spozhmay , Ahmady Mariam , Alimi Abdul Qawi , Faiz Hafizullah , Hakim Nadia , Sami Hashemi Sayed A. , Manaly Muhammad Amin , Naseri Roman , Parwiz Khesraw , Sadat Sayed Javid , Sharifi Mohammad Zahid , Shinwari Zalmai , Ahmadi Sayed Jafar , Amin Rohullah , Azimi Sayed , Hewad Atal , Musavi Zeinab , Siddiqi Abdul Majeed , Bragin Martha , Kashino Wataru , Lavdas Michalis , Miller Kenneth E. , Missmahl Inge , Omidian Patricia A. , Trani Jean-Francois , van der Walt Sarah Kate , Silove Derrick , Ventevogel Peter 
Published: July 2023

BackgroundFour decades of war, political upheaval, economic deprivation and forced displacement have profoundly affected both in-country and refugee Afghan populations.AimsWe reviewed literature on mental health and psychosocial well-being, to assess the current evidence and describe mental healthcare systems, including government programmes and community-based interventions.MethodIn 2022, we conducted a systematic search in Google Scholar, PTSDpubs, PubMed and PsycINFO, and a hand search of grey literature (N= 214 papers). We identified the main factors driving the epidemiology of mental health problems, culturally salient understandings of psychological distress, coping strategies and help-seeking behaviours, and interventions for mental health and psychosocial support.ResultsMental health problems and psychological distress show higher risks for women, ethnic minorities, people with disabilities and youth. Issues of suicidality and drug use are emerging problems that are understudied. Afghans use specific vocabulary to convey psychological distress, drawing on culturally relevant concepts of body–mind relationships. Coping strategies are largely embedded in one's faith and family. Over the past two decades, concerted efforts were made to integrate mental health into the nation's healthcare system, train cadres of psychosocial counsellors, and develop community-based psychosocial initiatives with the help of non-governmental organisations. A small but growing body of research is emerging around psychological interventions adapted to Afghan contexts and culture.ConclusionsWe make four recommendations to promote health equity and sustainable systems of care. Interventions must build cultural relevance, invest in community-based psychosocial support and evidence-based psychological interventions, maintain core mental health services at logical points of access and foster integrated systems of care.
Intracranial Pressure Monitoring in Children With Severe Traumatic Brain Injury: A Propensity Score Matching Analysis Using a Nationwide Inpatient Database in Japan
Authors: Shibahashi Keita , Ohbe Hiroyuki , Matsui Hiroki , Yasunaga Hideo 
Published: July 2023

BACKGROUND AND OBJECTIVES:
Clinical benefits of intracranial pressure (ICP) monitoring in the management of children with severe traumatic brain injury (TBI) are not universally agreed upon. We investigated the association between ICP monitoring and outcomes in children with severe TBI using a nationwide inpatient database.

METHODS:
This observational study used the Japanese Diagnostic Procedure Combination inpatient database from July 1, 2010, to March 31, 2020. We included patients younger than 18 years, admitted to the intensive care unit or high-dependency unit with severe TBI. Patients who died or were discharged on the day of admission were excluded. One-to-four propensity score matching was performed to compare patients who underwent ICP monitoring on the day of admission with those who did not. The primary outcome was in-hospital mortality. Mixed-effects linear regression analysis compared outcomes and estimated the interaction between ICP monitoring and subgroups in matched cohorts.

RESULTS:
Of the 2116 eligible children, 252 received ICP monitoring on the day of admission. One-to-4 propensity score matching selected 210 patients who had ICP monitoring on admission day and 840 patients who did not. In-hospital mortality was significantly lower in patients who underwent ICP monitoring than those who did not (12.7% vs 17.9%; within-hospital difference, −4.2%; 95% CI, −8.1% to −0.4%). There was no significant difference in the proportion of unfavorable outcomes (Barthel index <60 or death) at discharge, proportion of enteral nutrition at discharge, length of hospital stay, and total hospitalization cost. Subgroup analyses demonstrated a quantitative interaction between ICP monitoring and the Japan Coma Scale (P < .001).

CONCLUSION:
ICP monitoring was associated with lower in-hospital mortality in children with severe TBI. Our results demonstrated the clinical benefits of ICP monitoring in managing pediatric TBI. The advantages of ICP monitoring may be amplified in children who exhibit the most severe disturbances of consciousness.
Echo intensity and gray-level co-occurrence matrix analysis of soft tissue grafting biomaterials and dental implants: an in vitro ultrasonographic pilot study
Authors: Mancini Leonardo , Khehra Anahat , Nguyen Tu , Barootchi Shayan , Tavelli Lorenzo 
Published: July 2023

Objective:
To characterize different allogeneic and xenogeneic soft tissue graft substitutes and to assess their echo intensity and grayscale texture-related outcomes by using high-frequency ultrasonography (HFUS).

Methods:
Ten samples from each of the following biomaterials were scanned using HFUS: bilayered collagen matrix (CM), cross-linked collagen matrix (CCM), multilayered cross-linked collagen matrix (MCCM), human-derived acellular dermal matrix (HADM), porcine-derived acellular dermal matrix (PADM), collagen tape dressing (C) and dental implants (IMPs). The obtained images were then imported in a commercially available software for grayscale analysis. First-order grayscale outcomes included mean echo intensity (EI), standard deviation, skewness, and kurtosis, while second-order grayscale outcomes comprised entropy, contrast, correlation, energy and homogeneity derive from the gray-level co-occurrence matrix analysis. Descriptive statistics were performed for visualization of results, and one-way analysis of variance with Bonferroni post-hoc tests were performed to relative assessments of the biomaterials.

Results:
The statistical analysis revealed a statistically significant difference among the groups for EI (p &lt; .001), with the group C showing the lowest EI, and the IMP group presenting with the greatest EI values. All groups showed significantly higher EI when compared with C (p &lt; .001). No significant differences were observed for energy, and correlation, while a statistically significant difference among the groups was found in terms of entropy (p &lt; 0.01), contrast (p &lt; .001) and homogeneity (p &lt; .001). IMP exhibited the highest contrast, that was significantly higher than C, HADM, PADM, CCM and CM.

Conclusions:
HFUS grayscale analysis can be applied to characterize the structure of different biomaterials and holds potential for translation to in-vivo assessment following soft tissue grafting-related procedures.
Automated detection of cephalometric landmarks using deep neural patchworks
Authors: Weingart Julia Vera , Schlager Stefan , Metzger Marc Christian , Brandenburg Leonard Simon , Hein Anna , Schmelzeisen Rainer , Bamberg Fabian , Kim Suam , Kellner Elias , Reisert Marco , Russe Maximilian Frederik 
Published: July 2023

Objectives This study evaluated the accuracy of deep neural patchworks (DNPs), a deep learning-based segmentation framework, for automated identification of 60 cephalometric landmarks (bone-, soft tissue- and tooth-landmarks) on CT scans. The aim was to determine whether DNP could be used for routine three-dimensional cephalometric analysis in diagnostics and treatment planning in orthognathic surgery and orthodontics. Methods: Full skull CT scans of 30 adult patients (18 female, 12 male, mean age 35.6 years) were randomly divided into a training and test data set (each n = 15). Clinician A annotated 60 landmarks in all 30 CT scans. Clinician B annotated 60 landmarks in the test data set only. The DNP was trained using spherical segmentations of the adjacent tissue for each landmark. Automated landmark predictions in the separate test data set were created by calculating the center of mass of the predictions. The accuracy of the method was evaluated by comparing these annotations to the manual annotations. Results: The DNP was successfully trained to identify all 60 landmarks. The mean error of our method was 1.94 mm (SD 1.45 mm) compared to a mean error of 1.32 mm (SD 1.08 mm) for manual annotations. The minimum error was found for landmarks ANS 1.11 mm, SN 1.2 mm, and CP_R 1.25 mm. Conclusion: The DNP-algorithm was able to accurately identify cephalometric landmarks with mean errors <2 mm. This method could improve the workflow of cephalometric analysis in orthodontics and orthognathic surgery. Low training requirements while still accomplishing high precision make this method particularly promising for clinical use.
Evaluation of marginal and internal fit of metal crowns made from wax patterns made by conventional technique and CAD CAM milling technique: An in vivo study
Authors: Tawade Shubham , Dhamande Mithilesh , Sathe Seema 
Published: July 2023

Introduction: Marginal and internal fit of a metal crown are very important for a successful metal crown prosthesis. This study will evaluate the marginal and internal fit of metal crowns produced from wax patterns that are formed by two different wax pattern fabrication procedures: conventional wax pattern fabrication and wax pattern milled using the computer-aided design and manufacture (CAD CAM) method. Objectives: To evaluate the marginal and internal fit of metal crowns over prepared tooth made from wax patterns made by conventional technique and CAD CAM technique. Methodology: A total of 21 participants with endodontically restored mandibular first molar will be selected. Two all-metal crowns will be made for each participant, thus 42 metal crowns in total will be made. These 42 metal crowns will be divided into two groups based on the method used to create wax patterns: metal crowns made using conventional hand-carved wax pattern technique (Group I, n=21) and metal crowns made using CAD CAM-milled wax pattern technique (Group II, n=21). Then, the marginal and internal fit of metal crowns from both groups will be compared. Expected results: It is expected that metal crowns made by CAD CAM milled wax pattern fabrication method will have better marginal and internal fit than those of conventional method. Conclusions: The clinical acceptability and success of the dental crown will be assessed by this study. Minimal marginal gap and better internal fit of all metal crown are key qualities.
Fluorescence molecular tomography for quantum yield and lifetime
Authors: Cong Wenxiang , Wang Ge 
Published: July 2023

Fluorescence molecular tomography (FMT) is a promising modality for noninvasive imaging of internal fluorescence agents in biological tissues, especially in small animal models, with applications in diagnosis, therapy, and drug design. In this paper, we present a fluorescent reconstruction algorithm that combines time-resolved fluorescence imaging data with photon-counting microcomputed tomography (PCMCT) images to estimate the quantum yield and lifetime of fluorescent markers in a mouse model. By incorporating PCMCT images, a permissible region of interest of fluorescence yield and lifetime can be roughly estimated as prior knowledge, reducing the number of unknown variables in the inverse problem and improving the image reconstruction stability. Our numerical experiments demonstrate the accuracy and stability of the proposed reconstruction method in the presence of data noise, achieving a reconstruction error of 0.02 ns for the fluorescence lifetime and an average relative error of 18% for quantum yield reconstruction.
Elimination of signal amplitude disturbance in ghost imaging using an auxiliary laser channel
Authors: Oparin Egor N. , Shumigai Vladimir S. , Sulimov Danil V. , Kalinichev Alexey A. , Tcypkin Anton N. 
Published: July 2023

Ghost imaging can be used to detect objects in a nonstationary environment or in the presence of variable ambient light, making it attractive when conventional imaging methods are ineffective. However, the conventional ghost imaging algorithm is susceptible to temporal fluctuations in the detected signal. In this work, we propose a polarization-multiplexed auxiliary laser channel propagating along the same optical path with the main one. The signal in the auxiliary channel is used as a reference and allows the elimination of signal disturbance. A quantitative analysis and comparison of the proposed method’s performance to the high-pass filtering method are demonstrated. For an illumination pattern refresh rate of 10 Hz, effective suppression of bucket signal fluctuations has been experimentally demonstrated. For a disturbance frequency from 1 Hz to 10 Hz, the auxiliary channel method demonstrated a ghost image Pearson correlation coefficient (PCC) of not less than 0.70, while the high-pass filtering method showed a PCC sharp drop from 0.65 to 0.02.
A Phase-I pharmacokinetic, safety and food-effect study on flubentylosin, a novel analog of Tylosin-A having potent anti-Wolbachia and antifilarial activity
Authors: Alami Negar , Carter David C. , Kwatra Nisha V. , Zhao Weihan , Snodgrass Linda , Porcalla Ariel R. , Klein Cheri E. , Cohen Daniel E. , Gallenberg Loretta , Neenan Melina , Carr Robert A. , Marsh Kennan C. , Kempf Dale J. 
Published: July 2023

Background
The parasitic filariae responsible for onchocerciasis and lymphatic filariasis are host to an endosymbiotic bacterium, Wolbachia, which is essential to the fertility and development of the parasites. We performed a Phase-I pharmacokinetic, safety and food-effect study on single and multiple ascending doses of flubentylosin (ABBV-4083), a macrolide antibacterial with activity against Wolbachia, intended to sterilize and eliminate the parasites.

Methods
Seventy-eight healthy adults were exposed to flubentylosin; 36 were exposed to single ascending 40, 100, 200, 400 or 1000 mg doses; 12 received 1000 mg in the food-effect part; and 30 received multiple ascending daily doses of 100 mg for 7 days, 200 mg for 7 or 14 days, or 400 mg for 7 or 14 days. Twenty-two subjects received placebo.

Results
Maximum concentrations (Cmax) of flubentylosin were reached after 1–2 hours, with a half-life < 4 hours at doses ≤ 400 mg. Cmax and AUC increased in a more than dose-proportional manner, with similar exposure after multiple dose administration. The most frequently reported adverse events were nausea (8/78, 10%) and headache (6/78, 8%).
Two subjects given a single dose of flubentylosin 1000 mg in the food-effect part experienced reversible asymptomatic ALT and AST elevations at Grade 2 or Grade 4, with no elevation in bilirubin, deemed related to study drug. The effect of food on exposure parameters was minimal. No treatment-related serious adverse events were reported.

Discussion
Flubentylosin 400 mg for 14 days was the maximum tolerated dose in this first-in-human, Phase-I study in healthy adults. Based on preclinical pharmacokinetic/pharmacodynamic modeling, flubentylosin 400 mg once daily for 7 or 14 days is expected to be an effective dose. A Phase-II, proof-of-concept study with flubentylosin using these regimens is currently ongoing in patients with onchocerciasis in Africa.
Anxiety classification in virtual reality using biosensors: A mini scoping review
Authors: Mevlevioğlu Deniz , Tabirca Sabin , Murphy David 
Published: July 2023

Background
Anxiety prediction can be used for enhancing Virtual Reality applications. We aimed to assess the evidence on whether anxiety can be accurately classified in Virtual Reality.

Methods
We conducted a scoping review using Scopus, Web of Science, IEEE Xplore, and ACM Digital Library as data sources. Our search included studies from 2010 to 2022. Our inclusion criteria were peer-reviewed studies which take place in a Virtual Reality environment and assess the user’s anxiety using machine learning classification models and biosensors.

Results
1749 records were identified and out of these, 11 (n = 237) studies were selected. Studies had varying numbers of outputs, from two outputs to eleven. Accuracy of anxiety classification for two-output models ranged from 75% to 96.4%; accuracy for three-output models ranged from 67.5% to 96.3%; accuracy for four-output models ranged from 38.8% to 86.3%. The most commonly used measures were electrodermal activity and heart rate.

Conclusion
Results show that it is possible to create high-accuracy models to determine anxiety in real time. However, it should be noted that there is a lack of standardisation when it comes to defining ground truth for anxiety, making these results difficult to interpret. Additionally, many of these studies included small samples consisting of mostly students, which may bias the results. Future studies should be very careful in defining anxiety and aim for a more inclusive and larger sample. It is also important to research the application of the classification by conducting longitudinal studies.