bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production, biological activities and functional food of modified cassava flour (mocaf)
Authors: Khasanah Yuniar , Anastasia Wheni Indrianingsih  , Triwitono Priyanto , Agnes  Murdiati  
Published: January 2025

Cassava is predominantly produced in tropical regions, including Asia, Africa, and South America. In the developing countries, cassava includes in the big four comestibles with other commodities such as rice, wheat, and maize. It offers several advantages over other crops, such as affordability, ease of consumption, drought tolerance, the ability to grow on in marginal land at lower cost, and beeing the biggest producer of carbohydrates per hectare. However, cassava tuber is quickly perishable, because of its high-water content, making it more susceptible to rotting. To extend their shelf life, one approach is the production of modified cassava flour (mocaf). Mocaf is typically produced through a fermentation process by microorganism involving lactic acid bacteria. Studies have demonstrated that mocaf can serve as the primary ingredients for various food and various foods and snacks, such as cookies, cake, noodles, and others food traditionally made with wheat flour or starch-based material. Compared to regular cassava flour,mocaf offers improved flavor and color and is also more cost-effective than wheat flour. The use of mocaf is promising since several studies also showed the use of mocaf to produce functional foods for human health. The purpose of this review was to elaborate the published articles on the production, biological activities, and functional food from modified cassava flour. The promising potential of mocaf is summarized, along with data on its biological activities in food and health contexts. Furthermore, recommendations for future research on the industrial applications of mocaf are provided.
WITHDRAWN: Heterogeneous liver tissues with multicellular crosstalk and bile duct morphogenesis through organoid bioprinting
Authors: xue shengnan , Su Yijun , Xu Chengao , Xu Mingen , Yao Rui 
Published: January 2025

Abstract

The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Nano-engineered probiotic treats atherosclerosis via inhibiting intestinal microbiota-TMA-TMAO axis
Authors: Ma Boxuan , Chen Zhezhe , Zhu Qiongjun , Xu Hong , Hu Yiqing , Wang Yanan , Chen Zhebin , Wang Yao , Huang Xingru , Fu Guosheng , Zhang Wenbin 
Published: January 2025

Abstract

Considerable numbers of patient are suffering from atherosclerosis without typical risk factors, which can cause severe cardiovascular complication but is lack of practical treatment. Thereinto, trimethylamine N-oxide (TMAO), originated from enteric microorganism, emerges as an unconventional and crucial factor causing atherosclerosis. Here we demonstrate a strategy to inhibit TMAO through intestinal microbiota-trimethylamine (TMA)-TMAO axis for atherosclerotic treatment. The therapy is performed by an oral-treated nano-engineered probiotic PDMF@LGG, where the probiotic Lacticaseibacillus rhamnosus GG (LGG) is armed with polydopamine coating and conjugated with PMF nanoparticles based on a ROS-responsive polymeric prodrug of fluoromethylcholine (FMC). PDMF@LGG can durably colonize the intestinal canal due to sticky polydopamine coating and the protection of PMF against ROS-induced injury. The ROS trigger the delivery of FMC from nanoparticles, which can inhibit TMA production in enteric microorganisms. Meanwhile, LGG can strengthen the tight junctions of intestinal epithelium and reduce TMA entering the blood. The in vivo study suggests that PDMF@LGG reduces plasma TMAO and suppresses atherosclerotic progression. Furthermore, the microbiomics and metabolomics show that PDMF@LGG also regulates gut microbial composition and various metabolites, assisting in the therapeutic outcome. Together, PDMF@LGG offers a potential candidate for atherosclerotic therapy caused by TMAO and broadens the range of treatable atherosclerosis.
CRY1 fuels resistance to T cell-based immunotherapy in NANOGhigh cancers
Authors: Kim Tae Woo , Oh Se Jin , Woo Seon Rang , Ahn Jun Hyeok , Son Min Kyu , Lee Hyo-Jung , Cho Eunho , Lee Kyung-Mi , Park Yejin , Sim Younji , Yee Cassian , Son Gi Hoon , Jung Jong-Wha , Song Kwon-Ho 
Published: January 2025

Abstract

Cancer immunotherapies, including immune checkpoint blockade (ICB), have marked a significant breakthrough in cancer treatment but their clinical efficacy is limited in immune-resistant tumors. Previously, we found that immunotherapy-mediated immune selection enriches immune-resistant tumors with both tumor-intrinsic and -extrinsic refractory phenotypes via the transcriptional induction of HDAC1 by NANOG. Here, we identify CRY1 as a critical transcriptional target of NANOG that stabilizes Cyclin A and MCL1 to promote cancer stem cell-like property and resistance to cytotoxic T cell-mediated killing in NANOGhigh tumor cells through HDAC1-mediated epigenetic silencing of APC3 and TRIM17. Additionally, CRY1 downregulates CXCL10 via HDAC1-mediated repression, thereby suppressing T cell infiltration. Importantly, CRY1 inhibition synergizes with PD-1 blockade and adoptive T cell transfer in reducing tumor growth by converting immune-resistant tumors into immune-sensitive tumors. Collectively, these findings highlight CRY1 as a critical mediator of the NANOG/HDAC1 axis in the multiple refractory properties of immune-resistant tumors and suggest CRY1 as a potential therapeutic target.
Prevalence of overweight and obesity among health care professionals: A Multi-institutional Cross-Sectional Study
Authors: Ashraf Fariha , Silvia Sana , Ayub Bushra , Nisa Kanwal , Murtaza Ghulam 
Published: January 2025

Abstract

· KEYPOINTS: High Prevalence of Overweight and Obesity: The study found a significant number of healthcare workers in Pakistan are overweight or obese.
· Use of Asia Pacific BMI: The research utilized the Asia Pacific BMI classification, which is considered more suitable for assessing weight status in this region compared to the traditional Western BMI.
· Identification of Risk Factors: The study aimed to identify potential occupational risk factors that contribute to the high prevalence of overweight and obesity among healthcare workers.
· Need for Interventions: The findings emphasize the need for targeted interventions to improve the health and well-being of healthcare workers in Pakistan, such as promoting healthy lifestyles, creating supportive work environments, and providing relevant training and education programs.
Empowering Nurses to Provide Palliative Care for COPD Patients in a Pulmonary Department: Participatory Action Research
Authors: far narjes heshmati , amini mahnaz , talab Hamid reza Zendeh , Manzari Zahra Sadat 
Published: January 2025

Abstract

Background
Chronic obstructive pulmonary disease (COPD) affects the quality of life of patients and their caregivers. Although palliative care can improve quality of life, COPD patients and their caregivers have limited access to palliative care services. This study was conducted to empower nurses to provide palliative care to COPD patients in the pulmonary department.
Methods
This participatory action research was conducted in four steps: observation, reflection, planning, and action. The data were collected via PCKT, FATCOD-B, and PCPS questionnaires about palliative care, interviews, focus groups, and observation. Qualitative content analysis and paired t-tests were used for data analysis.
Results
Three major themes emerged: professional incompetence in palliative care, basic shortages in palliative care, and a lack of professional support. Three changes were made, including enhancing palliative care knowledge, establishing a palliative care team, and increasing career motivation. There were significant increases in PCKT, FATCOD-B, and PCPS scores before and after PAR (p = 0.000).
Conclusion
Given the importance of providing palliative care, necessary measures and actions, including developing interprofessional collaboration and training as well as motivating staff, should be taken by health managers.
Advanced Machine Learning-Driven Cyber Attack Detection in the Internet of Medical Things (IoMT) Ecosystem
Authors: Gopinath M , Man V. Gnana Sri , Ram M. Aditya , Khan Sajid , Kumar Praveen 
Published: January 2025

Abstract

Today, the rise of the Internet of Medical Things (IoMT) has evolved into a highly valued global market worth billions of dollars. However, this growth has also created many opportunities for massive and advanced attack scenarios due to the vast number of devices and their interconnected communication networks. Based on recent reports, it is observed that during the Covid-19 pandemic, the necessity of the IoMT ecosystem has increased significantly. On the other hand, attackers and intruders aim to impair data integrity and patient safety with the prevalence of sophisticated cyber attacks including Man in the Middle (MITM) attacks like spoofing and data injection. This research work uses the WUSTL-EHMS-2020 dataset to present a strong machine learning-based attack detection method. To tackle the distinct security issues of IoMT, we provide an ensemble model that combines Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) classifiers. By utilizing the complementing advantages of SVM's decision boundary precision and XGBoost's gradient-based optimization, our model outperforms baseline techniques with a superior detection accuracy of 94.29%. Further, it examines the applicability of a proposed model for IoMT-specific features, including heterogeneous medical device communication, resource limitations, and patient data sensitivity and compares the model with other IoT and IoMT datasets, revealing how cyberattack patterns vary based on environment. Thus this research work advances the creation of trustworthy and scalable cybersecurity solutions for Internet of Medical Things systems.
Propagation Modeling and Performance Analysis on Millimetre Waves for 5G and Beyond Mobile Networks Using OFDM
Authors: Farah Abdiaziz Hersi , Jete Ahmed Adan , Mohamud Abdiaziz Osman , Ali Abdirahman Farah 
Published: January 2025

Abstract

Recent studies have explored millimeter wave (mm-Wave) communication as a crucial enabling technology for advanced connectivity in 5G and future mobile networks. However, mm-wave transmissions face challenges, including a low signal-to-noise ratio and a high likelihood of outages due to significant propagation losses and sensitivity to obstructions. This thesis delves into the characteristics of millimeter wave propagation and presents modeling results for 5G cellular networks operating at frequencies of 6 GHZ, 38 GHz, and 73 GHz in densely populated urban areas. Simulations were conducted using the NYUSIM simulator to assess the performance of mm-wave channel characteristics, with results compared to previously collected field data from another research. Our analysis focuses on significant mm-wave properties, including path loss, delay spread, and power delay profile, for both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. We also investigate how the features and performance of different millimeter wave frequencies change as the distance between the transmitter and receiver increases. This comparison includes omnidirectional and directional propagation in a smaller microcell versus a cell five times larger. Our findings suggest that all 5G deployments could feasibly support mm-wave communication.
Pine Pollen-Derived Activated Carbon for High-Performance Supercapacitor Electrodes: A Comparative Study of KOH and CuCl 2 Activation
Authors: Atalay Funda Ersoy , Kaya Harun , Korkmaz Aydan Aksogan , Guler Seher 
Published: January 2025

Abstract

Carbon-containing materials are vital for supercapacitor electrodes. Activated porous carbons are especially attractive due to their high surface area, conductivity, and porous structure, making them ideal for double-layer supercapacitors. Recently, researchers have turned to biological materials like bacteria, algae, fungi, and pollen to create porous carbon structures. Among these, pine pollen stands out for its abundance and ease of collection. This study focused on converting pine pollen into porous carbon using hydrothermal carbonization in water, followed by activation with different agents. The carbonized pollen was activated with KOH and CuCl2 at various ratios to form nanostructured porous carbons. Scanning electron microscope images showed that activation with KOH and CuCl2 partially altered the pollen morphology. The sample with a 1:2 pollen-to-KOH ratio had the highest surface area at 2030.32 m²/g. To evaluate their electrochemical performance, supercapacitor electrodes were created using two types of activated carbons. The specific capacitance of KOH-activated carbon (KAC) was 230 F/g, while CuCl2-activated carbon (CuAC) showed 175.9 F/g, both at 5 A/g. After 5000 charge-discharge cycles, KAC retained 76% of its capacitance, and CuAC retained 93%. These results demonstrate pine pollen's potential as a precursor for high-performance porous carbons.
Age and Sex-Based Differences in Therapy Preferences Among Patients with Cancer: Evidence from a Novel Therapy Preference Scale
Authors: Dhakal Prajwal , Wichman Christopher S. , Pozehl Bunny J , Elnair Radowan , Yellala Amulya , Mahato Kalika , Bhatt Vijaya Raj 
Published: January 2025

Abstract

Background
Patients’ preferences are crucial to formulating personalized treatment plans. We developed a self-reported questionnaire, Therapy Preference Scale (TPS), to examine treatment preferences of patients with cancer.
Methods
TPS has 30 questions-19 on patients' preferences on safety, quality of life, and treatment effectiveness, 8 questions on importance of various treatment characteristics, and 3 on patients' preferred intent of therapy, expenses, and life expectancy gain. We recruited 300 adults>18 years with a cancer diagnosis and categorized them into 4 age-by-sex groups (younger men<60 years, older men≥60 years, younger women<60 years, older women≥60 years). Kruskal-Wallis non-parametric ANOVA method was used to compare responses among 4 groups.
Results
Older women, compared to other groups, were more likely to value maintenance of cognitive function and ability to perform daily activities. Older women were more likely to risk having a shorter life expectancy rather than facing the risk of long-term cognitive impairments. Younger men and women were more likely to accept more effective treatment, even if it caused significant pain. A higher percentage of younger men, compared to other groups, valued maintaining sex life. Older men and women were more likely to prefer oral pills over intravenous therapy.
Conclusion
Patient preferences may vary based on age and sex with older women prioritizing cognitive and physical function independence more frequently, whereas younger men and women willing to pursue more effective treatment options even with a greater risk of significant pain. TPS can elicit detailed preferences of an individual patient to facilitate shared decision-making with their oncologists.
Benchmarking Machine Learning Models for Cell Type Annotation in Single-Cell vs Single-Nucleus RNA-Seq Data
Authors: Tortelote Giovane 
Published: January 2025

Abstract

Background
Machine learning (ML) models can automate cell annotation and reduce human bias. However, it remains unclear which ML model best suits the characteristics of single-cell RNA sequencing data and whether a trained model can be applied to transcriptomes collected from nuclei rather than whole cells. This study evaluates the performance of eight selected ML models for cell annotation in single-cell (scRNA-seq) vs single-nucleus (snRNA-seq) RNA sequencing datasets, focusing on their ability to generalize across datasets with varying cell populations and transcriptome isolation techniques.
Results
In the first part, we use two publicly available scRNA-seq datasets of Peripheral Blood Mononuclear Cells (PBMC3K and PBMC10K) to assess the performance of each ML model in cell type classification within and across datasets. XGBoost achieved high accuracy (95.4%-95.8%), precision, and F1-scores, outperforming simpler models like Logistic Regression and Naive Bayes. Ensemble methods like XGBoost and Random Forest demonstrated strong precision and recall. Elastic Net demonstrated nearly as good generalizability achieving high accuracy (94.7%-95.1%). In the second part, we investigated the impact of transcriptome isolation techniques (single-cell vs. single-nucleus RNA-seq) on ML model performance using the publicly available cardiomyocyte differentiation datasets (GSE129096). Although models like XGBoost and Elastic Net excelled in single-cell data (accuracy and F1-scores > 95%), performance declined notably in single-nucleus data, suggesting inherent transcriptomic differences can impact ML model classification capacity. Notably, all models struggled with classifying intermediate-stage cells, highlighting challenges in distinguishing transitional cell populations, such as cardiac progenitors that retain stem cell markers while showing expression of differentiated cell markers.
Conclusion
ML models can be trained and applied to classify cells origination from both scRNA-seq and snRNA-seq. Ensemble tree-based models and penalized elastic regression demonstrated superior performance and generalizability across diverse datasets, emphasizing the importance of model selection for robust cell annotation. These findings underscore the need for tailored computational approaches when working with heterogeneous transcriptome data.
Pack-Years as a Stable Predictor of Cancer Incidence and Mortality: A Prospective Cohort Study from the UK Biobank
Authors: Liao Jiaojiao , Wang Zhaoyu , Liu Yu , Li Zhaoji , Wang Hui , Tao Liyuan 
Published: January 2025

Abstract

Background
To clarify the dose-response relationship between cigarette smoking and the risk of developing or dying from multiple site-specific cancers.
Methods
We prospectively analyzed baseline smoking pack-years in relation to cancer incidence and mortality in the UK Biobank, with data obtained from national cancer registries. Using a competing risk model, we assessed the associations between smoking pack-years and cancer outcomes, adjusting for age, gender, ethnicity, BMI, SES, drinking habits, and family cancer history.
Results
The study involved 336,885 individuals with a mean age of 55.9 years (SD 8.07), 53% of whom were female. There were 33,099 (9.8%) current smokers with an average of 27.16 (SD 18.38) pack-years and 87,241 (25.9%) former smokers with an average of 21.36 (SD 18.24) pack-years. Over a median follow-up of 13.93 years, 36,964 cancer events and 11,931 cancer deaths were recorded. The incidence and mortality risks of overall cancers increased linearly with smoking pack-years. Each additional pack-year increased the risk of all cancers by 0.9% (HR = 1.009, 95% CI = 1.008–1.009) and smoking-related cancers by 1.7% (HR = 1.017, 95% CI = 1.017–1.018). Cancer mortality rose by 1.5% per pack-year (HR = 1.015, 95% CI = 1.015–1.016), particularly in lung, bladder, esophageal, liver, and stomach cancers, with HRs ranging from 1.010 to 1.028. The study highlights the linear relationship between smoking pack-years and cancer risk, especially for smoking-related cancers. However, some cancers showed no significant correlation or an opposite effect.
Conclusion
Pack-years of smoking provide a linear representation of smoking’s impact on cancer incidence and mortality, significantly affecting various malignancies, particularly smoking-related ones.
Cost Comparison of a Multivariant Vacation and Working Vacation Queuing Model With Different Kind of Waiting Servers
Authors: R Remya 
Published: January 2025

Abstract

The research delves into evaluating the efficiency of different models in queueing systems with service interruptions, aiming to optimize service rates and enhance customer satisfaction. To determine the most cost-effective model for a single server serving multiple variants with working vacation periods and waiting servers. The study employs probability generating functions and MATLAB techniques to analyze and compare three queueing models.Findings: The research provides a steady-state solution and cost analysis for the examined models, shedding light on the optimal approach for managing service interruptions. The study contributes to operations management by offering insights into improving queueing systems' performance and customer service through efficient model selection. The data used in the study includes service times and vacation lengths following exponential distributions. The research involves analyzing the models' performance using probability generating functions and MATLAB simulations to compare their cost-effectiveness. The study addresses the question of which model among the three considered is the most efficient in terms of cost and service quality. The study identifies the most effective queueing model among the evaluated options for optimized service rates and enhanced customer satisfaction.
Mathematics Subject Classification (2000) 60K25 . 68M20 . 90B22
A novel SadP-scFv UCHT1 lectibody activates T cells and mediates lysis in Burkitt’s lymphoma cells
Authors: Tomisch Jana , Gräber Jonas , Makshakova Olga N. , Salavei Pavel , Rosato Francesca , Mariscal Sarah Frisancho , Varrot Annabelle , Imberty Anne , Römer Winfried 
Published: January 2025

Abstract

Purpose
Abnormal glycosylation has been long considered a hallmark of cancer progression. Carbohydrate-binding proteins, also known as lectins, offer a unique way to target glycosylation changes in malignant cells. The present study repurposes SadP, a lectin from Streptococcus suis, to target globotriaosylceramide (Gb3), a glycosphingolipid overly abundant in many cancer types including Burkitt’s lymphoma. SadP was genetically fused to a scFv of an anti-CD3 antibody, resulting in a bispecific T cell engager (BiTE)-like protein referred to as lectibody.
Methods
The lectibody was designed as a fusion protein by genetically linking the SadP to the scFv UCHT1 anti-CD3 antibody. Protein expression was carried out in Escherichia coli and the resulting lectibody was purified using affinity and size exclusion chromatography. The lectibody was tested for its specificity in binding Gb3-positive cancer cells by flow cytometry. T-cell-mediated cytotoxicity was measured in a bioluminescence-based cytotoxicity assay, and T-cell activation was assessed by evaluating CD69 and CD71 expression on PBMCs, incubated with target cells and the lectibody.
Results
The present study demonstrates that the SadP-scFv UCHT1 lectibody can redirect T cell cytotoxicity towards Gb3+ Burkitt’s lymphoma cells, resulting in a dose-dependent target cell lysis up to 65% in-vitro at a concentration of 10 nM. In the same experimental setting, negative control cells characterized by a low or absent Gb3 content remained unaffected. Lectibody-induced T cell activation resulted in a significant increase in CD69 and CD71 surface expression in PBMCs incubated with SadP-scFv UCHT1 and Gb3+ cancer cells.
Conclusion
This study highlights the potential of lectins in immunotherapy for the treatment and eradication of malignant cells. The SadP-based lectibody demonstrates improved efficacy and yield when compared to the previously published StxB-scFv UCHT1 lectibody, therefore opening the possibility for its use in an in-vivo model.