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Abstract A new system based on binary Deep Learning (DL) convolutional neural networks has been developed to recognize specific retinal abnormality signs on Optical Coherence Tomography (OCT) images useful for clinical practice. Images from the local hospital database were retrospectively selected from 2017 to 2022. Images were labeled by two retinal specialists and included central fovea cross-section OCTs. Nine models were developed using the Visual Geometry Group 16 architecture to distinguish healthy versus abnormal retinas and to identify eight different retinal abnormality signs. A total of 21,500 OCT images were screened, and 10,770 central fovea cross-section OCTs were included in the study. The system achieved high accuracy in identifying healthy retinas and specific pathological signs, ranging from 93 to 99%. Accurately detecting abnormal retinal signs from OCT images is crucial for patient care. This study aimed to identify specific signs related to retinal pathologies, aiding ophthalmologists in diagnosis. The high-accuracy system identified healthy retinas and pathological signs, making it a useful diagnostic aid. Labelled OCT images remain a challenge, but our approach reduces dataset creation time and shows DL models’ potential to improve ocular pathology diagnosis and clinical decision-making.

Decadal and multidecadal changes in the meridional overturning circulation may originate from either the subpolar North Atlantic or the Southern Hemisphere. New records of carbon and oxygen isotopes from an eastern Martinique Island (Lesser Antilles) coral reveal irregular, decadal, double-step events of low ∆14C and enhanced vertical mixing, high δ18O and high δ13C values starting in 1885. Comparison of the new and published ∆14C records indicates that the last event (1956-1969) coincides with a widespread, double-step ∆14C low of South Atlantic origin from 32°N to 18°S, associated with a major slowdown of the Caribbean Current transport between 1963 and 1969. This event and the past Martinique ∆14C lows are attributed to pulses of northward advection of low ∆14C Sub-Antarctic Mode Waters into the tropical Atlantic. They are coeval with changes of the tropical freshwater budget and likely driven by meridional overturning circulation changes since ~1880.

Data from the National Survey of Children's Health 2016-2019 was used to examine the co-occurrence of autism and ADHD and the impact on anxiety and depression among adolescents age 12-17. Rates of anxiety and depression were up to ten-fold the prevalence of adolescents not diagnosed with autism or ADHD. Over half of autistic females (57%) and nearly half of autistic males (49%) are also diagnosed with ADHD. Autistic females with ADHD had the highest co-occurrence of anxiety at 72% followed by autistic males with ADHD at 69%. The prevalence of depression was highest among autistic adolescents with ADHD yet was consistent across genders (male/female) at 38-39%. Adolescents diagnosed with autism and/or ADHD are at heightened risk for anxiety and depression.

Cardiac involvement strongly impacts prognosis in patients with Anderson–Fabry disease (AFD). All cardiac structures, such as the left ventricle and the left atrium, the aorta, the right sections, and the heart valves can be affected by morphological and functional abnormalities. Standard echocardiography has a crucial role in the characterization of AFD cardiomyopathy. Being a diffuse, non-invasive, easily reproducible, and inexpensive investigation, echocardiography represents the most appropriate tool for screening AFD cardiomyopathy. Furthermore, echocardiographic evaluation is the essential imaging method to support the physician also in the follow-up and risk stratification of AFD patients. Therefore, echocardiography is useful in all stages of the disease, both to reveal the first signs of cardiac involvement and to guarantee timely treatment in the preclinical stage and to estimate the extent of cardiac involvement, define possible complications, and evaluate the response to treatment in patients with established cardiomyopathy. The latest advanced echocardiographic techniques, such as speckle-tracking analysis, are offering new insights into the early detection of AFD cardiac involvement, thus suggesting a promising role for echocardiography in selecting appropriate candidates for treatment. In this review, we will examine the role of standard echocardiography in AFD, focusing on its use in screening for cardiac involvement, detailed characterization of AFD cardiomyopathy, and risk stratification of AFD patients.

IntroductionIn patients with Hereditary Angioedema (HAE) related to primary C1 inhibitor deficiency (C1INH), the defective clearance of immune complexes and apoptotic materials along with impairment of normal humoral response potentially leads to autoimmunity. Few studies report evidence on autoimmune diseases in C1INH-HAE, but no large population studies focus on rare connective tissue diseases (RCTDs). We aim at evaluating for the first time prevalence and distribution of RCTDs - Systemic Lupus Erytematosus (SLE), primary Sjogren Syndrome (SjS), primary antiphospholipid syndrome (APS), Systemic Sclerosis (SSc), and mixed connective tissue diseases (MCTD) in a large Italian cohort of C1INH-HAE patients.MethodsA multicenter observational study includes C1INH-HAE patients from ITACA Centers throughout Italy (time frame Sept 2023-March 2024). Inclusion criteria are i. a defined diagnosis of type I or type II C1INH-HAE; ii. age ≥15 years (puberty already occurred); iii. enrollment in the ITACA Registry. The diagnosis of SLE, primary SjS, primary APS, SSc, and MCTD are made in accordance with international classification criteria.ResultsData are collected from a total of 855 C1INH-HAE patients referring to 15 ITACA Centers. Patients with concomitant RCTDs were 18/855 (2.1%) with F:M ratio 3.5 and a prevalent type I C1INH-HAE diagnosis (87.2%). A diagnosis of SLE results in 44.5% of cases (n=8) while the remaining diagnoses are primary SjS (22.2%, n=4), primary APS (16.6%, n=3), SSc (11.2%, n=2), and a single case of MCTD (5.5%). The female gender is prevalent in all the RCTDs. Patients on long term prophylaxis (LTP) are significantly prevalent in RCTDs group than in the whole C1INH-HAE population (p

Thymic epithelial tumors (TETs) are rare malignant neoplasms arising in the thymus gland. Nevertheless, TETs, including thymomas (TMs), thymic carcinomas (TCs), and thymic neuroendocrine neoplasms (TNENs), are the most common mediastinal malignancies overall. A multidisciplinary approach is required for the appropriate diagnostic and therapeutic management of TETs. To date, the main therapeutic strategies are largely depended on the stage of the tumor and they include surgery with or without neoadjuvant or adjuvant therapy, represented by platinum-based chemotherapy, radiotherapy or chemoradiotherapy. Immune checkpoint inhibitors (ICIs) are ongoing under evaluation in the advanced or metastatic diseases despite the challenges related to the very low tumor mutation burden (TMB) and the high incidence of immune-related adverse events in TETs. In this regard, predictive impact of tissue biomarkers expression such as programmed cell death ligand-1 (PD-L1), and other emerging biomarkers, as well as their optimal and shared interpretation are currently under evaluation in order to predict response rates to ICIs in TETs.

Abstract Dexamethasone (DEX) is a synthetic analogue of cortisol commonly used for the treatment of different pathological conditions, comprising cancer, ocular disorders, and COVID-19 infection. Its clinical use is hampered by the low solubility and severe side effects due to its systemic administration. The capability of peptide-based nanosystems, like hydrogels (HGs) and nanogels (NGs), to serve as vehicles for the passive targeting of active pharmaceutical ingredients and the selective internalization into leukemic cells has here been demonstrated. Peptide based HGs loaded with DEX were formulated via the “solvent-switch” method, using Fmoc-FF homopeptide as building block. Due to the tight interaction of the drug with the peptidic matrix, a significant stiffening of the gel (G′ = 67.9 kPa) was observed. The corresponding injectable NGs, obtained from the sub-micronization of the HG, in the presence of two stabilizing agents (SPAN®60 and TWEEN®60, 48/52 w/w), were found to be stable up to 90 days, with a mean diameter of 105 nm. NGs do not exhibit hemolytic effects on human serum, moreover they are selectively internalized by RS4;11 leukemic cells over healthy PBMCs, paving the way for the generation of new diagnostic strategies targeting onco-hematological diseases.

Abstract Large language models (LLMs) can potentially transform healthcare, particularly in providing the right information to the right provider at the right time in the hospital workflow. This study investigates the integration of LLMs into healthcare, specifically focusing on improving clinical decision support systems (CDSSs) through accurate interpretation of medical guidelines for chronic Hepatitis C Virus infection management. Utilizing OpenAI’s GPT-4 Turbo model, we developed a customized LLM framework that incorporates retrieval augmented generation (RAG) and prompt engineering. Our framework involved guideline conversion into the best-structured format that can be efficiently processed by LLMs to provide the most accurate output. An ablation study was conducted to evaluate the impact of different formatting and learning strategies on the LLM’s answer generation accuracy. The baseline GPT-4 Turbo model’s performance was compared against five experimental setups with increasing levels of complexity: inclusion of in-context guidelines, guideline reformatting, and implementation of few-shot learning. Our primary outcome was the qualitative assessment of accuracy based on expert review, while secondary outcomes included the quantitative measurement of similarity of LLM-generated responses to expert-provided answers using text-similarity scores. The results showed a significant improvement in accuracy from 43 to 99% (p

Abstract Metastasis arises from disseminated tumour cells (DTCs) that are characterized by intrinsic phenotypic plasticity and the capability of seeding to secondary organs. DTCs can remain latent for years before giving rise to symptomatic overt metastasis. In this context, DTCs fluctuate between a quiescent and proliferative state in response to systemic and microenvironmental signals including immune-mediated surveillance. Despite its relevance, how intrinsic mechanisms sustain DTCs plasticity has not been addressed. By interrogating the epigenetic state of metastatic cells, we find that tumour progression is coupled with the activation of oncogenic enhancers that are organized in variable interconnected chromatin domains. This spatial chromatin context leads to the activation of a robust transcriptional response upon repeated exposure to retinoic acid (RA). We show that this adaptive mechanism sustains the quiescence of DTCs through the activation of the master regulator SOX9. Finally, we determine that RA-stimulated transcriptional memory increases the fitness of metastatic cells by supporting the escape of quiescent DTCs from NK-mediated immune surveillance. Overall, these findings highlight the contribution of oncogenic enhancers in establishing transcriptional memories as an adaptive mechanism to reinforce cancer dormancy and immune escape, thus amenable for therapeutic intervention.

Inclusive sports have emerged as a potential tool for building social inclusion within diverse populations. The Special Olympics Unified Sports programs are an example of inclusion initiatives specific to students with intellectual disability and sports that can be reevaluated with new understandings of inclusion. This systematic mixed studies review aimed to capture athlete Unified Sports experiences and identify what athletes reported about their participation. The systematic review identified nine original studies conducted by six unrelated research groups. Results across the studies are synthesized and suggestions for future research are presented. Athletes in all nine studies reviewed reported positive experiences with Unified Sports leading to increased social inclusion and/or self-concepts.

Nowadays, the application of Life Cycle Assessment (LCA) methodologies to vehicles and automotive components like electric motors is a cutting-edge research field. The goal of this paper is to gain a better understanding of how electric motors affect the environment and to shed light on the effects of certain assumptions on the LCA results. The LCA methodology was used to assess a wide range of environmental impacts in a cradle-to-use perspective and compare several electric motors designed for passenger cars. First, a baseline motor was identified and assessed. Then, a comparative LCA was conducted based on a novel scenario analysis framework. This framework ensures consistency in location settings, vehicle parameter settings, and scenario considerations so that all the comparisons are conducted on a like-to-like basis. The study examined two alternative scenarios to investigate the effect of geographical boundaries and vehicle applications. The methodological choices, including the specific modelling of environmental impacts, scenario modelling, and dataset selection are transparent and based on existing scientific literature or industrial publicly available data sources. The findings of this study provide indications on the relative life-cycle performance of the different scenarios considered and good evidence on how intended application and geographical factors influence life-cycle performance of electric motors. Moreover, while the use phase resulted as the main driver of the emissions in climate change and use of fossil resources, the other environmental categories resulted in a more balanced contribution between manufacturing and use phases, highlighting the importance of eco-design choices.

Abstract Emerging 4D printing techniques have enabled the realization of smart materials whose shape or properties can change with time. Two important phenomena play important roles in the 4D printing of shape memory polymeric materials. First, the anisotropic deformation of the printed filaments due to residual stresses can be harnessed to create out-of-plane shape transformations. Second, the unavoidable formation of micro-defects during the printing processes often affects the programmability of the printed object. Here, we propose a design approach that harnesses these two effects occurring during fused deposition modeling to create tailor-made curved geometries from initially 2D flat disks. We first determined the size and distribution of the imperfections formed within printed structures by varying two printing parameters namely the printing speed and the number of printed materials. Spatially varying the printing speed and combining polylactic acid filaments with a softer material without shape memory properties allowed us to cover a variety of shapes from negative to positive values of the mean and Gaussian curvature. We propose an analytical model to calculate the magnitude of the maximum out-of-plane deformation from the anisotropic expansion factor of the constituting microstructures. Furthermore, we develop computational models to predict the complex shape-changing of thermally actuated 4D printed structures given the distribution of rationally introduced imperfections and we demonstrate the potential applications of such defect-based metamaterials in drug delivery systems.

Several next-generation cells are now being researched to overcome the performance and sustainability limitations of the current Li-ion cells. The aim of this article is to assess the environmental impacts of the following next-generation cells chosen for their potential to meet the performance and safety requirements for future electric vehicle applications: Silicon-Polyacrylonitrile (SiCPAN), Silicon NanoWires (SiNWs), All-Solid-State (ASS) and Lithium-Sulphur (Li-S). Because the selected cells are emerging technologies, solely produced at the laboratory scale, a novel cradle-to-gate Prospective Life Cycle Assessment (P-LCA) was performed to ensure a fair comparison with the current Li-ion cell. The life cycle inventories of the selected cells were built by scaling up all the laboratory scale processes and activity data to industrial scale. The methodology is compliant with the most used frameworks for conventional LCAs, namely ISO 14040:2006 and ISO 14044:2018, and state-of-the-art guidelines for P-LCAs. The results showed that the Li-S cell has lower impact with respect to the current Li-ion cell in four out of the six most relevant impact categories, among which use of mineral and metal resources. The SiNWs cell revealed the greatest impact in almost all the impact categories. Lastly, a what-if analysis conducted on the silver content revealed that the ASS cell produced without silver would be the least impactful cell among the next-generation cells considered in this study.

Neonatal hyperbilirubinemia (NH) is a common condition in newborns, with elevated bilirubin levels potentially causing neurological damage or death. Accurate and timely measurements of total serum bilirubin are essential to prevent these outcomes. Direct spectrophotometry, a reliable method for measuring bilirubin, is particularly useful in constrained settings due to its potential for portable low-cost instrumentation. However, this method is susceptible to interference from hemoglobin, often present due to hemolysis. Typically, this interference is reduced using complex optical filters, reagents, multiple wavelengths, or combinations thereof, which increase costs and complexity while reducing usability. This study presents a hemoglobin compensation algorithm applied to a simple, portable, two-wavelength (465 and 590 nm) reflectance photometer designed to receive 30 µL of plasma or whole blood samples and perform the measurement without any reagents. Testing across five bilirubin and hemoglobin levels (4.96 to 28 mg/dL and 0.06 to 0.99 g/dL, respectively) demonstrated that the algorithm effectively reduces hemoglobin interference and overestimation errors. The overall root mean square error was reduced from 4.86 to 1.45 mg/dL, while the measurement bias decreased from −4.46 to −0.10 mg/dL. This substantial reduction in overestimation errors supports future clinical trials with neonatal blood samples.

Curcumin (Cur), the primary curcuminoid found in Curcuma longa L., has garnered significant attention for its potential anti-inflammatory and antibacterial properties. However, its hydrophobic nature significantly limits its bioavailability. Additionally, adipose-derived stem cells (ADSCs) possess immunomodulatory properties, making them useful for treating inflammatory and autoimmune conditions. This study aims to verify the efficacy of poly(ε-caprolactone) nanocapsules (NCs) in improving Cur’s bioavailability, antibacterial, and immunomodulatory activities. The Cur-loaded nanocapsules (Cur-NCs) were characterized for their physicochemical properties (particle size, polydispersity index, Zeta potential, and encapsulation efficiency) and stability over time. A digestion test simulated the behavior of Cur-NCs in the gastrointestinal tract. Micellar phase analyses evaluated the Cur-NCs’ bioaccessibility. The antibacterial activity of free Cur, NCs, and Cur-NCs against various Gram-positive and Gram-negative strains was determined using the microdilution method. ADSC viability, treated with Cur-NCs and Cur-NCs in the presence or absence of lipopolysaccharide, was analyzed using the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide assay. Additionally, ADSC survival was assessed through the Muse apoptotic assay. The expression of both pro-inflammatory (interleukin-1β and tumor necrosis factor-α) and anti-inflammatory (IL-10 and transforming growth factor-β) cytokines on ADSCs was evaluated by real-time polymerase chain reaction. The results demonstrated high stability post-gastric digestion of Cur-NCs and elevated bioaccessibility of Cur post-intestinal digestion. Moreover, Cur-NCs exhibited antibacterial activity against Escherichia coli without affecting Lactobacillus growth. No significant changes in the viability and survival of ADSCs were observed under the experimental conditions. Finally, Cur-NCs modulated the expression of both pro- and anti-inflammatory cytokines in ADSCs exposed to inflammatory stimuli. Collectively, these findings highlight the potential of Cur-NCs to enhance Cur’s bioavailability and therapeutic efficacy, particularly in cell-based treatments for inflammatory diseases and intestinal dysbiosis.

Herpes zoster ophthalmicus results from the reactivation of the latent varicella zoster virus, affecting the first branch of the trigeminal nerve. In 20–70% of cases, Zoster Ophthalmicus can lead to ocular involvement, affecting various orbital structures. Orbital myositis is a rare but severe complication of herpes zoster ophthalmicus. We present a case of a 52-year-old man with no significant medical history who developed zoster-associated right ocular myositis and dacryocystitis. He was treated with intravenous acyclovir and oral steroids. A review of the literature identified 29 patients across 19 studies. The median age was 61 years, with a slight female predominance. In 55% of cases, the patients had no notable medical history. The most common presentation of myositis involved all oculomotor muscles. There were 22 cases who were treated with intravenous antiviral therapy and 19 received steroids. A full resolution of symptoms was achieved in 51.7% of patients. Zoster-related orbital myositis is a rare complication that should be considered even in immunocompetent individuals. It may occur either before or after the appearance of a vesicular rash. Magnetic resonance imaging is the preferred radiological exam for assessing orbital involvement. Intravenous antiviral therapy should be started within 72 h of symptom onset, and its combination with systemic corticosteroids appears to be an effective treatment for zoster-related ocular myositis.

Brain–computer interfaces (BCIs) are promising tools for motor neurorehabilitation. Achieving a balance between classification accuracy and system responsiveness is crucial for real-time applications. This study aimed to assess how the duration of time windows affects performance, specifically classification accuracy and the false positive rate, to optimize the temporal parameters of MI-BCI systems. We investigated the impact of time window duration on classification accuracy and false positive rate, employing Linear Discriminant Analysis (LDA), Multilayer Perceptron (MLP), and Support Vector Machine (SVM) on data acquired from six post-stroke patients and on the external BCI IVa dataset. EEG signals were recorded and processed using the Common Spatial Patterns (CSP) algorithm for feature extraction. Our results indicate that longer time windows generally enhance classification accuracy and reduce false positives across all classifiers, with LDA performing the best. However, to maintain the real-time responsiveness, crucial for practical applications, a balance must be struck. The results suggest an optimal time window of 1–2 s, offering a trade-off between classification performance and excessive delay to guarantee the system responsiveness. These findings underscore the importance of temporal optimization in MI-BCI systems to improve usability in real rehabilitation scenarios.