Range Of Variation Research Articles

Role of Fe supplantation in tailoring structural, electrical conductivity, and magnetic properties in La2Ni1-xFexMnO6 double perovskites

Double perovskite system La2Ni1-xFexMnO6 (x = 0, 0.2, 0.5, 0.8 & 1.0) were developed using sol-gel method. Rietveld refinement revealed monoclinic structure (ordered) along with occurrence of rhombohedral and orthorhombic structures suggesting antisite cationic disorder. Crystallite size and average grain size of samples varied between 454 and 1058 Å and 0.774–1.429 μm respectively. XPS revealed the dual oxidation states of Ni, Fe, and Mn ions. La2NiMnO6 attained the highest DC conductivity among all compositions. The increase in DC conductivity with temperature suggested the semiconducting behavior of the samples, that explained by Thermal Activation (TA) and Variable Range Hopping (VRH) conduction mechanisms. Obtained activation energy(Edc) showed increasing trend with temperature. M-H loops exhibit a ferromagnetic nature accompanied by antiferromagnetic interactions as suggested by exchange bias and partially saturated loops. La2NiMnO6 attained the highest saturation magnetization (29.81emu/g) and decreased with Fe supplantation. The possible mechanism of tuning conductivity and magnetic properties of La2Ni1-xFexMnO6 has been discussed in detail.

Assessment of Strength and Power Capacities in Elite Male Soccer: A Systematic Review of Test Protocols Used in Practice and Research.

Strength and power represent two crucial physical qualities for the attainment of a high level of performance considering the frequency and the importance of explosive actions occurring during elite soccer match-play. Evaluation of strength and power is a multifaceted concept involving a vast array of tests and outcome variables. Nevertheless, a comprehensive and systematic search of strength and power assessment procedures in elite soccer has yet to be undertaken. The aims of this systematic review were to: (1) identify the tests and outcome variables used to assess strength and power of elite male soccer players; (2) provide normative values for the most common tests of strength and power across different playing levels; and (3) report the reliability values of these strength and power tests. A systematic review of the academic databases MEDLINE, CINAHL, SPORTDiscus, Web of Science and OVID for studies published until August 2023 was conducted, following the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were eligible for inclusion if they: (1) were original research studies, published in a peer-reviewed journal, and written in English language; (2) had the primary aim to assess strength and/or power; (3) players were male and older than 17years of age (i.e., mean age of the group); and (4) their playing level was defined as "professional", "international" or "elite". Regarding strength testing, 115 studies and 29 different tests were identified. The three most frequent strength tests were the knee extensor isokinetic strength test (58 studies), the knee flexor isokinetic strength test (55 studies) and the Nordic hamstring strength test (13 studies). In terms of power testing, 127 studies with 31 different tests were included. The three most frequent power tests were the countermovement jump with hands fixed on hips (99 studies), the squat jump (48 studies) and the vertical jump with arm swing (29 studies). The wide range of different tests and outcome variables identified in this systematic review highlights the large diversity in the employed testing procedures. The establishment of a hybrid testing approach, combining standardised and widely accepted tests for establishing normative standards and enabling comparisons across different contexts, with flexible context-specific testing batteries, has the potential to maximise the impact of testing information for practitioners. In addition, the limited reporting of reliability data across studies highlights the need for practitioners to establish their own reliability measure within their specific contexts, informing the selection of certain tests and outcome variables.

Uncovering corporate greenwashing: a predictive model based on Chinese heavy-pollution industries

Purpose As the global emphasis on environmental consciousness intensifies, many corporations claim to be environmentally responsible. However, some merely partake in “greenwashing” – a facade of eco-responsibility. Such deceptive behavior is especially prevalent in Chinese heavy-pollution industries. To counter these deceptive practices, this study aims to use machine learning (ML) techniques to develop predictive models against corporate greenwashing, thus facilitating the sustainable development of corporations. Design/methodology/approach This study develops effective predictive models for greenwashing by integrating multifaceted data sets, which include corporate external, organizational and managerial characteristics, and using a range of ML algorithms, namely, linear regression, random forest, K-nearest neighbors, support vector machines and artificial neural network. Findings The proposed predictive models register an improvement of over 20% in prediction accuracy compared to the benchmark value, furnishing stakeholders with a robust tool to challenge corporate greenwashing behaviors. Further analysis of feature importance, industry-specific predictions and real-world validation enhances the model’s interpretability and its practical applications across different domains. Practical implications This research introduces an innovative ML-based model designed to predict greenwashing activities within Chinese heavy-pollution sectors. It holds potential for application in other emerging economies, serving as a practical tool for both academics and practitioners. Social implications The findings offer insights for crafting informed, data-driven policies to curb greenwashing and promote corporate responsibility, transparency and sustainable development. Originality/value While prior research mainly concentrated on the factors influencing greenwashing behavior, this study takes a proactive approach. It aims to forecast the extent of corporate greenwashing by using a range of multi-dimensional variables, thus providing enhanced value to stakeholders. To the best of the authors’ knowledge, this is the first study introducing ML-based models designed to predict a company’s level of greenwashing.

Mixed convective heat transfer in an open cavity with fins

AbstractThis work numerically explores the mixed convective heat transfer in an open square enclosure containing conducting fins fixed to the heated vertical wall. This kind of work with fins has enormous potential due to its applications in research, engineering, and current industries. Therefore, the current work is highly significant to understand the impact of mixed convection. The external flow enters from the hole in the bottom wall and leaves from the hole in the upper wall. The left vertical wall of the enclosure is heated isothermally, and the fins are attached to the heated walls at a uniform height. Both the upper and lower walls are adiabatic, whereas the right sidewall is at a lower temperature. The non‐dimensional transport equations are resolved by using the finite element method. The study is accomplished for the wide control variables range, such as Reynolds number (50 ≤ Re ≤ 200), Richardson's number (0.1 ≤ Ri ≤ 10), the length of the fins (Lf = 0.2, 0.4, and 0.6), the size of the outlet opening (Wout = 0.1, 0.2, and 0.3), and the gaps in between the outlet hole and left heated wall (S = 0, 0.45, and 0.9). The results show that the thermal performance of the open enclosure is meaningfully affected by the control parameters. The maximum and minimum heat transfer happens when the position of the outlet opening is at the left (S = 0) and right (S = 0.9), respectively. The heat transfer improves by raising the Ri and Re, whereas increasing the fin's length and distance between the outlet opening and left wall reduces heat transfer significantly. The rises 13% with a decrease in the fin's length from 0.6 to 0.2 at Re = 200, S = 0 due to the improvement of the convection on the heated wall. Also, increases by 15% when Ri increases from 1 to 9.

PARENTAL AUTONOMY SUPPORT AND CHILD PSYCHOSOCIAL ADJUSTMENT: EXAMINING THE ROLE OF CULTURAL HIERARCHY

The studies described in this paper investigated whether cultural hierarchy plays a moderating role in the association between parental autonomy support and child psychosocial adjustment, employing samples presenting a wide range of cultural variability (parents born in 71 different nations). The participants’ cultural backgrounds, based on the parents’ birth country, were rated in terms of emphasis on hierarchical power using Schwartz’s dimensional coding system. Structural equation modelling analyses revealed no moderation effect of cultural hierarchy on the relation between parental autonomy support and child outcomes, with the exception of the relation between parental autonomy support and adolescents’ autonomous self-regulation. As expected, parental autonomy support and cultural hierarchy were significantly and negatively correlated. Parental autonomy support was often associated with indicators of youth psychosocial adjustment, whereas cultural hierarchy was generally unrelated to adjustment. These results support self-determination theory’s position on the universal benefits of autonomy support.

Immunosuppression in adult liver transplant recipients: a 2024 update from the Italian Liver Transplant Working Group.

Advances in surgical procedures and immunosuppressive therapies have considerably improved the outcomes of patients who have undergone liver transplantation in the past few decades. In 2020, the Italian Liver Transplant Working Group published practice-oriented algorithms for immunosuppressive therapy (IT) in adult liver transplant (LT) recipients. Due to the rapidly evolving LT field, regular updates to the recommendations are required. This review presents a consensus- and evidence-based update of the 2020 recommendations. The Italian Liver Transplant Working Group set out to address new IT issues, which were discussed based on supporting literature and the specialists' personal experiences. The panel deliberated on and graded each statement before consensus was reached. A series of consensus statements were formulated and finalized on: (i) oncologic indications for LT; (ii) management of chronic LT rejection; (iii) combined liver-kidney transplantation; (iv) immunosuppression for transplantation with an organ donated after circulatory death; (v) transplantation in the presence of frailty and sarcopenia; and (vi) ABO blood group incompatibility between donor and recipient. Algorithms were updated in the following LT groups: standard patients, critical patients, oncology patients, patients with specific etiology, and patients at high immunologic risk. A steroid-free approach was generally recommended, except for patients with autoimmune liver disease and those at high immunologic risk. The updated consensus- and evidence-based 2024 recommendations for immunosuppression regimens in adult patients with ABO-compatible LT address a range of clinical variables that should be considered to optimize the choice of the immunosuppression treatment in clinical practice in Italy.

Enhancing the Rationale of Convolutional Neural Networks for Glitch Classification in Gravitational Wave Detectors: A Visual Explanation

Abstract In the pursuit of detecting gravitational waves, ground-based interferometers (e.g. LIGO, Virgo, and KAGRA) face a significant challenge: achieving the extremely high sensitivity required to detect fluctuations at distances significantly smaller than the diameter of an atomic nucleus. Cutting-edge materials and innovative engineering techniques have been employed to enhance the stability and precision of the interferometer apparatus over the years. These efforts are crucial for reducing the noise that masks the subtle gravitational wave signals. Various sources of interference, such as seismic activity, thermal fluctuations, and other environmental factors, contribute to the total noise spectra characteristic of the detector. Therefore, addressing these sources is essential to enhance the interferometer apparatus's stability and precision. Recent research has emphasised the importance of classifying non-stationary and non-Gaussian glitches, employing sophisticated algorithms and machine learning methods to distinguish genuine gravitational wave signals from instrumental artefacts. The time-frequency-amplitude representation of these transient disturbances exhibits a wide range of new shapes, variability, and features, reflecting the evolution of interferometer technology. In this study, we developed a convolutional neural network model to classify glitches using spectrogram images from the Gravity Spy O1 dataset. We employed score-class activation mapping and the uniform manifold approximation and projection algorithm to visualise and understand the classification decisions made by our model. We assessed the model's validity and investigated the causes of misclassification from these results.

Is inflation targeting effective? Lessons from global financial crisis and COVID‐19 pandemic

AbstractThis paper explores the influence of inflation targeting (IT) policy on macroeconomic performance in 24 Asian economies by taking a wide range of macroeconomic variables from 2001 to 2022. Specifically, the study seeks to evaluate the influence of IT on macroeconomic performance during the global financial crisis (GFC) and the COVID‐19 pandemic periods separately. The empirical analysis comprises three approaches: propensity score matching, difference‐in‐differences, and panel‐corrected standard error methods. The empirical investigation reveals that IT significantly impacts inflation and its volatility during the GFC. In contrast, the effect on the unemployment rate is not statistically significant. Further, IT statistically influences the inflation and unemployment rates throughout the COVID‐19 pandemic. In contrast, its impact on inflation volatility during the COVID‐19 pandemic is not evident. Our results have significant policy implications for the Asian economies. It may be suggested that low‐income countries could benefit from implementing IT policy as a tool to ensure stable inflation. However, there is a need for continuous policy adaptation and targeted interventions to address evolving economic challenges, especially in situations like crises.

The revolution next door.

This paper explores the cascading influence of revolutionary moments on democracy and inequality, not at home, but across borders. We use data on revolutions and other social upheavals over the past 120years and examine their cross-national impact on a range of variables in neighboring countries. Engaging with debates on whether substantial democracy and equality increases require extraordinary circumstances, our research investigates whether revolutionary activities induce consequential spillovers, such as policy concessions from elites in neighboring contexts. In exploring spillover effects, the paper examines how significant events in one nation influence social life in adjacent ones. It encompasses an analysis of 171 countries over two centuries, connecting data on revolution with democracy and equality metrics, and hypothesizing that elite fear of revolutionary contagion may necessitate democracy and equality concessions to mitigate potential uprisings. Findings suggest neighboring revolutions positively impact domestic democracy and equality levels. We observe significant increases in an index of democracy and two indices of economic egalitarianism, although one of the egalitarianism measures is robust to all model specifications. Additionally, we find that isolated "protest-led ousters" can moderately increase suffrage and one of our indices of egalitarianism, while coups do not seem to impact democracy or inequality variables. By examining various upheaval types and outcomes across time and space, the study illuminates the causal relationship between global mobilizations and local changes, providing insights into how global events inform domestic outcomes.

COMPARISON OF THE CHEMICAL COMPOSITION AND MORPHOLOGICAL CHARACTERISTICS OF DIFFERENT CARROT VARIETIES

Carrot (Daucus carota L.) is a globally significant root vegetable, rich in bioactive and nutritional compounds. Carrot is a crop with a wide range of phenotypic variability including colour, shape, size, and other characteristics. The aim of this work was to determine and compare selected morphological traits and chemical composition of 24 carrot varieties grown under open field conditions in Slovakia. Altogether, 11 qualitative characteristics and 6 quantitative parameters were evaluated. The carrot roots were also analysed for essential chemical constituents including reducing sugars (fructose, glucose, saccharose), carotenoids, dietary fibre, dry matter, ash, and mineral compounds. A wide range of diversity in morphological characteristics and chemical composition indicates a high variability of studied varieties. The root length ranged from 59 to 205 mm, root diameter varied from 17.7 to 39.0 mm and root weight ranged from 21.0 to 74.8 g. Based on the measurement results, saccharose was the dominant sugar ranging from 1.89 to 4.67 g.100 g-1 of fresh weight, carotenoid content varied from 85.94 to 374.24 µg.g-1 of fresh weight, the amount of dietary fibre ranged from 25.67 to 36.02% of dry matter. Considerable differences were also observed in the content of macro and microelements [mg.100 g-1] ranging as follows: P (17.5 - 52.0), K (110.0 – 337.0), Na (65.9 – 186.0), Fe (0.324 – 3.340), Cu (0.042 – 0.126), Zn (0.152 – 0.945) and Mn (0.062 – 0.189). The presented results can provide useful information for carrot growers and consumers in terms of morphological characteristics as well as the chemical composition of individual carrot varieties.

COMPARISON OF THE CHEMICAL COMPOSITION AND MORPHOLOGICAL CHARACTERISTICS OF DIFFERENT CARROT VARIETIES

Carrot (Daucus carota L.) is a globally significant root vegetable, rich in bioactive and nutritional compounds. Carrot is a crop with a wide range of phenotypic variability including colour, shape, size, and other characteristics. The aim of this work was to determine and compare selected morphological traits and chemical composition of 24 carrot varieties grown under open field conditions in Slovakia. Altogether, 11 qualitative characteristics and 6 quantitative parameters were evaluated. The carrot roots were also analysed for essential chemical constituents including reducing sugars (fructose, glucose, saccharose), carotenoids, dietary fibre, dry matter, ash, and mineral compounds. A wide range of diversity in morphological characteristics and chemical composition indicates a high variability of studied varieties. The root length ranged from 59 to 205 mm, root diameter varied from 17.7 to 39.0 mm and root weight ranged from 21.0 to 74.8 g. Based on the measurement results, saccharose was the dominant sugar ranging from 1.89 to 4.67 g.100 g-1 of fresh weight, carotenoid content varied from 85.94 to 374.24 µg.g-1 of fresh weight, the amount of dietary fibre ranged from 25.67 to 36.02% of dry matter. Considerable differences were also observed in the content of macro and microelements [mg.100 g-1] ranging as follows: P (17.5 - 52.0), K (110.0 – 337.0), Na (65.9 – 186.0), Fe (0.324 – 3.340), Cu (0.042 – 0.126), Zn (0.152 – 0.945) and Mn (0.062 – 0.189). The presented results can provide useful information for carrot growers and consumers in terms of morphological characteristics as well as the chemical composition of individual carrot varieties.

Assessing Potential Bias in PFAS Concentrations in Groundwater and Surface Water Samples

AbstractPer‐ and polyfluoroalkyl substances (PFAS) encompass a large group of recalcitrant anthropogenic compounds that have been used in a variety of consumer and industrial products and processes over many decades. Drinking water standards were recently finalized for two PFAS at low nanogram per liter concentrations. Due to the widespread use of PFAS and low health‐based thresholds, a literature review and laboratory and field studies were conducted to assess several potential sources of bias in PFAS concentrations. Fluoropolymers are commonly present in equipment, products, and materials used during field sampling, potentially leading to false positive results. Laboratory results confirmed the presence of PFAS in multiple commonly used field materials. However, best practices can be used to limit pathways for cross contamination. Laboratory‐specified hold times and sample storage temperatures are scientifically founded and adequately prevent bias due to PFAS sorption to sampling containers or partial degradation of some PFAS to form others. PFAS are also known to accumulate at the air‐water interface and other interfaces. Results from laboratory and field studies indicate that PFAS enrichment in foam and in the surface microlayer does occur. However, the effect of this phenomenon is within the range of analytical and spatial sampling variability and therefore a change in sampling procedures is not needed. Findings were distilled into science‐based and practical recommendations to minimize bias during PFAS sampling without incurring unnecessary cost and effort.

Study on Genetic Variability for Forage Yield and Quality Traits in Forage Sorghum [Sorghum bicolor L. Moench

The initial research related to germplasm screening was carried out in the experimental area of Instructional Dairy Farm, GBPUAT Pantnagar during kharif season 2018. The experimental material for this experiment consisted of two hundreds and eighty diverse germplasm lines of sorghum along with six checks viz., SSG 59-3, Pant Chari- 5, Pant Chari- 6, CSV-21 F, CSH-22S, and CSV-24SS. The germplasm lines were evaluated in Augmented Block Design for nineteen forage yield related traits and thirteen quality traits. The statistical analysis for genetic variability was done using analysis of variance (ANOVA), heritability (h2), genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), and genetic advance (GA). The analysis of variance revealed that the genotypes and checks were showing a highly significant differences for all the traits under study indicated existence of inherent genetic differences among genotypes for different characters. Mean performance of forage yield and quality related traits exhibited a wide range of variability. GCV and PCV values were observed low for most of the characters whereas high for anthracnose, zonate leaf spot and shoot fly incidence. The value of genetic advance was observed high for leaf area, green fodder yield per plant, dry fodder yield per plant, hydrocyanic acid content, plant height, anthracnose, and shoot fly incidence were relatively more than other characters. Genetic advance as per cent of mean was observed low for days to maturity, dry matter per cent, in-vitro dry matter disappearance, neutral detergent fiber, acid detergent fiber, cellulose content whereas high for leaf area, flag leaf width, panicle length, panicle width, 1000-grains weight, grain yield per plant, green fodder yield per plant, dry fodder yield per plant, total soluble solids, silica content, anthracnose, zonate leaf spot and shoot fly incidence. Heritability values were found high for all the traits under study. The genotypes bearing the desired values for different genetic variability parameters and mean performance for can be exploited in future breeding programmes for the improving forage genotypes. These genotypes can be used as donor parents in crop improvement programme for improving forage yield and quality related traits along with improved resistance against anthracnose, shooty fly and zonate leaf spot.

Study on Genetic Variability for Forage Yield and Quality Traits in Forage Sorghum [Sorghum bicolor L. Moench

The initial research related to germplasm screening was carried out in the experimental area of Instructional Dairy Farm, GBPUAT Pantnagar during kharif season 2018. The experimental material for this experiment consisted of two hundreds and eighty diverse germplasm lines of sorghum along with six checks viz., SSG 59-3, Pant Chari- 5, Pant Chari- 6, CSV-21 F, CSH-22S, and CSV-24SS. The germplasm lines were evaluated in Augmented Block Design for nineteen forage yield related traits and thirteen quality traits. The statistical analysis for genetic variability was done using analysis of variance (ANOVA), heritability (h2), genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), and genetic advance (GA). The analysis of variance revealed that the genotypes and checks were showing a highly significant differences for all the traits under study indicated existence of inherent genetic differences among genotypes for different characters. Mean performance of forage yield and quality related traits exhibited a wide range of variability. GCV and PCV values were observed low for most of the characters whereas high for anthracnose, zonate leaf spot and shoot fly incidence. The value of genetic advance was observed high for leaf area, green fodder yield per plant, dry fodder yield per plant, hydrocyanic acid content, plant height, anthracnose, and shoot fly incidence were relatively more than other characters. Genetic advance as per cent of mean was observed low for days to maturity, dry matter per cent, in-vitro dry matter disappearance, neutral detergent fiber, acid detergent fiber, cellulose content whereas high for leaf area, flag leaf width, panicle length, panicle width, 1000-grains weight, grain yield per plant, green fodder yield per plant, dry fodder yield per plant, total soluble solids, silica content, anthracnose, zonate leaf spot and shoot fly incidence. Heritability values were found high for all the traits under study. The genotypes bearing the desired values for different genetic variability parameters and mean performance for can be exploited in future breeding programmes for the improving forage genotypes. These genotypes can be used as donor parents in crop improvement programme for improving forage yield and quality related traits along with improved resistance against anthracnose, shooty fly and zonate leaf spot.

Adaptive Finite-Time Prescribed Performance Control of Nonlinear Power Systems with Symmetry Full-State Constraints

Power system control is commonly based on linear controllers, where linear controllers are designed using a linearized model of the system at a specific operating point. However, when the system’s operating point is changed, the dynamic characteristics of the system shift significantly. At this point, linear controllers often fail to meet system stability requirements. Furthermore, the range of state variables in the power system is limited by the objective conditions. In addition, the power system has high-precision constraints on the deviation of the load frequency and so on. Therefore, it is worth designing a finite-time controller that satisfies the prescribed performance and full-state constraints based on the nonlinear model of the power systems. Firstly, the prescribed performance is incorporated into the barrier Lyapunov function to ensure that the tracking error is within the desired accuracy. Then, the tracking strategy is designed based on backstepping and incorporating a first-order filter to ensure that the controlled system’s signals and tracking errors remain bounded in finite time. Finally, two simulations are given to illustrate the effectiveness of the proposed control scheme, confirming that all states keep within the predefined range.

Coronary Artery Anomalies: A Computed Tomography Angiography Pictorial Review.

Coronary arteries have a wide range of anatomical variability, and their spectrum ranges from asymptomatic cases to those predisposed to hemodynamic compromise or even sudden cardiac death. This paper aims to review the classification of coronary artery anomalies (CAAs) and illustrate their imaging characteristics by highlighting the important role of CT coronary angiography. Some of the coronary anomalies usually met in current practice are the high origin coronary artery, multiple ostia, aberrant origin from the opposite/non-coronary Valsalva sinus, single coronary artery, ALCAPA syndrome, duplications of the left anterior descending artery, coronary fistulas, and extracardiac terminations. CT coronary angiography is a non-invasive diagnostic modality for CAAs. The complex anatomy of these anomalies can be accurately described by employing 3D reconstructions and post-processing techniques. Knowledge of the imaging characteristics and potential functional impact of these anomalies is essential for accurate diagnosis and therapeutic planning of patients.

A novel start-loss mutation of the SLC29A3 gene in a consanguineous family with H syndrome: clinical characteristics, in silico analysis and literature review

BackgroundThe SLC29A3 gene, which encodes a nucleoside transporter protein, is primarily located in intracellular membranes. The mutations in this gene can give rise to various clinical manifestations, including H syndrome, dysosteosclerosis, Faisalabad histiocytosis, and pigmented hypertrichosis with insulin-dependent diabetes. The aim of this study is to present two Iranian patients with H syndrome and to describe a novel start-loss mutation in SLC29A3 gene.MethodsIn this study, we employed whole-exome sequencing (WES) as a method to identify genetic variations that contribute to the development of H syndrome in a 16-year-old girl and her 8-year-old brother. These siblings were part of an Iranian family with consanguineous parents. To confirmed the pathogenicity of the identified variant, we utilized in-silico tools and cross-referenced various databases to confirm its novelty. Additionally, we conducted a co-segregation study and verified the presence of the variant in the parents of the affected patients through Sanger sequencing.ResultsIn our study, we identified a novel start-loss mutation (c.2T > A, p.Met1Lys) in the SLC29A3 gene, which was found in both of two patients. Co-segregation analysis using Sanger sequencing confirmed that this variant was inherited from the parents. To evaluate the potential pathogenicity and novelty of this mutation, we consulted various databases. Additionally, we employed bioinformatics tools to predict the three-dimensional structure of the mutant SLC29A3 protein. These analyses were conducted with the aim of providing valuable insights into the functional implications of the identified mutation on the structure and function of the SLC29A3 protein.ConclusionOur study contributes to the expanding body of evidence supporting the association between mutations in the SLC29A3 gene and H syndrome. The molecular analysis of diseases related to SLC29A3 is crucial in understanding the range of variability and raising awareness of H syndrome, with the ultimate goal of facilitating early diagnosis and appropriate treatment. The discovery of this novel biallelic variant in the probands further underscores the significance of utilizing genetic testing approaches, such as WES, as dependable diagnostic tools for individuals with this particular condition.

Lipid biomarkers and stable isotopes uncover paleovegetation changes in extremely species-rich forest-steppe ecosystems, Central Europe

The historical development of the vegetation of semi-dry grasslands in Central Europe is not satisfactorily understood. Long-term continuity of open vegetation or, conversely, deep-past forest phases are considered possible sources of the current extreme species diversity of these ecosystems. We aimed to reveal the trajectory of paleovegetation development in these ecosystems through detailed analysis of terrestrial in-situ soil geoarchives. We measured the bulk soil carbon and nitrogen contents, lipid molecular distribution, and compound-specific stable carbon and hydrogen isotopic signatures of mid- and long-chain n-alkanes extracted from soil and modern plant material tissues (i.e., deciduous and Pinus leaves and grass/herbaceous species).The C23-C33 n-alkane homologues were identified in soils with different abundances. Normally, C27 and C29 n-alkanes were the most abundant homologues in tree-leaf samples, while grass-derived n-alkanes were mostly C31 and C33 homologues. Soils were largely dominated by C29 and C31 n-alkanes. Odd-numbered C27-C33 soil n-alkane δ13C values ranged from -36.2‰ to -23.2‰, whereas their δ2H values showed a wider range of variability that fluctuated from -224‰ to -172‰. Molecular distribution in combination with radiocarbon analysis of soil organic matter (SOM) and δ13C and δ2H values of n-alkanes revealed a large contribution of C3 trees (both deciduous and coniferous trees/pine trees) as the main source of n-alkanes between the late Pleistocene and early Holocene (ca 15,000–8,200 calibrated year before present/cal year BP). A clear shift toward more grassy/herbaceous vegetation was observed from the early Holocene (ca 11,700–8,200 cal year BP) onwards. Distribution patterns of lipids and soil geochemical parameters showed that plants are the main source of SOM and that biodegradation and kinetic isotope fractionation are not the main reasons for 13C enrichment in soil profiles. Past C3 vegetation shifts as well as paleoclimate changes (i.e., aridity) can have played a role in the observed 13C depth profiles.

Study of heart rate and corticosterone variability in the simulation of rhino-surgical interventions in biological objects.

Aims: to assess changes in the time range of heart rate variability (HRV) and plasma corticosterone concentration in rats after simulating septoplasty. Materials and methods: a septoplasty was simulated in 30 mature male Wistar rats weighing 210-290 g. An ECG was recorded with subsequent analysis of the time domain of HRV, as well as blood sampling for changes in the concentration of corticosterone in the blood plasma. Results: SDNN significantly increased in comparison with the control on days 2 and 3 (p <0.001), but decreased on days 4-5 (p <0.001) and 6 days (p <0.01 ). rMSSD changed in waves with two irregular peaks on days 1 and 6. SDNN / rMSSD, in comparison with the 1st day of the postoperative period, increased on the 2nd day and continued to grow (p <0.05), and on the 4th day it began to decrease (p <0.01). The total power of HRV was low throughout the postoperative period (p <0.001), except for the 3rd day, when it was equal to the control data. The increase in the total power indicator fell on the 3rd day after the operation (p <0.01), after which its decline occurred again. The concentration of corticosterone in the blood plasma in rats was significantly higher than before (p <0.001). From the 2nd to the 4th postoperative day, its plateau was determined. Conclusion: Simulation of septoplasty leads to changes in the time range of HRV, an increase in the concentration of corticosterone in the blood plasma in rats with its maximum at the time of surgery and after 24 hours, the formation of a "plateau" from the 2nd to the 4th postoperative days, which coincides with changes of HRV.

Garden of forking paths in ERP research - Effects of varying pre-processing and analysis steps in an N400 experiment.

This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility of ERP studies. Here, we applied a multiverse analysis to a sample ERP N400 dataset, donated by an independent research team. We analyzed this dataset using 14 pipelines selected to showcase the full range of methodological variability found in the N400 literature using systematic review approach. The selected pipelines were compared in depth by looking into statistical test outcomes, descriptive statistics, effect size, data quality, and statistical power. In this way we provide a worked example of how analytic flexibility can impact results in research fields with high dimensionality such as ERP, when analyzed using standard null-hypothesis significance testing. Out of the methodological decisions that were varied, high-pass filter cut-off, artifact removal method, baseline duration, reference, measurement latency and locations, and amplitude measure (peak vs. mean) were all shown to affect at least some of the study outcome measures. Low-pass filtering was the only step which did not notably influence any of these measures. This study shows that even some of the seemingly minor procedural deviations can influence the conclusions of an ERP study. We demonstrate the power of multiverse analysis in both identifying the most reliable effects in a given study, and for providing insights into consequences of methodological decisions.