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The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a public health emergency of international concern. The current study aims to explore whether the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are associated with the development of death in patients with COVID-19. A total of 131 patients diagnosed with COVID-19 from 13 February 2020 to 14 March 2020 in a hospital in Wuhan designated for treating COVID-19 were enrolled in the current study. These 131 patients had a median age of 64 years old (interquartile range: 56–71 years old). Furthermore, among these patients, 111 (91.8%) patients were discharged and 12 (9.2%) patients died in the hospital. The pooled analysis revealed that the NLR at admission was significantly elevated for non-survivors, when compared to survivors (P < 0.001). The NLR of 3.338 was associated with all-cause mortality, with a sensitivity of 100.0% and a specificity of 84.0% (area under the curve (AUC): 0.963, 95% confidence interval (CI) 0.911–1.000; P < 0.001). In view of the small number of deaths (n = 12) in the current study, NLR of 2.306 might have potential value for helping clinicians to identify patients with severe COVID-19, with a sensitivity of 100.0% and a specificity of 56.7% (AUC: 0.729, 95% CI 0.563–0.892; P = 0.063). The NLR was significantly associated with the development of death in patients with COVID-19. Hence, NLR is a useful biomarker to predict the all-cause mortality of COVID-19.
This study identified possible risk factors for newly diagnosed mood disorders, including depressive and bipolar disorders, in prostate cancer patients.
Methods:
From 2000 to 2006, two cohorts were evaluated on the occurrence of mood disorder diagnosis and treatment. For the first cohort, data of patients diagnosed with prostate cancer was obtained from the Taiwan National Health Insurance (NHI) Research Database. As the second cohort, a cancer-free comparison group was matched for age, comorbidities, geographic region, and socioeconomic status.
Results:
Final analyses involved 12,872 men with prostate cancer and 12,872 matched patients. Increased incidence of both depressive (IRR 1.52, 95% CI 1.30–1.79, P <0.001) and bipolar disorder (IRR 1.84, 95% CI 1.25–2.74, P = 0.001) was observed among patients diagnosed with prostate cancer. Multivariate matched regression models show that cerebrovascular disease (CVD) and radiotherapy treatment could be independent risk factors for developing subsequent depressive and bipolar disorders.
Conclusion:
We observed that the risk of developing newly diagnosed depressive and bipolar disorders is higher among Taiwanese prostate cancer patients. Clinicians should be aware of the possibility of increased depressive and bipolar disorders among prostate cancer patients in Taiwan. A prospective study is necessary to confirm these findings.
Early identification of patients with bipolar disorder during their first depressive episode is beneficial to the outcome of the disorder and treatment, but traditionally this has been a great challenge to clinicians. Recently, brain-derived neurotrophic factor (BDNF) has been suggested to be involved in the pathophysiology of bipolar disorder and major depressive disorder (MDD), but it is not clear whether BDNF levels can be used to predict bipolar disorder among patients in their first major depressive episode.
Aims
To explore whether BDNF levels can differentiate between MDD and bipolar disorder in the first depressive episode.
Method
A total of 203 patients with a first major depressive episode as well as 167 healthy controls were recruited. After 3 years of bi-annual follow-up, 164 patients with a major depressive episode completed the study, and of these, 21 were identified as having bipolar disorder and 143 patients were diagnosed as having MDD. BDNF gene expression and plasma levels at baseline were compared among the bipolar disorder, MDD and healthy control groups. Logistic regression and decision tree methods were applied to determine the best model for predicting bipolar disorder at the first depressive episode.
Results
At baseline, patients in the bipolar disorder and MDD groups showed lower BDNF mRNA levels (P<0.001 and P = 0.02 respectively) and plasma levels (P = 0.002 and P = 0.01 respectively) compared with healthy controls. Similarly, BDNF levels in the bipolar disorder group were lower than those in the MDD group. These results showed that the best model for predicting bipolar disorder during a first depressive episode was a combination of BDNF mRNA levels with plasma BDNF levels (receiver operating characteristics (ROC) = 0.80, logistic regression; ROC = 0.84, decision tree).
Conclusions
Our findings suggest that BDNF levels may serve as a potential differential diagnostic biomarker for bipolar disorder in a patient's first depressive episode.
Based on quantitative trait locus (QTL) mapping, the gene for porcine uncoupling protein 3 (UCP3) was chosen as a candidate gene for pig fat deposition and meat quality traits. In this study, a partial coding region of the UCP3 gene was sequenced and one single nucleotide polymorphism (cSNP) was found at 395 bp. The mutation was G→A and resulted in the amino acid change from glycine to arginine. This site was also recognized by restriction endonuclease SmaI. The UCP3 SmaI polymorphism was analysed among 186 individuals of Large White×Meishan F2 progeny using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP). The genotypes of the UCP3 SmaI polymorphism were AA, AB and BB. The frequency of A and B alleles was respectively 0.56 and 0.44. Statistical analyses showed that the SmaI polymorphism in the F2 population was significantly associated with back-fat thickness at thorax–waist and buttock, as well as with intramuscular fat, drip-loss rate and water-holding capacity. The additive effect of UCP3 SmaI was clearly shown. The genotype AA reduced back-fat thickness and drip-loss rate, increased water-holding capacity, and decreased the intramuscular fat. The effect of the pig UCP3 SmaI polymorphism needs to be analysed in other populations using larger samples.
Pure vapor-grown carbon nanofibers (VGCNF's) with controllable diameters of 10–200 nm were prepared by an improved floating catalyst method. Through transmission electron microscopy (TEM) observation, it was found that VGCNF's have a duplex structure, a hollow and high-crystallinity graphite filament called primary carbon fiber surrounded by a pyrocarbon layer with low graphite crystallinity. It was observed using high-resolution TEM that VGCNF's have excellent graphitic crystallinity with graphite layers stacked neatly parallel to fiber axis. Moreover, x-ray diffraction results showed that the graphitic crystallinity of carbon fibers became higher with decreasing diameter of carbon fibers.
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