a severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection, and real-time reverse transcription-PCR is currently the most reliable diagnostic method for COVID-19 around the world. Korean Society for Laboratory Medicine and the Korea Centers for Disease Prevention and Control propose guidelines for diagnosing COVID-19 in clinical laboratories in Korea. These guidelines are based on other related domestic and international guidelines, as well as expert opinions and include the selection of test subjects, selection of specimens, diagnostic methods, interpretation of test results, and biosafety.

The triglyceride glucose (TyG) index, a product of triglyceride and fasting glucose, is a reliable marker for insulin resistance (IR). Obesity is also known to be closely related with IR. Recently, the efficiency of TyG-related markers that combine obesity markers with TyG index has been studied; however, earlier studies were limited in number and the results were inconsistent. Therefore, in this study, we investigated the efficiency of several combinations of TyG index and obesity indices, namely, body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR), in reflecting IR. Data were obtained from the Korean National Health and Nutrition Examination Survey from 2007–2010. A total of 11,149 subjects (4,777 men and 6,372 women) were included. IR was defined as the homeostasis model assessment for IR (HOMA-IR) of above the 75 th percentile for each gender. Logistic regression analysis was performed after adjusting for confounding factors, to compare and identify the associations of the 4 parameters (TyG index, TyG-BMI, TyG-WC, and TyG-WHtR) with IR. For each parameter, odds ratios (OR) and 95% confidence intervals (CIs) of quartiles 2–4 were calculated and compared with quartile 1 as a reference. A receiver operating characteristic (ROC) curve analysis was conducted to evaluate the ability of each parameter to predict IR. The adjusted ORs of quartile 4 in comparison with quartile 1 (95% CIs) for IR were 7.60 (6.52–8.87) for TyG index, 12.82 (10.89–15.10) for TyG-BMI, 16.29 (13.70–19.38) for TyG-WC, and 14.86 (12.53–17.62) for TyG-WHtR. The areas under the ROC curve for each parameter were 0.690 for TyG index, 0.748 for TyG-BMI, 0.731 for TyG-WC, and 0.733 for TyG-WHtR. In conclusion, TyG-BMI was found to be superior to other parameters for IR prediction. We propose TyG-BMI as an alternative marker for assessing IR in clinical settings.

Electrocorticogram (ECoG) recordings, taken from electrodes placed on the surface of the cortex, have been successfully implemented for control of brain machine interfaces (BMIs). Optogenetics, direct optical stimulation of neurons in brain tissue genetically modified to express channelrhodopsin-2 (ChR2), enables targeting of specific types of neurons with sub-millisecond temporal precision. In this work, we developed a BMI device, called an Opto- μECoG array, which combines ECoG recording and optogenetics-based stimulation to enable multichannel, bi-directional interactions with neurons. The Opto- μECoG array comprises two sub-arrays, each containing a 4 × 4 distribution of micro-epidural transparent electrodes ( ∼ 200 μm diameter) and embedded light-emitting diodes (LEDs) for optical neural stimulation on a 2.5 × 2.5 mm² footprint to match the bilateral hemispherical area of the visual cortex in a rat. The transparent electrodes were fabricated with indium tin oxide (ITO). Parylene-C served as the main structural and packaging material for flexibility and biocompatibility. Optical, electrical, and thermal characteristics of the fabricated device were investigated and in vivo experiments were performed to evaluate the efficacy of the device.

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BackgroundThe underlying genetic alterations for squamous cell carcinoma (SCC) and adenocarcinoma (AC) carcinogenesis are largely unknown.MethodsHigh-resolution array- CGH was performed to identify the differences in the patterns of genomic imbalances between SCC and AC of non-small cell lung cancer (NSCLC).ResultsOn a genome-wide profile, SCCs showed higher frequency of gains than ACs (p = 0.067). More specifically, statistically significant differences were observed across the histologic subtypes for gains at 2q14.2, 3q26.2–q29, 12p13.2–p13.33, and 19p13.3, as well as losses at 3p26.2–p26.3, 16p13.11, and 17p11.2 in SCC, and gains at 7q22.1 and losses at 15q22.2–q25.2 occurred in AC (P < 0.05). The most striking difference between SCC and AC was gains at the 3q26.2–q29, occurring in 86% (19/22) of SCCs, but in only 21% (3/14) of ACs. Many significant genes at the 3q26.2–q29 regions previously linked to a specific histology, such as EVI1,MDS1, PIK3CA and TP73L, were observed in SCC (P < 0.05). In addition, we identified the following possible target genes (> 30% of patients) at 3q26.2–q29: LOC389174 (3q26.2),KCNMB3 (3q26.32),EPHB3 (3q27.1), MASP1 and SST (3q27.3), LPP and FGF12 (3q28), and OPA1,KIAA022,LOC220729, LOC440996,LOC440997, and LOC440998 (3q29), all of which were significantly targeted in SCC (P < 0.05). Among these same genes, high-level amplifications were detected for the gene, EPHB3, at 3q27.1, and MASP1 and SST, at 3q27.3 (18, 18, and 14%, respectively). Quantitative real time PCR demonstrated array CGH detected potential candidate genes that were over expressed in SCCs.ConclusionUsing whole-genome array CGH, we have successfully identified significant differences and unique information of chromosomal signatures prevalent between the SCC and AC subtypes of NSCLC. The newly identified candidate target genes may prove to be highly attractive candidate molecular markers for the classification of NSCLC histologic subtypes, and could potentially contribute to the pathogenesis of the squamous cell carcinoma of the lung.