Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Endoscopic Ultrasound in Early Chronic Pancreatitis

Chronic pancreatitis (CP) is an irreversible and progressive inflammation of the pancreas that can involve both pancreatic parenchyma and the pancreatic duct. CP results in morphological changes in the gland in the form of fibrosis and calcification along with functional impairment in the form of exocrine and endocrine insufficiency. Studies on the natural history of CP reveal the irreversibility of the condition and the resultant plethora of complications, of which pancreatic adenocarcinoma is the most dreaded one. In Japanese population-based studies by Otsuki and Fuzino et al., CP was clearly shown to reduce lifespan among males and females by 10.5 years and 16 years, respectively. This dismal prognosis is superadded to significant morbidity due to pain and poor quality of life, creating a significant burden on health and health-related infrastructure. These factors have led researchers to conceptualize early CP, which, theoretically, is a reversible stage in the disease spectrum characterised by ongoing pancreatic injury with the presence of clinical symptoms and the absence of classical imaging features of CP. Subsequently, the disease is thought to progress through a compensated stage, a transitional stage, and to culminate in a decompensated stage, with florid evidence of the functional impairment of the gland. In this focused review, we will discuss the definition and concept of early CP, the risk factors and natural history of the development of CP, and the role of various modalities of EUS in the timely diagnosis of early CP.
Innovative Electrospun Nanofiber Mats Based on Polylactic Acid Composited with Silver Nanoparticles for Medical Applications

Nanofibers are some of the most attractive materials that can modify functionalities for developing new kinds of specific applications and are mainly used as a biomedical material. Herein, we designed and prepared antibacterial nonwoven fiber mats of PLA and PLA composited with Ag nanoparticles by electrospinning. The effects of varying filler contents on their chemical, surface morphology, thermal, water absorbency, and antibacterial properties were investigated using FTIR, SEM/EDS, DSC, swelling ratio, and qualitative and quantitative antibacterial tests. FTIR and EDS spectra indicated that Ag nanoparticles were incorporated in the PLA without chemical bonding. SEM revealed that the average diameter of the PLA nanofibers containing the Ag nanoparticles was more significant than those without those particles. In addition, fiber diameters are proportional to the amount of Ag nanoparticle contents. DSC indicated that the Ag nanoparticles can be incorporated within the PLA matrix without strongly affecting their thermal properties. Moreover, the crystallinity of the composite nonwoven fiber mats was higher than those of fiber mats in the neat PLA. However, TGA revealed that the loaded Ag can improve the thermal stability of the PLA electrospun fiber mats. Accordingly, the antibacterial activities revealed that all the composite nanofiber mats exhibited excellent resistance against S. aureus and E. coli bacterial strains. In addition, in the cell toxicity study, all produced hybrids of nonwoven fiber mats induced a reduction in cell viability for the L929 fibroblast cells. Our results suggest that the designed and prepared nonwoven fiber mats may have good potential for use in the biomedical field, particularly in wound dressing applications.
Impact of Levosimendan and Its Metabolites on Platelet Activation Mechanisms in Patients during Antiplatelet Therapy—Pilot Study

Levosimendan is used for the short-term treatment of severe heart failure or other cardiac conditions. The area of existing clinical applications for levosimendan has increased significantly. This study aimed to assess whether levosimendan and its metabolites impact the mechanisms related to platelet activation. In this study, we included patients with coronary artery disease receiving antiplatelet therapy. We analyzed the pharmacodynamic profile using three independent methods to assess platelet activity. The results of the conducted studies indicate a mechanism of levosimendan that affects the function of platelets, causing higher inhibition of platelet receptors and, thus, their aggregation. It is essential to clarify whether levosimendan may affect platelets due to the need to maintain a balance between bleeding and thrombosis in patients treated with levosimendan. This is especially important in the case of perioperative bleeding. This study was conducted in vitro; the research should be continued and carried out in patients to check the complete pharmacokinetic and pharmacodynamic profile.
Therapeutic Drug Monitoring for Biologic and Small-Molecule Therapies for Inflammatory Bowel Disease

Background: Inflammatory bowel disease (IBD), encompassing ulcerative colitis and Crohn’s disease, necessitates long-term medical therapy to manage symptoms and prevent complications. Therapeutic drug monitoring (TDM) has emerged as a strategy to optimize treatment efficacy, particularly with anti-tumour necrosis factor (anti-TNF) alpha drugs. This review explores the role of TDM for non-anti-TNF advanced therapies in IBD, focusing on vedolizumab, ustekinumab, tofacitinib, upadacitinib, risankizumab and ozanimod. Methods: The literature search, conducted through OVID (Medline) and PubMed, delves into proactive versus reactive TDM, timing of monitoring and methods for measuring drug levels and anti-drug antibodies. Results: While ustekinumab and vedolizumab exhibit exposure–response relationships, consensus on target levels and the role of TDM adjustments remains elusive. Limited data on risankizumab suggest a dose-dependent response, while for small molecule therapies (janus kinase inhibitors and ozanimod), the absence of real-world data and commercially available TDM tools pose challenges. Conclusion: At present, with the available data, there is a limited role for TDM in non-anti-TNF biologic and small-molecule therapies. This review underscores the need for further research to delineate the utility of TDM in guiding treatment decisions for these agents.
T Cell Features in Glioblastoma May Guide Therapeutic Strategies to Overcome Microenvironment Immunosuppression

Simple Summary Glioblastoma is a lethal primary brain tumor, and so far, immunotherapeutic strategies have not significantly improved patients’ prognosis, both in newly diagnosed and recurrent settings. Understanding the features of the immune environment of the central nervous system is crucial to designing new treatment strategies able to counteract site-specific immunosuppressive and pro-tumorigenic factors. Here, we review next-generation immunomodulating therapeutic strategies such as immune check-point blockade, vaccinations, and adoptive cell therapies, aiming to re-shape the tumor microenvironment and restore active anti-tumor immunity. The door for immunotherapeutic strategies in glioblastoma treatment is not completely closed; researchers should test combinatorial treatments and design trials with solid translational analyses to gain more close and deep insight into on-treatment modifications of the tumor microenvironment. Abstract Glioblastoma (GBM) is the most aggressive and lethal primary brain tumor, bearing a survival estimate below 10% at five years, despite standard chemoradiation treatment. At recurrence, systemic treatment options are limited and the standard of care is not well defined, with inclusion in clinical trials being highly encouraged. So far, the use of immunotherapeutic strategies in GBM has not proved to significantly improve patients’ prognosis in the treatment of newly diagnosed GBM, nor in the recurrent setting. Probably this has to do with the unique immune environment of the central nervous system, which harbors several immunosuppressive/pro-tumorigenic factors, both soluble (e.g., TGF-β, IL-10, STAT3, prostaglandin E2, and VEGF) and cellular (e.g., Tregs, M2 phenotype TAMs, and MDSC). Here we review the immune composition of the GBMs microenvironment, specifically focusing on the phenotype and function of the T cell compartment. Moreover, we give hints on the therapeutic strategies, such as immune checkpoint blockade, vaccinations, and adoptive cell therapy, that, interacting with tumor-infiltrating lymphocytes, might both target in different ways the tumor microenvironment and potentiate the activity of standard therapies. The path to be followed in advancing clinical research on immunotherapy for GBM treatment relies on a twofold strategy: testing combinatorial treatments, aiming to restore active immune anti-tumor responses, tackling immunosuppression, and additionally, designing more phase 0 and window opportunity trials with solid translational analyses to gain deeper insight into the on-treatment shaping of the GBM microenvironment.
Perennial grass species richness and diversity on Argentine rangelands recovering from disturbance: (with 3 figures & 5 tables)

The influence of types of disturbance (hereon referred to as treatments) on natural vegetation was determined on richness and diversity of perennial grasses in semiarid rangelands of Argentina (40° 39'S, 62° 54'W). Studies were performed in adjacent areas which received different treatments: (1) untreated control; (2) burning; (3) herbicide application (shrub control); (4) Old Field 1 or (5) Old Field 2 (areas previously subjected to mechanical soil disturbance for 25 years; Old Field 1 had been exposed to a more severe grazing than Old Field 2 previous to cropping); and (6) overgrazing. During 1984-1992, annual aboveground biomass was determined per perennial grass species within each treatment after clipping permanent plots (n=30). Grass species richness and diversity were higher (p 0.05) perennial grass species richness and diversity. Changes in grass species diversity among years within each treatment were due to changes in both richness and relative biomasses of the studied species. The declining trends in grass species richness or diversity during 1984-1992 had equal slope in all treatments, indicating that the reduction rate of these variables over time was the same independent of disturbance type. Principal Coordinate Analysis showed that the similarity of species composition was greater among years within any treatment than among treatments in any given year. However, more than 69% of all perennial grass species were desirable perennial grasses in all treatments and years.
Air‐sea exchange of carbon dioxide in the Southern Ocean and Antarctic marginal ice zone

Direct carbon dioxide flux measurements using eddy covariance from an icebreaker in the high‐latitude Southern Ocean and Antarctic marginal ice zone are reported. Fluxes were combined with the measured water‐air carbon dioxide partial pressure difference (ΔpCO2) to compute the air‐sea gas transfer velocity (k, normalized to Schmidt number 660). The open water data showed a quadratic relationship between k (cm h−1) and the neutral 10 m wind speed (U10n, m s−1), kopen = 0.245 U10n2 + 1.3, in close agreement with decades old tracer‐based results and much lower than cubic relationships inferred from previous open ocean eddy covariance studies. In the marginal ice zone, the effective gas transfer velocity decreased in proportion to sea ice cover, in contrast with predictions of enhanced gas exchange in the presence of sea ice. The combined open water and marginal ice zone results affect the calculated magnitude and spatial distribution of Southern Ocean carbon flux.
Mediator Effects of Cognitive Load on Association between Self-Efficacy and Task Load in Intensive Care Unit Nurses

Aims. To explore the mediating effect of cognitive load on the relationship between self-efficacy and task load among intensive care unit (ICU) nurses. Background. Studies related to ICU nurses’ self-efficacy, cognitive load, and task load are noteworthy but limited. Methods. A total of 253 ICU nurses from three tertiary hospitals in Beijing were recruited and investigated by the Chinese version of the National Aeronautics and Space Administration-Task Load Index (NASA-TLX), General Self-Efficacy Scale (GSES), and an instrument for Measuring Different Types of Cognitive Load (MDT-CL) scales. SPSS 25.0 was used for Pearson correlation analysis and multiple linear regression analysis and mediation effect analysis using Model 4 in PROCESS (5,000 resamples). Results. Mediation analysis indicated that a partial mediating effect of extraneous cognitive load between self-efficacy and task load among ICU nurses was −0.707 (95% CI: −0.940, −0.504), accounting for 51.64% of the total effect. Conclusion. This study suggests that enhancing ICU nurses’ self-efficacy can be a potential strategy to decrease extraneous cognitive load and task load. Implications for Nursing Management. Nursing administrators should actively implement intervention strategies based on influencing the task load pathway of ICU nurses to ensure they can provide safe and high-quality nursing services.
Effect of nutrient blending with FYM on biomass production and economics under hybrid cotton-soybean intercropping system.

The field experiment was conducted during kharif season of 2004 and 2005 at the Instructional Farm, Indira Gandhi Agricultural University, Raipur (C.G.) to study the effect of nutrient blending with FYM and intercropping on biomass production and economics of hybrid cotton soybean intercrops under irrigated condition. The growth characters of cotton likeplant height, number of branches, number of leaves, dry matter accumulation, LAI, CGR, and RGR were the highest with sole cotton with 100% RDF. In case of soybean, the growth parameters like-plant height, number of branches, number of leaves, dry matter accumulation, LAI, CGR, and RGR were the highest under sole soybean with 100% RDF. The bolls per plant in cotton were the highest under sole cotton with 100% RDF. Similar trend for yield components were observed in case of soybean. Sole cotton with 100% RDF resulted in maximum seed cotton and stalk yield as compared to other intercropping treatments. Similar trend was also noted with sole soybean with 100% RDF, which recorded significantly the highest seed and stover yield as compared to others. The maximum values of LER, cotton equivalent yield, monetary advantage gross realization, net realization ha -1 and B: C ratio were recorded under C+S (2:4) + 100%RDF, which was closely followed by treatment C+S (2:4) + 1 t FYM ha -1 + 75% RDF (BL).
Interplay of Structural, Climatic, and Volcanic Controls On Late Quaternary Lacustrine–Deltaic Sedimentation Patterns In the Western Branch of the East African Rift System, Rukwa Rift Basin, Tanzania

Abstract This paper presents the first detailed, outcrop-based sedimentologic investigation of the Pleistocene–Holocene upper Lake Beds succession in the Rukwa Rift Basin, located in the Western Branch of the East African Rift System, southwestern Tanzania. The goal of this investigation is to examine the sedimentary facies and reconstruct the depositional environments of this important archive of Quaternary climate and environmental change. Eleven diagnostic facies associations comprising 24 facies were identified and provide the basis for recognition of three key deposystems: 1) alluvial-to-fluvial channel system; 2) lake delta system; and 3) profundal lacustrine system. Analysis of paleocurrent indicators and sandstone provenance indicate widely dispersed source regions and drainage patterns that were strongly influenced by major border-fault systems and episodic volcanism. Six stratigraphic sequences (A–F), ranging from ∼ 2 to 17 m thick, were identified based on stratal stacking patterns and the development of sequence-bounding unconformities and lacustrine flooding surfaces. Sedimentation processes, facies architecture, and stratigraphic packaging record a complex interplay between Quaternary climate fluctuations and intense episodic volcanism in the nearby Rungwe Volcanic Province, set against large-scale tectonic controls associated with synchronous development of the East African Rift System. Sequence stratigraphic analysis reveals that the Rukwa Rift Basin episodically shifted between a balanced-fill lake basin and an overfilled lake basin. Deep water, basin-wide lake expansion occurred at different times during the late Quaternary. The final depositional sequence preserved in the basin, a fluvial–underfilled lake basin, initiated ∼ 7.9 ka and has persisted to the present day. High-frequency climate change played the key role in sequence development in the upper Lake Beds. However, voluminous, rift-related volcanism and erosion of abundant labile volcanic materials from the Rungwe Volcanic Province, as well as syntectonic evolution of the rift, led to high sedimentation rates and transformation of flash floods and debris flows in the hinterlands (rift margin) to hyperpycnal flows towards the basin depocenter.
Olfactory Critical Periods: How Odor Exposure Shapes the Developing Brain in Mice and Flies

Simple Summary Critical periods have been extensively studied in the context of the visual system in mammals. Despite an immense interest in critical periods, much less is known about the cellular and molecular mechanisms involved in olfactory critical periods. This review provides an overview of the olfactory critical periods drawing from the literature on both mice and fruit flies. We draw parallels to cellular and molecular mechanisms identified in the visual system to guide our discussion on critical periods in the olfactory circuit. Abstract Neural networks have an extensive ability to change in response to environmental stimuli. This flexibility peaks during restricted windows of time early in life called critical periods. The ubiquitous occurrence of this form of plasticity across sensory modalities and phyla speaks to the importance of critical periods for proper neural development and function. Extensive investigation into visual critical periods has advanced our knowledge of the molecular events and key processes that underlie the impact of early-life experience on neuronal plasticity. However, despite the importance of olfaction for the overall survival of an organism, the cellular and molecular basis of olfactory critical periods have not garnered extensive study compared to visual critical periods. Recent work providing a comprehensive mapping of the highly organized olfactory neuropil and its development has in turn attracted a growing interest in how these circuits undergo plasticity during critical periods. Here, we perform a comparative review of olfactory critical periods in fruit flies and mice to provide novel insight into the importance of early odor exposure in shaping neural circuits and highlighting mechanisms found across sensory modalities.
Comparative Analysis of Machine Learning Algorithms for 5G Coverage Prediction: Identification of Dominant Feature Parameters and Prediction Accuracy

5G technology is a key factor in delivering faster and more reliable wireless connectivity. One crucial aspect in 5G network planning is coverage prediction, which enables network providers to optimize infrastructure deployment and deliver high-quality services to customers. This study conducts a comprehensive analysis of machine learning algorithms for 5G coverage prediction, focusing on dominant feature parameters and accuracy. Notably, the Random Forest algorithm demonstrates superior performance with an RMSE of 1.14 dB, MAE of 0.12, and R2 of 0.97. The CNN model, the standout among deep learning algorithms, achieves an RMSE of 0.289, MAE of 0.289, and R2 of 0.78, showcasing high accuracy in 5G coverage prediction. Random Forest models exhibit near-perfect metrics with 98.4% accuracy, precision, recall, and F1-score. Although CNN outperforms other deep learning models, it slightly trails Random Forest in performance. The research highlights that the final Random Forest and CNN models outperform other models and surpass those developed in previous studies. Notably, 2D Distance Tx Rx emerges as the most dominant feature parameter across all algorithms, significantly influencing 5G coverage prediction. The inclusion of horizontal and vertical distances further improves prediction results, surpassing previous studies. The study underscores the relevance of machine learning and deep learning algorithms in predicting 5G coverage and recommends their use in network development and optimization. In conclusion, while the Random Forest algorithm stands out as the optimal choice for 5G coverage prediction, deep learning algorithms, particularly CNN, offer viable alternatives, especially for spatial data derived from satellite images. These accurate predictions facilitate efficient resource allocation by network providers, ensuring high-quality services in the rapidly evolving landscape of 5G technology. A profound understanding of coverage prediction remains pivotal for successful network planning and reliable service provision in the 5G era.
DEMOGRAPHIC STRUCTURE AND SPATIALLYCONTIGUOUS AREAS IN TUSCANY

It is argued that the organization of services by local authorities should take into account both the demographic features of the usually resident population and the spatial dimension of the territory involved. Focusing on the Italian region of Tuscany, the paper seeks to identify homogeneous and spatially contiguous areas between the municipal and regional levels. Demographic indexes of usually resident population and spatial attributes of each Tuscan municipality are used as the input of a spatial clustering and regionalization model in order to obtain n areas that minimize the internal heterogeneity of the demographic structure under the constraint of spatial contiguity.