Aortic stenosis (AS) is one of the most common types of valvular heart disease in older adults, with age being significantly associated with the development of AS. The transcatheter aortic valve replacement (TAVR) procedure, since it was first performed in 2002, has emerged as a preferred treatment option for patients who are at intermediate to high surgical risk due to advanced age or medical comorbidities. Older adults with severe AS may present with acute decompensated heart failure leading to cardiogenic shock (CS). Among patients 65 years and older with AS presenting for TAVR, 4.1% were reportedly in acute CS. Regardless of etiology, mortality from CS itself is high (30%-50%) and increases with advancing age. TAVR for these patients could provide a definite treatment for both AS and CS. There is still limited evidence regarding the safety and efficacy of TAVR in this population, but recent studies are promising, with successful procedural results and a good recovery rate after the procedure. However, particularly for older adults, there are other factors that clinicians should consider during pre- and post-procedural status, such as patient's goals, frailty, polypharmacy, dementia, or delirium. In this article, we reviewed current studies regarding TAVR for older adults with AS and CS, the reason for comprehensive geriatric assessment, and the introduction of appropriate geriatric assessment tools based on the Age-Friendly 4Ms framework that cardiologists can adopt in real-world practice.

High-altitude pulmonary hypertension (HAPH) occurs when blood pressure in the pulmonary arteries rises due to exposure to high altitudes above 2,500 m. At these elevations, reduced atmospheric pressure leads to lower oxygen levels, triggering a series of physiological responses, including pulmonary artery constriction, which elevates blood pressure. This review explored the complex pathophysiological mechanisms of HAPH and reviewed current pharmaceutical interventions for its management. Meanwhile, this review particularly emphasized on the emerging research concerning Chinese medicinal plants as potential treatments for HAPH. Traditional Chinese medicines are rich in diverse natural ingredients that show significant promise in alleviating HAPH symptoms. We reviewed both in vitro and in vivo studies to assess the efficacy, safety, and mechanisms of these natural medicines, along with their potential adverse effects. Additionally, this review highlighted new alternative natural remedies, underscoring the need for ongoing research to expand available treatment options for HAPH.

Colorectal cancer has substantial morbidity and mortality. Approximately one-quarter of cases are overlooked during screening colonoscopy, leading to interval colorectal cancer. The use of artificial intelligence (AI) through deep learning systems has demonstrated promising results in the detection of polyps and adenomas. Consequently, our objective was to evaluate the impact of AI on adenoma detection. To identify relevant studies, we searched the PubMed, MEDLINE, and Cochrane Library databases without restrictions on publication date. Ultimately, we analyzed 16 randomized controlled trials involving 13,685 participants. The primary outcome assessed was the effect of AI-assisted colonoscopy (AIAC) on the adenoma detection rate (ADR). Secondary outcomes included the polyp detection rate (PDR) and adenomas per colonoscopy (APC). A random-effects model was used to calculate pooled effect sizes, and statistical heterogeneity was evaluated using the Higgins I 2 statistic, with I 2 cutoff points of 25%, 50%, and 75% indicating low, moderate, and high heterogeneity, respectively. Publication bias was investigated using a funnel plot, and the quality of evidence was appraised using the Grading of Recommendations, Assessment, Development, and Evaluation framework. The findings indicated a 26% greater ADR with AIAC than with standard colonoscopy (40.4% vs. 31.9%). Additionally, AIAC was associated with a 30% greater PDR (52.9% vs.40.1%) and a 44% higher APC. The findings demonstrate that the integration of AI in colonoscopy improves ADR, PDR, and APC, potentially reducing the incidence of interval colorectal cancer.

Shiga toxin-producing Escherichia coli is the most prevalent bacterial strain responsible for Shiga toxin-related infections. While Shiga toxin is inherently toxic, it has potential therapeutic applications as a component of anticancer drugs. Despite its association with infections and harmful effects on human health, Shiga toxin is being explored as a viable element in drug delivery systems targeting cancer cells. The findings indicate that the production of mutated bacteria containing Shiga toxin is an effective preventive strategy for immunization against these toxins. Furthermore, the B subunit of Shiga toxin shows promise for imaging cancer cells, opening new paths for therapeutic interventions.

Colorectal cancer has substantial morbidity and mortality. Approximately one-quarter of cases are overlooked during screening colonoscopy, leading to interval colorectal cancer. The use of artificial intelligence (AI) through deep learning systems has demonstrated promising results in the detection of polyps and adenomas. Consequently, our objective was to evaluate the impact of AI on adenoma detection. To identify relevant studies, we searched the PubMed, MEDLINE, and Cochrane Library databases without restrictions on publication date. Ultimately, we analyzed 16 randomized controlled trials involving 13,685 participants. The primary outcome assessed was the effect of AI-assisted colonoscopy (AIAC) on the adenoma detection rate (ADR). Secondary outcomes included the polyp detection rate (PDR) and adenomas per colonoscopy (APC). A random-effects model was used to calculate pooled effect sizes, and statistical heterogeneity was evaluated using the Higgins I 2 statistic, with I 2 cutoff points of 25%, 50%, and 75% indicating low, moderate, and high heterogeneity, respectively. Publication bias was investigated using a funnel plot, and the quality of evidence was appraised using the Grading of Recommendations, Assessment, Development, and Evaluation framework. The findings indicated a 26% greater ADR with AIAC than with standard colonoscopy (40.4% vs. 31.9%). Additionally, AIAC was associated with a 30% greater PDR (52.9% vs.40.1%) and a 44% higher APC. The findings demonstrate that the integration of AI in colonoscopy improves ADR, PDR, and APC, potentially reducing the incidence of interval colorectal cancer.

Shiga toxin-producing Escherichia coli is the most prevalent bacterial strain responsible for Shiga toxin-related infections. While Shiga toxin is inherently toxic, it has potential therapeutic applications as a component of anticancer drugs. Despite its association with infections and harmful effects on human health, Shiga toxin is being explored as a viable element in drug delivery systems targeting cancer cells. The findings indicate that the production of mutated bacteria containing Shiga toxin is an effective preventive strategy for immunization against these toxins. Furthermore, the B subunit of Shiga toxin shows promise for imaging cancer cells, opening new paths for therapeutic interventions.

Colorectal cancer has substantial morbidity and mortality. Approximately one-quarter of cases are overlooked during screening colonoscopy, leading to interval colorectal cancer. The use of artificial intelligence (AI) through deep learning systems has demonstrated promising results in the detection of polyps and adenomas. Consequently, our objective was to evaluate the impact of AI on adenoma detection. To identify relevant studies, we searched the PubMed, MEDLINE, and Cochrane Library databases without restrictions on publication date. Ultimately, we analyzed 16 randomized controlled trials involving 13,685 participants. The primary outcome assessed was the effect of AI-assisted colonoscopy (AIAC) on the adenoma detection rate (ADR). Secondary outcomes included the polyp detection rate (PDR) and adenomas per colonoscopy (APC). A random-effects model was used to calculate pooled effect sizes, and statistical heterogeneity was evaluated using the Higgins I 2 statistic, with I 2 cutoff points of 25%, 50%, and 75% indicating low, moderate, and high heterogeneity, respectively. Publication bias was investigated using a funnel plot, and the quality of evidence was appraised using the Grading of Recommendations, Assessment, Development, and Evaluation framework. The findings indicated a 26% greater ADR with AIAC than with standard colonoscopy (40.4% vs. 31.9%). Additionally, AIAC was associated with a 30% greater PDR (52.9% vs.40.1%) and a 44% higher APC. The findings demonstrate that the integration of AI in colonoscopy improves ADR, PDR, and APC, potentially reducing the incidence of interval colorectal cancer.

Shiga toxin-producing Escherichia coli is the most prevalent bacterial strain responsible for Shiga toxin-related infections. While Shiga toxin is inherently toxic, it has potential therapeutic applications as a component of anticancer drugs. Despite its association with infections and harmful effects on human health, Shiga toxin is being explored as a viable element in drug delivery systems targeting cancer cells. The findings indicate that the production of mutated bacteria containing Shiga toxin is an effective preventive strategy for immunization against these toxins. Furthermore, the B subunit of Shiga toxin shows promise for imaging cancer cells, opening new paths for therapeutic interventions.

Background: Ellipticine (Ellip.) was recently reported to have beneficial effects on the differentiation of adipose-derived stem cells into mature chondrocyte-like cells. On the other hand, no practical results have been derived from the transplantation of bone marrow stem cells (BMSCs) in a rabbit osteoarthritis (OA) model. Objectives: This study examined whether autologous BMSCs incubated with ellipticine (Ellip.+BMSCs) could regenerate articular cartilage in rabbit OA, a model similar to degenerative arthritis in human beings. Methods: A portion of rabbit articular cartilage was surgically removed, and Ellip.+BMSCs were transplanted into the lesion area. After two and four weeks of treatment, the serum levels of proinflammatory cytokines, i.e., tumor necrosis factor α (TNF-α) and prostaglandin E2 (PGE2), were analyzed, while macroscopic and micro-computed tomography (CT) evaluations were conducted to determine the intensity of cartilage degeneration.Furthermore, immuno-blotting was performed to evaluate the mitogen-activated protein kinases, PI3K/Akt, and nuclear factor-κB (NF-κB) signaling in rabbit OA models. Histological staining was used to confirm the change in the pattern of collagen and proteoglycan in the articular cartilage matrix. Results: The transplantation of Ellip.+BMSCs elicited a chondroprotective effect by reducing the inflammatory factors (TNF-α, PGE2) in a time-dependent manner. Macroscopic observations, micro-CT, and histological staining revealed articular cartilage regeneration with the downregulation of matrix-metallo proteinases (MMPs), preventing articular cartilage degradation. Furthermore, histological observations confirmed a significant boost in the production of chondrocytes, collagen, and proteoglycan compared to the control group. Western blotting data revealed the downregulation of the p38, PI3K-Akt, and NF-κB inflammatory pathways to attenuate inflammation. Conclusions The transplantation of Ellip.+BMSCs normalized the OA condition by boosting the recovery of degenerated articular cartilage and inhibiting the catabolic signaling pathway.

Background: Coronavirus disease 2019 (COVID-19) has emerged as a pandemic for more than 2 years. Autopsy examination is an invaluable tool to understand the pathogenesis of emerging infections and their consequent mortalities. The aim of the current study was to present the lung and heart pathological findings of COVID-19–positive autopsies performed in Jordan. Methods: The study involved medicolegal cases, where the cause of death was unclear and autopsy examination was mandated by law. We included the clinical and pathologic findings of routine gross and microscopic examination of cases that were positive for COVID-19 at time of death. Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was confirmed through molecular detection by real-time polymerase chain reaction, serologic testing for IgM and electron microscope examination of lung samples. Results: Seventeen autopsies were included, with male predominance (76.5%), Jordanians (70.6%), and 50 years as the mean age at time of death. Nine out of 16 cases (56.3%) had co-morbidities, with one case lacking such data. Histologic examination of lung tissue revealed diffuse alveolar damage in 13/17 cases (76.5%), and pulmonary microthrombi in 8/17 cases (47.1%). Microscopic cardiac findings were scarcely detected. Two patients died as a direct result of acute cardiac disease with limited pulmonary findings. Conclusions The detection of SARS-CoV-2 in postmortem examination can be an incidental or contributory finding which highlights the value of autopsy examination to determine the exact cause of death in controversial cases.