Dissection of the Genetic Basis of Genotype by Environment Interactions for Morphological Traits and Protein Content in Winter Wheat Panel Grown in Morocco and Spain.

To fulfill the growing demand for wheat consumption, it is important to focus on enhancement breeding strategies targeting key parameters such as yield, thousand kernel weight (TKW), quality characteristics including morphological traits, and protein content. These elements are key to the ongoing and future objectives of wheat breeding programs. Prioritizing these factors will effectively help meet the rising demand for wheat, especially given the challenges posed by unpredictable weather patterns. This study evaluated the morphological traits and protein content of 249 winter wheat varieties and advanced lines grown in eleven different environments in Morocco and Spain incorporating three varied sowing dates. The results showed considerable variability in morphological traits and protein content. Significant correlations were observed among various grain traits, with most grain morphological parameters exhibiting negative correlations with protein content. Differences across environments (p ≤ 0.01) in all traits, genotypes, and genotype by environment interaction were significant. A factorial regression analysis revealed significant impacts of environmental conditions on all grain morphological parameters, protein content, and TKW during the three growth stages. The study identified several high-performing and stable genotypes across diverse environments, providing valuable insights for wheat breeding programs such as genotypes 129, 234, 241, and 243. Genome-Wide Association Studies pinpointed 603 significant markers across 11 environments, spread across chromosomes. Among these, 400 markers were linked with at least two traits or observed in at least two different environments. Moreover, twelve marker-trait associations were detected that surpassed the Bonferroni correction threshold. These findings highlight the importance of targeted breeding efforts to enhance wheat quality and adaptability to different environmental conditions.

Combined Use of Fatty Acid Profiles and Elemental Fingerprints to Trace the Geographic Origin of Live Baits for Sports Fishing: The Solitary Tube Worm (Diopatra neapolitana, Annelida, Onuphidae) as a Case Study.

Diopatra neapolitana Delle Chiaje, 1841 (Annelida, Onuphidae) is one of the most exploited polychaete species in European waters, particularly in Ria de Aveiro, a coastal lagoon in mainland Portugal, where the overexploitation of this resource has led to a generalized decline of local populations. In an attempt to reduce the impact of harvesting, several management actions were implemented, but illegal poaching still fuels a parallel economy that threatens the sustainable use of this marine resource. The present study evaluated the combination of fatty acid profiles and elemental fingerprints of the whole body and jaws, respectively, of D. neapolitana collected from four harvesting locations within Ria de Aveiro in order to determine if their geographic origin could be correctly assigned post-harvesting. Results showed that both fatty acid profiles and elemental fingerprints differ significantly among locations, discriminating the geographic origin with higher accuracy when combining these two natural barcodes than when employing each individually. The present work can, therefore, contribute to the implementation of an effective management plan for the sustainable use of this marine resource, making it possible to detect if D. neapolitana was sourced from no-take zones and if it was collected from the place of origin claimed by live bait traders.

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers.

Glioma is currently one of the most prevalent types of primary brain cancer. Given its high level of heterogeneity along with the complex biological molecular markers, many efforts have been made to accurately classify the type of glioma in each patient, which, in turn, is critical to improve early diagnosis and increase survival. Nonetheless, as a result of the fast-growing technological advances in high-throughput sequencing and evolving molecular understanding of glioma biology, its classification has been recently subject to significant alterations. In this study, we integrate multiple glioma omics modalities (including mRNA, DNA methylation, and miRNA) from The Cancer Genome Atlas (TCGA), while using the revised glioma reclassified labels, with a supervised method based on sparse canonical correlation analysis (DIABLO) to discriminate between glioma types. We were able to find a set of highly correlated features distinguishing glioblastoma from lower-grade gliomas (LGGs) that were mainly associated with the disruption of receptor tyrosine kinases signaling pathways and extracellular matrix organization and remodeling. Concurrently, the discrimination of the LGG types was characterized primarily by features involved in ubiquitination and DNA transcription processes. Furthermore, we could identify several novel glioma biomarkers likely helpful in both diagnosis and prognosis of the patients, including the genes PPP1R8, GPBP1L1, KIAA1614, C14orf23, CCDC77, BVES, EXD3, CD300A, and HEPN1. Collectively, this comprehensive approach not only allowed a highly accurate discrimination of the different TCGA glioma patients but also presented a step forward in advancing our comprehension of the underlying molecular mechanisms driving glioma heterogeneity. Ultimately, our study also revealed novel candidate biomarkers that might constitute potential therapeutic targets, marking a significant stride toward personalized and more effective treatment strategies for patients with glioma.

Acute Suppurative Thyroiditis in Childhood: An Atypical Presentation.

Neck stiffness is a common clinical sign in children presenting to the emergency department that may indicate a wide variety of diagnoses. Acute suppurative thyroiditis (AST) is an infection of the thyroid gland caused by a bacterium, virus, or, less commonly, fungus. It presents as an acute or subacute development of an anterior cervical mass, with associated inflammatory signs. The pressure upon neck muscles may be reflected as a limitation of cervical mobility. AST is often preceded by an upper respiratory tract infection, and pyriform sinus fistula is the most common predisposing factor. It is particularly uncommon in the pediatric age, with limited cases reported in the literature. Therefore, a heightened suspicion is required for proper diagnosis and timely intervention, due to its high mortality. Prompt treatment with broad-spectrum parenteral antibiotic therapy and drainage is mandatory to prevent the numerous complications associated, namely, mediastinitis and sepsis. We report the case of a two-year-old female child admitted with a two-week history of intermittent high-grade fever and sore throat, followed by prostration and limitation in neck movement on admission. Examination revealed neck stiffness with positive Kernig and Brudzinski signs. The laboratory tests showed elevated inflammatory parameters. Cranial computed tomography (CT) scan and lumbar puncture were normal. On day 2 after admission, an anterior cervical mass with slight signs of fluctuation was detected. Ultrasound was compatible with a hemorrhagic/overinfected thyroid nodule, and the patient was started on broad-spectrum antibiotics. Due to clinical worsening, a cervical CT scan was performed, which documented a thyroid abscess with extension into the retropharyngeal space. She underwent surgical drainage, and Streptococcus anginosus and mixed anaerobes were isolated, sensitive to ongoing antibiotherapy. On multidisciplinary follow-up, an esophageal barium study, laryngoscopy, and cervical magnetic resonance imaging (MRI) were performed, revealing no anatomical defects. AST is a rare disease in children, but potentially fatal, so its early recognition and treatment are essential. We aim to draw attention to this disease and its differential diagnosis to reduce the associated morbimortality.

Postpartum Onset of Multiple Sclerosis: A Case Report.

A breastfeeding 29-year-old woman who gave birth to her first child three months ago presented at the family doctor's appointment with a diverse array of symptoms, including vertigo, blurred vision, right lower limb weakness, and abdominal allodynia. She has a history of obesity and anxiety. The patient had a pre-pregnancy history of several visits to the family doctor. She takes folic acid, vitamin B12, iodine, and omega-3 supplements. The diverse symptomatology, the patient's insistence on seeking medical care, and the history of anxiety pose significant hurdles in arriving at a timely diagnosis. Magnetic resonance imaging showed signs compatible with primary demyelinating lesions of the central nervous system, which elicited a referral to neurology. The clinical and imagiological findings were suggestive of multiple sclerosis (MS), for which a conservative approach was taken. MS is a chronic inflammatory autoimmune disease with a mean age of onset of 20-30 years, more common in females. Stressful life events, viral infections, vaccination, physical trauma, previous anesthesia, excessive physical activity, and puerperium have all been described as trigger factors. This case underscores the importance of vigilance in postpartum healthcare and the importance of conducting a comprehensive diagnostic assessment. Early diagnosis has a positive impact on the prognosis of the disease.

Yellow fever neutralizing antibody seroprevalence proportion and titers in previously vaccinated adults with chronic kidney disease.

Studies on yellow fever vaccine (YF) in chronic kidney disease (CKD) patients are scarce. This cross-sectional study aimed to evaluate YF neutralizing antibody seroprevalence and titers in previously vaccinated adults with CKD, on dialysis (D-CKD) or not (ND-CKD), compared to healthy persons. The micro Plaque Reduction Neutralization-Horseradish Peroxidase (µPRN-HP) test was used. Antibody titers were expressed as the reciprocal of the highest dilution that neutralized the challenge virus by 50 % (µPRN50). Seropositivity cut-off was set at ≥ 1:100. We included 153 participants: 46 ND-CKD, 50 D-CKD and 57 healthy adults. Median ages were 58.3, 55 and 52.2 years, respectively. Median time since YF vaccination was 22.3, 18.5 and 48.3 months respectively. There were no statistically significant differences in YF seroprevalence and neutralizing antibodies titers among groups: 100 % of ND-CKD; 96 % of D-CKD and 100 % of healthy participants were seropositive. Geometric mean titers (GMT) were 818.5, 683.0 and 665.5, respectively (p = 0.289).

European soybean to benefit people and the environment.

Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha-1 from southern UK through to southern Europe (compared to a 3.5 t ha-1 average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37-291 Mt CO2e year-1 and fertiliser N use by 0.6-1.2 Mt year-1, concurrently improving human health and nutrition.

The decline of measles antibody titers in previously vaccinated adults: a cross-sectional analysis.

The global reemergence of measles in 2018-2019 reinforces the relevance of high-coverage immunization to maintain the disease elimination. During an outbreak in the Sao Paulo State in 2019, several measles cases were reported in individuals who were adequately vaccinated according to the current immunization schedule recommends. This study aimed to assess measles IgG antibody seropositivity and titers in previously vaccinated adults. A cross-sectional study was conducted at CRIE-HC-FMUSP (Sao Paulo, Brazil) in 2019. It included healthy adults who had received two or more Measles-Mumps-Rubella vaccines (MMR) and excluded individuals with immunocompromising conditions. Measles IgG antibodies were measured and compared by ELISA (Euroimmun®) and chemiluminescence (LIASON®). The association of seropositivity and titers with variables of interest (age, sex, profession, previous measles, number of measles-containing vaccine doses, interval between MMR doses, and time elapsed since the last MMR dose) was analyzed. A total of 162 participants were evaluated, predominantly young (median age 30 years), women (69.8%) and healthcare professionals (61.7%). The median interval between MMR doses was 13.2 years, and the median time since the last dose was 10.4 years. The seropositivity rate was 32.7% by ELISA and 75.3% by CLIA, and a strong positive correlation was found between the tests. Multivariate analyses revealed that age and time since the last dose were independently associated with positivity. Despite being a single-center evaluation, our results suggest that measles seropositivity may be lower than expected in adequately immunized adults. Seropositivity was higher among older individuals and those with a shorter time since the last MMR vaccine dose.

Iron overload induces dysplastic erythropoiesis and features of myelodysplasia in Nrf2-deficient mice.

Iron overload (IOL) is hypothesized to contribute to dysplastic erythropoiesis. Several conditions, including myelodysplastic syndrome, thalassemia and sickle cell anemia, are characterized by ineffective erythropoiesis and IOL. Iron is pro-oxidant and may participate in the pathophysiology of these conditions by increasing genomic instability and altering the microenvironment. There is, however, lack of in vivo evidence demonstrating a role of IOL and oxidative damage in dysplastic erythropoiesis. NRF2 transcription factor is the master regulator of antioxidant defenses, playing a crucial role in the cellular response to IOL in the liver. Here, we crossed Nrf2-/- with hemochromatosis (Hfe-/-) or hepcidin-null (Hamp1-/-) mice. Double-knockout mice developed features of ineffective erythropoiesis and myelodysplasia including macrocytic anemia, splenomegaly, and accumulation of immature dysplastic bone marrow (BM) cells. BM cells from Nrf2/Hamp1-/- mice showed increased in vitro clonogenic potential and, upon serial transplantation, recipients disclosed cytopenias, despite normal engraftment, suggesting defective differentiation. Unstimulated karyotype analysis showed increased chromosome instability and aneuploidy in Nrf2/Hamp1-/- BM cells. In HFE-related hemochromatosis patients, NRF2 promoter SNP rs35652124 genotype TT (predicted to decrease NRF2 expression) associated with increased MCV, consistent with erythroid dysplasia. Our results suggest that IOL induces ineffective erythropoiesis and dysplastic hematologic features through oxidative damage in Nrf2-deficient cells.

The decline of measles antibody titers in previously vaccinated adults: a cross-sectional analysis

ABSTRACT The global reemergence of measles in 2018-2019 reinforces the relevance of high-coverage immunization to maintain the disease elimination. During an outbreak in the Sao Paulo State in 2019, several measles cases were reported in individuals who were adequately vaccinated according to the current immunization schedule recommends. This study aimed to assess measles IgG antibody seropositivity and titers in previously vaccinated adults. A cross-sectional study was conducted at CRIE-HC-FMUSP (Sao Paulo, Brazil) in 2019. It included healthy adults who had received two or more Measles-Mumps-Rubella vaccines (MMR) and excluded individuals with immunocompromising conditions. Measles IgG antibodies were measured and compared by ELISA (Euroimmun®) and chemiluminescence (LIASON®). The association of seropositivity and titers with variables of interest (age, sex, profession, previous measles, number of measles-containing vaccine doses, interval between MMR doses, and time elapsed since the last MMR dose) was analyzed. A total of 162 participants were evaluated, predominantly young (median age 30 years), women (69.8%) and healthcare professionals (61.7%). The median interval between MMR doses was 13.2 years, and the median time since the last dose was 10.4 years. The seropositivity rate was 32.7% by ELISA and 75.3% by CLIA, and a strong positive correlation was found between the tests. Multivariate analyses revealed that age and time since the last dose were independently associated with positivity. Despite being a single-center evaluation, our results suggest that measles seropositivity may be lower than expected in adequately immunized adults. Seropositivity was higher among older individuals and those with a shorter time since the last MMR vaccine dose.

A toolbox of machine learning software to support microbiome analysis.

The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis.

Genetic Diversity and Genome-Wide Association Study for the Phenology Response of Winter Wheats of North America, Western Asia, and Europe.

Wheat is a staple food in many areas around the World. In the 20th century, breeders and scientists were able to boost wheat yield considerably. However, a yield plateau has become a concern and is threatening food security. Investments in cutting-edge technologies, including genomics and precision phenology measurements, can provide valuable tools to drive crop improvement. The objectives of this study were to (i) investigate the genetic diversity in a set of winter wheat lines, (ii) characterize their phenological response under different vernalization and photoperiod conditions, and (iii) identify effective markers associated with the phenological traits. A total of 249 adapted genotypes of different geographical origin were genotyped using the 35K Axiom® Wheat Breeder's Array. A total of 11,476 SNPs were used for genetic analysis. The set showed an average polymorphism information content of 0.37 and a genetic diversity of 0.43. A population structure analysis revealed three distinct subpopulations mainly related to their geographical origin (Europe, North America, and Western Asia). The lines of CGIAR origin showed the largest diversity and the lowest genetic distance to all other subpopulations. The phenology of the set was studied under controlled conditions using four combinations of long (19 h light) and short photoperiod (13 h light) and long vernalization (49 days at 5 °C) and no vernalization. With this, phenological traits such as earliness per se (Eps), relative response to vernalization (RRV), and relative response to photoperiod (RRP) were calculated. The phenotypic variation of growing degree days was significant in all phenology combinations. RRV ranged from 0 to 0.56, while RRP was higher with an overall average of 0.25. The GWAS analysis detected 30 marker-trait associations linked to five phenological traits. The highest significant marker was detected on chromosome 2D with a value of -log10(p) = 11.69. Only four loci known to regulate flowering exceeded the Bonferroni correction threshold of -log10(p) > 5.1. These results outline a solid foundation to address global food security and offer tremendous opportunities for advancing crop improvement strategies.

Pulmonary Embolization After Gastric Varices Obliteration.

N-butyl-2-cyanoacrylate (NB2CYA) is frequently used in the treatment of variceal hemorrhage with a success rate in hemostatic control of 87%-100%. Although rare, complications include esophageal perforation, infection, or arterial and venous embolization. We present the case of a 67-year-old male with chronic ethanolic liver disease hospitalized due to melena and hematemesis. He had anemia requiring transfusion support, octreotide, and pantoprazole infusion. Upper digestive endoscopy was performed showing gastric varices with a hemorrhagic rupture point treated with cyanoacrylate. The patient developed respiratory failure over the next 48 hours with chest computed tomography (CT) angiography showing several dense, scattered linear images, with arterial vascular trajectories suggestive of cyanoacrylate embolization. It was decided to provide ventilatory support with invasive mechanical ventilation, initiate systemic corticosteroid therapy, and transfer the patient to the intensive care unit (ICU). The patient was ventilated for 11 days with initial favorable evolution, but after two episodes of decompensation of his chronic liver disease (CLD) (hepatic encephalopathy and hepatorenal syndrome) and a new nosocomial pneumonia, he ended up dying. The present case illustrates a rare but potentially fatal complication associated with cyanoacrylate, highlighting the importance of a high suspicion index in cases of respiratory failure and dyspnea after this therapy.

Safety and immunogenicity of influenza A(H3N2) component vaccine in juvenile systemic lupus erythematosus.

INTRODUCTION: Seasonal influenza A (H3N2) virus is an important cause of morbidity and mortality in the last 50 years in population that is greater than the impact of H1N1. Data assessing immunogenicity and safety of this virus component in juvenile systemic lupus erythematosus (JSLE) is lacking in the literature. OBJECTIVE: To evaluate short-term immunogenicity and safety of influenza A/Singapore (H3N2) vaccine in JSLE. METHODS: 24 consecutive JSLE patients and 29 healthy controls (HC) were vaccinated with influenza A/Singapore/INFIMH-16-0019/2016(H3N2)-like virus. Influenza A (H3N2) seroprotection (SP), seroconversion (SC), geometric mean titers (GMT), factor increase in GMT (FI-GMT) titers were assessed before and 4 weeks post-vaccination. Disease activity, therapies and adverse events (AE) were also evaluated. RESULTS: JSLE patients and controls were comparable in current age [14.5 (10.1-18.3) vs. 14 (9-18.4) years, p = 0.448] and female sex [21 (87.5%) vs. 19 (65.5%), p = 0.108]. Before vaccination, JSLE and HC had comparable SP rates [22 (91.7%) vs. 25 (86.2%), p = 0.678] and GMT titers [102.3 (95% CI 75.0-139.4) vs. 109.6 (95% CI 68.2-176.2), p = 0.231]. At D30, JSLE and HC had similar immune response, since no differences were observed in SP [24 (100%) vs. 28 (96.6%), p = 1.000)], SC [4 (16.7%) vs. 9 (31.0%), p = 0.338), GMT [162.3 (132.9-198.3) vs. 208.1 (150.5-287.8), p = 0.143] and factor increase in GMT [1.6 (1.2-2.1) vs. 1.9 (1.4-2.5), p = 0.574]. SLEDAI-2K scores [2 (0-17) vs. 2 (0-17), p = 0.765] and therapies remained stable throughout the study. Further analysis of possible factors influencing vaccine immune response among JSLE patients demonstrated similar GMT between patients with SLEDAI < 4 compared to SLEDAI ≥ 4 (p = 0.713), as well as between patients with and without current use of prednisone (p = 0.420), azathioprine (p = 1.0), mycophenolate mofetil (p = 0.185), and methotrexate (p = 0.095). No serious AE were reported in both groups and most of them were asymptomatic (58.3% vs. 44.8%, p = 0.958). Local and systemic AE were alike in both groups (p > 0.05). CONCLUSION: This is the first study that identified adequate immune protection against H3N2-influenza strain with additional vaccine-induced increment of immune response and an adequate safety profile in JSLE. ( www. CLINICALTRIALS: gov , NCT03540823).

Impact of rising temperatures on historical wheat yield, phenology, and grain size in Catalonia.

Introduction: Climate change poses significant challenges to agriculture, impacting crop yields and necessitating adaptive strategies in breeding programs. This study investigates the genetic yield progress of wheat varieties in Catalonia, Spain, from 2007 to 2021, and examines the relationship between genetic yield and climate-related factors, such as temperature. Understanding these dynamics is crucial for ensuring the resilience of wheat crops in the face of changing environmental conditions. Methods: Genetic yield progress was assessed using a linear regression function, comparing the average yield changes of newly released wheat varieties to benchmark varieties. Additionally, a quadratic function was employed to model genetic yield progress in winter wheat (WW). The study also analyzed correlations between genetic yield (GY) and normalized values of hectoliter weight (HLW) and the number of grains (NG) for both spring wheat (SW) and WW. Weather data were used to confirm climate change impacts on temperature and its effects on wheat growth and development. Results: The study found that genetic yield was stagnant for SW but increased linearly by 1.31% per year for WW. However, the quadratic function indicated a possible plateau in WW genetic yield progress in recent years. Positive correlations were observed between GY and normalized values of HLW and NG for both SW and WW. Climate change was evident in Catalonia, with temperatures increasing at a rate of 0.050 °C per year. This rise in temperature had detrimental effects on days to heading (DH) and HLW, with reductions observed in both SW and WW for each °C increase in annual minimum and average temperature. Discussion: The findings highlighted the urgent need to address the impact of climate change on wheat cultivation. The stagnation of genetic yield in SW and the potential plateau in WW genetic yield progress call for adaptive measures. Breeding programs should prioritize phenological adjustments, particularly sowing date optimization, to align with the most favorable months of the year. Moreover, efforts should be made to enhance HLW and the number of grains per unit area in new wheat varieties to counteract the negative effects of rising temperatures. This research underscores the importance of ongoing monitoring and adaptation in agricultural practices to ensure yield resilience in the context of a changing climate.

A Remote Sensing Approach for Assessing Daily Cumulative Evapotranspiration Integral in Wheat Genotype Screening for Drought Adaptation.

This study considers critical aspects of water management and crop productivity in wheat cultivation, specifically examining the daily cumulative actual evapotranspiration (ETa). Traditionally, ETa surface energy balance models have provided estimates at discrete time points, lacking a holistic integrated approach. Field trials were conducted with 22 distinct wheat varieties, grown under both irrigated and rainfed conditions over a two-year span. Leaf area index prediction was enhanced through a robust multiple regression model, incorporating data acquired from an unmanned aerial vehicle using an RGB sensor, and resulting in a predictive model with an R2 value of 0.85. For estimation of the daily cumulative ETa integral, an integrated approach involving remote sensing and energy balance models was adopted. An examination of the relationships between crop yield and evapotranspiration (ETa), while considering factors like year, irrigation methods, and wheat cultivars, unveiled a pronounced positive asymptotic pattern. This suggests the presence of a threshold beyond which additional water application does not significantly enhance crop yield. However, a genetic analysis of the 22 wheat varieties showed no correlation between ETa and yield. This implies opportunities for selecting resource-efficient wheat varieties while minimizing water use. Significantly, substantial disparities in water productivity among the tested wheat varieties indicate the possibility of intentionally choosing lines that can optimize grain production while minimizing water usage within breeding programs. The results of this research lay the foundation for the development of resource-efficient agricultural practices and the cultivation of crop varieties finely attuned to water-scarce regions.

Agronomic performance and remote sensing assessment of organic and mineral fertilization in rice fields.

Introduction: Rice heavily relies on nitrogen fertilizers, posing environmental, resource, and geopolitical challenges. This study explores sustainable alternatives like animal manure and remote sensing for resource-efficient rice cultivation. It aims to assess the long-term impact of organic fertilization and remote sensing monitoring on agronomic traits, yield, and nutrition. Methods: A six-year experiment in rice fields evaluated fertilization strategies, including pig slurry (PS) and chicken manure (CM) with mineral fertilizers (MIN), MIN-only, and zero-fertilization. Traits, yield, spectral responses, and nutrient content were measured. Sentinel-2 remote sensing tracked crop development. Results: Cost-effective organic fertilizers (PS and CM) caused a 13% and 15% yield reduction but still doubled zero-fertilization yield. PS reduced nitrogen leaching. Heavy metals in rice grains were present at safe amounts. Organic-fertilized crops showed nitrogen deficiency at the late vegetative stages, affecting yield. Sentinel-2 detected nutrient deficiencies through NDVI. Discussion: Organic fertilizers, especially PS, reduce nitrogen loss, benefiting the environment. However, they come with yield trade-offs and nutrient management challenges that can be managed and balanced with reduced additional mineral applications. Sentinel-2 remote sensing helps manage nutrient deficiencies. In summary, this research favors cost-effective organic fertilizers with improved nutrient management for sustainable rice production.

Overview of data preprocessing for machine learning applications in human microbiome research.

Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical specificities of the data (e.g., sparse, over-dispersed, compositional, inter-variable dependency). This mini review explores preprocessing and transformation methods applied in recent human microbiome studies to address microbiome data analysis challenges. Our results indicate a limited adoption of transformation methods targeting the statistical characteristics of microbiome sequencing data. Instead, there is a prevalent usage of relative and normalization-based transformations that do not specifically account for the specific attributes of microbiome data. The information on preprocessing and transformations applied to the data before analysis was incomplete or missing in many publications, leading to reproducibility concerns, comparability issues, and questionable results. We hope this mini review will provide researchers and newcomers to the field of human microbiome research with an up-to-date point of reference for various data transformation tools and assist them in choosing the most suitable transformation method based on their research questions, objectives, and data characteristics.

Machine learning approaches in microbiome research: challenges and best practices.

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery. It is demonstrated that the use of compositional transformations and filtering methods as part of data preprocessing does not always improve the predictive performance of a model. In contrast, the multivariate feature selection, such as the Statistically Equivalent Signatures algorithm, was effective in reducing the classification error. When validated on a separate test dataset, this algorithm in combination with random forest modeling, provided the most accurate performance estimates. Lastly, we showed how linear modeling by logistic regression coupled with visualization techniques such as Individual Conditional Expectation (ICE) plots can yield interpretable results and offer biological insights. These findings are significant for clinicians and non-experts alike in translational applications.

Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action.

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.