Browse Articles

Utilizing MV-FLOW™ and multidimensional ultrasound characteristics for prognosticating FET outcomes in RIF patients: Study Protocol for a cross-sectional study

Recurrent implantation failure (RIF) is a common issue in frozen-thawed embryo transfer (FET). Prior to transfer, uterine endometrial receptivity of FET patients can be assessed using multimodal transvaginal ultrasound indicators to predict the success rate of the current FET cycle. Endometrial blood flow is a crucial element in evaluating endometrial receptivity. MV-FLOW™ is an advanced two-dimensional superb microvascular imaging technology that can detect and display blood flow in micro-vessels. The data for this study were obtained from an ongoing cross-sectional study comprising 323 RIF patients and 323 first implantation (FI) patients, who underwent transvaginal ultrasound before FET. We collected basic clinical data and multimodal ultrasound data from these patients as predictive features, with clinical pregnancy as the predictive label, for model training. Based on the above, this study aims to establish and validate a clinical prediction model for FET outcomes using support vector classification (SVC) algorithms, based on MV-FLOW™ and multidimensional transvaginal ultrasound imaging features. The objective is to determine the predictive role of multimodal transvaginal ultrasound in embryo transfer outcomes and provide evidence for the clinical application of MV-FLOW™. Trial registration: Trial Registration: ChiCTR2400086401.

Unsupervised monocular depth estimation with omnidirectional camera for 3D reconstruction of grape berries in the wild

Japanese table grapes are quite expensive because their production is highly labor-intensive. In particular, grape berry pruning is a labor-intensive task performed to produce grapes with desirable characteristics. Because it is considered difficult to master, it is desirable to assist new entrants by using information technology to show the recommended berries to cut. In this research, we aim to build a system that identifies which grape berries should be removed during the pruning process. To realize this, the 3D positions of individual grape berries need to be estimated. Our environmental restriction is that bunches hang from trellises at a height of about 1.6 meters in the grape orchards outside. It is hard to use depth sensors in such circumstances, and using an omnidirectional camera with a wide field of view is desired for the convenience of shooting videos. Obtaining 3D information of grape berries from videos is challenging because they have textureless surfaces, highly symmetric shapes, and crowded arrangements. For these reasons, it is hard to use conventional 3D reconstruction methods, which rely on matching local unique features. To satisfy the practical constraints of this task, we extend a deep learning-based unsupervised monocular depth estimation method to an omnidirectional camera and propose using it. Our experiments demonstrate the effectiveness of the proposed method for estimating the 3D positions of grape berries in the wild.

Unique North American isolates of severe metastatic hypervirulent Klebsiella pneumoniae strain infections with hepatic abscesses seen in young patients within Texas

Rationale Hypervirulent Klebsiella pneumoniae (hvKp) infections have principally been identified in Asia. Within a two-month period, two patients between the ages of 30 to 50 years old presented to a tertiary referral hospital in Texas with septic shock, hepatic abscess, and septic thrombophlebitis. Blood cultures were positive for Klebsiella pneumoniae (isolates 2020CK-00441 and 2021CK-00720 respectively). The first patient survived after a prolonged hospital course while the second patient expired. Objectives Describe the clinical presentation of these two patients. Perform whole genome sequencing and bioinformatic analysis to evaluate potential outbreak of specific hvKp bacteria isolates. Methods Whole genome sequencing was performed using both paired-end Illumina MiSeq and nanopore sequencing to obtain a Completed genome for both isolates. Main results 2020CK-00441 belonged to ST23 type while 2021CK-00720 was a ST65 type isolate. Kleborate analyses predicted with high confidence both isolates were hvKp. Phylogenetic analyses showed the two strains are not closely related to each other nor to any known hvKp isolates reported. Both isolates had yersiniabactin, colibactin, aerobactin and salmochelin producing loci which likely confer these isolates hvKp phenotype. 2020CK-00441 and 2021CK-00720 had a unique pK2044 like plasmid. Conclusions HvKp strains capable of causing devastating metastatic septic infections have emerged in Texas. These isolates are unique compared to other hvKp strains globally. Country-wide surveillance and whole genome sequencing of these strains is essential to prevent a major public health emergency in the USA.

Study on disaster-causing probability evaluation of gas pipeline in karst area

In this paper, a disaster-causing probability evaluation method of gas pipelines in karst areas based on disaster system theory and vulnerability theory is proposed. The hazard evaluation index system of gas pipeline disaster events in karst areas is established from three aspects: the activity of disaster-prone environment, the risk of disaster factors and the vulnerability of disaster-bearing bodies. Combined with the advantages of information transmission and updating of the Bayesian network model, the hazard probability of disaster events is gradually calculated from a multi-level perspective. Based on the structural reliability theory, the vulnerability evaluation function of gas pipelines in karst areas is established by considering the interaction between disaster hazard intensity and disaster resistance ability. Meanwhile, the design checkpoint method and finite element simulation are used to calculate the vulnerability probability. Finally, a new disaster-causing probability evaluation approach for gas pipelines in karst areas is formed, which comprehensively considers the event hazard and the pipeline vulnerability. The work presented in this paper can provide a reference for the safety management and accident prevention of gas pipelines crossing the karst areas.

A CACTA-like transposon in the Anthocyanidin synthase 1 (Ans-1) gene is responsible for apricot fruit colour in the raspberry (Rubus idaeus) cultivar ‘Varnes’

Cultivated raspberries (Rubus idaeus L.) most commonly bear small, red, highly aromatic fruits. Their colour is derived predominantly from anthocyanins, water soluble polyphenolic pigments, but as well as red forms, there exist cultivars that display yellow- and apricot-coloured fruits. In this investigation, we used a multi-omics approach to elucidate the genetic basis of the apricot fruit colour in raspberry. Using metabolomics, we quantified anthocyanins in red and apricot raspberry fruits and demonstrated that, in contrast to red-fruited raspberries, fruits of the apricot cultivar ‘Varnes’ contain low concentrations of only a small number of anthocyanin compounds. By performing RNASeq, we revealed differential expression patterns in the apricot-fruited ‘Varnes’ for genes in the anthocyanin biosynthesis pathway and following whole genome sequencing using long-read Oxford Nanopore Technologies sequencing, we identified a CACTA-like transposable element (TE) in the second exon of the Anthocyanidin synthase (Ans) gene that caused a truncated predicted ANS protein. PCR confirmed the presence in heterozygous form of the transposon in an unrelated, red-fruited cultivar ‘Veten’, indicating apricot fruit colour is recessive to red and that it may be widespread in raspberry germplasm, potentially explaining why apricot forms appear at regular intervals in modern raspberry breeding populations.

Cerebrovascular accidents association between serum trace elements and toxic metals level, a case-control study

Background Cerebrovascular accidents (CVAs) are among the most common complications of patients today. As the prevalence of ischemic CVAs rises, detecting related risk factors is crucial. Metal concentration has previously been considered a major risk factor in several neural complications, and in this study, we will investigate this. Methods In this case-control study, 70 CVA (clinically approved ischemic stroke cases by imaging and NIH Stroke Scale (NIHSS)) and 70 individuals with no history of CVA controls were enrolled as the control group. The serum level of several metals, including Fe (Iron), Co (Cobalt), Ni (Nickel), Cu (copper), Zn (Zinc), Mn (Manganese), Pb (lead), Hg (Mercury), has been assessed using Inductively coupled plasma mass spectrometry (ICP-MS) method. Logistic regression (LR) has also been used to determine the association between metals’ levels and CVA occurrence. Results As the mean age of the CVA group was 48.68  ±  15.25 years and for the non-CVA group was 47.89 ± 9.65 years, the result indicated that the serum level of Cu and Pb has been statically higher in the CVA group (respectively; P  <  0.001 and P  =  0.002) and Ni level was significantly lower (P  =  0.003). Other measured metals’ levels (Fe, Co, Ni, Mn, Hg) were not significantly different between CVA and non-CVA groups. In the LR model, all Cu, Pb, and Zn metals had a P value of 0.03 and an odd ratio (OR) and confidence interval (CI) of 1.34 (1.02–1.75), 1.19 (1.01–1.39) and 1.01 (1.001–1.02) respectively. Conclusion Given that some metals are associated with a higher risk of CVA, researchers and physicians must better understand the risk factors and causes of the burden of CVA. However, further studies with a larger population and investigation of the exact pathogenesis of these metals are needed.

The Interfaces Twitter Elections Dataset: Construction process and characteristics of big social data during the 2022 presidential elections in Brazil

The main objective of this study is to describe the process of collecting data extracted from Twitter (X) during the Brazilian presidential elections in 2022, encompassing the post-election period and the event of the attack on the buildings of the executive, legislative, and judiciary branches in January 2023. The work of collecting data took one year. Additionally, the study provides an overview of the general characteristics of the dataset created from 282 million tweets, named “The Interfaces Twitter Elections Dataset” (ITED-Br), the third most extensive dataset of tweets with political purposes. The process of collecting and creating the database for this study went through three major stages, subdivided into several processes: (1) A preliminary analysis of the platform and its operation; (2) Contextual analysis, creation of the conceptual model, and definition of Keywords and (3) Implementation of the Data Collection Strategy. Python algorithms were developed to model each primary collection type. The “token farm” algorithm, was employed to iterate over available API keys. While Twitter is generally a “public” access platform and fits into big data standards, extracting valuable information is not trivial due to the volume, speed, and heterogeneity of data. This study concludes that acquiring informational value requires expertise not only in sociopolitical areas but also in computational and informational studies, highlighting the interdisciplinary nature of such research.

Do health professionals know about overdiagnosis in screening, and how are they dealing with it? A mixed-methods systematic scoping review

Introduction Medical screening is a major driver of overdiagnosis, which should be considered when making an informed screening decision. Health professionals (HPs) often initiate screening and are therefore responsible for informing eligible screening participants about the benefits and harms of screening. However, little is known about HPs’ knowledge of overdiagnosis and whether they are prepared to inform screening candidates about this risk and enable people to make an informed screening decision. Methods This is a systematic review of studies examining HPs’ knowledge and perception of overdiagnosis, whether it affects their position on offering screening, and their willingness to inform screening candidates about overdiagnosis. We conducted systematic searches in MEDLINE, Embase, Web of Science, Scopus, CINAHL, and PsycArticles without language restrictions. Two authors analysed the qualitative and quantitative data separately. Confidence in the findings of the qualitative data was assessed using the GRADE-CERQual approach. Results We included 23 publications after screening 9786 records. No studies directly examined HPs’ knowledge of overdiagnosis. HPs’ perceptions of overdiagnosis varied widely, from considering it a significant harm to seeing it as negligible. This seems linked to their overall beliefs about the benefits and harms of screening and to their position on offering screening, which varies from discouraging to actively promoting it. HPs also hold diverging approaches to informing screening candidates about overdiagnosis, from providing detailed explanations to limited or no information. Conclusion There is a lack of research on HPs’ knowledge of overdiagnosis, however, HPs who do know about overdiagnosis attribute substantially different levels of harm to it. This seems intertwined with their overall beliefs about the benefits of screening, their position towards offering screening, and their willingness to inform screening candidates about overdiagnosis. This has important implications for the public’s right to evidence-based information and compromises an individual’s right to make an informed screening decision.

A meta-analysis of the impact of TOE adoption on smart agriculture SMEs performance

Background Agricultural SMEs face distinct challenges due to factors such as weather, climate change, and commodity price changes. Technology has become essential in helping SMEs overcome these challenges and grow their businesses. The relationship between technology and SMEs in the agriculture sector covers various aspects, such as using hardware and software, digital applications, sensors, and e-commerce strategies to be examined in further depth through literature study. Problem statement The implementation of the TOE (technology, organization, and environment) framework in smart agriculture faces several challenges. To overcome these challenges, an integrated approach is needed that involves technological capacity building, organizational management changes, and adequate policy and infrastructure support to help SMEs in the agricultural sector develop their businesses. Objectives This research aims to demonstrate and identify how TOE plays an important role in the performance of SMEs, particularly with regard to agriculture in order to improve agricultural productivity, efficiency, and sustainability while enabling access to broader markets in several countries. This study employs a meta-analysis method using a quantitative approach taken by each publication, which typically used SEM. Methods PRISMA technique was used to examine evidence from clinical trials, and clinical significance was determined using the GRADE approach. Statistical analysis was performed using the Fisher test to combine the results of several studies and Cohen’s approach to interpreting effect sizes. Findings The results of this study are in line with the findings of 27 previous studies which showed a direct positive relationship between TOE construction and the performance of agricultural SMEs, with variables including technological factors, organizational factors, environmental factors, and SME performance. The synergy between technology adoption by agricultural SMEs and Industry 4.0 can increase connectivity and automation in the agricultural sector. However, it is important to remember that adopting TOE to realize the smart agriculture concept has its own challenges and risks, such as resource management (technology), good organizational management (organization), and internal and external organizational environments (environments), including intense competition Research implication TOE adoption improves access to information about competitors and customers, providing practitioners and decision-makers with a clearer understanding. It enables focus on factors with a significant impact on TOE adoption, so that they are more independent in developing effective business concepts that are adaptive to the era of agricultural technology 4.0.

Development of an expectation management intervention for patients with Long COVID: A focus group study with affected patients

Background A significant number of individuals who have contracted SARS-CoV-2 report persistent somatic symptoms after the infection has resolved. Evidence-based treatment options for Long COVID are lacking to date. To ensure that an expectation management intervention, designed for the research project SOMA.COV, addresses relevant patient needs as well as to promote treatment acceptance and adherence, a participatory approach was chosen. Objective The aim of the present study was to explore needs and wishes of patients with Long COVID regarding the preliminary version of an expectation management intervention and to thereby inform the further development of the treatment manual. Methods Twenty-two patients affected by Long COVID participated in one of four focus groups in June and July 2023. Participants were presented with the draft content of a four-session expectation management intervention. Feedback was audio-recorded, transcribed, and analyzed using thematic analysis. Results Thirteen themes relating to the main components of the intervention manual were developed. Large parts of the manual received overall positive feedback, including psychoeducation on the biopsychosocial etiology of the condition, elements of cognitive restructuring, and an imagination exercise. Patients’ response to the presented vicious circle of fear and a behavior change exercise was mixed. Modifications to the manual were made in response to patients’ feedback. Conclusion Patients with Long COVID provided positive feedback on an expectation management intervention while also highlighting important adaptations necessary for this patient group. The study results informed the finalization of the treatment manual within the SOMA.COV project, which investigates the effectiveness of this intervention for patients with Long COVID in a three-armed randomized controlled trial.

Hypergamy reconsidered: Marriage in England, 1837–2021

It is widely believed that women value social status in marital partners more than men, leading to female marital hypergamy (“marrying up”), and more female intergenerational social mobility. Using evidence from more than 33 million marriages and 67 million births in England 1837–2021 we show that within this era there was never significant hypergamous marriage by women. The average status of women’s fathers equaled that of their husbands’ fathers. For marriages 1912–2007 the average social status of female surnames equaled that of male. This was true also for parent surnames of children. Consistent with this, there was no differential tendency in England of men and women to marry by family status. There is also ancillary evidence that physical attraction cannot have been the significant determinant of matching in marriages in any period 1837–2021, based on the very strong correlation observed in underlying social status for marital partners throughout these years.

And growth on form? How tissue expansion generates novel shapes, colours and enhance biological functions of Turing colour patterns of Eukaryotes

Evidenced in zebrafishes skin and Mimulus petal, Turing-like mechanisms are probably responsible for many periodic color patterns of Eukaryotes. They are characterized by the mathematical relationships linking their cellular or molecular actors, the periodicity and the geometrical range of the patterns they produce: spots, stripes or mazes. Nevertheless, some periodic patterns such as leopard iconic rosettes required additional ingredients to explain their formation. Growth being the main candidate, we extensively explore its multiple facets, at the Eukaryotes scale. We show that far beyond the particular feline coat pattern, putative-growth Turing color patterns are present in many diverse lineages of plants and animals and seem absent in Fungi and unicellular lineages. Using models, we show the many ways growth can induce new shapes and colors, and that putative-growth pattern locations correlates with tissue hot spots of growth, suggesting the latter as the underlying mechanism. By reverse reasoning, we show that growth effects could reveal crucial information about pattern formation. We show how putative growth patterns can contribute to influence organisms visibility, thereby improving camouflage or aposematism. Our results demonstrate the range of morphogenetic roles that tissue expansion can take, by interacting with a scale-sensitive mechanism, here Turing-like patterning. Considering this extensive overview of its biological importance, both qualitatively and quantitatively, links between growth and form might more than ever needed to be explored.

Association of adenylate cyclase activity in vasopressor-type neurally mediated syncope based on the α2b-AR gene

Neurally mediated syncope (NMS) arises from a neural reflex; however, its underlying cause remains unknown. Previous research has shown that variations in the Gi-α signal transduction rate led to changes in adenylate cyclase (AC) activity levels. Thus, we hypothesized that these fluctuations in AC activity could contribute to NMS. This study aimed to investigate the receptor genes associated with glutamate (Glu) repeat polymorphism sites Glu12 and Glu9 in the α2B-AR gene. A total of 50 patients with vasodepressor-type (VT)-NMS and 20 healthy volunteers were included in this study. We assessed AC activity levels and blood pressure responses during the head-up tilt (HUT) test and conducted a Glu repeat polymorphism analysis to explore its potential association with NMS. Our findings showed significantly higher AC activity in patients with the Glu12/12 homotype than healthy volunteers across all four HUT test points. Conversely, patients with the Glu9/12 heterotype exhibited a significant difference only 10 min after the test initiation, suggesting a pronounced activation effect of the β2-AR Gs-α subunit in these individuals. Both genotypes displayed the greatest blood pressure fluctuations under 70° tilt stress, with patients with Glu12/12 showing consistent cardiac load and higher values than those with Glu9/12 at two points. Notably, the frequency of NMS onset within 20 min during the tilt test varied, with one Glu12/12 patient and seven Glu9/12 patients experiencing syncope. Additionally, patients with the Glu9/12 heterotype were found to have a higher risk of syncope after prolonged standing compared to those with the Glu12/12 homotype. These results suggest that patients with the Glu12/12 homotype exhibit elevated AC activity levels, which may help increase blood pressure to prevent syncope. This study underscores that variations in AC activity among different gene types could influence the frequency of NMS onset during standing.

Shedding light on development: Leveraging the new nightlights data to measure economic progress

Nightlights (NTL) have been widely used as a proxy for economic activity, despite known limitations in accuracy and comparability, particularly with outdated Defense Meteorological Satellite Program (DMSP) data. The emergence of newer and more precise Visible Infrared Imaging Radiometer Suite (VIIRS) data offers potential, yet challenges persist due to temporal and spatial disparities between the two datasets. Addressing this, we employ a novel harmonized NTL dataset (VIIRS + DMSP), which provides the longest and most consistent database available to date. We evaluate the association between newly available harmonized NTL data and various indicators of economic activity at the subnational level across 34 countries in sub-Saharan Africa from 2004 to 2019. Specifically, we analyze the accuracy of the new NTL data in predicting socio-economic outcomes obtained from two sources: 1) nationally representative surveys, i.e., the household Wealth Index published by Demographic and Health Surveys, and 2) indicators derived from administrative records such as the gridded Human Development Index and Gross Domestic Product per capita. Our findings suggest that even after controlling for population density, the harmonized NTL remain a strong predictor of the wealth index. However, while urban areas show a notable association between harmonized NTL and the wealth index, this relationship is less pronounced in rural areas. Furthermore, we observe that NTL can also significantly explain variations in both GDP per capita and HDI at subnational levels.

Prevalence of communicable, non-communicable diseases, disabilities and related risk factors in Khyber Pakhtunkhwa Pakistan: Findings from the Khyber Pakhtunkhwa Integrated Population and Health Survey (2016–17)

Introduction Pakistan is facing a triple burden of diseases: communicable diseases (CDs), non-communicable diseases (NCDs) and disabilities. There is limited evidence on the patterns of these diseases in Pakistan, specifically Khyber Pakhtunkhwa. Additionally there remains limited study on the impact of sex-, age and setting-stratified morbidities in Khyber Pakhtunkhwa. Objectives The objective of this study was to present the demographic characteristics and the burden of locally-specific CDs (hepatitis B and C, TB, AIDS), NCDs (diabetes, renal diseases, asthma, epilepsy, coronary heart diseases, cancer, hypertension, cholesterol, thalassemia), and disabilities (congenital, post-disease, post-injury, paralysis) stratified by sex, age and setting in the Khyber Pakhtunkhwa province of Pakistan. Material and methods The Khyber Pakhtunkhwa Integrated Population and Health Survey (KP-IPHS) was conducted in 2016–17 to gather comprehensive information about the demographic characteristics and locale-specific health-related issues of the people of Khyber Pakhtunkhwa, Pakistan. This cross-sectional survey was conducted in 24 districts across all 7 divisions of Khyber Pakhtunkhwa on population ageing ≥18 years. A total of 20704 respondents were taken from primary (n = 1061) and secondary sampling units (n = 15724), designed with considerations for urban/rural and socio-economic status. Each primary unit included 250–300 households. The sample selection utilised a multi-staged stratified systematic cluster sampling technique, involving the inclusion of every 16th household in rural areas and every 12th household in urban areas. Observations were recorded on demographics, quality of life, physical activity, BMI, disabilities, CDs and NCDs. Results Among all NCDs, hypertension has the highest prevalence (29.2%), showing a significant difference between females (32.7%) and males (25.0%). The proportion of males and females with diabetes is 7.4% and 5.2%, respectively, with a more substantial percentage (11.2%) observed in the ≥50 years’ age group compared to 2.5% in the 18–29 years’ age group and 5.0% in the 30–49 years’ age group. Among the included CDs, hepatitis B and C (0.5% and 0.8%, respectively) are most prevalent. Hepatitis B is more common in females (0.8%) and in rural settings (0.6%) compared to males (0.3%) and urban settings (0.2%), respectively. The prevalence of congenital disabilities is the highest of all disabilities, with a significantly high prevalence in females (5.3%) and rural settings (3.5%) compared to males (0.9%) and urban settings (0.6%) respectively. Furthermore, post-injury, post-disease disabilities, and paralysis significantly increase with age (P < 0.001). Conclusions Our findings show that the prevalence of CDs, NCDs and disabilities varies across sex, age and settings, with a notable prevalence in females and the old-age population (≥50 years). The results emphasise the necessity of public health efforts, such as screening, prevention, and treatment, to tackle the triple burden of CDs, NCDs, and disabilities in Khyber Pakhtunkhwa Pakistan.

Correction: Can network attention effectively stimulate corporate ESG practices?—Evidence from China

Intelligent manufacturing policy, ESG performance, and total factor productivity: Evidence from China

Under the global wave of intelligence, intelligent manufacturing has become a crucial means of transforming and upgrading China’s manufacturing industry. Accurate evaluation of the implementation effects of intelligent manufacturing industry policies is an urgent issue. This study uses the introduction of the “Made in China 2025” policy as a quasi-natural experiment and employs the difference-in-differences method to investigate the impact of intelligent manufacturing policies on firms’ total factor productivity (TFP) and its mechanisms. These results indicate that implementing intelligent manufacturing policies significantly enhances firms’ TFP. Mechanism analysis reveals that intelligent manufacturing policies can improve firms’ ESG performance by enhancing green technology innovation capabilities, increasing capital market attention, and reducing internal control costs, thereby enhancing firms’ TFP. Heterogeneity analysis finds that intelligent manufacturing policies have a more pronounced effect on promoting TFP in large-scale enterprises, labor-intensive enterprises, firms with higher technical employee levels, companies in highly competitive industries, and enterprises in regions with higher levels of digital infrastructure development and lower economic development as compared to their counterparts. This study provides evidence of how intelligent manufacturing policies drive the high-quality and sustainable development of enterprises and offers insights for future policy formulation and implementation.

Adaptive wavelet base selection for deep learning-based ECG diagnosis: A reinforcement learning approach

Electrocardiogram (ECG) signals are crucial in diagnosing cardiovascular diseases (CVDs). While wavelet-based feature extraction has demonstrated effectiveness in deep learning (DL)-based ECG diagnosis, selecting the optimal wavelet base poses a significant challenge, as it directly influences feature quality and diagnostic accuracy. Traditional methods typically rely on fixed wavelet bases chosen heuristically or through trial-and-error, which can fail to cover the distinct characteristics of individual ECG signals, leading to suboptimal performance. To address this limitation, we propose a reinforcement learning-based wavelet base selection (RLWBS) framework that dynamically customizes the wavelet base for each ECG signal. In this framework, a reinforcement learning (RL) agent iteratively optimizes its wavelet base selection (WBS) strategy based on successive feedback of classification performance, aiming to achieve progressively optimized feature extraction. Experiments conducted on the clinically collected PTB-XL dataset for ECG abnormality classification show that the proposed RLWBS framework could obtain more detailed time-frequency representation of ECG signals, yielding enhanced diagnostic performance compared to traditional WBS approaches.

Disorders in brassinosteroids signal transduction triggers the profound molecular alterations in the crown tissue of barley under drought

The advanced molecular tools provide critical inputs in uncovering the regulatory mechanisms underlying plants’ adaptation to abiotic stress. Presented holistic studies were done on the barley crown tissue being essential for plant performance under various environmental stimuli. To investigate the effect of brassinosteroids (BRs), the known players in stress management, on molecular response of this tissue to drought, the genotypes with different BRs signal transduction efficiency were employed. Large-scale transcriptomic and proteomic profiling confirmed the specific re-modeling of behavior of the BRs-insensitive barley uzu1.a mutant under drought. On the other hand, a set of genes expressed independently of the genotype was identified, including dehydrin encoding genes. This study also uncovered the candidate genes to be linkers of phytohormones crosstalk. Importantly, we detected the converging upregulation of several proteins and encoding genes under drought, including late embryogenesis abundant proteins and chaperones; they represent a promising target for cereals’ improvement. Moreover, the greatest variation between genotypes in accumulation of BRs in the crown tissue exposed to drought was observed for castasterone. Presented multi-omics, high-throughput results enhanced the understanding of molecular response to drought in crown tissue. The new insight was provided into the relationships between gene expression, protein and phytohormone content in barley plants of different BRs signaling.

Translation, content validity and internal structure of the Brazilian version of the Adolescent Resilience Questionnaire (B-ARQ)

Resilience refers to one’s ability to face life’s challenges and achieve positive outcomes, and has drawn increasing interest from researchers and policymakers. The Adolescent Resilience Questionnaire (ARQ) is a measure that assesses resilience in adolescents according to a multidimensional perspective, encompassing its several different domains. This cross-sectional study aimed to translate and evaluate the measurement properties of the Brazilian version of the ARQ (B-ARQ) for use with Brazilian adolescents. Two native speakers in Brazilian Portuguese language who were also fluent in English language translated the ARQ from English into Portuguese. A committee of experts in validation studies compared the translated versions. A summarized version was produced and back-translated by a translator native of the English language and fluent in Portuguese. The B-ARQ was pre-tested in a sample of 21 adolescents. An expert committee considered the suggestions and defined the final version of the instrument, which was tested in a sample of 210 adolescent students from public and private schools in the city of Dom Pedrito, Brazil. All students filled out the 88-item instrument as well as a socio-demographic questionnaire. Statistical analysis included descriptive statistics of all variables (frequency distribution, floor, ceiling effects), internal consistency, and confirmatory factor analysis of the version with 88 items and the shortened version with 49 items. The short version with 49 items was validated in a cross-sectional study in an adolescent population of high school students using exploratory factor analysis in the Unites States. The 88-item ARQ had poor structural validity with unsatisfactory model fit indices. Therefore, the investigation focused on the short 49-item version of the ARQ (B-ARQ-SV). The final model presented satisfactory RMSEA = 0.042 (p = 0.994, 90% CI: 0.037–0.047) and SRMR of 0.076, despite the low CFI (0.878). The internal consistency was estimated with McDonald’s Omega for each factor: Confidence (ω = 0.480), Negative Cognition (ω = 0.588), Empathy/tolerance (ω = 0.295), Emotional insight (ω = 0.425), Social Skill (ω = 0.235), Family Domain Connectedness (ω = 0.785), Family Domain Availability (ω = 0.847), Peers Domain Connectedness (ω = 0.719), Peers Domain Availability (ω = 0.402), School Domain Supportive environment (ω = 0.677), School Domain Connectedness (ω = 0.013), Community Domain Connectedness (ω = 0.791). One scale showed a ceiling effect (frequency higher than 15.0%), but we identified no critical floor effect. The B-ARQ-SV is a valid (in terms of content and structural validity) and reliable (in terms of internal consistency) measurement instrument to assess resilience in Brazilian adolescents.