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Fulminant myocarditis (FM) is a rare, distinct form of myocarditis that has been difficult to classify. Since 1991, the definition of FM has evolved, and it is currently considered an acute illness with hemodynamic derangement and arrhythmias due to a severe inflammatory process requiring support of cardiac pump function and/or urgent management of serious arrhythmias. Diagnosis is aided through use of biomarkers and cardiac imaging, but endocardial biopsy remains the gold standard. Recent evidence has revealed that patients with FM are significantly more likely to die or require heart transplantation than those with the nonfulminant form, refuting previous studies proposing a paradoxically low mortality in patients with FM. Acute hemodynamic derangement is managed by intensive contemporary pharmacologic and interventional approaches, whereas the role of immunosuppressive therapy has not been clarified. Early recognition and aggressive management are essential for favorable outcomes. In conclusion, FM is an inflammatory process requiring intensive support, and it causes a higher morbidity and mortality than acute nonfulminant myocarditis.

Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies offer protection in interactions in dispersed locations such as, e-commerce, mobile networking, telecommunications and management of network. Furthermore, this article proposed on intelligent feature selection methods and intrusion detection (ISTID) organization in webs based on neuron-genetic algorithms, intelligent software agents, genetic algorithms, particulate swarm intelligence and neural networks, rough-set. These techniques were useful to identify and prevent network intrusion to provide Internet safety and improve service value and accuracy, performance and efficiency. Furthermore, new algorithms of intelligent rules-based attributes collection algorithm for efficient function and rules-based improved vector support computer, were proposed in this article, along with a survey into the current smart techniques for intrusion detection systems.

Cancer-associated fibroblasts (CAF) may exert tumor-promoting and tumor-suppressive functions, but the mechanisms underlying these opposing effects remain elusive. Here, we sought to understand these potentially opposing functions by interrogating functional relationships among CAF subtypes, their mediators, desmoplasia, and tumor growth in a wide range of tumor types metastasizing to the liver, the most common organ site for metastasis. Depletion of hepatic stellate cells (HSC), which represented the main source of CAF in mice and patients in our study, or depletion of all CAF decreased tumor growth and mortality in desmoplastic colorectal and pancreatic metastasis but not in nondesmoplastic metastatic tumors. Single-cell RNA-Seq in conjunction with CellPhoneDB ligand-receptor analysis, as well as studies in immune cell-depleted and HSC-selective knockout mice, uncovered direct CAF-tumor interactions as a tumor-promoting mechanism, mediated by myofibroblastic CAF-secreted (myCAF-secreted) hyaluronan and inflammatory CAF-secreted (iCAF-secreted) HGF. These effects were opposed by myCAF-expressed type I collagen, which suppressed tumor growth by mechanically restraining tumor spread, overriding its own stiffness-induced mechanosignals. In summary, mechanical restriction by type I collagen opposes the overall tumor-promoting effects of CAF, thus providing a mechanistic explanation for their dual functions in cancer. Therapeutic targeting of tumor-promoting CAF mediators while preserving type I collagen may convert CAF from tumor promoting to tumor restricting.

Ovarian cancer is one of the leading causes of cancer-related mortality among women and remains exceptionally difficult to manage and treat effectively in the clinic. Fragile X-related protein 1 (FXR1) is highly amplified and overexpressed in ovarian and several other cancers. FXR1 is a key regulator of the translation of multiple oncogenes and therefore represents a vulnerable target for cancer therapy. RNA interference (RNAi) of FXR1 using a locked nucleic acid (LNA) form of siRNA (siFXR1-LNA) inhibits tumor growth, ascites formation, and metastasis of ovarian cancer more efficiently than the native form of FXR1 siRNA in vivo. LNA modification of siRNA improves resistance to RNase mediated degradation and enhances tumor tissue uptake of siRNA with robust inhibition of target mRNA in tumor tissues. Single-cell RNA sequencing (scRNA-seq) analysis of ascites composed of tumor, stromal, and immune cells analysis reveals that FXR1 silencing suppresses tumor cell proliferation and reduces tumor-promoting M2-like macrophages. FXR1 silencing also increases cytotoxic T cells, NK cells, and dendritic cells with anti-tumor characteristics in vivo. Collectively, our data establishes FXR1 as an important regulator of oncogenic processes in cancer tissues and serves as a therapeutic liability. Therefore, FXR1 silencing in tumor tissues provides an effective strategy to treat tumors expressing high levels of FXR1. Fragile X-related protein 1 (FXR1) is a potential therapeutic target for ovarian cancer. Here, the authors show that RNA interference of FXR1 using a locked nucleic acid (LNA) form enables efficient inhibition of ovarian cancer growth and metastasis; single-cell RNA sequencing reveals the impacts on tumour proliferation pathways and the immune microenvironment.

Background Academic leadership within medical schools shapes institutional culture, policy, and educational priorities. While demographic diversity has been studied, specialty representation in leadership is less understood. This study evaluates the distribution of medical specialties in dean’s cabinets at the top 40 National Institutes of Health (NIH)-funded United States medical schools compared with national and hospital-based physician workforce data. Methods Publicly available institutional websites were reviewed to identify dean’s cabinet members across eight common leadership roles. Degree type and specialty (for MD/DO holders) were obtained from institutional profiles. Specialty representation was compared with 2023 national and hospital-based physician workforce data using paired t-tests. Results Of 320 leaders identified, 287 (89.7%) held an MD or DO. Internal Medicine (IM) accounted for 46.0%, followed by Pediatrics (13.2%) and Obstetrics/Gynecology (5.6%). Compared with the national workforce, IM ( p  < 0.0001), Pediatrics ( p  = 0.006), and Neurosurgery ( p  = 0.003) were overrepresented, while Family Medicine (FM; p  < 0.0001), Emergency Medicine ( p  = 0.04), Anesthesiology ( p  = 0.008), Orthopedic Surgery ( p  = 0.016), and Ophthalmology ( p  = 0.037) were underrepresented. Similar trends were observed against hospital-based workforce data, with additional overrepresentation of Dermatology ( p  = 0.0008), ENT ( p  = 0.0005), and Plastic Surgery ( p  < 0.00001). Among IM leaders, 41.4% were generalists and 58.6% subspecialists, most commonly in Cardiology, Infectious Disease, and Pulmonary/Critical Care. Conclusions Dean’s cabinets at top NIH-funded medical schools are dominated by IM and Pediatrics, with primary care, acute care, and procedural specialties underrepresented. These disparities may influence curriculum design, mentorship, and educational priorities related to community-based care, interprofessional education, interdisciplinary collaboration, and specialty-specific career pathways. Leadership development initiatives targeting underrepresented specialties could diversify expertise in academic medical governance.

Interest in local foods, especially locally grown fruit, is increasing. High tunnel vegetable growers are strategically poised to meet this demand by growing specialty melons ( Cucumis melo ). Although specialty melons are commonly grown in high tunnels in other parts of the world, it is an uncommon practice in the midwestern United States. The objectives of this study were to evaluate 10 specialty melon cultivars for high tunnel production and measure fruit yield and internal quality. Fruit of the cultivar Eden’s Gem yielded the greatest number of marketable fruits per plant; however, these melons are small and have a loose cavity. Fruit of the cultivars Honey Orange and Divergent yielded the largest marketable fruit per plant with tighter cavities; however, the cavities were large. All cultivars had good to excellent internal quality in terms of sugar content. The production of specialty melons in the high tunnel was successful, resulting in the production of melons with good to excellent internal quality, and several yielded three to four marketable fruit per plant. Implementing a strong pest management plan for cucumber beetle ( Diabrotica undecimpunctata howardi ) and powdery mildew ( Erysiphe cichoracearum, Sphaerotheca fuliginea ) is recommended to prevent yield loss, especially in locations such as the Midwest, where cucumber beetles often vector bacterial wilt ( Erwinia tracheiphila) .

Soil moisture is classified as an essential climate variable (ECV) and is relevant to understanding hydrological, agricultural and ecological processes. Yet, in spite of its importance, direct observations of soil moisture remain limited globally—those that exist are typically limited in duration and spatial extent. Consequently, alternative approaches for estimating soil moisture have been developed, including water balance (‘bucket’) models, the use of remotely sensed information and the application of land surface modelling techniques. Spaceborne and land surface modelling based methods offer significant potential for monitoring and modelling soil moisture at a variety of spatial scales; however, their resolution remains relatively coarse for global and continental scale applications. At country scale, land surface models have demonstrated their potential but they require access to computational resources to deliver high resolution products. With the advent of machine‐ and deep‐ learning and data fusion techniques, high resolution global and regional soil moisture datasets are increasingly becoming available. Here, we evaluated a statistical machine learning approach to downscale the European Space Agency's (ESA) Climate Change Initiative (CCI) combined passive and active soil moisture product for Ireland using covariates that included both static (e.g., topography) and dynamic (e.g., gridded rainfall and temperature) variables. The model was developed using in situ cosmic ray neutron sensor (CRNS) measurements obtained from a network of sites in the United Kingdom, justified on the basis that the United Kingdom is geographically similar to Ireland in terms of its climate, soil types and land cover management practices. The model was found to perform reasonably well when validated against limited in situ data obtained from available time domain reflectometry (TDR) measurements available from Ireland. The developed model was subsequently used to derive spatial estimates of soil moisture on a 1 km grid across the Republic of Ireland. A process‐informed machine learning approach, which included dynamic and static earth observation data and trained on in situ data from the United Kingdom, was capable of reproducing measured in situ values from locations not included in the model training. The model was then employed to derive daily, gridded estimates of soil moisture for Ireland. The results have relevance for informing sectors that require information on soil moisture but are currently not available due to limited in situ measurements.

The Soil and Water Assessment Tool (SWAT) includes plant parameters for only a few fruits and vegetables. Testing SWAT parameters for these crops remains very limited, including the need for evaluation of table food crops in historically low production areas. This study tests SWAT simulations for fruits and vegetables in the U.S. Western Corn Belt, to advance model evaluation in a data-limited region. We focus on 24 crops, integrating parameters from related models, expert opinions, and expected versus simulated yields. Parameters for 15 crops in the SWAT database were revised and nine crops were added. The resulting models achieved yield simulation errors within ±37%, a reasonable level of accuracy for underrepresented crops, and statistical tests further supported the robustness of the simulations. Future climate scenario analyses also revealed potential yield impacts and emphasized the need for adaptation strategies. Overall, this study helps fill important gaps in SWAT applications for fruits and vegetables and supports efforts to expand local table food production and crop diversification, although further testing is needed across additional climatic regions and longer crop yield time series.

Bacterial wilt of cucurbits, caused by Erwinia tracheiphila, is spread by spotted ( Diabrotica undeimpunctata howardi ) and striped ( Acalymma vittatum ) cucumber beetles and results in major losses for US cucurbit (Cucurbitaceae spp.) growers. Organic growers of muskmelon ( Cucumis melo ) lack reliable control measures against bacterial wilt. During previous field trials in Iowa, USA, a system called mesotunnels, which are 3.5-ft-tall barriers covered with a nylon mesh insect netting, resulted in a higher marketable yield of organic ‘Athena’ muskmelon than low tunnels or noncovered plots. However, satisfactory pollination and weed control are challenging in mesotunnels because the netting covers the crop for most or all of the growing season, and economic feasibility of these systems has not been determined. Consequently, two field trials conducted in Iowa from 2020 to 2022 evaluated strategies to ensure pollination under mesotunnels in commercial-scale plots, assess effectiveness of teff ( Eragrostis tef ) as a living mulch for weed control in mesotunnel systems, and compare the profitability of the treatment options for organic ‘Athena’ muskmelon. The treatments used during the pollination trial were as follows: full season, in which mesotunnels remained sealed all season and bumble bees ( Bombus impatiens ) were added at the start of bloom for pollination; open ends, wherein both ends of the tunnels were opened at the start of bloom then reclosed 2 weeks later; and on-off-on, in which nets were removed at the start of bloom and then reinstalled 2 weeks later. The full-season treatment had significantly higher marketable yield than the other treatments in two of three trial years. Plants with the full season and open ends treatments had a bacterial wilt incidence <2.5% across all three years and similar numbers of cucumber beetles, whereas plants with the on-off-on treatment had an average bacterial wilt incidence of 11.0% and significantly more cucumber beetles. The open ends treatment had fewer bee visits to ‘Athena’ muskmelon flowers than the other treatments. In the 2-year (2021–22) weed management trial, treatments applied to the furrow between plastic-mulched rows were as follows: landscape fabric; teff seeded at 4 lb/acre and mowed 3 weeks after seeding; teff seeded at 4 lb/acre and not mowed; a control with bare ground where weeds were mowed 3 weeks after transplanting; and a bare ground control with no mowing. The landscape fabric and mowed teff treatments had statistically similar marketable yield, and mowing appeared to minimize yield losses compared with nonmowed treatments. The landscape fabric had no weeds, followed by mowed teff, mowed bare ground, and nonmowed teff. Nonmowed bare ground had the highest weed biomass. The partial budget and cost-efficiency ratio analysis indicated that the full-season treatment was the most cost-efficient pollination option for mesotunnel systems. An economic analysis of the weed management strategies showed that using teff as a living mulch in the furrows between organic ‘Athena’ muskmelon rows, coupled with timely mowing to suppress its growth, can generate revenue comparable to that of landscape fabric. Our findings suggest that organic ‘Athena’ muskmelon growers in Iowa may gain the greatest yield and soil quality benefits when mesotunnels are kept closed for the entire season, bumble bees are used for pollination, and teff (mowed 3 weeks after seeding) is used to control weeds in the furrows. Further trials integrating these pollination and weed management strategies would help validate a comprehensive approach to organic ‘Athena’ muskmelon production under mesotunnels.

Organic growers of cucurbit (Cucurbitaceae) crops in the midwestern United States have difficulty managing bacterial wilt—a fatal disease with a pathogen ( Erwinia tracheiphila ) that is transmitted by striped and spotted cucumber beetles ( Acalymma vittatum and Diabrotica undecimpunctata howardi , respectively). Registered organic insecticides lack effectiveness, and host plant resistance is rare in commercial cultivars of many cucurbit crops. Row covers are widely used as barriers to minimize pest access, but the spunbonded polypropylene fabric covering traditional low tunnels must be removed at bloom to prevent overheating and facilitate pollination, thereby exposing the crop for the rest of the season. “Mesotunnels”—nylon mesh fabric covering 3.5-ft-high hoops—provide more space than low tunnels and mitigate overheating. In field experiments at Iowa State University (Ames, IA, USA) during 2016–18, two variations of mesotunnels—full-season tunnels [with purchased bumble bees ( Bombus impatiens ) added for pollination] and part-season tunnels (with covers removed for 2 weeks during bloom to provide pollinator access)—were compared with low tunnels and a noncovered treatment for organic ‘Athena’ muskmelon ( Cucumis melo) production. Based on scouting results, full-season mesotunnels required no insecticides and part-season mesotunnels averaged 0.6 spray per season compared with 1.0 and 5.0 sprays per season for the low-tunnel and noncovered treatments, respectively. Incidence of pest and disease damage was zero for the full-season mesotunnels, 5% to 22% for the part-season mesotunnels, and 37% to 70% for both of the other treatments. Marketable yield for the full-season mesotunnel treatment exceeded the noncovered treatment significantly each year, and mean marketable yields were greater numerically than for the other treatments. Both mesotunnel treatments had a marketable yield that averaged more than twice that of the noncovered treatment in each year. Economic analysis (partial budget and cost-efficiency ratio) indicated that mesotunnels were likely to be more profitable in Iowa, USA, than either the low-tunnel or noncovered systems, but also that the year-to-year differential among treatments in profitability could be substantial. Additional experiments are needed to evaluate the efficacy of these integrated pest management practices and their profitability at spatial scales representative of commercial farms.