A 'one stone, two birds' approach with mesenchymal stem cells for acute respiratory distress syndrome and Type II diabetes mellitus.

This review explores the intricate relationship between acute respiratory distress syndrome (ARDS) and Type II diabetes mellitus (T2DM). It covers ARDS epidemiology, etiology and pathophysiology, along with current treatment trends and challenges. The lipopolysaccharides (LPS) role in ARDS and its association between non-communicable diseases and COVID-19 are discussed. The review highlights the therapeutic potential of human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) for ARDS and T2DM, emphasizing their immunomodulatory effects. This review also underlines how T2DM exacerbates ARDS pathophysiology and discusses the potential of hUC-MSCs in modulating immune responses. In conclusion, the review highlights the multidisciplinary approach to managing ARDS and T2DM, focusing on inflammation, oxidative stress and potential therapy of hUC-MSCs in the future.

Machine learning approaches in diagnosing tuberculosis through biomarkers - A systematic review.

Biomarker-based tests may facilitate Tuberculosis (TB) diagnosis, accelerate treatment initiation, and thus improve outcomes. This review synthesizes the literature on biomarker-based detection for TB diagnosis using machine learning. The systematic review approach follows the PRISMA guideline. Articles were sought using relevant keywords from Web of Science, PubMed, and Scopus, resulting in 19 eligible studies after a meticulous screening. All the studies were found to have focused on the supervised learning approach, with Support Vector Machine (SVM) and Random Forest emerging as the top two algorithms, with the highest accuracy, sensitivity and specificity reported to be 97.0%, 99.2%, and 98.0%, respectively. Further, protein-based biomarkers were widely explored, followed by gene-based such as RNA sequence and, Spoligotypes. Publicly available datasets were observed to be popularly used by the studies reviewed whilst studies targeting specific cohorts such as HIV patients or children gathering their own data from healthcare facilities, leading to smaller datasets. Of these, most studies used the leave one out cross validation technique to mitigate overfitting. The review shows that machine learning is increasingly assessed in research to improve TB diagnosis through biomarkers, as promising results were shown in terms of model's detection performance. This provides insights on the possible application of machine learning approaches to diagnose TB using biomarkers as opposed to the traditional methods that can be time consuming. Low-middle income settings, where access to basic biomarkers could be provided as compared to sputum-based tests that are not always available, could be a major application of such models.

Targeted delivery of gold nanoparticles by neural stem cells to glioblastoma for enhanced radiation therapy: a review.

Glioblastoma (GB) is the most malignant subtype of brain cancer derived from astrocytes in the brain. Radiotherapy is one of the standard treatments for GB patients, but its effectiveness is often limited by the radioresistance of aggressive GB cells. Higher dose of radiation needs to be applied to GB patients to eliminate these stubborn cells, but this also means more side effects on the adjacent healthy cells because the radiation beam could indistinguishably harm all cells exposed to it. In order to address this problem, various strategies have been studied to enhance the radiosensitivity among the radioresistant cell populations for targeted eradication of GB without harming other surrounding healthy cells. One of the promising strategies for radiosensitization is to use gold nanoparticles (AuNPs) which can enhance photoelectric effects within the radioresistant cells for higher killing efficiency even at low doses of radiation. Nonetheless, there is no evidence showing the capability of these nanoparticles to travel to brain tumor cells, therefore, the application of this nanotechnology is very much dependent on the development of a suitable carrier to deliver the AuNPs to the GB tumor sites specifically. In this review article, we discussed the potentials of neural stem cells (NSCs) as biological carriers to carry AuNPs to targeted GB tumor sites and provided new insights into the potential of NSC-based targeted delivery system for GB treatment. The information reported here may pave a new direction for clinical transformation of next-generation nanoparticle-assisted radiotherapy to optimize the efficacy of radiotherapy for GB treatment.