bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel bronchoscopy method for molecular profiling of lung cancer: Targeted washing technique: A prospective cohort study
Authors: Kim Mi-Hyun , Seong Hayoung , Jang Hyojin , Kim Saerom , Yoo Wanho , Kim Soo Han , Jo Eun-Jung , Mok Jeongha , Lee Kwangha , Kim Ki Uk , Park Hye-Kyung , Lee Min Ki , Eom Jung Seop
Published: April 2024

Background Efforts have been made to identify alternative samples to standard samples of tumor tissue or plasma for mutational analyses of patients with lung cancer. However, no other samples or techniques have replaced mutational analysis using standard samples. In this prospective study, we assessed a novel bronchoscopic method, the targeted washing technique, for the detection of EGFR mutations.
Methods A 3.0-mm ultrathin bronchoscope was precisely navigated to the target lung lesion using virtual bronchoscopic navigation and fluoroscopy. Once the bronchoscope was placed in front of the target lung lesion, normal saline was administered for targeted washing. EGFR testing using targeted washing fluid (TWF) was compared with standard methods using plasma or tumor tissues.
Results In 41 TWF samples, the T790M mutation was detected in 22%, 10%, and 29% of tissue, plasma, and TWF samples, respectively. The overall EGFR T790M detection rate in the tissue, plasma, or TWF samples was 37%, with TWF samples increasing the T790M mutation detection rate by up to 10%. The accuracy of T790M mutation detection using the TWF sample was 83% compared to that of standard samples. Four patients were found to have the EGFR T790M mutation only through EGFR testing using TWF, and repeated re-biopsies using either plasma or tissue confirmed the presence of the T790M mutation.
Conclusion We demonstrated the clinical potential of targeted washing technique for molecular testing, which can be a good option to overcome spatial heterogeneity, low sensitivity of plasma samples, or technical limitations in collecting tumor tissues.
The correlation between healthy lifestyle habits and all cause and cardiovascular-related death among 19,000 residents in Guangxi
Authors: Mai Lan-Xian , Liu Ying , Wen Hong , Zeng Zhi-Yu
Published: April 2024

Background
Adherence to healthy lifestyle habits has become a mainstream approach for lessening the burden of cardiovascular disease(CVD) during initial prevention efforts. The purpose of this study was to investigate the prevalence of four healthy lifestyle habits, the associated factors, and their impact on all cause and cardiovascular-related death among residents of Guangxi Zhuang Autonomous Region.
Methods
From 2015 to 2019, individuals between the ages of 35 and 75 from Guangxi Zhuang Autonomous Region were recruited through the ChinaHeart Million Person Project. Our study examined four healthy lifestyle habits: not smoking, no or moderate amounts of alcohol, sufficient leisure time physical activity (LTPA) and a balanced diet.
Results
Out of the 19,969 individuals involved, the majority, 77.3% did not smoke, while 96.7% had limited alcohol intake, 24.5% engaged in sufficient LTPA, 5.5% followed a balanced diet, and merely 1.7% adhered to all four healthy lifestyle habits. Participants who were women, older, nonfarmers, living in cities, with a high income or level of education, or had hypertension or diabetes were more likely to follow all four healthy lifestyle habits (p < 0.001). People who followed the three healthy lifestyle habits had reduced chances of death from all cause (HR 0.34[95% CI:0.15,0.76]) and cardiovascular-related death (HR 0.23 [95% CI: 0.07, 0.68]) (p < 0.01) over a median period of 3.5 years.
Conclusions
In Guangxi Province, the level of adherence to healthy lifestyle habits is very minimal. Therefore, population-specific health promotion strategies are urgently needed.
Assessing the Long-Term Effectiveness of Sustainable Rural Water Treatment Technologies in Mitigating Arsenic Contamination of Groundwater in Afghanistan
Authors: Ahmadi Abdul Wahed , Annachhatre Ajit P.
Published: April 2024

Arsenic contamination in groundwater poses a significant global risk, affecting over fifty million people across more than seventy countries. Sources of contamination include anthropogenic, geogenic, and biogenic factors. In Afghanistan, where groundwater serves as a primary drinking water source, the need for sustainable arsenic removal technologies is paramount. Presently, 78% of the population relies on groundwater accessed through household tub wells for safe drinking water. Recent studies indicate alarming levels of arsenic contamination, with around 61% of water samples exceeding World Health Organization standards. This research aims to evaluate and compare existing arsenic removal technologies, focusing on their suitability for households in Afghanistan. Three popular methods, including Sono Sand Filter, Kanchan Arsenic Removal, and Arsenic Bio Sand Filter, will be assessed based on their effectiveness and feasibility. Preliminary findings suggest Arsenic Bio Sand Filter as the most efficient method, with a removal effectiveness of 95% and additional benefits in pathogen, bacteria, iron, and turbidity reduction. Ultimately, this study seeks to inform policymakers and stakeholders to develop mitigation strategies, thereby reducing arsenic-related health risks and improving public health outcomes in Afghanistan
Global acute malnutrition is associated with geography, season and malaria incidence in the conflict-affected regions of Ouham and Ouham Pendé prefectures, Central African Republic
Authors: Stambach Nicola , Lambert Helen , Eves Katie , Nfornuh Blaise Alenwi , Bowler Emily , Williams Peter , Lama Marcel , Bakamba Pascal , Allan Richard
Published: April 2024

Background: Ongoing conflict between multiple armed groups, including pastoralist herders in the Central African Republic (CAR) causes frequent population displacements, food insecurity and scarcity of healthcare services. The inaccessibility and insecurity of many areas of CAR limit data collection and assessments from national nutritional surveys. Community health workers (CHWs) trained by an international non-governmental organisation, The MENTOR Initiative, deliver basic healthcare to children under 5 years old living in hard-to-reach and conflict-affected areas in eight subprefectures of north-west CAR. Their nutritional status and its associations with geography, malaria, season and conflict are unknown.
Methods: CHW monthly records (October 2015 - August 2021), Armed Conflict Location and Event Data project conflict data and The World Bank Group meteorological data for eight subprefectures of north-west CAR were analysed. Associations between counts of global acute malnutrition (GAM) assessed by mid-upper arm circumference and malaria, season and conflict were investigated using negative binomial regression. Sub-analysis of Paoua subprefecture data was performed using negative binomial regression.
Results: Of the 457,325 consultations with children aged 6-59 months, 6.2% and 0.4% were classified as moderately or severely malnourished, respectively. The negative binomial model demonstrated differences in counts of GAM by subprefecture. Counts of GAM were positively associated with case rate of severe malaria (IRR=1.045; 95% CI: 1.04—1.06) and rainy season (July-September) (IRR=1.10; 95% CI: 1.03—1.17). In Paoua subprefecture, conflict events targeting civilians and all conflict events were associated with decreased counts of GAM (IRR=0.73; 95% CI: 0.55—0.96 and IRR=0.55; 95% CI: 0.34—0.90, respectively).
Conclusion: This analysis shows geographical differences in levels of malnutrition in north-west CAR and demonstrates clear associations between malnutrition, season and malaria. It provides evidence that levels of GAM may be underestimated in north-west CAR in areas experiencing conflict. These findings highlight the need for targeted nutritional support to reach children most at risk of malnutrition. CHWs are a proven effective means of delivering essential primary healthcare services in hard-to-reach, conflict-affected areas.
Extracellular vesicles miR-574-5p and miR-181a-5p as prognostic markers in NSCLC patients treated with Nivolumab
Authors: Genova Carlo , Marconi Silvia , Chiorino Giovanna , Guana Francesca , Ostano Paola , Santamaria Sara , Rossi Giovanni , Vanni Irene , Longo Luca , Tagliamento Marco , Zullo Lodovica , Bello Maria Giovanna Dal , Dellepiane Chiara , Alama Angela , Rijavec Erika , Ludovini Vienna , Barletta Giulia , Passiglia Francesco , Metro Giulio , Baglivo Sara , Chiari Rita , Rivoltini Licia , Biello Federica , Baraibar Iosune , Gil-Bazo Ignacio , Novello Silvia , Grossi Francesco , Coco Simona
Published: April 2024

Background
Immune checkpoint inhibitors (ICIs) have revolutionized the management of advanced non-small cell lung cancer (NSCLC), although patient survival is still unsatisfactory. Accurate predictive markers capable of personalizing the treatment of patients with NSCLC are still lacking. Circulating extracellular vesicles involved in cell-to-cell communications through miRNAs (EV-miRs) transfer are promising markers.
Methods
Plasma from 245 patients with advanced NSCLC who received nivolumab as second-line therapy was collected and analyzed. EV-miRnome was profiled on 174/245 patients by microarray platform and selected EV-miRs were validated by qPCR. A prognostic model combining EV-miR and clinical variables was built using stepwise Cox regression analysis and tested on an independent patient cohort (71/245). EV-PD-L1 gene copy number was assessed by digital PCR. For 54 patients with disease control, EV-miR changes at best response versus baseline were investigated by microarray and validated by qPCR.
Results
EV-miRNome profiling at baseline identified two EV-miR (miR-181a-5p, miR-574-5p) that, combined with performance status, are capable of discriminating patients unlikely from those that are likely to benefit from immunotherapy (median overall survival of 4 months or higher than 9 months, respectively). EV-PD-L1 digital evaluation reported higher baseline copy number in patients at increased risk of mortality, without improving the prognostic score. Best response EV-miRNome profiling selected six deregulated EV-miRs (miR19a-3p, miR-20a-5p, miR-142-3p, miR-1260a, miR-1260b, miR-5100) in responding patients. Their longitudinal monitoring highlighted a significant downmodulation already in the first treatment cycles, which lasted more than six months.
Conclusions
Our results demonstrate that EV-miRs are promising prognostic markers for NSCLC patients treated with nivolumab.
Safety and effectiveness of conversion from sleeve gastrectomy to banded Roux-en-Y Gastric Bypass
Authors: Dam Kayleigh Ann Martina van , de Witte Evelien , Broos Pieter Petrus Henricus Luciën , Greve Jan Willem M , Boerma Evert-Jan Gijsbert
Published: April 2024

Background
Weight recurrence, suboptimal clinical response and functional disorder (such as reflux) after a Sleeve Gastrectomy (SG) are problems that may require conversional surgery. For reflux, conversion to Roux-en-Y Gastric Bypass (RYGB) is considered effective. Regarding treatment for suboptimal clinical response, the technique of choice remains a subject of debate. This study aims to evaluate the safety and effectiveness of conversion from SG to banded RYGB (BRYGB).
Methods
All laparoscopic SG to BRYGB conversions performed between January 2016 and January 2022 were included. Primary outcome was percentage total weight loss (%TWL) after 1-year follow-up. Secondary outcomes consisted of cumulative %TWL, complications (with a focus on ring-related complications), and resolution of associated medical problems.
Results
We included 50 patients of whom 44 were female. Mean pre-conversion BMI was 37.6 kg/m2. All patients have reached the 1-year follow-up point, however 10 were lost to follow-up. After 1-year mean TWL was 17.8% while mean cumulative TWL, calculated from primary SG, was 32%. A total of 10 complications occurred in 8 patients within 30 days, 6 of which were ≤ CD3a and 4 ≥ CD3b. One MiniMizer was removed for complaints of severe dysphagia. Of the 35 obesity associated medical problems present at screening 5 remained unchanged(14.2%), 15 improved(42.9%) and 15 achieved remission(42.9%).
Conclusion
Our series of 50 patients undergoing conversion from SG to BRYGB is safe and successful regarding additional weight loss 1 year after conversion, cumulative weight loss and achievement of improvement or remission of comorbidities. Short term complications are comparable to current literature.
Clinical significance of Cyclin D1 by complete quantification detection in mantle cell lymphoma: Positive indicator in prognosis
Authors: Yang Yan , Song Liling , Yin Ying , Gao Yuan , Wang Yunjun , Wu Shishou , Wang Jun , Pan Yu , Sui Xiaolong , Jiang Lei , Zhang Yunyun , Yu Guohua
Published: April 2024

Background: The positive expression of Cyclin D1 in immunohistochemical (IHC) staining serves as the cornerstone for diagnosing mantle cell lymphoma (MCL). However, existing literature does not conclusively establish whether the expression ratio and staining intensity significantly influence diagnostic outcomes or patient prognosis. In this retrospective study, the correlation between comprehensive Cyclin D1 quantification and the prognosis of MCL patients was studied.
Methods:The Cyclin D1 protein level was assessed in 120 formalin-fixed paraffin-embedded samples from mantle cell lymphoma (MCL) patients using the quantitative dot blot (QDB) analysis technique. R language software was employed for statistical analysis to determine the optimal threshold with statistical significance. Additionally, Kaplan-Meier method was utilized to evaluate the relationship between the absolute level of Cyclin D1 protein and overall survival (OS) of patients. Furthermore, the Chi-square test was applied to analyze the causes of single and multiple fractures, with a significance level of p < 0.05. Finally, the Log-rank test was used to compare two survival curves, where a significance level of p < 0.05 was considered statistically significant.
Results: At the optimized cutoff of 0.46 nmol/g, univariate analysis revealed a positive correlation between Cyclin D1 protein level and patient survival (OS). Specifically, in the subgroup with complete quantification of Cyclin D1 higher than the cutoff, the 5-year OS was 18%, whereas in the subgroup with complete quantification of Cyclin D1 lower than the cutoff, the 5-year OS was 4.8% (Log-rank test, P=0.017). This indicates that patients with Cyclin D1 levels above the cutoff had significantly better overall survival compared to those below the cutoff. Additionally, in the Pearson distribution test, Ki-67 emerged as an independent prognostic factor for the complete quantification of Cyclin D1. Notably, Cyclin D1 complete quantification results remained unaffected by factors such as gender, age, LDH level, Ann Arbor stage, Ki-67, IPI, MIPI, and MIPI-c (Chi-square test, p > 0.05).
Investigation of beta lactam resistance in Escherichia coli isolated from wild bird feces.
Authors: Halaç Barış , Kekeç Ayşe Ilgın , Çelik Baran , Kahraman Beren Başaran , Sığırcı Belgi Diren , Bağcıgil Arzu Funda , Çokal Yavuz , Ak Seyyal
Published: April 2024

The study's objective was to identify beta-lactamase-resistant Escherichia coli both phenotypically and genotypically in the feces of resident wild birds and passing migrants in the Marmara region. The study involved 272 noninvasively collected fresh fecal samples. The birds of interest were categorized into four groups, assuring that each group comprised 68 samples as follows: Group 1 = resident wild waterbirds; Group 2 = urban resident terrestrial birds; Group 3 = winter migrants; and Group 4 = summer migrants. Extended-spectrum beta-lactamase (ESBL) and ampicillin Class C (AmpC) beta-lactamase positivity of E. coli isolates grown on cefotaxime-supplemented MacConkey agar were assessed by phenotypic screening and confirmation tests in sixty-two (62/272; 22.8%) out of 84 E. coli strains, irrespective of group-wise distribution. Fifty of these E. coli strains were positive for ESBL, 7 for AmpC, and 5 showed both ESBL and AmpC activities. E. coli isolates were detected in fifty-nine (21.7%) of 272 birds, and 57 of these 59 birds were positive for ESBL, six for AmpC, and six for both ESBL and AmpC. Modified Hodge Test revealed no carbapenemase production. Forty-eight out of 84 E. coli isolates grown on cefotaxime-supplemented MacConkey agar were positive for ESBL, three for AmpC, and 5 for both ESBL and AmpC-encoding genes by Polymerase Chain Reaction. The distribution of genes was blaCTX−M (n = 50), blaSHV (n = 2), and blaOXA10 (n = 10) for ESBL and blaMOX (n = 6) and blaCIT (n = 2) for AmpC. Carbapenemase genes (blaKPC, blaVIM, blaOXA, blaNDM−1) were undetected. According to the group and species-wise findings, Group 1, predominantly in seagulls, harbored the highest rates of ESBL- and/or AmpC-producing E. coli isolates. Considering that the seagull species that feed on human, animal, and agricultural waste products mainly through garbage dumps are widely distributed in Istanbul, the antimicrobial resistance in E. coli strains collected from wild birds is considered to be of human and/or animal origin.
The effect of different concentrations of aluminum phosphide and (sodium bromide, calcium carbonate and potassium nitrate) as its possible antidotes on the digestive and reproductive system in the rat model
Authors: Soltanieh Negin , Ostadi Ali , Mesgari-Abbasi Mehran , Khordadmehr Monireh , Behrouzi-Kahlan Azin , Mohammadi Ali Banagozar , Ghaffari Alireza
Published: April 2024

Aluminum phosphide (AlP) is often used as a suicide poison. Considering that there is no effective antidote, the purpose of this study was to investigate the toxic effect of ALP and evaluate the antidote potency of sodium bromide, calcium carbonate, and potassium nitrate as antidotes. In the first stage, 36 female Wistar rats were divided into 6 groups to receive AlP in different doses (0–40 mg/kg). After being sacrificed, the rats were histologically evaluated for the esophagus, stomach, pancreas, uterus, and ovary. In the second stage, animals were evaluated regarding the effect of ALP (20 mg/kg) on various fertility hormones, and subsequently the role of proposed antidots were investigated to reverse the toxic changes. Histological findings did not show significant changes in all examined tissues. The studied hormonal changes showed a significant inverse relationship between AlP and LH, prolactin, and estradiol hormones. In the studies related to the studied antidotes, the results showed that prolactin and estradiol decreased and increased, respectively, due to treatment with AlP compared to the control group. Antidote studies revealed that the prolactin level in rats poisoned with AlP and treated with KNO3 was not different from the control group, and estradiol also returned to normal and control levels due to the treatment with KNO3 and NaBr. KNO3 was shown to be an efficient antidote against AlP toxicity regarding prolactin and estradiol among the tested antidotes, while sodium bromide successfully mitigated the effect of AlP toxicity.
An effcient strategy for halogenation addition of olefins catalyzed by Polyoxometalate-based Iron Catalyst
Authors: Zhou Junting , Deng Mengjie , Xie Ya , Han Sheng , Yu Han
Published: April 2024

The halogenation of alkenes is a crucial pathway in forming C-X bonds, with significant impact in organic synthesis and pharmaceuticals. However, traditional methodologies present potential hazards to both the environment and human health, making the quest for green and efficient halogenation methods paramount. In this study, we introduce a novel iron catalyst based on a polyoxomolybdate, (NH4)3[FeMo6O18(OH)6], simplified as Fe(III)Mo6. Employing this catalyst, a plethora of styrene derivatives and alcohols were efficiently and successfully converted to the corresponding halogenated products. Also, our catalysts showed excellent performance towards to the reaction with various substrates. Moreover, it demonstrates high stability and activity in cycle test. In addition, we also described the reaction mechanism based on the control experiment. The catalyst exhibits non-toxic, green, and environmentally friendly characteristics that provide future industrialization potential.
Biomethane produced from maize grown on peat emits more CO2 than natural gas
Authors: Evans Christopher , Rowe Rebecca , Freeman Benjamin , Rhymes Jennifer , Cumming Alex , Lloyd Isobel , Morton Daniel , Williamson Jennifer , Morrison Ross
Published: April 2024

Cultivation of maize for biomethane production has expanded rapidly, including on drained peat soils. The resulting soil CO2 emissions at the point of feedstock production are largely overlooked when assessing biogas climate mitigation potential. Based on field-scale flux measurements, we calculate that soil CO2 emissions from biomethane feedstock production on drained peat exceed embodied emissions for an equivalent amount of natural gas by up to a factor of three.
Lateral flow assay as radiological prognosis factor of pulmonary cryptococcosis: A single center retrospective study in China
Authors: Shi Jiejun , Chen Jianhua , Ding Qianjiang , Qian Guoqing
Published: April 2024

Background
Lateral flow assay (LFA) showed high sensitivity and specificity for diagnosing cryptococcosis. However, its predictive value for therapeutic efficacy of pulmonary cryptococcosis (PC) was rarely reported.
Methods
We conducted a retrospective analysis on HIV-negative PC to present the clinical profile and identify the potential predictors for radiological prognosis.
Results
All the 168 participants received antifungal therapy with a triazole agent. Of these, 84.5% experienced partial or complete absorption of pulmonary lesions. The results of the gamma test, chi-square trend test, and ordinal logistic regression all indicated that baseline LFA and changes in LFA after treatment were both predictors of imaging prognosis. The degree of radiological improvement showed a downward trend as the baseline LFA positive grade increased (P for linear-by-linear association: 0.011, Spearman correlation coefficient = -0.17; γ= -0.368, P = 0.045). Patients who experienced a decrease in LFA after therapy had a significantly better radiological prognosis than those with equal or increased LFA (linear-by-linear association, P = 0.014, Spearman correlation coefficient = 0.188; γ = 0.371, P = 0.012). Moreover, favorable outcomes were more likely in cases with lesions restricted in the right lung.
Conclusions
LFA is potential to monitor radiological outcomes of PC.
Multifactorial Analysis for Predicting Drug Resistance in Tuberculosis: Integrated Approaches to Improve Treatment
Authors: Falcão Igor W. S. , Cardoso Diego L. , Santos Albert E. C. dos , Leite Karla T. F. , Carneiro Saul R. , Moura Flávio R. T. , Pereira Ronilson W. Da S. , Pinto Lyanh V. L. , Alves André V. N. , Seruffo Marcos C. da R.
Published: April 2024

Tuberculosis (TB) remains a significant threat to global health, exacerbated by drug resistance, socio-economic, and environmental factors. These challenges make the treatment of the disease not only prolonged but also costly. With these issues in mind, this study introduces a multifaceted predictive model that integrates clinical, environmental, and socioeconomic factors to predict drug resistance in TB patients. Utilizing a dataset of 103,846 patient records from São Paulo, Brazil, spanning from 2006 to 2016, we applied machine learning techniques, including clustering, segmentation, and predictive modeling, to identify patterns and predictors of drug resistance. The proposed methodology enabled us to predict, analyze, and anticipate the clinical outcomes of patients in relation to TB drug resistance, with the XGBoost model achieving an accuracy of 84.65% and an F1-score of 85.34%. Moreover, the clustering of data allowed for the analysis of how comorbidities influence the likelihood of developing drug resistance in TB. Through this approach, it becomes possible to foster a better understanding of the clinical picture and diagnosis of patients, thereby facilitating more targeted and effective interventions.
PATHAK: An NLP-Based Method to Mine Gene and Function Relationships from Published Articles
Authors: Kumar Nilesh , Mukhtar M. Shahid
Published: April 2024

Understanding the intricacies of genes function within biological systems is paramount for scientific advancement and medical progress. Owing to evolving landscape of this research and the complexity of biological processes, however, this task presents challenges. We introduce PATHAK, a natural language processing (NLP)-based method that mines relationships between genes and their functions from published scientific articles. PATHAK utilizes a pre-trained Transformer language model to generate sentence embeddings from a vast dataset of scientific documents. This enables the identification of meaningful associations between genes and their potential functional annotations. Our approach is adaptable and applicable across diverse scientific domains. Applying PATHAK to over 5,000 research articles focused on Arabidopsis thaliana, we demonstrate its efficacy in elucidating gene function relationships. This method promises to significantly advance our understanding of gene functionality and potentially accelerate discoveries in the context of plant development, growth and stress responses in plants and other systems.
Medication Adherence and Associated Factors Among Chronic Heart Failure Patients on Follow Up in North Shewa Public Hospitals, Oromia Region, Ethiopia
Authors: Hussein Dursa , Jima Abyot Kebede , Geleta Leta Adugna , Gashaw Ketema , Girma Derara , Ibrahim Seifu Mohammed , Lakew Meron Seyoum , Kumbe Bedo Megersa , Oyato Befekadu Tesfaye , Siyum Getu , Senbate Addis Adugna
Published: April 2024

Background
Chronic heart failure affects around 26 million people globally. World Health Organization data shows only about half of chronically ill patients in developed countries adhere to recommended medication, with even lower rates in developing countries. Medication adherence is critical for managing chronic heart failure affects symptoms, delaying disease progression, and preventing hospitalizations. However, poor adherence leads to increased re-hospitalizations, morbidity, mortality, and healthcare costs.
Objective
To assess medication adherence and its associated factors among chronic heart failure patients on follow-up at North Shewa public hospitals, Oromia Region, Ethiopia, in 2023.
Methods
An institutional-based cross-sectional study design was conducted from March 1 to April 30 2023 G.C. A total of 603 sample size were selected consecutively among those coming for chronic OPD after being proportionally allocated to five hospitals in the zone. Data were collected using an interviewer-administered questionnaire and a medical chart review. Data were entered into Epi-data version 3.1, then exported to SPSS version 26 for analysis. Variables with a P value < 0.25 in the bivariate analysis were included in the multivariate logistic regression model. The degree of association was expressed using an adjusted odds ratio (AOR) with a 95% confidence interval (CI) at a P value < 0.05
Result
Among 603 patients, 56% had optimal medication adherence with 95% CI: (52.1, 60). Being able to read and write (AOR: 2.20; 95% CI: 1.34, 3.61), having a secondary education (AOR: 1.97; 95% CI: 1.06, 3.67), having community-based health insurance (AOR: 1.82; 95% CI: 1.22, 2.71), not having co-morbidity (AOR: 1.82; 95% CI: 1.18, 2.52), taking a number of drugs < 2 (AOR: 2.11; 95% CI: 1.20, 2.45), not adding salt when cooking (AOR: 1.72; 95% CI: 1.20, 2.45), and asking a doctor or nurse without fear (AOR: 1.87; 95% CI: 1.03, 3.40) were factors associated with medication adherence among CHF.
Conclusion
This study found 56% of chronic heart failure patients had optimal medication adherence. Factors associated with higher adherence included higher education, community health insurance, lack of comorbidities, fewer medications, avoiding added salt, and comfort communicating with providers. Health professionals should provide education to strengthen medication adherence.
Design and Analysis of a Dual-Port Multiband RF-to-DC Converter for IoT Energy Harvesting Applications
Authors: Tariq Bismah , Amjad Muhammad , Al-Jaloud Khaled A. , Tahir Farooq A. , Malik Waqar Ahmad , Hussain Rifaqat
Published: April 2024

The proliferation of Internet of Things (IoT) devices has led to an increasing demand for efficient and sustainable energy sources to power these autonomous systems. Radio Frequency (RF) energy harvesting has emerged as a promising solution, capitalizing on the omnipresent RF signals in our environment. This article presents the design and analysis of a Dual-Port Multiband RF-to-DC Converter using a multi-stage Cockcroft Walton Voltage Multiplier (CWVM) topology, which is tailored to meet the specific needs of IoT energy harvesting applications. Impedance matching is achieved by the implementation of L-network and π-network using distributed elements. The proposed design enables simultaneous energy harvesting across six bands from 0.87 to 2.5 GHz. It exhibits peak efficiency of 66% and 62% at 10kΩ and 18kΩ, respectively. The multiband feature enhances the energy acquisition versatility. The key parameters, including impedance matching, output voltage, and conversion efficiency, are simultaneously analyzed and optimized for all the frequency bands to achieve the desired performance. The proposed design performance is compared with the recent converter designs in literature, which shows that this research contributes to the ongoing development of energy-efficient solutions for IoT devices, addressing the critical need for prolonged autonomy of IoT devices and reduced reliance on traditional power sources.
Assessing Model Validity Using KL Divergence and Beta-Stacy Process for Right Censored Data
Authors: Labadi Luai Al
Published: April 2024

Model validation constitutes a crucial component of statistical analysis, with heightened challenges encountered when addressing censored data. This paper introduces a novel approach that integrates the Kullback-Leibler divergence, the beta-Stacy process, and relative belief ratio inferences to form a comprehensive method for model validation. Significantly, this method is applicable to both complete and right-censored data. Theoretical results related to this approach are presented, accompanied by a computational algorithm for implementation. The effectiveness of the approach is illustrated through a series of data analysis examples, highlighting its good performance.
MSC 2020 62N03, 62F15.
An Intellectual Hybrid Machine Learning Model for Effective Breast Cancer Diagnosis
Authors: Nallamala Sri Hari , Mishra Pragnyaban , Koneru Suvarna Vani , Chakrabarti Prasun , Chakrabarti Tulika , Shanmuganathan Vimal , Margala Martin
Published: April 2024

Cancer was characterized as an illness brought about by an uncontrolled division of irregular cells in a piece of the body. Breast Cancer is characterized as a harmful development or tumor coming about because of an uncontrolled division of cells in the breast. Breast cancer is one of the most dangerous types of cancer after the lung cancer. The breast cancer is also considering as critical one like as skin cancer. Since, decades, women are suffering due to this breast cancer and also most of times majority percentage of them are dying due to non-identification at early stages and with the severity of the disease. Therefore, most of the doctors, scientists, researchers are did a major research and contributed for diagnosing the breast cancer at early stages and also curing process of the breast cancer. Here, in our research, we are also going to be diagnosing the breast cancer at early stages with the available less symptoms or data sets in an effective way to serve the needy people and finally trying to decrease the mortality rate by recovering them from the breast cancer. In this work, we have taken the most popular breast cancer datasets, i.e. Wisconsin Breast Cancer Datasets (i.e. Original and Diagnostic) as input to our proposed classifier to obtain the effective accuracy of classification which are nearly 98.97% and 97.73% respectively.
Sodium Dithionite-Assisted Gold Nanoparticle Synthesis and BSA Conjugation
Authors: Natarajan Belliraj , Krishnasamy Ilamurugu , Palaniyappan Kumaresan , Rajendran Gobinath , Natarajan Balakrishnan
Published: April 2024

The wet chemical method has long been a widely accepted approach for synthesizing gold nanoparticles (AuNPs). Trisodium citrate (Na3C6H5O7) has traditionally served as a common reducing agent in the colloidal gold nanoparticle synthesis (known as the Turkevich method), effectively converting citrate ions into bulk AuCl4 in ionic form. In contrast, sodium dithionite (Na2S2O4), an inexpensive reducing agent, acts on precursor materials by reducing their functional groups. In our current investigation, we explored the reducing capacity of sodium ions within the dithionite compound, leading to the formation of unique-sized ionic gold nanoparticles. The synthesized gold nanoparticles exhibited a strong surface plasmon resonance (PR) band at 531 nm in UV spectroscopy at a concentration of 1 mM. Additionally, the Raman spectrum of sodium dithionite-derived gold nanoparticles displayed intense bands at 523.4, 547, 593.4, and 1027 cm-1. The FT-IR spectrum revealed a weak intensity peak at 3934.78 and 3838.34 cm-1, with medium intensity observed at 3390 and 3367.71 cm-1. Furthermore, high-resolution transmission electron microscopy (HR-TEM) analysis indicated that the gold nanoparticles exhibited anisotropic shapes, with average diameters of 3.24 nm and 8.5 nm, respectively. However, conjugated with bovine serum albumin (BSA), the gold nanoparticles demonstrated maximum absorbance at a concentration of 400 µg/ml. Notably, BSA-conjugated gold nanoparticles exhibited strong surface plasmon resonance peaks at 537 nm under acidic conditions. This proposed synthesis protocol, utilizing dithionite as a reducing agent and BSA protein conjugation, may yield uniform-sized colloidal Au nanoparticles suitable for biomedical applications.
Density Functional Theory Study of Interaction between Oxazepam and Alginic Acid as a Nanocarrier
Authors: Shahi Masoumeh , Azarakhshi Fatemeh , Sahraei Mahya , Khorshidi Negar
Published: April 2024

Alginic acid is a hydrophilic linear polysaccharide that is of interest due to its unique physicochemical and biological properties. In this study, the interaction between Oxazepam and Alginic acid as a drug nanocarrier has been studied using Density Functional Theory (DFT) at the M06-2X/6–31 + G* level of theory. Here, the DFT results showed that the non-covalent interaction between Oxazepam and Alginic acid affects the electronic properties, chemical shift tensors, electronic potential of the molecule and atomic charges. Natural Bond Orbital (NBO) analysis showed that Oxazepam molecule as electron donor and Alginic acid play the role of electron acceptor in Oxazepam/Alginic acid complex. The electronic spectrum of the Oxazepam/Alginic acid complex was calculated to investigate the effect of Oxazepam drug absorption on Alginic acid on the maximum wavelength. Quantum Theory of Atoms in Molecules (QTAIM) analysis showed that the main driving force in complex formation is the non-covalent interaction between Alginic acid and Oxazepam. This result led to the possibility of using Alginic acid to deliver Oxazepam to diseased cells.
Timely vaccination and its associated factors among parents with children aged from 0-23 months in Wolaita Zone Public hospitals, southern Ethiopia, 2024: a facility-based cross-sectional study
Authors: Hardido Temesgen Geta , Atinafu Bizuayehu , Elifios Eshetu
Published: April 2024

Background
In Ethiopia, vaccination is mentioned as the vital preventive measure of undue childhood mortality from measles, pneumonia, diarrheal diseases, and other VPDs. Although there are studies conducted on full vaccine coverage, there is relatively no data available about timely vaccination and its related factors in southern Ethiopia. Thus, this study assessed timely vaccination and related factors in children who age from 0 to 23 months in the study area.
Methods and material:
An institution-based cross-sectional study was undertaken in Wolaita zone Public hospitals, from December 2023, G.C to January 2024, G.C. A total of 376 study subjects were randomly selected through systematic sampling method among parents with children who are 0–23 months old. Data were gathered by questionnaire with a structure which was based on mother’s recalling as well as vaccination cards. A basic questionnaire was completed by respondents and the responses were entered into Epidata Version 4.6, which was later transferred to SPSS Version 23 for analysis. Data were entered into Epidata Version 4.6 and exported to SPSS Version 23 for analysis. An adjusted odds ratio (AOR) along with a 95% confidence interval at a P-value less than 0.05 was used to declare significance level.
Results
A total of 376 study participants responded to the interview with 100% response rate. This study found that 269 children (71.5%) were timely vaccinated and 107 children (28.5%) had not got their children vaccinated timely. The independent variables, like time to reach the health facility[AOR = 5.7; 95% CI (1.81,17.55), place of delivery[AOR = 4.91; 95% CI (2.85, 10.83)], ANC follow-up[AOR = 8; 95% CI (5.81, 25.01)], attitude[AOR = 2.5; 95% CI (1.23,4.3)] and knowledge [AOR = 3.45; 95% CI (1.61, 10.62)] on the vaccine time, significantly attributed to timely vaccination.
Conclusion
71.5% of study participants vaccinated their children on the national recommended vaccination schedule. The research also revealed statistical correlation between time taken from home to health facility, antenatal care follow up, place of delivery, maternal attitude and knowledge of the prompt vaccination and vaccination timeline. For the all stake holders, highly strategic interventions like promoting maternal knowledge about the benefits versus risks of timely vaccination, community-based vaccination programs or campaigns, routine supervision, and counseling during antenatal visits are very effective ways of improving timely vaccination.
Revisiting the Titius-Bode law: planetary distances with advanced data analysis for better physical significance
Authors: Ray Saibal , Sanyal Aritra , Sharma U. K. , Sen B.
Published: April 2024

The Titius-Bode law, initially proposed as an empirical relationship describing planetary distances from the Sun, has been a subject of both fascination and scrutiny in the field of celestial mechanics. Over time, variations and modifications to the original law have emerged, aiming to enhance its predictive accuracy and explanatory power. This research paper presents a comparative analysis of the original Titius-Bode law and a modified version proposed in recent literature. The study assesses the predictive performance and goodness of fit of both laws using statistical metrics such as mean squared error (MSE) and R 2 score. Additionally, graphical representations of observed and predicted distances for various planet positions are analyzed to discern patterns and deviations. The findings reveal significant differences between the original and modified laws in terms of predictive accuracy and model fit. While the original law demonstrates superior performance in capturing the observed data patterns and providing accurate predictions, the modified law exhibits limitations, potentially stemming 1 from over-fitting or simplifications. The implications of these findings for understanding planetary dynamics and the broader field of celestial mechanics are discussed, highlighting the importance of rigorous model evaluation and refinement in advancing our understanding of the cosmos. Furthermore, this study introduces a novel polynomial equation derived from observational data, offering insights into potential refinements of existing models and avenues for future research.
Challenges of Depth Estimation for Transparent Objects
Authors: Weibel Jean-Baptiste , Thalhammer Stefan , Vincze Markus
Published: April 2024

Transparent objects and surfaces are pervasive in man-made environments and need to be considered in any vision system.
Accurate depth data is a key factor for the reliability of such systems, requiring methods tailored for transparency to overcome the sensing shortcomings.
However, the current state-of-the-art methods to predict the depth of such objects are not yet reliable enough to ensure safe operation of autonomous systems in arbitrary complex environments.
In order to better understand and improve upon existing solutions, we evaluate the performance of a variety of depth estimation methods.
Doing so, we disentangle the different factors impacting their performance.
Among our findings, neural radiance fields offer the best accuracy, but are very sensitive to the number of images used to understand the scene, and do not benefit from any level of object understanding to help them fill in the gaps.
Genomic mechanisms of resistance to tyrosine kinase inhibitors in HER2 amplified breast cancer
Authors: Parsons Heather , Messer Conor , Santos Katheryn , Weiss Jakob , Merrell David , Danysh Brian , Hughes Melissa , Kirkner Greg , Patel Ashka , Hess Julian , Sendrick Kerry , Stewart Chip , Grant Elizabeth , Schlueter-Kuck Kristy , Grinshpun Albert , Wagle Nikhil , Veeraraghavan Jamunarani , Leone José , Freedman Rachel , Metzger Otto , Schiff Rachel , Winer Eric , Tolaney Sara , Rimawi Mothaffar , Krop Ian , Getz Gad , Lin Nancy
Published: April 2024

Though there has been substantial progress in the development of anti-HER2 therapies to treat HER2-positive metastatic breast cancer (MBC) within the past two decades, most patients still experience disease progression and cancer-related death. HER2-directed tyrosine kinase inhibitors (TKIs) can be highly effective therapies for patients with HER2-positive MBC, however, an understanding of resistance mechanisms is needed to better inform treatment approaches. We performed whole exome sequencing on 111 patients with 73 tumor biopsies and 120 cell-free DNA (cfDNA) samples to assess mechanisms of resistance. In 11/26 patients with acquired resistance, we identified alterations in previously characterized genes, such as PIK3CA and ERBB2 that could explain treatment resistance. Mutations in growing subclones identified potential novel mechanisms of resistance in 5/26 patients and included alterations in ESR1, FGFR2, and FGFR4. Additional studies are needed to assess the functional role and clinical utility of these alterations in driving resistance.
Machine Learning based Radiomics from Multiparametric Magnetic Resonance Imaging for Predicting Lymph Node Metastasis in Cervical Cancer
Authors: Liu Jing , Zhu Mingxuan , Li Li , Zang Lele , Luo Lan , Zhu Fei , Zhang Huiqi , Xu Qin
Published: April 2024

Background
Construct and compare multiple machine-learning models to predict lymph node (LN) metastasis in cervical cancer, utilizing radiomic features extracted from preoperative multi-parametric magnetic resonance imaging (MRI).
Methods
This study retrospectively enrolled 407 patients with cervical cancer who were randomly divided into training cohort (n = 284) and validation cohort (n = 123). A total of 4065 radiomic features were extracted from the tumor regions of interest on contrast-enhanced T1-weighted imaging, T2-weighted imaging, and diffusion-weighted imaging for each patient. The Mann-Whitney U test, Spearman correlation analysis, and selection operator Cox regression analysis were employed for radiomic feature selection. The relationship between MRI radiomic features and LN status was analyzed by five machine-learning algorithms. Model performance was evaluated by measuring the area under the receiver-operating characteristic curve (AUC) and accuracy (ACC). Moreover, Kaplan–Meier analysis was used to validate the prognostic value of selected clinical and radiomics characteristics.
Results
LN metastasis was pathologically detected in 24.3% (99/407) of patients. Following three-step feature selection, 18 radiomic features were employed for model construction. The XGBoost model exhibited superior performance compared to other models, achieving an AUC, accuracy, sensitivity, specificity, and F1-score of 0.9268, 0.8969, 0.7419, 0.9891, and 0.8364, respectively, on the validation set. Additionally, Kaplan − Meier curves indicated a significant correlation between radiomic scores and progression-free survival in cervical cancer patients (p < 0.05).
Conclusion
Machine learning-based multi-parametric MRI radiomic analysis demonstrates a promising performance in the preoperative prediction of LN metastasis and clinical prognosis in cervical cancer.
Study on Sliding Surface Characteristics of Expansive Soil Based on Quantitative Evaluation of Microstructure
Authors: Kong Youxing , Li Zhiqing , Qi Zhiyu , Sun Kai , Hu Ruilin
Published: April 2024

Expansive soils are widely distributed and the landslides happened in these area cause significant economic losses. The sliding surface records crucial information about landslides, providing insight into the mechanisms behind their occurrences. This research delves into the microstructural features of landslide surfaces in expansive soils. Various sliding surfaces were created through direct shear tests under different water contents (10%, 20%, 30%) and normal stresses (50 kPa, 100 kPa, 200 kPa, 400 Pa). Scanning electron microscopy (SEM) was used to observe the surfaces and based on their structural morphology and formation mechanisms, we categorized the surfaces’ structure into scratch, tension crack, and residual pore. Four parameters, porosity, average pore area, probability entropy, and area probability distribution index, were calculated and used to quantitatively characterized the surface structures. By correlating field landslide surface features with geological survey data, it was inferred that the triggering moisture content was 25.3–26.8% at least, the sliding surface was situated 10 to 12 meters deep within the slope, and multiple sliding events occurred. The water infiltration from the slope top and precipitation along fractures coupled with rising irrigation water levels that saturated the slope base ultimately leading to fracture layer breakthrough and slope failure.