Background: Distractor efficiency (DE) of multiple-choice questions (MCQs) responses is a component of the psychometric analysis used by the examiners to evaluate the distractors’ credibility and functionality. This study was conducted to evaluate the impact of the DE on the difficulty and discrimination indices. Methods: This cross-sectional study was conducted from April to June 2023. It utilizes the final exam of the Principles of Diseases Course with 45 s-year students. The exam consisted of 60 type A MCQs. Item analysis (IA) was generated to evaluate KR20, difficulty index (DIF), discrimination index (DIS), and distractor efficiency (DE). DIF was calculated as the percentage of examinees who scored the item correctly. DIS is an item’s ability to discriminate between higher and lower 27% of examinees. For DE, any distractor selected by less than 5% is considered nonfunctional, and items were classified according to the non-functional distractors. The correlation and significance of variance between DIF, DI, and DE were evaluated. Results: The total number of examinees was 45. The KR-20 of the exam was 0.91. The mean (M), and standard deviation (SD) of the DIF of the exam was 37.5(19.1), and the majority (69.5%) were of acceptable difficulty. The M (SD) of the DIS was 0.46 (0.22), which is excellent. Most items were excellent in discrimination (69.5%), only two were not discriminating (13.6%), and the rest were of acceptable power (16.9%). Items with excellent and good efficiency represent 37.3% each, while only 3.4% were of poor efficiency. The correlation between DE and DIF (p = 0.000, r= -0.548) indicates that items with efficient distractors (low number of NFD) are associated with those having a low difficulty index (difficult items) and vice versa. The correlation between DE and DIS is significantly negative (P = 0.0476, r=-0.259). In such a correlation, items with efficient distractors are associated with low-discriminating items. Conclusions: There is a significant moderate negative correlation between DE and DIF (P = 0.00, r = -0.548) and a significant weak negative correlation between DE and DIS (P = 0.0476, r = -0.259). DIF has a non-significant negative correlation with DIS (P = 0.7124, r = -0.0492). DE impacts both DIF and DIS. Items with efficient distractors (low number of NFD) are associated with those having a low difficulty index (difficult items) and discriminating items. Improving the quality of DE will decrease the number of NFDs and result in items with acceptable levels of difficulty index and discrimination power.

Insulin resistance (IR) is a significant factor in the development and progression of metabolic-related diseases like dyslipidemia, T2DM, hypertension, nonalcoholic fatty liver disease, cardiovascular and cerebrovascular disorders, and cancer. The pathogenesis of IR depends on multiple factors, including age, genetic predisposition, obesity, oxidative stress, among others. Abnormalities in the insulin-signaling cascade lead to IR in the host, including insulin receptor abnormalities, internal environment disturbances, and metabolic alterations in the muscle, liver, and cellular organelles. The complex and multifaceted characteristics of insulin signaling and insulin resistance envisage their thorough and comprehensive understanding at the cellular and molecular level. Therapeutic strategies for IR include exercise, dietary interventions, and pharmacotherapy. However, there are still gaps to be addressed, and more precise biomarkers for associated chronic diseases and lifestyle interventions are needed. Understanding these pathways is essential for developing effective treatments for IR, reducing healthcare costs, and improving quality of patient life.

Idiopathic pulmonary fibrosis (IPF) is an irreversible and life-threatening lung disease of unknown etiology presenting only a few treatment options. TGF-β signaling orchestrates a cascade of events driving pulmonary fibrosis (PF). Notably, recent research has affirmed the augmentation of TGF-β receptor (TβR) signaling via HSP90 activation. HSP90, a molecular chaperone, adeptly stabilizes and folds TβRs, thus intricately regulating TGF-β1 signaling. Our investigation illuminated the impact of alvespimycin, an HSP90 inhibitor, on TGF-β-mediated transcriptional responses by inducing destabilization of TβRs. This outcome stems from the explicit interaction of TβR subtypes I and II with HSP90, where they are clients of this cellular chaperone. It is worth noting that regulation of proteasome-dependent degradation of TβRs is a critical standpoint in the termination of TGF-β signal transduction. Oleuropein, the principal bioactive compound found in Olea europaea, is acknowledged for its role as a proteasome activator. In this study, our aim was to explore the efficacy of a combined therapy involving oleuropein and alvespimycin for the treatment of PF. We employed a PF rat model that was induced by intratracheal bleomycin infusion. The application of this dual therapy yielded a noteworthy impediment to the undesired activation of TGF-β/mothers against decapentaplegic homologs 2 and 3 (SMAD2/3) signaling. Consequently, this novel combination showcased improvements in both lung tissue structure and function while also effectively restraining key fibrosis markers such as PDGF-BB, TIMP-1, ACTA2, col1a1, and hydroxyproline. On a mechanistic level, our findings unveiled that the antifibrotic impact of this combination therapy likely stemmed from the enhanced degradation of both TβRI and TβRII. In conclusion, the utilization of proteasomal activators in conjunction with HSP90 inhibitors ushers in a promising frontier for the management of PF.

Sorafenib, a multikinase inhibitor, is a first-line treatment for advanced hepatocellular carcinoma, but its long-term effectiveness is limited by the emergence of resistance mechanisms. One such mechanism is the reduction of microvessel density and intratumoral hypoxia caused by prolonged sorafenib treatment. Our research has demonstrated that HSP90 plays a critical role in conferring resistance to sorafenib in HepG2 cells under hypoxic conditions and N-Nitrosodiethylamine-exposed mice as well. This occurs through the inhibition of necroptosis on the one hand and the stabilization of HIF-1α on the other hand. To augment the effects of sorafenib, we investigated the use of ganetespib, an HSP90 inhibitor. We found that ganetespib activated necroptosis and destabilized HIF-1α under hypoxia, thus enhancing the effectiveness of sorafenib. Additionally, we discovered that LAMP2 aids in the degradation of MLKL, which is the mediator of necroptosis, through the chaperone-mediated autophagy pathway. Interestingly, we observed a significant negative correlation between LAMP2 and MLKL. These effects resulted in a reduction in the number of surface nodules and liver index, indicating a regression in tumor production rates in mice with HCC. Furthermore, AFP levels decreased. Combining ganetespib with sorafenib showed a synergistic cytotoxic effect and resulted in the accumulation of p62 and inhibition of macroautophagy. These findings suggest that the combined therapy of ganetespib and sorafenib may offer a promising approach for the treatment of hepatocellular carcinoma by activating necroptosis, inhibiting macroautophagy, and exhibiting a potential antiangiogenic effect. Overall, continued research is critical to establish the full therapeutic potential of this combination therapy.

Introduction: With the incorporation of artificial intelligence (AI), significant advancements have occurred in the field of fetal medicine, holding the potential to transform prenatal care and diagnostics, promising to revolutionize prenatal care and diagnostics. This scoping review aims to explore the recent updates in the prospective application of AI in fetal medicine, evaluating its current uses, potential benefits, and limitations. Methods: Compiling literature concerning the utilization of AI in fetal medicine does not appear to modify the subject or provide an exhaustive exploration of electronic databases. Relevant studies, reviews, and articles published in recent years were incorporated to ensure up-to-date data. The selected works were analyzed for common themes, AI methodologies applied, and the scope of AI’s integration into fetal medicine practice. Results: The review identified several key areas where AI applications are making strides in fetal medicine, including prenatal screening, diagnosis of congenital anomalies, and predicting pregnancy complications. AI-driven algorithms have been developed to analyze complex fetal ultrasound data, enhancing image quality and interpretative accuracy. The integration of AI in fetal monitoring has also been explored, with systems designed to identify patterns indicative of fetal distress. Despite these advancements, challenges related to the ethical use of AI, data privacy, and the need for extensive validation of AI tools in diverse populations were noted. Conclusion: The potential benefits of AI in fetal medicine are immense, offering a brighter future for our field. AI equips us with tools for enhanced diagnosis, monitoring, and prognostic capabilities, promising to revolutionize the way we approach prenatal care and diagnostics. This optimistic outlook underscores the need for further research and interdisciplinary partnerships to fully leverage AI’s potential in driving forward the practice of fetal medicine.

Background: Type 2 diabetes mellitus (T2DM) is becoming a major global health concern, especially in developing nations. The high prevalence of obesity and related diabetes cases are attributed to rapid economic progress, physical inactivity, the consumption of high-calorie foods, and changing lifestyles. Objectives: We investigated the roles of pro-inflammatory chemokines CCL1, 2, 4, and 5 in T2DM with varying levels of obesity in the Asir region of Saudi Arabia. Materials and Methods: In total, 170 confirmed T2DM subjects and a normal control group were enrolled. Demographic data, serum levels of CCL-1, 2, 4, and 5, and biochemical indices were assessed in the subjects and control groups by standard procedures. Results: T2DM subjects were divided into four groups: A (normal body weight), B (overweight), C (obese), and D (highly obese). We observed that male and female control subjects had similar mean serum concentrations of pro-inflammatory chemokines CCL-1, 2, 4, and 5. T2DM subjects in all the four groups showed significantly higher levels of all the four chemokines compared to the controls, regardless of gender. In T2DM subjects with obesity and severe obesity, the rise was most significant. There was a progressive rise in the concentrations of CCL-1, 2, and 4 in T2DM subjects with increasing BMI. Serum CCL5 levels increased significantly in all T2DM subject groups. The increase in CCL5 was more predominant in normal-weight people, compared to overweight and obese T2DM subjects. Conclusions: Male and female control subjects had similar serum levels of pro-inflammatory chemokines CCL-1, 2, 4, and 5. The progressive rise in blood concentrations of three pro-inflammatory chemokines CCL-1, 2, and 4 in T2DM subjects with increasing BMI supports the idea that dyslipidemia and obesity contribute to chronic inflammation and insulin resistance. Serum CCL5 levels increased significantly in all T2DM subject groups. The selective and more pronounced increase in CCL5 in the T2DM group with normal BMI, compared to subjects with varying degrees of obesity, was rather surprising. Further research is needed to determine if CCL5 underexpression in overweight and obese T2DM subjects is due to some unexplained counterbalancing processes.