Low Variability Research Articles

Cardiac myosin-binding protein-C: assessing fragmentation patterns to differentiate between forms of myocardial injury

Abstract Background Cardiac myosin-binding protein-C (cMyC) is a novel biomarker of myocardial injury. We hypothesize that fragmentation of cMyC differs according to aetiology of myocardial injury. Assessing the fragmentation pattern of the protein may aid diagnosis of these conditions. Purpose This work represents an examination of cMyC fragmentation in human serum, and studies its utility in differentiating between forms of myocardial injury. Methods Patients who were admitted to a hospital during October-November 2023 with acute myocardial injury were recruited. Acute myocardial injury was defined as a dynamic troponin rise above the 99th centile (Abbott Alinity: cTnI>34ng/L male, cTnI >16ng/L female). Following collection, samples were left at room temperature for 30 minutes and then centrifuged. Serum was separated for cMyC measurement, frozen in liquid nitrogen and stored at -80 °C. Recruited patients were followed up during their inpatient journey. Their final diagnosis was defined using the 4th universal definition of MI by two cardiologists, with a third cardiologist acting as adjudicator, if required. The serum samples were analysed using two separate electrochemiluminescence sandwich ELISA assays detecting different portions of cMyC. One assay formulated for total concentration of cMyC using high affinity mouse N-terminal monoclonal antibodies (mAb) targeting epitopes in close proximity (Limit of Detection (LoD) = 9.0ng/L). The other assay uses a N-terminal and a C-terminal mouse mAb which straddle the major proteolytic cleavage site of cMyC. This assay detects the intact (fuller-length) cMyC (LoD= 14.2ng/L). Both assays perform with good sensitivity, low variability and are capable of detecting cMyC at concentrations well below the 99th centile. Results 11 patient samples were collected with final diagnoses of; type 1 MI (STEMI n=3, NSTEMI n=4), type 4 MI (alcohol septal ablation n=1), acute myocardial injury (myocarditis n=2) and type 2 MI (chest sepsis with known coronary disease n=2). Figure one details the percentage of intact cMyC relative to total cMyC measured in serum for each patient, and is split into their adjudicated diagnosis. The bars display the median and interquartile range (IQR). Our findings suggest that the fragmentation pattern of cMyC could help differentiate between forms of myocardial injury. The ratio of intact: total cMyC was higher in the type 2 MI than any other condition. The results did not reach statistical significance (p = 0.06) due to the small sample size. Conclusions The fragmentation pattern of cMyC is dependent on the type of myocardial injury and could aid in the differentiation between type 2 MI and other forms of myocardial injury.Figure One

Beat-to-beat measurement of R-wave peak time for left bundle branch area pacing: man versus machine using a novel automated algorithm

Abstract Background Assessment of stimulation spike to R-wave peak time (RWPT) in V6 and in aVL, and V6-V1 interpreak interval, may be used to evaluate presence of conduction system capture during left bundle branch area pacing (LBBAP). This is performed by manual measurements which is tedious and requires a skilled operator to limit variability in the measurements. Automatic beat-to-beat measurement of these intervals may streamline workflow during implantation, but such an algorithm has never been tested so far. Purpose To test the feasibility of performing beat-to-beat automatic measurement of RWPT using an algorithm designed to measure the interval between the stimulation spike and the peak positive voltage, and to compare the results with manual measurements. Methods ECG recordings from 50 patients (28% female, mean age 81.5 ± 9.0 years) undergoing LBBAP implantation were evaluated on a electrophysiology recording system by manually measuring RWPT in V6 and in aVL and the V6-V1 interpeak intervals . A single operator performed offline measurements on 10 consecutive beats in each patient. The same beats were subjected to the same measurements using an automatic algorithm after signal conditioning in a novel EP recording System. The correlation between manual and automatic measurements was calculated. Variability of the measurements (evaluated by standard deviation) in the 10 consecutive beats was also compared. Results Of the 500 beats measured, 3 were excluded due to obvious morphological differences affecting the interval measurement (e.g. due to fusion beats). The algorithm was unable to make a measurement in V6 in 20 beats and manual assessment of aVL was not possible in one patient, meaning that 1461/1500 (97.4%) measurements were compared between the manual and automatic methods. The results are shown in the figure. There was excellent correlation between manual and automatic measurements, with lower variability using the latter method. Conclusion Beat-to-beat automatic measurement of RWPT is feasible and provides excellent correlation with manual measurements, with less variability in the values. This algorithm may streamline the measurements during implantation. However, prospective evaluation is required to confirm operation of the algorithm in the clinical setting to include challenges such as electrical noise.

Differential production of mitochondrial reactive oxygen species between mouse (Mus musculus) and crucian carp (Carassius carassius).

In most vertebrates, oxygen deprivation and subsequent re-oxygenation are associated with mitochondrial impairment and excess production of reactive oxygen species (ROS) like hydrogen peroxide (H2O2). This in turn triggers a cascade of cell-damaging events in a temperature-dependent manner. The crucian carp (Carassius carassius) is one of few vertebrates that survives months without oxygen at cold temperatures and overcomes oxidative damage during re-oxygenation periods. Mitochondria of this anoxia-tolerant species therefore serve as an excellent model in translational research to study adaptation and resilience to low oxygen conditions and thermal variability. Here, we used high-resolution respirometry on isolated mitochondria from hearts of crucian carp and the anoxia-intolerant mouse (Mus musculus), at 37 and 8°C; two temperatures relevant for transplantation medicine (i.e., graft preservation and subsequent rewarming). We find: (1) a striking difference in H2O2 release between the two species at 37°C despite comparable mitochondrial efficiency and capacity, (2) a massive H2O2 release after inhibition of complex V in mouse at 37°C that is absent in crucian carp, and prevented in mouse by incubation at 8°C or uncoupling with a protonophore at 37°C, and (3) indications that differences in mitochondrial complex I and II capacity and thermal sensitivity influence the release of mitochondrial H2O2 relative to respiration. Our findings provide comparative insights into a spectrum of mitochondrial adaptations in vertebrates and the importance of thermal variability. Furthermore, the species- and temperature-related changes associated with mitochondria highlighted in this study may help identify mitochondria-based targets for translational medicine.

Mediterranean Diet, ultra-processed food consumption and semen quality in healthy young men

Abstract Background Diet quality can have beneficial effects on male reproductive health, although studies are still limited, and little is known on the potential impact of ultra-processed foods (UPFs) on semen quality parameters. Methods A cross-sectional analysis was run on 126 participants (mean age 20.0 ± 1.2 y) from the FAST randomized controlled trial in 2018-2019. Food intake was assessed through a FFQ. UPF was defined following the Nova classification and calculated as the ratio (weight ratio) between UPF (g/d) and total food (g/d). Adherence to the Mediterranean Diet (MD) was ascertained by the Mediterranean Diet Score (MDS). The semen analyses were performed using a microscope for optical evaluation with a Makler counting chamber and two automated semen analysers. The primary outcomes were sperm volume, concentration, motility and morphology. A hierarchical mixed model approach was utilized to accommodate the within-subject correlation arising from the triple temporal repetition of measurements. Results Highest UPF consumption (Q4), compared to lowest (Q1), was associated with lower sperm concentration (β=-54.1×106 spz./ml; 95%CI: -92.9 to -15.4; p-trend=0.002 across quarters), and progressive motility (β=-14.2%; 95%CI: -28.2 to -0.09; p-trend=0.036). The percentage of cells with normal morphology tended to be reduced in young men consuming more UPF compared to lowest intake (β=-2.93%; 95%CI: -6.22 to 0.37; p-trend=0.071). The MDS was not associated with any of the parameters under study. Conclusions A larger dietary share of UPF was inversely associated with sperm concentration and progressive motility in young men of reproductive age. MD adherence was not associated with semen quality parameters, and this is possibly due to the low variability of MD adherence in this sample. Dietary recommendations for improving sperm health should prioritize limiting UPF in the diet. Key messages • Ultra-processed food (UPF) intake was unfavourably associated with semen quality parameters amongst young men. • Dietary recommendations for improving sperm health should recommend limiting UPF.

Reliability of a standardized protocol of the Single Leg Heel Rise Test

The single leg heel rise (SLHR) test is a widely used method for assessing calf muscle-tendon unit (MTU) endurance in various fields, including medicine, sports, and dance. The objectives of this study were to examine the reliability of a standardized SLHR test protocol with a heel rise measurement device and to investigate the relationship between SLHR repetitions, SLHR total work, and both maximal voluntary isometric contraction (MVIC) and reactive strength index (RSI) outcomes of the plantar flexors. 21 sport students (8 females, 13 males) were assessed for SLHR outcomes (number of repetitions, height of heel rises, total positive work performed) in two data collection sessions, as well as unilateral lower extremity MVIC and RSI. Test-retest reliability showed excellent reliability and low variability for the number of repetitions (Intraclass correlation coefficient (ICC)=0.91, 95% CI: 0.73 to 0.97; coefficient of variability (CV): 8.1- 8.7%), height of the heel rises (ICC=0.92, 95% CI: 0.81 to 0.97; CV: 4.6 - 5.2%) and total positive work performed (ICC=0.96, 95% CI: 0.87 to 0.99; CV: 6.8 - 9.8%) in both feet. No significant correlation was identified between SLHR repetitions, MVIC, and reactive strength outcome measures. A moderate correlation was observed between the total work performed in the SLHR and RSI outcomes that could potentially be explained by the body weight (BW) of the participants. The SLHR test provides reliable measures for lower leg muscular endurance, yet it does not predict plantar flexor maximal strength or reactive strength. In future studies, we advise employing this standardized protocol for screenings of athletes and dancers.

Reproducibility of Thermography for Measuring Skin Temperature of Upper Limbs in Breast Cancer Survivors

Background/Objectives: Breast cancer-related lymphedema (BCRL) is a chronic condition that has early diagnosis as a critical component for proper treatment. Thermography, a non-invasive imaging method, is considered a promising complementary tool for the diagnosis and monitoring of BCRL, especially in subclinical stages. The present study aimed to evaluate the intra- and inter-examiner reproducibility of thermography for measuring the skin temperature of the upper limbs (UL) of women with and without BCRL. Methods: This study, conducted with women who underwent a unilateral mastectomy, assessed BCRL using indirect volumetry. Maximum, minimum, and mean skin temperatures were measured in five regions of interest (ROI) of each UL (C1, C2, C3, C4, and Cup) in four different postures. Reproducibility measures were assessed using an intraclass correlation coefficient, 95% confidence interval, and coefficient of variation. Results: The sample comprised 30 women; 14 were diagnosed with BCRL. A total of 120 thermograms were recorded in different postures, and 3600 ROI were analyzed in the UL with and without BRCL. The intraclass correlation coefficient of the analyses indicated intra- and inter-examiner reproducibility from good to excellent (0.82 to 1.00) for all skin temperatures evaluated (maximum, minimum, and mean). The coefficient of variation for all measures was below 10%, indicating low variability. Conclusions: Our findings demonstrate that thermography shows good-to-excellent reproducibility across multiple postures and regions of interest, reinforcing its potential as a non-invasive and reliable method for assessing lymphedema in breast cancer survivors. This study establishes a foundation for incorporating thermography into clinical practice for early BCRL detection, particularly in subclinical stages, thus improving patient management and outcomes.

Methodological evaluation of river discharges derived from remote sensing and land surface models

This study assesses river discharges derived using remote sensing and hydrologic modeling approaches throughout the CONUS. The remote sensing methods rely on total water storage anomalies (TWSA) from the GRACE satellite mission and water surface elevations from altimetry satellites (JASON-2/3, Sentinel-3). Surface and subsurface runoff from two Land Surface Models (NOAH, CLSM) are routed using the Hillslope River Routing model to determine discharge. The LSMs are part of NASA’s Global Land Data Assimilation System (GLDAS). Differences in key physical processes represented in each model, model forcings, and use of data assimilation provide an intriguing basis for comparison. Evaluation is performed using the Kling Gupta Efficiency and USGS stream gauges. Results highlight the effectiveness of both satellite-derived discharge methods, with altimetry generally performing well over a range of discharges and TWSA capturing mean flows. LSM-derived discharge performance varies based on hydroclimatic conditions and drainage areas, with NOAH generally outperforming CLSM. CLSM-derived discharges may be impacted by the use of data assimilation (GLDAS v2.2). Low correlation and high variability contribute to lower KGE values. GLDAS models tend to perform poorly in snow dominated, semi-arid and water-regulated systems where both the timing and magnitude of the simulated results are early and overestimated.

Optimization of the Small Wind Turbine Design—Performance Analysis

In recent decades, the intensive development of renewable energy technology has been observed as a great alternative to conventional energy sources. Solutions aimed at individual customers, which can be used directly in places where electricity is required, are of particular interest. Small wind turbines pose a special challenge because their design must be adapted to environmental conditions, including low wind speed or variability in its direction. The research study presented in this paper considers the energy efficiency of a small wind turbine with a horizontal axis of rotation. Three key design parameters were analyzed: the shape and inclination of the turbine blades and additional confusor–diffuser shape casings. The tests were carried out for three conceptual variants: a confusor before the turbine, a diffuser after the turbine, and a confusor–diffuser combination. Studies have shown that changing the shape of the blade can increase the analyzed wind turbine power by up to 35%, while changing the blade inclination can cause an increase of up to 16% compared to the initial installation position and a 66% increase in power when comparing the extreme inclination of the blades of the tested turbine. The study has shown that to increase the wind speed, the best solution is to use a confusor–diffuser configuration, which, with increased length, can increase the air velocity by up to 21%.

A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks

Genome-scale metabolic models (GEMs) cover the entire list of metabolic genes in an organism and associated reactions, in a tissue/condition non-specific manner. RNA-seq provides crucial information to make the GEMs condition-specific. Integrative Metabolic Analysis Tool (iMAT) and Integrative Network Inference for Tissues (INIT) are the two most popular algorithms to create condition-specific GEMs from human transcriptome data. The normalization method of choice for raw RNA-seq count data affects the model content produced by these algorithms and their predictive accuracy. However, a benchmark of the RNA-seq normalization methods on the performance of iMAT and INIT algorithms is missing in the literature. Another important phenomenon is covariates such as age and gender in a dataset, and they can affect the predictivity of analysis. In this study, we aimed to compare five different RNA-seq data normalization methods (TPM, FPKM, TMM, GeTMM, and RLE) and covariate adjusted versions of the normalized data by mapping them on a human GEM using the iMAT and INIT algorithms to generate personalized metabolic models. We used RNA-seq data for Alzheimer’s disease (AD) and lung adenocarcinoma (LUAD) patients. The results demonstrated that RNA-seq data normalized by the RLE, TMM, or GeTMM methods enabled the production of condition-specific metabolic models with considerably low variability in terms of the number of active reactions compared to the within-sample normalization methods (FPKM, TPM). Using these models, we could more accurately capture the disease-associated genes (average accuracy of ~0.80 for AD and ~0.67 for LUAD) for the RLE, TMM, and GeTMM normalization methods. An increase in the accuracies was observed for all the methods when covariate adjustment was applied. We found a similar accuracy trend when we compared the metabolites of perturbed reactions to metabolome data for AD. Together, our benchmark study shows that the between-sample RNA-seq normalization methods reduce false positive predictions at the expense of missing some true positive genes when mapped on GEMs.

Lake shape and the characteristics of migration behavior modify Atlantic salmon smolt migration success through lakes.

Migration is a high-risk behavior. For the Atlantic salmon, Salmo salar, migrating from its river nursery area to marine feeding grounds, the magnitude of risk varies with habitat type. Passage through lakes, in particular, is associated with low rates of migration success. Downstream migrating salmon smolts are rheotactic when migrating in rivers, but lakes typically provide poorer directional currents for migrating salmon. In this study we tested if, in the absence of clear navigational cues in lakes, Atlantic salmon smolts switch to a random search strategy to find the outflowing river. We constructed random search simulations to test if lake basin shape has an effect on migration success. We also compared simulated migration characteristics with migrations of salmon smolts through five real lakes for which there are telemetry data for migrating salmon. Correlated random walk simulations showed that a random search strategy could be successful for all lake shapes tested but was more successful in curved (round and elliptical) than rectangular basin shapes. Rectangular basins with the migration start and stoppoints at the ends of the lake had a higher success than those where these points were perpendicular to the axis of the lake. In general, a random walk model predicted the migration success rate of fish tracked through real lakes. However, for two lakes the simulated migration success exceeded that of actual success, suggesting that fish passing through these lakes were not adopting a random search strategy. We speculate that this is the result of either conflicting navigational cues which inhibit smolts from finding the lake outlet or that they temporarily suspend migration (e.g., to feed). Modelling predicted that for small lakes, directional swimming in short steps (ca. 100 m) followed by turns with very low variation from the direction of travel resulted in the highest migration success. For larger lakes, longer step lengths but also with low turn variation (simulated turning angle drawn from distributions of standard deviation 2° and 5° around a mean of 0°) resulted in the highest migration success. We conclude that navigation in downstream migrating salmon smolts switches from rheotaxis in rivers to a random search tactic in lakes except where residual flow cues in some lakes prevent this, at times resulting in suboptimal navigation outcomes.

Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity

Abstract The success of plant species under climate change will be determined, in part, by their phenological responses to temperature. Despite the growing need to forecast such outcomes across entire species ranges, it remains unclear how phenological sensitivity to temperature might vary across individuals of the same species. In this study, we harnessed community science data to document intraspecific patterns in phenological temperature sensitivity across the multicontinental range of six herbaceous plant species. Using linear models, we correlated georeferenced temperature data with 23,220 plant phenological records from iNaturalist to generate spatially-explicit estimates of phenological temperature sensitivity across the shared range of species. We additionally evaluated the geographic association between local historic climate conditions (i.e. mean annual temperature and interannual variability in temperature) and the temperature sensitivity of plants. We found that plant temperature sensitivity varied substantially at both the interspecific and intraspecific level, demonstrating that phenological responses to climate change have the potential to vary both within and among species. Additionally, we provide evidence for a strong geographic association between plant temperature sensitivity and local historic climate conditions. Plants were more sensitive to temperature in hotter climates (i.e., regions with high mean annual temperature), but only in regions with high interannual temperature variability. In regions with low interannual temperature variability, plants displayed universally weak sensitivity to temperature, regardless of baseline annual temperature. This evidence suggests that pheno-climatic forecasts may be improved by accounting for intraspecific variation in phenological temperature sensitivity. Broad climatic factors such as mean annual temperature and interannual temperature variability likely serve as useful predictors for estimating temperature sensitivity across species’ ranges.

Hymenochaete ametzii sp. nov. (Hymenochaetales, Basidiomycota), an endangered bark-dwelling species inhabiting old Quercus pyrenaica trees from the Iberian Peninsula

Bark-dwelling fungi represent a group of ecologically highly specialized organisms. This study deals with an undescribed species of Hymenochaete characterized by specifically inhabiting the bark of Pyrenean oak (Quercus pyrenaica), and producing effuse-reflexed basidiomata and mainly globose to subglobose basidiospores. Maximum Likelihood and Bayesian analyses of the nuclear ITS-LSU regions revealed that the sequences of H. ametzii form a monophyletic group with a low intraspecific variation and substantially different from closest taxa, further supporting its recognition as a species. The seven localities H. ametzii is known from are old forests with a long ecological continuity, containing large old Q. pyrenaica trees, and are located in the supramediterranean belt of the Mediterranean biogeographical region. Based on habitat availability and field counts of colonized trees, the global population of H. ametzii is estimated at 8,670 mature individuals. Considering that the traditional use of old Q. pyrenaica stands ceased several decades ago in the Iberian Peninsula, with a consequent decline in habitat quality and availability, it is concluded that H. ametzii is Endangered (EN) according to the IUCN criteria.

Development and validation of a new anthropometric equation to predict fat mass percentage in a white Spanish population.

(1) To develop a new regression equation for estimating fat mass percentage (%FM) from anthropometric measurements in a heterogeneous Caucasian population and (2) to compare it with the Durnin and Womersley equation, which is one of the most used anthropometric equations for fat mass assessment. Body mass, stature, and four skinfolds (biceps, triceps, subscapular, and supracrestal) were assessed by an accredited anthropometrist, according to the International Society for Advancement in Kinanthropometry. Participants completed a dual-energy X-ray absorptiometry (DXA) whole-body scan to determine their %FM. A new anthropometric equation to estimate %FM was developed using multiple forward regression analyses with DXA as the reference method. Tests for the accuracy of the different equations included mean differences, coefficient of determination, standard error of the estimate (SEE), concordance correlation coefficient (CCC), and Bland-Altman plots. Spain. Two hundred and eighteen healthy Caucasian participants aged 18-65 years participated in this cross-sectional study. Our proposed equation explained 89.9% of the variance in the DXA-derived %FM, with a low random error (SEE = 3.00%), a very strong agreement (CCC = 0.93), no fixed or proportional bias, and a relatively low individual variability (5.84%). However, the Durnin and Womersley equations obtained a fixed bias of -3.65% when compared to DXA and a greater individual variability (6.74%). The proposed equation can accurately estimate %FM in a heterogeneous Caucasian population with a wide age range (18-65 years). Additionally, the Durnin and Womersley equation was inadequate when applied to our participants.

Measurement reproducibility and storage impact on VOC/SVOC emission rate from decorative materials

Building materials are the major sources of Volatile and Semi-Volatile Organic Compounds (VOCs and SVOCs) in indoor air. Measurements of emission rates of these compounds are likely to be influenced by variation in certain environmental factors resulting in intra-specimen variability. This study aims to (i) evaluate the reproducibility of measurements between specimens and (ii) evaluate the impact of storage on VOC and SVOC emissions from antifungal acrylic paint (applied on polyester-cellulose). For this purpose, 15 discs of tested materials (1.63 ± 0.04 g) were prepared. From these, the emissions rates (ER) of 5 samples were analyzed simultaneously during three measurement campaigns (October 2021, January 2022 and March 2022). Between each campaign, specimens were stored in the dark at ambient temperature (25 ± 4 °C) and relative humidity (50 ± 20 %). Measurements were performed using the field and laboratory emission cell (FLEC) and characterized by gas chromatography (TD-GC-MS/FID) and liquid chromatography (HPLC). Intra-specimen reproducibility was assessed by comparing 5 ER of different specimens collected simultaneously. The impact of storage was evaluated by comparing the average VOC/SVOC ER between each campaign. The results show, concerning the reproducibility of the measurements, that the first measurement campaign provides ER with high variability (10–36 %) compared to the second and third measurement campaigns, which show lower intra-specimen variability (5–24 % and 8–20 % respectively). However, weakly emitted compounds (ER < 10 μg m−2 h−1) such as aromatics and aldehydes show large variabilities (6–100 % of variation) in all measurement campaigns. Regarding the effect of the 5-months storage a significant decrease in the ER of individual VOC/SVOCs (37–85 %) and of TVOCs (74 %) was noted, except for aldehydes, aromatic hydrocarbons, isopropylacetone and vinyl crotonate, which showed a stability or eventual increase (up to 100 %) in the ER over time, depending on the type of emitted compound.

Mitochondrial genome insights into the spatio-temporal distribution and genetic diversity of Dendrobium hancockii Rolfe (Orchidaceae).

With its distinctive evolutionary rate and inheritance patterns separate from the nuclear genome, mitochondrial genome analysis has become a prominent focus of current research. Dendrobium hancockii Rolfe, a species of orchid with both medicinal and horticultural value, will benefit from the application of the fully assembled and annotated mitochondrial genome. This will aid in elucidating its phylogenetic relationships, comparative genomics, and population genetic diversity. Based on sequencing results from Illumina combined with PacBio and Nanopore, the mitochondrial genome map of D. hancockii was constructed. Comparative analysis was conducted from the perspectives of phylogeny across multiple species, selection pressure on protein-coding genes, and homologous segments. The population diversity of D. hancockii was analyzed using single nucleotide polymorphism (SNP) data from the mitochondrial genome and single-copy nuclear genes. This research constructed a circular mitochondrial map for D. hancockii, spanning 523,952 bp, containing 40 unique protein-coding genes, 37 transfer RNA genes, and 4 ribosomal RNA genes. Comparative analysis of mitochondrial genes from 26 land plants revealed a conserved gene cluster, "rpl16-ccmFn-rps3-rps19," particularly within the Dendrobium genus. The mitochondrial genome of D. hancockii exhibits a lower point mutation rate but significant structural variation. Analysis of 103 resequencing samples identified 19,101 SNP sites, dividing D. hancockii into two major groups with limited gene flow between them, as supported by population diversity, genetic structure analysis, principal component analysis, and phylogenetic trees. The geographical distribution and genetic differentiation of D. hancockii into two major groups suggest a clear phytogeographical division, likely driven by ancient geological or climatic events. The close alignment of mitochondrial data with nuclear gene data highlights the potential of the mitochondrial genome for future studies on genetic evolution in this species.

Genomic epidemiology and evolutionary dynamics of the Omicron variant of SARS-CoV-2 during the fifth wave of COVID-19 in Pakistan.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed extraordinary challenges to global health systems and economies. The virus's rapid evolution has resulted in several variants of concern (VOCs), including the highly transmissible Omicron variant, characterized by extensive mutations. In this study, we investigated the genetic diversity, population differentiation, and evolutionary dynamics of the Omicron VOC during the fifth wave of COVID-19 in Pakistan. A total of 954 Omicron genomes sequenced during the fifth wave of COVID-19 in Pakistan were analyzed. A Bayesian framework was employed for phylogenetic reconstructions, molecular dating, and population dynamics analysis. Using a population genomics approach, we analyzed Pakistani Omicron samples, revealing low within-population genetic diversity and significant structural variation in the spike (S) protein. Phylogenetic analysis showed that the Omicron variant in Pakistan originated from two distinct lineages, BA.1 and BA.2, which were introduced from South Africa, Thailand, Spain, and Belgium. Omicron-specific mutations, including those in the receptor-binding domain, were identified. The estimated molecular evolutionary rate was 2.562E-3 mutations per site per year (95% HPD interval: 8.8067E-4 to 4.1462E-3). Bayesian skyline plot analysis indicated a significant population expansion at the end of 2021, coinciding with the global Omicron outbreak. Comparative analysis with other VOCs showed Omicron as a highly divergent, monophyletic group, suggesting a unique evolutionary pathway. This study provides a comprehensive overview of Omicron's genetic diversity, genomic epidemiology, and evolutionary dynamics in Pakistan, emphasizing the need for global collaboration in monitoring variants and enhancing pandemic preparedness.

Quantifying interstellar extinction at high galactic latitudes

Abstract A detailed map of the distribution of dust at high Galactic latitudes is essential for future cosmic microwave background (CMB) polarization experiments because the dust, while diffuse, remains a significant foreground in these regions. We develop a Bayesian model to identify a region of the Hertzsprung-Russell (HR) diagram suited to constrain the single-star extinction accurately at high Galactic latitudes. Using photometry from Gaia, 2MASS and ALLWISE, and parallax from Gaia, we employ nested sampling to fit the model to the data and analyse the posterior over stellar parameters for both synthetic and real data. Charting low variations in extinction is complex due to systematic errors and degeneracies between extinction and other stellar parameters. The systematic errors can be minimised by restricting our data to a region of the HR diagram where the stellar models are most accurate. Moreover, the degeneracies can be reduced by including astrophysical priors and spectroscopic constraints. We show that accounting for the measurement error of the data and the assumed inaccuracies of the stellar models are critical in accurately recovering small variations in extinction. We compare the posterior distribution for individual stars with spectroscopic stellar parameter estimates from LAMOST and Gaia ESO and illustrate the importance of estimating extinction and effective temperature as a joint solution.

Analyzing switching variability of SiNx-based RRAM in terms of Joule heating dissipation

In this paper, the switching variability of SiNx-based RRAM with reactive metal electrodes in terms of Joule heating dissipation was analyzed. The electrode with high (low) thermal conductivity showed low LRS (HRS) variability in SiNx-based RRAM. By analyzing the I–V characteristics and the current conduction mechanism, we proposed that the thermal conductivity of reactive electrodes significantly affected the number of ions involved in the switching process and the vacancies distribution in the switching layer, resulting in the difference in the switching performance. This study suggested that attention should be paid to the influence of electrode thermal conductivity on variability, providing ideas for designing RRAM with low switching variability.

Quality of Recovery in Pediatrics After Tonsillectomy Under Total Intravenous Anesthesia Versus Sevoflurane Anesthesia

Introduction: Inhalational anesthetics are often the first choice in pediatric anesthesia. However, the most recent literature demonstrates possible advantages of total intravenous anesthesia (TIVA). The goal of this study was to compare the postoperative quality in children submitted to tonsillectomy under TIVA versus sevoflurane anesthesia. Materials and Methods: Prospective observational case-control study (Sevoflurane vs TIVA) including children submitted to (adeno) tonsillectomy to compare the quality of anesthesia considering intra and postoperative parameters. Data was collected from clinical records, anesthetic monitoring and interviews. Results: From the 52 children included, 25% received TIVA. TIVA group had a shorter time for liquid diet reintroduction (42 minutes vs. 95 minutes) (p&lt;0.05) and the Sevoflurane group had a lower mean blood pressure variation (p=0.027). Mean wake up time was similar for both groups (11.3±6.2 minutes for TIVA and 11.6±5.3 minutes for Sevoflurane). In PACU, TIVA group demonstrated, although not statistically significant, a shorter time of stay (40 minutes vs. 41 minutes), less emergence delirium (7.7% vs. 12.5%) and less nausea and vomiting (0% vs. 5.1%). At 24 hours, TIVA group presented, although not statistically significant, less nausea and vomiting (7.7% vs 13.5%), lower pain (69.2% with &lt;5 on the numerical pain scale vs 56.8%) and higher parental satisfaction (10 vs 8). Conclusion: This study suggests that TIVA for tonsillectomy may be associated with better recovery quality. However, given the limited sample size of this study, it should be repeated in a larger sample, or in a multicentric study, for more robust conclusions.

Analysis of Wheat Export Performance in India

Wheat is a plant which is valued highly for its kernel as an edible part and an important source of carbohydrates. India ranks second position in wheat production in the world with a contribution of roughly 13.53 per cent to global wheat output (Naga Latha et. al., 2022). The study analyses the export performance of wheat and examines the trends in the growth performance of wheat in terms of area, production and productivity, export quantity and export value during 1973-2022 which is a period of 50 years. The analysis reveals that the highest compound growth rate in terms of area was 1.16 per cent, production was 4.49 per cent and productivity was 3.29 per cent respectively. The results of the study on the compound growth rates during the study periods have shown positive and increasing value which indicates high potential for the export of wheat from India. In the analysis of instability, there exists a high positive correlation between the export quantity and value of export in the overall period. Wheat area, production and productivity exhibit higher variability and instability in the overall period. Period II shows lower variability and instability, indicating increased stability. Period I exhibits moderate variability and instability. The overall period has the highest instability, suggesting unpredictable production. Instability indices show high instability at 126.97 per cent in Period I and 138.18 per cent overall, while Period II exhibits moderate instability at 101.94 per cent. Market volatility, trade policies, economic fluctuations, weather patterns and production variability contribute to these fluctuations. As of trend analysis, there is a positive and significant increase. The NPC value of wheat during the overall period was 0.051, it indicates that the commodity is not protected. NPC&lt;1 indicates that the commodity is exportable and possesses export competitiveness and hence the hypothesis i.e. Indian wheat has better competitiveness in the International market.