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Periferia sinistra della frase in vedico: topic e focus
No full textThis article addresses selected aspects of the information structure
of the Vedic clause, with particular emphasis on the left periphery and
its interaction with phenomena such as topicalization, focalization, and
left dislocation. The analysis is based on data drawn from both Vedic
prose and poetry, with special attention to the Atharvaveda and the
Ṛgveda. From a theoretical perspective, the study is situated within the
framework of Split-CP approaches and aims to assess the extent to
which the left periphery of the Vedic clause can be described as a
structurally articulated domain, rather than as a single discoursefunctional
position, as has sometimes been assumed. Specific attention
is devoted to the co-occurrence of topicalized constituents, often
associated with resumptive pronouns, and focalized elements, which
generally lack resumption and are sometimes marked by focus
particles. The behavior of complementizers in subordinate clauses is
also examined, in order to evaluate whether discursively salient
material may occur in the left periphery even in the presence of a Ctype
head, and whether complementizers themselves may occupy
different positions within the CP domain. Finally, the article considers
correlative constructions in Vedic, discussing their placement in the left
periphery and their relationship to the clause’s information structure
DEEP LEARNING ALGORITHM FOR MOLECULAR CLASSIFICATION OF ENDOMETRIAL CANCER FROM WHOLE SLIDE HISTOPATHOLOGY IMAGES
No full textEndometrial cancer (EC) is a common malignancy whose molecular classification (POLEmut, MMRd, p53-abn, NSMP) guides prognosis and treatment. While MMRd and p53-abn can be assessed through IHC, POLEmut identification requires gene sequencing, which is costly and often unavailable. In this study, we developed a fully supervised deep learning (DL) model to classify EC molecular subtypes directly from H&E-stained whole-slide images (WSIs). From an initial cohort of 1,362 cases, 230 FFPE WSIs were selected and annotated to train three sequential binary classifiers (POLEmut vs non-POLE, MMRd vs non-MMRd, p53-abn vs NSMP), forming a hierarchical, clinically aligned architecture. Prediction heatmaps were generated to enhance interpretability. The model showed excellent performance for POLEmut (AUROC 0.95; accuracy 87.5%; F1 0.86) and good performance for MMRd (AUROC 0.88; F1 0.81) and p53-abn (accuracy 74%; F1 0.70). Overall, it achieved an average precision of 76% and recall of 88%. These results demonstrate the feasibility of DL-based prediction of EC molecular subtypes from routine histology, offering a scalable approach to support diagnostic workflows and expand access to precision oncology where molecular assays are limited
Bridging the gap: addressing real-life challenges to the implementation of DTG/3TC in treatment-naive people living with HIV
No full textDolutegravir/lamivudine (DTG/3TC), used as a two-drug regimen (2DR), has demonstrated non-inferiority to traditional three-drug regimens (3DRs) in treatment-naive people with HIV (PWH), with sustained virological efficacy, favorable tolerability, and a good safety profile. However, its implementation in routine clinical practice raises several questions, particularly in populations underrepresented in registration trials. This review critically appraises current evidence supporting DTG/3TC as first-line antiretroviral therapy, drawing from randomized clinical trials and real-world studies. Available data indicate that DTG/3TC maintains high virological suppression rates even in individuals with high baseline viral load (>500,000 copies/mL), with no emergent resistance. Evidence from test-and-treat settings suggests comparable efficacy to triple therapy, provided that hepatitis B coinfection and transmitted resistance are adequately excluded. Preliminary data in late presenters and those with advanced disease support its effectiveness, although confirmatory trials are warranted. Beyond viro-immunological outcomes, DTG/3TC appears equivalent to triple regimens in reducing viral reservoirs, immune activation, and systemic inflammation. Evidence in women living with HIV, including during pregnancy, remains limited but reassuring, with no major safety concerns identified. Overall, the body of clinical and real-world evidence supports DTG/3TC as a simplified and durable first-line regimen for most treatment-naive PWH. Ongoing research should further define its role in acute infection, advanced HIV disease, and specific subpopulations such as women and individuals from regions with high prevalence of non-B subtypes
Evaluation of Oral Supplementation of Black Cumin (Nigella sativa) on Growth Performance, Immune Response, Disease Incidence and Mortality Rate of Suckling Zaraibi Goat Kids
No full textThe aim of this study was to evaluate the effects of Nigella sativa supplementation on the immune response, disease incidence, mortality rate and growth performance of suckling Zaraibi goat kids. Sixty suckling Zaraibi goat kids (33 males and 27 females) with an average body weight of 3.03 ± 0.02 kg were divided into three groups: a control group (G1), which was fed a basal diet and two treatment groups (G2 and G3), which were fed the same diet supplemented with 0.5 g and 1.0 g of N. sativa per kid per day, respectively, for 84 days. The data were analysed with a general linear model to assess the differences among dietary treatments, and Duncan's multiple range test was applied for post hoc comparisons. Compared with G1, the body weight of the kids in the treatment groups was significantly higher (p < 0.05). Consequently, total weight gain and average daily gain were significantly raised in the G2 and G3 groups compared to the control group (p < 0.05). In addition, the feed intake was significantly higher, whereas the feed conversion ratio was significantly lower in G3 compared to G1 (p < 0.05). The outputs of weaning weight and the adjusted mortality rate increased significantly (p < 0.05), in line with the increasing levels of N. sativa in G2 and G3. G3 fed the highest level of N. sativa and registered the lowest occurrence of diseases, followed by G2, whereas the control, G1, showed the highest incidence (p < 0.05). In particular, the mortality rate decreased significantly (p < 0.05) with the inclusion of N. sativa, showing a clear dose-dependent effect. The highest mortality rate was observed in G1 (15%), followed by G2 (10%), while G3 exhibited the lowest mortality rate (5%) (p < 0.05). The plasma IgG levels were significantly higher in the G2 and G3 groups compared to the control group (p < 0.05), with G3 exhibiting increased IgG levels than G2 (p < 0.05). These findings suggest that N. sativa supplementation can enhance the health and growth performance of suckling Zaraibi goat kids, contributing to sustainable farming practices and potentially reducing antibiotic use in livestock
Clinical and Genotypic Spectrum of Twinkle-Related Disorders: Insights From a Multinational Cohort Study
No full textBackground and objectives: Twinkle, encoded by the TWNK gene, is a mitochondrial DNA helicase that unwinds the double helix of DNA during replication, playing a pivotal role in mitochondrial function. Twinkle-related disorders encompass a variety of genetic disorders characterized by mitochondrial dysfunction. Although several phenotypes have been described, the full clinical and molecular spectrum remains poorly defined. The aim of this study was to characterize the phenotypic and genotypic variability among multinational patients diagnosed with Twinkle-related disorders. Methods: A retrospective cohort study was conducted in patients with Twinkle-related disorders at several specialized centers in Italy, France, Germany, Spain, Denmark, Hungary, and the United States, establishing the Twinkle-Related Disorders International Consortium for Trial Readiness (TReDIC). Data were collected from medical records, including clinical features, age at onset, disease progression, and results from genetic testing. Phenotypic categories included infantile-onset cerebellar ataxia, parkinsonism, primary mitochondrial myopathy (PMM), multisystem involvement, asymptomatic carriers, undetermined phenotypes, and other phenotypes. All patients' diagnoses were confirmed by genetic analysis, and their genetic variants were noted. Outcomes included prevalence of phenotypes, symptom chronology, and mutational patterns. Results: The study included a total of 189 patients (116 female), with a mean age at symptom onset of 40.3 years. At the time of analysis, 70.4% were alive. PMM was the predominant syndrome (85.2%), and most common features were progressive external ophthalmoplegia (84.7%) and skeletal myopathy (55.6%), followed by hearing loss (17.5%) and psychiatric symptoms (15.3%). Most patients (76.8%) presented with neuromuscular symptoms, with fewer showing CNS (19.6%) or multiorgan (3.6%) features at onset; by more than 8 years from onset, these proportions shifted to 54.4%, 23.3%, and 23.3%, respectively. A total of 73 TWNK variants (16 novel) were found, mostly missense, clustered in functionally critical regions. Discussion: This large multinational cohort analysis advances our understanding of Twinkle-related disorders by identifying mutational hotspots with clinical relevance and illustrating the broad phenotypic spectrum and progression patterns. In the context of such rare diseases, the formation of international collaborations, such as TReDIC, can enhance our understanding and support the design of upcoming clinical trials
And without Thorn the Rose. Variazioni ambrosiane su una metafora concettuale
No full textA passage from Ambrose's Hexameron is examined in light of 'Conceptual Metaphor Theory', in order to demonstrate the usefulness of CMT in shedding light on the strategies employed by the Fathers to be effective when preaching to diverse audiences
Diffusion-augmented direct classification: A few-shot learning framework for Synthetic Aperture Radar image automatic target recognition
No full textDeep learning-based (DL-based) synthetic aperture radar automatic target recognition technology (SAR-ATR) has undergone extensive development, demonstrating superiority over other competitive methods. However, the intrinsic requirement of deep learning for a large labeled dataset restricts its practical application. Moreover, some DL-based few-shot SAR-ATR methods are overly complex, hindering their deployment in real-world applications. In addressing these obstacles, our solution introduces a straightforward yet efficient few-shot learning approach titled Diffusion-Augmented Direct Classification for few-shot SAR-ATR applications. The proposed method adopts a two-stage paradigm, where a diffusion model first learns from unlabeled data and then produces synthetic samples to train a recognition model. In the upstream stage, a lightweight diffusion-based image generator build upon the shuffle-residual network structure is trained on a limited number of annotated SAR images to generate artificial training samples for the downstream recognition model. In the downstream stage, a Siamese network-based recognition model and a similarity training procedure are proposed to train the model on a combination of real-world and artificial samples, thereby improving recognition accuracy. A projection expansion layer is proposed to improve the efficiency of cosine similarity loss in the downstream. Experiments conducted on the Moving and Stationary Target Acquisition and Recognition dataset demonstrated that our method outperformed other few-shot learning methods concerning recognition accuracy in SAR-ATR tasks. Specifically, our method achieves over 73% accuracy in a 5-sample-per-class scenario and over 85% accuracy in a 10-samples-per-class scenario. Source code of our paper is available at https://github.com/yikuizhai/DADC
Celebrating 30 years since the Gerhard Leyendecker and colleagues' formulation of the hyper-dysperistalsis theory in endometriosis
No full textHazard and determinants of dropout and rehospitalization in patients with obesity after residential rehabilitation
No full textPurpose: To identify clinical and sociodemographic factors that predict follow-up discontinuation and rehospitalisation after multidisciplinary residential rehabilitation for severe obesity, thereby defining high-risk patient profiles and guiding tailored retention strategies. Methods: We retrospectively followed 1,851 adults with obesity discharged from a multidisciplinary residential programme between 2015 and 2018 (median BMI 42 kg m−2). Dropout, defined as more than twelve months without contact, was studied with discrete-time survival models; time to rehospitalisation was analysed with Cox regression. Results: Within twelve months 1,513 patients (87%) discontinued follow-up. Each five-year increase in age lowered drop-out risk (HR 0.97, 95% CI 0.94–0.99, p = 0.004); diabetes had a similar protective effect (HR 0.89, 0.79–1.00, p = 0.0455). Rehospitalisation occurred in 591 patients (32%). Risk increased with age (5-years increment; HR = 1.05, 95% CI 1.01–1.09, p = 0.0191), baseline BMI (HR = 1.04, 95% CI 1.03–1.05, p < 0.0001), diabetes (HR = 1.22, 95% CI 1.02–1.30, p = 0.0306) and eating disorders (HR = 1.48, 95% CI 1.07–2.05, p = 0.0193). Discussion: Maintaining the benefits of residential rehabilitation is important. In our cohort, 87% of patients dropped out of follow-up within one year and 32% were readmitted. Two distinct profiles emerged: younger and non-diabetic subjects were prone to dropout, while patients with higher BMI, diabetes, or eating disorders were at higher risk of rehospitalization. Early identification of these groups may suggest flexible, technology-assisted follow-up for working-age patients and integrated metabolic-psychiatric care for complex cases, safeguarding outcomes and optimizing resources
SUSTAINABILITY STRATEGIES AND GREENWASHING ALONG FOOD VALUE CHAINS: AN EMPIRICAL ANALYSIS OF THE DETERMINANTS
No full textThe food system is vital in sustaining livelihoods on the planet, but it also entails major impacts in terms of environmental and social sustainability. In order to address the sustainability-related challenges, companies have been increasingly taking an active role in promoting sustainability, by adopting voluntary sustainability standards (VSS). Companies may not be necessarily truthful when communicating their sustainability activities, and this trend has given rise to greenwashing. To enhance sustainability, it is crucial to identify which variables promote or hinder sustainability strategies adoption and greenwashing behaviour. In our analysis, an integrated theoretical framework is developed by combining Stakeholder theory, GVC theory and Risk dependence theory to explain sustainability strategies adoption, and the focus is on the role of firm characteristics. Three samples of companies operating along different agri-food value chains were selected, and three original datasets were created by combining data from the Orbis database and from a content analysis carried out on company websites. In Chapter 1, I explore the firm characteristics which shape the pattern of sustainability strategies adoption in the cocoa-chocolate global value chain (GVC), by collecting data over a sample of 304 cocoa-chocolate companies. In Chapter 2, I assess the relationship between firm characteristics and the communication of environmental VSS in the European beef value chain. In Chapter 3, I analyse the extent to which firm characteristics relate to greenwash behaviour in the value chains of five different agri-food products, namely coconut, coffee, processed tomatoes, shrimps, soft drinks and tea. A tailored empirical strategy was developed for each chapter, and a different regression model was employed based on the characteristics and distribution of the dependent variables. The thesis demonstrates that a vast proportion of companies do not communicate any sustainability activity. Moreover, our findings suggest that highly visible, close to consumer agri-food firms are likely to make efforts to achieve sustainability. However, they are simultaneously more inclined to disclose misleading sustainability claims and engage in a greenwashing behaviour. Therefore, results imply that stronger efforts are needed to meet the SDGs set by the UN Agenda 2030