bluuebunny/crossref_metadata_2025 huggingface dataset:
Marine-Derived Compound Targeting mTOR and FGFR-2: A Promising Strategy for Breast, Lung, and Colorectal Cancer Therapy
Authors: Mythili Vijay Murali Ravi , K Kumaran , Chattopadhyay Sayantani , Basha Shahjahan Ahmad , Sekar Sruthi , Senthil Sowmya , D Prabhu , Rangasamy Kirubakaran , ArulJothi KN
Published: January 2025

Introduction:

The marine habitat is a plentiful source of diverse, active compounds that
are extensively utilised for their medicinal properties. Pharmaceutical trends have currently
changed towards utilising a diverse range of goods derived from the marine environment.

Method:

This study aimed to examine the inhibitory effects of bioactive chemicals derived from
marine algae and bacteria. The identification of these compounds was carried out through the process
of Gas Chromatography-Mass Spectrometry (GC-MS) profiling. Subsequently, these compounds
were subjected to docking simulations against a specific set of target proteins that are
known to be frequently overexpressed in three distinct types of cancer.

Result:

From the docking results, the ligand 1,4:3,6:5,7-Tribenzal-beta-mannoheptitol was found to
be effective against the proteins mTOR (PDB ID: 4JSV) and FGFR2 (PDB ID:6V6Q). The findings
of this study highlight the significant benefits offered by the tool under investigation, which effectively
enhances the efficiency of the docking procedures.

Conclusion:

These compounds hold significant potential for further development and exploration
in the field of cancer therapeutics.
Jellyfish Collagen as a Promising Source for Nutraceutical and Biomedical Applications
Authors: James Saira , Tilvi Supriya
Published: January 2025

Jellyfish blooms have become increasingly common worldwide, driven by climate
change, eutrophication, and the jellyfish’s unique life cycle. The rich protein derived from these
resources notably, jellyfish collagen (JFC) and its hydrolysates (JFCH) peptides stands out as
promising, sustainable alternatives to traditional collagen sources like bovine and rat tail collagen.
Notably, JFC carries a reduced risk of prion and viral contamination, making it a safer option for
diverse applications. As a fundamental collagen form, JFC is compatible with various cell types,
enhancing its utility across multiple domains. Furthermore, JFCH peptides act as potent bioactive
ingredients, especially in the food industry, where their high antioxidant properties are valued in
nutraceutical formulations. Immunological research also suggests that JFC can promote
immunoglobulin production and stimulate cytokine synthesis, revealing its potential for immune
system support. Due to its versatility, JFC can facilitate the growth of various human cell types,
positioning it as an effective biomaterial for wound care, tissue engineering, cartilage regeneration,
drug delivery, and cell culture applications. This review highlights recent advancements in JFC and
JFCH applications across nutraceuticals, immunology, wound healing, tissue engineering, and
regenerative medicine in —those not extensively covered in previous literature.
Screening of Candidate Chemical Regulators for the m6A Writer MTA in Arabidopsis
Authors: Lei Beilei , Jia Chengchao , Tan Cuixia , Ding Pengjun , Li Zenglin , Yang Jing , Liu Jiyuan , Wei Xiaomin , Tao Shiheng , Ma Chuang
Published: January 2025

Background:

The MTA gene encodes a core component of m6A methyltransferase complex,
which plays a crucial role in the post-transcriptional modification of RNA that influences
many vital processes in plants. However, due to the constraint of embryonic lethality in MTA
knockout mutation, the molecular function of MTA gene has yet to be comprehensively investigated.

Objective:

The aim of this study is to investigate the expression and regulation of MTA in Arabidopsis.

Methods:

A large-scale transcriptome and genome analysis were carried out for the expression and
nsSNP (non-synonymous Single Nucleotide Polymorphism) studies. Structured-based virtual screening,
molecular dynamics simulation, binding free energy calculation and m6A modification level assay
were employed to mine and validate MTA regulators from COCONUT natural product database.

Results:

Tissue-specific expression and stress-responsive expression patterns of MTA were observed
in Arabidopsis. nsSNPs from the 1,001 Arabidopsis project were not detected in the binding
site of the methyl-donor substrate S-adenosylmethionine (SAM) in MTA. 10 small molecules were
identified as potential regulators, among which CNP0251613 (adenosine diphosphate glucose,
ADPG) was selected and validated to decrease m6A levels at 10 μM vs. the control in Arabidopsis.

Conclusion:

Our results provide a new insight and chemical entity into the in-depth study of RNA
m6A writer MTA in plants.
Research on Controllable Synthesis and Growth Mechanism of Sodium Vanadium Fluorophosphate Nanosheets
Authors: Yuan Xinran , Teng Aijun , Liu Tianhao , Yang Yadong , Xin Yanan , Yong Lingling , Zhang Dongbin
Published: January 2025

Background:

Sodium vanadium fluorophosphate is a sodium ion superconductor material
with high sodium ion mobility and excellent cyclic stability, making it a promising cathode material
for sodium-ion batteries. However, most of the literature and patents report preparation through
traditional methods, which involve complex processes, large particle sizes, and low electronic conductivity,
thereby limiting development progress.

Objective:

Aiming at the limitation of high cost and poor performance of vanadium sodium fluorophosphate
cathode material, the low temperature and high-efficiency nano preparation technology
was developed.

Methods:

This study uses a homogenizer with high dispersion and shear force to directionally control
the collision of sodium vanadium fluorophosphate nanoparticles with higher specific surface
energy during the initial nucleation stage, forming nanosheet structures.

Results:

The growth mechanism of these nanosheets was analyzed using SEM, XRD, AFM, and
DFT simulation. Results indicate that the crystal surfaces with higher surface energy undergo directional
collisions in the early nucleation stage, gradually reducing the surface energy and stabilizing
the system, resulting in sodium vanadium fluorophosphate nanosheets.

Conclusion:

Due to the larger specific surface area and pore structure, these nanosheets exhibit excellent
rate performance and cycle stability, making them suitable for application and promotion in
the field of fast-charging energy storage.
Recent Advances in Nanoformulations of Citrus Bioactives & Potential Health Benefits
Authors: Verma Minakshi , Das Alok Kumar
Published: January 2025

Citrus fruits are widely recognized not only for their refreshing taste but also for their
rich content of bioactive compounds, including flavonoids, carotenoids, and essential oils. The molecular
mechanisms through which citrus-derived compounds exert their effects highlight their antioxidant,
anti-inflammatory, anticancer, and cardioprotective properties. Flavonoids, such as hesperidin
and naringin, exhibit potent antioxidant and anti-inflammatory properties, reducing oxidative
stress and inflammation-related diseases. Carotenoids like beta-cryptoxanthin and lutein offer protective
effects against various cancers and support eye health. The essential oils, dominated by limonene,
show promising anticancer, antimicrobial, and cardioprotective effects. The role of citrus bioactive
in modulating metabolic pathways, improving immune function, and promoting gut health.
Nanoformulation of citrus-based compounds involves the development of nanometer-scale formulations
of active ingredients derived from citrus plants. These formulations show the promising effect
of preventing and managing chronic diseases such as diabetes, cardiovascular diseases, and certain
types of cancer. The bioavailability and metabolism of citrus bioactive, emphasizing the importance
of food matrix interactions and individual variability. By exploring current research, it is easy to
understand the health benefits of citrus fruits and their therapeutic potential in nutritional science
and preventive medicine.
Isolation and Structural Determination of Cyclic Dipeptides Produced by Arthrobacter sp.
Authors: Arije Amonah T. , Agbakpo Andy E. , Patel Shivam G , Fox Sean J. , Shilabin Abbas G.
Published: January 2025

Introduction:

Arthrobacter is a genus of bacteria that has gained recent attention due to
its unique ability to produce bioactive compounds that possess potential antimicrobial properties.

Method:

In this study, we isolated two cyclic dipeptides (CDPs) from Arthrobacter sp. obtained
from a soil sample.

Result:

The isolated Arthrobacter sp. exhibited inhibitory activity against a filamentous indicator
bacterium and a violacein-producing Janthinobacterium sp. Cultivation of Arthrobacter sp.
TAJX1902 was carried out using rich medium broth and agar to facilitate the extraction of metabolites.
The isolated compounds were characterized through spectroscopic techniques. GCMS analysis
of the crude extract revealed the presence of bioactive cyclic dipeptides.

Conclusion:

The structures of the isolated CDPs were determined as acylated cyclo(Dphenylalanine-
4-hydroxy-D-proline) (1) and cyclo(D-phenylalanine-D-proline) (2). Furthermore,
two additional metabolites, 2,4-dihydroxypyrimidine (3) and 2,4-dihydroxy-5-methylpyrimidine (4),
were identified and verified through NMR spectral analysis.
Lavender Oil: A Versatile Natural Therapeutic – Extraction, Composition, Applications, and Innovative Formulation Strategies
Authors: Shaikh Farooque , Harde Manoj , Mallya Rashmi
Published: January 2025

The present review comprehensively explores an overview of a versatile essential oil from
genus Lavandula. Oil finds wide application in the aromatherapy and cosmetic industry. This paper
emphasizes the chemical constituents of the oil that are responsible for the diverse therapeutic applications.
Various extraction techniques, such as steam distillation, hydro distillation, supercritical
liquid extraction and ultrasound assisted extraction are discussed. Also the article elucidates the
mechanism of action that explains the therapeutic application of the oil in microbial infections, oxidative
stress and neurodegenerative diseases. This review also extensively discusses the preclinical
and clinical studies of the use of the oil for the management or treatment of psoriasis, depression,
wound, anxiety, Alzheimer’s’ disease, myocardial infarction, acute lung injury and acute inflammation.
Additionally, the article highlights granted patents and the novel formulation strategies such as
hydrogels, nanofibers, emulsions and nanoparticles used to enhance the bioavailability and the targeted
delivery of the oil. The review also provides future perspectives, emphasizing the need for
further research for harnessing the potential of lavender oil.
Preparation, Computational and Spectroscopic Analysis of an Efficient Medicinal Molecule: 4-Bromoquinoline-2-carboxaldehyde
Authors: Mir M. Amin
Published: January 2025

Introduction:

This paper presents the synthesis, spectroscopic characterization, and
computational modeling of 4-Bromoquinoline-2-carboxaldehyde (4-BQCA), an effective therapeutic
compound. 4-BQCA, a quinoline derivative, has drawn interest because of its distinct chemical
structure and its medical uses.

Method:

The chemical was produced with excellent yield and purity using a simple, repeatable
reaction route. Density functional theory (DFT) studies were carried out to learn more about the
compound's molecular characteristics, including its electronic structure, bonding, and stability. The
structure and functional groups found in 4-BQCA were verified by spectroscopic investigation,
which included UV-Vis, FT-IR, NMR, and mass spectrometry.

Result:

The compound's stability and advantageous electrical characteristics are highlighted by the
results of both computational and experimental methods, indicating that it may find application in
medication design and development.

Conclusion:

These results offer a starting point for further investigations into the biological activity
and therapeutic effectiveness of 4-BQCA, indicating that it is a viable option for more study in
pharmaceutical applications.
Notas sobre o ensino universitário da sociologia e a profissão de sociólogo
Authors: Gonçalves Carlos Manuel
Published: January 2025

A set of synthetic notes on university teaching of sociology and the profession of sociologist are presented. The aim is to contribute to the debate, which must be continued and permanent within the professional group of sociologists. In the case of teaching, data on its institutional demand and supply are presented, which will serve to discuss some attributes of sociologists in the job market.
Dongalábas gyermekek szüleinek internethasználata, illetve a dongalábbal kapcsolatos internetes tartalmak elemzése
Authors: Szabó Miklós Károly , Ökrös Konrád , Gresits Orsolya , Szeverényi Csenge
Published: January 2025

A dongaláb diagnosztizálása akár már az intrauterin életben is megtörténhet. A szülők a gyermekük betegségéről azonban jellemzően csak hetekkel később kapnak tájékoztatást. Mindeközben bőven van idejük arra, hogy az interneten keressenek információkat. A szerzők kutatásuk során arra voltak kíváncsiak, vajon mit találnak a szülők az interneten és hogyan értékelik az ott talált információkat. A szerzők a dongalábas gyermekek szülei között kérdőívet töltettek ki az internethasználatukkal kapcsolatban, illetve a „dongaláb” kulcsszót a Google keresőjébe beírva, áttekintették az első 20 weboldal tartalmát és megbízhatóságát. A tartalmi elemzés egy 100 pontos pontrendszer segítségével történt, míg a megbízhatósági elemzéshez az EgészségKommandó pontrendszerét használták. A válaszolók 97,2%-a jelezte, hogy mielőtt ortopéd orvoshoz fordult, információt keresett az interneten a dongalábról. A szülők 32,9%-a nem találta teljesen érthetőnek, 60%-a pedig nem találta elegendőnek az interneten talált információkat. A tartalmi értékelés alapján egyetlen honlap sem felelt meg a „jó” minőségi kritériumnak. Az EgészségKommandó pontrendszere alapján egyetlen honlap volt csak hitelesnek tekinthető. A szülők nagyon gyakran fordulnak az internethez információért, azonban az ott találtak egy része nem érthető és nem elegendő a számukra. A dongalábas weboldalak tartalma szakmai szempontból is közepes, gyenge minőségű. A helyzet javítása érdekében szükség lenne az internetes tartalmak frissítésére, korszerűsítésére. Mindezek azon túl, hogy segítik a betegek tájékoztatását, az orvosi munka végzését is megkönnyítik, és az orvos-beteg kapcsolatot is javítják.
Penerapan Metode ARIMA dalam Memprediksi Jumlah Impor Mobil di Indonesia pada Tahun 2023
Authors: Mardhani Dwi Novianto  , Riza Isna Khoirun Nisa  , Muhamad Rizky Febriawan
Published: January 2025

Sektor industri transportasi terus berkembang secara masif, tidak terkecuali untuk transportasi roda empat yang banyak diminati yaitu mobil. Menurut data dari laman Gabungan Industri Kendaraan Bermotor Indonesia (GAIKINDO) tahun 2022, total penjualan mobil secara keseluruhan sebanyak 1.048.040 unit, total produksi dalam negeri mencapai 1.470.146 unit, dengan jumlah ekspor sebanyak 473.602 unit, dan jumlah impor sebanyak 83.298 unit. Hal itu menunjukkan bahwa angka produksi dalam negeri sudah dapat mencukupi kebutuhan pembeli tanpa melakukan impor dari luar negeri. Namun, terdapat alasan-alasan penting yang menjadikan impor mobil tetap diperlukan setiap tahun. Salah satu alasan utamanya adalah ketersediaan model dan jenis mobil tertentu yang tidak diproduksi secara lokal. Berdasarkan hal tersebut, dibutuhkan metode untuk memprediksi jumlah impor mobil pada tahun 2023. Berkaitan dengan itu, pada penelitian ini dilakukan prediksi jumlah impor mobil menggunakan metode ARIMA. Model ARIMA terbaik yang digunakan untuk peramalan adalah ARIMA(2,1,2). Hasil peramalan yang diperoleh untuk bulan Juli s.d. Desember 2023 secara berturut-turut adalah 8073,926; 10001,218; 11337,540; 11070,056; 9753,595; dan 8719,446 dengan nilai MAPE yaitu 26,61.
Pelabelan Total Koprima
Authors: Komarullah Hafif
Published: January 2025

Pelabelan total koprima merupakan pengembangan dari pelabelan prima. Pelabelan total prima pada graf  adalah suatu fungsi injektif  sedemikian sehingga jika  dengan , maka setiap titik yang bertetangga relatif prima dan setiap label sisi-sisi yang bersisian dengan satu titik harus relatif prima. Nilai minimum  pada pelabelan titik dan sisi prima pada graf  disebut total coprime number yang dinotasikan dengan  Penelitian ini termasuk penelitian eksploratif yang bertujuan untuk menambah wawasan atau pengetahuan dan memunculkan gagasan baru pada teori graf khususnya dalam topik pelabelan graf. Dalam penelitian ini diperoleh bahwa total coprime number pada graf lintasan dan graf cycle berturut-turut adalah   dan
Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study
Authors: Holler Emma , Ludema Christina , Ben Miled Zina , Rosenberg Molly , Kalbaugh Corey , Boustani Malaz , Mohanty Sanjay
Published: January 2025

Background

Postoperative delirium (POD) is a common complication after major surgery and is associated with poor outcomes in older adults. Early identification of patients at high risk of POD can enable targeted prevention efforts. However, existing POD prediction models require inpatient data collected during the hospital stay, which delays predictions and limits scalability.

Objective

This study aimed to develop and externally validate a machine learning-based prediction model for POD using routine electronic health record (EHR) data.

Methods

We identified all surgical encounters from 2014 to 2021 for patients aged 50 years and older who underwent an operation requiring general anesthesia, with a length of stay of at least 1 day at 3 Indiana hospitals. Patients with preexisting dementia or mild cognitive impairment were excluded. POD was identified using Confusion Assessment Method records and delirium International Classification of Diseases (ICD) codes. Controls without delirium or nurse-documented confusion were matched to cases by age, sex, race, and year of admission. We trained logistic regression, random forest, extreme gradient boosting (XGB), and neural network models to predict POD using 143 features derived from routine EHR data available at the time of hospital admission. Separate models were developed for each hospital using surveillance periods of 3 months, 6 months, and 1 year before admission. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Each model was internally validated using holdout data and externally validated using data from the other 2 hospitals. Calibration was assessed using calibration curves.

Results

The study cohort included 7167 delirium cases and 7167 matched controls. XGB outperformed all other classifiers. AUROCs were highest for XGB models trained on 12 months of preadmission data. The best-performing XGB model achieved a mean AUROC of 0.79 (SD 0.01) on the holdout set, which decreased to 0.69-0.74 (SD 0.02) when externally validated on data from other hospitals.

Conclusions

Our routine EHR-based POD prediction models demonstrated good predictive ability using a limited set of preadmission and surgical variables, though their generalizability was limited. The proposed models could be used as a scalable, automated screening tool to identify patients at high risk of POD at the time of hospital admission.
Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study (Preprint)
Authors: Holler Emma , Ludema Christina , Ben Miled Zina , Rosenberg Molly , Kalbaugh Corey , Boustani Malaz , Mohanty Sanjay
Published: January 2025

BACKGROUND

Postoperative delirium (POD) is a common complication after major surgery and is associated with poor outcomes in older adults. Early identification of patients at high risk of POD can enable targeted prevention efforts. However, existing POD prediction models require inpatient data collected during the hospital stay, which delays predictions and limits scalability.

OBJECTIVE

This study aimed to develop and externally validate a machine learning-based prediction model for POD using routine electronic health record (EHR) data.

METHODS

We identified all surgical encounters from 2014 to 2021 for patients aged 50 years and older who underwent an operation requiring general anesthesia, with a length of stay of at least 1 day at 3 Indiana hospitals. Patients with preexisting dementia or mild cognitive impairment were excluded. POD was identified using Confusion Assessment Method records and delirium International Classification of Diseases (ICD) codes. Controls without delirium or nurse-documented confusion were matched to cases by age, sex, race, and year of admission. We trained logistic regression, random forest, extreme gradient boosting (XGB), and neural network models to predict POD using 143 features derived from routine EHR data available at the time of hospital admission. Separate models were developed for each hospital using surveillance periods of 3 months, 6 months, and 1 year before admission. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Each model was internally validated using holdout data and externally validated using data from the other 2 hospitals. Calibration was assessed using calibration curves.

RESULTS

The study cohort included 7167 delirium cases and 7167 matched controls. XGB outperformed all other classifiers. AUROCs were highest for XGB models trained on 12 months of preadmission data. The best-performing XGB model achieved a mean AUROC of 0.79 (SD 0.01) on the holdout set, which decreased to 0.69-0.74 (SD 0.02) when externally validated on data from other hospitals.

CONCLUSIONS

Our routine EHR-based POD prediction models demonstrated good predictive ability using a limited set of preadmission and surgical variables, though their generalizability was limited. The proposed models could be used as a scalable, automated screening tool to identify patients at high risk of POD at the time of hospital admission.
Designing a Preventive Stress Management mHealth Intervention: Factorial Experiment to Optimize Intervention Components (Preprint)
Authors: Kowalski Leo , Finnes Anna , Koch Sabine , Bujacz Aleksandra
Published: January 2025

UNSTRUCTURED

Work stress is a prevalent risk factor for health problems such as burnout and cardiovascular disease. mHealth interventions – digital interventions delivered via mobile devices - are a promising way to combat this issue, offering the possibility of scalable programs that are easily accessible. A wide range of evidence-based stress management techniques can be used in the digital context to mitigate the negative consequences of work stress. However, evidence is needed to support what specific intervention content is most effective at preventing symptoms of stress-related health problems. This study tested five digital intervention components that may improve stress management among workers – Engagement, Demands, Control, Journaling, Psychoeducation - in a factorial experimental study among healthcare workers in Sweden (N = 283). It was of special interest to observe the interaction effect between Engagement & Demands, Demands & Control, and Journaling & Psychoeducation. Results indicate that components aiding self-insight should be integrated with components providing actionable advice for optimal intervention effects. Results from this optimization may inform the development of digital stress management interventions to be tested in future randomized controlled trials.
Evaluation of inclusive educational videos on mental health(care) by migrants in Europe: A MentalHealth4All think-aloud study (Preprint)
Authors: de Looper Melanie , Chen Yuhui Olivia , Mankauskienė Dalia , Hodáková Sona , Okulska-Łukawska Ursula , Czarnocka-Gołębiewska Katarzyna , Lázaro Gutiérrez Raquel , Damyanova Radeva Silviya , Gualco Carlotta , Muzi Stefania , Mösko Mike , Hanft-Robert Saskia , Hollebeke Ily , Cox Antoon , Kerremans Koen , Temizöz Özlem , Delfani Jaleh , Schouten Barbara C.
Published: January 2025

BACKGROUND

Migrants face higher risks of developing some mental health issues, such as posttraumatic stress disorder and psychosis, compared to individuals without a migrant or refugee background. However, they can encounter significant barriers to accessing mental healthcare, due to language difficulties, lack of qualified interpreters, stigma, and system-related barriers. Furthermore, limited knowledge of the healthcare system further restricts access. Providing culturally-tailored online multilingual health materials can enhance migrants’ access to mental healthcare, with co-created animated videos being a promising medium.

OBJECTIVE

Therefore, this study aimed to 1) identify key factors influencing the evaluation of educational videos on mental health by migrants and their healthcare providers, focusing on critical mental health themes, and 2) actively involve these groups in co-creating the videos based on feedback.

METHODS

Eight animated videos were developed through an iterative process involving the entire multidisciplinary MentalHealth4all consortium, including numerous feedback sessions. The videos were evaluated using a hybrid approach that combined think-aloud observations and interviews with migrants (N = 31) and their healthcare providers (N = 35).

RESULTS

Thematic coding of the verbatim transcribed interviews highlighted four essential aspects: comprehensibility, attractiveness, reliability, and relevance, with specific elements identified for both migrants and for their healthcare providers.

CONCLUSIONS

These insights can guide the creation of effective health information materials for migrants facing mental health challenges.
Peculiarities of vitamin D metabolism in diabetic kidney disease
Authors: Yerokhovych V.M. , Karpenko O.V. , Paliienko I.A. , Dumka I.V. , Rudenko O.A. , Komisarenko Iu.I.
Published: January 2025

The analysis of literature revealed the peculiarities of vitamin D metabolism in diabetic kidney damage, as well as its role in the development of renal, metabolic changes, including bone and mineral disorders. Vitamin D, due to its influence on various physiological processes through vitamin D receptors, plays a key role in the regulation of mineral and bone metabolism, the functioning of the immune system and the control of other extraskeletal effects. In patients with diabetic kidney damage, vitamin D deficiency causes impaired hydroxylation and the formation of an active metabolite (1,25(OH)2D3), which leads to the progression of kidney damage, the development of proteinuria and fibrosis. The mechanisms of glucose and vitamin D interaction at the level of the proximal tubules were analyzed, which emphasizes the need for further research to develop therapeutic strategies for correcting vitamin D deficiency in patients with diabetic kidney damage in order to improve their prognosis.
Políticas migratorias para la protección de los migrantes climáticos en México
Authors: Torre Cantalapiedra Eduardo
Published: January 2025

En el campo de los estudios sobre migración hay un creciente interés sobre la movilidad migratoria debida al cambio climático y las respuestas que los Estados dan a tales flujos migratorios forzados en términos de gestión y protección. El objetivo de este trabajo es analizar las categorías de protección humanitaria de México, ya sean permanentes o temporales, en relación con la salvaguardia de los migrantes climáticos. Se evidencia que el sistema legal mexicano carece de categorías propicias para la protección de los migrantes climáticos extranjeros, por lo que en muchas ocasiones estos quedarían parcialmente protegidos, cuando no desprotegidos. Ante esta situación se hace una propuesta de introducir nuevas definiciones para el otorgamiento de visas humanitarias (tarjetas de visitante por razones humanitarias) para la protección de los derechos humanos de los migrantes climáticos.
Córdova, Arnaldo (2024). La política de masas y la lucha por la democracia. Antología, Alberto Enríquez Perea (selección y presentación). Biblioteca del Estudiante Universitario, núm. 158. México. Coordinación de HumanidadesUniversidad Nacional Autón
Authors: Torres Alonso Eduardo
Published: January 2025

Córdova, Arnaldo (2024). La política de masas y la lucha por la democracia. Antología, Alberto Enríquez Perea (selección y presentación). Biblioteca del Estudiante Universitario, núm. 158. México. Coordinación de Humanidades-Universidad Nacional Autónoma de México
Inteligencia emocional y estrés percibido en médicos residentes
Authors: Garcia-Mendoza Dulce Yajaira , Rosillo-Ortiz Ivonne , Escorcia-Reyes Verónica , Villarreal-Ríos Enrique , Galicia-Rodríguez Liliana , Carballo-Santander Erasto , Ramírez-Bernal José Asunción
Published: January 2025

Introducción: El plan académico de los estudiantes de especialidades se ha enfocado en desarrollar habilidades y aptitudes del área clínica, sin tomar en cuenta la demanda psicológica que requiere y el desarrollo de una inteligencia emocional que es fundamental para mejorar la praxis médica.
Objetivo: Determinar el perfil de inteligencia emocional y estrés percibido en médicos residentes.
Método: Diseño trasversal descriptivo en estudiantes de postgrado de primero y segundo año durante la residencia médica. Se incluyó a toda la población integrada por 52 médicos residentes. La inteligencia emocional se evaluó con el instrumento Trait Meta Mood Scale: TTMS-24, conformado por 24 ítems (alfa de Cronbach de 0.87). El estrés percibido se evaluó a través del instrumento PSS-14 en su versión de 14 ítems (alfa de Cronbach de 0.84). El análisis estadístico incluyo intervalos de confianza para porcentajes y promedios.
Resultados: La inteligencia emocional en la dimensión atención en la categoría escasa es 46.2% (IC 95% 32.6-59.8), en la dimensión claridad la categoría adecuada es 50.0% (IC 95%; 36.4-63.7) y en la dimensión reparación la categoría adecuada es 59.6% (IC 95% 46.3-72.9). El 82.7% (IC 95%; 72.4-93.0) de los médicos residentes perciben que a menudo están estresados.
Discusión: En la especialización médica a menudo se experimenta altos niveles de estrés debido a la carga laboral, presión en la toma de decisiones críticas y la exposición a situaciones emocionalmente desafiantes como la muerte, en esta investigación se encontró que a menudo están estresados los médicos residentes y esto explica los resultados obtenidos por dimensión de inteligencia emocional en donde ninguna fue excesiva e incluso en la dimensión atención esta fue escasa.
Conclusión: La inteligencia emocional en el médico residente en la dimensión atención es escasa, en la dimensión claridad y reparación es adecuada y respecto al estrés percibido se encontró que muy a menudo están estresados.
Educación para la salud: Modelos de intervención en salud desde la pedagogía crítica
Authors: Nassar Tobón Andrea Catalina
Published: January 2025

Este artículo aborda la educación para la salud en Latinoamérica, evaluando modelos de intervención en salud tradicionales y emergentes desde una perspectiva crítica. Se examinan enfoques clásicos y nuevas propuestas, destacando las limitaciones de los modelos tradicionales en involucrar a la comunidad. Se expone el potencial transformador de la pedagogía crítica y la educación popular, resaltando su capacidad para generar cambios sociales. El análisis se centra en la aplicación de estos modelos en contextos de atención médica y promoción de la salud en Latinoamérica, subrayando su impacto en la participación comunitaria y el cambio de comportamiento. Se resalta el papel crucial de la pedagogía crítica en la salud como un enfoque que desafía estructuras subyacentes y promueve la equidad. Así mismo, se identifican desafíos en su implementación y se destaca su potencial para empoderar comunidades y mejorar las percepciones y los estados de salud, ofreciendo una mirada crítica que trasciende los paradigmas establecidos.
Modificación de las actividades académicas en estudiantes de medicina durante la pandemia por COVID-19
Authors: Delgado-Fernández Abel , Robles-Rivera Karina , Gómez-Gudiño Guadalupe , Carrasco-Contreras Sofia , Negrete-Hernández Daniela , Villalobos-Piñera Katya , Limón-Rojas Ana Elena , Wakida-Kuzunoki Guillermo Hideo
Published: January 2025

Introducción: La pandemia por COVID-19 impactó significativamente al mundo, cambió la forma en la que vivimos y aprendemos. La educación médica se vio particularmente afectada con la suspensión de actividades presenciales para la prevención de contagios. Como resultado, se desarrollaron e implementaron diversas modalidades y estrategias para adaptarse a la nueva situación.
Objetivo: Describir las actividades académicas y de evaluación en alumnos del quinto año de la carrera de Medicina durante de pandemia por COVID-19 en México.
Método: Se aplicó un cuestionario autoadministrado de 40 preguntas para recopilar información sobre las actividades académicas y de evaluación, llevadas a cabo por su institución educativa durante la pandemia. Las variables se describieron mediante la mediana, el rango intercuartílico, la frecuencia y la proporción. Se realizó la prueba de proporciones inmediato para evaluar diferencias entre sexo.
Resultados: De los 541 participantes, más del 80.0% reportó la interrupción de actividades del entrenamiento médico y quirúrgico, así como modificaciones en las rotaciones hospitalarias. Si bien el 86.9% llevó a cabo las actividades en línea, solo el 38.5% se sintió satisfecho con dicha experiencia. Los métodos de evaluación más empleados fueron los exámenes, la participación en sesiones y el portafolio de evidencias. Además, se observó un aumento significativo en el promedio escolar durante el regreso a clases presenciales.
Conclusiones: Los resultados de este estudio describen los cambios necesarios que las instituciones académicas del área de la salud implementaron para adaptarse a la pandemia. La educación en línea e híbrida han abierto oportunidades para la innovación pedagógica y exploración de estrategias efectivas de aprendizaje y evaluación que permitan el desarrollo de competencias en los estudiantes del área de la salud a pesar de las condiciones epidemiológicas.
Percepción de los médicos internos sobre la implementación del método socrático como estrategia de aprendizaje
Authors: Andrade-Castellanos Carlos Alberto , Cuevas-Álvarez Leobardo , Ramos-Herrera Igor Martín
Published: January 2025

Introducción: La pregunta, un recurso ancestral, sigue siendo fundamental tanto en el ámbito educativo como en el médico. Inspirado por Sócrates, el método socrático de preguntas fomenta el pensamiento crítico y la reflexión. En el campo de la medicina, este método facilita la transición de la teoría a la práctica clínica, estableciendo conexiones entre los conocimientos. A pesar de estas ventajas, la investigación sobre esta estrategia, en el pase de visita, es escasa.
Objetivo: Explorar las percepciones de los médicos internos de pregrado del Nuevo Hospital Civil de Guadalajara “Dr. Juan I. Menchaca”, respecto a la implementación del método socrático como estrategia de aprendizaje durante su rotación por el servicio de medicina interna.
Método: Se llevó a cabo una investigación cualitativa mediante un estudio de caso intrínseco. La muestra consistió en 8 informantes clave, seleccionados de manera intencionada. Posteriormente, se realizó un grupo focal con estos estudiantes tras la rotación en medicina interna, previa obtención de consentimiento informado. El análisis de datos se hizo utilizando el método de comparación constante de Glaser y Strauss, siguiendo los pasos descritos por Miles y Huberman, y se empleó el programa Atlas.ti como herramienta computacional.
Resultados: Se identificaron 151 unidades de significado, las cuales fueron agrupadas en 34 categorías descriptivas, emergiendo 7 metacategorías y 3 dominios cualitativos: “significado de la estrategia”, “proceso enseñanza-aprendizaje” y “factores que influyen en la aplicación de la estrategia”.
Conclusiones: Los médicos internos perciben el método socrático de preguntas como una estrategia de aprendizaje que fortalece la autoconfianza y la motivación para aprender. Esta estrategia promueve el aprendizaje significativo conectando conocimientos previos con nuevos aprendizajes; además, fomenta la colaboración y la reflexión, creando un ambiente propicio para el crecimiento personal y profesional. Sin embargo, su plena implementación requiere compromiso docente y ajustes en el entorno hospitalario.
Venganza vicaria en la formación médica
Authors: Lifshitz Alberto
Published: January 2025

La formación de médicos, sobre todo en los cursos de especialización, ha caído en una espiral de maltrato que perpetúa conductas que han llegado a normalizarse y a justificarse. Es tiempo de reconocer que no es un camino adecuado porque atenta contra la dignidad y la autoestima de los futuros médicos, y de romper con la inercia que lo ha vuelto una costumbre
Uso de la inteligencia artificial en la educación médica: ¿herramienta o amenaza? Revisión de alcance
Authors: Aguirre Flórez Mateo , Gómez González José Fernando , Jiménez Osorio Laura Alejandra , Moreno Gómez Mateo , Moreno Gómez Juanita , Rojas Paguanquiza Karla Liseth , Rojas Paguanquiza Donald Jehison , Quintero Cabrera Yuly Mabel , Pantoja Chazatar Lency Yurani , Moreno Gómez Germán Alberto
Published: January 2025

Introducción: La inteligencia artificial (IA) ha captado considerable atención entre las tecnologías emergentes. La IA se refiere a la capacidad de las máquinas para aprender y tomar decisiones autónomas, asemejándose a la inteligencia humana. En la formación de profesionales de la salud, la IA muestra potencial para mejorar la enseñanza y el aprendizaje.
Objetivo: Analizar las aplicaciones de la IA en la formación de médicos, incluyendo sus beneficios, limitaciones e implicaciones éticas y sociales.
Método: Se realizó una búsqueda en bases de datos electrónicas como PubMed, EMBASE, Web of Science y Google Scholar, utilizando términos MeSH y operadores booleanos para refinar los estudios. Se analizaron y sintetizaron los estudios seleccionados para identificar las principales aplicaciones de la IA en la formación médica y los beneficios y limitaciones asociados.
Resultados: Se identificaron múltiples aplicaciones de la IA en la educación médica, como el aprendizaje personalizado, la retroalimentación inmediata y el fácil acceso a la información. Los beneficios incluyen mayor eficiencia y efectividad del aprendizaje. Las consideraciones éticas y precauciones incluyen el sesgo potencial, la privacidad y seguridad de los datos, la dependencia excesiva de la tecnología y los impactos en la relación médico-paciente.
Conclusión: La IA ofrece ventajas significativas para la formación de médicos, mejorando la calidad de la educación y el tratamiento oportuno de los pacientes. Sin embargo, es importante considerar sus implicaciones. La implementación adecuada de la IA puede aprovechar sus beneficios mientras se mitigan sus riesgos. Los médicos deben estar preparados para usar la IA de manera responsable, equilibrando la tecnología con el cuidado humanista.
La alta prevalencia de trastornos mentales en alumnos de medicina merece más atención
Authors: Rodríguez-Orozco Alain Raimundo
Published: January 2025

Uno de cada siete jóvenes entre 10 y 19 años padece algún tipo de trastorno mental, y el suicidio es la tercera causa de muerte entre los 15 y 29 años.
Oportunidades de la inteligencia artificial en los posgrados de medicina deportiva y áreas afines
Authors: Bustos-Viviescas Brian Johan , García Yerena Carlos Enrique , Villamizar Navarro Amalia
Published: January 2025

Cada día se emplea con mayor frecuencia la inteligencia artificial (IA) en la educación médica para los procesos de aprendizaje, mediante experiencias personalizadas y optimización de resultados
Application of metal oxide/metal nanoparticle-based antimicrobial films in food packaging: Potential use, risk factors, safety assessments and regulatory matters
Authors: Vats T. , Arora G. , Tiwari P.
Published: January 2025

Packaging is an important feature of our everyday life and it has a vital role to play in food industry. A lot of work is being done for diversifying the role of packaging including use of packaging for increasing the storage time of food items. In this review, we have discussed the role of commonly used metals and metal oxide nanoparticles based antimicrobial agents as a component of packaging material. Though “nano” is a magic word used these days, in this article the potential health hazards on the probable leaching of packaging nanomaterial into food have been discussed. Besides, the safety regulations of various economies have also been covered.
Research Paper on Cybersecurity and Insider Threat Detection: The Role of User Behavior Analytics (UBA) in Modern Defense Strategies
Authors: Trivedi Aayush
Published: January 2025

Insider threats have emerged as one of the most pressing challenges in modern cybersecurity. These threats, which
originate from within an organization, pose a unique risk due to the trusted access that insiders—such as employees,
contractors, and business partners—have to sensitive systems and data. Detecting and preventing insider threats is particularly
challenging because traditional security measures, designed to guard against external attacks, are often insufficient to identify
malicious or negligent behavior from trusted individuals.
This research paper delves into the complexities of insider threat detection and prevention, with a particular emphasis on the
role of User Behavior Analytics (UBA). UBA leverages advanced machine learning algorithms and statistical analysis to
monitor, analyze, and model user behavior, enabling the identification of deviations from established norms that may indicate
potential insider threats. The paper provides a comprehensive analysis of UBA, discussing its core components, functionality,
and integration with existing security frameworks.
Additionally, the paper examines the challenges and limitations of implementing UBA, including technical hurdles, data privacy
concerns, and the impact of human factors. Through case studies and practical examples, the research highlights the real-world
applications of UBA in various industries and its effectiveness in mitigating insider threats. The paper also explores future
trends in UBA and insider threat detection, considering advancements in artificial intelligence, machine learning, and their
implications for cybersecurity. Finally, the paper presents best practices for organizations seeking to implement UBA, offering
strategic recommendations to maximize the effectiveness of this technology while ensuring compliance with legal and ethical
standards. The research concludes that while UBA significantly enhances the ability to detect insider threats, it must be part of a
holistic cybersecurity strategy that includes robust access controls, continuous monitoring, and a culture of security awareness.
A Study on Solid Waste Management and Waste Water Treatment by Leachates Recirculation and Moving Bed Bio Film Reactor [MBBR] Technique in Ambala
Authors: Preet Angad
Published: January 2025

Ambala is crowded district with Approx Sixty Five lakhs and Thirty Five thousand Twenty Seven population including
Ambala City, Ambala Sadar, Barara And Naraingarh, During rainy seasons waste from domestic Houses create blockage of
sewerage system and effect the solid waste management system. According to district environment plan prepared by ULB In
2023 Ambala City has a Population of 351650 and generates about 158 Solid Waste Generated per day (TPD) On the other hand
Ambala Cantt has 31 wards with population of 236850 and 110 Solid Waste Generated per day(TPD) leachate generation is very
high in the city due to this people faces problem of heath and Hygiene. In this paper , various methods like MBBR Technique
and Leachate Recirculation techniques is discussed to overcome this issue and to increase the efficiency of landfill and solid
waste decomposition.
A dynamic integrity and data confidentiality based wireless N2N data communication and security protocol on large networks
Authors: Ganta Seshagiri Rao , Naga Malleswara Rao Nallamothu
Published: January 2025

WANET  is a network built in an ad hoc network where various connecting devices and moving wireless nodes make connection with the exchange valuable information and wireless medium to one another. As the size of the wireless networks and internet architectures are increasing, there is an exponential demand for data processing and sharing resources in the WANETs. Most of the traditional node authentication models in WANET’s require high computational memory and resource constraints for data security and node authentication. In order to overcome these problems in the traditional models, a novel non-linear integrity-based intrusion detection models is designed and implemented in WANETs. In this work, a hybrid security protocol is designed and developed for the node-to-node communication system. In the proposed security protocol, a hybrid integrity approach and encryption framework is implemented on N2N communication process. Experimental results show that the present security protocol has better improvement on different metrics over traditional security approaches.
BCDNet: An Enhanced Convolutional Neural Network in Breast Cancer Detection Using Mammogram Images
Authors: Bandla Raghuramaiah  , Suresh Chittineni
Published: January 2025

Breast cancer is a leading cause of death among women worldwide. The emergence of Artificial Intelligence (AI) has led to significant progress in breast cancer detection research. Early detection of breast cancer is crucial for making informed decisions about treatment and eradicating the disease. Deep Learning (DL) techniques, commonly used in computer vision, have been applied to various domains, including healthcare. The Convolutional Neural Network (CNN) is a widely used model for medical image processing, but its performance may not be optimal for a specific imaging modality without empirical study. This paper introduces an enhanced CNN model called Breast Cancer Detection Network (BCDNet), designed to be more efficient with breast mammogram images. We also propose an algorithm called Learning-Based Cancer Screening (LBCS) that leverages the BCDNet model. An empirical study using the CBID-DDSM benchmark dataset demonstrates that BCDNet outperforms many existing deep learning models, achieving the highest accuracy of 97.68%. This proposed model can be utilized for breast cancer screening in healthcare units as part of a Clinical Decision Support System (CDSS).
Tradução – Tempo(s) perturbador(es) e ecologias do nada: re-tornando, re-lembrando e enfrentando o incalculável
Authors: Da Veiga Ádamo , Garcia Victor , Ranniery Thiago
Published: January 2025

Tradução.
Mathematical Problem-Solving Ability with a Mathematical Modeling Approach Using ICT-Based Learning Media
Authors: Syabillah Dinda , Kurniadi Elika , Harini Bunda , Suganda Vina Amilia
Published: January 2025

Problem-solving is one aspect of high-level thinking skills that is important for students to have. Problem-solving is closely related to mathematical modeling, this is because mathematical modeling is usually considered the art of applying mathematics to real-world problems. This research is a qualitative descriptive study and the subjects of this study were 32 students of class VII C junior high school number 1 at Pagar Alam. This study aims to determine students' mathematical problem-solving abilities for the one variable linear equation topic with a mathematical modeling approach using ICT-based learning media. Data collection techniques used in this study were written tests and interviews. Based on the results of the study, it was found that learning mathematical modeling using Google Sites media was able to make a significant contribution to the problem-solving abilities of senior high school number 1 at Pagar Alam students. The results of the achievement of problem-solving abilities of VII C students with an average of 53.90% are categorized as sufficient. Students are more interested in using mathematical modeling learning using Google Sites.