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In this paper, we present the design and analysis of the proof mass for capacitive based MEMS accelerometers. A study was done to determine the parameters (length of hinge and number of combs) to be optimized for the MEMS accelerometer design. The proposed design can measure the acceleration in -, - and -axes. The design features a proof mass with interdigitated fingers along each side. These interdigitated fingers act as parallel plate capacitors. Due to acceleration, capacitance changes along the comb drive. This change in capacitance can be used to monitor the acceleration. Analysis has been carried out with different comb width designs. Using the MEMS CAD tool CoventorWare, the structure has been designed, simulated and analyzed. The process flow for the fabrication has also been proposed for the above structure. Comparative study with several designs has been made and the efficient design parameters to be considered while designing MEMS accelerometer were proposed. Based on the study, a set of optimized design parameters for the comb accelerometer were reported. [ABSTRACT FROM AUTHOR]

Context: Sweat glands (SGs) play a vital role in thermal regulation. The function and structure are altered during the different pathological conditions. Objective: These alterations are studied through three techniques: biopsy, sweat analytes and electrical activity of SG. Methods: The morphological study of SG through biopsy and various techniques involved in quantifying sweat analytes is focussed on here. Electrical activities of SG in diabetes, neuropathy and nephropathy cases are also discussed, highlighting their limitations and future scope. Results and Conclusion: The result of this review identified three areas of the knowledge gap. The first is wearable sensors to correlate pathological conditions. Secondly, there is no device to look for its structure and quantify its associated function. Finally, therapeutic applications of SG are explored, especially for renal failure. With these aspects, this paper provides information collection and correlates SG with pathologies related to diabetes. Hence this could help researchers develop suitable technologies for the gaps identified. [ABSTRACT FROM AUTHOR]

The potential of trimetallic nanoparticles (TMNPs) to enhance biogas production through microbe-to-microbe interactions and boost biogas yield is evident. This present study employed the central composite design (CCD) of response surface methods (RSM) to determine the optimal conditions of iron-cobalt-zinc TMNPs influenced anaerobic digestion for higher biogas yield. The impact of initial pH (6.6–7.4), TMNPs concentration (0–30 mg L−1), temperature (25-45 °C), and hydraulic retention time (HRT) (0-4 days) were modelled for improved biogas production. The results indicated that the linear model terms of pH and TMNPs concentration, and quadratic model terms of temperature and HRT, significantly affect the biogas production. Linear model terms of TMNPs, temperature, pH, and HRT have significant interactive effects and the numerical analysis identified the best conditions for the evaluated parameters. Ideal anaerobic process settings generated a maximum cumulative biogas production of 3700 mL−1 POME than blank (2000 mL−1), corresponding to an 85 % yield. Optimizing the initial pH, TMNPs concentration, temperature, and HRT can significantly improve biogas yield and could be helpful for developing more efficient AD processes at large volume and commercial biogas plants. Promoting TMNPs as catalysts positively improves an AD process towards sustainable biogas production. [Display omitted] [ABSTRACT FROM AUTHOR]

Single-cell analysis (SCA) improves the detection of cancer, the immune system, and chronic diseases from complicated biological processes. SCA techniques generate high-dimensional, innovative, and complex data, making traditional analysis difficult and impractical. In the different cell types, conventional cell sequencing methods have signal transformation and disease detection limitations. To overcome these challenges, various deep learning techniques (DL) have outperformed standard state-of-the-art computer algorithms in SCA techniques. This review discusses DL application in SCA and presents a detailed study on improving SCA data processing and analysis. Firstly, we introduced fundamental concepts and critical points of cell analysis techniques, which illustrate the application of SCA. Secondly, various effective DL strategies apply to SCA to analyze data and provide significant results from complex data sources. Finally, we explored DL as a future direction in SCA and highlighted new challenges and opportunities for the rapidly evolving field of single-cell omics. [Display omitted]. • Single-cell analysis uses deep learning to process complex data and enhance disease detection. • Deep learning techniques in single-cell analysis are superior in analyzing diverse cell types. • With deep learning techniques, single-cell analysis revolutionizes disease detection by analyzing high-dimensional data effectively. • Deep learning has emerged as a key player in the evolving field of single-cell omics for cancer research. [ABSTRACT FROM AUTHOR]

Porcupine bezoar (PB) is a calcified undigested material generally found in porcupine's (Hystrix brachyura) gastrointestinal tract. The bezoar is traditionally used in South East Asia and Europe for the treatment of cancer, poisoning, dengue, typhoid, etc. However, limited scientific studies have been performed to verify its anticancer potential to substantiate its traditional claims in the treatment of cancers. Hence, this study was aimed at investigating the in vitro and in vivo anticancer properties of two grassy PB aqueous extract (PB-A and PB-B) using A375 cancer cell line and zebrafish model, respectively. This paper presents the first report on in vitro A375 cell viability assay, apoptosis assay, cell cycle arrest assay, migration assay, invasion assay, qPCR experimental assay and in vivo anti-angiogenesis assay using the grassy PBs. Experimental findings revealed IC 50 value are 26.59 ± 1.37 μg/mL and 30.12 ± 3.25 μg/mL for PB-A and PB-B respectively. PBs showed anti-proliferative activity with no significant cytotoxic effect on normal human dermal fibroblast (NHDF). PBs were also found to induce apoptosis via intrinsic pathway and arrest cell cycle at G2/M phase. Additionally, the findings indicated its ability to debilitate migration and invasion of A375 cells. Further evaluation using embryo zebrafish model revealed LC 50 = 450.0 ± 2.50 μg/mL and 58.7 ± 5.0 μg/mL for PB-A and PB-B which also exerted anti-angiogenesis effect in zebrafish. Moreover, stearic acid, ursodeoxycholic acid and pregnenolone were identified as possible metabolites that might contribute to the anticancer effect of the both PBs. Overall, this study demonstrated that PB-A and PB-B possess potential in vitro and in vivo anticancer effects which are elicited through selective cytotoxic effect, induction of apoptosis, inhibition of migration and invasion and anti-angiogenesis. This study provides scientific evidence that the porcupine bezoar do possess anti-cancer efficacy and further justifies its traditional utility. However, more experiments with higher vertebrae models are still warranted to validate its traditional claims as an anticancer agent. [ABSTRACT FROM AUTHOR]