bluuebunny/crossref_metadata_2025 huggingface dataset:
Lysyl Oxidase as a Target to Reduce Graft Failure Post Solid Organ Transplantation, a Potential Target for Novel Treatment
Authors: Khodashahi Rozita , Sabbagh Mahin Ghorban , Ferns Gordon A. , Toutouni Mohammad Naser , Bonab Mohammad Semsari , Aliakbarian Mohsen , Arjmand Mohammad-Hassan
Published: February 2025

The present review was undertaken to clarify the potential role of the lysyl
oxidase (Lox) family of enzymes in delaying graft dysfunction. Delayed graft failure is
a well-known event that occurs post-transplantation period. Ischemia and trauma to the
graft tissue before or during the operation procedures are likely to be the most important
etiological causes of this complication. The lox proteins family including Lox and Lox--
like proteins (LoxL1-4) are copper-dependent enzymes that catalyze the cross-linking of
collagens to stabilize extracellular matrix (ECM). Hypoxia-induced factor 1-α (HIF-1α)
and transforming growth factor β (TGF-β) are two upstream regulators of the Lox proteins
family whose expression increased following hypoxia and tissue injury. Lox proteins’
overactivation upregulates several intracellular transduction pathways to promote
oxidative stress (OS), ECM proteins accumulation, and epithelial to mesenchymal transition
(EMT) contribute to vascular stiffness and tissue fibrogenesis, which increase the
risk of graft failure post solid organ transplantation (SOT). Preclinical studies have
shown that Lox protein inhibitors have the potential to prevent organ fibrosis. Regarding
the molecular effects of Lox proteins in causing tissue fibrosis, these molecules can be
further investigated as a drug target in reducing the possibility of organ fibrosis after allograft
transplantation.
Synthesis, Anticancer Activity, and Mitochondria-targeted Bioimaging Applications of Novel Fluorescent Calix [4]arenes-benzimidazole
Derivatives
Authors: Solmaz Beyza , Oguz Alev , Oguz Mehmet , Ozturk Bahadir , Yilmaz Mustafa
Published: February 2025

Background:

Calix[n]arenes have attracted great attention due to their biocompatibility and superior stability. When the necessary functional groups are attached
to these compounds, they may have the potential to target tumor tissues. Benzimidazoles
are among the anticancer drugs discovered in recent years.

Aim:

The aim of this study was to design and synthesise a series of calix[4]arenes-benzimidazoles. For comparison purposes, a benzimidazole derivative was synthesized by attaching it to the diester. The anticancer effects of these compounds were investigated by
performing cell proliferation, apoptosis, and cell imaging studies on cancer cell lines.

Methods:

Some of the obtained compounds were synthesized by employing the methods
available in literature studies, and the rest were synthesized by modifying previous methods. As a result, a total of 3 new fluorescent calix[4]arene-benzimidazole derivatives
were synthesized. MTT was used for cell proliferation, and Annexin V was used for
apoptosis studies. For confocal imaging studies, cells were treated with DAPI and MitoTracker dyes.

Results:

Four designed calix[4]arene-benzimidazoles were successfully synthesized and
structurally confirmed by 1H-NMR, 13C-NMR, and IR spectroscopy. The anticancer
study on four synthesized compounds was performed. Bio-imaging studies were performed using confocal microscopy for the three successfully synthesized fluorescent
compounds.

Conclusion:

CB5-a and CB5-c were found to be the most effective against MCF-7 cells
and CB5-b against HT-29 cells in the MTT test. Apoptosis analyses also proved that these compounds inhibited the proliferation of cancer cells. As a comparison compound,
the synthesized CB5-R proved to be less cytotoxic than the fluorescent compounds by
the MTT method, and we found the cationic compound to bind to the calix[4]arene more
effectively than the molecule’s binding to the diester.
Advances in the Synthesis and SAR of Pyrido[2,3-d]pyrimidine Scaffold
Authors: Wei Xiongpiao , Fan Dang , Dong Haifeng , Li Min , Lv Qiaoli , Zheng Pengwu , Wang Linxiao
Published: February 2025

Pyrido[2,3-d]pyrimidine and its derivatives have garnered significant attention due to their
potential biological and pharmacological activities. Research has demonstrated their significant potential
for antitumor and antibacterial applications. Over the years, pyrido[2,3-d]pyrimidine derivatives have
remained a research focus for scientists, with numerous synthetic methods and reaction conditions reported.
This review comprehensively summarizes the fast, facile, and economical synthetic methods for pyrido[2,3-
d]pyrimidine derivatives over the past years, which are categorized based on different synthetic precursors,
and evaluates their antitumor and antibacterial activities, aiming to make them better serve the cause of human
health.
The Impact of Thermal and pH Variations on the Structure of Cathepsin D in the Hepatopancreas of Japanese Clam (Ruditapes philippinarum)
Authors: Francisco Cadena-Cadena , Josafat Marina Ezquerra-Brauer , Francisco Javier Cinco-Moroyoqui , Alonso Alexis López-Zavala , Hisila del Carmen Santacruz-Ortega , Ignacio Alfredo Rivero-Espejel , Ofelia Rouzaud-Sández , José Luis Cárdenas-López
Published: February 2025

Background:

Cathepsin D is a lysosomal enzyme that plays a critical role in the process
of protein catabolism. In marine organisms, research has primarily concentrated on the identification
of the enzyme. However, in crustaceans and molluscs, it is known to have digestive functions,
as it is the sole enzyme responsible for protein degradation at extremely acidic pH in the hepatopancreas.
In the Japanese clam (Ruditapes philippinarum), cathepsin D was purified and partially
characterised by the hepatopancreas.

Methods:

To evaluate changes in secondary structure, circular dichroism (CD) was employed under
a range of 5-70°C and pH of 1-7.5. Following dissection, the enzyme was purified from the hepatopancreas
by ultrafiltration and affinity chromatography. SDS-PAGE was used to verify the
sample purity, and gel filtration was used to determine the molecular weight.. CD spectra were obtained
at a concentration of 0.125 mg/mL, expressed as mean ellipticity per residue.

Results:

The purified cathepsin D demonstrated a specific activity of 5,553 ± 220 U/mg and a
molecular weight of 36.5 kDa. The enzyme demonstrated optimal activity within a temperature
range of 45-50°C and a pH range of 3-3.5. CD analyses demonstrated alterations in the secondary
structure at elevated temperatures and pH fluctuations, which were correlated with a reduction in
enzyme activity.

Conclusion:

cathepsin D from R. philippinarum exhibited high thermostability up to 50°C and activity
at pH 2-4. Its stability and characteristics are comparable to those of other species, which
opens avenues in biotechnology for protein hydrolysis and peptide production.
A Novel Platinum-Resistance-related Gene Signature in Ovarian Cancer:
Identification and Patient-derived Organoids Verification
Authors: Lin Jie , Cai Xintong , Liu Linying , Li Anyang , Huang Huaqing , Fu Yixin , Dai Zhisen , Sun Yang
Published: February 2025

Background:

Platinum-based chemotherapy resistance is one of the main contributors to the mortality of Ovarian Cancer (OC). It is believed that sensitive biomarkers
for identifying the population that is platinum-resistant are urgently needed. This study
aims to develop a platinum-resistance gene-based signature to predict OC patients' responses to platinum drugs as well as survival outcomes.

Methods:

A platinum-resistance-related gene model was built by bioinformatics analysis.
Then, its predictive power was internally validated. Continually, a nomogram was constructed to confirm the model's predictive ability. Afterward, GSEA was used to explore
our model's potential functions. The ESTIMATE, CIBERSORT, TIMER, and ssGSEA
were applied to estimate immune conditions. Then, somatic mutation and drug sensitivity
were also analyzed. Finally, to gain insights into the roles of targeted genes in drug sensitivity, patient-derived tumor organoids (PDOs) validation was performed.

Results:

Nine platinum-resistance-related genes, including SLC22A2, TAP1, PC, MCM3,
GTF2H2, FXYD5, SUPT6H, IGKC, and MATN2, were anchored to build the predictive
model, which was well internally validated. Subsequently, GSEA unveiled that our model
genes enriched in the Hedgehog signaling pathway. The predictive signature was associated with immune checkpoint inhibitors such as PD-1, PD-L1, and CTLA4, guiding immunotherapy applications for OC patients. Drugs such as dasatinib, midostaurin, metformin,
MK-2206, and mitomycin C might also benefit OC patients with different risk scores.
PDOs showed patients with high-risk scores were more resistant to cisplatin than patients
with low-risk scores.

Conclusion:

The platinum-resistance-related gene signature (SLC22A2, TAP1, PC,
MCM3, GTF2H2, FXYD5, SUPT6H, IGKC, and MATN2) is valuable for prognosis prediction and guidance of treatment choices for OC patients
A Recent Progress in Biological Activities of 1,3,4-thiadiazole and its Derivatives: A Review
Authors: chandurwala Sarah , Balachandran Hardha , Gowramma B. , M. Yokkesh , Pranav Vishal , Vinethmartin J. , Jangra Aryan , Arun Sowmiya , L. Kaviarasan
Published: February 2025

1,3,4-thiadiazole can be produced in several ways and has a wide range of possible biological
uses. As a result, scientists have created novel procedures for producing 1,3,4-thiadiazole
derivatives and their use in medicine. Among the activities are Anticancer, anticonvulsant, antimicrobial,
antifungal, antiinflammatory, antiHIV, antidiabetic, antitubercular, antifungal, and other
properties. We have compiled different biological activities of 1,3,4-thiadazole in this review study.
Many researchers may find the material on this page helpful, which could result in the identification
of new medicinal species beneficial to society.
Hexagonal Fractals: Topological Indices, Fractal Dimensions, Structure-Property Modeling and its Applications
Authors: K. B. Gayathri , Santiago Roy , S Govardhan
Published: February 2025

Background:

Hexagonal fractals are intricate geometric patterns that exhibit self-similarity. They are characterized by their repetitive hexagonal shapes at different scales. Due to their unique properties and potential applications, hexagonal fractals have been stud-ied in various fields, including mathematics, physics, and chemistry.

Objective:

The primary aim of this research is to provide a comprehensive analysis of hex-agonal fractals, focusing on their topological indices, fractal dimensions, and their applica-tions in structure-property modeling. We aim to calculate topological indices to quantify the structural complexity and connectivity of hexagonal fractals. Additionally, we will determine fractal dimensions to characterize their self-similarity and scaling behaviour. Finally, we will explore the relationship between topological indices, fractal dimensions, and relevant prop-erties through structure-property modeling.

Methods:

A systematic approach was employed to investigate hexagonal fractals. Various topological indices were computed using established mathematical techniques. Fractal di-mensions were determined. Structure-property modeling was conducted by establishing re-lationships between the calculated topological indices and fractal dimensions with experi-mentally measured properties.

Results:

The research yielded significant findings regarding hexagonal fractals. A variety of topological indices were calculated, revealing the intricate connectivity and structural com-plexity of these fractals. Fractal dimensions were determined, confirming their self-similar nature and scaling behaviour. Structure-property modeling demonstrated strong correlations between the topological indices and fractal dimensions with properties such as conductivity, mechanical strength, and chemical reactivity.

Conclusion:

This research provides valuable insights into the topological characteristics, fractal dimensions, and potential applications of hexagonal fractals. The findings contribute to a deeper understanding of these complex structures and their relevance in various scien-tific domains. The developed structure-property modeling approaches offer a valuable tool for predicting and controlling the properties of materials based on their fractal structure. Fu-ture research may explore additional applications and delve into the underlying mechanisms governing the relationship between fractal structure and properties.
Unveiling miR-1468-5p: A New Prognostic Biomarker and Therapeutic Target in Lung Adenocarcinoma
Authors: Chen Yi , Li Dongbing , Fang Yueyu
Published: February 2025

Background:

miR-1468-5p, a type of microRNA, is acknowledged for its crucial involvement
in a variety of cancerous processes. Nonetheless, the specific impact of this microRNA
on lung adenocarcinoma (LUAD) has not yet been clearly defined.

Objective:

Our aim was to investigate how miR-1468-5p influences LUAD.

Methods:

The Cancer Genome Atlas (TCGA) offered specimens for our research. Employing statistical
techniques, we assessed the diagnostic and prognostic significance of miR-1468-5p, as
well as its association with clinical characteristics. Our analysis delved into the target genes and
the regulatory mechanisms influenced by miR-1468-5p. The expression levels of miR-1468-5p in
LUAD cell lines were validated through quantitative reverse transcription polymerase chain reaction
(qRT-PCR).

Results:

The expression of miR-1468-5p varied significantly across different cancer types. The
presence of reduced miR-1468-5p levels was correlated with a lower likelihood of overall survival
in LUAD patients, with a statistically significant result (p = 0.005). miR-1468-5p demonstrated independent
prognostic significance in LUAD and potentially contributes to disease progression via
multiple pathways, including the HIF-1 signaling pathway and more. There was a significant reduction
in miR-1468-5p expression in LUAD cell lines when compared to cells of the normal lung
epithelium.

Conclusion:

miR-1468-5p may serve as a useful patent as a therapeutic intervention target and a
prognostic indicator for LUAD patients.
The Present State and Potential Applications of Artificial Intelligence in Cancer Diagnosis and Treatment
Authors: Mishra Anuja , Sharma Srishti , Pandey Swaroop Kumar
Published: February 2025

An aberrant increase in cancer incidences has demanded extreme attention globally
despite advancements in diagnostic and management strategies. The high mortality rate is concerning,
and tumour heterogeneity at the genetic, phenotypic, and pathological levels exacerbates
the problem. In this context, lack of early diagnostic techniques and therapeutic resistance
to drugs, sole awareness among the public, coupled with the unavailability of these modern
technologies in developing and low-income countries, negatively impact cancer management.
One of the prime necessities of the world today is the enhancement of early detection of cancers.
Several independent studies have shown that screening individuals for cancer can improve
patient survival but are bogged down by risk classification and major problems in patient selection.
Artificial intelligence (AI) has significantly advanced the field of oncology, addressing
various medical challenges, particularly in cancer management. Leveraging extensive medical
datasets and innovative computational technologies, AI, especially through deep learning (DL),
has found applications across multiple facets of oncology research. These applications range
from early cancer detection, diagnosis, classification, and grading, molecular characterization of
tumours, prediction of patient outcomes and treatment responses, personalized treatment, and
novel anti-cancer drug discovery. Over the past decade, AI/ML has emerged as a valuable tool
in cancer prognosis, risk assessment, and treatment selection for cancer patients. Several patents
have been and are being filed and granted. Some of those inventions were explored and are being
explored in clinical settings as well. In this review, we will discuss the current status, recent
advancements, clinical trials, challenges, and opportunities associated with AI/ML applications
in cancer detection and management. We are optimistic about the potential of AI/ML in improving
outcomes for cancer and the need for further research and development in this field.
Exploring Coding Sequence Length Distributions Across Taxonomic
Kingdoms Based on Maximum Information Principle
Authors: Temesgen Sebu Aboma , Grace-Mercure Bakanina Kissanga , Ahmad Basharat , Jin Yan-Ting , Liu Li , Lin Hao
Published: February 2025

Background:

Genetic information about organisms' traits is stored and encoded in deoxyribonucleic acid (DNA) sequences. The fundamental inquiry into the storage mechanisms of this genetic information within genomes has long been of interest to geneticists and biophysicists.

Objective:

The objective of this study was to investigate the distribution of coding sequence (CDS)
lengths in species genomes across different kingdoms.

Methods:

In this study, we used the maximum entropy principle and the gamma distribution model
based on a comprehensive dataset including viruses, archaea, bacteria, and eukaryote species

Results:

Our study result revealed unique patterns in CDS length distributions among kingdoms and
CDS lengths exhibit a right-skewed distribution, with varying preferences among kingdoms. Eukaryotes displayed bimodal distributions, with CDS sequences longer than those of prokaryotes. Fitting
the gamma distribution model revealed differences in shape and scale parameters among kingdoms,
with eukaryotes exhibiting larger scale parameters, indicating longer CDS sequences. Additionally,
analysis of moments highlighted the complexity of eukaryotic genomes relative to prokaryotes.

Conclusion:

This study result deepens our understanding of genome evolution and provides valuable insights for biological research.Conclusion: This study result deepens our understanding of genome evolution and provides valuable insights for biological research.
Innovative Approaches in Amphiphilic Small Molecule Design for Inhibiting Monkeypox Virus: Computational and Nanoassembly Approaches
Authors: Hussain Afzal , Hussain Ashfaq
Published: February 2025

The Monkeypox virus (MPXV) has recently been identified as a new global health
concern and, as such, requires new therapeutic approaches. Small molecules that can selfassemble
into micelles have been demonstrated to improve solubility, pharmacokinetics, and antiviral
activity. Latest results suggest that amphiphilic small molecules enhance drug delivery and,
importantly, can disrupt virus envelopes, which is required for MPXV. Moreover, encapsulating
amphiphilic antiviral molecules with various hydrophobic drugs will significantly enhance their
therapeutic indexes. This article presents a computational strategy based on molecular docking,
dynamics simulations, and drug-mate nano assembly technologies in high antiviral efficiency
against MPXV. This study, in fact, proposes new pathways for developing antiviral agents
through the identification of key viral proteins as targets and based on insights obtained from already
existing research. Safety considerations of amphiphilic molecules in humans have also been
discussed. To this end, and through the identification of key viral proteins and the application of
drug design principles, we hope to progress the development of novel antiviral agents and potential
treatment strategies for MPXV.
Natural Products: A Promising Avenue for Aquaporin-targeted Drug
Discovery
Authors: Fazliev Sunnatullo , Gulyamov Shokhid , Razzokov Jamoliddin , Normakhamatov Nodirali , Sharipov Avez , Wang Tianfu , Aisa Haji Akber
Published: February 2025

Aquaporins are one of the important but challenging targets in drug discovery. They are of
great interest owing to their diverse physiological roles in health and diseases and their broad tissue
distribution. However, there has been little progress so far in this quest and some have started to
doubt whether AQPs are druggable at all. Essential challenges in AQP drug development seem to be
difficult in modeling selective inhibitors and a lack of robust and reliable in vitro and in vivo assays.
Numerous studies report natural products modulating AQPs at the expression level, directly inhibiting AQPs and disturbing their interaction with
other intracellular proteins. Since direct targeting of
AQPs has not yielded promising results, using natural products as AQP modulators could be a new
possibility.
Therapeutic Applications of Oxalate-degrading Bacteria in Kidney Stone Prevention
Authors: Mani Ravishankar Ram , Ranganathan Venkatalakshmi , Panneerselvam Jithendra , Begam Sameema , Chinnappan Sasikala , Anbalagan Muralidharan
Published: February 2025

Urolithiasis is a condition where kidney stones exit through the renal pelvis, causing
chronic pain. Kidney stones are usually formed due to the deposition of calcium and oxalate crystals.
It is known to be a prevalent health condition that affects a large portion of the global human population.
Inopportunely, no medications that show effective prevention of urolithiasis are currently available.
Extensive research has highlighted the significant role of commensal microbes in regulating
host oxalate homeostasis and oxalate-associated pathological conditions. However, limited
knowledge of the pathophysiology of urolithiasis poses difficulties in designing target-based therapeutics.
Growing evidence suggests the role of gut microbiota and probiotics in helping reduce the
disease burden. Understanding the intricate relationship between gut-associated microbiota and its
host symbiosis reveals the therapeutic potential of specific bacteria to prevent and/or treat such metabolic
diseases. Oxalobacter formigenes, a bacterium, is considered crucial for degrading dietary
oxalates through the oxalyl-CoA decarboxylase enzyme. The absence of this enzyme leads to hyperoxaluria
and calcium oxalate urolithiasis, underscoring the impact of microbiota on kidney stone
formation. Studies on the urinary microbiome, including those focusing on Oxalobacter formigenes,
Lactobacillus, Bifidobacterium, Eubacterium lentum, Enterococcus faecalis, and Escherichia coli,
elucidate the metabolism of dietary oxalates, providing a novel approach to kidney stone management.
This review aims to consolidate the present information on the urinary microbiome, aetiology,
pathogenesis, and disease prevention.
Study of Drug Release of Diclofenac Sodium Matrix Tablets Using Synergistic Effect of HPMC and Xanthan Gum Polymer
Authors: Rahaman Syed Mustafizur , Ashique Sumel , Bhowmick Mithun , Mollick Mirazuddin , Bhowmick Pratibha
Published: February 2025

Aims:

To check the release efficacy of active pharmaceutical ingredients from tablet
dosage form using synthetic and natural polymers.

Background:

Diclofenac sodium in sustained release manner tablets was created by Xanthan
gum, HPMC, and mixed with both polymers to change the concentration ratio. The dosage form
of the tablet was examined for the early stage formulation studies such as repose angle, apparent
density, compressibility index, and some corporal properties like weight variant, friability, and
content of the drug. For post-formulation studies, like in-vitro studies were implemented in a
solution of phosphate buffer pH 7.4 for 8 hours. All the corporal properties of the diclofenac sodium
tablets were within the limit of tolerance.

Objective:

The study checked the Diclofenac Sodium release kinetics from synthetic and natural
polymer-modified tablets.

Method:

Following the wet granulation method, we prepared a diclofenac sodium tablet using
HPMC and Xanthan Gum Polymer

Result:

The tablet that contained both HPMC and Xanthan gum (Batch C-I and C-II) shows the
best drug content than other polymer-based batches like HPMC (Batch A-I, A-II) and Xanthan
gum (Batch B-I, B-II). The great sustained drug release was shown in the HPMC and Xanthan
gum mixed polymer-based matrix tablet (Batch C-I). The data showed that the mixing of polymers
could lead to sustaining drug release from the formulation.

Conclusion:

From the research, we can conclude that the diclofenac release % was maximum
when we used a combination of both polymers in the tablet dosage form.
Uncovering the Impact of MMP-9 and TIMPs in Diabetic Nephropathy: A Review on Bioflavonoids in Disease Management
Authors: Ritu  , Kaur Prabhnain , Goyal Kanika , Goyal Ramesh K. , Singh Ayushi , Sharma Kalicharan
Published: February 2025

This article provides a thorough analysis of the complex roles played by tissue inhibitors of metalloproteinases (TIMPs) and matrix metalloproteinase-9 (MMP-9) in the development and progression of diabetic nephropathy (DN). Diabetic nephropathy, a notable complication of diabetes, is characterized by a progressive decline in kidney function, prompting a thorough examination of its fundamental molecular pathways. This article pre-sents a comprehensive overview of the function played by MMP-9, a key enzyme in the re-modeling of extracellular matrix, in developing tubulointerstitial and glomerular fibrosis, which are critical aspects of renal dysfunction in DN. Simultaneously, the review delves into the regulatory functions of TIMPs, emphasizing their crucial role in maintaining the delicate balance between matrix degradation and repair. The abnormal regulation of the MMP-9/TIMP axis is explored as a pivotal factor contributing to increased vascular permeability, inflammation, and structural alterations within the renal microenvironment. By synthesizing current research findings, the purpose of this review was to unravel the complex molecular interplay between MMP-9 and TIMPs in diabetic nephropathy. The insights derived from this comprehensive analysis hold promise for identifying potential therapeutic targets that could mitigate renal damage, arrest disease progression, and enhance clinical outcomes for individuals grappling with diabetic nephropathy. Finally, it concludes by emphasizing the necessity for additional research to validate these findings and facilitate the translation of this knowledge into targeted therapeutic interventions for improved management of diabetic nephropathy.
Interleukin-24: A Versatile Regulator of Wound Healing
Authors: . Anju , . Uma , . Ritu , Mangla Mohit
Published: February 2025

The skin, as the body's largest organ, is crucial for maintaining homeostasis and providing
protection, making it susceptible to wounds from various causes. Wound healing is a complex
process involving numerous cellular activities. Any interruptions can lead to chronic, non-healing
wounds, which present significant challenges in healthcare. Interleukin-24 (IL-24), a cytokine
within the IL-10 family, has become recognized for its significant role in wound healing due to its
diverse effects on cellular processes. IL-24 can inhibit keratinocyte migration, potentially leading
to chronic wounds, and promote endothelial cell migration and angiogenesis, which are vital for
tissue repair. This dual role highlights IL-24's intricate involvement in wound healing, as it can
hinder and aid different aspects of the process. Research indicates that IL-24 expression increases
in response to inflammatory mediators and is involved in various immune responses, emphasizing
its regulatory function. Further research on IL-24's mechanisms and interactions is essential for developing
new therapeutic strategies to enhance tissue regeneration and treat chronic wounds and
skin disorders. A deeper understanding of IL-24's functions could transform wound care, providing
new approaches for effectively managing and treating conditions involving impaired healing.
Breaking the Mold: Advances and Hurdles in Antifungal Resistance Management for Dermatophytes
Authors: Alnsour Zaid Ra’ed , Alnsour Mouiad Ra’ed , Alnsour Ayham Ra’ed , Massadeh Majd Majed , Alzoubi Karem Hassan , Masadeh Majed Mohammad
Published: February 2025

Examining antifungal resistance in dermatophytes is crucial in infectious diseases, dermatology,
and clinical microbiology. The increasing occurrence of resistant infections and their influence
on the effectiveness of therapy seem overwhelming. This study examines the present condition
of antifungal resistance in dermatophytes, highlighting the need for ongoing and up-to-date research.
Fungal diseases constantly change, and fungi have developed new resistance mechanisms.
Here, we analyze the historical context of research on antifungal resistance, examining the variables
that contribute to the development of resistance, such as the growing use of antifungals in clinical
and agricultural contexts. We also explore the consequences of resistance to antifungal agents in
clinical practice and public health. The review emphasizes the significance of new diagnostic technologies,
like next-generation sequencing, in comprehending resistance mechanisms. It also underscores
the crucial role of international collaboration in tackling this worldwide health concern. In
conclusion, the paper emphasizes the need for continuous research to adjust to the evolving epidemiology
of dermatophyte infections, create efficient treatment approaches, and guide public health
interventions. This will ensure that the management of antifungal resistance is grounded in the most
up-to-date scientific knowledge and optimal methods.
PENGEMBANGAN E-MODUL BERBASIS GREEN CHEMISTRY UNTUK SMA KELAS XI MATERI ASAM BASA
Authors: Sari Winda Putri Permata
Published: February 2025

Penelitian ini bertujuan untuk mengembangkan, menentukan karakteristik, dan mengetahui kualitas e-modul asam basa berbasis green chemistry yang diakses melalui link website http://bitly.ws/sB4f. Karakteristik produk ditentukan berdasarkan validasi ahli pembelajaran kimia dan penilaian kualitas berdasarkan uji kedapatgunaan oleh reviewer (guru) dan uji keterbacaan siswa. Penelitian ini menggunakan model pengembangan four-D model (4D). Tahapan yang dilakukan dalam model pengembangan 4D adalah define (pendefinisian), design (perancangan), develop (pengembangan), disseminate (penyebaran). Penilaian kualitas e-modul dilakukan oleh 6 reviewer yaitu guru kimia kelas XI di SMA Negeri di Kabupaten Sleman dan 60 siswa kelas XI. Penelitian ini menghasilkan e-modul  asam basa berbasis green chemistry dengan 4 kegiatan belajar yaitu asam basa di lingkungan sekitar, teori asam basa, derajat keasaman (pH), indikator asam basa yang dilengkapi dengan info greenmist, fitur link, dan video pembelajaran. Berdasarkan hasil penilaian kualitas oleh reviewer diperoleh skor rata-rata secara keseluruhan terhadap produk sebesar 101,8 dari skor maksimal 115, persentase keidealan 88,5 % yang termasuk dalam kategori Sangat Baik (SB). Hasil uji keterbacaan siswa diperoleh skor rata-rata secara keseluruhan sebesar 77,67 dari skor maksimal 90, persentase keidealan 86,3%  yang termasuk dalam kategori Sangat Baik (SB), sehingga e-modul dapat digunakan guru dan siswa sebagai sumber belajar mandiri yang dapat meningkatkan kesadaran terhadap lingkungan.
PENGARUH MEDIA YOUTUBE (CHEMTUBE) TERHADAP HASIL BELAJAR SISWA KELAS X MIPA SMAN 1 TALUN, BLITAR
Authors: Ciptarini Novita Dwi , Utomo M. Pranjoto
Published: February 2025

Penelitian ini bertujuan untuk mengetahui ada tidaknya perbedaan penggunaan media Youtube (ChemTube) dan tanpa penggunaan media Youtube (ChemTube) terhadap hasil belajar siswa, serta level pencapaian hasil belajar siswa kelas X MIPA SMA N 1 Talun, Blitar pada materi larutan elektrolit dan nonelektrolit. Metode penelitian yang digunakan adalah kuasi eksperimen dengan post-test only design. Penelitian dilakukan di SMA N 1 Talun, Kabupaten Blitar, Provinsi Jawa Timur. Sampel berjumlah 72 siswa dari kelas X MIPA yang dibagi menjadi 2 kelompok yaitu kelas eksperimen dan kelas kontrol. Data yang diambil adalah data skor post-test materi larutan elektrolit dan nonelektrolit. Teknik pengumpulan data yang digunakan adalah teknik tes yaitu post-test yang terdiri dari 25 butir soal objektif. Pelaksanaan post-test dilakukan secara daring melalui platform google form. Hasil penelitian menunjukkan bahwa tidak terdapat perbedaan hasil belajar (kognitif) antara pembelajaran dengan menggunakan media Youtube (ChemTube) dan tanpa menggunakan media Youtube (ChemTube). Level pencapaian hasil belajar siswa kelas X MIPA di SMA N 1 Talun, Blitar dalam materi larutan elektrolit dan nonelektrolit berada dalam kategori sedang dengan persentase 65,2%.
PENGARUH PENERAPAN CHEMISTRY LEARNING COMMUNITY BERBASIS DISCOVERY TERHADAP MINAT DAN HASIL BELAJAR PESERTA DIDIK
Authors: Sari Anggi Mei Indah , Salirawati Das
Published: February 2025

Penelitian ini bertujuan untuk mengetahui perbedaan minat belajar dan hasil belajar peserta didik sebelum dan sesudah mengikuti penerapan Chemistry Learning Community (CLC) berbasis discovery di kelas XI SMA N 2 Ngaglik pada materi Larutan Asam Basa. Penelitian ini merupakan penelitian pre-experiment dengan desain one-group pretest-posttest. Variable bebas penelitian berupa model pembelajaran yaitu CLC berbasis discovery dengan variabel terikatnya adalah minat dan hasil belajar Kimia. Pemilihan sample menggunakan teknik convenience sampling, dengan instrumen pengumpulan data berupa angket untuk minat belajar dan soal untuk hasil belajar kimia peserta didik. Analisis hasil belajar menggunakan uji Wilcoxon signed rank, sedangkan untuk minat belajar menggunakan uji Paired t-test. Hasil analisis paired sample t-test menunjukkan nilai signifikan sebesar 0,000 untuk minat belajar yang menunjukkan adanya perbedaan minat belajar yang signifikan antara peserta didik sebelum dan sesudah mengikuti pembelajaran CLC berbasis discovery. Sementara hasil uji Wilcoxon signed rank sebesar 0,000 menunjukkan adanya perbedaan hasil belajar yang signifikan antara peserta didik sebelum dan sesudah pembelajaran.
Exploring the Role of ChatGPT in Urinary Symptom Management for Individuals with Spinal Cord Injury/Disease: A Qualitative Study (Preprint)
Authors: Hose Bat-Zion , Rounds Amanda K. , Nandwani Ishaan , Busog Deanna-Nicole , Giardina Traber Davis , Haskell Helen , Smith Kelly M. , Miller Kristen E.
Published: February 2025

BACKGROUND

Individuals with spinal cord injury or disease (SCI/D) experience disproportionately high rates of recurrent urinary tract infections (UTIs), which are often complicated by atypical symptoms and delayed diagnoses. Patient-centered tools, like the Urinary Symptom Questionnaires for Neurogenic Bladder (USQNB), have been developed to support symptom assessment yet remain underutilized. Generative AI tools, such as ChatGPT, may offer a more usable approach to improving symptom management by providing real-time, tailored health information directly to patients.

OBJECTIVE

This study explores the role of ChatGPT (version 3.5) in supporting urinary symptom management for individuals with SCI/D, focusing on its perceived accuracy, usefulness, and impact on healthcare engagement and self-management practices.

METHODS

Thirty individuals with SCI/D were recruited through advocacy groups and healthcare networks. Using realistic, scenario-based testing derived from validated tools for symptom management with SCI/D, such as the USQNB, participants interacted with ChatGPT to seek advice for urinary symptoms. Follow-up interviews were conducted remotely to assess individuals’ experiences using ChatGPT for urinary symptom management. Data were analyzed using inductive content analysis, with themes refined iteratively through a consensus-based process.

RESULTS

People with SCI/D reported high levels of trust in ChatGPT’s recommendations, with all 30 participants agreeing or strongly agreeing with the advice provided. ChatGPT’s responses were perceived as clear and comparable to professional medical advice. Participants mentioned concerns about the lack of sources and integration with patient-specific data. ChatGPT influenced individuals’ decision-making by supporting symptom assessment and guiding participants on when to seek professional care or pursue self-management strategies.

CONCLUSIONS

ChatGPT is a promising tool for symptom assessment and managing chronic conditions, such as urinary symptoms in individuals with SCI/D. While ChatGPT enhances accessibility to health information, further research is needed to improve its transparency and integration with personalized health data to be a more usable tool in making informed health decisions.
Using a Multilingual AI Care Agent to Reduce Disparities in Colorectal Cancer Screening: Higher FIT Test Adoption Among Spanish-Speaking Patients (Preprint)
Authors: Bhimani Meenesh , Baker R. Hal , Ausin Markel Sanz , Meixiong Gerald , Lasko Rae , Raglow-Defranco Mariska , Miller Alex , Mukherjee Subhabrata , Godil Saad , Cook Anderson , Agnew Jonathan D. , Atreja Ashish
Published: February 2025

BACKGROUND

Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations. While artificial intelligence (AI) has shown promise in healthcare delivery, its impact on health equity remains unclear.

OBJECTIVE

To evaluate the effectiveness of a bilingual generative AI voice agent outreach program in engaging Spanish-speaking patients for CRC screening compared to English-speaking patients.

METHODS

We conducted a retrospective analysis of AI-powered outreach calls for CRC screening at a large integrated health system serving central Pennsylvania and northern Maryland in September 2024. The study included 1,878 patients (517 Spanish-speaking, 1,361 English-speaking) eligible for colorectal cancer screening. The AI care agent conducted personalized phone calls in the patient's preferred language to discuss screening and facilitate fecal immunochemical test (FIT) kit requests. The primary outcome was FIT test opt-in rate. Secondary outcomes included call connect rates and duration.

RESULTS

Spanish-speaking patients demonstrated significantly higher engagement across all measures compared to English-speaking patients: FIT test opt-in rates (18.2% vs. 7.1%, p<0.001), connect rates (88.8% vs. 53.3%, p<0.001), and call duration (6.05 vs. 4.03 minutes, p<0.001). In multivariate analysis, Spanish language preference remained an independent predictor of FIT test opt-in (adjusted OR 2.012, 95% CI 1.340-3.019, p<0.001) after controlling for demographic and other factors (gender, age, state of residence, and call duration).

CONCLUSIONS

Contrary to concerns about technology exacerbating disparities, AI-powered outreach achieved significantly higher engagement among Spanish-speaking patients. These findings suggest that language-concordant AI interactions may help address healthcare disparities and improve preventive care engagement in traditionally underserved populations.
Do the symptoms of chronic constipation improve with a Primary Care programme based on behavioural re-education and abdominal massage? Protocol of a randomised clinical trial (Preprint)
Authors: Segura-Bayona Cristina , Vidal-Alaball Josep , Ramírez-Morros Anna , Miró-Catalina Queralt , Ruiz-Comellas Anna
Published: February 2025

BACKGROUND

Background: Constipation is one of the most common digestive problems in today's society. In Spain, it is estimated that this condition affects between 12% and 20% of the population, being more frequent in women, contributing considerably to the quality of life, to the increase of medical visits and to high costs for the health system.

OBJECTIVE

The objectives of the study are to reduce the rate of constipation and laxative use in the short term with a structured rehabilitation programme consisting of abdominal massage therapy and behavioural re-education, to improve the quality of life of these patients, and to assess whether the proposed treatment is effective in the short and medium term.

METHODS

Randomised clinical trial. Participants: people with constipation in the region of Central Catalonia. There will be 3 groups: the control group (CG), behavioural intervention group (BIG) and behavioural intervention and massage group (BIMG). Constipation will be assessed with the Bristol scale, Rome IV Criteria and the number of laxatives; and quality of life with the CVE-20 Questionnaire.

RESULTS

Enrollment concluded in April 2024, with data collection set to finish by February 2026. The findings will be presented at national and international conferences and published in peer-reviewed journals.

CONCLUSIONS

Research is needed on conservative, non-pharmacological treatment to try to reduce one of the main conditions affecting public health, and thus reduce the possible illnesses associated with constipation and reduce costs to the health system.

CLINICALTRIAL

Registry - Clinical Trials, trial registration number - NCT06359249, 05/04/2024.
Construction of Personalized Predictive Models for Missed Medication Doses Using Wearable Device Data: Prospective Observational Study (Preprint)
Authors: Iino Haru , Kizaki Hayato , Imai Shungo , Hori Satoko
Published: February 2025

BACKGROUND

Declining medication adherence remains a critical healthcare issue, often assessed through unreliable self-reporting methods. Wearable devices (WDs) may offer an objective means to improve adherence monitoring by continuously recording physiological and activity data.

OBJECTIVE

This study aimed to develop and internally validate personalized predictive models for identifying missed medication doses using WD-derived data.

METHODS

A 30-day prospective observational study was conducted with 8 participants who wore Apple Watches and used a dedicated iOS application. The application collected demographics, medication details, psychological factors, mealtimes, and daily missed dose events. WDs recorded time-series data (activity, heart rate, sleep) at 3-minute intervals. Data were aggregated into 1-hour segments, and lag (6- and 12-hour) as well as rolling (24-hour) features were generated. Light Gradient Boosting Machine models were constructed for each individual’s dosing regimen if the missed dose rate exceeded 20%. Two modeling approaches were compared: a Group Cross-Validation (CV) model that grouped data by day to avoid data leakage from rolling features, and a Non-rolling Feature model that excluded rolling features and used leave-one-out CV. F1 score, accuracy, recall, and precision were assessed.

RESULTS

Of the 15 enrolled participants, 8 completed the study; 4 had a missed dose rate above 20%. In these 4 individuals, the Group CV model achieved F1 scores of 0.435 to 0.902, accuracy ranging from 0.711 to 0.911, recall from 0.278 to 0.822, and precision of 1.000 for the most robust regimens. The Non-rolling Feature model yielded F1 scores of 0.667 to 0.910, accuracy ranging from 0.800 to 0.906, recall from 0.500 to 0.835, and precision of 1.000. Morning dosing regimens generally showed higher predictive performance than evening or afternoon. Time-series features, particularly those reflecting 6-, 12-, and 24-hour patterns, emerged as key predictors, indicating that physiological and lifestyle variations prior to dosing strongly influenced missed dose events.

CONCLUSIONS

Personalized predictive models using WD-derived data demonstrated high precision for detecting missed medication doses, especially in morning and evening regimens. These findings underscore the feasibility of employing objective physiological and activity data to forecast nonadherence and highlight the role of lifestyle patterns in determining missed doses. Future work should involve larger populations for external validation, strategies to improve recall—especially for clinically critical medications—and careful consideration of real-world implementation challenges.
BACTERIAL PROFILE, ANTIMICROBIAL SUSCEPTIBILITY PATTERNS, AND ASSOCIATED FACTORS OF COMMUNITY-ACQUIRED PNEUMONIA AMONG ADULT PATIENTS IN SOUTH INDIA: A CROSS-SECTIONAL STUDY
Authors: S. A. RAHIL PASHA
Published: February 2025

Objective: This study aimed to analyze the bacterial profile, antibiotic sensitivity patterns, and prevalence of multidrug resistance in community-acquired pneumonia patients at a tertiary care hospital in Bangalore, India.
Methods: Bacterial isolates were identified using standard microbiological techniques and their antibiotic sensitivity was determined using the Kirby-Bauer disk diffusion method.
Results: A total of 215 sputum samples were processed, of which 150 tested positive for bacteria. Klebsiella pneumoniae (32%) was the most common isolate, followed by Acinetobacter spp. (20.66%), and Pseudomonas aeruginosa (16%). Notable antibiotic resistance, particularly against third-generation cephalosporins, was observed, with 17.2% of g-negative isolates exhibiting multidrug resistance, primarily due to Extended-Spectrum Beta-Lactamase (ESBL) production.
Conclusion: These findings highlight the need for more effective empirical treatment strategies for CAP.
Climate Narrative in Barbara Kingsolver’s Flight Behavior
Authors: Chandan Surabhi
Published: February 2025

The impacts of climate change are negative and appear in the form of extreme weather events, disrupted ecosystems, and socio-economic challenges, disproportionately affecting vulnerable populations. Literature such as Barbara Kingsolver's Flight Behavior provides an indispensable lens for viewing these profound environmental and societal impacts. This paper attempts to explicate the extreme polarisation of the environment and anthropogenic catastrophe positioned in climate change in 21st-century literature, as particularly illustrated in Barbara Kingsolver's Flight Behavior. Dellarobia Turnbow — provides a nuanced glimpse into the complex effects of climate change on our ecosystems and rural communities. The unusual migration of monarch butterflies to Tennessee is a powerful symbol of the broader disruptions to the environment wrought by global warming. Kingsolver’s writings capture the feeling of ecological disarray and the need for change. This analysis will examine how the environmental tragedy is leveraged to elaborate on the socio-economic and cultural challenges that communities grapple with in confronting these environmental transformations and in following through with climate change mitigation. The scholarship will examine the conflation of scientific language with a vocabulary of personal transformation and the language of community through a critical lens, isolating how the novel not only furthers the genre of environmental literature but also calls for increased ecological consciousness. In addition, the article will explore the function of storytelling as a tool for creating public awareness and interest in climatic issues, Arguing that novel literature is an indispensable medium for confronting the complexities of global climate change. Through a close reading of Kingsolver's published work, I will argue that literature is both a mirror of our contemporary environmental crises and an illusion of a sustainable future.