Microbial Spectrum of Complete Denture Wearer in Old Age People of Chitwan.

BACKGROUND: Human oral cavity contains many microorganisms, the habitat of which may be changed by complete denture among edentulous people. The complete dentures favor aggregation of microorganism. The aim of this study was to identify the microorganisms present in the complete dentures of old age people of Chitwan and assess the sensitivity pattern of the microorganisms to the common antibiotics. METHODS: A descriptive cross-sectional study was conducted at Chitwan Medical College, Chitwan, Nepal among 45 old age people who have been wearing dentures above one year. The duration of the study was from 18th Nov 2021 to 12th May 2022. Swab was taken from the polished and tissue surfaces of both maxillary and mandibular dentures in the Department of Prosthodontics while the laboratory-based experiments were conducted in the Department of Microbiology. Antibiotic sensitivity was also done. The data was analyzed using Statistical Package for Social Science (SPSS) version 16.0. Descriptive statistics were used. The data was presented in form of frequency, percentage, mean and standard deviation. RESULTS: Streptococcus spp. was predominant microorganism followed by Coagulase-negative Staphylococci and Staphylococcus aureus. The highest sensitivity pattern was observed to Amikacin, Nalidixic acid and Ciprofloxacin while the most resistant antibiotics were Amoxicillin/clavulanic acid and Cefixime. Escherichia coli was sensitive to all the tested antibiotics. CONCLUSIONS: In this study, Streptococcus spp. followed by Coagulase-negative Staphylococci and Staphylococcus aureus were the most frequently identified microorganisms from the dentures of old age people. Amikacin, Nalidixic acid and Ciprofloxacin were highly sensitive among the people of old age.

Precision Heart Rate Estimation Using a PPG Sensor Patch Equipped with New Algorithms of Pre-Quality Checking and Hankel Decomposition.

A new method for accurately estimating heart rates based on a single photoplethysmography (PPG) signal and accelerations is proposed in this study, considering motion artifacts due to subjects' hand motions and walking. The method comprises two sub-algorithms: pre-quality checking and motion artifact removal (MAR) via Hankel decomposition. PPGs and accelerations were collected using a wearable device equipped with a PPG sensor patch and a 3-axis accelerometer. The motion artifacts caused by hand movements and walking were effectively mitigated by the two aforementioned sub-algorithms. The first sub-algorithm utilized a new quality-assessment criterion to identify highly noise-contaminated PPG signals and exclude them from subsequent processing. The second sub-algorithm employed the Hankel matrix and singular value decomposition (SVD) to effectively identify, decompose, and remove motion artifacts. Experimental data collected during hand-moving and walking were considered for evaluation. The performance of the proposed algorithms was assessed using the datasets from the IEEE Signal Processing Cup 2015. The obtained results demonstrated an average error of merely 0.7345 ± 8.1129 beats per minute (bpm) and a mean absolute error of 1.86 bpm for walking, making it the second most accurate method to date that employs a single PPG and a 3-axis accelerometer. The proposed method also achieved the best accuracy of 3.78 bpm in mean absolute errors among all previously reported studies for hand-moving scenarios.

A diagnostic and prognostic value of blood-based circulating long non-coding RNAs in thyroid, pancreatic and ovarian cancer.

Several studies have demonstrated the potential of circulating long non-coding RNAs (lncRNAs) as promising cancer biomarkers. Herein, we addressed the regulatory role of circulating lncRNAs and their potential value as diagnostic/prognostic markers for thyroid, pancreatic and ovarian cancers. Furthermore, we analyzed and measured the clinical implications and association of lncRNAs with sensitivity, specificity, and area under the ROC curve (AUC). Based on our meta-analysis, we found that GAS8-AS1 could discriminate thyroid cancer from non-cancer and other cancers with higher accuracy (AUC = 0.746; sensitivity = 61.70 %, and specificity = 90.00 %). Similarly, for ovarian cancer, lncRNA RP5-837J1.2 was found to have ideal diagnostic potential with critical clinical specifications of AUC = 0.996; sensitivity = 97.30 % and specificity = 94.60 %. Whereas we could not find any lncRNA having high diagnostic/prognostic efficiency in pancreatic cancer. We believe that lncRNAs mentioned above may explore clinical settings for the diagnosis and prognosis of cancer patients.

Precursor- and Time-Dependent Morphological Evolution of ZnO Nanostructures for Comparative Photocatalytic Activity and Adsorption Dynamics with Methylene Blue Dye.

Diverse ZnO nanostructures were successfully fabricated at 700 °C by direct annealing of 1D Zn(II) coordination polymer precursors, namely, [Zn2(bpma)2(adc)2] n , [Zn2(bpea)2(adc)2] n , and {[Zn2(bpta)2(adc)2]·2H2O} n . The effect of sacrificial ligands present in the precursors as well as a variation in the retention time (6-24 h) during their synthesis resulted in 0D nanospheres, 1D microrods, and 3D polyhedra (with a diamond-like structure) of ZnO. The as-synthesized ZnO nanostructures were characterized by field-emission scanning electron microscopy, transmission electron microscopy, X-ray diffractometry, diffuse reflectance spectroscopy, and Raman spectroscopy. The hexagonal crystal structure was confirmed for all the ZnO samples. A lattice spacing of 0.22 nm has been observed for nanospheres, whereas a lattice spacing of 0.26 nm has been observed for the polyhedra. Their Raman spectra confirm the wurtzite phase of ZnO. UV-vis spectra of ZnO nanostructures exhibit broad peaks in the range of 350-370 nm, and the band gap energies are found to be in the range of 3.02-3.20 eV. Based on the photoluminescence spectra photocatalytic activities of the as-synthesized ZnO nanostructures calcined for 12 h were tested with methylene blue (MB) as a contaminant in an aqueous solution. These results demonstrate that the photocatalytic efficiency of polyhedra is higher than those of nanospheres and microrods. The adsorption kinetics of MB dye by these nanostructures were studied by three different kinetic models-Elovich's, intraparticle, and pseudo-second-order. The maximum rate of adsorption was observed with the intraparticle diffusion model.