bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research Progress of Natural Products with the Activity of Anti-nonalcoholic Steatohepatitis
Authors: Wang Rui , Mao Yuheng , Yu Chunping , Rong Zhenji , Wang Ruyue , Wang Yixin , Lv Linjin , Gao Yang , Wang Zhigang , Zhang Hailong 
Published: May 2024

:
Nonalcoholic steatohepatitis (NASH), a multi-target disease, is becoming a global epidemic.
Although several anti-NASH drug candidates are being evaluated in late-stage clinical trials,
none have been approved by the FDA to date. Given the global prevalence of the disease, the lack of
effective drugs, and the very limited therapeutic efficacy of most of the existing synthetic drugs focusing
on a single target, there is an urgent need to continue to develop new therapeutic agents. In
contrast, many natural products, including pure compounds and crude extracts, possess hepatoprotective
activities. Usually, these natural components are characterized by multi-targeting and low
side effects. Therefore, natural products are important resources for the development of new anti-
NASH drugs. In this paper, we focus on reviewing the anti-NASH potential, structure, and some of
the side effects of natural products based on structural classification. We hope this mini-review will
help researchers design and develop new anti-NASH drugs, especially based on the structure of natural
products.
Anticancer Therapy with Proteolysis-targeting Chimeras [PROTACs] Targeting Towards the Tumor-microenvironment: Development, Current
State and Prospects
Authors: Vanangamudi Murugesan , Kaushik Monika , Madeswaraguptha Prathap , Surendran Vijayaraj , Gupta Pawan kumar 
Published: May 2024

Abstract:
Targeted protein degradation is a rapidly expanding area that offers hope for novel approaches
to combat drug resistance. The creation of heterobifunctional proteolysis-targeting chimeras
[PROTACs], a new group of pharmaceutical compounds, has made TPD a useful method for completely
getting rid of harmful proteins using regular small-molecule inhibitors. A big plus is that
PROTACs can target multi-domain proteins that cannot be broken down. This is the case, particularly
for proteins lacking a conserved interaction surface for small-molecule ligands [SMIs] and featuring
smooth surfaces. Poor oral bioavailability and pharmacokinetic [PK] and ADMET [absorption, distribution,
metabolism, excretion, and toxicity] characteristics are among the long-term issues with
traditional PROTACs. Their larger size and more complex structure set them apart from other smallmolecule
inhibitors, which is why they are so effective. Clinical studies have been conducted on a
plethora of PROTAC compounds in the past 20 years, all with the goal of inducing the degradation of
targets relevant to cancer. In this article, we closely examine the major developments and recent advancements
in PROTAC technology. We seek to summarize and fully assess PROTAC-based targeted
protein degradation studies on "undruggable" targets. Discussing their molecular structure, action
mechanism, design concepts, development benefits, and obstacles will help to illustrate the significance
of developing highly successful PROTAC-based techniques in treating many illnesses, including
cancer treatment resistance.
Persistent Inflammation, Immunosuppression, and Catabolism Syndrome in Pediatric Populations: A Brief Perspective
Authors: Santarelli Michael D. , Davis Kelly A. , Stark Ryan J. 
Published: May 2024

Abstract:
Surviving near-lethal insults, such as sepsis, trauma, and major surgery is more common
due to advances in medical care. The decline in mortality has unmasked a population of
chronic critically ill patients, many with the pathological immunophenotype known as Persistent
inflammation, Immunosuppression, and Catabolism Syndrome (PICS). Though initially described
in adults, many critically ill children exhibit the hallmarks of PICS, including lymphopenia, hyperinflammation,
and evidence of ongoing somatic protein catabolism. These patients are plagued
with recurrent infections and suffer worse outcomes. There remains a need to understand the
pathophysiology underlying this condition to elucidate potential therapies and develop interventions.
This perspective provides the most current update of PICS within the pediatric population.
Virtual Analysis for Spinal Cord Injury Rehabilitation
Authors: Narendra Modigari , Mohanty Pratik , Anbarasi L Jani , Ravi Vinayakumar 
Published: May 2024

Background
Spinal cord injuries (SCI) are debilitating conditions affecting individuals worldwide annually, leading to physical, emotional, and cognitive challenges. Effective rehabilitation for SCI patients is crucial for restoring motor function and enhancing their overall quality of life. Advances in technology, including machine learning (ML) and computer vision, offer promising avenues for personalized SCI treatment.

Aims
This paper aimed to propose an automated and cost-effective system for spinal cord injury (SCI) rehabilitation using machine learning techniques, leveraging data from the Toronto Rehab Pose dataset and Mediapipe for real-time tracking.

Objective
The objective is to develop a system that predicts rehabilitation outcomes for upper body movements, highlighting the transformative role of ML in personalized SCI treatment and offering tailored strategies for improved outcomes.

Methods
The proposed system utilized data from the Toronto Rehab Pose dataset and Mediapipe for real-time tracking. Machine learning models, including Support Vector Machines (SVM), Logistic Regression, Naive Bayes, and XGBoost, were employed for outcome prediction. Features such as joint positions, angles, velocities, and accelerations were extracted from movement data to train the models.

Results
Statistical analysis revealed the ability of the system to accurately classify rehabilitation outcomes, with an average accuracy of 98.5%. XGBoost emerged as the top-performing algorithm, demonstrating superior accuracy and precision scores across all exercises.

Conclusion
This paper emphasizes the importance of continuous monitoring and adjustment of rehabilitation plans based on real-time progress data, highlighting the dynamic nature of SCI rehabilitation and the need for adaptive treatment strategies. By predicting rehabilitation outcomes with high accuracy, the system enables clinicians to devise targeted interventions, optimizing the efficacy of the rehabilitation process.
In Silico Prediction of Quercetin Analogs for Targeting Death-Associated Protein Kinase 1 (DAPK1) Against Alzheimer’s Disease
Authors: Sun Yilu , Zhao Jia , Lu Yizhu , Ngo Fung Yin , Shuai Bo , Zhang Zhang-Jin , Feng Yibin , Rong Jianhui 
Published: May 2024

:
Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder that greatly affects
the health and life quality of the elderly population. Existing drugs mainly alleviate symptoms but fail
to halt disease progression, underscoring the urgent need for the development of novel drugs. Based
on the neuroprotective effects of flavonoid quercetin in AD, this study was designed to identify potential AD-related targets for quercetin and perform in silico prediction of promising analogs for the
treatment of AD. Database mining suggested death-associated protein kinase 1 (DAPK1) as the most
promising AD-related target for quercetin among seven protein candidates. To achieve better biological effects for the treatment of AD, we devised a series of quercetin analogs as ligands for DAPK1,
and molecular docking analyses, absorption, distribution, metabolism, and excretion (ADME) predictions, as well as molecular dynamics (MD) simulations, were performed. The energy for drug-protein
interaction was predicted and ranked. As a result, quercetin-A1a and quercetin-A1a1 out of 19 quercetin analogs exhibited the lowest interaction energy for binding to DAPK1 than quercetin, and they had
similar dynamics performance with quercetin. In addition, quercetin-A1a and quercetin-A1a1 were
predicted to have better water solubility. Thus, quercetin-A1a and quercetin-A1a1 could be promising
agents for the treatment of AD. Our findings paved the way for further experimental studies and the
development of novel drugs.
Interactive Health Technology Tool for Kidney Living Donor Assessment to Standardize the Informed Consent Process: Usability and Qualitative Content Analysis
Authors: Ortiz Fernanda , Grasberger Juulia , Ekstrand Agneta , Helanterä Ilkka , Giunti Guido 
Published: May 2024

Background
Kidney living donation carries risks, yet standardized information provision regarding nephrectomy risks and psychological impacts for candidates remains lacking.

Objective
This study assesses the benefit of interactive health technology in improving the informed consent process for kidney living donation.

Methods
The Kidney Hub institutional open portal offers comprehensive information on kidney disease and donation. Individuals willing to start the kidney living donation process at Helsinki University Hospital (January 2019-January 2022) were invited to use the patient-tailored digital care path (Living Donor Digital Care Path) included in the Kidney Hub. This platform provides detailed donation process information and facilitates communication between health care professionals and patients. eHealth literacy was evaluated via the eHealth Literacy Scale (eHEALS), usability with the System Usability Scale (SUS), and system utility through Likert-scale surveys with scores of 1-5. Qualitative content analysis addressed an open-ended question.

Results
The Kidney Hub portal received over 8000 monthly visits, including to its sections on donation benefits (n=1629 views) and impact on donors’ lives (n=4850 views). Of 127 living kidney donation candidates, 7 did not use Living Donor Digital Care Path. Users’ ages ranged from 20 to 79 years, and they exchanged over 3500 messages. A total of 74 living donor candidates participated in the survey. Female candidates more commonly searched the internet about kidney donation (n=79 female candidates vs n=48 male candidates; P=.04). The mean eHEALS score correlated with internet use for health decisions (r=0.45; P<.001) and its importance (r=0.40; P=.01). Participants found that the Living Donor Digital Care Path was technically satisfactory (mean SUS score 4.4, SD 0.54) and useful but not pivotal in donation decision-making. Concerns focused on postsurgery coping for donors and recipients.

Conclusions
Telemedicine effectively educates living kidney donor candidates on the donation process. The Living Donor Digital Care Path serves as a valuable eHealth tool, aiding clinicians in standardizing steps toward informed consent.

Trial Registration
ClinicalTrials.gov NCT04791670; https://clinicaltrials.gov/study/NCT04791670

International Registered Report Identifier (IRRID)
RR2-10.1136/bmjopen-2021-051166
Participatory Disease Surveillance for the Early Detection of Cholera-Like Diarrheal Disease Outbreaks in Rural Villages in Malawi: Prospective Cohort Study
Authors: Valerio Mariana Gasparoto Pereira , Laher Beverly , Phuka John , Lichand Guilherme , Paolotti Daniela , Leal Neto Onicio 
Published: May 2024

Background
Cholera-like diarrheal disease (CLDD) outbreaks are complex and influenced by environmental factors, socioeconomic conditions, and population dynamics, leading to limitations in traditional surveillance methods. In Malawi, cholera is considered an endemic disease. Its epidemiological profile is characterized by seasonal patterns, often coinciding with the rainy season when contamination of water sources is more likely. However, the outbreak that began in March 2022 has extended to the dry season, with deaths reported in all 29 districts. It is considered the worst outbreak in the past 10 years.

Objective
This study aims to evaluate the feasibility and outcomes of participatory surveillance (PS) using interactive voice response (IVR) technology for the early detection of CLDD outbreaks in Malawi.

Methods
This longitudinal cohort study followed 740 households in rural settings in Malawi for 24 weeks. The survey tool was designed to have 10 symptom questions collected every week. The proxies’ rationale was related to exanthematic, ictero-hemorragica for endemic diseases or events, diarrhea and respiratory/targeting acute diseases or events, and diarrhea and respiratory/targeting seasonal diseases or events. This work will focus only on the CLDD as a proxy for gastroenteritis and cholera. In this study, CLDD was defined as cases where reports indicated diarrhea combined with either fever or vomiting/nausea.

Results
During the study period, our data comprised 16,280 observations, with an average weekly participation rate of 35%. Maganga TA had the highest average of completed calls, at 144.83 (SD 10.587), while Ndindi TA had an average of 123.66 (SD 13.176) completed calls. Our findings demonstrate that this method might be effective in identifying CLDD with a notable and consistent signal captured over time (R2=0.681404). Participation rates were slightly higher at the beginning of the study and decreased over time, thanks to the sensitization activities rolled out at the CBCCs level. In terms of the attack rates for CLDD, we observed similar rates between Maganga TA and Ndindi TA, at 16% and 15%, respectively.

Conclusions
PS has proven to be valuable for the early detection of epidemics. IVR technology is a promising approach for disease surveillance in rural villages in Africa, where access to health care and traditional disease surveillance methods may be limited. This study highlights the feasibility and potential of IVR technology for the timely and comprehensive reporting of disease incidence, symptoms, and behaviors in resource-limited settings.
Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study
Authors: Majdik Zoltan P , Graham S Scott , Shiva Edward Jade C , Rodriguez Sabrina N , Karnes Martha S , Jensen Jared T , Barbour Joshua B , Rousseau Justin F 
Published: May 2024

Background
Large language models (LLMs) have the potential to support promising new applications in health informatics. However, practical data on sample size considerations for fine-tuning LLMs to perform specific tasks in biomedical and health policy contexts are lacking.

Objective
This study aims to evaluate sample size and sample selection techniques for fine-tuning LLMs to support improved named entity recognition (NER) for a custom data set of conflicts of interest disclosure statements.

Methods
A random sample of 200 disclosure statements was prepared for annotation. All “PERSON” and “ORG” entities were identified by each of the 2 raters, and once appropriate agreement was established, the annotators independently annotated an additional 290 disclosure statements. From the 490 annotated documents, 2500 stratified random samples in different size ranges were drawn. The 2500 training set subsamples were used to fine-tune a selection of language models across 2 model architectures (Bidirectional Encoder Representations from Transformers [BERT] and Generative Pre-trained Transformer [GPT]) for improved NER, and multiple regression was used to assess the relationship between sample size (sentences), entity density (entities per sentence [EPS]), and trained model performance (F1-score). Additionally, single-predictor threshold regression models were used to evaluate the possibility of diminishing marginal returns from increased sample size or entity density.

Results
Fine-tuned models ranged in topline NER performance from F1-score=0.79 to F1-score=0.96 across architectures. Two-predictor multiple linear regression models were statistically significant with multiple R2 ranging from 0.6057 to 0.7896 (all P<.001). EPS and the number of sentences were significant predictors of F1-scores in all cases ( P<.001), except for the GPT-2_large model, where EPS was not a significant predictor (P=.184). Model thresholds indicate points of diminishing marginal return from increased training data set sample size measured by the number of sentences, with point estimates ranging from 439 sentences for RoBERTa_large to 527 sentences for GPT-2_large. Likewise, the threshold regression models indicate a diminishing marginal return for EPS with point estimates between 1.36 and 1.38.

Conclusions
Relatively modest sample sizes can be used to fine-tune LLMs for NER tasks applied to biomedical text, and training data entity density should representatively approximate entity density in production data. Training data quality and a model architecture’s intended use (text generation vs text processing or classification) may be as, or more, important as training data volume and model parameter size.
Does Fair Value Taxation Affect Banks’ Investment Portfolios and Risk Taking?
Authors: Auer Sylvia , Bornemann Tobias , Eberhartinger Eva 
Published: May 2024

ABSTRACT
We analyze the implications of including fair value changes in taxable income on banks’ asset allocation and risk taking. Exploiting variation in fair value tax regimes and tax rates across 27 countries from 2010 to 2018, we find that fair value taxation is associated with banks’ investment portfolio choices and risk taking. On average, banks hold fewer fair-value taxed securities when fair value taxes increase. This effect is pronounced for savings and cooperative banks. Further, the effect is pronounced for banks that report under local GAAP for tax purposes. Our results also suggest that banks instead invest more in securities that are not taxed at fair value. Lastly, we provide evidence that the risk taking of savings and cooperative banks is positively associated with the tax rate when subject to fair value taxes. In addition, banks that report under local GAAP increase risk taking when subject to fair value taxes.
Data Availability: Data are available from the sources cited in the text.
JEL Classifications: G21; G28; H25; M41.
A Randomized Clinical Trial to Evaluate the Efficacy of an Oral Probiotic in Acne Vulgaris
Authors: Eguren Cristina , Navarro-Blasco Ariadna , Corral-Forteza Marina , Reolid-Pérez Alejandra , Setó-Torrent Núria , García-Navarro Alejandro , Prieto-Merino David , Núñez-Delegido Eva , Sánchez-Pellicer Pedro , Navarro-López Vicente 
Published: May 2024

The relevance of the gut microbiota in some skin inflammatory diseases, including acne vulgaris, has been emphasized. Probiotics could play a role in the modulation of the microbiota, improving the clinical course of this disease. A 12-week randomized, double-blind, placebo-controlled, clinical trial with patients aged 12 to 30 years with acne vulgaris was conducted. The study product was a capsule composed of the probiotic Lacticaseibacillus rhamnosus (CECT 30031) and the cyanobacterium Arthrospira platensis (BEA_IDA_0074B). Patients with improvement in the Acne Global Severity Scale were 10/34 (29.41%) in the placebo group compared with 20/40 (50%) in the probiotic group (p = 0.03). A significant reduction (p = 0.03) in the number of non-inflammatory acne lesions was observed in the probiotic group (–18.60 [–24.38 to –12.82]) vs the placebo group (–10.54 [–17.43 to –3.66]). Regarding the number of total lesions, a reduction almost reaching statistical significance (p = 0.06) was observed in the probiotic group (–27.94 [–36.35 to –19.53]) compared with the placebo group (–18.31 [–28.21 to –8.41]). In addition, patients with improvement attending the Global Acne Grading System were 7/34 (20.58%) in the placebo group vs 17/40 (42.50%) in the probiotic group (p = 0.02). The number of adverse events was similar in both groups. The probiotic used in this study was effective and well tolerated, and it should be considered for acne vulgaris patients.
Penguasaan Konsep Siswa Kelas Xi Mipa Pada Materi Fluida Statis Dalam Model Problem Based Online Learning Menggunakan Gnomio
Authors: Azizah Nafilah Husnaul , Yuliati Lia , Parno Parno 
Published: May 2024

Tujuan penelitian ini adalah untuk mengetahui penguasaan konsep siswa kelas XI MIPA 1 di MAN Pasuruan pada materi fluida statis dalam model problem based online learning menggunakan gnomio. Penelitian ini menggunakan pendekatan mixed-methods dengan instrumen soal berupa pilihan ganda sebanyak 10 butir soal berdasarkan indikator pada tingkatan kognitif. Subjek penelitian terdiri dari 35 siswa kelas XI MIPA 1 di MAN Pasuruan. Hasil penelitian menunjukkan bahwa ada peningkatan yang signifikan untuk penguasaan konsep siswa kelas XI MIPA 1 dengan rata-rata pretest (29,71) sedangkan rata-rata postest (80,00), diuji menggunakan uji N-gain memperoleh hasil 0,72 kategori tinggi. Penelitian ini berguna sebagai referensi untuk peneliti yang lain dalam melakukan penelitian tentang penguasaan konsep siswa dalam model pembelajaran problem based online learning menggunakan gnomio.
The Human Resources Competency Development as the Key to Organizational Success in Indonesia
Authors: Kosasih  , Darmo Ika Suhartanti , Rony Zahara Tussoleha , Fatmawati Endang , Ali Helmi 
Published: May 2024

Purpose: HR competency development is essential for organizational success in Indonesia, examining current practices and impacting organizational performance.

Theoretical Framework: The study is grounded in the Human Resource Management (HRM) literature, precisely the concept of HR competency development. This framework suggests that developing HR competencies, such as strategic thinking, leadership, and communication, can improve organizational performance, including increased employee engagement, productivity, and profitability.

Design/Methodology/Approach: The research design is a qualitative study that involves in-depth interviews with HR professionals from various industries in Indonesia. The data collected from the interviews will be analyzed using content analysis to identify themes related to HR competency development practices and their impact on organizational success.

Findings: The study's findings are expected to provide insights into the current state of HR competency development in Indonesian organizations and the impact of HR competency development on organizational success. The findings will highlight the importance of HR competency development for organizational success in Indonesia.

Research, Practical & Social Implications: This research has implications for research, practice, and society. It will provide empirical evidence on the impact of HR competency development on organizational success in Indonesia, inform HR professionals and leaders about its importance, and lead to the development of HR policies and programs to improve the skills and competencies of Indonesian workers.

Originality/Value: This study focuses on HR competency development in Indonesia, which has yet to receive much attention in the existing literature. It will provide practical insights for HR professionals and organizational leaders.