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Abstract Nucleotide-binding leucine-rich repeat (NLR) disease resistance genes typically confer resistance against races of a single pathogen. Here, we report that Yr87/Lr85, an NLR gene from Aegilops sharonensis and Aegilops longissima, confers resistance against both P. striiformis tritici (Pst) and Puccinia triticina (Pt) that cause stripe and leaf rust, respectively. Yr87/Lr85 confers resistance against Pst and Pt in wheat introgression as well as transgenic lines. Comparative analysis of Yr87/Lr85 and the cloned Triticeae NLR disease resistance genes shows that Yr87/Lr85 contains two distinct LRR domains and that the gene is only found in Ae. sharonensis and Ae. longissima. Allele mining and phylogenetic analysis indicate multiple events of Yr87/Lr85 gene flow between the two species and presence/absence variation explaining the majority of resistance to wheat leaf rust in both species. The confinement of Yr87/Lr85 to Ae. sharonensis and Ae. longissima and the resistance in wheat against Pst and Pt highlight the potential of these species as valuable sources of disease resistance genes for wheat improvement.

Unmanned aircraft have had a great impact on society, their applications in various fields are increasing day by day, so it becomes necessary to propose, develop or validate new designs and concepts that help minimize operating errors or improve the safety of aircraft. One way to understand the operating principle of these unmanned aircraft is through laboratory prototypes or test benches; these prototypes allow experimentation and testing in controlled environments to minimize errors in their operation. This article presents a novel configuration for a laboratory prototype of a tandem-rotor helicopter with two degrees of freedom (DOF), and the dynamic modeling, control, signal filtering, and implementation of the control and filtering system using a microcontroller and a low-cost prototype made with easily accessible materials. This is to promote education, research, and technological development in this area of engineering.

The production of biofuels has had a great impact on climate change and the reduction of the use of fossil fuels. There are different technologies used for the separation and production of biofuels, which allow having compounds such as ethanol, methane, oxygen, and hydrogen, one of these promising technologies is the Pressure Swing Adsorption process (PSA). The objectives of this article focus on the production and purification of compounds that achieve purities of 99.5% bioethanol, 94.85% biohydrogen, 95.00% medical oxygen, and 99.99% biomethane through the PSA process; also, a significant review is contemplated to identify the different natural and synthetic adsorbents that have greater adsorption capacity, the different configurations in which a PSA operates are studied and identified, and the different mathematical models that describe the dynamic behavior of all the variables are established that interact in this PSA process, parametric studies are carried out in order to identify the variables that have the greatest effect on the purity obtained. The results obtained in this review allow facilitating the calculation of parameters, the optimization of the process, the automatic control to manipulate certain variables and to achieve the rejection of disturbances to have a recovery and production of biofuels with a high degree of purity.

Industry 4.0 involves various areas of engineering such as advanced robotics, Internet of Things, simulation, and augmented reality, which are focused on the development of smart factories. The present work presents the design and application of the methodology for the development of augmented reality applications (MeDARA) using a concrete, pictorial, and abstract approach with the intention of promoting the knowledge, skills, and attitudes of the students within the conceptual framework of educational mechatronics (EMCF). The flight of a drone is presented as a case study, where the concrete level involves the manipulation of the drone in a simulation; the graphic level requires the elaboration of an experiential storyboard that shows the scenes of the student’s interaction with the drone in the concrete level; and finally, the abstract level involves the planning of user stories and acceptance criteria, the computer design of the drone, the mock-ups of the application, the coding in Unity and Android Studio, and its integration to perform unit and acceptance tests. Finally, evidence of the tests is shown to demonstrate the results of the application of the MeDARA.

Today, there are new technologies to produce bioethanol: one of them is the Pressure Swing Adsorption (PSA) process. This process has displaced other separation technologies due to the use of natural adsorbents and its methodology to obtain high purities with a lower energy cost. The aim of this work focuses on the optimization of the PSA process (experimental case) to obtain a higher recovery and production of bioethanol using lower energy consumption. The results are favorable since the energy cost is reduced to a range of 60% and 62%, obtaining purities above 99% wt of ethanol and recovery between 75% and 77.41%. The bioethanol produced and purified in the different scenarios meets international standards to be used as a fuel or oxygenating additive.

Three members of the Puccinia genus, Puccinia triticina (Pt), P. striiformis f.sp. tritici (Pst), and P. graminis f.sp. tritici (Pgt), cause the most common and often most significant foliar diseases of wheat. While similar in biology and life cycle, each species is uniquely adapted and specialized. The genomes of Pt and Pst were sequenced and compared to that of Pgt to identify common and distinguishing gene content, to determine gene variation among wheat rust pathogens, other rust fungi, and basidiomycetes, and to identify genes of significance for infection. Pt had the largest genome of the three, estimated at 135 Mb with expansion due to mobile elements and repeats encompassing 50.9% of contig bases; in comparison, repeats occupy 31.5% for Pst and 36.5% for Pgt. We find all three genomes are highly heterozygous, with Pst [5.97 single nucleotide polymorphisms (SNPs)/kb] nearly twice the level detected in Pt (2.57 SNPs/kb) and that previously reported for Pgt. Of 1358 predicted effectors in Pt, 784 were found expressed across diverse life cycle stages including the sexual stage. Comparison to related fungi highlighted the expansion of gene families involved in transcriptional regulation and nucleotide binding, protein modification, and carbohydrate degradation enzymes. Two allelic homeodomain pairs, HD1 and HD2, were identified in each dikaryotic Puccinia species along with three pheromone receptor (STE3) mating-type genes, two of which are likely representing allelic specificities. The HD proteins were active in a heterologous Ustilago maydis mating assay and host-induced gene silencing (HIGS) of the HD and STE3 alleles reduced wheat host infection.

From the very beginning, the COVID-19 crisis management could have hardly been considered rational. Many governments had prepared plans for dealing with exactly this kind of pandemic after the 9/11 [...]

This paper presents the design and development of an IoT device, called MEIoT weather station, which combines the Educational Mechatronics and IoT to develop the required knowledge and skills for Industry 4.0. MEIoT weather station connects to the internet, measures eight weather variables, and upload the sensed data to the cloud. The MEIoT weather station is the first device working with the IoT architecture of the National Digital Observatory of Intelligent Environments. In addition, an IoT open platform, GUI-MEIoT, serves as a graphic user interface. GUI-MEIoT is used to visualize the real-time data of the weather variables, it also shows the historical data collected, and allows to export them to a csv file. Finally, an OBNiSE architecture application to Engineering Education is presented with a dynamic system case of study that includes the instructional design carried out within the Educational Mechatronics Conceptual Framework (EMCF) to show the relevance of this proposal. This work main contribution to the state of art is the design and integration of the OBNiSE architecture within the EMCF offering the possibility to add more IoT devices for several smart domains such as smart campus, smart cities, smart people and smart industries.

Objectives This study aims to evaluate and compare health outcomes and costs between home hospitalisation and traditional hospitalisation for three common diagnoses—cellulitis, urinary tract infection (UTI) and pneumonia.Design A retrospective cohort study.Setting Primary care, nationwide.Participants 1311 patients in home hospitalisation and 992 in traditional hospitalisation.Interventions The primary intervention is home hospitalisation, compared with traditional hospitalisation. The intervention was performed according to medical considerations by a specialised team, and this study was done retrospectively to evaluate it.Primary and secondary outcome measures Primary measures included healthcare costs, length of hospitalisation, referrals for further medical services and mortality.Results Costs of home hospitalisation were lower compared with traditional hospitalisation (6056 vs 9619 NIS for pneumonia, 6011 vs 9767 NIS for cellulitis, 6466 vs 8552 NIS for UTI and p value

BackgroundAcinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. This study aimed to construct an innovative Machine Learning (ML) based prediction tool for Acinetobacter baumanni infection, among patients in the ICU, and to examine its robustness and predictive power.MethodsFor model development and internal validation, we used The Medical Information Mart for Intensive Care database (MIMIC) III data from 19,690 consecutive adult patients admitted between 2001 and 2012 at a Boston tertiary center ICU. For external validation, we used a different dataset from Rabin Medical Center (RMC, Israeli tertiary center) ICU, of 1,700 patients admitted between 2017 and 2021. After training on MIMIC cohorts, we adapted the algorithm from MIMIC to RMC and evaluated its discriminating power in terms of Area Under the Receiver Operating Curve (AUROC), sensitivity, specificity, Negative Predictive Value and Positive Predictive Value.ResultsThe prediction model achieved AUROC = 0.624 (95% CI 0.604-0.647). The most significant predictors were (i) physiological parameters of cardio-respiratory function, such as carbon dioxide (CO2) levels and respiratory rate, (ii) metabolic disturbances such as lactate and acidosis (pH) and (iii) past administration of antibiotics.ConclusionsInfection with Acinetobacter baumanni is more likely to occur in patients with respiratory failure and higher lactate levels, as well as patients who have used larger amounts of antibiotics. The accuracy of Acinetobacter prediction may be enhanced by future studies.

Background Acute upper respiratory infections are the most common reason for primary physician visits in the community. This study investigated whether the type of antibiotic used to treat streptococcal tonsillitis can reduce the burden by affecting the number of additional visits.Objectives To assess the effect of different antibiotic treatments for tonsillitis on the number of additional primary physician visits and the development of infectious or inflammatory sequels.Methods This retrospective study included first cases of culture-confirmed streptococcal tonsillitis (n = 242,366, 55.3% females, 57.6% aged 3–15 years) treated in primary clinics throughout Israel between the years 2010 and 2019. Primary outcomes were the number of additional primary physician visits, due to any cause or due to specific upper airway infections. Secondary outcomes were the number of developed complications, such as peritonsillar abscess, post-streptococcal glomerulonephritis, rheumatic fever, post-streptococcal arthritis, chorea and death.Results Compared to penicillin-V, adjusted incidence rate ratios (IRR) for additional primary physician visits at 30–days were highest for IM benzathine-benzylpenicillin (IRR = 1.46, CI 1.33–1.60, p

Background: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. This study aimed to construct an innovative Machine Learning (ML) based prediction tool for Acinetobacter baumanni infection, among patients in the ICU, and to examine its robustness and predictive power. Methods: For model development and internal validation, we used The Medical Information Mart for Intensive Care database (MIMIC) III data from 19,690 consecutive adult patients admitted between 2001 and 2012 at a Boston tertiary center ICU. For external validation, we used a different dataset from Rabin Medical Center (RMC, Israeli tertiary center) ICU, of 1,700 patients admitted between 2017 and 2021. After training on MIMIC cohorts, we adapted the algorithm from MIMIC to RMC and evaluated its discriminating power in terms of Area Under the Receiver Operating Curve (AUROC), sensitivity, specificity, Negative Predictive Value and Positive Predictive Value. Results: The prediction model achieved AUROC = 0.624 (95% CI 0.604–0.647). The most significant predictors were (i) physiological parameters of cardio-respiratory function, such as carbon dioxide (CO2) levels and respiratory rate, (ii) metabolic disturbances such as lactate and acidosis (pH) and (iii) past administration of antibiotics. Conclusions: Infection with Acinetobacter baumanni is more likely to occur in patients with respiratory failure and higher lactate levels, as well as patients who have used larger amounts of antibiotics. The accuracy of Acinetobacter prediction may be enhanced by future studies. [ABSTRACT FROM AUTHOR]

The perception of signals from within the body, known as interoception, is increasingly recognized as a prerequisite for physical and mental health. This study is dedicated to the development of effective technological approaches for enhancing interoceptive abilities. We provide evidence of the effectiveness and practical feasibility of a novel real‐time haptic heartbeat supplementation technology combining principles of biofeedback and sensory augmentation. In a randomized controlled study, we applied the developed naturalistic haptic feedback on a group of 30 adults, while another group of 30 adults received more traditional real‐time visual heartbeat feedback. A single session of haptic, but not visual heartbeat feedback resulted in increased interoceptive accuracy and confidence, as measured by the heart rate discrimination task, and in a shift of attention toward the body. Participants rated the developed technology as more helpful and pleasant than the visual feedback, thus indicating high user satisfaction. The study highlights the importance of matching sensory characteristics of the feedback provided to the natural bodily prototype. Our work suggests that real‐time haptic feedback might be a superior approach for strengthening the mind–body connection in interventions for physical and mental health. In the study, we evaluate the efficacy of a newly developed interoceptive training—supplementation of heartbeat sensations through real‐time haptic feedback. We revealed that the haptic feedback technology improves interoceptive accuracy, increases confidence, and shifts attention toward bodily sensations more effectively than the traditional visual feedback approach, opening new possibilities for clinical and neurowellness applications. [ABSTRACT FROM AUTHOR]

Long‐term genetic studies of wild populations are very scarce, but are essential for connecting ecological and population genetics models, and for understanding the dynamics of biodiversity. We present a study of a wild wheat population sampled over a 36‐year period at high spatial resolution. We genotyped 832 individuals from regular sampling along transects during the course of the experiment. Genotypes were clustered into ecological microhabitats over scales of tens of metres, and this clustering was remarkably stable over the 36 generations of the study. Simulations show that it is difficult to determine whether this spatial and temporal stability reflects extremely limited dispersal or fine‐scale local adaptation to ecological parameters. Using a common‐garden experiment, we showed that the genotypes found in distinct microhabitats differ phenotypically. Our results provide a rare insight into the population genetics of a natural population over a long monitoring period. [ABSTRACT FROM AUTHOR]

Background Maccabi-RED is a new service developed in Israel that allows primary care staff to direct urgent cases to specialists in the community for evaluation in their local clinics on the same day as an alternative to an emergency department (ED) visit. A primary care physician or a nurse can activate the service, and all nearby specialists receive "a call" and can decide if they are willing to accept it, thus allowing the patient to avoid an unnecessary visit to the ED. Aim To quantify and characterize the medical care provided by this service in a large national healthcare system. Design and Setting Multicenter, community-based, retrospective cohort study. Methods All Maccabi-RED visits recorded between September 2021 and August 2022 were included. Patient characteristics were compared to national demographics. Descriptive statistics were used to present data regarding recorded diagnoses, treating physicians, treatments or referrals provided, and subsequent emergency department admissions or hospitalizations. Results 31831 visits were recorded. Most frequent diagnoses were musculoskeletal pain (12.1%), otitis or otalgia (7.8%), contusions (7.6%), fractures (7.1%), foreign body (6.7%), pregnancy-related symptoms (6.3%), and upper-respiratory or unspecified viral infection (6.3%). The most common treatments reported were foreign body removal (5%) and cast application (3.5%). Only 7.8% of visits resulted in emergency department admission within seven days (any cause). The average time from patient request to physician treatment was 91 min. Conclusions Maccabi-RED is being widely used by patients nationwide. Additional studies are needed to investigate whether Maccabi-RED reduces emergency department visits and costs. [ABSTRACT FROM AUTHOR]

Abstract Background Sarcopenia may be more present in older adults with diabetes (DM). Accordingly, we evaluated the prevalence of sarcopenia and its associated risk factors among community-dwelling older adults with DM. Methods A cross-sectional analysis of older people living in the community was carried out. Participants (aged 75 years and more) came from an European multicenter prospective cohort (SCOPE study). Global geriatric assessment including short physical performance battery, handgrip strength test and bioelectrical impedance analysis was performed. Sarcopenia was defined by the updated criteria of the European Working Group on Sarcopenia in Older People (EWGSOP2). Estimated glomerular filtration rate (eGFR) was calculated using Berlin Initiative Study (BIS) to define the stages of chronic kidney disease (CKD). Previous known DM was defined as physician-diagnosed DM registered in the patient's medical record or the use of DM-related medications. Hemoglobin A1c levels and specific DM therapies administered were collected. Time elapsed from the first diagnosis of DM was not collected and, therefore, was not included in the analyses. Results A total of 1,420 subjects were evaluated with a median age of 79.0 (6.0) years, of which 804 (56.6%) were women and 615 (43.3%) men; 315 (22.2%) participants had prior DM diagnosis, with a median age of 80.0 (6.0), 146 (46.3%) were women. Using EWGSOP2 definition, 150 (10.6%) participants in the SCOPE study met diagnostic criteria for sarcopenia. Participants without diabetes had more often normal results in the 3 sarcopenia components than participants with diabetes [887 (80.31%) vs. 227 (72.1%), p = 0.002], highlighting higher percentages of severe sarcopenia in participants with diabetes [27 (8.6%) vs. 58 (5.2%), p = 0.028]. Confirmed or severe sarcopenia was detected in 41 (13%) participants with diabetes and 109 (9.8%) participants without diabetes (p = 0.108). According to BIS equation, sarcopenia was not significantly more prevalent in the more advanced stages of CKD (p = 0.845). In multivariate analyses, older age (odds ratios [OR], 1.17; 95% confidence interval [CI], 1.08–1.27), and lower body mass index (OR, 0.79; 95% CI, 0.71–0.89 were associated with the presence of sarcopenia. Conclusions One tenth of all older community-dwelling subjects have sarcopenia. Older age and being thinner, but not worse renal function, were associated with higher prevalence of sarcopenia in older older adults with diabetes.