Category: Nevin Manimala

Int J Fertil Steril. 2023 Jan 1;17(1):7-11. doi: 10.22074/ijfs.2022.542410.1219.

ABSTRACT

Toxoplasma gondii is found as an intracellular protozoan parasite in the Apicomplexa phylum that can be transmitted to the fetus and causes miscarriage, infection, and asymptomatic neonatal disease. In the present study, we characterized the seroprevalence rate of anti-Toxoplasma gondii antibodies in a population of Iranian women with a recent a spontaneous abortion. We examined our national and international databases including Irandoc, Magiran, SID, Medlib, Scopus, PubMed, and the Science Direct. The search strategy was carried out by using keywords and MeSH terms. The statistical analysis was performed by STATA 14.2. By using the random effects model and the fixed effects model the statistical analysis was performed while the heterogeneity was ≥75 and ≤50%, respectively. We used the chi-squared test and I2 index to calculate heterogeneity among studies, and for evaluating publication bias, Funnel plots and Egger tests were used. The seroprevalence positive rate of IgG among women who had experienced abortion was observed 32% [95% confidence interval (CI): 20-45%] based on the random-effects model. The seroprevalence positive rate of IgM based on the fixed-effect model and positive IgG rate based on the random-effect model was evaluated 4% (95% CI: 3-6%) and 32% (9% CI: 3-42%) among women immediately after an abortion, respectively. According to the finding of our study, toxoplasmosis can be one of the most significant causes of abortion.

PMID:36617196 | DOI:10.22074/ijfs.2022.542410.1219

Brief Bioinform. 2023 Jan 6:bbac607. doi: 10.1093/bib/bbac607. Online ahead of print.

ABSTRACT

Differential abundance analysis (DAA) is one central statistical task in microbiome data analysis. A robust and powerful DAA tool can help identify highly confident microbial candidates for further biological validation. Current microbiome studies frequently generate correlated samples from different microbiome sampling schemes such as spatial and temporal sampling. In the past decade, a number of DAA tools for correlated microbiome data (DAA-c) have been proposed. Disturbingly, different DAA-c tools could sometimes produce quite discordant results. To recommend the best practice to the field, we performed the first comprehensive evaluation of existing DAA-c tools using real data-based simulations. Overall, the linear model-based methods LinDA, MaAsLin2 and LDM are more robust than methods based on generalized linear models. The LinDA method is the only method that maintains reasonable performance in the presence of strong compositional effects.

PMID:36617187 | DOI:10.1093/bib/bbac607

J AOAC Int. 2023 Jan 6:qsad006. doi: 10.1093/jaoacint/qsad006. Online ahead of print.

ABSTRACT

BACKGROUND: Given the recent detection of TTX in bivalve molluscs but the absence of a full collaborative validation study for TTX determination in a large number of shellfish samples, interlaboratory assessment of method performance was required to better understand current capabilities for accurate and reproducible TTX quantitation using chemical and immunoassay methods.

OBJECTIVE: The aim was to conduct a collaborative study with multiple laboratories, using results to assess method performance and acceptability of different TTX testing methods.

METHODS: Homogenous and stable mussel and oyster materials were assessed by participants using a range of published and in-house detection methods to determine mean TTX concentrations. Data was used to calculate recoveries, repeatability and reproducibility, together with participant acceptability z-scores.

RESULTS: Method performance characteristics were good, showing excellent sensitivity, recovery and repeatability. Acceptable reproducibility was evidenced by HorRat values for all LC-MS/MS and ELISA methods being less than the 2.0 limit of acceptability. Method differences between the LC-MS/MS participants did not result in statistically-different results. Method performance characteristics compared well with previously-published single-laboratory validated methods and no statistical difference was found in results returned by ELISA in comparison with LC-MS/MS.

CONCLUSIONS: The results from this study demonstrate that current LC-MS/MS methods and the ELISA are on the whole capable of sensitive, accurate and reproducible TTX quantitation in shellfish. Further work is recommended to expand the number of laboratories testing ELISA and to standardise an LC-MS/MS protocol to further improve interlaboratory precision.

HIGHLIGHTS: Multiple mass spectrometric methods and a commercial ELISA have been successfully assessed through collaborative study, demonstrating excellent performance.

PMID:36617186 | DOI:10.1093/jaoacint/qsad006

Eur J Cardiothorac Surg. 2023 Jan 6:ezad006. doi: 10.1093/ejcts/ezad006. Online ahead of print.

ABSTRACT

OBJECTIVES: We developed a novel wireless localization technique after electromagnetic navigation bronchoscopy-guided radiofrequency identification marker placement for fluoroscopically invisible small lung lesions. We conducted an observational study to investigate the feasibility of this technique and retrospectively compared 2 marking approaches with or without cone-beam computed tomography.

METHODS: Consecutive patients from January 2021 to March 2022 in our institution were enrolled. Markers were placed central to the lesions either in a bronchoscopic suite under intravenous anaesthesia or a hybrid operation theater with cone-beam computed tomography under general anaesthesia. The efficacy of the two marking methods was compared using an inverse probability of treatment weighting adjusted analysis.

RESULTS: Totally 80 markers were placed (45 under cone-beam computed tomography and 35 under fluoroscopy) for 74 patients with 80 lesions ((mean size: 6.9 mm (interquartile range: 5.1-8.4) at a median depth from the pleura of 14.0 mm (interquartile range: 8.5-19.5)). The median distance from marker to lesion was 9.1 mm, with a pleural depth of 15.5 mm. The tumour resection rate was 97.5% (78/80) with the median surgical margin of 10.0 mm (interquartile range: 8.0-11.0). Although the bronchoscopy time was longer using cone-beam computed tomography because of the need for 2.8 scans per lesion, the distance from the marker to the lesion was shorter for marking using cone-beam computed tomography than marking using fluoroscopy (adjusted difference: -4.56, 95% CI: -6.51 to -2.61, p < 0.001).

CONCLUSIONS: Electromagnetic navigation bronchoscopy-guided radiofrequency identification marking provided a high tumour resection rate with sufficient surgical margins.

PMID:36617166 | DOI:10.1093/ejcts/ezad006

Sensors (Basel). 2023 Jan 3;23(1):531. doi: 10.3390/s23010531.

ABSTRACT

By leveraging the conventional Vehicular Ad-hoc Networks (VANETs), the Internet of Vehicles (IoV) paradigm has attracted the attention of different research and development bodies. However, IoV deployment is still at stake as many security and privacy issues are looming; location tracking using overheard safety messages is a good example of such issues. In the context of location privacy, many schemes have been deployed to mitigate the adversary’s exploiting abilities. The most appealing schemes are those using the silent period feature, since they provide an acceptable level of privacy. Unfortunately, the cost of silent periods in most schemes is the trade-off between privacy and safety, as these schemes do not consider the timing of silent periods from the perspective of safety. In this paper, and by exploiting the nature of public transport and role vehicles (overseers), we propose a novel location privacy scheme, called OVR, that uses the silent period feature by letting the overseers ensure safety and allowing other vehicles to enter into silence mode, thus enhancing their location privacy. This scheme is inspired by the well-known war strategy “Give up a Pawn to Save a Chariot”. Additionally, the scheme does support road congestion estimation in real time by enabling the estimation locally on their On-Board Units that act as mobile edge servers and deliver these data to a static edge server that is implemented at the cell tower or road-side unit level, which boosts the connectivity and reduces network latencies. When OVR is compared with other schemes in urban and highway models, the overall results show its beneficial use.

PMID:36617126 | DOI:10.3390/s23010531

Sensors (Basel). 2023 Jan 2;23(1):499. doi: 10.3390/s23010499.

ABSTRACT

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.

PMID:36617092 | DOI:10.3390/s23010499

Sensors (Basel). 2023 Jan 2;23(1):493. doi: 10.3390/s23010493.

ABSTRACT

With the advent of the era of big data information, artificial intelligence (AI) methods have become extremely promising and attractive. It has become extremely important to extract useful signals by decomposing various mixed signals through blind source separation (BSS). BSS has been proven to have prominent applications in multichannel audio processing. For multichannel speech signals, independent component analysis (ICA) requires a certain statistical independence of source signals and other conditions to allow blind separation. independent vector analysis (IVA) is an extension of ICA for the simultaneous separation of multiple parallel mixed signals. IVA solves the problem of arrangement ambiguity caused by independent component analysis by exploiting the dependencies between source signal components and plays a crucial role in dealing with the problem of convolutional blind signal separation. So far, many researchers have made great contributions to the improvement of this algorithm by adopting different methods to optimize the update rules of the algorithm, accelerate the convergence speed of the algorithm, enhance the separation performance of the algorithm, and adapt to different application scenarios. This meaningful and attractive research work prompted us to conduct a comprehensive survey of this field. This paper briefly reviews the basic principles of the BSS problem, ICA, and IVA and focuses on the existing IVA-based optimization update rule techniques. Additionally, the experimental results show that the AuxIVA-IPA method has the best performance in the deterministic environment, followed by AuxIVA-IP2, and the OverIVA-IP2 has the best performance in the overdetermined environment. The performance of the IVA-NG method is not very optimistic in all environments.

PMID:36617090 | DOI:10.3390/s23010493

Sensors (Basel). 2022 Dec 30;23(1):434. doi: 10.3390/s23010434.

ABSTRACT

In this article, a new capsule-like smart aggregate (CSA) is developed and verified for impedance-based stress monitoring in a pre-determined frequency range of less than 100 kHz. The pros and cons of the existing smart aggregate models are discussed to define the requirement for the improved CSA model. The conceptual design and the impedance measurement model of the capsule-like smart aggregate (CSA) are demonstrated for concrete damage monitoring. In the model, the interaction between the CSA and the monitored structure is considered as the 2-degrees of freedom (2-DOF) impedance system. The mechanical and impedance responses of the CSA are described for two conditions: during concrete strength development and under compressive loadings. Next, the prototype of the CSA is designed for impedance-based monitoring in concrete structures. The local dynamic properties of the CSA are numerically simulated to pre-determine the sensitive frequency bands of the impedance signals. Numerical and experimental impedance analyses are performed to investigate the sensitivity of the CSA under compressive loadings. The changes in the impedance signals of the CSA induced by the compressive loadings are analyzed to assess the effect of loading directions on the performance of the CSA. Correlations between statistical impedance features and compressive stresses are also made to examine the feasibility of the CSA for stress quantification.

PMID:36617032 | DOI:10.3390/s23010434

Brief Bioinform. 2023 Jan 5:bbac567. doi: 10.1093/bib/bbac567. Online ahead of print.

ABSTRACT

Accurate in silico prediction of conformational B-cell epitopes would lead to major improvements in disease diagnostics, drug design and vaccine development. A variety of computational methods, mainly based on machine learning approaches, have been developed in the last decades to tackle this challenging problem. Here, we rigorously benchmarked nine state-of-the-art conformational B-cell epitope prediction webservers, including generic and antibody-specific methods, on a dataset of over 250 antibody-antigen structures. The results of our assessment and statistical analyses show that all the methods achieve very low performances, and some do not perform better than randomly generated patches of surface residues. In addition, we also found that commonly used consensus strategies that combine the results from multiple webservers are at best only marginally better than random. Finally, we applied all the predictors to the SARS-CoV-2 spike protein as an independent case study, and showed that they perform poorly in general, which largely recapitulates our benchmarking conclusions. We hope that these results will lead to greater caution when using these tools until the biases and issues that limit current methods have been addressed, promote the use of state-of-the-art evaluation methodologies in future publications and suggest new strategies to improve the performance of conformational B-cell epitope prediction methods.

PMID:36611255 | DOI:10.1093/bib/bbac567

Nurs Open. 2023 Jan 7. doi: 10.1002/nop2.1596. Online ahead of print.

ABSTRACT

AIM: This study aims to explore the perception of nurses on the use of mobile phone SMS for managing diabetes in rural Ghana.

DESIGN: Exploratory Descriptive Qualitative Design.

METHODS: Purposive sampling was used to recruit (13) participants relative to data saturation after ethical clearance (REDACTED); using a semi-structured interview guide. All interviews were transcribed verbatim and analysed using thematic content analysis.

RESULTS: Participants believe SMS was useful in facilitating interaction between nurses, clients, family and statistically significant others; improving medication adherence and supporting blood glucose monitoring. The use of infographics was preferred to traditional SMS among digitally literate patients and voice calls for those who were illiterate. Participants had limited knowledge of downloadable diabetic applications. Participants were willing to accept and use SMS for the management of diabetes mellitus.

PATIENT OR PUBLIC CONTRIBUTION: Thirteen nurses actively participated in the study.

PMID:36611225 | DOI:10.1002/nop2.1596