Characterization and outcomes of 414 patients with primary SS who developed haematological malignancies

Objective: To characterize 414 patients with primary SS who developed haematological malignancies and to analyse how the main SS- and lymphoma-related features can modify the presentation patterns and outcomes. Methods: By January 2021, the Big Data Sjögren Project Consortium database included 11 966 patients fulfilling the 2002/2016 classification criteria. Haematological malignancies diagnosed according to the World Health Organization (WHO) classification were retrospectively identified. Results: There were 414 patients (355 women, mean age 57 years) with haematological malignancies (in 43, malignancy preceded at least one year the SS diagnosis). A total of 376 (91%) patients had mature B-cell malignancy, nearly half had extranodal marginal zone lymphoma (MZL) of mucosa-associated lymphoid tissue (MALT lymphoma) (n = 197), followed by diffuse large B-cell lymphoma (DLBCL) (n = 67), nodal MZL lymphoma (n = 29), chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) (n = 19) and follicular lymphoma (FL) (n = 17). Rates of complete response, relapses and death were 80%, 34% and 13%, respectively, with a 5-year survival rate of 86.5% after a mean follow-up of 8 years. There were significant differences in age at diagnosis (younger in MALT, older in CLL/SLL), predominant clinical presentation (glandular enlargement in MALT lymphoma, peripheral lymphadenopathy in nodal MZL and FL, constitutional symptoms in DLBCL, incidental diagnosis in CLL/SLL), therapeutic response (higher in MALT lymphoma, lower in DLBCL) and survival (better in MALT, nodal MZL and FL, worse in DLBCL). Conclusion: In the largest reported study of haematological malignancies complicating primary SS, we confirm the overwhelming predominance of B-cell lymphomas, especially MALT, with the salivary glands being the primary site of involvement. This highly-specific histopathological scenario is linked with the overall good prognosis with a 5-year survival rate of nearly 90%

Tasso di abbandono fra i lanciatori finalisti dei campionati mondiali juniores

Scopo dello studio \ue8 stato quello di indagare il fenomeno del drop-out nelle specialit\ue0 dei lanci nell\u2019atletica leggera. Sono stati monitorati quali e quanti atleti finalisti delle quattro edizioni dei campionati del mondo juniores dal 2002 al 2008 siano riusciti a rimanere nella top-10 del ranking mondiale assoluto fino al 2010. Sono stati presi in considerazione i 10 finalisti delle specialit\ue0 dei lanci divisi per genere che hanno partecipato ai mondiali juniores nelle edizioni di Kingston 2002, Grosseto 2004, Beijing 2008 e Bydygoszcz 2008. Tramite un calcolatore elettronico e il programma di Excel per l\u2019elaborazione dei dati \ue8 stata monitorata l\u2019et\ue0 e la posizione nel ranking mondiale assoluto a partire dall\u2019anno del mondiale fino al 2010. Per dropout \ue8 stata considerata l\u2019assenza dell\u2019atleta nella graduatoria internazionale assoluta per due anni successivi. Di tutti gli atleti presi in considerazione verranno presentati i risultati relativi ai tassi di drop-out suddivisi per mondiale juniores. Questi poi verranno distinti per genere e specialit\ue0. In generale si assiste ad un incremento del tasso di abbandono nella specialit\ue0 in cui il passaggio da una categoria a quella successiva comporta un aumento significativo del peso dell\u2019attrezzo, rendendo gli adattamenti riguardanti sia gli aspett

Does the junior IAAF athletic world championship represent a springboard for the success in the throwing events? : a retrospective study

Aim. The aim of the present study was to analyze how many finalists of the IAAF World Junior Championships (WJC) in the throwing events were present in the senior IAAF ranking at the end of 2012. Methods. The results of the 8 male and the 8 female finalists of all throwing events of the last 5 editions of the WJC from the 2002 edition were gathered. We analyzed how many ath- letes were missing from the IAAF ranking in 2012. For those athletes that did not drop out we monitored their progression in performance comparing their WJC and their 2012 per- formance. Moreover, we evaluated if the relative age effects (RAE) influenced drop out rate. Results. Drop out rate was 58% in 2002, 59% in 2004, 39% in 2006, and 28% in 2008 and in 2010. The female javelin throwers showed the highest drop out rate (100%) in 2002, while the female hammer throwers showed the lowest drop out rate (0%) in 2008. Performance decreased for all male shot putters, discus and hammer throwers (P<0.001). For fe- males and for male javelin throwers, performance increased (P<0.001). RAEs showed no significant influence on drop out rate Conclusion. Even if 8 of the finalists won a medal at the Olympic Games or at the World Championships, it is still not clear if participation at the WJC is a prerequisite to success at a senior level, given the elevated drop out rate observed in the present study

Concurrent strength and endurance training effects on running economy in master endurance runners

Running economy (RE) has been seen to improve with concurrent strength and endurance training in young and elite endurance athletes. The purpose of the present study was to evaluate the effects of 2 different strength training protocols on RE and strength parameters in a group of regularly training master marathon runners. Sixteen participants were randomly assigned to a maximal strength training program (MST; n = 6; 44.2 \ub1 3.9 yrs), a resistance training (RT; n = 5; 44.8 \ub1 4.4 yrs) and a control group (CG; n = 5; 43.2 \ub1 7.9 yrs). Before and after the experimental period, resting metabolic rate, body composition, 1 repetition maximum, squat jump, countermovement jump and RE were evaluated. The MST group showed significant increases (p 0.05). Anthropometric data were unchanged after the training intervention (p > 0.05). Taken together, the results of this preliminary study indicate that master endurance athletes seem to benefit from concurrent strength and endurance training because the rate of force development may be crucial for RE improvement, one of the major determinants of endurance performance

Breathable hydrogel dressings containing natural antioxidants for management of skin disorders

Traditional wound dressings are not effective enough to regulate the moisture content and remove excessive exudate from the environment. Wet wound dressings formed from hydrogels such as alginate are widely used in clinical practice for treatment of skin disorders. Here, we functionalize alginate dressings with natural antioxidants such as curcumin and t-resveratrol to render them both anti-inflammatory and antibacterial. The hydrogel maintains excellent mechanical properties and oxygen permeability over time. The release rate of the compounds from the hydrogels is assessed and their impact on bacterial and cellular growth is evaluated. The antioxidant compounds act as bactericidal agents and improve cell viability. The optimal concentration of active compounds in the engineered alginate-based dressings is determined

1RM prediction: A novel methodology based on the force-velocity and load-velocity relationships

Purpose: This study aimed to evaluate the accuracy of a novel approach for predicting the one-repetition maximum (1RM). The prediction is based on the force-velocity and load-velocity relationships determined from measured force and velocity data collected during resistance-training exercises with incremental submaximal loads. 1RM was determined as the load corresponding to the intersection of these two curves, where the gravitational force exceeds the force that the subject can exert. Methods: The proposed force-velocity-based method (FVM) was tested on 37 participants (23.9 ± 3.1 year; BMI 23.44 ± 2.45) with no specific resistance-training experience, and the predicted 1RM was compared to that achieved using a direct method (DM) in chest-press (CP) and leg-press (LP) exercises. Results: The mean 1RM in CP was 99.5 kg (±27.0) for DM and 100.8 kg (±27.2) for FVM (SEE = 1.2 kg), whereas the mean 1RM in LP was 249.3 kg (±60.2) for DM and 251.1 kg (±60.3) for FVM (SEE = 2.1 kg). A high correlation was found between the two methods for both CP and LP exercises (0.999, p < 0.001). Good agreement between the two methods emerged from the Bland and Altman plot analysis. Conclusion: These findings suggest the use of the proposed methodology as a valid alternative to other indirect approaches for 1RM prediction. The mathematical construct is simply based on the definition of the 1RM, and it is fed with subject's muscle strength capacities measured during a specific exercise. Its reliability is, thus, expected to be not affected by those factors that typically jeopardize regression-based approaches

Performance of an AI algorithm during the different phases of the COVID pandemics: what can we learn from the AI and vice versa

Background: Artificial intelligence (AI) has proved to be of great value in diagnosing and managing Sars-Cov-2 infection. ALFABETO (ALL-FAster-BEtter-TOgether) is a tool created to support healthcare professionals in the triage, mainly in optimizing hospital admissions. Methods: The AI was trained during the pandemic's “first wave” (February-April 2020). Our aim was to assess the performance during the “third wave” of the pandemics (February-April 2021) and evaluate its evolution. The neural network proposed behavior (hospitalization vs home care) was compared with what was actually done. If there were discrepancies between ALFABETO's predictions and clinicians' decisions, the disease's progression was monitored. Clinical course was defined as “favorable/mild” if patients could be managed at home or in spoke centers and “unfavorable/severe” if patients need to be managed in a hub center. Results: ALFABETO showed accuracy of 76%, AUROC of 83%; specificity was 78% and recall 74%. ALFABETO also showed high precision (88%). 81 hospitalized patients were incorrectly predicted to be in “home care” class. Among those “home-cared” by the AI and “hospitalized” by the clinicians, 3 out of 4 misclassified patients (76.5%) showed a favorable/mild clinical course. ALFABETO's performance matched the reports in literature. Conclusions: The discrepancies mostly occurred when the AI predicted patients could stay at home but clinicians hospitalized them; these cases could be handled in spoke centers rather than hubs, and the discrepancies may aid clinicians in patient selection. The interaction between AI and human experience has the potential to improve both AI performance and our comprehension of pandemic management