Autoantibodies, antigen-autoantibody complexes and antigens complement CA125 for early detection of ovarian cancer.

BACKGROUND: Multiple antigens, autoantibodies (AAb), and antigen-autoantibody (Ag-AAb) complexes were compared for their ability to complement CA125 for early detection of ovarian cancer. METHODS: Twenty six biomarkers were measured in a single panel of sera from women with early stage (I-II) ovarian cancers (n = 64), late stage (III-IV) ovarian cancers (186), benign pelvic masses (200) and from healthy controls (502), and then split randomly (50:50) into a training set to identify the most promising classifier and a validation set to compare its performance to CA125 alone. RESULTS: Eight biomarkers detected ≥ 8% of early stage cases at 98% specificity. A four-biomarker panel including CA125, HE4, HE4 Ag-AAb and osteopontin detected 75% of early stage cancers in the validation set from among healthy controls compared to 62% with CA125 alone (p = 0.003) at 98% specificity. The same panel increased sensitivity for distinguishing early-stage ovarian cancers from benign pelvic masses by 25% (p = 0.0004) at 95% specificity. From 21 autoantibody candidates, 3 AAb (anti-p53, anti-CTAG1 and annt-Il-8) detected 22% of early stage ovarian cancers, potentially lengthening lead time prior to diagnosis. CONCLUSION: A four biomarker panel achieved greater sensitivity at the same specificity for early detection of ovarian cancer than CA125 alone.

Screening and staging of chronic obstructive pulmonary disease with deep learning based on chest X-ray images and clinical parameters.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed with the current gold standard measure pulmonary function test (PFT). A more sensitive and simple option for early detection and severity evaluation of COPD could benefit practitioners and patients. METHODS: In this multicenter retrospective study, frontal chest X-ray (CXR) images and related clinical information of 1055 participants were collected and processed. Different deep learning algorithms and transfer learning models were trained to classify COPD based on clinical data and CXR images from 666 subjects, and validated in internal test set based on 284 participants. External test including 105 participants was also performed to verify the generalization ability of the learning algorithms in diagnosing COPD. Meanwhile, the model was further used to evaluate disease severity of COPD by predicting different grads. RESULTS: The Ensemble model showed an AUC of 0.969 in distinguishing COPD by simultaneously extracting fusion features of clinical parameters and CXR images in internal test, better than models that used clinical parameters (AUC = 0.963) or images (AUC = 0.946) only. For the external test set, the AUC slightly declined to 0.934 in predicting COPD based on clinical parameters and CXR images. When applying the Ensemble model to determine disease severity of COPD, the AUC reached 0.894 for three-classification and 0.852 for five-classification respectively. CONCLUSION: The present study used DL algorithms to screen COPD and predict disease severity based on CXR imaging and clinical parameters. The models showed good performance and the approach might be an effective case-finding tool with low radiation dose for COPD diagnosis and staging.

Role cognition of assigned nurses supporting Hubei Province in the fight against COVID-19 in China: a hermeneutic phenomenological study.

Aims: During the COVID-19 epidemic, nurses played a crucial role in clinical treatment. As a special group, front-line nurses, especially those assigned to support Hubei Province in the fight against COVID-19 between February and April 2020, brought diverse experiences from different provinces in China in taking care of COVID-19 patients and role cognition. Therefore, our purpose is to explore the real coping experience and role cognition of front-line nurses during the novel coronavirus outbreak to provide relevant experience references for society and managers in the face of such major public health emergencies in the future. Design: This qualitative study was performed using the phenomenological hermeneutics method. Method: This is a qualitative phenomenological study. Semi-structured in-depth interviews were used to collect data. The interviewees were 53 front-line nurses who assisted and supported the fight against COVID-19 in Hubei Province during the COVID-19 epidemic. Data were collected through individual online and telephone interviews using a semi-structured interview during March 2020. The COREQ guidance was used to report this study. Results: The findings revealed that front-line nurses assisting in the fight against COVID-19 developed a context-specific role cognition of their work and contribution to society. The qualitative analysis of the data revealed 15 sub-categories and 5 main categories. These five themes represented the different roles identified by nurses. The roles included expectations, conflicts, adaptation, emotions, and flow of blessing. Belief in getting better, a sense of honor, and training could help them to reduce feelings of conflict in this role and adapt more quickly. Discussion: This article discusses the real coping experience and role cognition of front-line nurses during the novel coronavirus epidemic. It provides relevant experience references for society and managers to face similar major public health emergencies in the future. This study makes a significant contribution to the literature because it demonstrates how non-local nurses sent to Hubei to work perceived their roles as part of a larger narrative of patriotism, duty, solidarity, and hope.

The Impact of Frailty on Chemotherapy Outcomes in Patients With Digestive System Tumors: A Systematic Review and Meta-analysis.

BACKGROUND: The prevalence of patients with digestive system tumors has been high. In recent years, frailty has been considered to be associated with poor prognosis of digestive system tumors, but there are conflicting research results. A better understanding of the relationship between frailty and outcomes after chemotherapy can help advance the development of oncology care. OBJECTIVE: The aim of this study was to evaluate the effects of prechemotherapy frailty on chemotherapy toxicity, overall mortality, unplanned hospitalization, and overall survival in patients with digestive system tumors. METHODS: Up to April 2023, observational studies assessing the impact of frailty on chemotherapy outcomes in patients with digestive system tumors were collected through searching 10 online research databases. Two evaluators independently extracted literature based on the inclusion and exclusion criteria and evaluated the quality of the studies using the Newcastle-Ottawa Scale. RESULTS: Eventually, 11 cohort studies encompassing 2380 patients were included. The meta-analysis revealed that the frail group exhibited an increased risk of overall mortality, with poorer overall survival than the nonfrail group. CONCLUSION: Frailty increases the risk of chemotherapy-induced toxic effects, unplanned hospitalization, and death in patients. However, because of this study's limited number of participants, large-sample, multicenter studies to verify these findings are required. IMPLICATIONS FOR PRACTICE: This study provides theoretical support for incorporating frailty assessment into the nursing evaluation of patients with digestive system tumors before chemotherapy. This integration aids in predicting patients at a high risk of chemotherapy toxicity, mortality, and unplanned hospitalization, therefore providing corresponding interventions in advance to reduce adverse outcomes.

DIRAS3 induces autophagy and enhances sensitivity to anti-autophagic therapy in KRAS-driven pancreatic and ovarian carcinomas.

Pancreatic ductal adenocarcinoma (PDAC) and low-grade ovarian cancer (LGSOC) are characterized by the prevalence of KRAS oncogene mutations. DIRAS3 is the first endogenous non-RAS protein that heterodimerizes with RAS, disrupts RAS clustering, blocks RAS signaling, and inhibits cancer cell growth. Here, we found that DIRAS3-mediated KRAS inhibition induces ROS-mediated apoptosis in PDAC and LGSOC cells with KRAS mutations, but not in cells with wild-type KRAS, by downregulating NFE2L2/Nrf2 transcription, reducing antioxidants, and inducing oxidative stress. DIRAS3 also induces cytoprotective macroautophagy/autophagy that may protect mutant KRAS cancer cells from oxidative stress, by inhibiting mutant KRAS, activating the STK11/LKB1-PRKAA/AMPK pathway, increasing lysosomal CDKN1B/p27 localization, and inducing autophagic gene expression. Treatment with chloroquine or the novel dimeric chloroquine analog DC661 significantly enhances DIRAS3-mediated inhibition of mutant KRAS tumor cell growth in vitro and in vivo. Taken together, our study demonstrates that DIRAS3 plays a critical role in regulating mutant KRAS-driven oncogenesis in PDAC and LGSOC.Abbreviations: AFR: autophagic flux reporter; ATG: autophagy related; CQ: chloroquine; DCFDA: 2'-7'-dichlorodihydrofluorescein diacetate; DIRAS3: DIRAS family GTPase 3; DOX: doxycycline; KRAS: KRAS proto-oncogene, LGSOC: low-grade serous ovarian cancer; MiT/TFE: microphthalmia family of transcription factors; NAC: N-acetylcysteine; PDAC: pancreatic ductal adenocarcinoma; ROS: reactive oxygen species; TFEB: transcription factor EB.

Crizotinib enhances PARP inhibitor efficacy in ovarian cancer cells and xenograft models by inducing autophagy.

Poly (ADP-ribose) polymerase inhibitors (PARPi) can encounter resistance through various mechanisms, limiting their effectiveness. Our recent research showed that PARPi alone can induce drug resistance by promoting autophagy. Moreover, our studies have revealed that anaplastic lymphoma kinase (ALK) plays a role in regulating the survival of ovarian cancer cells undergoing autophagy. Here, we explored whether the ALK-inhibitor crizotinib could enhance the efficacy of PARPi by targeting drug-induced autophagic ovarian cancer cell and xenograft models. Our investigation demonstrates that crizotinib enhances the anti-tumor activity of PARPi across multiple ovarian cancer cells. Combination therapy with crizotinib and olaparib reduced cell viability and clonogenic growth in two-olaparib resistant cell lines. More importantly, this effect was consistently observed in patient-derived organoids. Furthermore, combined treatment with crizotinib and olaparib led to tumor regression in human ovarian xenograft models. Mechanistically, the combination resulted in increased levels of reactive oxygen species (ROS), induced DNA damage, and decreased the phosphorylation of AKT, mTOR, and ULK-1, contributing to increased olaparib-induced autophagy and apoptosis. Notably, pharmacologic, or genetic inhibition or autophagy reduced the sensitivity of ovarian cancer cell lines to olaparib and crizotinib treatment, underscoring the role of autophagy in cell death. Blocking ROS mitigated olaparib/crizotinib-induced autophagy and cell death while restoring levels of phosphorylated AKT, mTOR and ULK-1. These findings suggest that crizotinib can improve the therapeutic efficacy of olaparib by enhancing autophagy. Implications: The combination of crizotinib and PARPi presents a promising strategy, that could provide a novel approach to enhance outcomes for patients with ovarian cancer.

Identification of the body fluid donor in mixtures through target mRNA cSNP sequencing.

In forensic practice, mixture stains containing various body fluids are common, presenting challenges for interpretation, particularly in multi-contributor mixtures. Traditional STR profiles face difficulties in such scenarios. Over recent years, RNA has emerged as a promising biomarker for body fluid identification, and mRNA polymorphism has shown excellent performance in identifying body fluid donors in previous studies. In this study, a massively parallel sequencing assay was developed, encompassing 202 coding region SNPs (cSNPs) from 45 body fluid/tissue-specific genes to identify both body fluid/tissue origin and the respective donors, including blood, saliva, semen, vaginal secretion, menstrual blood, and skin. The specificity was evaluated by examining the single-source body fluids/tissue and revealed that the same body fluid exhibited similar expression profiles and the tissue origin could be identified. For laboratory-generated mixtures containing 2-6 different components and mock case mixtures, the donor of each component could be successfully identified, except for the skin donor. The discriminatory power for all body fluids ranged from 0.997176329 (menstrual blood) to 0.99999999827 (blood). The concordance of DNA typing and mRNA typing for the cSNPs in this system was also validated. This cSNP typing system exhibits excellent performance in mixture deconvolution.

Blood urea nitrogen to serum albumin ratio independently predicts 30-day mortality and severity in patients with Escherichia coli bacteraemia

Background: Elevated blood urea nitrogen to serum albumin (BUN/ALB) ratio had been identified as an independent risk factor related to mortality in community-acquired and hospital-acquired pneumonia. This study aimed to investigate whether this clinical index can predict the clinical outcomes of E. coli bacteraemia.Material and methodsClinical data were collected from patients with E. coli bacteraemia attended at our hospital between January 2012 and December 2018. The endpoints were mortality within 30 days after the diagnosis of E. coli bacteraemia and intensive care (IC) requirement. Cox regression analysis was performed to evaluate the risk factors.ResultsA total of 398 patients with E. coli bacteraemia were enrolled in this study and 56 patients died within 30 days after bacteraemia onset. Multivariate Cox regression analysis showed that age greater than 65 years, lymphocyte count<.8×10e9/L, elevated BUN/ALB ratio, increased SOFA score, carbapenem resistance, central venous catheterization before onset of bacteraemia, and infection originating from abdominal cavity were independent risk factors for 30-day mortality (P<.05). The risk factors associated with IC requirement were similar to those for 30-day mortality except central venous catheterization before onset of bacteraemia. The area under the receiver-operating characteristic curve for BUN/ALB ratio predicting 30-day mortality and IC requirement was similar to that for SOFA score, but higher than that for lymphocyte count. The cut-off points of BUN/ALB ratio to predict 30-day mortality and IC requirement were both .3.ConclusionsBUN/ALB ratio is a simple but independent predictor of 30-day mortality and severity in E. coli bacteraemia. A higher BUN/ALB ratio at the onset of bacteraemia predicts a higher mortality rate and IC requirement. (AU)

Antecedentes: Se ha identificado la elevación de la proporción de nitrógeno ureico en sangre con respecto a albúmina sérica (NUS/ALB) como un factor de riesgo independiente asociado a la mortalidad de la neumonía adquirida en la comunidad y la neumonía intrahospitalaria. El objetivo de este estudio fue investigar si este índice clínico puede predecir los resultados clínicos de bacteremia por E. coli.Material y métodosSe recopilaron los datos clínicos de los pacientes con bacteremia por E. coli atendidos en nuestro hospital entre enero de 2012 y diciembre de 2018. Las variables de evaluación fueron la mortalidad a 30 días tras el diagnóstico de bacteremia por E. coli y la necesidad de cuidados intensivos (CI). Se realizó un análisis de regresión de Cox para evaluar los factores de riesgo.ResultadosSe incluyó en el estudio a un total de 398 pacientes con bacteremia por E. coli, falleciendo 56 pacientes en el plazo de 30 días tras el inicio de la bacteremia. El análisis de regresión de Cox multivariante reflejó que la edad superior a 65 años, el recuento linfocitario <0,8×109/l, la elevación del ratio NUS/ALB, el incremento de la puntuación SOFA, la resistencia al carbapenem, la cateterización venosa central anterior al inicio de la bacteremia y la infección originada por la cavidad abdominal eran factores de riesgo independientes de la mortalidad a 30 días (p<0,05). Los factores de riesgo asociados a la necesidad de CI fueron similares a los de la mortalidad a 30 días, exceptuando la cateterización venosa central anterior al inicio de la bacteremia. El área bajo la curva característica operador-receptor para el ratio NUS/ALB que predice la mortalidad a 30 días, y la necesidad de CI fue similar a la puntuación SOFA, aunque superior a la correspondiente al recuento linfocitario. Los puntos de corte del ratio NUS/ALB para predecir la mortalidad a 30 días y la necesidad de CI se situaron en 0,3. (AU)