bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential Association Between Triglyceride-Glucose Related Indices and Type 2 Diabetes-Related Complications: Insights from the National Metabolic Management Center and MIMIC-IV 3.0 Databases
Authors: Zhang Yue-Yang , Bai Xue , Chen Bing-Xue , Wan Qin 
Published: August 2024

Abstract

Background
The triglyceride-glucose index (TyG) and its related indices are predominantly utilized for the effective assessment of insulin resistance. However, their predictive value concerning type 2 diabetes-related complications remains uncertain. Therefore, this study aims to investigate the potential association between TyG-related indices and type 2 diabetes-related complications through a retrospective analysis of two distinct populations.
Methodss
Established in 2016, the National Metabolic Management Center (MMC) serves as a comprehensive platform designed for the standardized diagnosis, treatment, and long-term follow-up of metabolic diseases, encompassing nearly 300 hospitals across various regions of China. Out of 8,669 initially hospitalized patients, 2,194 were selected for subsequent analysis. Patients were stratified into three groups according to the tertiles of TyG-related indices, with circulatory abnormalities (CA), diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic peripheral neuropathy (DPN) serving as the primary outcomes. Logistic regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between TyG-related indices and complications associated with type 2 diabetes. Finally, a validation analysis was performed on 9,715 samples from the MIMIC-IV 3.0 database to bolster the reliability and generalizability of the findings.
Results
Logistic regression analysis of patients in the MMC database revealed that, in fully adjusted models, each 1 SD increase in TyG and TyG-WC was significantly associated with an elevated risk of DKD. Restricted cubic spline (RCS) analysis indicated a non-linear inverse L-shaped relationship between TyG and DKD risk, while TyG-WC demonstrated a distinct dose-response relationship with DKD risk. Validation analysis conducted in the MIMIC-IV database further corroborated the significant association between TyG-related indices and the risk of DKD.
Conclusions
The findings of this study, involving both Chinese and American populations, indicate that TyG-related indices may serve as robust and independent potential biomarkers for assessing the risk of DKD in individuals with type 2 diabetes.
Enhancing AI Chatbot Responses in Healthcare: The SMART Prompt Structure in Head and Neck Surgery
Authors: Vaira Luigi Angelo , Lechien Jerome R. , Abbate Vincenzo , Gabriele Guido , Frosolini Andrea , De Vito Andrea , Maniaci Antonino , Yanez Miguel Mayo , Boscolo-Rizzo Paolo , Saibene Alberto Maria , Maglitto Fabio , Salzano Giovanni , Califano Gianluigi , Troise Stefania , Chiesa-Estomba Carlos Miguel , De Riu Giacomo 
Published: August 2024

Abstract

Objective. To evaluate the impact of prompt construction on the quality of AI chatbot responses in the context of head and neck surgery. Study design. Observational and evaluative study. Setting. International collaboration involving 16 researchers from 11 European centers specializing in head and neck surgery. Methods. A total of 24 questions, divided into clinical scenarios, theoretical questions, and patient inquiries, were developed. These questions were inputted into ChatGPT-4o both with and without the use of a structured prompt format, known as SMART (Seeker, Mission, AI Role, Register, Targeted Question). The AI-generated responses were evaluated by experienced head and neck surgeons using the QAMAI instrument, which assesses accuracy, clarity, relevance, completeness, source quality, and usefulness. Results. The responses generated using the SMART prompt scored significantly higher across all QAMAI dimensions compared to those without contextualized prompts. Median QAMAI scores for SMART prompts were 27.5 (IQR 25–29) versus 24 (IQR 21.8–25) for unstructured prompts (p < 0.001). Clinical scenarios and patient inquiries showed the most significant improvements, while theoretical questions also benefited but to a lesser extent. The AI's source quality improved notably with the SMART prompt, particularly in theoretical questions. Conclusions. The study suggests that the structured SMART prompt format significantly enhances the quality of AI chatbot responses in head and neck surgery. This approach improves the accuracy, relevance, and completeness of AI-generated information, underscoring the importance of well-constructed prompts in clinical applications. Further research is warranted to explore the applicability of SMART prompts across different medical specialties and AI platforms.
Analysis of shoreline dynamics of Lake Sibaya in South Africa between 1986 and 2020 using the Landsat series and DSAS algorithm
Authors: Kemp Fallon Kagney , Xulu Sifiso , Gebreslasie Michael 
Published: August 2024

Abstract

Lake Sibaya is the largest nearshore freshwater lake in South Africa. It is ecologically and socioeconomically linked to the human development agenda in the northeastern coastal region of the country. It is part of the iSimangaliso Wetland Park, the first proclaimed World Heritage Site in the country and the only water resource serving surrounding areas. However, Lake Sibaya is reportedly drying up rapidly for various reasons (e.g., commercial forestry), yet the extent and pattern of this drying are unidentified. Here, we used the Landsat satellite data series and the Digital Shoreline Analysis System (DSAS) algorithm to analyze the changes in the shoreline of Lake Sibaya between 1986 and 2020. The study results indicate that Lake Sibaya displayed major retracting changes from 70.6 km2 in 1986 to 49.5 km2 in 2020, with marked erosional changes in the regions of the southeastern basin and northern arm. This occurred with a net shoreline displacement of − 1338 m and an end point rate of − 39 m/year, averaging ± 6 m/year. Our results projected further lake retreat from 49.5 km2 in 2020 to 39.1 km2 in 2030. We observed vegetation growth on sandbanks separating the southeastern basin from the main system, threatening to isolate these systems entirely. Improved rainfall is expected to reconnect these basins because they rely heavily on groundwater recharge. Otherwise, activities served by the southeastern basin will be affected. We recommend further research to accurately quantify the levels of abstraction by different users, including fine-scale mapping of planted forests surrounding this lake.
One-dimensional Fermi polaron after a kick: Two-sided singularity of the momentum distribution, Bragg reflection and other exact results
Authors: Gamayun Oleksandr , Lychkovskiy Oleg 
Published: August 2024

A mobile impurity particle immersed in a quantum fluid forms a polaron - a quasiparticle consisting of the impurity and a local disturbance of the fluid around it. We ask what happens to a one-dimensional polaron after a kick, i.e. an abrupt application of a force that instantly delivers a finite impulse to the impurity. In the framework of an integrable model describing an impurity in a one-dimensional gas of fermions or hard-core bosons, we calculate the distribution of the polaron momentum established when the post-kick relaxation is over. A remarkable feature of this distribution is a two-sided power-law singularity. It emerges due to one of two processes. In the first process, the whole impulse is transferred to the polaron, without creating phonon-like excitations of the fluid. In the second process, the impulse is shared between the polaron and the center-of-mass motion of the fluid, again without creating any fluid excitations. The latter process is, in fact, a Bragg reflection at the edge of the emergent Brillouin zone. We carefully analyze the conditions for each of the two processes. The asymptotic form of the distribution in the vicinity of the singularity is derived.
AI-powered Solutions for Casualty Assessment in Drug Safety and Patient Care
Authors: Sharma Himanshu , Mahajan Shushank , Garg Nitika , Chauhan Samrat , Saini Monika , Singh Thakur Gurjeet , Dhankhar Sanchit , Mittal Pooja 
Published: August 2024

Objective:
An adverse drug reaction is defined as “an appreciably harmful or unpleasant reaction, resulting from an intervention related to the use of a
medicinal product, which warrants prevention or specific treatment, alteration of the dosage regimen, or withdrawal of the product, as it predicts
hazard from future administration.”

Methodology:
Currently used to report such responses, the International Classification of Diseases will soon incorporate WHO's Adverse Reaction Terminology.
A medication's bad effects can fall into one of six types, each having its own mnemonic: withdrawal, therapeutic failure, dose-and time-related,
non-dose-related, weird, increased withdrawal, and withdrawal overall (time-related). Factors such as timing, illness pattern, investigation findings,
and retesting the medicine could be useful in pinpointing the reason for a suspected adverse drug reaction. Management includes treating the
effects of the medication specifically as well as, if feasible, stopping it altogether.

Results:
Reporting suspected adverse medication reactions is important. Monitoring techniques are able to identify responses and establish connections.
There is many software that is used to report and monitor adverse drug reaction responses. Various Pharmacovigilance companies use AI
technology to utilize this method to record signals, communicate, and solve new issues in order to limit or avoid harm because of large data size.
Biosurfactant Nanomicelles and Peptide Integration: Novel Approaches to Targeted Gene Delivery in Colon Cancer Treatment
Authors: Bhattacharya Sankha , Kumar Devendra , Prajapati Bhupendra G. , Anjum Md Meraj 
Published: August 2024

Abstract:
A notable breakthrough in the treatment of colon cancer involves the utilisation
of a cutting-edge drug delivery technology known as biosurfactant-derived nanomicelles.
These nanomicelles, composed of natural biosurfactant molecules, possess the
distinct capability to enclose pharmaceuticals or genetic material, such as DNA, siRNA,
or mRNA, within spherical formations. With a size ranging from 10 to 100 nanometers,
these nanomicelles exhibit precision targeting capabilities towards colon cancer cells,
hence minimising the occurrence of side effects typically associated with treatment. Upon
being specifically targeted, the nanomicelles liberate their cargo into cancer cells, resulting
in enhanced therapy efficacy. This novel strategy utilises the specific attributes
of the tumour microenvironment to administer precise and focused treatment. These nanomicelles
improve the absorption by cells and reduce harm to healthy tissues by imitating
important nutrients or utilising compounds that specifically target tumours. Furthermore,
the incorporation of stimuli-responsive components allows for regulated medication
release in reaction to the acidic environment seen in tumours. The review focuses
on examining the use of biosurfactants and natural peptides in nanomicellar carriers as
ways to fight against colon cancer. Folate-coated nanomicelles incorporating curcumin
facilitate precise gene delivery, while the partnership of biosurfactants, such as surfactin
from Bacillus subtilis and natural peptides, enables the transportation of particular cyclopeptides
into the tumour network. Peptides, similar to bombesin, direct nanomicelles
to specific places, while peptides based on curcumin control the release of medicinal substances.
While preclinical investigations demonstrate promise, obstacles remain in formulation
and regulatory issues. However, biosurfactant-based nanomicelles, particularly
folate-coated carriers loaded with curcumin, show tremendous potential in overcoming
biological barriers and delivering medicines efficiently to colon cancer cells.
Single-cell Transcriptomics, Web-based Systems Pharmacology and Integrated Transcriptomics Network Analysis Identified Diagnostic Targets and Drug Candidates for Type 2 Diabetes
Authors: Li Tingting , Lin Qiumei , Zhou Danni , Jiang Yi , Chen Sheng , Li Ruoqing 
Published: August 2024

Aim:
To discover new therapeutic targets for Type 2 diabetes (T2D) and develop a
new diagnostic model.

Background:
T2D is a chronic disease that can be controlled by oral hypoglycemic drugs, however,
it cannot be fully cured. The continued increase in the prevalence of T2D and the limitations
of existing treatments urgently call for the development of new drugs to be able to effectively
control the progression of the disease.

Objective:
We aimed to discover new therapeutic targets for T2D and to develop a new diagnostic
model.

Method:
Single-cell transcriptome, web-based systematic pharmacology, and transcriptology
were applied to identify T2D diagnostic targets and drug candidates and to analyze the underlying
molecular mechanisms.

Results:
By single-cell clustering analysis, we identified seven subsets between the normal islet
β-cell samples and T2D islet β-cell samples. A total of 27 key genes in the intersection of insulin-
related genes and diabetes-related genes were selected by protein-protein interaction (PPI)
analysis and MolecularComplexDetection (MCODE) analysis. Notably, ESR1, MME, and
CCR5 had the area under curves (AUC) values as high as 67.95%, 66.67%, and 66.03% for the
diagnosis of T2D, respectively. Since the expression of MME in T2D samples was significantly
higher than in normal samples, we screened 155 drug candidates against MME in T2D. Finally,
the molecular docking revealed a strong binding strength between MME and DB05490, which
was one of the most effective candidate drugs for treating T2D.

Conclusion:
Our study screens for diagnostic signatures and potential therapeutic agents for
T2D, which provides valuable insights into the development of T2D biomarkers and their drug
discovery.
A Comparative Analysis of Open Flap Debridement with and without Autogenous Periosteal Graft as a Barrier Membrane for the Treatment of Class II Furcation Involvement in Mandibular Molars: A Case-control Study
Authors: Jain Amiyavardhan , Bhusari Prashant , Alasqah Mohammed , Khan Mohammad Shoyab , Gufran Khalid 
Published: August 2024

Background
The current study aimed to compare the efficiency of autogenous periosteal graft (APG) as a barrier to open flap debridement (OFD) in Class II mandibular furcation defects.

Methods
A total of 24 patients participated in this research and were divided into the test group and the control group. The test group received treatment with OFD plus APG as a barrier, while the control group received only OFD. Plaque index (PI), papillary bleeding index (PBI), vertical probing pocket depth (V-PPD), vertical relative attachment level (V-RAL), relative gingival marginal level (RGML), and horizontal probing depth (HPD) were assessed at baseline, 3 and 6 months, respectively, in both groups. The normality test was performed with the Shapiro-Wilk test. Descriptive statistics were performed for V-PPD, HPD, RGM, L, and V-RAL. A comparison between baseline and 3 months and 6 months was made using the paired t-test.

Results
The PI and PBI scores were compared at baseline, 3, and 6 months in both groups, which indicated no significant differences. A comparison of clinical parameters, V-PPD, V-RAL, RGML, and HPD, from baseline to 3 and 6 months in both groups showed significant differences except for RGML from baseline to 6 months in the control group. Moreover, the comparative analysis between the control and test groups showed significant improvement in all clinical parameters.

Conclusion
APG, along with OFD as a barrier in the management of Class II mandibular furcation defects, demonstrated a significant advancement in clinical parameters.
Things to know about Sacroiliac Joint Pain
Authors: Samolsky Dekel Boaz G. , Campesato Manuela , Salis Eleonora , Secli Roberto , Sorella Maria C. , Vasarri Alessio , Ventola Matteo 
Published: August 2024

Background
Sacroiliac Joint dysfunction is a significant pain generator (>25%) in Lower Back Pain patients; however, differential diagnosis and treatment in these patients can be challenging for pain physicians. Understanding its complex anatomy, function, and possible primary and secondary pain etiologies is essential to formulate appropriate diagnostic workup and treatment options for SI joint disorders.

Objective
To report a concise narrative review of the Sacroiliac Joint anatomy, function, and injury mechanisms, along with an overview of its painful dysfunction diagnosis workup and potential treatments.

Methods
A concise summary of the current literature relevant to Sacroiliac Joint dysfunction, putting previous research and findings in context and presenting recent developments in a critical and focused manner.

Results and Conclusion
Sacroiliac Joint dysfunction diagnosis is challenging given its complex anatomy, physiology, and variable mechanisms of injury and pain presentation features. According to the underlying etiopathogenesis, SIJ dysfunction chronic pain may be secondary or primary (arising or not from an underlying classified disease, respectively). The clinical implications of this review are (a) for the diagnosis workup, a combination of history, physical examination, specific provocative tests, articular and periarticular block, and appropriate imaging is imperative; (b) treatment may include conservative management, therapeutic blocks (intra- and periarticular) with local anesthetics and corticosteroids, neuro ablation (Crio or Radio Frequency techniques), and surgery for patients unresponsive to therapies.
miRVim: Three-dimensional miRNA Structure Database
Authors: Sahu Vishal Kumar , Parida Ankita Subhadarsani , Ranjan Amit , Madhyastha Harishkumar , Basu Soumya 
Published: August 2024

Introduction:
MicroRNAs (miRNAs), a distinct category of non-coding RNAs, exert
multifaceted regulatory functions in a variety of organisms, including humans, animals, and
plants. The inventory of identified miRNAs stands at approximately 60,000 among all species
and 1,926 in Homo sapiens manifests miRNA expression. Their theranostic role has been explored
by researchers over the last few decades, positioning them as prominent therapeutic targets
as our understanding of RNA targeting advances. However, limited availability of experimentally
determined miRNA structures has constrained drug discovery efforts relying on virtual screening
or computational methods, including machine learning and artificial intelligence.

Methods:
To address this lacuna, miRVim has been developed, providing a repository of human
miRNA structures derived from both two-dimensional (MXFold2, CentroidFold, and RNAFold)
and three-dimensional (RNAComposer and 3dRNA) structure prediction algorithms, in addition
to experimentally available structures from the RCSB PDB repository.

Results:
miRVim contains 13,971 predicted secondary structures and 17,045 predicted three-dimensional
structures filling the gap of unavailability of miRNA structure data bank. This database
aims to facilitate computational data analysis for drug discovery, opening new avenues for advancing
technologies such as machine learning-based predictions in the field of RNA biology.

Conclusion:
The publicly accessible structures provided by miRVim, available at
https://mirna.in/miRVim, offer a valuable resource for the research community, advancing the
field of miRNA-related computational analysis and drug discovery.
In-vitro and Ex-vivo Evaluation of Central Composite Design Implemented Formulation and Characterization of Itraconazole Nanocrystal Loaded Hydrogel
Authors: Singh Bhawana , Upadhyay Prabhat Kumar , Kumar Manish 
Published: August 2024

Aim:
The study aimed to develop and optimize itraconazole nanocrystal-loaded hydro-gel by central composite design.

Background:
Itraconazole is a broad spectrum antifungal drug classified as a BCS Class II drug with poor water solubility that limits its dermal availability and serves as a rate-limiting barrier in topical formulations. Thus, it was aimed at developing and optimizing itraconazole nanocrystal-loaded hydrogel to improve its skin penetration by solving its solubility issue.

objective:
The objective of the study was to improve the topical delivery of itraconzole by solving its solubility issue.

Methods:
Nanocrystals were prepared using the solvent anti-solvent precipitation method fol-lowed by ultrasonication. The solvent-antisolvent and stabilizer were selected based on a screen-ing study. Optimizations of nanocrystal formulation were carried out using Central Composite Design (CCD). The Optimized formulation(D14) was characterized for % drug release, saturation solubility, particle size, zeta potential, PDI, and DSC analysis.The optimized formulation D14 was incorporated into hydrogel using HPMC K15M at three different concentrations (1%, 1.5%, and 2% w/w). The gels that were developed underwent assessment for their physical appearance, pH determination, rheological study, spread ability study, drug release study, and ex-vivo permea-tion study.

Results:
The optimized nanocrystal formulation (D14) presented that the observed values of Drug Release in 10min % was 93.532 ± 0.263 and Saturation solubility of 624.12 ± 0.76 μg/ml. The mean particle size of the optimized nanocrystal formulation was 253.7nm, with a PDI value of 0.202 and zeta potential of 26.4 mv ± 0.7mv possesses good physical stability. There is approxi-mately a 37.76-fold increase in saturation solubility compared to the saturation solubility of the pure drug, among the developed nanocrystal-loaded gel formulation. The D15 formulation (con-taining 1% HPMC) demonstrated maximum drug release up to 87.948 ± 0.298% within 24 hours compared to the control gel that showed 19.792 ± 0.046% and desirable rheological characteris-tics. The ex-vivo permeation study of D15 gel revealed 4.6 times enhanced permeation compared to the control gel

Conclusion:
In conclusion, the present study successfully demonstrated the formulation of itra-conazole nanocrystal-loaded hydrogel for topical delivery with improved drug release and perme-ation characteristics. The release kinetics of the drug best fitted the Higuchi model (r2 =0.9837), suggesting the sustained release of the drug from the gel matrix.