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IntroductionFoot-and-mouth disease (FMD) is one of the most economically significant global livestock diseases. In the U.S., economic optimization models run in 2011 demonstrate the highest mean epidemic impact of a potential FMD outbreak in California would occur in livestock-dense regions, resulting in national agriculture losses of $2.3 to $69.0 billion. In the case that an FMD outbreak occurred in the U.S., mass depopulation, carcass disposal, and disinfection protocols for infected premises have been designed to prevent further viral spread. Because the FMD virus (FMDV) is spread mechanically via the environment, characteristics of viral environmental stability are important. Temperature and adsorption to soil particles are reported to be the most important factors affecting general virus survival; however, how much these factors alter FMDV survival has not been tested.MethodsSoil samples were examined from typical U.S. regions containing the highest cattle population densities: Tennessee, Georgia, Nebraska, California, Pennsylvania, Kentucky, and Iowa. Soils were spiked with known quantities of FMDV and FMDV stability was evaluated over seven distinct time points between 0 hours and 12 days at incubation temperatures of 25°C and 37°C to represent a range of typical ambient temperatures during the summer. FMDV stability was quantified via virus titration.ResultsVirus decayed faster at higher ambient temperatures for all soils, but decay at 25°C was faster in some soils. Consequently, areas with high ambient temperatures may have lower between-farm transmission rates, slower outbreak spread, and simpler farm decontamination.DiscussionThis study provides a helpful exploration into understanding soil survival of the virus. Additional investigations into FMDV survival across different soil types will aid in developing better disinfection protocols and further refining regional viral transmission rate estimates.

Upper extremity true arterial aneurysms are rare and often present as a pulsatile mass with associated pain and paresthesia from peripheral nerve compression, and can lead to acute limb ischemia from thromboembolic sequela. History of arteriovenous dialysis access and immunosuppression after renal transplantation may contribute to the development of true aneurysms.This report describes the management of a patient with end-stage renal disease (ESRD) with multiple left upper extremity dialysis access who presented with an axillary and brachial artery aneurysm.

Abstract The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interruptions for some parts of the grid as compared to others. This paper proposes an equity‐aware power distribution system restoration model in an effort to ensure a more equitable yet resilient power distribution operation after outages. To this end, the proposed equity‐aware distribution system restoration model balances the efficiency of the restoration operation and the equitable allocation of distributed energy resources among affected customers after an outage, while prioritizing the critical infrastructure (e.g. hospitals). The results demonstrate the effectiveness of the proposed framework to ensure a more equitable restoration process as measured by the proposed fairness and restoration performance indices.

Objetivo: Determinar la efectividad de las incisiones arcuatas asistidas con láser de femtosegundo para el tratamiento del astigmatismo residual posterior a trasplante de córnea. Método: Estudio observacional, descriptivo de serie de casos, de corte transversal. Se evaluaron 18 pacientes con astigmatismo corneal residual a trasplante de córnea. Los parámetros evaluados incluyeron: agudeza visual, valor astigmático, queratometría, paquimetría, pretratamiento, a las 24 horas, 7 días y 30 días posterior a la cirugía y análisis vectorial (método de Alpin). Resultados: los índices de seguridad y eficacia fue de 0,66 D y 0,5 D respectivamente. Un mes postoperatorio, se observó una mejora significativa en la agudeza visual, con una ganancia de visión del 50,1% y una reducción del astigmatismo en un 49,12%. El 75% de los pacientes alcanzaron los resultados visuales esperados. Conclusiones: las incisiones corneales arcuatas son un método efectivo para corregir el astigmatismo residual post-queratoplastia, con mejoras significativas en la visión que se mantuvieron hasta el tercer mes. Sin embargo, las limitaciones incluyeron un pequeño tamaño muestral y un período de seguimiento corto.

Abstract Background Enteric neuropathies, which result from abnormalities of the enteric nervous system, are associated with significant morbidity and high health-care costs, but current treatments are unsatisfactory. Cell-based therapy offers an innovative approach to replace the absent or abnormal enteric neurons and thereby restore gut function. Methods Enteric neuronal stem cells (ENSCs) were isolated from the gastrointestinal tract of Wnt1-Cre;R26tdTomato mice and generated neurospheres (NS). NS transplants were performed via injection into the mid-colon mesenchyme of nNOS −/− mouse, a model of colonic dysmotility, using either 1 (n = 12) or 3 (n = 12) injections (30 NS per injection) targeted longitudinally 1–2 mm apart. Functional outcomes were assessed up to 6 weeks later using electromyography (EMG), electrical field stimulation (EFS), optogenetics, and by measuring colorectal motility. Results Transplanted ENSCs formed nitrergic neurons in the nNOS −/− recipient colon. Multiple injections of ENSCs resulted in a significantly larger area of coverage compared to single injection alone and were associated with a marked improvement in colonic function, demonstrated by (1) increased colonic muscle activity by EMG recording, (2) faster rectal bead expulsion, and (3) increased fecal pellet output in vivo. Organ bath studies revealed direct neuromuscular communication by optogenetic stimulation of channelrhodopsin-expressing ENSCs and restoration of smooth muscle relaxation in response to EFS. Conclusions These results demonstrate that transplanted ENSCs can form effective neuromuscular connections and improve colonic motor function in a model of colonic dysmotility, and additionally reveal that multiple sites of cell delivery led to an improved response, paving the way for optimized clinical trial design.

The goal of this study is to determine the feasibility of a wearable multi-sensor positioning prototype to be used as a training tool to evaluate rowing technique and to determine the positioning accuracy using multiple mathematical models and estimation methods. The wearable device consists of an inertial measurement unit (IMU), an ultra-wideband (UWB) transceiver, and a global navigation satellite system (GNSS) receiver. An experiment on a rowing shell was conducted to evaluate the performance of the system on a rower’s wrist, against a centimeter-level GNSS reference trajectory. This experiment analyzed the rowing motion in multiple navigation frames and with various positioning methods. The results show that the wearable device prototype is a viable option for rowing technique analysis; the system was able to provide the position, velocity, and attitude of a rower’s wrist, with a positioning accuracy ranging between ±0.185 m and ±1.656 m depending on the estimation method.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10–20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

The enteric nervous system (ENS) is an extensive network of neurons and glia within the wall of the gastrointestinal (GI) tract that regulates many essential GI functions. Consequently, disorders of the ENS due to developmental defects, inflammation, infection, or age-associated neurodegeneration lead to serious neurointestinal diseases. Despite the prevalence and severity of these diseases, effective treatments are lacking as they fail to directly address the underlying pathology. Neuronal stem cell therapy represents a promising approach to treating diseases of the ENS by replacing the absent or injured neurons, and an autologous source of stem cells would be optimal by obviating the need for immunosuppression. We utilized the swine model to address key questions concerning cell isolation, delivery, engraftment, and fate in a large animal relevant to human therapy. We successfully isolated neural stem cells from a segment of small intestine resected from 1-month-old swine. Enteric neuronal stem cells (ENSCs) were expanded as neurospheres that grew optimally in low-oxygen (5%) culture conditions. Enteric neuronal stem cells were labeled by lentiviral green fluorescent protein (GFP) transduction, then transplanted into the same swine from which they had been harvested. Endoscopic ultrasound was then utilized to deliver the ENSCs (10,000–30,000 neurospheres per animal) into the rectal wall. At 10 and 28 days following injection, autologously derived ENSCs were found to have engrafted within rectal wall, with neuroglial differentiation and no evidence of ectopic spreading. These findings strongly support the feasibility of autologous cell isolation and delivery using a clinically useful and minimally invasive technique, bringing us closer to first-in-human ENSC therapy for neurointestinal diseases.

Fruit juices (FJ) have gained widespread global consumption, driven by their perceived health benefits. The accuracy of nutrition information is essential for consumers assessing FJ quality, especially with increasing concerns about added sugars and obesity risk. Conversely, ascorbic acid (Vitamin C), found in nature in many fruits and vegetables, is often lost due to its susceptibility to light, air, and heat, and it undergoes fortification during FJ production. Current analytical methods for determining FJ components are time-consuming and labor-intensive, prompting the need for rapid analytical tools. This study employed a field-deployable portable FT-IR device, requiring no sample preparation, to simultaneously predict multiple quality traits in 68 FJ samples from US markets. Using partial least square regression (PLSR) models, a strong correlation (RCV ≥ 0.93) between FT-IR predictions and reference values was obtained, with a low standard error of prediction. Remarkably, 21% and 37% of FJs deviated from nutrition label values for sugars and ascorbic acid, respectively. Portable FT-IR devices offer non-destructive, simultaneous, simple, and high-throughput approaches for chemical profiling and real-time prediction of sugars and acid levels in FJs. Their handiness and ruggedness can provide food processors with a valuable “out-of-the-laboratory” analytical tool.

The natural variation in estrogen secretion throughout the female menstrual cycle impacts various organs, including estrogen receptor (ER)-expressed skeletal muscle. Many women commonly experience increased fatigue or reduced energy levels in the days leading up to and during menstruation, when blood estrogen levels decline. Yet, it remains unclear whether endogenous 17β-estradiol, a major estrogen component, directly affects the energy metabolism in skeletal muscle due to the intricate and fluctuating nature of female hormones. In this study, we employed 2D 31P FID-MRSI at 7T to investigate phosphoryl metabolites in the soleus muscle of a cohort of young females (average age: 28 ± 6 years, n = 7) during the early follicular (EF) and peri-ovulation (PO) phases, when their blood 17β-estradiol levels differ significantly (EF: 28 ± 18 pg/mL vs. PO: 71 ± 30 pg/mL, p < 0.05), while the levels of other potentially interfering hormones remain relatively invariant. Our findings reveal a reduction in ATP-referenced phosphocreatine (PCr) levels in the EF phase compared to the PO phase for all participants (5.4 ± 4.3%). Furthermore, we observe a linear correlation between muscle PCr levels and blood 17β-estradiol concentrations (r = 0.64, p = 0.014). Conversely, inorganic phosphate Pi and phospholipid metabolite GPC levels remain independent of 17β-estradiol but display a high correlation between the EF and PO phases (p = 0.015 for Pi and p = 0.0008 for GPC). The robust association we have identified between ATP-referenced PCr and 17β-estradiol suggests that 17β-estradiol plays a modulatory role in the energy metabolism of skeletal muscle.

The diagnostic criteria for fibromyalgia (FM) have relied heavily on subjective reports of experienced symptoms coupled with examination-based evidence of diffuse tenderness due to the lack of reliable biomarkers. Rheumatic disorders that are common causes of chronic pain such as rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, and chronic low back pain are frequently found to be comorbid with FM. As a result, this can make the diagnosis of FM more challenging. We aim to develop a reliable classification algorithm using unique spectral profiles of portable FT-MIR that can be used as a real-time point-of-care device for the screening of FM. A novel volumetric absorptive microsampling (VAMS) technique ensured sample volume accuracies and minimized the variation introduced due to hematocrit-based bias. Blood samples from 337 subjects with different disorders (179 FM, 158 non-FM) collected with VAMS were analyzed. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. The OPLS-DA algorithm enabled the classification of the spectra into their corresponding classes with 84% accuracy, 83% sensitivity, and 85% specificity. The OPLS-DA regression plot indicated that spectral regions associated with amide bands and amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases.

Fibromyalgia (FM) is a chronic muscle pain disorder that shares several clinical features with other related rheumatologic disorders. This study investigates the feasibility of using surface-enhanced Raman spectroscopy (SERS) with gold nanoparticles (AuNPs) as a fingerprinting approach to diagnose FM and other rheumatic diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), osteoarthritis (OA), and chronic low back pain (CLBP). Blood samples were obtained on protein saver cards from FM (n = 83), non-FM (n = 54), and healthy (NC, n = 9) subjects. A semi-permeable membrane filtration method was used to obtain low-molecular-weight fraction (LMF) serum of the blood samples. SERS measurement conditions were standardized to enhance the LMF signal. An OPLS-DA algorithm created using the spectral region 750 to 1720 cm−1 enabled the classification of the spectra into their corresponding FM and non-FM classes (Rcv > 0.99) with 100% accuracy, sensitivity, and specificity. The OPLS-DA regression plot indicated that spectral regions associated with amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases. This exploratory work suggests that the AuNP SERS method in combination with OPLS-DA analysis has great potential for the label-free diagnosis of FM.

In this study, a new wireless electronic circuitry to analyze weight distribution was designed and incorporated into a chair to gather data related to common human postures (sitting and standing up). These common actions have a significant impact on various motor capabilities, including gait parameters, fall risk, and information on sarcopenia. The quality of these actions lacks an absolute measurement, and currently, there is no qualitative and objective metric for it. To address this, the designed analyzer introduces variables like Smoothness and Percussion to provide more information and objectify measurements in the assessment of stand-up/sit-down actions. Both the analyzer and the proposed variables offer additional information that can objectify assessments depending on the clinical eye of the physicians.

Post Acute Sequelae of SARS-CoV-2 infection (PASC or Long COVID) is characterized by lingering symptomatology post-initial COVID-19 illness that is often debilitating. It is seen in up to 30–40% of individuals post-infection. Patients with Long COVID (LC) suffer from dysautonomia, malaise, fatigue, and pain, amongst a multitude of other symptoms. Fibromyalgia (FM) is a chronic musculoskeletal pain disorder that often leads to functional disability and severe impairment of quality of life. LC and FM share several clinical features, including pain that often makes them indistinguishable. The aim of this study is to develop a metabolic fingerprinting approach using portable Fourier-transform mid-infrared (FT-MIR) spectroscopic techniques to diagnose clinically similar LC and FM. Blood samples were obtained from LC (n = 50) and FM (n = 50) patients and stored on conventional bloodspot protein saver cards. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. Through the deconvolution analysis of the spectral data, a distinct spectral marker at 1565 cm−1 was identified based on a statistically significant analysis, only present in FM patients. This IR band has been linked to the presence of side chains of glutamate. An OPLS-DA algorithm created using the spectral region 1500 to 1700 cm−1 enabled the classification of the spectra into their corresponding classes (Rcv > 0.96) with 100% accuracy and specificity. This high-throughput approach allows unique metabolic signatures associated with LC and FM to be identified, allowing these conditions to be distinguished and implemented for in-clinic diagnostics, which is crucial to guide future therapeutic approaches.

Educational remote laboratories, when properly designed, have been demonstrated to be highly effective from a pedagogical point of view. Throughout the years their technology has evolved and they offer great capabilities, that are sometimes even superior to hands on labs. Nonetheless, despite their potential, they are not yet a widespread tool across learning institutions. One of the main reasons is that many remote laboratories have traditionally been research-oriented and have not been able to guarantee a high-enough quality of service (QoS) in a real-world educational environment. Such a QoS requires a relatively high number of students being able to access the labs concurrently, since classes may include dozens of students. Likewise, such a QoS requires reliability: the laboratory must work, be available and provide correct results. This work evaluates whether by applying an architecture oriented towards cost-effective instance replication and a model oriented towards fault-detection, it is possible to create laboratories that can provide a high QoS and that can therefore be used in a real environment, across multiple institutions. The study encompasses a period of 736 days and over 72,377 laboratory sessions, and relies on real data, from multiple institutions, of professors and students using the LabsLand Intel DE1-SoC FPGA remote laboratory, of which many instances are deployed. The results show that the QoS did indeed meet very high standards, and that such an approach can indeed lead to trusted remote laboratories, appropriate for real-world educational usage, and their eventual widespread adoption.

Abstract Vesicular stomatitis (VS) is a vector‐borne viral disease that causes lesions in livestock, premises, county and state quarantines, and important economic losses. We investigated vector–habitat characteristics for vectors associated with VS in regions of recurrent disease within the western United States (US) that consistently lead to the environment where vector, host, and pathogen populations intersect to enable pathogen transmission. We analyzed the habitats of previously identified insect vectors, including black flies (BFs) (Simulium vittatum complex), biting midges (BMs) (Culicoides variipennis complex, which includes Culicoides sonorensis), and sand flies (SFs) (Lutzomyia shannoni) in six regions of interest (ROIs) containing hotspots of VS ranging from Texas (TX) to Wyoming. This analysis broadened the understanding of (1) how regions of reoccurring VS differ from the broader western US, (2) how geographically separated regions and hotspots are similar across time, and (3) how vector–environment habitat a priori knowledge relates to observed hotspots. Analysis of watershed factors (livestock densities, land‐cover proportions, stream and lake densities, and irrigation methods) indicated a complex system separating areas with high, recurring VS from the broader western US. Although no single characteristic separated the six ROIs from other areas, we found two distinct emerging groups (northern ROI and TX). Hotspots, estimated from monthly VS concentrations, evolved northward throughout the year and most hotspots were closer to flowing water and agricultural land than the broader ROI. All ROIs contained environmental conditions suitable for multiple vectors at some point in the year, but BFs had the highest suitability scores, whereas BM scores were lower and varied annually with higher suitability in summer. SFs had the lowest suitability score in all ROIs, consistent with their low likelihood of being vectors. BM habitat patches were often orders of magnitude smaller than BF patches, and hotspot patches reinforce the likelihood that BF may be the most critical vector in northern ROI, whereas both BM and BF have similar likelihood in southern ROI. Given limited existing vector data, this analysis provides an alternate pathway for using habitat information to associate likely vectors responsible for transmission. Results could support early warning and mitigation efforts to reduce the incidence of VS.

Abstract Background Bone marrow-derived mesenchymal stem cells (BM-MSCs) have shown therapeutic potential in various in vitro and in vivo studies in cutaneous wound healing. Furthermore, there are ubiquitous studies highlighting the pro-regenerative effects of BM-MSC extracellular vesicles (BM-MSC EVs). The similarities and differences in BM-MSC EV cargo among potential healthy donors are not well understood. Variation in EV protein cargo is important to understand, as it may be useful in identifying potential therapeutic applications in clinical trials. We hypothesized that the donors would share both important similarities and differences in cargo relating to cell proliferation, angiogenesis, Wnt signaling, and basement membrane formation—processes shown to be critical for effective cutaneous wound healing. Methods We harvested BM-MSC EVs from four healthy human donors who underwent strict screening for whole bone marrow donation and further Good Manufacturing Practices-grade cell culture expansion for candidate usage in clinical trials. BM-MSC EV protein cargo was determined via mass spectrometry and Proteome Discoverer software. Corresponding proteomic networks were analyzed via the UniProt Consortium and STRING consortium databases. Results More than 3000 proteins were identified in each of the donors, sharing > 600 proteins among all donors. Despite inter-donor variation in protein identities, there were striking similarities in numbers of proteins per biological functional category. In terms of biologic function, the proteins were most associated with transport of ions and proteins, transcription, and the cell cycle, relating to cell proliferation. The donors shared essential cargo relating to angiogenesis, Wnt signaling, and basement membrane formation—essential processes in modulating cutaneous wound repair. Conclusions Healthy donors of BM-MSC EVs contain important similarities and differences among protein cargo that may play important roles in their pro-regenerative functions. Further studies are needed to correlate proteomic signatures to functional outcomes in cutaneous repair.

Background Stem cell therapy holds promise to improve healing and stimulate tissue regeneration after burn injury. Preclinical evidence has supported this; however, clinical studies are lacking. We examined the application of bone marrow-derived mesenchymal stem cells (BM-MSC) to deep second-degree burn injuries using a two-dose escalation protocol. Methods Ten individuals aged 18 years or older with deep second-degree burn wounds were enrolled. The first five patients were administered 2.5 × 10³ BM-MSC/cm 2 to their wounds. After safety of the initial dose level was assessed, a second group of five patients was treated with a higher concentration of 5 × 10³ allogeneic BM-MSC/cm 2 . Safety was assessed clinically and by evaluating cytokine levels in mixed recipient lymphocyte/donor BM-MSC reactions (INFγ, IL-10 and TNFα). At each visit, we performed wound measurements and assessed wounds using a Patient and Observer Scar Assessment Scale (POSAS). Results All patients responded well to treatment, with 100% closure of wounds and minimal clinical evidence of fibrosis. No adverse reactions or evidence of rejection were observed for both dose levels. Patients receiving the first dose concentration had a wound closure rate of 3.64 cm 2 /day. Patients receiving the second dose concentration demonstrated a wound closure rate of 10.47 cm 2 /day. The difference in healing rates between the two groups was not found to be statistically significant ( P = 0.17). Conclusion BM-MSC appear beneficial in optimising wound healing in patients with deep second-degree burn wounds. Adverse outcomes were not observed when administering multiple doses of allogeneic BM-MSC. Lay Summary Thermal injuries are a significant source of morbidity and mortality, constituting 5%–20% of all injuries and 4% of all deaths. Despite overall improvements in the management of acutely burned patients, morbidities associated with deeper burn injuries remain commonplace. Burn patients are too often left with significant tissue loss, scarring and contractions leading to physical loss of function and long-lasting psychological and emotional impacts. In previous studies, we have demonstrated the safety and efficacy of administering bone marrow-derived mesenchymal stem cells (BM-MSC) to chronic wounds with substantial improvement in healing and evidence of tissue regeneration. In this report, we have examined the application of BM-MSC to deep second-degree burn injuries in patients. The aim of the present phase I/II clinical trial was to examine the safety and efficacy of administering allogeneic BM-MSC to deep second-degree burns. We utilised two different dose levels at concentrations 2.5 × 10 3 and 5 × 10 3 cells/cm 2 . Patients with deep second-degree burn wounds up to 20% of the total body surface area were eligible for treatment. Allogeneic BM-MSC were applied to burn wounds topically or by injection under transparent film dressing

Today, one of the world’s biggest problems is the assurance of food integrity from farm to fork. Economically motivated food adulteration and food authenticity problems are increasing daily with considerable health and economic effects. Early detection and prevention of food integrity-related problems could be provided by the application of effective on-site food analysis technologies. FTIR spectroscopy coupled with chemometrics can be used for the rapid quality control of a wide variety of food products with fast, high-throughput, accurate and nondestructive analysis advantages. In particular, hand-held and portable FTIR instruments have the potential to surveil food quality and food safety in various critical segments of the food supply chain. In this review, we explore the abilities of hand-held and portable FTIR spectrometers combined with multivariate statistics to conduct a quality evaluation of various food products in terms of food adulteration and authenticity issues. An examination of the literature showed that comparable results were obtained based on detection limits, correlation coefficient (R2) values, standard error values and discrimination power by using both portable/hand-held FTIR spectrometers and benchtop FTIR spectrometers. In conclusion, this review highlights the potential usefulness of portable and hand-held FTIR spectrometers combined with chemometrics for maintaining the food quality through the presentation of various applications that may shed light for on-site food control at any point of the food supply chain.

Birth weight discordance (BWD) is not an uncommon event in twin pregnancies and can be associated with maternal and newborn characteristics. We aimed to analyse the association between maternal sociodemographic and newborn characteristics with BWD in twin infants born in Yucatan, Mexico, during 2008–2017 (n = 2091 pairs). BWD was calculated as the percentage of birth weight of the heavier twin. We defined three categories of BWD: concordant twins:

In this work, we propose and experimentally demonstrate a new distributed short linear cavity fiber laser. At one of the cavity ends, fabricated by a commercial femtosecond fiber laser chirped pulse amplifier, an artificially controlled backscattering erbium doped fiber section has been connected. This distributed reflector acts also as a saturable absorber, leading to the generation of tunable and switchable single longitudinal-mode laser emissions. The distributed reflector consists of 9 micro-drilled sections of about 1cm each one and randomly spread throughout 2 meters of highly doped erbium fiber. The total length of the fiber laser is 9.5 m and the laser shows a single mode behavior at all the emitted wavelengths. Using this new kind of reflecting saturable absorber, single and multiple single-mode emissions can be obtained. The achieved laser presents a pump threshold as low as 45 mW and shows up to 8 different single-mode emission lines with an optical signal to noise ratio of 45dB.

Educational remote laboratories allow users to access and control via the Internet remote equipment, that may be physically located anywhere in the world. They have a great potential for education, since they offer many advantages, such as cost reduction, high flexibility or the possibility of sharing equipment among institutions. However, their use is not yet as widespread as it could be. Freely available laboratories often present significant reliability issues. Instructors often plan their lessons in advance, and incorporating third-party tools that are prone to failure is risky, since they may be unavailable for the class and present errors to the students, which may make it necessary to suspend the session or find alternatives on the go. This contribution analyzes the reliability of a set of state-of-the-art laboratories with a view to categorizing and quantifying the most common failures. It then describes a multi-layered software model for detecting errors in laboratories. This model has two main goals. First, to ensure that the laboratory management system is aware of the state of the laboratory, so that users do not experience errors and laboratory maintenance personnel can repair it as soon as possible. Second, to serve as a base for a fault-tolerance model that leverages replicated instances of the laboratory. This fault-tolerance model is also described, and is designed to provide high availability and support for multiple concurrent users. The effectiveness of this model is validated by analyzing the reliability and availability of two remote laboratories in which it has been implemented.

Objectives: The aim of this study was to assess the cause-specific mortality rate related to COVID-19 (CMR) in patients with rheumatic and musculoskeletal diseases (RMDs) and COVID-19 and to analyze the role of the different RMDs in their mortality risk. Methods: An observational longitudinal study was conducted during the first pandemic wave in our center. Patients with the diagnosis of RMDs and COVID-19 were included. Main outcome is the death related to COVID-19. Independent variable – type of RMDs: autoimmune rheumatic diseases (ARD), such as chronic inflammatory arthritis (CIA) and connective tissue diseases (CTD) and non-autoimmune Rheumatic Diseases (non-ARD). Survival techniques were used to estimate the CMR per 1000 patients-month with a 95% confidence interval (CI), and Cox multivariate regression analysis was run to examine the effect of ARD compared to non-ARD on mortality risk adjusted by confounders. Results were expressed by Hazard Ratio (HR) and CI. Results: Overall, 405 patients were included (642.5 patients-month). During the study period, 44 (10.86%) deaths were recorded. CMR was 68.48 (50.96–92.01). After adjusting for confounders, HR of mortality in ARD compared to non-ARD did not achieve statistical significance [HR: 1.15 (0.64–2.07)], neither CTD versus CIA nor CTD versus non-ARD. Age and certain comorbidities which are being diagnosed in March compared to April or May [HR: 2.43 (1.1–5.55)] increased the mortality risk. Glucocorticoids and disease-modifying antirheumatic drugs (DMARDs) dropped from the final model. Conclusion: In patients with RMDs and COVID-19, CMR was 6.8% patients-month. This study shows that mortality risk is higher in males, older patients, and similar between CTD, CIA, and non-ARD. COVID-19 management improved after the first month of pandemic. Plain Language Summaries Mortality related to the outbreak of COVID-19 in patients with rheumatic and musculoskeletal diseases Why was this study done? - To report the COVID-19-specific mortality rate in patients with a variety of RMDs during the first pandemic peak in a tertiary hospital in Madrid and to analyze the role of specific types of ARD and other possible factors in the risk of death related to COVID-19. What did the researchers do? - We performed a retrospective observational study during the first wave of the COVID-19 pandemic in Madrid, Spain. What did the researchers find? - In this study, neither the different diagnoses of RMDs, including CIA, CTD, or non-ARD disease or its treatment were not implicated as a potential risk of death related to COVID-19 - In consonance with other studies, RMDs patients and COVID-19, older age, male sex, and certain comorbidities implied more mortality risk - Our data reflect COVID-19 severity in a particular context, time, and population. In times of the absence of COVID-19 vaccine, healthcare, social, and political measures taken to contain the coronavirus outbreak have worked properly. What do the findings mean? - The presence of comorbidities in RMDs patients represents a greater risk than the different types of RMDs themselves, in the development of COVID-19 fatal outcome. It is important to integrate the control of comorbidities in the daily management.

Introduction Non-infectious uveitis include a heterogeneous group of sight-threatening and incapacitating conditions. Their correct management sometimes requires the use of immunosuppressive drugs (ISDs), prescribed in monotherapy or in combination. Several observational studies showed that the use of ISDs in combination could be more effective than and as safe as their use in monotherapy. However, a direct comparison between these two treatment strategies has not been carried out yet.Methods and analysis The Combination THerapy with mEthotrexate and adalImumAb for uveitis (CoTHEIA) study is a phase III, multicentre, prospective, randomised, single-blinded with masked outcome assessment, parallel three arms with 1:1:1 allocation, active-controlled, superiority study design, comparing the efficacy, safety and cost-effectiveness of methotrexate, adalimumab or their combination in non-infectious non-anterior uveitis. We aim to recruit 192 subjects. The duration of the treatment and follow-up will last up to 52 weeks, plus 70 days follow-up with no treatment. The complete and maintained resolution of the ocular inflammation will be assessed by masked evaluators (primary outcome). In addition to other secondary measurements of efficacy (quality of life, visual acuity and costs) and safety, we will identify subjects’ subgroups with different treatment responses by developing prediction models based on machine learning techniques using genetic and proteomic biomarkers.Ethics and dissemination The protocol, annexes and informed consent forms were approved by the Reference Clinical Research Ethic Committee at the Hospital Clínico San Carlos (Madrid, Spain) and the Spanish Agency for Medicines and Health Products. We will elaborate a dissemination plan including production of materials adapted to several formats to communicate the clinical trial progress and findings to a broad group of stakeholders. The promoter will be the only access to the participant-level data, although it can be shared within the legal situation.Trial registration number 2020-000130-18; NCT04798755.

Abstract Background Rheumatoid arthritis (RA) is one of the leading chronic inflammatory rheumatism. First-line therapy with synthetic disease-modifying antirheumatic drugs (sDMARD) is insufficiently effective in 40% of cases and these patients are treated with biotherapies. The increased use of these drugs each year is becoming a public health issue with considerable economic burden. This cost is 20 times higher than that of sDMARD. However, among patients treated with biotherapies, clinical practice shows that about one third will not respond to the selected drug. In nonresponse cases, practitioners currently have no choice but to perform an empirical switching between different treatments, because no tool capable of predicting the response or nonresponse to these molecules is currently available. Methods The study is a prospective, phase III, controlled, multicenter, and randomized, single-blind (patient) clinical trial, including RA patients with a previous failure to anti-TNF therapies. The main objective is the analysis of the clinical and pharmacoeconomic impact after 6 months of treatment. Intervention arm: prescription of biotherapy (rituximab, adalimumab, abatacept) using SinnoTest® software, a prediction software based on proteomic biomarkers. Control arm: prescription of biotherapy based on current practice, without the SinnoTest® software (any biotherapy). In addition, a substudy will be carried out within this trial to generate a biobank and further analyze the proteomic profile of the patients and their modification throughout the study. Discussion This clinical trial study will be the first validation study of a biotherapy response prediction software, bringing personalized medicine into the management of RA. We expect that the findings from this study will bring several benefits for the patient and the Health Care System. Trial registration ClincalTrials.gov NCT04147026 . Registered on 31 October, 2019.

Technological advances in imaging and data acquisition are leading to the development of petabyte-scale neuroscience image datasets. These large-scale volumetric datasets pose unique challenges since analyses often span the entire volume, requiring a unified platform to access it. In this paper, we describe the Brain Observatory Storage Service and Database (BossDB), a cloud-based solution for storing and accessing petascale image datasets. BossDB provides support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API). A key feature is the scalable indexing of spatial data and automatic and manual annotations to facilitate data discovery. Our project is open source and can be easily and cost effectively used for a variety of modalities and applications, and has effectively worked with datasets over a petabyte in size.

Resiliency has been studied in the power and water systems separately. Often the resiliency study is not so comprehensive as to understand interdependent, integrated water and power systems. This research outlines the relevant factors necessary to understand and advance quantification of such integrated systems. It also presents a review of integrated water-power systems resiliency. Based on literature survey and identification of challenges, the authors present quantification and computational steps needed to understand integrated water-power systems resiliency. A conceptual framework is proposed to quantify integrated water-power system resiliency. Finally, the authors presented an opportunity for improved water and power system resilience.

Fibromyalgia syndrome (FM), one of the most common illnesses that cause chronic widespread pain, continues to present significant diagnostic challenges. The objective of this study was to develop a rapid vibrational biomarker-based method for diagnosing fibromyalgia syndrome and related rheumatologic disorders (systemic lupus erythematosus (SLE), osteoarthritis (OA) and rheumatoid arthritis (RA)) through portable FT-IR techniques. Bloodspot samples were collected from patients diagnosed with FM (n = 122) and related rheumatologic disorders (n = 70), including SLE (n = 17), RA (n = 43), and OA (n = 10), and stored in conventional protein saver bloodspot cards. The blood samples were prepared by four different methods (blood aliquots, protein-precipitated extraction, and non-washed and water-washed semi-permeable membrane filtration extractions), and spectral data were collected with a portable FT-IR spectrometer. Pattern recognition analysis, OPLS-DA, was able to identify the signature profile and classify the spectra into corresponding classes (Rcv > 0.93) with excellent sensitivity and specificity. Peptide backbones and aromatic amino acids were predominant for the differentiation and might serve as candidate biomarkers for syndromes such as FM. This research evaluated the feasibility of portable FT-IR combined with chemometrics as an accurate and high-throughput tool for distinct spectral signatures of biomarkers related to the human syndrome (FM), which could allow for real-time and in-clinic diagnostics of FM.

Purpose: To present a 22-month-old girl with a complete retinal detachment who was found to have systemic exam findings consistent with neurofibromatosis type 1 during the course of multi-specialty exam under anesthesia. Observations: During examination under anesthesia, ophthalmic exam findings demonstrated retinal detachment with cyst formation, as well as peripheral non-perfusion of the retina in the left eye. Non-ophthalmic findings discovered on difficulty with intubation included a laryngeal plexiform neurofibroma and café-au-lait spots. Conclusions: Pediatric retinal detachments are uncommon compared to those in adults. Pediatric patients with neurofibromatosis type 1 can present with vision loss as the presenting symptom. Systemic signs and symptoms should be carefully screen and monitored.

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world’s vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.

A questionnaire is a basic tool for collecting information in survey research. Often, these questions are measured using a Likert scale. With multiple items on the same broad object, these codes could be summed or averaged to give an indication of each respondent’s overall positive or negative orientation towards that object. This is the basis for Likert scales. Aggregation methods have been widely used in different research areas. Most of them are mathematical methods, such as the arithmetic mean, the weighted arithmetic mean, or the OWA (Ordered Weighted Averaging) operator. The usual presentation of Likert scale derived data are Mean. This paper presents a new approach to compute an aggregate value that represents Likert scale responses as a histogram adequate to treat better than Mean with asymmetric distributions. This method generates a set of partitions using an approach based on successive division. After every division, each partition is evaluated using a consensus measure and the one with the best value is then selected. Once the process of division has finished, the aggregate value is computed using the resulting partitions. Promising results have been obtained. Experiments show that our method is appropriate for distributions with large asymmetry and is not far from the behavior of the arithmetic mean for symmetric distributions. Overall, the article sheds light on the need to consider other presentations of Likert scale derived data beyond Mean more suitable for asymmetric distributions.

This work presents a dual-wavelength C-band erbium-doped fiber laser assisted by an artificial backscatter reflector. This fiber-based reflector, inscribed by femtosecond laser direct writing, was fabricated into a single mode fiber with a length of 32 mm. The dual-wavelength laser obtained, centered at 1527.7 nm and 1530.81 nm, showed an optical signal-to-noise ratio over 46 dB when pumped at 150 mW. Another feature of this laser was that the power difference between the two channels was just 0.02 dB, regardless of the pump power, resulting in a dual emission laser with high equalization. On the other hand, an output power level and a central wavelength instability as low as 0.3 dB and 0.01 nm were measured, in this order for both channels. Moreover, the threshold pump power was 40 mW. Finally, the performance of this dual-wavelength fiber laser enhanced with a random reflector for sensing applications was studied, achieving the simultaneous measurement of strain and temperature with sensitivities around 1 pm/με and 9.29 pm/°C, respectively.

ABSTRACT Hybridization is an important evolutionary mechanism that can enable organisms to adapt to environmental challenges. It has previously been shown that the fungal allodiploid species Verticillium longisporum, the causal agent of verticillium stem striping in rapeseed, originated from at least three independent hybridization events between two haploid Verticillium species. To reveal the impact of genome duplication as a consequence of hybridization, we studied the genome and transcriptome dynamics upon two independent V. longisporum hybridization events, represented by the hybrid lineages “A1/D1” and “A1/D3.” We show that V. longisporum genomes are characterized by extensive chromosomal rearrangements, including between parental chromosomal sets. V. longisporum hybrids display signs of evolutionary dynamics that are typically associated with the aftermath of allodiploidization, such as haploidization and more relaxed gene evolution. The expression patterns of the two subgenomes within the two hybrid lineages are more similar than those of the shared A1 parent between the two lineages, showing that the expression patterns of the parental genomes homogenized within a lineage. However, as genes that display differential parental expression in planta do not typically display the same pattern in vitro, we conclude that subgenome-specific responses occur in both lineages. Overall, our study uncovers genomic and transcriptomic plasticity during the evolution of the filamentous fungal hybrid V. longisporum and illustrates its adaptive potential. IMPORTANCE Verticillium is a genus of plant-associated fungi that includes a few plant pathogens that collectively affect a wide range of hosts. On several occasions, haploid Verticillium species hybridized into the stable allodiploid species Verticillium longisporum, which is, in contrast to haploid Verticillium species, a Brassicaceae specialist. Here, we studied the evolutionary genome and transcriptome dynamics of V. longisporum and the impact of the hybridization. V. longisporum genomes display a mosaic structure due to genomic rearrangements between the parental chromosome sets. Similar to other allopolyploid hybrids, V. longisporum displays an ongoing loss of heterozygosity and more relaxed gene evolution. Also, differential parental gene expression is observed, with enrichment for genes that encode secreted proteins. Intriguingly, the majority of these genes display subgenome-specific responses under differential growth conditions. In conclusion, hybridization has incited the genomic and transcriptomic plasticity that enables adaptation to environmental changes in a parental allele-specific fashion.

BackgroundAccumulating evidence suggests that the COVID-19 pandemic has negatively impacted the mental health of individuals. However, the susceptibility of individuals to be impacted by the pandemic is variable, suggesting potential influences of specific factors related to participants’ demographics, attitudes, and practices. ObjectiveWe aimed to identify the factors associated with psychological symptoms related to the effects of the first wave of the pandemic in a multicountry cohort of internet users. MethodsThis study anonymously screened 13,332 internet users worldwide for acute psychological symptoms related to the COVID-19 pandemic from March 29 to April 14, 2020, during the first wave of the pandemic amidst strict lockdown conditions. A total of 12,817 responses were considered valid. Moreover, 1077 participants from Europe were screened a second time from May 15 to May 30, 2020, to ascertain the presence of psychological effects after the ease down of restrictions. ResultsFemale gender, pre-existing psychiatric conditions, and prior exposure to trauma were identified as notable factors associated with increased psychological symptoms during the first wave of COVID-19 (P

Electroencephalography (EEG) signals analysis is non-trivial, thus tools for helping in this task are crucial. One typical step in many studies is feature extraction, however, there are not many tools focused on that aspect. In this paper, eeglib: a Python library for EEG feature extraction is presented. It includes the most popular algorithms when working with EEG and can be easily combined with popular Python libraries. This paper also presents a simple workflow for creating features dataset which allows a high degree of customization and that is suitable for both experts and newcomers.

Obesity has been established as a risk factor for renal cell carcinoma (RCC). Recently, studies have described obesity as a probable protecting factor in the metastatic stage of RCC. In this study, we assessed the relationship between body mass index (BMI) and overall survival in patients under systemic therapy. The correlation between BMI and overall median survival was studied in 76 patients diagnosed with metastatic RCC under systemic therapy. The groups were divided into overweight and obesity (BMI > 25 kg/m2) and underweight or normal (BMI < 25 kg/m2). Statistical analysis was performed using the Cox regression model adjusted by gender. A total of 76 patients were studied: 16 women (21%) and 60 men (79%). The median BMI was 27.96 kg/m2; 24 patients (31.6%) had low BMI and 52 (68.4%) had high BMI. Median overall survival in the group with BMI > 25 kg/m2 was 17 months (95% confidence interval [CI]: 13–34 months), while in the group with BMI ≤ 25 kg/m2, it was 14 months (95% CI: 8–20 months). When adjusted by gender, the group with BMI > 25 kg/m2 presented a hazards ratio of 0.54 (95% CI: 0.30–0.96), P = 0.044 (Log Rank). A high BMI significantly acts as a protecting factor. We observed an increased overall survival of overweight and obese patients within the context of metastatic RCC under systemic treatment. These data confirm the findings published in other studies that suggest the role of lipid metabolism in this type of tumors.

Summary: Large-scale mapping of antigens and epitopes is pivotal for developing immunotherapies but challenging, especially for eukaryotic pathogens, owing to their large genomes. Here, we developed an integrated platform for genome phage display (gPhage) to show that unbiased libraries of the eukaryotic parasite Trypanosoma cruzi enable the identification of thousands of antigens recognized by serum samples from patients with Chagas disease. Because most of these antigens are hypothetical proteins, gPhage provides evidence of their expression during infection. We built and validated a comprehensive map of Chagas disease antibody response to show how linear and putative conformation epitopes, many rich in repetitive elements, allow the parasite to evade a buildup of neutralizing antibodies directed against protein domains that mediate infection pathogenesis. Thus, the gPhage platform is a reproducible and effective tool for rapid simultaneous identification of epitopes and antigens, not only in Chagas disease but perhaps also in globally emerging/reemerging acute pathogens.

Abstract China has a huge resource potential for biomass‐based renewable energy development, but the resources of field residues are still not effectively used. Rice, maize, and wheat made up 89% of staple crop production in China in 2009. A comprehensive assessment of field residues of these three crops is necessary for the development of biomass‐based industries. This research was based on multiyear county‐level data of crop production, area and yield, as well as the crop phenology information from agrometeorological stations. Spatial and temporal analyses were conducted to quantify the spatial patterns, seasonal variations, and temporal trends of the three major field residues. The mean amount of field residue of rice, maize, and wheat was 470.8 Mt/year from 2002 to 2009. Rice residue topped the field residues at 188.5 Mt/year, followed by maize (152.6 Mt/year) and wheat (129.8 Mt/year). The resource supply of field residues varied temporally throughout the season, where peak months are May, June, September, and October. The resources of all three field residues increased from 2002 to 2009, topped by maize residues at a rate of 10.0 Mt/year. Spatially, high production counties had the fast growth rate and a strong positive spatial autocorrelation. The results showed that the intersection area of East and South Central regions has a spatially concentrated residue density and a stable supply for 5 months. The region can be considered as a suitable region for bioenergy development. A better understanding of spatial and temporal distribution of crop residues could facilitate strategic and tactical bioenergy planning.

Abstract Purpose The purpose of the study was to compare the safety and efficacy of autologous mesenchymal stem cells (MSCs) embedded in a xenogenic scaffold for repairing the supraspinatus tendon. Methods This was a randomized, double-blind and placebo-controlled trial evaluating patients with full-thickness rotator cuff tears (Eudra-CT, 2007–007630-19). Effectiveness was evaluated using the Constant score and a visual analogue pain scale (VAS). Constant score has four domains including pain (15 possible points), activities of daily living (20 possible points), mobility (40 possible points), and strength (25 possible points). Scores range from 0 points (most disability) to 100 points (least disability). The structural integrity of the repaired tendon was assessed by magnetic resonance imaging (MRI) according to Patte and Thomazeau classification criteria. The primary study end point was an improvement in the Constant score by 20 points at one year compared to initial assessment. Results The trial was stopped due to adverse effects observed in both groups. Only thirteen patients were included and analyzed. The Constant questionnaire showed a significant improvement in the MSC treatment group compared with the preoperative data (p = 0.0073). Secondary outcome measures were similar in both groups. Conclusions Our study showed preliminary inconclusive clinical outcomes in the patients treated with MSCs. Adverse events revealed the need for further approaches using scaffolds of a different nature or perhaps no scaffolds, in the context of small joints. Trial registration Eudra-CT, 2007-007630-19. Registered on 30 January 2008. Level of evidence A Level 1 of evidence treatment study.

Abstract Background Allogeneic cardiac-derived progenitor cells (CPC) without immunosuppression could provide an effective ancillary therapy to improve cardiac function in reperfused myocardial infarction. We set out to perform a comprehensive preclinical feasibility and safety evaluation of porcine CPC (pCPC) in the infarcted porcine model, analyzing biodistribution and mid-term efficacy, as well as safety in healthy non-infarcted swine. Methods The expression profile of several pCPC isolates was compared with humans using both FACS and RT-qPCR. ELISA was used to compare the functional secretome. One week after infarction, female swine received an intracoronary (IC) infusion of vehicle (CON), 25 × 106 pCPC (25 M), or 50 × 106 pCPC (50 M). Animals were followed up for 10 weeks using serial cardiac magnetic resonance imaging to assess functional and structural remodeling (left ventricular ejection fraction (LVEF), systolic and diastolic volumes, and myocardial salvage index). Statistical comparisons were performed using Kruskal-Wallis and Mann-Whitney U tests. Biodistribution analysis of 18F-FDG-labeled pCPC was also performed 4 h after infarction in a different subset of animals. Results Phenotypic and functional characterization of pCPC revealed a gene expression profile comparable to their human counterparts as well as preliminary functional equivalence. Left ventricular functional and structural remodeling showed significantly increased LVEF 10 weeks after IC administration of 50 M pCPC, associated to the recovery of left ventricular volumes that returned to pre-infarction values (LVEF at 10 weeks was 42.1 ± 10.0% in CON, 46.5 ± 7.4% in 25 M, and 50.2 ± 4.9% in 50 M, p

Intelligent tutors and conversational agents (CAs) have proven to be useful learning tools. They have potential not only as stand-alone devices but also as integrable components to enrich and complement other educational resources. For this, new authoring approaches and platforms are required. They should be accessible to non-programmers (such as most teachers) and they should be integrable into current web-based educational platforms. This paper proposes a new approach to define such agents through a visual domain-specific language based on Google Blockly (a scratch-like language). It also develops a web-based integrable authoring platform to serve as a prototype, describing the requirements and architecture. To evaluate whether this novel approach is effective, a multi-stage experiment was conducted. First, participants learned to use the prototype authoring platform through an interactive tutorial. Second, they created a CA with a specific domain model. Times and performance were measured. Finally, they answered a standardized usability questionnaire (UMUX) and a purpose-specific survey. Results show that participants were able to learn to use the domain-specific language in a short time. Moreover, the purpose-specific survey indicates that their perception of the approach (and its potential) is positive. The standardized questionnaire indicates that even in its prototype stage, its usability is satisfactory.

Online remote laboratories are a particularly promising tool for effective STEM education. They offer online universal access to different hardware devices in which students can experiment and can test and improve their knowledge. However, most of them have two significant limitations. First, given that most of them are developed as, or evolve from single-user proofs of concept, they have no scalability provisions other than full laboratory replication. And second, when this is done, cost efficiency is often neglected. This paper presents the requirements for the creation of a novel remote laboratory architecture focused on, but not limited to, embedded systems experimentation. An architecture, based on Redis (an open source, in-memory data structure store, which is often used as database, cache or message broker), a modular design, and hardware-sharing techniques, is proposed in order to achieve the combined requirements of high scalability and cost efficiency. This mixed hardware-software architecture serves as a basis for the development of remote laboratories, especially those focused on microcontroller-based systems experimentation and embedded devices experimentation. From a user perspective the architecture is web-based, and has provisions to be easily adaptable to different Learning Management Systems and different hardware embedded devices. A new microcontroller-oriented remote laboratory based on the architecture has been developed, with the aim of providing valid evaluation data, and has been used in a real environment. The architecture and the resulting remote laboratory have been compared with other state of the art remote laboratories and their architectures. Results suggest that the proposed architecture does indeed meet the main requirements, which are scalability through replicability and cost efficiency. Furthermore, similarly to previous architectures, it promotes usability, universal access, modularity and reliability.

Abstract Background In recent years, research has consistently proven the occurrence of genetic overlap across autoimmune diseases, which supports the existence of common pathogenic mechanisms in autoimmunity. The objective of this study was to further investigate this shared genetic component. Methods For this purpose, we performed a cross-disease meta-analysis of Immunochip data from 37,159 patients diagnosed with a seropositive autoimmune disease (11,489 celiac disease (CeD), 15,523 rheumatoid arthritis (RA), 3477 systemic sclerosis (SSc), and 6670 type 1 diabetes (T1D)) and 22,308 healthy controls of European origin using the R package ASSET. Results We identified 38 risk variants shared by at least two of the conditions analyzed, five of which represent new pleiotropic loci in autoimmunity. We also identified six novel genome-wide associations for the diseases studied. Cell-specific functional annotations and biological pathway enrichment analyses suggested that pleiotropic variants may act by deregulating gene expression in different subsets of T cells, especially Th17 and regulatory T cells. Finally, drug repositioning analysis evidenced several drugs that could represent promising candidates for CeD, RA, SSc, and T1D treatment. Conclusions In this study, we have been able to advance in the knowledge of the genetic overlap existing in autoimmunity, thus shedding light on common molecular mechanisms of disease and suggesting novel drug targets that could be explored for the treatment of the autoimmune diseases studied.

Objective: To compare the capacity of various disease activity indices to evaluate changes in function, IL-6 levels, and radiographic progression in early and established rheumatoid arthritis (RA).Methods: Secondary data analysis of a clinical trial assessing the efficacy of tocilizumab in patients with established RA (ACT-RAY) and a longitudinal prospective register of early arthritis (PEARL). Targeted outcomes were changes in physical function, measured with the health assessment questionnaire (HAQ), IL-6 serum levels, and radiographic progression. The “Hospital Universitario La Princesa Index” (HUPI), DAS28 using erythrocyte sedimentation rate and SDAI were the disease activity indices compared. Models adjusted for age and sex were fitted for each outcome and index and ranked based on the R2 parameter and the quasi-likelihood under the independence model criterion.Results: Data from 8,090 visits (550 patients) from ACT-RAY and 775 visits (534 patients) from PEARL were analyzed. The best performing models for HAQ were the HUPI (R2 = 0.351) and SDAI ones (R2 = 0.329). For serum IL-6 levels, the SDAI (R2 = 0.208) followed by the HUPI model (R2 = 0.205). For radiographic progression in ACT-RAY, the HUPI (R2 = 0.034) and the DAS28 models (R2 = 0.026) performed best whereas the DAS28 (R2 = 0.030) and HUPI models (R2 = 0.023) did so in PEARL.Conclusions: HUPI outperformed other indices identifying changes in HAQ and radiographic progression and performed similarly to SDAI for IL-6 serum levels.

The primary goal of the present research was to determine the order of swimmers on a mixed relay team that would ensure the best performance in the Fédération Internationale de Natation (FINA) World Championships held in Kazan (Russia, 2015), Budapest (Hungary, 2017), and Gwangju (South Korea, 2019). The data were obtained from database websites for the 4 × 100 m freestyle and 4 × 100 m medley official results,1 including 660 records from 188 entries of finals and 472 preliminary events. The results showed that the fastest swimmers (according to their best season times) were located primarily in the first or second positions of the freestyle relay. The most successful gender strategy for the 4 × 100 m freestyle (57 out of 82 observations) and for the 4 × 100 m medley (29 out of 83) relays was the order male-male-female-female, although no statistical differences were found (p = 0.79) for the medley relays. In the 4 × 100 m freestyle, the second (p = 0.002; β = 1.62) and third (p =0.003; β = 1.41) relay legs had a statistical effect on the total relay time, whereas in the 4 × 100 m medley, all four relay legs had a statistical effect (p < 0.001) on the final performance, the weight of the four strokes being different in heats with respect to the final round. Also, a later position of the first female swimmer or the consecutive position of two female swimmers in the team order significantly affected the relay performance in specific events. Mixed relay events appeared to present specific strategies in comparison to traditional male- or female-only relay lineups.

Aims: In this pandemic, it is essential for rheumatologists and patients to know the relationship between COVID-19 and inflammatory rheumatic diseases (IRDs). We wanted to assess the role of targeted synthetic or biologic disease-modifying antirheumatic drugs (ts/bDMARDs) and other variables in the development of moderate-severe COVID-19 disease in IRD. Methods: An observational longitudinal study was conducted during the epidemic peak in Madrid (1 March to 15 April 2020). All patients attended at the rheumatology outpatient clinic of a tertiary hospital in Madrid with a medical diagnosis of IRD were included. Main outcome: hospital admission related to COVID-19. Independent variable: ts/bDMARDs. Covariates: sociodemographic, comorbidities, type of IRD diagnosis, glucocorticoids, non-steroidal anti-inflammatory drugs (NSAIDs), and conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). Incidence rate (IR) of hospital admission related to COVID-19 was expressed per 1000 patient-months. Cox multiple regression analysis was run to examine the influence of ts/bDMARDs and other covariates on IR of hospital admission related to COVID-19. Results: A total of 3951 IRD patients were included (5896 patient-months). Methotrexate was the csDMARD most used. Eight hundred and two patients were on ts/bDMARDs, mainly anti-TNF agents, and Rtx. Hospital admissions related to COVID-19 occurred in 54 patients (1.36%) with an IR of 9.15 (95% confidence interval: 7–11.9). In the multivariate analysis, older, male, comorbidities, and specific systemic autoimmune conditions (Sjögren, polychondritis, Raynaud, and mixed connective tissue disease) had more risk of hospital admissions. Exposition to ts/bDMARDs did not achieve statistical significance. Use of glucocorticoids, NSAIDs, and csDMARDs dropped from the final model. Conclusion: This study provides additional evidence in IRD patients regarding susceptibility to moderate–severe infection related to COVID-19.

The appearance of defects during the manufacture of tanker trucks via arc-welding is a significant problem in the industry. A reliable low-cost and non-destructive on-line method could aid the discovery of solutions to overcome productivity problems. Plasma optical spectroscopy was employed in this study to correlate the presence of several elemental emission lines with certain quality-related events, such as the appearance of porosities. Results obtained through field trials and also during in-line production show that the convenient processing of acquired process signals facilitates not only the detection of defects, but also the identification of their causes. Output monitoring signals have been compared with X-ray inspections of the seam welds performed. It has been demonstrated that the spectroscopic monitoring variables obtained are good indicators for evaluating contamination in the process and therefore the occurrence of welding defects.