Background: In an era of dramatic technological progress, the consequent economic transformations, and an increasing need for an adaptable workforce, the importance of education has risen to the forefront of the social discourse. The concurrent increase in the awareness of issues pertaining to social justice and the debate over what this justice entails and how it ought to be effected, feed into the education policy more than ever before. From the nexus of the aforementioned considerations, concern about the so-called education gap has emerged, with worldwide efforts to close it. Methods: I analyze the premises behind such efforts and demonstrate that they are founded upon fundamentally flawed ideas. Results: I show that in a society in which education is delivered equitably, education gaps emerge naturally as a consequence of differentiation due to talents, the tendency for matched mate selection, and the heritability of intellectual traits. Conclusion: I issue a call for a redirection of efforts away from the ill-founded idea of closing the education gap to the understanding of the magnitude of its unfair contributions, as well as to those social aspects that can modulate it in accordance with what a society deems fair according to its values. Full article

Corynebacterium rouxii is one of the recently described species of the Corynebacterium diphtheriae complex. As this species can potentially infect different hosts and harbor the tox gene, producing diphtheria toxin, we present its first pangenomic analysis in this work. A total of fifteen genomes deposited in online databases were included. After confirming the taxonomic position of the isolates by genomic taxonomy, the genomes were submitted to genomic plasticity, gene synteny, and pangenome prediction analyses. In addition, virulence and antimicrobial resistance genes were investigated. Finally, epidemiological data were obtained through molecular typing, clustering, and phylogenetic analysis. Our data demonstrated genetic diversity within the species with low synteny. However, the gene content is extensively conserved, and the pangenome is composed of 2606 gene families, of which 1916 are in the core genome and 80 are related to unique genes. Prophages, insertion sequences, and genomic islands were found. A type I-E CRISPR-Cas system was also detected. Besides the tox gene, determinants involved in adhesion and iron acquisition and two putative antimicrobial resistance genes were predicted. These findings provide valuable insight about this species’ pathogenicity, evolution, and diversity. In the future, our data can contribute to different areas, including vaccinology and epidemiology. Full article

Endophytic fungus is crucial for maintaining plant health and defense mechanisms, acting as protective barriers against pathogens, and producing medicinally beneficial bioactive compounds. Genome sequencing and metagenomics have significantly enhanced the understanding of fungal diversity and metabolic capabilities, enabling the identification of new genes and substances. Traditional culture-dependent methods have been complemented by culture-independent techniques, offering a more comprehensive view of fungal diversity. Using both culture-dependent and culture-independent techniques, the present research investigation explored the diversity of endophytic fungi encountered in the foliage of Hardwickia binata. The study examined the topographical characteristics and nutritional content of soil samples collected from the locality of the selected plant sample, H. binata, to better comprehend the effects on the plant’s growth. The balanced nutrient constituted approximately a pH of 7.2, which suggested an alkaline nature and promoted plant development. The ratio of nitrogen, phosphorous, and potassium remained 3:1:1. A total of 25 fungal isolates, categorized into 17 morphotypes, were obtained using the culture-dependent approach; Curvularia and Nigrospora emerged as the most common genera. Furthermore, the prediction of the ITS2 secondary structure supports the identification of species, highlighting a wide variety of fungal species present in H. binata. The culture-independent approach generated 69,570 high-quality sequences, identifying 269 Operational Taxonomic Units (OTUs). The dominant Ascomycota phylum, along with various genera, indicated a rich fungal community associated with H. binata. This study advances the understanding of the endophytic fungus communities that are associated with H. binata and the nature of soil ecology. The findings emphasize the significance of holistic techniques in the study of microbial dynamics within plant systems as well as their implications for ecosystem management and plant health. Full article

Infective pleural effusions are mainly represented by parapneumonic effusions and empyema. These conditions are a spectrum of pleural diseases that are commonly encountered and carry significant mortality and morbidity rates reaching upwards of 50%. The causative etiology is usually an underlying bacterial pneumonia with the subsequent seeding of the infectious culprit and inflammatory agents to the pleural space leading to an inflammatory response and fibrin deposition. Radiographical evaluation through a CT scan or ultrasound yields high specificity and sensitivity, with features such as septations or pleural thickening indicating worse outcomes. Although microbiological yields from pleural studies are around 56% only, fluid analysis assists in both diagnosis and prognosis by evaluating pH, glucose, and other biomarkers such as lactate dehydrogenase. Management centers around antibiotic therapy for 2–6 weeks and the drainage of the infected pleural space when the effusion is complicated through tube thoracostomies or surgical intervention. Intrapleural enzymatic therapy, used to increase drainage, significantly decreases treatment failure rates, length of hospital stay, and surgical referrals but carries a risk of pleural hemorrhage. This comprehensive review article aims to define and delineate the progression of parapneumonic effusions and empyema as well as discuss pathophysiology, diagnostic, and treatment modalities with aims of broadening the generalist’s understanding of such complex disease by reviewing the most recent and relevant high-quality evidence. Full article

Introduction: Necrotizing fasciitis (NF) is a critical disease with high morbidity and mortality rates that poses significant challenges in diagnosis and treatment. Prognostic factors for the clinical course of NF remain unclear and are currently under research. This study aims to identify such factors in a large cohort of patients which represents a major comprehensive investigation of prognostic factors for NF. Methods: Retrospective analysis was conducted on necrotizing fasciitis cases from 2003 to 2023 at two German hospitals. Data included demographics, comorbidities, laboratory findings, infection site, causative microorganisms and outcomes. Statistical analysis involved t-tests, chi-square tests, and ROC analysis. Results: A total of 209 patients were included, with a mortality rate of 18%. Patients were categorized into survivors (n = 171) and non-survivors (n = 38). Non-survivors were significantly older (68.9 ± 13.9 years vs. 55.9 ± 14.3 years; p < 0.01) and exhibited a higher prevalence of peripheral vascular diseases, cancer, and heart, liver, or renal insufficiency. Laboratory findings and scoring results also varied significantly between the two groups. The ROC curve analysis identified age as a predictor of mortality, with an optimal cut-off value of 68.5 years (sensitivity: 60.5%, specificity: 81.9%). Higher age was associated with increased mortality risk. Conclusions: The patient’s age stands out as the primary predictive element for mortality in necrotizing fasciitis. Additionally, we advocate for employing the Laboratory and Anamnestic Risk Indicator for Necrotizing Fasciitis (LARINF—score), which holds substantial prognostic significance and is straightforward to calculate. Considering our findings, crafting a clinical algorithm or scoring mechanism to forecast mortality in NF would be a promising target for future research. Full article

Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). The current solutions for its management, such as oral rehydration salts (ORS), inhibitors of gut motility, antibiotics, and living probiotics, only partially counteract the mechanisms of the disease and do not provide a full coverage of the problem. The potential risks of the use of living probiotic strains, particularly in immunocompromised patients, can be eliminated with the use of tyndallized (heat-killed) postbiotic bacteria and yeast. ABB C22^® is a postbiotic combination of three tyndallized yeasts, namely Saccharomyces boulardii, Saccharomyces cerevisiae, and Kluyveromyces marxianus. To assess the action of the postbiotic combination on diarrhoea, immune and gut epithelial cell signalling assays, the gut barrier formation assay, and the rotavirus gene expression assay were performed. ABB C22^® showed a strong anti-inflammatory effect, an induction of the build-up of the gut epithelium, and a degree of protection against rotavirus infection. These experimental studies support the use of the postbiotic ABB C22^® as a solution for the management of diarrhoea and gastrointestinal conditions, alone or in combination with existing but incomplete treatments. Full article

This study presents an innovative lateral flow microfluidic paper-based analytical device (μPAD) designed for conducting quantitative paper-based enzyme-linked immunosorbent assays (p-ELISA), seamlessly executing conventional ELISA steps in a paper-based format. The p-ELISA device utilizes a passive fluidic circuit with functional elements such as a multi-bi-material cantilever (B-MaC) assembly, delay channels, and a buffer zone, all enclosed within housing for autonomous, sequential loading of critical reagents onto the detection zone. This novel approach not only demonstrates a rapid assay completion time of under 30 min, but also boasts reduced reagent requirements, minimal equipment needs, and broad applicability across clinical diagnostics and environmental surveillance. Through detailed descriptions of the design, materials, and fabrication methods for the multi-directional flow assay (MDFA), this manuscript highlights the device’s potential for complex biochemical analyses in a user-friendly and versatile format. Analytical performance evaluation, including a limit of detection (LOD) of 8.4 pM for Rabbit IgG, benchmarks the device’s efficacy compared to existing p-ELISA methodologies. This pioneering work lays the groundwork for future advancements in autonomous diagnostics, aiming to enhance global health outcomes through accessible and reliable testing solutions. Full article

The purpose of this mixed-method study was to (1) examine the effect of an adapted physical activity program, Fitness Access McGill (FAM), on leisure-time physical activity (LTPA), autonomous and controlled motivation, and the basic psychological needs of self-determination theory among university students/staff with a physical disability and/or chronic conditions, and (2) explore participants’ experiences after completing FAM. Nineteen participants completed validated questionnaires for all study outcomes pre- and post-FAM. Nine participants partook in a 30–60 min semi-structured interview conducted within three months of completing FAM. Quantitative data were analyzed using repeated measures effect size calculations. Qualitative data were analyzed using directed content analysis. Participants reported an increase in total LTPA (dRMpooled = 0.58), with the greatest positive change on strenuous intensity (dRMpooled = 0.81). Large effects were found for changes in autonomous motivation (dRMpooled = 0.52), autonomy (dRMpooled = 0.79), competence (dRMpooled = 0.79), and relatedness (dRMpooled = 0.89). Participants reported FAM being supportive towards their psychological needs, the development of a LTPA routine, and enhanced overall well-being. Future research can be built upon this study to develop a robust understanding as to how need-supportive, adapted LTPA programs could be implemented within community settings or out-patient rehabilitation to support exercise engagement, physical health and overall well-being among adults with disabilities. Full article

The hepatobiliary system is vital for the biotransformation and disposition of endogenous molecules. Any impairment in the normal functioning of the hepatobiliary system leads to a spectrum of hepatobiliary diseases (HBDs), such as liver cirrhosis, fatty liver, biliary dyskinesia, gallbladder cancer, etc. Especially in pregnancy, HBD may result in increased maternal and fetal morbidity and mortality. Maternal HBD is a burden to the fetus’s growth, complicates fetal development, and risks the mother’s life. In fetal programming, the maternal mechanism is significantly disturbed by multiple factors (especially diet) that influence the development of the fetus and increase the frequency of metabolic diseases later in life. Additionally, maternal under-nutrition or over-nutrition (especially in high-fat, high-carbohydrate, or protein-rich diets) lead to dysregulation in gut hormones (CCK, GLP-1, etc.), microbiota metabolite production (SCFA, LPS, TMA, etc.), neurotransmitters (POMC, NPY, etc.), and hepatobiliary signaling (insulin resistance, TNF-a, SREBPs, etc.), which significantly impact fetal programming. Recently, biotherapeutics have provided a new horizon for treating HBD during fetal programming to save the lives of the mother and fetus. This review focuses on how maternal impaired hepatobiliary metabolic signaling leads to disease transmission to the fetus mediated through the gut–brain axis. Full article

(1) Background: Although Physaloptera retusa is one of the most widespread species infecting reptiles in the Americas, numerous taxonomic problems and little genetic data are associated with it. To clarify the taxonomy of this species, we used an integrative approach. (2) Methods: Physaloptera retusa-infecting Erythrolamprus typhlus (snake) from the Pantanal wetlands, Brazil, was morphologically and genetically characterised (18S and 28S rDNA; COI mtDNA) and compared with conspecific sequences available in GenBank, from parasites of Tupinambis teguixin (lizard), using species delimitation methods. Type specimens of P. liophis were re-evaluated given its morphological similarities with P. retusa. (3) Results: The morphology of the present specimens was equal to that of P. retusa, in which the only difference from P. liophis was the relative position of the vulva. Species delimitation methods were more accurate for the COI dataset; all of them (except ABGD) indicated interspecificity among P. retusa sequences. However, a lack of morphological data or voucher material, associated with the deposited sequences, prevented more assertive conclusions. (4) Conclusions: The present results highlight the importance of a clear association between genetic data and morphology of the isolation source, or at least its adequate vouchering. Moreover, P. retusa may represent a species complex in cryptic speciation, since it is widespread and has low hosts specificity. Full article

In the process of collecting evidence of activities and events in network devices, there are problems with content and storage, and we aim to solve the problems faced by network devices in network forensics. In this paper, we propose a simple method for solving the problems with content and storage in acquiring communication logs on end hosts, implement a sniffing tool that captures raw packets with communication event control, compare it with existing tools, and conduct experiments and considerations. Through these experiments and considerations, we confirmed that the proposed communication log acquisition method can be implemented on the end host, and that the problem can be solved by using a tool that implements the proposed method. Also, we confirmed that it can be applied to real-world communication log collection scenarios, and that it can coexist with existing systems and tools that collect communication logs. Full article

(1) Background: MGMT (O-6-methylguanine-DNA methyltransferase) promoter methylation remains an important predictive biomarker in high-grade gliomas (HGGs). The influence of necrosis on the fidelity of MGMT promoter (MGMTp) hypermethylation testing is currently unknown. Therefore, our study aims to evaluate the effect of varying degrees of necrosis on MGMTp status, as determined by pyrosequencing, in a series of primary and recurrent HGGs; (2) Methods: Within each case, the most viable blocks (assigned as ‘true’ MGMTp status) and the most necrotic block were determined by histopathology review. MGMTp status was determined by pyrosequencing. Comparisons of MGMTp status were made between the most viable and most necrotic blocks. (3) Results: 163 samples from 64 patients with HGGs were analyzed. MGMTp status was maintained in 84.6% of primary and 78.3% of recurrent HGGs between the most viable and necrotic blocks. A threshold of ≥60% tumor cellularity was established at which MGMTp status was unaltered, irrespective of the degree of necrosis. (4) Conclusions: MGMTp methylation status, as determined by pyrosequencing, does not appear to be influenced by necrosis in the majority of cases at a cellularity of at least 60%. Further investigation into the role of intratumoral heterogeneity on MGMTp status will increase our understanding of this predictive marker. Full article

Background: Rare diseases, predominantly caused by genetic factors and often presenting neurological manifestations, are significantly underrepresented in research. This review addresses the urgent need for advanced research in rare neurological diseases (RNDs), which suffer from a data scarcity and diagnostic challenges. Bridging the gap in RND research is the integration of machine learning (ML) and omics technologies, offering potential insights into the genetic and molecular complexities of these conditions. Methods: We employed a structured search strategy, using a combination of machine learning and omics-related keywords, alongside the names and synonyms of 1840 RNDs as identified by Orphanet. Our inclusion criteria were limited to English language articles that utilized specific ML algorithms in the analysis of omics data related to RNDs. We excluded reviews and animal studies, focusing solely on studies with the clear application of ML in omics data to ensure the relevance and specificity of our research corpus. Results: The structured search revealed the growing use of machine learning algorithms for the discovery of biomarkers and diagnosis of rare neurological diseases (RNDs), with a primary focus on genomics and radiomics because genetic factors and imaging techniques play a crucial role in determining the severity of these diseases. With AI, we can improve diagnosis and mutation detection and develop personalized treatment plans. There are, however, several challenges, including small sample sizes, data heterogeneity, model interpretability, and the need for external validation studies. Conclusions: The sparse knowledge of valid biomarkers, disease pathogenesis, and treatments for rare diseases presents a significant challenge for RND research. The integration of omics and machine learning technologies, coupled with collaboration among stakeholders, is essential to develop personalized treatment plans and improve patient outcomes in this critical medical domain. Full article

The surveillance and treatment of parasites are important features of preventative healthcare plans in zoological institutes. The parasite control strategies employed in temperate regions often involve prophylactic anthelmintic treatments during seasons where the burden of gastrointestinal parasites in fecal testing is high. These strategies are, however, not applicable in the tropics, where temperatures remain high throughout the year, allowing continuous parasitic development. A risk-based parasite management strategy was adopted by a tropical zoological institute. For parasite surveillance, routine fecal direct smears and magnesium sulfate flotations were performed to determine parasitic prevalence. The frequency of fecal checks for the year was determined by the frequency at which clinically relevant parasitism (fecal tests that resulted in the animal being treated) was detected during routine fecal checks in the previous year. A yearly anthelmintic drug-class rotation schedule was also implemented. The total number of fecal tests performed per year and the number of animals with clinically significant parasitic disease decreased by 30.0% (637/2126) and 46.9% (207/451), respectively, over the four-year period of the study. Anthelmintic class rotation also improved the efficacy of fenbendazole in treating Strongyloides spp. infecting the group of orangutans. This parasite control strategy is a targeted approach to managing preventative healthcare, reducing the work required to perform routine surveillance tests whilst maintaining the health of the collection of animals. Full article

This study offers an in-depth analysis and optimization of a microgrid system powered by renewable sources, designed for the efficient production of hydrogen and dimethyl ether—key elements in the transition toward sustainable fuel alternatives. The system architecture incorporates solar photovoltaic modules, advanced battery storage solutions, and electrolytic hydrogen production units, with a targeted reduction in greenhouse gas emissions and the enhancement of overall energy efficiency. A rigorous economic analysis was conducted utilizing the HYSYS V12 software platform and encompassing capital and operational expenditures alongside profit projections to evaluate the system’s economic viability. Furthermore, thermal optimization was achieved through heat integration strategies, employing a cascade analysis methodology and optimization via the General Algebraic Modeling System (GAMS), yielding an 83% decrease in annual utility expenditures. Comparative analysis revealed that the energy requirement of the optimized system was over 50% lower than that of traditional fossil fuel-based reforming processes. A comprehensive assessment of CO₂ emissions demonstrated a significant reduction, with the integration of thermal management solutions facilitating a 99.24% decrease in emissions. The outcomes of this study provide critical insights into the engineering of sustainable, low-carbon energy systems, emphasizing the role of renewable energy technologies in advancing fuel science. Full article

The ability to overcome an opposition in team sports is reliant upon an understanding of the tactical behaviour of the opposing team members. Recent research is limited to a performance analysts’ own playing team members, as the required opposing team athletes’ geolocation (GPS) data are unavailable. However, in professional Australian rules Football (AF), animations of athlete GPS data from all teams are commercially available. The purpose of this technical study was to obtain the on-field location of AF athletes from animations of the 2019 Australian Football League season to enable the examination of the tactical behaviour of any team. The pre-trained object detection model YOLOv4 was fine-tuned to detect players, and a custom convolutional neural network was trained to track numbers in the animations. The object detection and the athlete tracking achieved an accuracy of 0.94 and 0.98, respectively. Subsequent scaling and translation coefficients were determined through solving an optimisation problem to transform the pixel coordinate positions of a tracked player number to field-relative Cartesian coordinates. The derived equations achieved an average Euclidean distance from the athletes’ raw GPS data of 2.63 m. The proposed athlete detection and tracking approach is a novel methodology to obtain the on-field positions of AF athletes in the absence of direct measures, which may be used for the analysis of opposition collective team behaviour and in the development of interactive play sketching AF tools. Full article

To solve the short working distance and small measurement range of an all-fibre interferometer, we proposed a Mach–Zehnder Fabry–Perot hybrid fibre-optic interferometry system based on sinusoidal phase modulation. In this paper, a low-finesse fibre interferometer with a larger linear operating range for displacement measurement is realised using a self-collimating probe and incorporating a Kalman filter-based phase demodulation algorithm. Through experimental comparisons, it is demonstrated that the interferometer proposed in this paper can effectively reduce the phase delay, compensate for the depth of modulation drift, and correct the error due to parasitic interference introduced by the optical path structure through the algorithm. A linear large measurement working range of 20 cm is realised. Full article

This paper presents a novel class of interior solutions for anisotropic stars under the imposition of a self-similar symmetry. This means proposing exact solutions to the Einstein field equations to describe charged matter distribution with radiation flow. The Einstein–Maxwell system by employing specific choices of mass function is formulated to describe the gravitational collapse of charged, anisotropic, spherically symmetric distributions using the Schwarzschild metric. Two ordinary differential equations governing the dynamics are derived by matching a straightforward solution of the symmetry equations to the charged exterior (Reissner–Nordström–Vaidya). Models with satisfactory physical behavior are constructed by extensively exploring self-similar solutions for a set of parameters and initial conditions. Finally, the paper presents the evolution of physical variables and the collapsing radius, demonstrating the inevitable collapse of the matter distribution. Full article

We consider a toy model for the study of monitored dynamics in many-body quantum systems. We study the stochastic Schrödinger equation resulting from continuous monitoring with a rate $\Gamma$ of a random Hermitian operator, drawn from the Gaussian unitary ensemble (GUE) at every time t. Due to invariance by unitary transformations, the dynamics of the eigenvalues ${\left\{{\lambda }_{\alpha }\right\}}_{\alpha =1}^n$ of the density matrix decouples from that of the eigenvectors, and is exactly described by stochastic equations that we derive. We consider two regimes: in the presence of an extra dephasing term, which can be generated by imperfect quantum measurements, the density matrix has a stationary distribution, and we show that in the limit of large size $n\to \infty$ it matches with the inverse-Marchenko–Pastur distribution. In the case of perfect measurements, instead, purification eventually occurs and we focus on finite-time dynamics. In this case, remarkably, we find an exact solution for the joint probability distribution of $\lambda$’s at each time t and for each size n. Two relevant regimes emerge: at short times $t\Gamma =O\left(1\right)$, the spectrum is in a Coulomb gas regime, with a well-defined continuous spectral distribution in the $n\to \infty$ limit. In that case, all moments of the density matrix become self-averaging and it is possible to exactly characterize the entanglement spectrum. In the limit of large times $t\Gamma =O\left(n\right)$, one enters instead a regime in which the eigenvalues are exponentially separated $\log ({\lambda }_{\alpha }/{\lambda }_{\beta })=O(\Gamma t/n)$, but fluctuations $\sim O\left(\sqrt{\Gamma t/n}\right)$ play an essential role. We are still able to characterize the asymptotic behaviors of the entanglement entropy in this regime. Full article

Texture, soil organic matter (SOM), and soil depth (SoD) are crucial properties in forest management because they can supply spatial information on forest site productivity and guide fertilizer applications. However, soil properties possess an inherent uncertainty that must be mapped to enhance decision making in management applications. Most digital soil mapping predictions primarily concentrate on the mean of the distribution, often neglecting the estimation of local uncertainty in soil properties. Additionally, there is a noticeable scarcity of practical soil examples to demonstrate the prediction uncertainty for the benefit of forest managers. In this study, following a digital soil mapping (DSM) approach, a Quantile Regression Forest (QRF) model was developed to generate high-resolution maps and their uncertainty regarding the texture, SoD, and SOM, which were expressed as standard deviation (Sd) values. The results showed that the SOM (R² = 0.61, RMSE = 2.03% and with an average Sd = 50%), SoD (R² = 0.74 and RMSE = 19.4 cm), clay (R² = 0.63, RMSE = 10.5% and average Sd = 29%), silt (R² = 0.59, RMSE = 6.26% and average Sd = 33%), and sand content (R² = 0.55, RMSE = 9.49% and average Sd = 35%) were accurately estimated for forest plantations in central south Chile. A practical demonstration of precision fertilizer application, utilizing the predictive distribution of SOM, effectively showcased how uncertainty in soil attributes can be leveraged to benefit forest managers. This approach holds potential for optimizing resource allocation and maximizing economic benefits. Full article

Background and Objectives: Low-flow vascular lesions are commonly encountered in the oral cavity and may require removal due to aesthetic concerns, repeated bleeding or a cluttering sensation. Laser devices represent an excellent aid due to their affinity with blood and to their biostimulating properties and have been substituting traditional excision in selected cases. Materials and Methods: In this study, 30 patients presenting with low-flow oral vascular lesions were included. The lesions were clinically evaluated as follows: lesion’s site, reason for treatment, lesion’s dimensions, confirmation of positive diascopy via compression with a glass slide and photograph. The lesions were treated with laser forced dehydration (LFD) and then followed-up after 3 weeks, 6 months and 1 year. The laser source was a K-Laser Blu Derma (Eltech, K-Laser S.r.l., Via Castagnole, 20/H, Treviso, Italy). In the case of incomplete healing, a further protocol was performed at the three-week follow-up, and a further follow-up was scheduled for three weeks after. The following aspects were evaluated at each appointment: pain, using a Numeric Rating Scale (NRS) from 0 to 10 (0 = no pain, 10 = worst pain ever); the need to take painkillers (day of intervention and during follow-up); bleeding (yes/no); scar formation. Results: Complete regression was obtained in all patients, with no side effects. Only one patient required a second LFD protocol. NRS was 0 for all patients for the whole duration of the follow-up. None of the patients took painkillers on the day of the intervention and during the follow-up. One patient declared slight bleeding the day of the intervention, which she easily managed at home. One patient showed a small non-retracting and non-painful scar at the three-week follow-up. No recurrences were found after six months and one year. Conclusions: LFD targets endogenous chromophores, minimizing damage to adjacent tissue and limiting side effects. LFD is effective and could be considered a conservative alternative to traditional excision in low-flow lesions. Full article

Introduction: Systemic Lupus Erythematosus (SLE) is an autoimmune disease associated with an increased risk of cardiovascular diseases (CVDs), leading to elevated mortality rates among patients. We aimed to evaluate the levels of cardio–ankle vascular index (CAVI), global longitudinal strain (GLS), ventricular–arterial coupling (VAC), and high-sensitivity cardiac troponin I (hsTnI) in SLE patients and to explore their relationship with clinical parameters. Methods: This cross-sectional study enrolled 82 SLE patients without evident cardiac or kidney impairment and 41 age- and sex-matched healthy controls. We comparatively evaluated CAVI, GLS, VAC, and hsTnI between SLE patients and controls, and we assessed their association among SLE patients with disease activity based on the SELENA–SLEDAI Activity Index. Multivariate regression analysis was performed to identify independent predictors of CAVI and hsTnI within the SLE cohort. Results: In comparison to healthy controls, SLE patients presented with significantly higher CAVI, GLS, and hsTnI levels, while VAC was significantly reduced (p < 0.001). Furthermore, SLE patients with active disease (SELENA–SLEDAI ≥ 4) exhibited higher levels of CAVI and troponin than those with inactive disease (p < 0.001). SLEDAI was an independent predictor of CAVI, while VAC and SLEDAI were independent determinants of hsTnI in the SLE cohort. Conclusions: SLE patients displayed abnormal levels of CAVI, VAC, GLS, and troponin compared to healthy individuals. Our findings implicate the potential of those CV novel CVD risk factors to refine screening and therapeutic strategies for this specific population. Full article