Biomolecular Interaction Analysis Quantification with a Low-Volume Microfluidic Chip and Particle Diffusometry.

Microfluidic techniques are widely applied in biomolecular analysis and disease diagnostic assays. While the volume of the sample that is directly used in such assays is often only femto-to microliters, the "dead volume" of solutions supplied in syringes and tubing can be much larger, even up to milliliters, increasing overall reagent use and making analysis significantly more expensive. To reduce the difficulty and cost, we designed a new chip using a low volume solution for analysis and applied it to obtain real-time data for protein-protein interaction measurements. The chip takes advantage of air/aqueous two-phase droplet flow, on-chip rapid mixing within milliseconds, and a droplet capture method, that ultimately requires only 2 µL of reagent solution. The interaction is analyzed by particle diffusometry, a nonintrusive and precise optical detection method to analyze the properties of microparticle diffusion in solution. Herein, we demonstrate on-chip characterization of human immunodeficiency virus p24 antibody-antigen protein binding kinetics imaged via fluorescence microscopy and analyzed by PD. The measured kon and koff are 1 × 106 M-1 s-1 and 3.3 × 10-4 s-1, respectively, and agree with independent measurement via biolayer interferometry and previously calculated p24-antibody binding kinetics. This new microfluidic chip and the protein-protein interaction analysis method can also be applied in other fields that require low-volume solutions to perform accurate measurement, analysis, and detection.

Minichromosome maintenance protein 5 - a promising prognostic marker of oral epithelial dysplasias and oral squamous cell carcinomas.

Background: Early diagnosis is the single most effective means of reducing the mortality rate of oral cancer. Aim: This study was undertaken to assess the expression of minichromosome maintenance protein 5 (MCM5) in oral epithelial dysplasias and oral squamous cell carcinomas (OSCCs) and to evaluate their possible role as a biomarker for early diagnosis and prognosis of OSCC. Design: A retrospective cross-sectional study. Materials and Methods: The study was conducted to assess the expression of MCM5 immunohistochemically in the tissue samples of oral epithelial dysplasias (n = 27) and OSCCs (n = 30) diagnosed between 2014 and 2019. Statistical Analysis: The difference in the mean nuclear labelling index (LI) between the groups and the subgroups was analysed statistically using the Kruskal-Wallis test and the post hoc test, and the Dunn-Bonferroni multiple comparison analysis was conducted for pairwise comparison between the four main groups and the subgroups. The association between mean MCM5 LI and clinicopathological parameters was analysed using Spearman's rank correlation coefficient. Results: A progressive increase in the nuclear expression of MCM5 protein (P-value <0.001) was noticed from normal oral mucosa through oral epithelial hyperplasia and oral epithelial dysplasia to OSCC. A significant correlation was also observed between the mean nuclear MCM5 LI of OSCC and TNM staging (R2 = 0.268, P = 0.029). Conclusion: Our findings suggest that MCM5 may be of great value in assessing the malignant potential of dysplastic lesions and may serve as biomarker of utility in the early diagnosis and prognosis of OSCC.

Effect of Covid 19 lockdown on the lifestyle and dietary diversity of women handloom workers.

BACKGROUND: Covid-19 lockdown has influenced the lifestyle of handloom women as weaving is the only mean of earnings for them. The nutrition profile of working women is a vital part of their general health as they have more chances of dietary deficiencies; in addition they face various safety related problems at workplace. Working conditions and household responsibilities complicate role conflict leading to stress that in turn affect nutrition and health status. MATERIAL AND METHODS: Purposive sampling method was used to collect data from 100 samples of women handloom workers between the ages of 30-60 years from Kanhirode Weaver's Co-operative Society, Kannur, Kerala, India. Personal interview method was used for data collection. The interview schedule included occupational health profile, anthropometric, physical activity and food frequency assessment. Dietary diversity questionnaire was used to assess the levels and adequacy of dietary diversity. Depression Anxiety Stress Scale (DASS) was used to assess psychological well-being among the samples. RESULTS: COVID-19 lockdown downgraded the life style of majority (90.7%) of women workers. Majority of samples were with mean age 46.74 ± 5.73 years and height of 1.52 ± 0.10 m respectively. Out of 100, 63 samples noticed a weight change from which majority (71.4%) noticed an increase in their body weight. The mean weight before lockdown was 54.100 ± 7.603 Kg and after lockdown 55.020 ± 8.013 Kg. The mean BMI before lockdown was 23.232 ± 2.866 and after lockdown BMI slightly increased to 23.572 ± 2.928. Lockdown introduced a significant reduction in percentage of consumption of pulses (3.7 ± 1.2g), fish (4.1 ± 0.5g), chicken (2.0 ± 0.6g), meat (1.4 ± 0.6g) and milk products (4.6 ± 1.05 ml). Most of the subsamples were not meeting the calories (2063.3 ± 166.9 Kcal), fat (20.6 ± 4.3g) and micronutrients such as vitamin A (761.3 ± 180.3 mg), vitamin C (61.2 ± 15.9 mg) and calcium (963.3 ± 183.9 mg) requirements which indicate the incomplete dietary diversity. CONCLUSION: The nutrition profile of women handloom workers was negatively influenced by the COVID-19 pandemic.

Discriminating electrocardiographic responses to His-bundle pacing using machine learning.

BACKGROUND: His-bundle pacing (HBP) has emerged as an alternative to conventional ventricular pacing because of its ability to deliver physiological ventricular activation. Pacing at the His bundle produces different electrocardiographic (ECG) responses: selective His-bundle pacing (S-HBP), non-selective His bundle pacing (NS-HBP), and myocardium-only capture (MOC). These 3 capture types must be distinguished from each other, which can be challenging and time-consuming even for experts. OBJECTIVE: The purpose of this study was to use artificial intelligence (AI) in the form of supervised machine learning using a convolutional neural network (CNN) to automate HBP ECG interpretation. METHODS: We identified patients who had undergone HBP and extracted raw 12-lead ECG data during S-HBP, NS-HBP, and MOC. A CNN was trained, using 3-fold cross-validation, on 75% of the segmented QRS complexes labeled with their capture type. The remaining 25% was kept aside as a testing dataset. RESULTS: The CNN was trained with 1297 QRS complexes from 59 patients. Cohen kappa for the neural network's performance on the 17-patient testing set was 0.59 (95% confidence interval 0.30 to 0.88; P <.0001), with an overall accuracy of 75%. The CNN's accuracy in the 17-patient testing set was 67% for S-HBP, 71% for NS-HBP, and 84% for MOC. CONCLUSION: We demonstrated proof of concept that a neural network can be trained to automate discrimination between HBP ECG responses. When a larger dataset is trained to higher accuracy, automated AI ECG analysis could facilitate HBP implantation and follow-up and prevent complications resulting from incorrect HBP ECG analysis.

An immunohistochemical evaluation of podoplanin expression in oral leukoplakia and oral squamous cell carcinoma to explore its potential to be used as a predictor for malignant transformation.

BACKGROUND: Oral leukoplakia (OL) is a potentially malignant disorder with increased risk for the development of oral squamous cell carcinoma (OSCC). Many cases of OSCC arise from the malignant transformation of preexisting OL. However, the risk of progression into OSCC and the possible prediction of malignant potential of OL remain inconclusive. Recent studies have shown that podoplanin, a mucin-like transmembrane glycoprotein specifically expressed in lymphatic endothelial cells, is expressed in various neoplasms including OSCC, indicating its possible biologic role in tumor cells. In this study, an evaluation of podoplanin expression in OL and OSCC has been carried out to assess its potential role as a biomarker to predict the possibility of malignant transformation in OL cases. AIMS AND OBJECTIVES: To assess the usefulness of podoplanin as a potential biomarker for predicting the risk of malignant transformation in OL, by comparing its immunohistochemical expression in OL and OSCC. MATERIALS AND METHODS: Archival paraffin-embedded blocks of 25 OL cases with varying grades of dysplasia and 30 OSCC cases showing its varying grades were selected. Sections were subjected to immunohistochemical staining for podoplanin and compared with the control group for evaluation of results in the three groups. RESULTS: A statistically significant increase in podoplanin expression was observed from normal mucosa through OL to OSCC. In the OL cases, the podoplanin staining score progressively increased from mild dysplasia to carcinoma in situ, whereas in OSCC, well-differentiated group showed the maximum expression of podoplanin. CONCLUSION: The progressive increase in podoplanin expression through the increasing grades of dysplasia in OL is suggestive of an increased risk for malignant transformation with increased expression of podoplanin in OL cases. A high podoplanin expression in the well-differentiated OSCC may indicate a vital role for podoplanin in the early stages of tumorigenesis.