High Level Of Variability Research Articles

Surviving and thriving: How changes in teaching modalities influenced student satisfaction before, during and after COVID-19

This paper leverages analytics methods to investigate the impact of changes in teaching modalities shaped by the COVID-19 pandemic on undergraduate students’ satisfaction within a Spanish brick-and-mortar higher education institution. Unlike research that has focused on faculty- or programme-level data, this study offers a comprehensive institutional perspective by analysing large-scale data (N = 83,532) gathered from satisfaction surveys across all undergraduate courses in eight faculties from 2018 to 2021. The longitudinal analysis revealed significant changes (p < 0.05) in satisfaction indicators, particularly overall satisfaction and perceived workload. During the emergency remote teaching period, there was a significant decrease in satisfaction and high levels of variability across courses. However, a year after emergency remote teaching, with increased implementations of technology-supported online and mixed teaching modalities, satisfaction measures not only recovered but exceeded pre-COVID levels in the aforementioned indicators when the teaching modality was fully co-located. The variability of answers also reached historical lows, reflecting more uniform student experiences. These findings highlight the resilience of educators and the current higher education system and suggest a capacity to learn and improve from disruptive pedagogical changes. The study also provides insights into how data analytics can help monitor and inform the evolution of teaching practices. Implications for practice or policy Higher education institution administrators should improve the understanding of the effects derived from changes in their teaching and learning models, for example, in teaching modalities and related technology support. Student satisfaction data analytics offer useful indicators to study the impact of those effects. Higher education institutions should provide support for educators to ensure minimal deviations from expected averages of educational quality indicators regardless of the educators’ capacity to adapt to changes in the teaching models.

Филогенетика и географическое распространение скальных ящериц (Lacertidae, Reptilia) на горной системе Эльбурс

Rock lizards of the genus Darevskia have long been an important model object for study of reptile evolution. To understand the overall picture, it is important to know how bisexual and parthenogenetic species are distributed within this genus. The ranges of Caucasian species of rock lizards have been studied for a long time and in detail. However, recent attention to the species inhabiting the territory of Iran has been attracted after the description of several new species in 2013. As part of the continuation of these studies, we studied the distribution and genetic diversity of five species of lizards of the Darevskia genus along the Alborz mountain range in Iran: D. chlorogaster, D. caspica, D. defilippii, D. schaekeli and D. raddei. In the course of this, we discovered new localities of D. defilippii that are outside their known range. We assessed the phylogenetic relationships between the studied species according to the ND4 – Leu tRNA region of mitochondrial DNA and found a relatively high level of genetic variability in D. defilippii and D. chlorogaster, while D. raddei, despite its wide distribution, has low variability. In general, the phylogenetic position of the studied species is somewhat different from that described by Ahmadzadeh et al. (2013).

Genetic characterization of domestic pigs in the core zone of swine production of Argentina.

Argentina is a small player in the global pork market, contributing only 0.7% of the total production. With increasing global demand for meat, there is an opportunity for countries with an agricultural profile to grow their pork production. However, there is a need to understand the current state of the pork production sector in all aspects to inform decision-making. The aim of this study was to genetically characterize pig herds from different production strata in the primary region for pork production in the country. For this purpose, phylogenetic and genetic variability analyses were performed using the mitochondrial control region marker (n=95 pig samples). Moreover, genotyping of ryr1 and PRKAG3 genes (n=108 pig samples) were performed to evaluate the frequency of deleterious alleles for meat quality traits in the region. The results showed high levels of genetic variability in the pig herds (Hd= 0.840 ± 0.031 and π= 0.010 ± 0.001), with a creole sow and Iberian lineage standing out in the phylogeny. The genotyping of the ryr1 marker revealed the presence of the deleterious t allele in all analyzed strata. However, the RN-allele of the PRKAG3 gene was detected only in the two lower strata. This study represents the first analysis of the phylogenetic relationships among domestic pigs from Argentina and provides an initial assessment of genetic variability in the region. Additionally, the results present, for the first time, the frequency of deleterious alleles for pig production in the productive core area, demonstrating their prevalence.

Attribution of neuropsychiatric symptoms and prioritisation of evidence in the diagnosis of neuropsychiatric lupus: mixed methods analysis of patient and clinician perspectives from the international INSPIRE study.

Neuropsychiatric lupus (NPSLE) is challenging to diagnose. Many neuropsychiatric symptoms, such as headache and hallucinations, cannot be verified by tests or clinician assessment. We investigated prioritisations of methods for diagnosing NPSLE and attributional views. Thematic and comparative analyses were used to investigate how clinicians prioritise sources of evidence from a 13-item list, and explore discordances in clinician and patient perspectives on attribution. We identified high levels of variability and uncertainty in clinicians' assessments of neuropsychiatric symptoms in SLE patients. In attributional decisions, clinicians (surveys n = 400, interviews n = 50) ranked clinicians' assessments above diagnostic tests (many of which they reported were often unenlightening in NPSLE). Clinicians ranked patient opinion of disease activity last, and 46% of patients reported never/rarely having been asked if their SLE was flaring, despite experienced patients often having "attributional insight". SLE Patients (surveys n = 676, interviews n = 27) estimated higher attributability of neuropsychiatric symptoms to the direct effects of SLE on the nervous system than clinicians (p < 0.001 for all symptoms excluding mania), and 24% reported that their self-assessment of disease activity was never/rarely concordant with their clinicians. Reports of misattributions were common, particularly of non-verifiable diffuse symptoms. Terminology differed between clinicians and influenced attribution estimates. NPSLE diagnostic tests and clinician assessments have numerous limitations, particularly in detecting diffuse neuropsychiatric symptoms that can be directly attributable and benefit from immunosuppression. Our findings suggest that incorporating patient attributional insights-although also subject to limitations-may improve attribution decision-making. Consensus regarding terminology and interpretations of "direct attributability" is required.

A Model Personalization-based Federated Learning Approach for Heterogeneous Participants with Variability in the Dataset

Federated learning is an emerging paradigm that provides privacy-preserving collaboration among multiple participants for model training without sharing private data. The participants with heterogeneous devices and networking resources decelerate the training and aggregation. The dataset of the participant also possesses a high level of variability, which means the characteristics of the dataset change over time. Moreover, it is a prerequisite to preserve the personalized characteristics of the local dataset on each participant device to achieve better performance. This article proposes a model personalization-based federated learning approach in the presence of variability in the local datasets. The approach involves participants with heterogeneous devices and networking resources. The central server initiates the approach and constructs a base model that executes on most participants. The approach simultaneously learns the personalized model and handles the variability in the datasets. We propose a knowledge distillation-based early-halting approach for devices where the base model does not fit directly. The early halting speeds up the training of the model. We also propose an aperiodic global update approach that helps participants to share their updated parameters aperiodically with server. Finally, we perform a real-world study to evaluate the performance of the approach and compare with state-of-the-art techniques.

Complementary authentication of Chinese herbal products to treat endometriosis using DNA metabarcoding and HPTLC shows a high level of variability.

Traditional Chinese Medicine (TCM) is popular for the treatment of endometriosis, a complex gynecological disease that affects 10% of women globally. The growing market for TCMs has yielded a significant incentive for product adulteration, and although emerging technologies show promise to improve their quality control, many challenges remain. We tested the authenticity of two traditional Chinese herbal formulae used in women's healthcare for the treatment of endometriosis, known as Gui Zhi Fu Ling Wan (FL) and Ge Xia Zhu Yu Tang (GX). Dual-locus DNA metabarcoding analysis coupled with high-performance thin-layer chromatography (HPTLC) were used to authenticate 19 FL and six GX commercial herbal products, as well as three ad hoc prepared artificial mixtures. HPTLC was able to detect most of the expected ingredients via comparative component analysis. DNA metabarcoding was able to detect an unexpected species diversity in the products, including 38 unexpected taxa. Chromatography has a resolution for all species indirectly through the identification of marker compounds for the different species ingredients. Metabarcoding on the other hand yields an overview of species diversity in each sample, but interpretation of the results can be challenging. Detected species might not be present in quantities that matter, and without validated quantification, some detected species can be hard to interpret. Comparative analysis of the two analytical approaches also reveals that DNA for species might be absent or too fragmented to amplify as the relevant chemical marker compounds can be detected but no amplicons are assigned to the same species. Our study emphasizes that integrating DNA metabarcoding with phytochemical analysis brings valuable data for the comprehensive authentication of Traditional Chinese Medicines ensuring their quality and safe use.

A Semi-automatic Pipeline for Generation of Large Cohorts of Four-Chamber Heart Meshes.

Computational models for cardiac electro-mechanics have been increasingly used to further understand heart function. Small cohort and single patient computational studies provide useful insight into cardiac pathophysiology and response to therapy. However, these smaller studies have limited capability to capture the high level of anatomical variability seen in cardiology patients. Larger cohort studies are, on the other hand, more representative of the study population, but building several patient-specific anatomical meshes can be time-consuming and requires access to larger datasets of imaging data, image processing software to label anatomical structures and tools to create high fidelity anatomical meshes. Limited access to these tools and data might limit advances in this area of research. In this chapter, we present our semi-automatic pipeline to build patient-specific four-chamber heart meshes from CT imaging datasets, including ventricular myofibers and a set of universal ventricular and atrial coordinates. This pipeline was applied to CT images from both heart failure patients and healthy controls to generate cohorts of tetrahedral meshes suitable for electro-mechanics simulations. Both cohorts were made publicly available in order to promote computational studies employing large virtual cohorts.

A Systematic Meta-Review of Measures of Classroom Management in School Settings

The purpose of this study was to conduct a systematic meta-review with the goal of documenting the landscape of measures of classroom management in the school-based literature. Our systematic search for systematic reviews and extraction of primary studies in the classroom management research yielded 73 studies for inclusion that captured 76 different classroom management measures. We present an inclusive repository of measures from the field. Results revealed high levels of variability in aspects of both scales and observational measures across a range of domains assessed. We discuss our descriptive analysis of the landscape of classroom management measures and provide implications for future work.

Continuous agile cyber–physical systems architectures based on digital twins

Modern cyber-physical systems, for the most part, are large-scale multilevel heterogeneous distributed systems that integrate subsystems of different kinds and are built on the Internet of Things platforms, where system structure and behavior are not constant. Managing such systems and keeping them in working condition throughout their lifetime is a difficult task. The proposed article discusses one of the possible approaches to solving this problem, based on the use of well-known continuous and agile architecture paradigms. However, there are currently no effective mechanisms for implementing these paradigms. The proposed article suggests a new approach to implementing continuous agile architectures by utilizing digital twins and proposes a reference architecture for a run-time dynamic digital twin. This method is unique because it builds a series of dynamic digital twins that model the system in real time, utilizing data about system events. Build the first models using the models used in earlier stages of the system lifecycle. This gives the following opportunities: i) a way to use dynamic digital twins to implement the continuous agile architecture paradigm; ii) a generalized three-level model of the life cycle of the continuous agile architecture; iii) a reference architecture for dynamic digital twins; and iv) a set of models that are all about using dynamic digital twins. The suggested approach enables the management of heterogeneous multilevel cyber-physical systems with variable structure and behavior variability.

Translated article] Wound closure after knee and hip replacement (TKA and THA): Survey results on the clinical practice in Spain

Background and objectiveIn orthopaedic surgery, it is clear that an optimal standardised closure technique has not yet been developed. Locally, there are no objective data describing the standard surgical practice in wound closure. The aim of this study is to analyse the clinical practice of surgical wound closure in orthopaedic surgery by means of a survey of a representative local sample and thus obtain information on the context of closure in Spain. Material and MethodAn ad hoc group of specialists in orthopaedic surgery and traumatology was formed. The group of experts, after analyzing the literature, developed a questionnaire of 32 closed multiple-choice questions divided into the following blocks: hemostasis, surgical wound closure (deep, superficial, and cutaneous), and dressings. ResultsA total of 471 surgeons responded to the survey completely and with sufficient information to perform the descriptive analysis. 79% believe that ATX can influence the decrease in surgical site infection rate. 96% believe that the type of deep closure at the level of the arthrotomy could influence outcomes and complications after hip and/or knee replacements. 85% believe that the type of shallow closure at the subcutaneous level may influence outcomes and complications after hip and/or knee replacement. 64% of surgeons use single-use incisional negative pressure therapy for the treatment of surgical wound complications (seroma, prolonged drainage, dehiscence). ConclusionsThere is a high level of variability in wound closure in our setting and a low level of training on the subject. The authors recommend that the different scientific societies invest resources to improve training in this field and reduce the percentage of surgeons who are considered inadequately trained, as well as adapting closure techniques to those considered gold standard according to the evidence.

Patterns of genetic diversity and structure of Eucalyptus grandis breeding population in Kenya: Implication for genetic improvement

Eucalyptus grandis is an important commercial plantation tree species providing raw materials for many industrial products. The species is widely cultivated in the tropics because of its wood quality and adaptability to wider climatic conditions, and is currently undergoing genetic improvement in Kenya for first growth and superior wood quality. Generally, tree breeding operations involve recurrent selection of genetically superior individuals, which potentially alters genetic diversity in the breeding populations. It is therefore essential to determine the genetic diversity of breeding populations to support improvement programmes. We evaluated the genetic diversity and structure of 250 individuals from five first generation breeding populations of E. grandis in Kenya using seventeen nuclear microsatellite markers. The microsatellite markers revealed an average polymorphic information content (PIC) of 0.826, confirming their suitability for discriminating the genotypes and populations. High genetic diversity was found within all the breeding populations. The number of alleles per population (Na), observed heterozygosity (Ho), expected heterozygosity (He), and Shannon’s information index (I) averaged at 6.9, 0.801, 0.821, and 1.662, respectively. The findings indicate that the breeding population has high levels of genetic variability offering possibilities to develop advanced generation breeding programmes for the species. Furthermore, lower fixation index (F) was detected in the seed trees (-0.101) than their offspring (0.121), suggesting selection against inbred individuals between seedling and adult stages. The genetic differentiation among the breeding populations was low and non-significant (Rst = 0.017; P = 0.117), indicating close genetic relationship among the germplasm used to establish the breeding populations. The studied breeding populations are viable for genetic improvement; however, new genetic infusions are recommended to expand the gene pool in the subsequent breeding generations.

Selection Criteria for Identification of Turkey Berry (Solanum torvum) Genotypes for Variability, Heritability and Genetic Advance

Background: Breeders can determine the likelihood of passing on advantageous traits to the following generation by using heritability, which calculates the portion of phenotypic variation that can be attributed to genetic factors. Methods: The present study was conducted at College Orchard on clay loam soil in the years 2022-2023 at the Department of Vegetable Science, Horticultural College and Research Institute, TNAU, Coimbatore. The experimental orchard site at HCandRI is located in the tropical plain topography at 11 degrees north latitude, 77 degrees east longitude and 411 metres above mean sea level (MSL). There are 20 genotypes of turkey berry for variability, heritability and genetic advance study. These genotypes are collected from different areas of Tamil Nadu and other Indian states. One season measurements have been taken of the following traits: plant height, internodal length, number of branches per plant, stem girth, number of stem prickles, number of leaves, leaf area cm2, number of leaf prickles per plant, days of first flowering, number of flowers/clusters, number of flowers per plant, number of fruits/clusters, the number of fruit clusters per plant, fruit diameter, the individual fruit weight and the fresh fruit yield (gm/plant). As part of the current study, five randomly chosen plants from each genotype in each replication were tagged to record the observations. Result: The results from this study revealed that higher values of PCV, GCV, heritability and GAM are indicative of a greater influence of environmental factors, according to variability studies. These data demonstrated that there was a high level of variability for these traits in the germplasm and that selection for these traits might be successful. These data were combined with high estimates of genetic advance for traits like the number of leaf prickles per plant, number of flowers per cluster, fruit diameter, number of fruits per cluster, leaf area, stem girth, number of stem prickles per plant and internodal length. The promising accessions discovered in this study could be applied to projects aimed at improving crops, such as pre-breeding for turkey berries.

10 What Role Could Old/Heritage Genetics Play in Climate adaptation?

Abstract Creole or Criollo breeds descend directly from cattle introduced by the Spanish and Portuguese conquerors in the XVth century, being the only cattle breeds in the Americas that have endured 500 years of natural selection to local conditions. Their genetic background includes Iberian and African taurine breeds. This ancestry combined with local adaptations to a very wide variety of environments throughout all the continent created the wide spectrum of American Criollo breeds that we see today, from USA to the Patagonian region. Criollo cattle was the basis of colonial times livestock industry until they were displaced by more specialized European and cebuine type cattle breeds at the end of the 19th century. Efforts by local producers and research institutions helped to preserve Criollo populations and to avoid their extinction. Most of Criollo animals were relegated to marginal regions unsuitable for commercial breeds, which reinforced their ability to adapt to unfavorable environments. Their adaptation to different environments allowed the expression of high levels of genetic variability, being a source of hidden alleles of potential use in animal production and thus very important to study and preserve. The analysis of nuclear and cytoplasmic markers, such as SNP, microsatellites and mitochondrial DNA, has allowed estimations of genetic diversity, admixture events with other breeds, and the elucidation of genetic relationships within Criollo breeds and with European and African breeds. Criollo breeds differ considerably from each other, and most have their own identity or group with others from neighboring regions. These results indicate that Criollo breeds represent important reservoirs of cattle genetic diversity and that appropriate conservation measures should be implemented for these heritage breeds to minimize inbreeding and uncontrolled crossbreeding. Several studies have demonstrated that these animals can produce high quality meat, are more resistant to diseases and heat stress, and emphasize their high fertility, calving ease, longevity and ability to adapt to harsh environments, including arid regions. More studies are needed to elucidate the genetic basis of these traits. Properly managed, Criollo cattle “old genetics” can certainly be part of the solution to modern livestock production problems.

ChatGPT identifies gender disparities in scientific peer review

The peer review process is a critical step in ensuring the quality of scientific research. However, its subjectivity has raised concerns. To investigate this issue, I examined over 500 publicly available peer review reports from 200 published neuroscience papers in 2022–2023. OpenAI’s generative artificial intelligence ChatGPT was used to analyze language use in these reports, which demonstrated superior performance compared to traditional lexicon- and rule-based language models. As expected, most reviews for these published papers were seen as favorable by ChatGPT (89.8% of reviews), and language use was mostly polite (99.8% of reviews). However, this analysis also demonstrated high levels of variability in how each reviewer scored the same paper, indicating the presence of subjectivity in the peer review process. The results further revealed that female first authors received less polite reviews than their male peers, indicating a gender bias in reviewing. In addition, published papers with a female senior author received more favorable reviews than papers with a male senior author, for which I discuss potential causes. Together, this study highlights the potential of generative artificial intelligence in performing natural language processing of specialized scientific texts. As a proof of concept, I show that ChatGPT can identify areas of concern in scientific peer review, underscoring the importance of transparent peer review in studying equitability in scientific publishing.

ChatGPT identifies gender disparities in scientific peer review.

The peer review process is a critical step in ensuring the quality of scientific research. However, its subjectivity has raised concerns. To investigate this issue, I examined over 500 publicly available peer review reports from 200 published neuroscience papers in 2022-2023. OpenAI's generative artificial intelligence ChatGPT was used to analyze language use in these reports, which demonstrated superior performance compared to traditional lexicon- and rule-based language models. As expected, most reviews for these published papers were seen as favorable by ChatGPT (89.8% of reviews), and language use was mostly polite (99.8% of reviews). However, this analysis also demonstrated high levels of variability in how each reviewer scored the same paper, indicating the presence of subjectivity in the peer review process. The results further revealed that female first authors received less polite reviews than their male peers, indicating a gender bias in reviewing. In addition, published papers with a female senior author received more favorable reviews than papers with a male senior author, for which I discuss potential causes. Together, this study highlights the potential of generative artificial intelligence in performing natural language processing of specialized scientific texts. As a proof of concept, I show that ChatGPT can identify areas of concern in scientific peer review, underscoring the importance of transparent peer review in studying equitability in scientific publishing.

Phylogeographic inference for Bichromomyia flaviscutellata sensu stricto (Diptera: Psychodidae: Phebotominae) from the Brazilian Amazon rainforest, based on the 3' region of the COI gene.

Bichromomyia flaviscutellata (Mangabeira, 1942) sensu stricto (Diptera: Psychodidae) has been recognized as the main vector of Leishmania amazonensis in the Brazilian Amazon. For this reason, it is of paramount importance to understand the distribution of genetic diversity of populations of this vector, particularly the genetic structure and gene flow, for its management and control efforts. This study investigated the phylogeographic structure of five B. flaviscutellata s.s. populations from the central Brazilian Amazon region by analyzing 1,141 bp fragment of the 3' region of the COI gene. A total of 85 specimens of B. flaviscutellata s.s. were sequenced from Manaus (14), Rio Preto da Eva (10), Pitinga (14), Novo Airão (21), and Autazes (26); all in the state of Amazonas. The dataset yielded 59 haplotypes, most of them connected to each other in the main network. There were high levels of intrapopulation genetic variability (h = 0.945 ± 0.035 - 0.978 ± 0.054). The genetic distance values among populations varied from moderate (0.0873) to very high (0.3535), and all comparisons were significant, as well as the hierarchical analysis (ΦST = 0.2145). In contrast, these comparisons revealed a high number of shared sites (Ss = 6-34) and no difference in fixed sites (Sf = 0) among populations indicating absence of historical isolation. The Mantel test indicated that 67.92% (r = 0.6792; P = 0.06) of the genetic structure observed in B. flaviscutellata s.s. cannot be explained by the isolation-by-distance (IBD) model. This genetic structure, weakly explained by the IBD, may be due mainly by the forest habitat fragmentation and the low dispersal (flight) capacity of sand flies. Both factors could lead to population fragmentation and isolation, which promote genetic differentiation. Taken together, these findings suggest that the genetic structure observed in the studied populations of B. flaviscutellata s.s. is likely generated by microevolutionary processes acting at the population level at the present time and, therefore, evolutionary lineages were not recognized among the populations analyzed.

Disease modifying therapies in multiple sclerosis: cost-effectiveness systematic review

ObjectiveTo identify and describe cost-effectiveness studies that evaluate disease modifying therapies in the context of relapsing-remitting multiple sclerosis. MethodA systematic review of the literature was carried out by searching MEDLINE, Embase, the Cochrane Library, LILACS, the Tufts Medical Center Cost-Effectiveness Analysis Registry, the National Health Service Economic Evaluation Database and Open Grey. The search was performed in January 2018 and covered articles published between January 2010 and December 2017 The studies reviewed were payer-perspective cost-effectiveness analyses for interferon beta-1a, interferon beta-1b, glatiramer acetate, teriflunomide, fingolimod, dimethyl fumarate, natalizumab, alemtuzumab and rituximab. The Quality of Health Economic Studies instrument was used to determine the quality of the studies reviewed. Risk of bias was assessed without a standardized tool. An analysis was made of direct costs, quality-adjusted life-years and the incremental cost-effectiveness ratio. Data extraction and evaluation of information were conducted separately by each author. ResultsFour hundred one references were found; nine studies were included. A great degree of variability was identified for several methodological aspects. Two studies that applied the incremental cost-effectiveness ratio (cost) showed no first-line therapy to be cost-effective. A third study demonstrated dominance of interferon beta-1 b over placebo (USD –315,109.45) and a fourth paper showed dominance of teriflunomide over interferons and glatiramer acetate (USD –121,840.37). As regards second-line therapies, dimethyl fumarate was cost-effective in a study that compared it to glatiramer acetate and interferon beta-1a and it was dominant in another study that compared it with glatiramer acetate (USD –158,89793) and fingolimod (USD –92,988.97). In the third line of treatment, one study showed natalizumab to be cost-effective as compared with fingolimod, and another study showed alemtuzumab to be dominant over fingolimod (USD –49,221). A third trial demonstrated alemtuzumab to be dominant over natalizumab (USD –1,656,266.07). Many of the trials have sponsorship bias. Eight of the trials received a high QHES score. ConclusionsThe present paper shows that cost-effectiveness studies have high levels of methodological variability, some of them reaching contradictory results. As a result, it is not possible to determine which disease-modifying therapy is really cost-effective in the context of relapsing-remitting multiple sclerosis.

Temperature management in the intensive care unit: a practical survey from China

ABSTRACT Introduction: Temperature management is an important aspect of the treatment of critically ill patients, but there are differences in the measurement and management of temperature in different Intensive Care Units (ICUs). The objective of this study was to understand the current situation of temperature measurement and management in ICUs in China, and to provide a basis for standardized temperature management in ICUs. Methods: A 20-question survey was used to gather information on temperature management strategies from ICUs across China. Data such as method and frequency of temperature measurement, management goals, cooling measures, and temperature management recommendations were collected. Results: A total of 425 questionnaires from unique ICUs were included in the study, with responses collected from all provinces and autonomous regions in China. Mercury thermometers were the most widely used measurement tool (82.39%) and the axilla was the most common measurement site (96.47%). There was considerable variability in the frequency of temperature measurement, the temperature at which intervention should begin, intervention duration, and temperature management goals. While there was no clearly preferred drug-based cooling method, the most widely used equipment-based cooling method was the ice blanket machine (93.18%). The most frequent recommendations for promoting temperature management were continuous monitoring and targeted management. Conclusion: Our investigation revealed a high level of variability in the methods of temperature measurement and management among ICUs in China. Since fever is a common clinical symptom in critically ill patients and can lead to prolonged ICU stays, we propose that standardized guidelines are urgently needed for the management of body temperature (BT) in these patients.

Dryland Winter Wheat Production and Its Relationship to Fine-Scale Soil Carbon Heterogeneity—A Case Study in the US Central High Plains

Soil carbon plays a key role in maintaining soil quality, but its direct impact on crop yields depends on the interplay of different factors. This study aims to study fine–spatial variation soil properties and their effect on grain productivity in fallow–wheat cropping systems in the US central High Plains. We evaluate wheat yields in relation to soil macro and micronutrients, total C (TC), and texture as well as subtle variations in field elevation. To document soil–yield relationships at a fine spatial scale, soil sampling (0–15 and 15–30 cm depths) was conducted using a regular 30 m grid spacing in eleven adjacent fields. Interpolated yield maps indicated that the availability of key nutrients and textures contributed to the spatial distribution of wheat productivity. Random forest (RF) showed that these soil attributes were able to explain slightly under 30% of the spatial variation in crop yields. Our findings demonstrate that TC can often serve as a reliable proxy for delineating yield-based management zones, even in inherently low C soils. In addition, Fe, Zn, SO4-S, sand, and subtle topographic changes were also critical factors affecting wheat yield. Our results highlight that developing management zones in these soils relying exclusively on soil information is not straightforward. However, the high level of within-field spatial variability observed needs to be addressed.

An RNA interference (RNAi) target with potential to control Dothistroma needle blight

Spray-induced gene silencing (SIGS) involves exogenous spray applications of double-stranded RNA (dsRNA) molecules targeting specific genes, such as those essential to pathogens. This technique has shown great potential for controlling fungal pathogens of horticultural and agricultural plants, but few studies have evaluated its application to forest pathogens. Here we report the first demonstration of exogenous application of dsRNA molecules targeting a gene required for virulence in the foliar pine pathogen Dothistroma septosporum, the causal agent of Dothistroma needle blight (DNB). Constructs expressing sense and antisense dsRNAs were generated targeting a 509 bp fragment of the dothistromin toxin regulatory gene (DsAflR) in D. septosporum. DsAflR is required for the production of dothistromin, a phytotoxin essential for full pathogen virulence. We found that exogenous dsRNA is taken up and the RNA silencing mechanism is functional in D. septosporum through a series of in vitro and in planta trials, such as monitoring the uptake of fluorescently labelled DsAflR-dsRNA into the cell by confocal microscopy and quantifying the extent of gene silencing by quantitative Polymerase Chain Reaction (qPCR). In vitro applications of DsAflR-dsRNA to D. septosporum reduced the accumulation of DsAflR mRNA compared to controls and, in some cases, were found to be statistically significant, despite a high level of variability in the results. Our study also demonstrated a reduction in DNB symptoms on infected pine needles sprayed with DsAflR-dsRNA, which was further supported by a significant reduction in fungal biomass. This preliminary study highlights the potential for SIGS as a future management scheme for controlling the forest pathogen D. septosporum, as well as other forest pathogens.