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Abstract Since its identification in the vitreous humour of the eye and laboratory biosynthesis, hyaluronic acid (HA) has been a vital component in several pharmaceutical, nutritional, medicinal, and cosmetic uses. However, little is known about its potential toxicological impacts on aquatic inhabitants. Herein, we investigated the hematological response of Clarias gariepinus to nominal doses of HA. To achieve this objective, 72 adult fish were randomly and evenly distributed into four groups: control, low-dose (0.5 mg/l HA), medium-dose (10 mg/l HA), and high-dose (100 mg/l HA) groups for two weeks each during both the exposure and recovery periods. The findings confirmed presence of anemia, neutrophilia, leucopoenia, lymphopenia, and eosinophilia at the end of exposure to HA. In addition, poikilocytosis and a variety of cytomorphological disturbances were observed. Dose-dependent histological alterations in spleen morphology were observed in the exposed groups. After HA removal from the aquarium for 2 weeks, the groups exposed to the two highest doses still exhibited a notable decline in red blood cell count, hemoglobin concentration, mean corpuscular hemoglobin concentration, and an increase in mean corpuscular volume. Additionally, there was a significant rise in neutrophils, eosinophils, cell alterations, and nuclear abnormalities percentages, along with a decrease in monocytes, coupled with a dose-dependent decrease in lymphocytes. Furthermore, only the highest dose of HA in the recovered groups continued to cause a significant increase in white blood cells. White blood cells remained lower, and the proportion of apoptotic RBCs remained higher in the high-dose group. The persistence of most of the haematological and histological disorders even after recovery period indicates a failure of physiological compensatory mechanisms to overcome the HA-associated problems or insufficient duration of recovery. Thus, these findings encourage the inclusion of this new hazardous agent in the biomonitoring program and provide a specific pattern of hematological profile in HA-challenged fish. Further experiments are highly warranted to explore other toxicological hazards of HA using dose/time window protocols.

AI holds the potential to transform healthcare, promising improvements in patient care. Yet, realizing this potential is hampered by over-reliance on limited datasets and a lack of transparency in validation processes. To overcome these obstacles, we advocate the creation of a detailed registry for AI algorithms. This registry would document the development, training, and validation of AI models, ensuring scientific integrity and transparency. Additionally, it would serve as a platform for peer review and ethical oversight. By bridging the gap between scientific validation and regulatory approval, such as by the FDA, we aim to enhance the integrity and trustworthiness of AI applications in healthcare.

Abstract Despite artificial intelligence (AI) technology progresses at unprecedented rate, our ability to translate these advancements into clinical value and adoption at the bedside remains comparatively limited. This paper reviews the current use of implementation outcomes in randomized controlled trials evaluating AI-based clinical decision support and found limited adoption. To advance trust and clinical adoption of AI, there is a need to bridge the gap between traditional quantitative metrics and implementation outcomes to better grasp the reasons behind the success or failure of AI systems and improve their translation into clinical value.

Human T-Lymphotropic Virus type-1 (HTLV-1) is a unique retrovirus associated with both leukemogenesis and a specific neuroinflammatory condition known as HTLV-1-Associated Myelopathy (HAM). Currently, most proposed HAM biomarkers require invasive CSF sampling, which is not suitable for large cohorts or repeated prospective screening. To identify non-invasive biomarkers for incident HAM in a large Brazilian cohort of PLwHTLV-1 (n=615 with 6,673 person-years of clinical follow-up), we selected all plasma samples available at the time of entry in the cohort (between 1997–2019), in which up to 43 cytokines/chemokines and immune mediators were measured. Thus, we selected 110 People Living with HTLV-1 (PLwHTLV-1), of which 68 were neurologically asymptomatic (AS) at baseline and 42 HAM patients. Nine incident HAM cases were identified among 68 AS during follow-up. Using multivariate logistic regression, we found that lower IL-10, IL-4 and female sex were independent predictors of clinical progression to definite HAM (AUROC 0.91), and outperformed previously suggested biomarkers age, sex and proviral load (AUROC 0.77). Moreover, baseline IL-10 significantly predicted proviral load dynamics at follow-up in all PLwHTLV-1. In an exploratory analysis, we identified additional plasma biomarkers which were able to discriminate iHAM from either AS (IL6Rα, IL-27) or HAM (IL-29/IFN-λ1, Osteopontin, and TNFR2). In conclusion, female sex and low anti-inflammatory IL-10 and IL-4 are independent risk factors for incident HAM in PLwHTLV-1,while proviral load is not, in agreement with IL-10 being upstream of proviral load dynamics. Additional candidate biomarkers IL-29/IL-6R/TNFR2 represent plausible therapeutic targets for future clinical trials in HAM patients.

BackgroundHTLV-1-Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is an incapacitating neuroinflammatory disorder for which no disease-modifying therapy is available, but corticosteroids provide some clinical benefit. Although HAM/TSP pathogenesis is not fully elucidated, older age, female sex and higher proviral load are established risk factors. We investigated systemic cytokines and a novel chronic inflammatory marker, GlycA, as possible biomarkers of immunopathogenesis and therapeutic response in HAM/TSP, and examined their interaction with established risk factors.Patients and methodsWe recruited 110 People living with HTLV-1 (PLHTLV-1, 67 asymptomatic individuals and 43 HAM/TSP patients) with a total of 946 person-years of clinical follow-up. Plasma cytokine levels (IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ, TNF) and GlycA were quantified by Cytometric Bead Array and 1NMR, respectively. Cytokine signaling and prednisolone response were validated in an independent cohort by nCounter digital transcriptomics. We used multivariable regression, machine learning algorithms and Bayesian network learning for biomarker identification.ResultsWe found that systemic IL-6 was positively correlated with both age (r = 0.50, p

Abstract The field of ecology has undergone a molecular revolution, with researchers increasingly relying on DNA‐based methods for organism detection. Unfortunately, these techniques often require expensive equipment, dedicated laboratory spaces and specialized training in molecular and computational techniques; limitations that may exclude field researchers, underfunded programmes and citizen scientists from contributing to cutting‐edge science. It is for these reasons that we have designed a simplified, inexpensive method for field‐based molecular organism detection—FINDeM (Field‐deployable Isothermal Nucleotide‐based Detection Method). In this approach, DNA is extracted using chemical cell lysis and a cellulose filter disc, followed by two body‐heat inducible reactions—recombinase polymerase amplification and a CRISPR‐Cas12a fluorescent reporter assay—to amplify and detect target DNA, respectively. Here, we introduce and validate FINDeM in detecting Batrachochytrium dendrobatidis, the causative agent of amphibian chytridiomycosis, and show that this approach can identify single‐digit DNA copies from epidermal swabs in under 1 h using low‐cost supplies and field‐friendly equipment. This research signifies a breakthrough in ecology, as we demonstrate a field‐deployable platform that requires only basic supplies (i.e. micropipettes, plastic consumables and a UV flashlight), inexpensive reagents (~$1.29 USD/sample) and emanated body heat for highly sensitive, DNA‐based organism detection. By presenting FINDeM in an ecological system with pressing, global biodiversity implications, we aim to not only highlight how CRISPR‐based applications promise to revolutionize organism detection but also how the continued development of such techniques will allow for additional, more diversely trained researchers to answer the most pressing questions in ecology.

Abstract The Gulf of California is known for its high productivity, diversity, and unique oceanography. Based on old and recent contributions, we estimate a richness of 160 copepod species in this province. This work seeks to identify latitudinal and seasonal patterns of the copepod composition, abundance, and diversity in the Gulf of California during 1985. Differences between four zones of the gulf (NGC, CGC, SGC, EGC) and between the cold and warm seasons were hypothesized, based on taxonomic and ecological data. Samples were collected during the CORTES cruises (1985), which also measured salinity, temperature, and dissolved oxygen at each station. We analyzed the latitudinal and seasonal variation of the copepod community with multivariate analyses (NMDS-PCA) and correlated these with the environmental data (CCA). Seventy-nine copepod species were identified, averaging 265,649 and 98,885 ind/10 m3 in the cold and warm seasons, respectively. Only 53 of these occurred in both seasons, indicating seasonal change in species composition. Composition and diversity varied latitudinally in the cold season (P < 0.05 in all comparisons but CGC vs. SGC), but not in the warm season (except NGC vs. the rest of the gulf). There was seasonal change in the composition and the abundance (P < 0.005 cold vs. warm season). Richness and diversity were negatively correlated with salinity (decreasing from the north of the gulf); the abundance and composition were mainly affected by the shift in temperature. These patterns also match the phytoplankton abundance and size structure in the gulf, probably the main factors affecting copepod distribution.

Background: Quercetin (QR) is one of the major constituents of the methanolic extract of the leaves of Psidium guajava (Guava leaves). Objectives: The work’s aim is to understand the Quercetin’s mechanism in improving insulin resistance, use the homeostasis model assessment for insulin resistance (HOMA-IR) to determine the influence of quercetin on glycemic control, Look at how quercetin affects diabetes-related lipid metabolism and lipid profile measures. Analyze the impact of QR on oxidative stress in diabetic rats and contrast its antidiabetic effects whether administered as a nutrient or supplement. Materials and methods: Sixty adult male Wister rats that were matched in age and had starting body weights between 150 and 200 g were used in this study. One normoglycemic control group and 3 diabetic control groups (15 rats per group) were used. The diabetic control rats received the vehicle orally as saline daily, the normoglycemic control group received quercetin orally in a dose of 50 mg/kg per day, and the diabetic rats received quercetin orally in a dose of 100 mg/kg per day. Results: After six weeks of therapy, the rats with diabetes receiving isolated quercetin at doses of 50 and 100 mg/kg had reduced blood glucose levels, and their triglyceride, low-density lipoprotein, and total cholesterol profiles all significantly improved. Also, there was significant decrease homeostatic model assessment for insulin resistance, serum transaminases, hepatic malondialdehyde, and HMG CoA expression in liver and a substantial rise in levels of insulin, hepatic GSH, and insulin receptor substrate (IRS2) expression & Phosphoinositide 3-kinases in liver as compared to those of control group, but non- significance changes in high-density lipoprotein, AKT expression in liver were observed. Conclusions: Quercetin could be considered as a potential hypoglycmeic medication with possible mechanisms controlling the hyperglycemic state and cholesterol, triglycerides and LDL levels.

Several studies suggest that HTLV-1 infection may be associated with a wider spectrum of neurological and clinical manifestations that do not meet diagnostic criteria for HAM. These conditions may later progress to HAM or constitute an intermediate clinical form: intermediate syndrome (IS), a mid-point between asymptomatic HTLV-1 carriers and those with full myelopathy. Thus, we determined the incidence of HAM cases in the HTLV-1-asymptomatic and IS patients, and the clinical/laboratory associated markers. A total of 204 HTLV-1-positive patients were included in this study, divided into two groups: Group 1, including 145 asymptomatic HTLV-1 subjects (ASY), and Group 2, including 59 patients with inflammatory clinical symptoms in more than three systems and a high proviral load (PVL). During a 60-month follow-up time, with the age ranging from 47 to 79 years, ten patients of the fifty-nine initially diagnosed as IS developed HAM (iHAM), and two patients of the initial 145 ASY developed HAM directly. Women were more prevalent in all groups. For the iHAM patients, the age ranged from 20 to 72 years, with a mean of 53 (±15 SD). Older age was associated with the development of HAM, higher PVL and IS; however, there was no any specific symptom or clinical sign, that was associated with risk for iHAM. In conclusion, IS cases could be an early phase of development of HAM. These findings show the presence of higher incidence probabilities in our cohort than previously reported.

Background: During the development of human T-cell lymphotropic virus (HTLV-1)-associated myelopathy (HAM), the inflammatory phenomenon is very prominent and is a major factor in the outcome of the disease. The use of corticosteroids can modify their natural history, and in this study, we evaluated the effectiveness of using daily low-dose prednisone. Methods: This was a cross-sectional study using data collected by physicians monitoring patients with HAM at the Institute of Infectious Diseases “Emilio Ribas”, the main referral center for patients with infectious diseases in São Paulo, Brazil. The objective was to determine if daily low-dose oral prednisone would be able to stabilize the progression of HAM. The outcome measure was a change in the Osame Motor Disability Score (OMDS). Results: Fifty-four patients used treatment with oral prednisone, 5 milligrams daily. Nine cases were excluded from the study because they did not have at least two rating scales within a minimum interval of one year, and six were excluded for being co-infected with HIV and/or HCV. Thirty-nine patients met this criterion and were included for analysis. The majority were women (71.8%), the mean age was 56.51 years old (SD ± 9.74), and the median time of use of prednisone was 16 months. Thirty-two patients (82.05%) maintained the same OMDS, 5/39 (12.82%) had clinical worsening, and 2/39 (5.13%) improved. Conclusions: There was a trend toward clinical stability with the use of oral corticosteroids. However, randomized controlled trials are necessary to evaluate the use in clinical practices in all stages of HAM.

Land use and land cover (LULC) mapping initiatives are essential to support decision making related to the implementation of different policies. There is a need for timely and accurate LULC maps. However, building them is challenging. LULC changes affect natural areas and local biodiversity. When they cause landscape fragmentation, the mapping and monitoring of changes are affected. Due to this situation, improving the efforts for LULC mapping and monitoring in fragmented biomes and ecosystems is crucial, and the adequate separability of classes is a key factor in this process. We believe that combining multidimensional Earth observation (EO) data cubes and spectral vegetation indices (VIs) derived from the red edge, near-infrared, and shortwave infrared bands provided by the Sentinel-2/MultiSpectral Instrument (S2/MSI) mission reduces uncertainties in area estimation, leading toward more automated mappings. Here, we present a low-cost semi-automated classification scheme created to identify croplands, pasturelands, natural grasslands, and shrublands from EO data cubes and the Surface Reflectance to Vegetation Indexes (sr2vgi) tool to automate spectral index calculation, with both produced in the scope of the Brazil Data Cube (BDC) project. We used this combination of data and tools to improve LULC mapping in the Brazilian Cerrado biome during the 2018–2019 crop season. The overall accuracy (OA) of our results is 88%, indicating the potential of the proposed approach to provide timely and accurate LULC mapping from the detection of different vegetation patterns in time series.

Arterial dysfunction is major risk factor for cardiovascular complications, and arterial stiffness is an independent risk factor in end-stage renal disease patients. As the distance from the heart increases, arterial stiffness (pulse wave velocity) becomes progressively more marked. This generates a centrifugal stiffness gradient, which leads to partial, continuous local wave reflections, which in turn attenuate the transmission of pulsatile pressure into the microcirculation, thus limiting the potentially deleterious outcomes both upstream (on the heart: left-ventricular hypertrophy and coronary perfusion) and downstream (on the renal and cerebral microcirculation: reduced glomerular filtration and impaired cognitive functions). The impact of arterial aging is greater on the aorta and central capacitive arteries, and it is characterized by a loss or reversal of the physiological stiffness gradient between central and peripheral arteries. Recently, however, in contrast to observations on the aorta, several studies have shown less pronounced, absent, or even negative associations between muscular peripheral arteries and age–stiffness relationships, which may be associated with a decrease in or reversal of the stiffness gradient. These findings point to a potential benefit of assessing the muscular peripheral arteries to predict the risk of cardiovascular disease and suggest that reversal of the stiffness gradient may be an independent risk factor for all-cause mortality.

Abstract Background HTLV-1-Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is an incapacitating neuroinflammatory disorder for which no disease-modifying therapy is available, but corticosteroids provide some clinical benefit. Although HAM/TSP pathogenesis is not fully elucidated, older age, female sex and higher proviral load are established risk factors. We investigated systemic cytokines and a novel chronic inflammatory marker, GlycA, as possible biomarkers of immunopathogenesis and therapeutic response in HAM/TSP, and examined their interaction with established risk factors. Patients and methods We recruited 110 People living with HTLV-1 (PLHTLV-1, 67 asymptomatic individuals and 43 HAM/TSP patients) with a total of 946 person-years of clinical follow-up. Plasma cytokine levels (IL-2, IL-4, IL-6, IL-10, IL-17A, IFN-γ, TNF) and GlycA were quantified by Cytometric Bead Array and 1NMR, respectively. Cytokine signaling and prednisolone response were validated in an independent cohort by nCounter digital transcriptomics. We used multivariable regression, machine learning algorithms and Bayesian network learning for biomarker identification. Results We found that systemic IL-6 was positively correlated with both age (r = 0.50, p

The interfacial Dzyaloshinskii-Moriya interaction (DMI) is of great interest as it can stabilize chiral spin structures in thin films. Experiments verifying the orientation of the interfacial DMI vector remain rare, in part due to the difficulty of separating vector components of DMI. In this study, Fe/Ni bilayers and Co/Ni multilayers were deposited epitaxially onto Cu(001) and Pt(111) substrates, respectively. By tailoring the effective anisotropy, spin reorientation transitions (SRTs) are employed to probe the orientation of the DMI vector by measuring the spin structure of domain walls on both sides of the SRTs. The interfacial DMI is found to be sufficiently strong to stabilize chiral Néel walls in the out-of-plane magnetized regimes, while achiral Néel walls are observed in the in-plane magnetized regimes. These findings experimentally confirm that the out-of-plane component of the DMI vector is insignificant in these fcc(001) and fcc(111) oriented interfaces, even in the presence of atomic steps.

Games practiced by Erotes and children are known mainly by a series of small paintings in the Casa dei Cervi of Herculanum. These scenes allow the reconstruction of the gestures, material, and the number of players involved in these games, thus completing the information taken from literary sources, often lacunary. Among the many painted games, the ephedrismos is particularly well represented in other domestic contexts in Pompeii, such as the Casa dei Vettii, the Casa dei Pittori al lavoro and the Casa del Bracciale d’oro. This paper shows the reception of this Greek game “par excellence” in pictorial art as well as in ludic Roman practices.

Abstract Background Timely identification of deteriorating COVID-19 patients is needed to guide changes in clinical management and admission to intensive care units (ICUs). There is significant concern that widely used Early warning scores (EWSs) underestimate illness severity in COVID-19 patients and therefore, we developed an early warning model specifically for COVID-19 patients. Methods We retrospectively collected electronic medical record data to extract predictors and used these to fit a random forest model. To simulate the situation in which the model would have been developed after the first and implemented during the second COVID-19 ‘wave’ in the Netherlands, we performed a temporal validation by splitting all included patients into groups admitted before and after August 1, 2020. Furthermore, we propose a method for dynamic model updating to retain model performance over time. We evaluated model discrimination and calibration, performed a decision curve analysis, and quantified the importance of predictors using SHapley Additive exPlanations values. Results We included 3514 COVID-19 patient admissions from six Dutch hospitals between February 2020 and May 2021, and included a total of 18 predictors for model fitting. The model showed a higher discriminative performance in terms of partial area under the receiver operating characteristic curve (0.82 [0.80–0.84]) compared to the National early warning score (0.72 [0.69–0.74]) and the Modified early warning score (0.67 [0.65–0.69]), a greater net benefit over a range of clinically relevant model thresholds, and relatively good calibration (intercept = 0.03 [− 0.09 to 0.14], slope = 0.79 [0.73–0.86]). Conclusions This study shows the potential benefit of moving from early warning models for the general inpatient population to models for specific patient groups. Further (independent) validation of the model is needed.