Machine Learning-Assisted Determination of C6H14 Mole Fraction From Molecular Emissions of Laser-Induced Hexane-Air Plasmas.

Laser-induced plasmas of materials containing hydrocarbons present strong carbon molecular emission features. Using these emissions to build models relating changes in spectral features to a physical parameter of the system, such as hydrocarbon content, can be difficult because of the dynamic complexity of the spectral features and temperature disequilibrium between molecular species. This study presents machine learning models trained to quantify the mole fraction of hexane in hexane-air plasmas from CN Violet and C2 Swan spectral features. Ensemble regression methods provide the most accurate predictions with root mean squared error on the order 10-2. Artificial neural network regressions produce predictions with superlative sensitivity, exhibiting detection limits as low as 0.008. These foundational models can be further refined with more advanced data to quantify the presence of carbon species in complex plasma environments, such as high-speed reacting flows.

Medical students' career preferences in Bangladesh.

AIM: This study aimed to investigate the career preferences among Bangladeshi medical students, identify the factors that influence their present choices, and additionally report the role of gender and academic year behind their decisions. METHODS: This cross-sectional study conducted in Bangladesh from August 2022 to April 2023 included 801 medical students conveniently selected from medical colleges in eight divisions. Data were collected using a web-based survey and analysed using STATA version 16.0. Statistical tests included the Kolmogorov-Smirnov test, arithmetic mean, standard deviation, frequency, and Kruskal-Wallis H test. The response rate was 94.6%, and the CHERRIES guideline was followed for reporting the results. RESULT: The majority of the participants were female (64.42%) and under the age of 23 years (58.8%). The study revealed that medicine was the preferred career choice for the majority of students (65%), with surgery being the most popular first choice (30.21%) among them. Female medical students showed a significantly higher preference for gynaecology & obstetrics (p < 0.001), while male students had a significantly higher tendency to choose general practice (p = 0.002). There is a significant gender difference (p < 0.05) in the career preference factors, including professional prestige, role model influence, easy money, family time, promotion opportunities, income for lifestyle, and research opportunities. Academic year differences were also observed, with increasing interest in medicine and public health (p < 0.001), a decrease in interest in surgery (p < 0.001), and a decline in preference for non-medical careers as students progressed through their MBBS life (p < 0.05). CONCLUSION: Overall, medicine was the most popular speciality choice, however, male students preferred general practice and female students preferred gynaecology and obstetrics more. Personal passion, opportunities for contribution to society, professional prestige, having a direct dealing with patients, and income will allow an enjoyable lifestyle were the most important factors in the choice of their career.

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference.

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.

Author Correction: Impact of imaging cross-section on visualization of thyroid microvessels using ultrasound: Pilot study.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Impact of imaging cross-section on visualization of thyroid microvessels using ultrasound: Pilot study.

Non-invasive, contrast-free microvascular imaging of human thyroids can be potentially beneficial in reducing the large number of benign biopsies of suspicious nodules. However, motion incurred by thyroid due to its proximity to the pulsating carotid artery significantly impacts the visualization of blood flow in small vessels. Singular value based spatiotemporal clutter filtering (SVD-STF) improves the performance of tissue rejection in the presence of motion. However, despite effective clutter filtering, motion in thyroid imaging can impact coherent integration of the Doppler ensemble and degrade the visualization of the underlying vasculature. Recently studies have demonstrated that motion correction using 2D normalized cross-correlation based speckle tracking can address this issue, however, only in-plane motion can be tracked and corrected. Given the natural anatomical orientation of the rigid trachea, thyroid and the pulsating carotid artery, we hypothesize that imaging of thyroid microvessels may be more reliable in the longitudinal view than in the transverse. Specifically, distal presence of rigid trachea can limit out-of-plane motion in the longitudinal view. We tested this hypothesis on 48 acquisitions obtained from 24 thyroid patients having at least one suspicious nodule. In each patient, ultrasound images of the thyroid were acquired in both longitudinal and transverse views. Compounded plane-wave imaging was used to acquire the ultrasound images at high frame-rate, which is important for contrast-free small vessel blood flow imaging. Thyroid motion was tracked using 2D normalized cross-correlation based speckle tracking. Tissue clutter was rejected using singular value decomposition based spatiotemporal clutter filtering. The clutter-filtered Doppler ensemble was motion corrected prior to slow-time power Doppler integration. Signal-to-noise and contrast-to-noise ratios were computed to assess the improvement in quality of the power Doppler images. Out-of-plane motion was detected by estimating normalized ensemble cross-correlation coefficient. The results demonstrated that motion associated with the thyroid due to the carotid artery was primarily in the lateral direction, which could be estimated and corrected using 2D speckle tracking. However, the motion in the transverse view displayed increased speckle decorrelation. The average ensemble cross-correlation coefficient of the thyroid ultrasound images were significantly higher (p < 0.05) in the longitudinal view than in the transverse view. The largest improvement in SNR and CNR of the estimated PD images upon motion correction was observed in the longitudinal view (12.95 ± 3.76 dB and 16.48 ± 4.6 dB) than in the transverse view (3.72 ± 0.894 dB and 6.217 ± 1.689 dB). These preliminary results show that motion encountered by the thyroid due to carotid pulsations can be effectively tracked and corrected in the longitudinal view relative to transverse, which is important for reliably visualizing the underlying blood flow.

Smartphone-imaged microfluidic biochip for measuring CD64 expression from whole blood.

Sepsis, a life-threatening syndrome that contributes to millions of deaths annually worldwide, represents a moral and economic burden to the healthcare system. Although no single, or even a combination of biomarkers has been validated for the diagnosis of sepsis, multiple studies have shown the high specificity of CD64 expression on neutrophils (nCD64) to sepsis. The analysis of elevated nCD64 in the first 2-6 hours after infection during the pro-inflammatory stage could significantly contribute to early sepsis diagnosis. Therefore, a rapid and automated device to periodically measure nCD64 expression at the point-of-care (POC) could lead to timely medical intervention and reduced mortality rates. Current accepted technologies for measuring nCD64 expression, such as flow cytometry, require manual sample preparation and long incubation times. For POC applications, however, the technology should be able to measure nCD64 expression with little to no sample preparation. In this paper, we demonstrate a smartphone-imaged microfluidic biochip for detecting nCD64 expression in under 50 min. In our assay, first unprocessed whole blood is injected into a capture chamber to immunologically capture nCD64 along a staggered array of pillars, which were previously functionalized with an antibody against CD64. Then, an image of the capture channel is taken using a smartphone-based microscope. This image is used to measure the cumulative fraction of captured cells (γ) as a function of length in the channel. During the image analysis, a statistical model is fitted to γ in order to extract the probability of capture of neutrophils per collision with a pillar (ε). The fitting shows a strong correlation with nCD64 expression measured using flow cytometry (R2 = 0.82). Finally, the applicability of the device to sepsis was demonstrated by analyzing nCD64 from 8 patients (37 blood samples analyzed) along the time they were admitted to the hospital. Results from this analysis, obtained using the smartphone-imaged microfluidic biochip were compared with flow cytometry. Again, a correlation coefficient R2 = 0.82 (slope = 0.99) was obtained demonstrating a good linear correlation between the two techniques. Deployment of this technology in ICU could significantly enhance patient care worldwide.