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CT-derived measurements of the pectoralis muscle can be useful in predicting disease severity and mortality rate of COVID-19 pneumonia in adult patients.

CT-derived measurements of the pectoralis muscle can be useful in predicting disease severity and mortality rate of COVID-19 pneumonia in adult patients.

Physiological measurements from coronary angiography show that coronary stenosis with necrotic core plaque reduces coronary flow reserve (CFR). Myocardial flow reserve (MFR) estimated by

N-ammonia PET (NH

-PET) is a different index from CFR. Low attenuation plaque (LAP) on coronary CTA (CCTA) contains necrotic core, but the link between LAP and MFR has not been elucidated. We aimed to investigate the influence of LAP on MFR in coronary artery disease (CAD).

The study included 105 consecutive patients who underwent NH

-PET and CCTA within 3 months. buy Mycro 3 Nonevaluable coronary arteries due to severe calcification and stent implants were excluded. Finally, 290 major vessels were retrospectively analyzed. Coronary arteries were divided into mild (1%-49%), moderate (50%-69% stenosis), and severe (≥70% stenosis) groups. Coronary plaques were classified either LAP (including soft tissue CT value <30 HU) or completely classified plaques. MFR for the major vessels were calculated and MFR <2.0 was considered a significant decrease. Comparison of MFR between territories with and without LAP, and the effect of plaque characteristics on MFR was analyzed.

MFR was significantly lower for territories with LAP than with calcified plaques or no plaque (2.1 ± 0.7, 2.4 ± 0.7, and 2.3 ± 0.7; p < 0.05). There was no difference between calcified plaque and no plaque territories (p = 0.79). Multivariate logistic analysis for plaque characteristics and stenosis severity revealed that LAP and severe stenosis were independent predictors for territories with MFR <2.0 with odds ratios of 3.1 (95% confidence interval, 1.2-8.1) and 3.0 (95% confidence interval, 1.7-5.3).

LAP reduced MFR compared with calcified plaque or no plaque in CAD. LAP is an independent predictor of the territory with MFR <2.0.

LAP reduced MFR compared with calcified plaque or no plaque in CAD. LAP is an independent predictor of the territory with MFR less then 2.0.

To investigate the association between rapid access to radiographs, blood tests, urine cultures, and intravenous (IV) therapy in a long-term care (LTC) home with resident transfers to the emergency department (ED).

Retrospective cohort study.

21,811 residents living in 162 LTC homes in Ontario, Canada.

We administered a survey to LTC homes to collect wait times for radiographs, basic blood tests, urine culture, and IV therapy. Rapid availability was defined as typically receiving test results within 1 or 2days, or same-day IV therapy. We linked the survey results to administrative data and defined a cohort of residents living in survey-respondent homes between January and May 2017. We followed residents in the linked administrative databases for 6months, until discharge, or death. Two physicians identified diagnostic codes for ED visits that were potentially preventable with rapid availability of each of the 4 resources. Multilevel logistic regression models estimated associations between potentially to these resources may prevent ED visits and allow residents to stay home.

Breast cancer (BC) is the most common cancer in women, with a high disease burden, especially in the advanced disease stages. Our study investigated the metabolomic profile of breast cancer patients' serum with the aim of identifying novel diagnostic biomarkers that could be used, especially for early disease detection.

Using targeted metabolomic serum profiling based on high-performance liquid chromatography mass spectrometry, women with BC (n = 39) and a control group (n = 21) were examined for 232 endogenous metabolites.

The top performing biomarkers included acylcarnitines (ACs) and 9,12-linoleic acid. A combined panel of the top 4 biomarkers achieved 83% sensitivity and 81% specificity, with an area under the curve (AUC) of 0.839 (95% confidence interval, 0.811-0.867). Individual markers also provided significant predictive values AC 120, sensitivity of 72%, specificity of 67%, and AUC of 0.71; AC 142, sensitivity of 74%, specificity of 71%, and AUC of 0.73; AC 140 sensitivity of 67%, specificity of 81%, and AUC of 0.73; and 9,12-linoleic acid, sensitivity of 69%, specificity of 67%, and AUC of 0.71. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination.

Using mass spectrometry-targeted metabolomic profiling, ACs and 9,12-linoleic acid were identified as potential diagnostic biomarkers for breast cancer. Additionally, these identified metabolites could provide additional insight into cancer cell metabolism.

Using mass spectrometry-targeted metabolomic profiling, ACs and 9,12-linoleic acid were identified as potential diagnostic biomarkers for breast cancer. Additionally, these identified metabolites could provide additional insight into cancer cell metabolism.

The estrogen receptor-1 (ESR1) gene encodes estrogen receptor-α, which is a major biomarker in the development of breast cancer. This study aimed to investigate the effect of ESR1 polymorphisms on breast cancer in Chinese Han women.

We genotyped 4 candidate single nucleotide polymorphisms (SNPs) in ESR1 among 503 patients with breast cancer and 503 healthy people using the Agena MassARRAY platform. The association between ESR1 polymorphisms and breast cancer risk was evaluated using odds ratios (ORs) and 95% confidence intervals (95% CIs) under 4 genetic models. The HaploReg v4.1 and GEPIA database were used for SNP functional annotation and ESR1 expression analysis, respectively.

The T allele of rs9383938 in ESR1 was significantly associated with an increased breast cancer risk (OR, 1.26; 95% CI, 1.05-1.50; P= .013). In genetic models, rs9383938 increased breast cancer risk in the codominant model (OR, 1.54; 95% CI, 1.07-2.22; P= .021), the dominant model (OR, 1.31; 95% CI, 1.01-1.68; P= .040), and the additive model (OR, 1.