bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deregulation of MicroRNA-146a and 155 expression levels might underlie complicated pregnancy in Toxoplasma Gondii seronegative women
Authors: Naguib Marwa M. , Zaher Youssef Abdel , Ali Hemat Salah M. , Elnoury Hamasat Abdelhafiz , Mohammed Lina Abdelhady , Habashy Omnia Youssef , Mohammed Dina Abdelhady 
Published: July 2024

Abstract
Background
To evaluate the ability of the estimated plasma expression levels of genes of microRNA (MiR-) 146a and 155 to differentiate between samples of pregnant women suspected to be infected by T. gondii. 50 newly pregnant women who had at least one of the criteria of high risk for toxoplasma infection and 50 newly primigravida women free of these criteria gave blood samples for qualitative determination of serum toxoplasma antibodies and estimation of plasma expression levels of MiR-146a and 155 using the qRT-PCR. During the pregnancy course, the incidence of pregnancy complications was recorded.

Results
Twenty-six women were IgM−/IgG−, 17 women were IgM+/IgG− and 7 women were IgM+/IgG+. Thirty-two women had pregnancy complications with significantly lower incidence in IgM−/IgG− women. Plasma expression levels of MiR-146a and 155 were significantly higher in total patients compared to control levels and were significantly higher in samples of IgM+/IgG+ patients than in other samples. Statistical analyses defined a high plasma level of MiR-155 as the highly significant predictor for oncoming pregnancy complications and high levels of both microRNAs as predictors for the presence of toxoplasmosis despite seronegativity. Kaplan-Meier regression analysis defined increasing cumulative risk of having toxoplasmosis despite seronegativity with plasma levels of MiR-146a and MiR-155 of 1.2 and 3, respectively.

Conclusion
The incidence of pregnancy complications is high, irrespective of the seronegativity of women at high risk of toxoplasmosis. Estimated plasma levels of MiR-155 might identify women liable to develop complications and differentiate seronegative women vulnerable to having T. gondii infection.

Trial registration
The study protocol was approved preliminarily by the Local Ethical Committee at Benha Faculty of Medicine. Before enrollment, the study protocol was discussed in detail with the study participants, and those accepted to participate in the study signed written fully informed consents. The final approval of the study protocol was obtained after the end of case collection and registered by RC: 5-11-2022.
Cancer nurses’ experience during the COVID-19 pandemic: Multicenter mixed-methods study on coping and resilience strategies
Authors: Cadorin Lucia , Mazzega-Fabbro Cristina , Cedrone Sonja 
Published: July 2024

Abstract
Background
In early 2020, the COVID-19 pandemic created severe difficulties in clinical and organizational fields. Healthcare workers needed to protect their health and avoid infecting their family members, but also limit the virus’s spread among vulnerable oncology patients undergoing hospital treatment.

Objective
To evaluate the resilience and coping strategies of nurses working in the oncology setting.

Methods
A mixed-methods study was conducted. First, two questionnaires (CD-RISK and COPE- NVI-25) were used to assess nurses’ resilience strategies and coping mechanisms quantitatively. Second, qualitative semi-structured interviews were conducted to explore the personal experiences of nurses who cared for patients during the pandemic, and Colaizzi’s framework was used for content analysis.

Results
The 164 participants, the majority of whom were women (88.4%), reported high resilience. The CD-RISK score varied according to education. With respect to COPE-NIV-25, transcendent orientation and avoidance strategies had the lowest mean scores, while problem orientation was higher in nurses aged ≥ 40. Five themes emerged: (1) changes in work and personal areas; (2) feelings/emotions, such as fear of infection of themselves or their loved ones, difficulty in using the face mask, relational repercussions with patients or their families; (3) personal and working group strategies used to counteract the suffering attributable to COVID-19; (4) professionalism/nursing responsibilities in developing new rules and protocols, and (5) metaphors to describe their experiences.

Conclusions
The COVID-19 pandemic led to major changes in the nurses’ roles, but they showed resilience and generated a positive working climate.

Implication for practice
Even in emergency situations, nursing administrations and policymakers ought to ensure that nurses receive adequate training and support to develop resilience and coping strategies.
NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study
Authors: He Shan , Nader Karam , Abarrategi Julen Segura , Bediaga Harbil , Nocedo-Mena Deyani , Ascencio Estefania , Casanola-Martin Gerardo M. , Castellanos-Rubio Idoia , Insausti Maite , Rasulev Bakhtiyor , Arrasate Sonia , González-Díaz Humberto 
Published: July 2024

AbstractNeurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe3O4_A and Fe3O4_B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe3O4_A and Fe3O4_B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.
Associations of dietary inflammatory index scores and serum inflammatory factors with the risk of osteoporosis: a cross-sectional study from Xinjiang, China
Authors: Tong Min , Zhang Huanwen , Li Yuanyuan , Fu Wenhui , Luo Tao , Dai Jianghong , Huang Yifei 
Published: July 2024

Abstract
Background
Previous studies have shown that the inflammatory potential of the diet is associated with a variety of chronic noncommunicable diseases characterized by a chronic low-grade inflammatory response. However, the relationships between dietary inflammatory potential and organismal inflammatory status and osteoporosis have been less studied. This study aimed to investigate the relationships among inflammatory diet, inflammatory state and osteoporosis in the Xinjiang multiethnic population.

Methods
The participants consisted of 4452 adults aged 35 to 74 years from Xinjiang, China. The dietary inflammatory index (DII) was calculated using dietary data collected with a semiquantitative food frequency questionnaire, and information about osteoporosis was derived from quantitative ultrasound measurements. The relationships of the DII score and inflammatory factors with the risk of osteoporosis were analysed using multivariate logistic regression, and the nonlinear associations between DII and osteoporosis were further analysed using restricted cubic splines.

Results
The results showed that proinflammatory diets were associated with a greater risk of osteoporosis (T3 vs. T1: OR = 1.87; 95% CI = 1.44, 2.45) and that there was no nonlinear relationship between the DII and the risk of osteoporosis. Increased concentrations of the inflammatory factors IL-6, IL-10, IL-12p70, IL-17, and IL-23 were associated with a greater risk of osteoporosis.

Conclusions
The risk of osteoporosis can be reduced by increasing the consumption of an appropriate anti-inflammatory diet.
Probiotic potential of lactic acid bacteria isolated from Ethiopian traditional fermented Cheka beverage
Authors: Albene Dawit , Lema Niguse Kelile , Tesfaye Getaneh , Andeta Addisu Fekadu , Ali Kidist , Guadie Awoke 
Published: July 2024

Abstract
Introduction
: Lactic acid bacteria (LAB) are a cluster of microbes distributed in a variety of environments and have potential probiotic activity to improve human well-being. This study was aimed at assessing the probiotic potential of LAB isolated from Cheka, an Ethiopian traditionally fermented beverage.

Method
Pure isolates obtained from 16 Cheka samples from Konso (n = 8) and Derashe (n = 8) were characterized morphologically, biochemically, and physiologically by considering basic criteria to identify the LAB. The probiotics properties of the LAB were evaluated in vitro at low pH values (2.0 and 3.0), and two bile salt concentrations (0.3 and 0.5%) for 3 and 6 h. The 16 S rRNA gene sequencing was done using an ABI 3730xl sequencer, and the gene sequences were aligned.

Results
Of the 27 pure isolates, 11 isolates were proven to be LAB with non-motile, negative for catalase, and non-spore former characteristics. Based on cultural characteristics and sugar fermentation ability, the 11 isolates were assembled into the genera Lactobacillus (55%), Lactococcus (18%), Pediococcus (18%), and Leuconostoc (9%). At pH 3.0 and a bile salt concentration of 0.3%, isolate ChK-11 showed a better survival rate (97 and 94%) than other isolates [ChK-7 (93 and 80%) > ChD-5 (84 and 76%) > ChD-8 (46 and 36%) > ChK-4 (41 and 34%)] for 6 and 3 h, respectively. According to 16 S rRNA sequencing results, isolates ChK-11 and ChK-7 were found to be Weissella paramesenteroides and Leuconostoc pseudomesenteroides with sequence similarity of 99 and 91%, respectively.

Conclusions
In the present study, probiotic LAB (Weissella paramesenteroides and Leuconostoc pseudomesenteroides) was successfully isolated and sequenced from Cheka samples. The findings of this in vitro study indicated that fermented beverages like Cheka are a source of the LAB with probiotic functional properties. Overall, Weissella paramesenteroides and Leuconostoc pseudomesenteroides isolates, which showed promising probiotic properties under in vitro conditions, can be used for starter culture development for the Cheka fermentation process.
Modeling behavioral patterns of family violence aggressors
Authors: Jolliffe Simpson Apriel D. , Joshi Chaitanya , Polaschek Devon L. L. 
Published: July 2024

Abstract
Background setting
The presumption that family violence will repeat and escalate is embedded in practices including risk assessment and case management. However, there is limited evidence that further episodes are inevitable, or that subsequent episodes will increase in severity. Therefore, we need to better understand temporal patterns in aggressor behavior to inform how risk is conceptualized in practice.

Methods
For a sample of 2115 family violence aggressors who came to police attention in Integrated Safety Response catchment areas in Aotearoa New Zealand, we collected information New Zealand Police routinely recorded about reported harm between 2018 and 2020. We used a hidden Markov model to estimate the latent (i.e., unmeasurable) states behind the information reported to police, and modeled aggressors’ movement between those states over time.

Results
We identified three latent states. The first contained low or no reported harm, the second contained low probabilities of reported harm, and the third involved a high probability of reported verbal abuse and a moderate probability of reported physical violence. We identified four pathways through the latent states over the two-year follow-up period, which we called No reported harm, High reported harm, Low reported harm, and De-escalation.

Conclusions
The findings add to the body of research indicating that family violence aggressors do not inevitably repeat or escalate their harmful behavior, and that a small subset of cases account for a large proportion of reported harm. This study demonstrates how information that police routinely collect can be used to estimate aggressors’ latent behavioral states and model pathways communicating the probability that they will continue to come to police attention for family violence, contributing to improved risk assessment and practice.
An efficient PGD solver for structural dynamics applications
Authors: Vella Clément , Gosselet Pierre , Prudhomme Serge 
Published: July 2024

AbstractWe propose in this paper a Proper Generalized Decomposition (PGD) solver for reduced-order modeling of linear elastodynamic problems. It primarily focuses on enhancing the computational efficiency of a previously introduced PGD solver based on the Hamiltonian formalism. The novelty of this work lies in the implementation of a solver that is halfway between Modal Decomposition and the conventional PGD framework, so as to accelerate the fixed-point iteration algorithm. Additional procedures such that Aitken’s delta-squared process and mode-orthogonalization are incorporated to ensure convergence and stability of the algorithm. Numerical results regarding the ROM accuracy, time complexity, and scalability are provided to demonstrate the performance of the new solver when applied to dynamic simulation of a three-dimensional structure.
Intelligent assessment system of material deterioration in masonry tower based on improved image segmentation model
Authors: Zou Jianshen , Deng Yi 
Published: July 2024

Abstract
Accurate and timely data collection of material deterioration on the surfaces of architectural heritage is crucial for effective conservation and restoration. Traditional methods rely heavily on extensive field surveys and manual feature identification, which are significantly affected by objective conditions and subjective factors. While machine vision-based methods can help address these issues, the accuracy, intelligence, and systematic nature of material deterioration assessment for large-scale masonry towers with complex geometries still require significant improvement. This research focuses on the architectural heritage of masonry towers and proposes an intelligent assessment system that integrates an improved YOLOv8-seg machine vision image segmentation model with refined 3D reconstruction technology. By optimizing the YOLOv8-seg model, the system enhances the extraction capabilities of both detailed and global features of material deterioration in masonry towers. Furthermore, by complementing it with image processing methods for the global visualization of large-scale objects, this research constructs a comprehensive intelligent assessment process that includes "deterioration feature extraction—global visualization—quantitative and qualitative comprehensive assessment." Experimental results demonstrate that the intelligent assessment system significantly improves the performance of target feature extraction for material deterioration in masonry towers compared to existing methods. The improved model shows improvements of 3.39% and 4.55% in the key performance metrics of mAP50 and mAP50-95, respectively, over the baseline model. Additionally, the efficiency of global feature extraction and visualization of material deterioration increased by 66.36%, with an average recognition accuracy of 95.78%. Consequently, this system effectively overcomes the limitations and subjective influences of field surveys, enhancing the objectivity and efficiency of identifying and analyzing material deterioration in masonry towers, and providing invaluable data support for the subsequent preservation and restoration efforts.
Hate speech detection in the Bengali language: a comprehensive survey
Authors: Al Maruf Abdullah , Abidin Ahmad Jainul , Haque Md. Mahmudul , Jiyad Zakaria Masud , Golder Aditi , Alubady Raaid , Aung Zeyar 
Published: July 2024

AbstractThe detection of hate speech (HS) in online platforms has become extremely important for maintaining a safe and inclusive environment. While significant progress has been made in English-language HS detection, methods for detecting HS in other languages, such as Bengali, have not been explored much like English. In this survey, we outlined the key challenges specific to HS detection in Bengali, including the scarcity of labeled datasets, linguistic nuances, and contextual variations. We also examined different approaches and methodologies employed by researchers to address these challenges, including classical machine learning techniques, ensemble approaches, and more recent deep learning advancements. Furthermore, we explored the performance metrics used for evaluation, including the accuracy, precision, recall, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), sensitivity, specificity, and F1 score, providing insights into the effectiveness of the proposed models. Additionally, we identified the limitations and future directions of research in Bengali HS detection, highlighting the need for larger annotated datasets, cross-lingual transfer learning techniques, and the incorporation of contextual information to improve the detection accuracy. This survey provides a comprehensive overview of the current state-of-the-art HS detection methods used in Bengali text and serves as a valuable resource for researchers and practitioners interested in understanding the advancements, challenges, and opportunities in addressing HS in the Bengali language, ultimately assisting in the creation of reliable and effective online platform detection systems.
A qualitative comparison of parents’ experiences of early childhood expulsion following a legislative ban
Authors: Zinsser Katherine M. , Coba-Rodriguez Sarai , Lowe-Fotos Allison 
Published: July 2024

AbstractOver the past decade, numerous reports have indicated pervasively high rates of early childhood expulsion nationwide. In response, state and federal policymakers have enacted various measures to ban or reduce reliance on such exclusionary discipline. Prior evaluations of the implementation of one such legislative ban on expulsion enacted in Illinois in 2018 showed partial reductions but relied only on program administrator-reported data. Parents (N = 16) of children (43.75% children of color) expelled from Illinois early childhood programs before and in the years since the 2018 legislative ban were interviewed about their experiences. Parents in both groups reported similar incidents regarding how and why children are excluded, how programs communicated with parents about children’s behavioral concerns, and how programs assisted (or did not) with accessing resources and supports that may enable a child to be retained. Findings indicate that expulsions continue to happen despite the ban and families’ experiences were essentially unchanged and negative. Findings hold implications for the implementation of similar policy efforts across the country.
Eggshell membrane and green seaweed (Ulva lactuca) micronized powders for in vivo diabetic wound healing in albino rats: a comparative study
Authors: Moustafa Moustafa H. , Turkey Mohamed S. , Mohamedin Noha S. , Darwish Amira A. , Elshal Amira A. M. , Yehia Mona A. H. , El Safwany Mohamed M. , Mohamed Ehab I. 
Published: July 2024

Abstract
Background
Nonhealing diabetic wounds are a serious complication associated with extremely lethargic wound closure and a high risk of infection, leading to amputation or limb loss, as well as substantial health care costs and a poor quality of life for the patient. The effects of either eggshell membrane (ESM) and green seaweed (Ulva lactuca) extracts alone or in combination were evaluated for in vivo skin wound healing in a rat model of induced diabetes.

Methods
Micronized powders of waste hen ESM, Ulva lactuca, and their 1:1 mixture were prepared using regular procedures. The mechanical, electrical, and surface morphology characteristics of powders were examined using direct compression, LCR-impedancemetry, and scanning electron microscopy. The effect of ESM, Ulva lactuca, and their mixture as compared to standard Dermazin treatments were evaluated on wounds inflicted on male Wistar Albino rats with induced diabetes. Quantitative wound healing rates at baseline and at 3, 7, 14, and 21 days of treatments among all rat groups were conducted using ANOVA. Qualitative histological analysis of epidermal re-epithelization, keratinocytes, basement membrane, infiltrating lymphocytes, collagen fibrines, and blood vessels at day 21 were performed using Image J processing program.

Results
Compressive strength measurements of tablets showed a Young’s modulus of 44.14 and 27.17 MPa for the ESM and ESM + Ulva lactuca mixture, respectively. Moreover, both samples exhibited relatively low relative permittivity values of 6.62 and 6.95 at 1 MHz, respectively, due to the porous surface morphology of ESM shown by scanning electron microscopy. On day 21, rats treated with ESM had a complete diabetic wound closure, hair regrowth, and a healing rate of 99.49%, compared to 96.79% for Dermazin, 87.05% for Ulva lactuca, 90.23% for the mixture, and only 36.44% for the negative controls. A well-formed basement membrane, well-differentiated epithelial cells, and regular thick keratinocytes lining the surface of the epidermal cells accompanied wound healing in rats treated with ESM, which was significantly better than in control rats.

Conclusion
Ground hen ESM powder, a low-cost effective biomaterial, is better than Ulva lactuca or their mixture for preventing tissue damage and promoting diabetic wound healing, in addition to various biomedical applications.