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Efficient thermal management in microelectronic assemblies is crucial for the optimal performance and reliability of microprocessors. This study investigates the thermal, static, and creep performance of pressure-sensitive adhesives (PSAs) used in bonding heatsinks to microchips, focusing on the impact of adhesive coverage on thermal conductivity, mechanical strength, and long-term deformation under sustained loads. Shear loading, specifically analyzed due to the prevalence of shear stresses in vertically oriented microelectronic assemblies, is critical for understanding the long-term reliability of these bonds. The thermal analysis revealed that perfectly bonded heatsinks enhanced heat dissipation, with only a minor reduction in thermal conductivity observed due to incomplete adhesive coverage. Static tests demonstrated that perfectly bonded samples exhibited better load-bearing capacity overall, although joints with defects showed higher calculated stress due to the reduced bonded area at failure, with a 21% reduction in load-bearing capacity at room temperature and a 3.5% reduction at high temperature for joints with adhesive loss. Creep tests showed that at room temperature, the time to failure decreased by approximately 150% for samples with adhesive defects, while at high temperature, the reduction was over 66%. The study found that creep life is more sensitive to defects at lower temperatures, where adhesive loss has a more pronounced impact on performance. A predictive surface model was developed to estimate time to failure based on creep stress and temperature. [ABSTRACT FROM AUTHOR]

Garnering much attention and public health concern, the opioid epidemic has generated severe health consequences across the United States. Of particular interest, opioid use during pregnancy has been criminalized by state-level and national policies to quell the rising rates of maternal addiction and neonatal abstinence syndrome. However, recent research, has found that punitive policies (PPs) may instead exacerbate addiction by disincentivizing treatment-seeking behavior in pregnant women. Using treatment facility admissions data from 2013–2020, this study applies difference-in-difference methodology to extend previous studies' exploration of the effects that PPs have on rates of pregnant admissions. Moreover, this study discerns the effect that PPs have on the prevalence of medication-assisted treatment for women of childbearing age. The impacts of PPs were modeled within a variety of policy landscapes, accounting for potential policy and resource interactions. With support from supplemental event study models, findings suggest that 1) PPs reduce the use of medication-assisted treatment in all policy landscapes and 2) when in isolation, PPs stifle rates of pregnant admissions. When active in states with more complex policy landscapes (i.e. not just in isolation), PPs were found to have more complicated effects on pregnant admissions, dynamics which merit future exploration. [ABSTRACT FROM AUTHOR]

This paper presents an improved entropy-based freight tour synthesis (FTS) using fuzzy logic (FL). One approach used in formulating FTS models is entropy maximization, which aims to obtain the most probable freight (trucks) tour flow distribution in a network based on traffic counts. These models consider fixed parameters and constraints. However, the variations in costs, traffic counts, and truck demands depending on human behavior, are not always captured in detail in such models. FL can include such variabilities in its modeling. The flexibility FL provides to the model allows to obtain solutions where some or all the constraints do not entirely satisfy—but are close to—their expected values. Moreover, the modeling approach used based on FL theory is the membership function, specifically the triangular membership function, which is defined by three points corresponding to the vertices. This optimization problem was transformed into a bi-objective problem when the optimization variables are the membership and the entropy. The performance of the proposed formulation was assessed in the Sioux Falls network. To solve the problem, the model was run in General Algebraic Modeling System (GAMS), applying the ε approach, where ε value (ε ∈ [0, 1] with steps of 0.01) represents the level of accomplishment that at least one of the constraints (but can be more) gets. The results show that the entropy value decreased as the accomplishment level increased, and this behavior indicates a Pareto frontier, which proves that the optimization problem is bi-objective. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is associated with a heightened risk of cardiovascular and renal complications. While glycemic control remains essential, newer therapeutic options, such as SGLT2 inhibitors, offer additional benefits beyond glucose reduction. This review delves into the mechanisms underlying the cardio-renal protective effects of SGLT2 inhibitors. By inducing relative hypoglycemia, these agents promote ketogenesis, optimize myocardial energy metabolism, and reduce lipotoxicity. Additionally, SGLT2 inhibitors exert renoprotective actions by enhancing renal perfusion, attenuating inflammation, and improving iron metabolism. These pleiotropic effects, including modulation of blood pressure, reduction of uric acid, and improved endothelial function, collectively contribute to the cardiovascular and renal benefits observed with SGLT2 inhibitor therapy. This review will provide clinicians with essential knowledge, understanding, and a clear recollection of this pharmacological group's mechanism of action. [ABSTRACT FROM AUTHOR]

Patients with chronic kidney disease (CKD) are at a high risk of cardiovascular (CV) complications. In these patients, sodium-glucose cotransporter-2 inhibitors (SGLT2i) have been shown to reduce CV events. Mineralocorticoid receptor antagonists (MRAs) exert similar benefits in diabetic CKD, though their effects in non-diabetic CKD remain unclear. This study aimed to evaluated whether the combination of Dapagliflozin (DAPA) and Eplerenone (EPLE) would have positive effects on cardiorenal functions in a non-diabetic CKD model. CKD was induced in rats via 5/6 nephrectomy, followed by treatment with DAPA (5 mg/kg/day PO), EPLE (100 mg/kg/day PO) or the combination for 3 months following CKD induction. Cardiorenal functions were assessed after the treatment period. All treated groups showed reduced kidney fibrosis though plasma creatinine and urea levels remained unchanged. Compared to untreated CKD, EPLE or DAPA/EPLE reduced left ventricle (LV) end-diastolic pressure and LV end-diastolic pressure volume relationship, whereas DAPA alone did not achieve significant reductions. Compared to untreated CKD, EPLE and DAPA/EPLE improved cardiac perfusion but DAPA alone did not. Cardiac fibrosis in CKD was blunted by either DAPA or EPLE alone, with the combination showing an additive effect. In conclusion, co-treatment with DAPA and EPLE enhances diastolic function, cardiac perfusion and reduces myocardial fibrosis in non-diabetic CKD rats. [ABSTRACT FROM AUTHOR]

The KRAS oncogene drives many common and highly fatal malignancies. These include pancreatic, lung, and colorectal cancer, where various activating KRAS mutations have made the development of KRAS inhibitors difficult. Here we identify the scaffold protein SH3 and multiple ankyrin repeat domain 3 (SHANK3) as a RAS interactor that binds active KRAS, including mutant forms, competes with RAF and limits oncogenic KRAS downstream signalling, maintaining mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) activity at an optimal level. SHANK3 depletion breaches this threshold, triggering MAPK/ERK signalling hyperactivation and MAPK/ERK-dependent cell death in KRAS-mutant cancers. Targeting this vulnerability through RNA interference or nanobody-mediated disruption of the SHANK3–KRAS interaction constrains tumour growth in vivo in female mice. Thus, inhibition of SHANK3–KRAS interaction represents an alternative strategy for selective killing of KRAS-mutant cancer cells through excessive signalling. The multidomain scaffold protein SH3 and multiple ankyrin repeat domain 3 (SHANK3) can bind GTP-bound Ras and Rap small GTPases. Here the authors show that, by binding active KRAS, SHANK3 maintains oncogenic KRAS/MAPK/ERK signaling at an optimal level while its depletion in KRAS-mutant cancer cell lines results in ERK signalling overdose and impaired cell proliferation. [ABSTRACT FROM AUTHOR]

Gerotors are a family of mechanical pumps used for cooling, lubrication and fuel transfer in aerospace, medicine, etc. Modern industry demands to shorten the development time of products. This means further integration between the different design stages. As in any hydraulic machinery, an important bottleneck in the design process is the simulation time to validate designs. This is due mainly to the fact that Computational Fluid Dynamics (CFD) remains the go-to tool to perform simulations of hydraulic phenomena. One way to reduce this bottleneck is to adopt approximate yet fast simulation routines to refine the design before entering a precise simulation stage. This manuscript presents an interactive design tool that estimates the efficiency response of gerotor pumps using fast simulation routines. The presented tool intends to shorten and accelerate the design cycles of Gerotor pumps by providing the engineer with an estimation of the effect of geometry changes in the pump's efficiencies in real time. The software tool integrates 2D and 3D design capabilities with real-time simulation response. The resulting efficiency estimations differ from the CFD models in maximum 8% in the case of volumetric efficiency. For mechanical efficiency the error ranges between around 20% and 45%, but the pump's internal forces is estimated within a 1% accuracy. Future work focuses on refining the accuracy of the efficiency estimations and further integration of the design tool with physical data. [ABSTRACT FROM AUTHOR]

The article focuses on a response to critiques regarding the authors' review of SGLT2 inhibitors, highlighting their broader benefits in the general population. Topics include the acknowledgment of personalized medicine, the importance of tailoring treatment, the ongoing research on SGLT2 inhibitors, and the recognition of their efficacy in various patient populations.

Apparent resistant hypertension (aTRH) is a significant public health issue. Once low adherence to antihypertensive treatment has been ruled out and true resistant hypertension is diagnosed, aldosterone-direct-renin-ratio (ADRR) aids in the screening of an aldosterone-producing adenoma (APA) and primary aldosteronism (PA). Once PA and other secondary causes have been ruled out, the values of aldosterone and renin allow patients to be classified into phenotypes such as low renin hypertension (LRH), Liddle's-like (LLph), and primary hyperaldosteronism (PAph). These classifications could aid in the treatment decision-making process. However, optimal cut-off points for these classifications remain uncertain. This study aims to assess the prevalence of these phenotypes and the behavior of different cut-offs of the ADRR in an Afro-Colombian population with apparent resistant hypertension, as well to describe their sodium consumption. Afro-descendant individuals 18 years of age or older, diagnosed with resistant hypertension and attending to a primary care center in Colombia were recruited as volunteers. As part of the study, their plasma renin concentration (PRC) and plasma aldosterone concentration (PAC) were measured. The phenotypes were categorized into three groups based on multiple cut-off points from different authors: low renin and low aldosterone phenotype (LLph), low renin and high aldosterone phenotype (PAph), and high renin and high aldosterone phenotype, referred to as the renal phenotype (Rph). The prevalence of ADRR values exceeding the cut-off and phenotypes were calculated. A linear regression model was derived to assess the effect of sodium consumption with PAC, PRC and ADRR. A total of 88 patients with aTRH were included. Adherence to at least 3 antihypertensive medications was 62.5%. The median age was 56 years (IQR 48–60), 44% were female, and 20% had diabetes. The study found that the prevalence of ADRR values exceeding the cut-off ranged from 4.5 to 23%, while low-renin hypertension (LRH) varied from 15 to 74%, Rph was found in approximately 30 to 34% of patients, PAph in 30 to 51%, and the LLph in 15 to 41%, respectively, depending on the specific cut-off value by different authors. Notably, sodium consumption was associated with lower aldosterone (β − 0.15, 95% CI [− 0.27, − 0.03]) and renin concentrations (β − 0.75, 95% CI [− 1.5, − 0.02]), but ADRR showed no significant association with sodium consumption. There were no significant differences in prevalences between the groups taking < 3 vs ≥ 3 antihypertensive medications. Altered aldosterone-direct-renin-ratio, low renin hypertension, Liddle's-like, and primary hyperaldosteronism are prevalent phenotypes in patients within Afro-Colombian patients with apparent treatment-Resistant hypertension. [ABSTRACT FROM AUTHOR]

The treatment of agroindustrial wastewater using microbial fuel cells (MFCs) is a technological strategy to harness its chemical energy while simultaneously purifying the water. This manuscript investigates the organic load effect as chemical oxygen demand (COD) on the production of electricity during the treatment of cassava wastewater by means of a dual-chamber microbial fuel cell in batch mode. Additionally, specific conditions were selected to evaluate the semi-continuous operational mode. The dynamics of microbial communities on the graphite anode were also investigated. The maximum power density delivered by the batch MFC (656.4 μW m - 2 ) was achieved at the highest evaluated organic load (6.8 g COD L - 1 ). Similarly, the largest COD removal efficiency (61.9%) was reached at the lowest organic load (1.17 g COD L - 1 ). Cyanide degradation percentages (50–70%) were achieved across treatments. The semi-continuous operation of the MFC for 2 months revealed that the voltage across the cell is dependent on the supply or suspension of the organic load feed. The electrode polarization resistance was observed to decreases over time, possibly due to the enrichment of the anode with electrogenic microbial communities. A metataxonomic analysis revealed a significant increase in bacteria from the phylum Firmicutes, primarily of the genus Enterococcus. [ABSTRACT FROM AUTHOR]

Foundation models are transforming artificial intelligence (AI) in healthcare by providing modular components adaptable for various downstream tasks, making AI development more scalable and cost-effective. Foundation models for structured electronic health records (EHR), trained on coded medical records from millions of patients, demonstrated benefits including increased performance with fewer training labels, and improved robustness to distribution shifts. However, questions remain on the feasibility of sharing these models across hospitals and their performance in local tasks. This multi-center study examined the adaptability of a publicly accessible structured EHR foundation model (FMSM), trained on 2.57 M patient records from Stanford Medicine. Experiments used EHR data from The Hospital for Sick Children (SickKids) and Medical Information Mart for Intensive Care (MIMIC-IV). We assessed both adaptability via continued pretraining on local data, and task adaptability compared to baselines of locally training models from scratch, including a local foundation model. Evaluations on 8 clinical prediction tasks showed that adapting the off-the-shelf FMSM matched the performance of gradient boosting machines (GBM) locally trained on all data while providing a 13% improvement in settings with few task-specific training labels. Continued pretraining on local data showed FMSM required fewer than 1% of training examples to match the fully trained GBM's performance, and was 60 to 90% more sample-efficient than training local foundation models from scratch. Our findings demonstrate that adapting EHR foundation models across hospitals provides improved prediction performance at less cost, underscoring the utility of base foundation models as modular components to streamline the development of healthcare AI. [ABSTRACT FROM AUTHOR]

Humans can solve image classification tasks by learning from a few images and reusing prior-knowledge. In Artificial Intelligence, deep-learning models have been implemented to simulate human learning and face problems with little data available, few-shot learning. Nevertheless, one crucial problem of deep-learning is the selection of architectures and initial parameters that accomplish the requirements for a specific task. Therefore, we propose a novel methodology based on the meta-learning paradigm, which reuses prior- and meta-knowledge to select the best architecture and its initial parameters to solve different few-shot image classification tasks, as humans do. Our methodology was designed to understand the knowledge flow of the meta-learning paradigm by dividing the learning into prior-models, meta-models, meta-unsupervised algorithm, and base-models. We considered 9 architectures of deep convolutional neural networks as prior-models. Also, we propose a meta-unsupervised algorithm inspired by the human-cognitive problem-solving process, which acquires knowledge by solving tasks to recommend initial parameters to solve other new tasks. Furthermore, we propose a New Task Distribution Scheme to better evaluate few-shot learning models and analyze the difficulty of the new tasks. We evaluated our meta-learning methodology by applying the NTDS to the Mini-ImageNet and Caltech-UCSD-Birds-200-2011 (CUB) datasets. The achieved Adjusted Mutual Information average scores are 0.955 (zero-shot) and 0.957 (five-shot) for Mini-ImageNet, and 0.822 (zero-shot) and 0.848 (five-shot) for CUB. Moreover, we demonstrated the applicability of our meta-learning methodology in a real-world scenario using a new copro-parasite dataset. The performances of our meta-learning methodology are competitive regarding the state-of-the-art unsupervised few-shot learning models. [ABSTRACT FROM AUTHOR]

Aim: Schizomids are one of the less-known arachnid groups in terms of their natural history and ecology. However, due to their remarkable short-range endemic distribution, they may be vulnerable to climate change and habitat loss. In Colombia, although the national IUCN red list of threatened invertebrates has categorized species of schizomids as vulnerable (VU), this assessment was based on expert criteria. Therefore, information about the ecology of schizomids is critical for a more accurate reassessment of their conservation status. In this study, we describe the habitat of two species of Surazomus in endangered Andean tropical forests of Colombia after a sampling effort of 15.12 m2 (n = 168 soil samples) and the collection of 6999 soil fauna individuals from the samples. We analyzed soil fauna communities associated with schizomids as well as different forest and environmental variables from permanent plots installed a decade ago in the Sabana de Bogotá region. Detailed information on climate, plant communities, and forest structure was obtained from these plots. Thus, we provide the first comprehensive habitat description of schizomids including both above- and belowground compartments. We found that each species lives in specific habitats with different soil fauna communities, suggesting a potential association between geographical fidelity and habitat conditions. This result could indicate that schizomids are highly sensitive to dramatic environmental changes, such as those experienced in the Andean region of Colombia. Implications for insect conservation: Our study is valuable for the future reassessment of the conservation status of schizomids in the country, particularly considering that the previous categorization was based on expert criteria. Since habitat conditions and soil fauna communities are species-specific, schizomids could be disproportionately vulnerable to climate change and human disturbances in the Colombian Andes. [ABSTRACT FROM AUTHOR]

Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2. Wastewater surveillance has the potential to be used for early detection of new SARS-CoV-2 lineages. Here, the authors present Crykey, a computational method for detecting cryptic SARS-CoV-2 mutations in wastewater that co-occur on the same sequencing read, potentially representing new lineages. [ABSTRACT FROM AUTHOR]

Many annelids can regenerate missing body parts or reproduce asexually, generating all cell types in adult stages. However, the putative adult stem cell populations involved in these processes, and the diversity of cell types generated by them, are still unknown. To address this, we recover 75,218 single cell transcriptomes of the highly regenerative and asexually-reproducing annelid Pristina leidyi. Our results uncover a rich cell type diversity including annelid specific types as well as novel types. Moreover, we characterise transcription factors and gene networks that are expressed specifically in these populations. Finally, we uncover a broadly abundant cluster of putative stem cells with a pluripotent signature. This population expresses well-known stem cell markers such as vasa, piwi and nanos homologues, but also shows heterogeneous expression of differentiated cell markers and their transcription factors. We find conserved expression of pluripotency regulators, including multiple chromatin remodelling and epigenetic factors, in piwi+ cells. Finally, lineage reconstruction analyses reveal computational differentiation trajectories from piwi+ cells to diverse adult types. Our data reveal the cell type diversity of adult annelids by single cell transcriptomics and suggest that a piwi+ cell population with a pluripotent stem cell signature is associated with adult cell type differentiation. The cellular atlas of Pristina leidyi reveals cell type diversity in adult annelids by single cell transcriptomics, discovering several novel cell types and suggesting a pluripotent stem cell signature associated with adult cell type differentiation [ABSTRACT FROM AUTHOR]

Which functional traits allow a bat species to survive habitat disturbance? Empirical evidence regarding this question remains limited for many tropical regions despite their importance for conservation. Here, we used body mass, wing morphology, trophic level, and diet to identify which traits make phyllostomid bat species more vulnerable to human impacts in the Colombian Orinoco Llanos. Bats were sampled using mist nets in riparian forests, unflooded forests, flooded savannahs, and conventional rice crops on traditional farmlands with high-intensity agriculture and in private reserves with greater ecosystem protection. We tested the associations between species traits and landscape-structure variables (habitat cover and type, number of habitat patches, shortest distance to water) using RLQ and fourth-corner analyses, accounting for both spatial and phylogenetic autocorrelation. Trophic level and diet were the most important traits linked to disturbance sensitivity. Our results indicated that rice crop cover, savannah patches, and altered unflooded forest act as a filter, benefiting disturbance-adapted frugivorous genera in farmlands (e.g., Artibeus spp., Carollia spp., Platyrrhinus spp., Uroderma spp.). Conversely, animalivorous species were strongly associated with savannah cover and riparian forests within reserves (e.g., Lampronycteris brachyotis, Lophostoma brasiliense, Micronycteris minuta, Trachops cirrhosus). Encouraging the creation of more wildlife-friendly landscapes through payments for ecosystem services across the Colombian Llanos will ensure the long-term persistence of disturbance-sensitive species and sustain a complete set of ecological functions and ecosystem services that these bats provide. [ABSTRACT FROM AUTHOR]

The Global South has suffered an accelerated population and urban growth. This has created multiple impacts at the regional level such as erosion, soil degradation and biodiversity loss, as well as temperature increase in the cities causing urban heat islands. Bogotá, the capital of Colombia, is one of the largest cities in the Global South and in the last five decades has undergone a rapid urban transition, impacting surrounding ecosystems. However, little is known about how urbanization affects the local flora. To understand how plants are responding and adapting to urbanization processes in the city of Bogotá, we used a land cover gradient of urban, peri-urban and rural areas, and four plant functional traits (leaf area [LA], specific leaf area [SLA], leaf dry matter content [LDMC] and wood density [WD]). We analyzed 16 species shared in at least two land covers. Although urban and peri-urban areas had higher temperatures and higher LDMC and lower SLA values than rural areas, there were no significant differences in functional traits between land covers. Some species showed significant changes between land covers, indicating that there is a species-specific response to urbanization. Considering the need for urban areas to prioritize species that promote cooling and exhibit resistance to stress, as well as the capacity to adapt to climate change, it is essential to include plants possessing different combinations of functional traits. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this work was to demonstrate that clinical OAT1-mediated DDIs can be predicted using physiologically based pharmacokinetic (PBPK) modeling. Methods: LY404039 is a metabotropic glutamate receptor 2/3 agonist and the active moiety of the prodrug pomaglumetad methionil (LY2140023). After oral administration, pomaglumetad methionil is rapidly taken up by enterocytes via PEPT1 and once absorbed, converted to LY404039 via membrane dehydropeptidase 1 (DPEP1). LY404039 is renally excreted by both glomerular filtration and active secretion and in vitro studies showed that the active secretion of LY404039 was mediated by the organic anion transporter 1 (OAT1). Both clinical and in vitro data were used to build a PBPK model to predict OAT1-mediated DDIs. Results: In vitro inhibitory potencies (IC50) of the known OAT inhibitors, probenecid and ibuprofen, were determined to be 4.00 and 2.63 µM, respectively. Subsequently, clinical drug-drug interaction (DDI) study showed probenecid reduced the renal clearance of LY404039 by 30 to 40%. The PBPK bottom-up model, predicted a renal clearance that was approximately 20% lower than the observed one. The middle-out model, using an OAT1 relative activity factor (RAF) of 3, accurately reproduced the renal clearance of LY404039 and pharmacokinetic (PK) changes of LY404039 in the presence of probenecid. Conclusions: OAT1- mediated DDIs can be predicted using in vitro measured IC50 and PBPK modeling. The effect of ibuprofen was predicted to be minimal (AUC ratio of 1.15) and not clinically relevant. [ABSTRACT FROM AUTHOR]

The implementation of brain-computer interfaces (BCI) for real-time has become a paramount technology. Implementation of real-time BCI systems requires of methodologies that achieve high performance on classification over general brain signals of different subjects. Therefore, this work presents two simple and efficient methodologies to classify two and four motor imageries. The methodology to classify two motor imageries (MC-TM) includes an analysis of feature extraction methods based on spatial patterns and time–frequency transforms; and a convolutional neural network that preserves the information of the magnitude in the frequency bands of the sensorimotor rhythms (CNN-PIM). Besides, the methodology to classify four motor imageries (MC-FM) includes a modular classification scheme that instances 6 CNN-PIM; a new algorithm that uses the output of the softmax of each CNN-PIM to enhance the performance of the MC-FM methodology; an electroencephalogram sampling protocol that includes a specific procedure for 4 MIs classes; and a new dataset with the brain signals of 15 subjects. The MC-TM methodology achieved an accuracy of 94.44 ± 02.18% evaluated in BCI Competition IV dataset 2a (BCI-IV-2a), and accuracy of 97.67 ± 02.06% when evaluated in the EEGdataset. Meanwhile, the MC-FM achieved accuracies of 91.37 ± 3.29% and 86.48 ± 4.74% when evaluated in BCI-IV-2a and in the proposed dataset, respectively. These results situate our methodologies in a competitive position in comparison with the state-of-the-art methods. Moreover, the approximate processing time that the MC-FM methodology takes to classify EEG signals is 270 ms. Thus, it is suitable to be implemented in a real-time BCI system. [ABSTRACT FROM AUTHOR]

Professor David E. Smith, a renowned scientist and mentor in Pharmaceutical Sciences, is honored in this article for his significant contributions to the field. His research on loop diuretics, renal drug elimination, anticancer drugs, and proton-coupled oligopeptide transporters has had a lasting impact. Professor Smith's academic journey took him around the world, and he actively participated in professional organizations. Colleagues and students praise his expertise, dedication, and support, highlighting his passion for teaching and mentoring. Dr. Smith's retirement from the University of Michigan marks the end of a successful career that has left a legacy of excellence and inspiration. [Extracted from the article]

Convolutional Neural Networks (CNN) have become a common choice for industrial quality control, as well as other critical applications in the Industry 4.0. When these CNNs behave in ways unexpected to human users or developers, severe consequences can arise, such as economic losses or an increased risk to human life. Concept extraction techniques can be applied to increase the reliability and transparency of CNNs through generating global explanations for trained neural network models. The decisive features of image datasets in quality control often depend on the feature's scale; for example, the size of a hole or an edge. However, existing concept extraction methods do not correctly represent scale, which leads to problems interpreting these models as we show herein. To address this issue, we introduce the Scale-Preserving Automatic Concept Extraction (SPACE) algorithm, as a state-of-the-art alternative concept extraction technique for CNNs, focused on industrial applications. SPACE is specifically designed to overcome the aforementioned problems by avoiding scale changes throughout the concept extraction process. SPACE proposes an approach based on square slices of input images, which are selected and then tiled before being clustered into concepts. Our method provides explanations of the models' decision-making process in the form of human-understandable concepts. We evaluate SPACE on three image classification datasets in the context of industrial quality control. Through experimental results, we illustrate how SPACE outperforms other methods and provides actionable insights on the decision mechanisms of CNNs. Finally, code for the implementation of SPACE is provided. [ABSTRACT FROM AUTHOR]

In laser metal deposition of overhanging geometries, non-planar layers are used to partially avoid the highly inconvenient support structures. Multi-axis machines provide extra degrees of freedom that allow the deposition of non-planar layers. However, path planning for non-planar slicing is complex because, in most geometries, it encourages non-homogeneous metal deposition among the dispenser paths. For workpieces presenting a direction normal to which all cross sections have non-null common kernel (called here "revolute workpieces"), it is possible to use a cylindrical (i.e., iso-radial) slicing which still enables homogeneous path generation and metal deposition. This manuscript presents the implementation and experimental validation of a path-planner for laser deposition metal dispensers which build revolute workpieces by stacking iso-radial layers. Isometry is preserved between each 3D cylindrical layer and the 2D parametric space (κ , γ) where the dispenser path is planned, so deposed metal density can be homogenized. The path-planner takes advantage of the natural isometry between the (κ , γ) flat surface and the 3D cylinder (due to the cylinder developability). This isometry allows for (i) the application of conventional 2D dispenser path planning for 3D iso-radial layers and (ii) the control of inter-bead distance and dispenser velocity. The implemented path-planner also allows the control of the deposed thickness for each iso-radial layer. To validate experimentally our strategy, we manufacture spur and helical gear teeth on a cylindrical substrate. The results of these experiments show that our strategy generates toolpaths suitable for the manufacturing of industrial workpieces via laser metal deposition. [ABSTRACT FROM AUTHOR]

In this work we establish the nuclearity on Lebesgue spaces for a class of power series kernels in higher dimensions. This class includes important examples arising as Maclaurin series kernels as well as the Fox-Li and related operators. As a consequence we derive the rate of decay of the corresponding eigenvalues and trace formulae. [ABSTRACT FROM AUTHOR]

Introduction: Despite HLA-B27-associated uveitis is one of the most frequent etiologies of uveitis worldwide, there are scarce studies on the clinical spectrum of this disease and the implications of therapeutic strategies used in the Latin-American population, with none conducted in Colombia. Thus, this study aimed to describe the clinical characteristics of a cohort of patients with positive HLA-B27-associated uveitis in Colombia and evaluate the impact of systemic treatment on the recurrence rate. Methods: We retrospectively reviewed 490 clinical charts of patients with uveitis, searching for those with positive HLA-B27-associated uveitis over eight years in a referral center in Bogotá, Colombia. We used descriptive statistics to summarize demographic and clinical characteristics and conducted a Chi-square test, Fisher Exact test, Spearman correlation, and Mann–Whitney test to assess associations between treatment strategies and the recurrences rate. Results: We analyzed 39 patients (59% females) with positive HLA-B27-associated uveitis, with a median age at the first consultation of 44.5 years (Range: 2–80) and a mean follow-up time of 86.4 weeks (1.65 years). Most patients had unilateral uveitis (53.8%) and an anterior anatomical diagnosis (76.6%); two had anterior chamber fibrinous reaction, and only one had hypopyon. Most patients did not show associated systemic symptoms (66.7%). Topical corticosteroids, NSAIDs, methotrexate, mydriatics, and adalimumab were the most used treatments. The most common complications included cataracts, posterior synechiae, and macular edema. We identified that the rate of recurrences decreases over time (r = -0.6361, P = 0.002571), and this decrease seems to be associated with the initiation of disease-modifying antirheumatic drugs (DMARDs) in chronic and recurrent cases. Conclusion: The clinical spectrum of HLA-B27-associated uveitis in Colombian patients is distinct from other latitudes. Notably, we found a female predominance, older age at presentation, higher frequency of bilateral and vitreous involvement, and lower frequency of concomitant systemic diseases. Additionally, our results suggest that DMARDs such as methotrexate and biologic agents are good therapeutic options to avoid recurrences in chronic and recurrent cases. [ABSTRACT FROM AUTHOR]

Trypanosoma cruzi has a complex life cycle consisting of four morphological and distinct biological stages. Although some authors suggest that T. cruzi primarily follows clonal reproduction, recent genomic and transcriptomic studies indicate an unorthodox capacity for recombination. We aimed to estimate the differential gene expression of 10 meiosis/homologous recombination-related genes during the T. cruzi life cycle, including epimastigotes, under two different types of stress (oxidative stress and pH changes). We performed RT-qPCR tests using novel-designed primers to estimate the differential gene expression (∆Ct and ∆∆Ct) of nine genes (SPO11, HAP2, RAD50, MRN complex, BRCA2, DMC1, MND1, and RPA1) and RAD51, which was previously reported. Our results show basal expression of all genes during the life cycle, indicating their hypothetical role in several cellular processes but with specific signatures of differential gene expression during the life cycle (HAP2, RPA, RAD50, BRCA2, MND1, and DMC1) and oxidative stress (RPA, MRE11, NBS1, BRCA2, MND1, and RAD51). Additionally, we found that the MRN complex has an independent level of expression in T. cruzi, with profiles of MRE11 and NBS1 upregulated in some stages. Recent studies on other trypanosomatids have highlighted the influence of HAP2 and RPA in recombination and hybridization. If T. cruzi uses the same repertoire of genes, our findings could suggest that metacyclogenesis may be the putative step that the parasite uses to undergo recombination. Likewise, our study reveals the differential profiles of genes expressed in response to oxidative and pH stress. Further studies are necessary to confirm our findings and understand the recombination mechanism in T. cruzi. [ABSTRACT FROM AUTHOR]

Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 103 and 106 SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8–36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time. [ABSTRACT FROM AUTHOR]

We present a novel near-infrared spectroscopy technique based on Dual-Comb optical interrogation (DC-NIRS) applied to dispersive media. The technique recovers the frequency response of the medium under investigation by sampling its spectral response in amplitude and phase. The DC-NIRS reference and sample signals are generated using electro-optic modulation which offers a cost-effective, integrable solution while providing high adaptability to the interrogated medium. A careful choice of both line spacing and optical span of the frequency comb ensures that the retrieved information enables the reconstruction of the temporal impulse response of the medium, known as the diffuse-time-of-flight (DTOF), to obtain its optical properties with a 70 µs temporal resolution and 32 ps photon propagation delay resolution. Furthermore, the DC-NIRS technique also offers enhanced penetration due to noiseless optical amplification (interferometric detection). The presented technique was demonstrated on a static bio-mimetic phantom of known optical properties reproducing a typical brain's optical response. The DTOF and optical properties of the phantom were measured, showing the capabilities of this new technique on the estimation of absolute optical properties with a deviation under 3%. Compared to current technologies, our DC-NIRS technique provides enhanced temporal resolution, spatial location capabilities, and penetration depth, with an integrable and configurable cost-effective architecture, paving the way to next-generation, non-invasive and portable systems for functional brain imaging, and brain-computer interfaces, among other. The system is patent pending PCT/ES2022/070176. [ABSTRACT FROM AUTHOR]

Cancer alters the function of multiple organs beyond those targeted by metastasis1,2. Here we show that inflammation, fatty liver and dysregulated metabolism are hallmarks of systemically affected livers in mouse models and in patients with extrahepatic metastasis. We identified tumour-derived extracellular vesicles and particles (EVPs) as crucial mediators of cancer-induced hepatic reprogramming, which could be reversed by reducing tumour EVP secretion via depletion of Rab27a. All EVP subpopulations, exosomes and principally exomeres, could dysregulate hepatic function. The fatty acid cargo of tumour EVPs—particularly palmitic acid—induced secretion of tumour necrosis factor (TNF) by Kupffer cells, generating a pro-inflammatory microenvironment, suppressing fatty acid metabolism and oxidative phosphorylation, and promoting fatty liver formation. Notably, Kupffer cell ablation or TNF blockade markedly decreased tumour-induced fatty liver generation. Tumour implantation or pre-treatment with tumour EVPs diminished cytochrome P450 gene expression and attenuated drug metabolism in a TNF-dependent manner. We also observed fatty liver and decreased cytochrome P450 expression at diagnosis in tumour-free livers of patients with pancreatic cancer who later developed extrahepatic metastasis, highlighting the clinical relevance of our findings. Notably, tumour EVP education enhanced side effects of chemotherapy, including bone marrow suppression and cardiotoxicity, suggesting that metabolic reprogramming of the liver by tumour-derived EVPs may limit chemotherapy tolerance in patients with cancer. Our results reveal how tumour-derived EVPs dysregulate hepatic function and their targetable potential, alongside TNF inhibition, for preventing fatty liver formation and enhancing the efficacy of chemotherapy.Remote tumours cause liver dysfunction by releasing extracellular vesicles and particles containing palmitic acid, which induces TNF signalling in Kupffer cells, resulting in inflammation, fatty deposits and metabolic dysregulation, thus both reducing the efficacy and increasing the toxicity of chemotherapies. [ABSTRACT FROM AUTHOR]

In this work, the impact of good manufacturing practices (GMP) on the specific energy consumption (SEC) of plastic injection molding process, in 9 representative companies in Colombia, was studied. The GMP applied to the injection molding process and the degree to which they are adopted by the companies were defined. Afterwards, the SEC of 17 representative injection molding processes in those companies were evaluated. Finally, the impact of applying the GMP and their effect on SEC were studied. The degree of application of GMP on the analyzed companies ranges from 35 to 72%. A single SEC value could not be established for all the injection systems, because it depends on the injected weight and the productivity of each mold-machine-material combination. Nevertheless, a characteristic curve was defined for different systems. A relationship between the application of GMP and SEC was found. It was observed that all GMP contributed to improve the SEC, with different significance, ranging the relevance from 6 to 14%. Finally, it was concluded, taking in consideration a representative company, that “Plasticizing” and “Drive Units” were the most relevant categories to impact the SEC. [ABSTRACT FROM AUTHOR]

We consider the Feynman–Kitaev formalism applied to a spin chain described by the transverse-field Ising model. This formalism consists of building a Hamiltonian whose ground state encodes the time evolution of the spin chain at discrete time steps. To find this ground state, variational wave functions parameterised by artificial neural networks—also known as neural quantum states (NQSs)—are used. Our work focuses on assessing, in the context of the Feynman–Kitaev formalism, two properties of NQSs: expressivity (the possibility that variational parameters can be set to values such that the NQS is faithful to the true ground state of the system) and trainability (the process of reaching said values). We find that the considered NQSs are capable of accurately approximating the true ground state of the system, i.e. they are expressive enough ansätze. However, extensive hyperparameter tuning experiments show that, empirically, reaching the set of values for the variational parameters that correctly describe the ground state becomes ever more difficult as the number of time steps increase because the true ground state becomes more entangled, and the probability distribution starts to spread across the Hilbert space canonical basis. [ABSTRACT FROM AUTHOR]

Purpose: Gold mining has historically and significantly contributed to the Colombian economy. Gold extraction in Colombia is mainly done through two techniques: open-pit and alluvial mining. In this study, the environmental impacts of both these mining systems were analyzed using the life cycle assessment (LCA) framework, including identification of the system components that contribute most to impacts. Methods: Inventory data were obtained for two medium-scale mines in Colombia, one representing the open-pit method and the other the alluvial method. Environmental impacts were classified and characterized by mid-point impact categories and further aggregated into end-point indicators through the ReCiPe (v. 1.11) methodology, which uses a hierarchist perspective. Results: Results for end-point indicators show that the open-pit mining presents higher values in the human health damage category, influenced primarily by tailings and by the excavation process. For the alluvial mining, the overall impacts were an order of magnitude lower, with ecosystem quality as the most significant contributor due to the stripping of soil and vegetation. In the case of mid-point indicators, freshwater and marine ecotoxicity contribute the most to open-pit mining, while for alluvial mining, metal depletion and natural land transformation contribute the most. Climate change is also a significant impact category for alluvial and open-pit mining. Conclusions: The is a substantial difference in environmental impacts between the two mining systems: the quantified total environmental impact was 1.0 × 1004 points for the open-pit mine and 2.4 × 1003 points for the alluvial mine. Since these mines represent specific Colombian operational conditions, this conclusion cannot be confidently extended to other operational contexts. For example, results in other cases may depend on the local geological features and natural environment conditions. Knowing the critical mining supply chain stages for environmental performance will allow the decision-makers to provide the tools for more sustainable extraction and production. [ABSTRACT FROM AUTHOR]

Temporal distribution shift negatively impacts the performance of clinical prediction models over time. Pretraining foundation models using self-supervised learning on electronic health records (EHR) may be effective in acquiring informative global patterns that can improve the robustness of task-specific models. The objective was to evaluate the utility of EHR foundation models in improving the in-distribution (ID) and out-of-distribution (OOD) performance of clinical prediction models. Transformer- and gated recurrent unit-based foundation models were pretrained on EHR of up to 1.8 M patients (382 M coded events) collected within pre-determined year groups (e.g., 2009–2012) and were subsequently used to construct patient representations for patients admitted to inpatient units. These representations were used to train logistic regression models to predict hospital mortality, long length of stay, 30-day readmission, and ICU admission. We compared our EHR foundation models with baseline logistic regression models learned on count-based representations (count-LR) in ID and OOD year groups. Performance was measured using area-under-the-receiver-operating-characteristic curve (AUROC), area-under-the-precision-recall curve, and absolute calibration error. Both transformer and recurrent-based foundation models generally showed better ID and OOD discrimination relative to count-LR and often exhibited less decay in tasks where there is observable degradation of discrimination performance (average AUROC decay of 3% for transformer-based foundation model vs. 7% for count-LR after 5–9 years). In addition, the performance and robustness of transformer-based foundation models continued to improve as pretraining set size increased. These results suggest that pretraining EHR foundation models at scale is a useful approach for developing clinical prediction models that perform well in the presence of temporal distribution shift. [ABSTRACT FROM AUTHOR]

Background: Urinary incontinence (UI) is a common dysfunction of the pelvic floor, affecting 10–20% of all women, and up to 70% in the elderly general prevalence of 17% 20-year-old women and 38% in women over 60 years. It is estimated that only 25% of patients seek treatment for this debilitating condition. Aim: The aim of this study was to evaluate the efficacy of a device based on top flat magnetic stimulation to treat pelvic floor disorders especially female urinary incontinence. Methods: A total of 33 volunteer patients were divided into 5 groups according to the type of complaint. Subjects received 8 treatment sessions, with a frequency of twice a week with two different settings. Pelvic Floor Bother Questionnaire (PFBQ), Pelvic Organ Prolapse/Urinary Incontinence Sexual Function Questionnaire (PISQ-12) and Urinary Incontinence Short Form (ICIQ-UI-SF) were compiled by all patients at the beginning and after 3 months from the end of the last treatment (3MFU). Results: The patient's scores from validated Questionnaires significantly decreased (p < 0.01) from baseline up to 3MFU inside most of the groups. Conclusions: The noninvasiveness and safety of device make this approach an interesting tool as alternative approach for pelvic floor dysfunctions. [ABSTRACT FROM AUTHOR]

Background: The bocachico (Prochilodus magdalenae) is a migratory freshwater fish and one of the main species of Colombian continental fishery. Interest in it is due to the fish's excellent reproductive characteristics and sociocultural value in its native region. As part of native fish species repopulation programs carried out by the GIPEN research group of the San Silvestre fish farm and ISAGEN, the present study aimed to characterize the embryogenesis and early larval development of bocachico from zygote phase to the exogenous feeding period, using morphological and histological landmarks. Results: Embryos were obtained by fertilization from hormonally induced, wild-caught brood stock, and subsequent development was monitored at temperatures coinciding with native conditions. Embryonic development from fertilization to hatch lasted 13 h. This included the following stages: zygote, cleavage, blastula, gastrula, segmentation and organogenesis, pharyngula and hatching. Larvae emerged with unpigmented eyes; the cephalic area and the eye primordium were more developed at 1 day post-hatching. At 2–3 days post-hatching, the somites formed myotomes and pharyngeal arches were present as well as an undifferentiated digestive tract (endogenous feeding period). At 3–4 days post-hatching, the mouth was open, and the oral valve was developed; the mouth was continuous with the esophagus and the rest of the digestive system (beginning of the endo–exogenous feeding period). The yolk was observed for up to 9 days post-hatching (end of the endo–exogenous feeding period and beginning of the exogenous feeding period). Conclusion: To the best of our knowledge, this is the most comprehensive analysis made of the development of the bocachico to date, from early embryonic development to the larval phase, and this research will contribute to improving the knowledge of the developmental intervals of this species, the critical stages in feeding phases, as well as a more concrete approximation of when the fish is suitable for repopulation based on its morphological development. [ABSTRACT FROM AUTHOR]

To our knowledge, there is no available standardized educational curriculum designed to promote the incorporation of skin cancer examinations and procedures into general practice. To explore the contemporary training landscape, we conducted a systematic review of educational interventions designed to support skin cancer diagnostic examinations by primary care providers (PCPs). Our review uniquely encompasses all PCPs, including practicing physicians, residents, and advanced practice practitioners (APPs). The objective of this study is to review and synthesize worldwide data on educational interventions addressing PCP performance of skin cancer diagnostic examinations. A systematic review was performed in MEDLINE, Cochrane, EMBASE, and Scopus for English language articles worldwide published from 2000 onwards. Articles were screened for eligibility, and possibly overlapping datasets were resolved. Data extracted included curriculum content, delivery format, and educational outcomes. This review followed the PRISMA guidelines. A total of 63 studies were selected for data inclusion with one addressing training for resident physicians, 4 for APPs, and the remainder for practicing physicians. Educational interventions included in this review reflect the pre-SARS-CoV-2 pandemic educational environment: half provided live/synchronous instruction of about 5-h duration on average, and a quarter featured interactive components. Less than a quarter of interventions included practice change as a specific reported outcome. Without sustainable practice change, the anticipated long-term benefits of early cancer detection in patients remain limited. Previous and existing educational interventions designed to support skin cancer detection by PCPs demonstrate heterogeneous curriculum content, delivery methods, and educational outcomes. An ideal intervention would teach consensus-derived clinical competencies, provide meaningful learner feedback, and measure outcomes, such as knowledge/competency, confidence/attitudes, and practice change, using validated instruments. [ABSTRACT FROM AUTHOR]

Purpose: Lesbian, gay, and bisexual (LGB) individuals, and LB women specifically, have an increased risk for psychiatric morbidity, theorized to result from stigma-based discrimination. To date, no study has investigated the mental health disparities between LGB and heterosexual AQ1individuals in a large cross-national population-based comparison. The current study addresses this gap by examining differences between LGB and heterosexual participants in 13 cross-national surveys, and by exploring whether these disparities were associated with country-level LGBT acceptance. Since lower social support has been suggested as a mediator of sexual orientation-based differences in psychiatric morbidity, our secondary aim was to examine whether mental health disparities were partially explained by general social support from family and friends. Methods: Twelve-month prevalence of DSM-IV anxiety, mood, eating, disruptive behavior, and substance disorders was assessed with the WHO Composite International Diagnostic Interview in a general population sample across 13 countries as part of the World Mental Health Surveys. Participants were 46,889 adults (19,887 males; 807 LGB-identified). Results: Male and female LGB participants were more likely to report any 12-month disorder (OR 2.2, p < 0.001 and OR 2.7, p < 0.001, respectively) and most individual disorders than heterosexual participants. We found no evidence for an association between country-level LGBT acceptance and rates of psychiatric morbidity between LGB and heterosexualAQ2 participants. However, among LB women, the increased risk for mental disorders was partially explained by lower general openness with family, although most of the increased risk remained unexplained. Conclusion: These results provide cross-national evidence for an association between sexual minority status and psychiatric morbidity, and highlight that for women, but not men, this association was partially mediated by perceived openness with family. Future research into individual-level and cross-national sexual minority stressors is needed. [ABSTRACT FROM AUTHOR]

M30D is a new multifunctional compound against AD and joined to FDA-approved drugs exhibits neuroprotective properties; and in parallel, several derivatives of cinnamic acid, are reported to benefit the treatment of AD. Novel hybrids based on the known multipotent M30D and the cinnamoyl subunit were designed, synthetized, characterized, and tested as potential anti-Alzheimer agents. The synthesized conjugates were evaluated for their neuroprotector activity using the glutamate-mediated excitotoxicity assay in neurons and astrocytes in vitro, cytotoxicity LDH release, viability luminescent ATP assay and calcium imaging. Of those, 7d (3-methoxy-4-hydroxy substituted) and 7g (3,5-dimethoxy-4-hydroxy substituted) exhibit a valuable neuroprotective response by reducing injury effects caused after glutamate exposure and/or pre-treatment, with a maximum protection reached about 45.27 ± 2.03 (7d) and 40.01 ± 2.97% (7g) in comparison with memantine (37.27 ± 2.69%). Likewise, we chose 7d as hit compound, which in a glutamate excitotoxity co-culture model prevented astroglia reactivity and neuronal death, as well an 88% restoration of calcium levels and an increasing ATP level in both pre/post-treatments in 53.18 ± 4.07 and 66.99 ± 6.47%, respectively. Both, computational studies and experimental data suggest that a blockade of NMDA channel pore by 7d could explain its neuroprotective effect. Finally, hit-compound 7d exhibited an optimal in silico neuropharmacokinetic profile. A new scaffold was devised by combination of the cinnamoyl moiety and the prototype M30D with a valuable neuroprotector response that should be considered in future investigations oriented at developing new drugs for treating AD. [ABSTRACT FROM AUTHOR]

Purpose: Root inoculation of plants with beneficial microorganisms promotes plant growth and improves tolerance to biotic and abiotic stresses. In banana plants, microbial inoculation has shown promising effects on plant growth, but the effect on foliar diseases and on the resident native microbial community is yet unknown. We examined the effects of Bacillus subtilis EA-CB0575 introduced on roots of micropropagated banana plants on black Sigatoka disease and on the root microbiome. Methods: In vitro banana seedlings were root-inoculated with strain EA-CB0575, and then treated with the foliar pathogen Pseudocercospora fijiensis. Root bacterial communities were characterized using 16S rRNA gene sequencing, before and after pathogen inoculation; and the severity of the disease was determined. Results: Inoculation of strain EA-CB0575 on in vitro banana roots provided a reduction in the severity of black Sigatoka disease in greenhouse. This inoculation induced changes in the composition of the bacterial root microbiome, changes that arose from amplicon sequence variants (ASVs) of low abundances. Differential abundance analysis of ASV indicated that prior pathogen inoculation significantly more enriched sequences were identified in roots treated with EA-CB0575 (191-ASVs) compared to control plants (73-ASVs), but after pathogen inoculation more sequences were found in control (277-ASVs) than bacterial inoculated plants (60-ASVs). Furthermore, in vitro banana roots host a bacterial community that differ from that of greenhouse plants. Conclusion: Results suggest that banana plants inoculated with B. subtilis EA-CB0575, reshape the composition of the bacterial community in a P. fijiensis dependent manner and induce systemic resistance protecting plants against black Sigatoka. [ABSTRACT FROM AUTHOR]