bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning Approaches for Prediction of Fertility Determinants in Bangladesh: evidence from the BDHS 2017-18 data
Authors: Uddin Md Jamal , Kabir Ahmad , Naznin Shayla 
Published: February 2024

Abstract
Background
Fertility is a social indicator that represents the country’s growth and economic sustainability. The fertility rate of a country refers to number of average children born to a woman during her lifetime. It is an important demographic indicator that influences population dynamics, economic growth, social welfare, and public policy. This research leverages advanced machine learning methodologies to achieve more precise predictions of fertility and fertility determinants in Bangladesh.
Methods
The dataset utilized in this study was sourced from the Bangladesh Demographic Health Survey (BDHS) conducted in the year 2017–18. Python 3.0 programming language were used to implement and test the machine learning (ML) models such as Random Forests (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), XGBoost, LightGBM and Neural Network (NN). We have used Boruta algorithm of Feature selection with R programming language packages. Conventional methods were analyzed using SPSS Version 25 and R programming language. The predictive models performance was evaluated and compared with the metrics such as macro average and weighted average of the Confusion Matrix, Accuracy, F1 Score, Precision, Recall, Area Under the Receiver Operating Characteristics Curve (AUROC) and K-fold cross-validation.
Results
We preferred with the Support Vector Machine (SVM) model of fertility in Bangladesh with macro average recall (93%), precision (89%), F1 score (90%) in addition with weighted average recall (97%), precision (96%), F1 score (96%) K-fold accuracy (95.9%). Our predictive models showed that Access to mass media, Husband/partner's education level, Highest educational level, Number of household members, Body Mass Index of mother, Number of living children and Son or daughter died stand out as the key determinants influencing fertility in Bangladesh.
Conclusions
In the realm of constructing advanced predictive models, Machine Learning methods surpass conventional statistical approaches in classifying concealed information. In our Study the Support Vector Machine (SVM) emerged as the top-performing model for fertility prediction in Bangladesh.
Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube-voltage and tube-current
Authors: Zhu Shumeng , Zhang Baoping , Tian Qian , Li Ao , Liu Zhe , Hou Wei , Zhao Wenzhe , Huang Xin , Xiao Yao , Wang Yiming , Wang Rui , Li Yuhang , Yang Jian , Jin Chao 
Published: February 2024

Abstract

Background: Low tube-voltage technique (e.g., 80 kV) could efficiently reduce the radiation dose and increase the contrast enhancement of vascular and parenchymal structures in abdominal CT. However, a high tube current is always required in this setting and limits the dose reduction potential. By using a deep learning iterative reconstruction algorithm (Deep IR), this paper aims to investigate the feasibility of a Deep IR in reducing radiation dose while improving the image quality for abdominal computed tomography (CT) with low tube-voltage and tube-current.
Methods: Sixty patients (Male/female, 36/24; Age, 57.72±10.19 years) undergoing the abdominal portal venous phase CT were randomly divided into groups A (100 kV, automatic exposure control [AEC] with reference tube-current of 213 mAs) and B (80 kV, AEC with reference of 130 mAs). Images were reconstructed by hybrid iterative reconstruction (HIR) and Deep IR (levels 1-5). The mean CT and standard deviation (SD) values of four regions of interest (ROI), i.e. liver, spleen, main portal vein and erector spinae at the porta hepatis level in each image serial were measured, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The image quality was subjectively scored by two radiologists using a 5-point criterion.
Results: A significant reduction of radiation dose by 69.94% (5.09±0.9 mSv vs. 1.53±0.37 mSv) were detected in group B when compared to group A. With regard to Deep IR algorithm at various levels, there was no significant change in CT value, but SD gradually increased. Group B had higher CT values than group A, and the portal vein CT values significantly differed between groups (P<0.003). The SNR and CNR in group B with Deep IR at levels 1-5 were higher than those in group A and significantly differed when HIR and Deep IR were applied at levels 1-3 of HIR and Deep IR (P<0.003). The subjective scores (distortion, clarity of the portal vein, visibility of small structures and overall image quality) with Deep IR at levels 4-5 in group B were significantly higher than those in group A with HIR (P<0.003).
Conclusion: Deep IR algorithm can reduce radiation dose and improve the image quality of parenchymal organs and portal vein clarity in portal venous phase abdominal CT with low tube-voltage and tube-current.
Mapping of a novel locus Ra conferring extreme resistance against potato virus A in cultivated potato (Solanum tuberosum L.)
Authors: Huang Wei , Zheng Jie , Nie Bihua , Li Jiana , Chen Ruhao , Nie Xianzhou , Tu Zhen , Gardner Kyle , Chen Jiaru , Yang Manhua , Li Jingcai , Dong Jianke , Ma Hui , Song Botao 
Published: February 2024

Abstract

Potato virus A (PVA) is one of the major viruses affecting potato worldwide, and can cause serious disease symptoms and yield losses. Previously, we determined that potato cultivar Barbara harbors Rysto (genotye: Ryryryry) and Ra (genotype: Rararara) that each independently confers extreme resistance (ER) to PVA. In this study, employing a combination of next-generation sequencing and bulked-segregant analysis, we further located this novel Ra on chromosome 4 using a tetraploid BC1 potato population derived from a Ry-free progeny (Rararararyryryry) of Barbara (RarararaRyryryry) × F58050 (rararararyryryry). Using 39 insertion-deletion (InDel) spanning chromosome 4, Ra was delimited by the Indel markers M8-83 and M10-8 within a genetic interval of 1.47 cM, corresponding to a 1.33 Mb genomic region in the potato DM reference genome. The InDel marker M10-8, which displayed 99.3% agreement with the phenotypic results in the Ry-free segregating populations, was then used to screen 43 tetraploid potato cultivars and breeding clones. An overall correlation of 76.6% between the marker and phenotype was observed. These findings obtained above are of importance in furthering the cloning of Ra and employing the marker-assisted selection for PVA resistance.
Evaluation of a reporting and supporting tool in interventional trials - the KarmApp
Authors: Tapia José , Gabrielson Marike , Hammarström Mattias , Wengström Yvonne , Bergqvist Jenny , Tuuliainen Aki , Eriksson Mikael , Czene Kamila , Hall Per , Bäcklund Magnus 
Published: February 2024

Abstract
Background In an increasingly digitalized world, telemedicine and mobile health tools have emerged as powerful resources in clinical trials and in managing chronic diseases. We have developed KarmApp, a smartphone application, to optimize data quality, safety and user-friendliness in our breast cancer prevention trials. The aim of this study was to evaluate the performance and the usage of the KarmApp over time.Methods The KarmApp functions include adverse event reporting, personalized study activity overviews, study questionnaires, and direct communication with study staff. Users are healthy women aged 40 to 74 participating in our randomized interventional trials evaluating risk-reducing medications at different doses and formulations. Development and deployment have followed a systematic, iterative approach, from requirements specification to post-release monitoring. We have calculated the usage frequencies of the various KarmApp features and performed statistical analysis across age groups and respective trials using SAS version 9.4 and R version 4.2.1.Results Of the participants in the randomized clinical trials KARISMA 2 (N = 1,440) and KARMA Creme (N = 90), 1406 (91.9%) used the KarmApp, across all age groups. There were 14,212 user interactions with the KarmApp, with the “Study Activities Overview” being the most frequently used. A total of 2,081 spontaneous adverse event reports collected in the trials. The majority, 1,535 (73.8%), were reported through KarmApp, less via the other reporting channels.Conclusions KarmApp exemplifies the potential for transformative impacts in healthcare and clinical research, which is supported by our data showing trends towards an increased use of the app over time. Our experiences of KarmApp reflects the growing acceptance of mobile technology across age groups, presenting opportunities for further integration in clinical trials.
Infusion of 14 days Blinatumomab in Combination with Chemotherapy for 46-day MRD+ Pediatric B-ALL Patients in Intermediate/High-Risk Group Results in MRD Conversion and BiTE Induced Immune Response to Malignant Cells
Authors: Xue Changwen , Wu Chao , Yang Wenyu , Zou Yao , Guo Ye , Chen Yumei , Chen Xiaojuan , Ma Yueshen , wan Yang , Zhu Xiaofan , Zhang Li 
Published: February 2024

Abstract

The conventional intensity of chemotherapy has reached its limit. Despite the efficacy of blinatumomab in B-cell acute lymphoblastic leukemia (B-ALL) adults with measurable residual disease (MRD) has been proved, studies in children with MRD positivity (MRD+) are still lacking. We conducted an exploratory trial of 14 days of blinatumomab monotherapy in combination with a B-ALL chemotherapy protocol in pediatric patients with MRD+ at the day 46 and evaluated the early efficacy and safety of this approach (Blin-14d-therapy, ChiCTR2100053318, registered on 11/18/2021). Totally 9 pediatric patients were included in Blin-14d group and 38 in non-Blin-14d group. After monotherapy with blinatumomab, all evaluable patients became MRD negative in Blin-14d group and achieved MRD conversion earlier than conventional chemotherapy group, predicting better treatment outcomes. Compared to previous investigations, the incidence of AEs was lower and MRD clearance was higher in this study. In conventional blinatumomab studies, a single course was administered for 28 days. T-cell counts continued to trend upward from day 14 to 21, whereas a downward trend was observed from day 21 to 28, suggesting that T-cell exhaustion occured. While in our regimen, blinatumomab was administered for 14 days, and T-cell levels still had an upward trend in the first week after the end of the infusion, suggesting that T-cell exhaustion at this time was not significant and anti-tumor effect prolonged. Initial data from this study demonstrate that Blin-14d-therapy with chemotherapy has encouraging clinical activity and a manageable safety profile in pediatric patients with day46 MRD+ B-ALL in IR/HR groups.
Impact of Riparian Buffer Strips on Aquatic Phosphorus Concentrations: Insights into Effective Land Management Strategies
Authors: Shahbazi Maneli , Mozaffari Afshin , Voroney Paul , Bazrgar Amir , Thevathasan Naresh 
Published: February 2024

Abstract
This study examined the effects of riparian buffers on the concentrations of soluble reactive phosphorus (SRP) in water and available phosphorus in sediment samples collected along Washington Creek, a moderately degraded stream typical of agricultural landscapes (AG) in Southern Ontario. This research was performed along the entire length of the creek (9250 m). Four different land uses were identified in the study area: natural forest (NF), rehabilitated forest (RH), grassland (GR), and agricultural field (AG). Although the concentrations of SRP in water samples were much lower (i.e., < 0.001 ppm) than the federal-provincial water quality objectives for streams (i.e., 0.03 ppm), the concentrations of SRP in the water samples collected from plots adjacent to the AG without riparian buffers were significantly higher than those from areas covered with vegetated buffers. The concentrations of available P in the sediments collected from the plots influenced by AG were significantly higher than those with riparian buffers, which was up to 5.2 mg P kg− 1 sediment. This study showed the accumulation of available P in the sediments was correlated with SRP concentrations in Washington Creek. These findings suggest that the implementation of riparian buffer strips can effectively mitigate the influx of phosphorus into aquatic systems, thereby reducing the risk of eutrophication and maintaining water quality within acceptable limits.
Genome sequencing of captive white tigers from Bangladesh
Authors: Das Ashutosh , Suvo Md Shahadat Hossain , Shaha Mishuk , Gupta Mukta Das 
Published: February 2024

Abstract
Objectives:
The Bengal tiger Panthera tigris tigris, is an emblematic animal for Bangladesh. Despite being the apex predator in the wild, their number is decreasing due to anthropogenic activities such as hunting, urbanization, expansion of agriculture and deforestation. By contrast, captive tigers are flourishing due to practical conservation efforts. Breeding within the small captive population can produce inbreeding depression and genetic bottlenecks, which may limit the success of conservation efforts. Despite past decades of research, a comprehensive database on genetic variation in the captive and wild Bengal tigers in Bangladesh still needs to be included. Therefore, this research aimed to investigate the White Bengal tiger genome to create a resource for future studies to understand variation underlying important functional traits.
Data description:
Blood samples from Chattogram Zoo were collected for three white Bengal tigers. Genomic DNA for all collected samples were extracted using a commercial DNA extraction kit. Whole genome sequencing was performed using a DNBseq platform. We generated 77 Gb of whole-genome sequencing (WGS) data for three white Bengal tigers (Average 11X coverage/sample). The data we generated will establish a paradigm for tiger research in Bangladesh by providing a genomic resource for future functional studies on the Bengal white tiger.
Differential Item Functioning and Response Shift may reveal hidden differences between groups and over time in anxiety and depression in patients with early-stage melanoma or breast cancer: interpretation and impact using the RespOnse Shift ALgorithm at the Item level (ROSALI)
Authors: Dubuy Yseulys , Blanchin Myriam , Perrot Bastien , Bourdon Marianne , Sébille Véronique 
Published: February 2024

Abstract

Purpose
Anxiety and depression are common psychiatric comorbidities in cancer patients that may vary depending on cancer type. Differential item functioning (DIF) and response shift (RS) may impact self-reported outcomes when patients don’t interpret items about their experience in the same way between groups and over time, respectively.
Objectives: detect/interpret DIF/RS in self-reports measuring anxiety/depression in breast cancer patients (BC-p) and melanoma patients (M-p). Provide estimates of change in anxiety/depression in BC and melanoma, considering DIF/RS, if appropriate.
Methods
Anxiety and depression were assessed in BC-p (n=337) and M-p (n=110) using the Hospital-Anxiety-and-Depression-Scale (HADS) at 1- (T1) and 6-month (T2) post-diagnosis. DIF/RS analyses were performed using Rasch models.
Results
DIF and RS were identified in the anxiety (DIF/RS) and depression (RS) subscales of the HADS. DIF/RS had a moderate (anxiety) or significant impact (depression) on the results, providing different conclusions depending on whether or not they were considered. Considering DIF/RS, BC-p were more anxious than M-p (T1). Anxiety decreased for BC-p and became similar as M-p (T2) whose anxiety remained stable. Changes in depression differed between BC-p and M-p, remaining stable in BC-p while increasing in M-p who were more depressed than BC-p (T2).
Conclusion
DIF and RS were found in self-reports of anxiety/depression in melanoma and BC patients, possibly revealing psychological distress but also adaptation to cancer. DIF/RS can lead to possibly erroneous conclusions, if ignored, but are also meaningful/important to consider to better understand patients’ experiences. They are still too often ignored which can lead to suboptimal healthcare-decision-making.
Trial registration number: NCT.gov: NCT02893774, registration date: 2014. Of note, this was a prospective study which was retrospectively registered.
Comprehensive Epidemiological Assessment of Trauma Incidents: A Study of 16,585 Patients at a Level I Trauma Center in Lanzhou City, Northwestern China
Authors: Su Zhaoyin , Wei Hui , Liu Yao , Liu Yatao , Wang Weining , Wang Weitao , Li Chao , Li Sha , Michael Nerich , Lyu Yuan 
Published: February 2024

Abstract

Objective
Analyzing the epidemiological characteristics of trauma patients admitted to a Level I Trauma Center in Lanzhou City, Northwestern China, to provide theoretical references for improving the quality of trauma care.
Methods
A retrospective analysis of clinical data from 16,585 trauma patients treated at the First Hospital of Lanzhou University's trauma center from November 1, 2021, to October 31, 2023, was conducted. Data including age, gender, time of trauma, cause of trauma, and major injured body parts were statistically analyzed.
Results
During the period from November 1, 2021, to October 31, 2023, a total of 18,235 patients were admitted, with complete data for 16,585 cases. Of these, 9,793 were male and 6,792 were female, with a male-to-female ratio of 1.44:1. The peak times for trauma occurrence were 10–12 AM and 6–10 PM, and the peak months were from May to October. The leading causes of trauma were Falls (45.32%), Other trauma (15.88%), Road Traffic Accidents (15.15%), Violence (10.82%), Cutting/stabbing (9.41%), Mechanical injuries (2.65%), Winter sports injuries (0.36%), Animal bites (0.22%), Burns (0.09%), and Electrical injuries (0.02%). The distribution of major injured body parts showed statistical significance, with limbs/skin being the most affected, followed by the head/neck, chest/abdomen, and back.
Conclusions
Trauma is more common in middle-aged and young individuals, with a higher incidence in males than females. Falls is the leading cause of trauma. Medical institutions and government agencies can implement corresponding preventive measures and policies based on the characteristics of trauma to enhance the quality and level of trauma care.
The ReInvigorate Study - Phrenic Nerve-to-Diaphragm Stimulation for Weaning from Mechanical Ventilation: A Protocol for a Randomized Pivotal Clinical Trial
Authors: Schaaf Katie , Mullin Christopher M. , Cunningham Kyle W. , Eaton Jonathan , Conrad Steven A. 
Published: February 2024

Abstract
Background In the United States in 2017, there were an estimated 903,745 hospitalizations involving mechanical ventilation (MV). Complications from ventilation can result in longer hospital stays, increased risk of disability and increased healthcare costs. It has been hypothesized that electrically pacing the diaphragm by phrenic nerve stimulation during mechanical ventilation may minimize or reverse diaphragm dysfunction, resulting in faster weaning.
Methods The ReInvigorate Trial is a prospective, multicenter, randomized, controlled clinical trial evaluating the safety and efficacy of Stimdia’s pdSTIM System for facilitating weaning from MV. The pdSTIM system employs percutaneously placed multipolar electrodes to stimulate the cervical phrenic nerves and activate contraction of the diaphragm bilaterally. Patients who were on mechanical ventilation for at least 96 hours and who failed at least one weaning attempt were considered for enrollment in the study. The primary efficacy endpoint was the time to successful liberation from mechanical ventilation (treatment vs. control). Secondary endpoints will include maximal inspiratory pressure, the rapid shallow breathing index, and other physiological and system characteristics. Safety will be summarized for both primary and additional analyses. All endpoints will be evaluated at 30 days or at the time of removal of mechanical ventilation, whichever is first.
Discussion This pivotal study is being conducted under an investigational device exception with the U.S. Food and Drug Administration. The technology being studied could provide a first-of-kind therapy for difficult-to-wean patients on mechanical ventilation in an intensive care unit setting.
Trial Registration Clinicaltrials.gov, NCT05998018, registered August 2023.
Machine Learning-Based ECG Signal Classification for Enhanced Early Detection of Doxorubicin-Induced Cardiotoxicity in Rats
Authors: Mohammed Haitham S. , H.Hanafy A. , abdo Abd El-Rahman M. A. , Alazoul Abdelaziz H. , Rashid Mohamed E. , El-Naggar Rabab 
Published: February 2024

Abstract
Cardiotoxicity, which leads to irreversible myocardial damage, is a major adverse effect associated with chemotherapy. Electrocardiogram (ECG) is an inexpensive, rapid, and simple tool that may provide valuable diagnostic information pertinent to cardiotoxicity. An automatic interpretation and classification of the ECG signals by machine learning algorithms is considered superior to human interpretation of the ECG which may not be able to early detect subtle alterations in the ECG and vary according to the experience of the specialist. The present work aimed at using different machine learning algorithms to classify ECG signals recorded from doxorubicin-injected rats. Rats were divided into four groups and each group was intraperitoneally injected with different cumulative doses of doxorubicin (0, 6, 12, and 18 mg/kg). ECG signal classification depended on multiple features that were extracted from the recorded signals under different conditions. K nearest neighbors’ algorithm achieved higher classification accuracy (99.83 %) than random forest (99.56 %), decision tree (99.54 %), artificial neural network (99.50 %), and support vector machine (99.38 %). Furthermore, the dose-dependent cardiotoxicity was validated via a histopathological examination of the left ventricle that indicated significant pathological alterations in the cardiac tissue. The present findings emphasized the potential of the machine learning-based enhanced detection of cardiotoxicity and validated the dose-dependent toxicity of doxorubicin in the cardiac left ventricle. This approach might be applicable clinically to avoid cardiotoxicity in chemotherapy-treated patients.
Green Synthesis and Characterization of Zinc Oxide Nanoparticles using Aquoes Extract of G. Mangostana leaves at Different Calcination Temperatures
Authors: Rusli R. K. , Mahata M. E. , Yuniza A. , Zurmiati Z , Reski S. , Hidayat C. , Hilmi M. , Mutia R. 
Published: February 2024

Abstract
This study aims to synthesize ZnO nanoparticles at different calcination temperatures (300 oC, 400 oC, 500 oC, and 600 oC) using the green synthesis method by aquoes Extract of G. mangostana leaves as a bioreductor of ZnO nanoparticles. The active groups contained in mangosteen leaf extract act as a bioreductor and capping agent, assisting in the synthesis of nanoparticles. The characterization of ZnO NPs using aquoes extract of G. mangostana leaves bioreductor at different calcination temperatures was evaluated by a Particle size analyzer (PSA), scanning electron microscope (SEM), energy dispersive X-ray (EDX), X-ray diffractometer (XRD), and Fourier transform infrared (FTIR). Characterization results using PSA showed an average particle size between 641.97 nm − 915.94 nm. SEM showed some particles in nanoform and agglomeration. EDX showed that the elements of ZnO NPs consisted of Zn and oxygen. XRD showed a specific peak of ZnO crystallinity at 2θ = 36.25o, with a crystal size of 40.98–46.92 nm, and FTIR showed the presence of ZnO vibrations at cm− 1 and the absorption peak of the -OH functional group at 3330.58–3415.04. In conclusion, ZnO NPs with aquoes Extract of G. mangostana leaves as a bioreductor could synthesize at 300 oC with a smaller size than 600 oC.