Lundsgaardhjelm4939

Ovarian cancer has been nicknamed the "silent killer". Most patients with ovarian cancer are diagnosed at an advanced stage of the disease for the first time because of its insignificant early clinical symptoms. In addition to the difficulty of early screening and delay in diagnosis, the high recurrence rate and relapsed refractory status of patients with ovarian cancer are also important factors for their high mortality. Patients with recurrent ovarian cancer often use neoadjuvant chemotherapy followed by surgery as the first choice. However, this is often accompanied by chemotherapy resistance, leading to treatment failure and a mortality rate of more than 90%. In the past, it was believed that the anti-tumor effect of chemotherapeutics represented by cisplatin was entirely attributable to its irreversible damage to DNA, but current research has found that it can inhibit cell growth and cytotoxicity via nuclear and cytoplasmic coordinated integration. As an important hub and integration platform for intracellular signal communication, mitochondria are responsible for multiple key factors during tumor occurrence and development, such as metabolic reprogramming, acquisition of metastatic ability, and chemotherapy drug response. The role of mitochondria in ovarian cancer chemotherapy resistance is becoming increasingly recognized. In this review, we discuss the cellular interactive regulatory network surrounding mitochondria, elucidate the mechanisms of tumor cell survival under chemotherapy, and discuss potential means of interfering with mitochondrial function as a novel anti-cancer therapy.

The purpose of this study was to evaluate temporal trends in the frequency of revascularization and associated outcomes in patients with diabetes mellitus and critical limb ischemia (CLI).

Little is known about outcomes following revascularization for CLI in patients with diabetes mellitus.

Temporal trends in hospitalization for CLI among patients with diabetes were determined using the 2002-2015 National Inpatient Sample database. Propensity score matching was used to compare patients who underwent revascularization with those who did not and, separately, to compare those who underwent endovascular versus surgical revascularization. The main study outcome was in-hospital mortality.

The analysis included 1,222,324 hospitalizations. The number of hospitalizations for CLI among patients with diabetes increased over time (p

< 0.001). There was an increase in the use of lower extremity revascularization, paralleled by a decline in in-hospital mortality during the study period. In the matched cohort, pmpared with surgical revascularization, endovascular revascularization was associated with lower in-hospital mortality but higher rates of major amputation.

In this national analysis of patients with DM and CLI, we demonstrated an increase in hospitalization for CLI among patients with diabetes in the United States. Although in-hospital mortality decreased over time regardless of the treatment strategy used, this outcome occurred less frequently among those who underwent revascularization than not. Compared with surgical revascularization, endovascular revascularization was associated with lower in-hospital mortality but higher rates of major amputation.

The authors sought to determine whether coronary artery tortuosity negatively affects clinical outcomes after stent implantation.

Coronary artery tortuosity is a common angiographic finding and has been associated with increased rates of early and late major adverse events after balloon angioplasty.

Individual patient data from 6 prospective, randomized stent trials were pooled. Outcomes at 30days and 5 years following percutaneous coronary intervention of a single coronary lesion were analyzed according to the presence or absence of moderate/severe vessel tortuosity, as determined by an angiographic core laboratory. The primary endpoint was target vessel failure (TVF) (composite of cardiac death, target vessel-related myocardial infarction [TV-MI], or ischemia-driven target vessel revascularization [ID-TVR]).

A total of 6,951 patients were included, 729 of whom (10.5%) underwent percutaneous coronary intervention in vessels with moderate/severe tortuosity. check details At 30days, TVF was more frequent in patients with versus without moderate/severe tortuosity (3.8% vs. 2.4%; hazard ratio [HR] 1.64; 95% confidence interval [CI] 1.09 to 2.46; p=0.02), a difference driven by a higher rate of TV-MI. At 5 years, TVF remained increased in patients with moderate/severe tortuosity (p=0.003), driven by higher rates of TV-MI (p=0.003) and ID-TVR (p=0.01). Definite stent thrombosis was also greater in patients with versus without moderate/severe tortuosity (1.9% vs. 1.0%; HR 1.86; 95% CI 1.02 to 3.39; p=0.04). After adjustment for baseline covariates, moderate/severe vessel tortuosity was independently associated with TV-MI and ID-TVR at 5 years (p=0.04 for both).

Stent implantation in vessels with moderate/severe coronary artery tortuosity is associated with increased rates of TVF due to greater rates of TV-MI and ID-TVR.

Stent implantation in vessels with moderate/severe coronary artery tortuosity is associated with increased rates of TVF due to greater rates of TV-MI and ID-TVR.An improved understanding of stem cell niches, organogenesis, and disease models has paved the way for developing a three-dimensional (3D) organoid culture system. Organoid cultures can be derived from primary tissues (single cells or tissue subunits), adult stem cells (ASCs), induced pluripotent stem cells (iPSCs), or embryonic stem cells (ESCs). As a significant technological breakthrough, 3D organoid models offer a promising approach for understanding the complexities of human diseases ranging from the mechanistic investigation of disease pathogenesis to therapy. Here, we discuss the recent applications, advantages, and limitations of organoids as in vitro models for studying metabolomics, drug development, infectious diseases, and the gut microbiome. We further discuss the use of organoids in cancer modeling using high throughput sequencing approaches.