Tapping into non-English-language science for the conservation of global biodiversity.

The widely held assumption that any important scientific information would be available in English underlies the underuse of non-English-language science across disciplines. However, non-English-language science is expected to bring unique and valuable scientific information, especially in disciplines where the evidence is patchy, and for emergent issues where synthesising available evidence is an urgent challenge. Yet such contribution of non-English-language science to scientific communities and the application of science is rarely quantified. Here, we show that non-English-language studies provide crucial evidence for informing global biodiversity conservation. By screening 419,679 peer-reviewed papers in 16 languages, we identified 1,234 non-English-language studies providing evidence on the effectiveness of biodiversity conservation interventions, compared to 4,412 English-language studies identified with the same criteria. Relevant non-English-language studies are being published at an increasing rate in 6 out of the 12 languages where there were a sufficient number of relevant studies. Incorporating non-English-language studies can expand the geographical coverage (i.e., the number of 2° × 2° grid cells with relevant studies) of English-language evidence by 12% to 25%, especially in biodiverse regions, and taxonomic coverage (i.e., the number of species covered by the relevant studies) by 5% to 32%, although they do tend to be based on less robust study designs. Our results show that synthesising non-English-language studies is key to overcoming the widespread lack of local, context-dependent evidence and facilitating evidence-based conservation globally. We urge wider disciplines to rigorously reassess the untapped potential of non-English-language science in informing decisions to address other global challenges. Please see the Supporting information files for Alternative Language Abstracts.

The ATTRACT study: screening for the early identification of axial psoriatic arthritis in a cohort of Italian psoriatic patients.

OBJECTIVE: There is growing interest in the early identification of patients with axial psoriatic arthritis (axPsA). We aimed to evaluate whether a dermatology-based screening strategy could help to identify axPsA patients. METHODS: The dermatologist-centered screening (DCS) questionnaire was administrated by Dermatologists to consecutive patients fulfilling the inclusion criteria (1. age ≥ 18 years and 2. clinical diagnosis of psoriasis made by a dermatologist) to identify patients eligible (affirmative answers 1-3c of the DCS) for rheumatological evaluation. Clinical, laboratory, genetic, and imaging data were collected from all referred patients. RESULTS: Among the 365 patients screened, 265 fulfilled the inclusion criteria and 124/265 (46.8%) were eligible for rheumatological referral. Diagnosis of axPsA, with or without peripheral PsA (pPsA), was made in 36/124 (29.0%) patients; pPsA without axial involvement was found in 21/124 (16.9%) patients. Back pain at screening was recorded in 174 (66%) patients, with 158 (60%) reporting a back pain duration longer than 3 months, and 140 (53%) reporting back pain onset before the age of 45. Active inflammatory and/or structural post-inflammatory changes in the sacroiliac joints and/or spine were observed in all axPsA patients.Patients with PsA showed a numerically longer duration of back pain and higher CRP levels in comparison with patients with Pso without PsA. CONCLUSION: The DCS tool proved to be a valuable screening strategy for detecting and characterizing patients with axPsA in a real-life cohort of psoriasis patients in a dermatological setting and helped to identify a substantial number of patients affected by undiagnosed pPsA.

The spectral color of natural and anthropogenic time series and its impact on the statistical significance of cross correlation.

The cross-correlation between time series is a common tool to study and quantify the impact of climatic and anthropogenic changes on ecosystems. The traditional method for estimating the statistical significance of correlation relies on the assumption that the data are independent, but time series found in nature are often strongly auto-correlated because of low-frequency environmental variability and ecosystem inertia. Previous authors have used Monte Carlo simulations to study the impact of serial auto-correlation on the significance of cross-correlations. Most studies have used random time series that are often a poor representation of those found in nature, e.g., low-order auto-regressive models with normally distributed noise. Moreover, we are not aware of any tests of the applicability of those methods to anthropogenic time series. Here, we study the effect of serial auto-correlation on the performance of two methods for estimating the significance of cross-correlations determined from Monte Carlo simulations with time series that are generated synthetically based on power-law specification of spectral characteristics. Such time series have an auto-correlation structure defined by a single parameter, their spectral "color", and are generally more convenient representations of natural time series than the autoregressive models. Our results show that one of the two methods considered here accurately reproduces prescribed error rates for the wide range of spectral colors representative of climatic, ecological and anthropogenic time series. For this, we characterized roughly 1800 observational records in different categories of spectral colors, including climate variability, abundance of vertebrate species, and pollution. We specifically focus on time series with annual sampling over data records of at least 40 years, which are particularly relevant for climate studies. The methodology advocated in this study provides a simple and realistic assessment of the significance of sample estimates of cross correlation for time series with any sample interval and record length.

SARS-COV-2 Infection, Vaccination, and Immune-Mediated Diseases: Results of a Single-Center Retrospective Study.

Objectives: The relationship between infections or vaccine antigens and exacerbations or new onset of immune-mediated diseases (IMDs) has long been known. In this observational study, conducted during the COVID-19 pandemic, we evaluated the onset of clinical and laboratory immune manifestations related to COVID-19 or SARS-CoV-2 vaccination. Methods: Four groups of patients were evaluated: A) 584 COVID-19 inpatients hospitalized from March 2020 to June 2020 and from November 2020 to May 2021; B) 135 outpatients with previous SARS-CoV-2 infection, assessed within 6 months of recovery; C) outpatients with IMDs in remission and flared after SARS-COV-2 infection; D) outpatients with symptoms of probable immune-mediated origin after SARS-CoV-2 vaccination. Results: In cohort A we observed n. 28 (4.8%) arthralgia/myalgia, n. 2 (0.3%) arthritis, n. 3 (0.5%) pericarditis, n. 1 (0.2%) myocarditis, n. 11 (1.9%) thrombocytopenia or pancytopenia, and in the follow up cohort B we identified 9 (6.7%) cases of newly diagnosed IMDs after the recovery from COVID-19. In all cases, serological alterations were not observed.In cohort C we observed n.5 flares of pre-existing IMD after SARS-COV2 infection, and in the cohort D n. 13 IMD temporally close with SARS-CoV-2 vaccination in 8 healthy subjects (with clinical classifiable IMD-like presentation) and in 5 patients affected by an anamnestic IMD. Also in these latter cases, except in 2 healthy subjects, there were not found serological alterations specific of a classifiable IMD. Conclusions: This study suggests that the interplay between SARS-CoV-2 and the host may induce complex immune-mediated reactions, probably induced by the anti-spike antibodies, in healthy people and IMD patients without specific serological autoimmunity. Moreover, our data suggest that the anti-SARS-CoV-2 antibodies generated by the vaccination may cause in healthy subjects' clinical manifestations similar to well-definite IMDs. These findings support the hypothesis that SARS-Cov2 infection in COVID-19 induce an innate and adaptive immune response that may be both responsible of the symptoms correlated with the occurrence of the IMDs described in our study. And, in this context, the IMDs observed in healthy people in close temporal correlation with the vaccination suggest that the anti-Spike antibodies may play a key role in the induction of an abnormal and deregulated immune response.

Diagnostic Performance of Digital Breast Tomosynthesis, Unenhanced MRI, and Their Combination in the Preoperative Assessment of Breast Cancer: A Multi-reader Study.

RATIONALE AND OBJECTIVES: To compare the diagnostic performance of digital breast tomosynthesis (DBT) and unenhanced magnetic resonance imaging (UMRI) in the preoperative assessment of breast cancer. MATERIALS AND METHODS: We retrospectively included 59 patients with 74 pathology-proven cancers who underwent DBT and preoperative 1.5 T magnetic resonance imaging between January 2016 and February 2017. Four residents with 2-3 years of experience, blinded to pathology, independently reviewed DBT and UMRI (diffusion-weighted and unenhanced T1-weighted sequences), using the breast imaging reporting and data system (BI-RADS) and a 0-5 Likert score, respectively. We calculated per-lesion sensitivity and positive predictive value of DBT, UMRI, and combined DBT+UMRI, as well as the agreement between DBT and UMRI vs. pathology in assessing cancer size (Bland-Altman analysis). Logistic regression was performed to assess clinical features predictive of missing cancer. RESULTS: Of 74 lesions, 84% were invasive ductal carcinoma, 27% of which with an in situ component; 31% of cancers were ≤10 mm large. Sensitivity of UMRI (74-85%) was equal or higher than that of DBT (68-82%), with similar positive predictive value (93-97% vs. 98-100%, respectively). DBT+UMRI increased the sensitivity up to 88%. UMRI showed closer limits of agreement with pathological size than DBT. Missing cancer was independently predicted by size ≤10 mm on DBT, UMRI, and DBT+UMRI (odds ratio 18.7, 5.1, and 13.3, respectively), and by increased breast density on DBT alone (odds ratio 3.50). CONCLUSION: UMRI was equal or better than DBT in the preoperative assessment of breast cancer. Combined imaging achieved up to 88% per-lesion sensitivity, suggesting potential use in clinical practice.

Preoperative assessment of breast cancer: Multireader comparison of contrast-enhanced MRI versus the combination of unenhanced MRI and digital breast tomosynthesis.

PURPOSE: To compare the sensitivity for breast cancer (BC) and BC size estimation of preoperative contrast-enhanced magnetic resonance imaging (CEMRI) versus combined unenhanced magnetic resonance imaging (UMRI) and digital breast tomosynthesis (DBT). PATIENTS AND METHODS: We retrospectively included 56 women who underwent DBT and preoperative 1.5 T CEMRI between January 2016-February 2017. Three readers with 2-10 years of experience in CEMRI and DBT, blinded to pathology, independently reviewed CEMRI (diffusion-weighted imaging [DWI], T2-weighted imaging, pre- and post-contrast T1-weighted imaging) and a combination of UMRI (DWI and pre-contrast T1-weighted imaging) and DBT. We calculated per-lesion sensitivity of CEMRI and UMRI + DBT, and the agreement between CEMRI, UMRI and DBT versus pathology in assessing cancer size (Bland-Altman analysis). Logistic regression was performed to assess features predictive of cancer missing. RESULTS: We included 70 lesions (64% invasive BC, 36% ductal carcinoma in situ or invasive BC with in situ component). UMRI + DBT showed lower sensitivity (86-89%) than CEMRI (94-100%), with a significant difference for the most experienced reader only (p = 0.008). False-positives were fewer with UMRI + DBT (4-5) than with CEMRI (18-25), regardless of the reader (p = 0.001-0.005). For lesion size, UMRI showed closer limits of agreement with pathology than CEMRI or DBT. Cancer size ≤1 cm was the only independent predictor for cancer missing for both imaging strategies (Odds ratio 8.62 for CEMRI and 19.16 for UMRI + DBT). CONCLUSIONS: UMRI + DBT showed comparable sensitivity and less false-positives than CEMRI in the preoperative assessment of BC. UMRI was the most accurate tool to assess cancer size.

Clinical and patient reported outcomes of the multidisciplinary management in patients with inflammatory bowel disease-associated spondyloarthritis.

OBJECTIVE: Arthritis is the most frequent extra-intestinal manifestation in patients with inflammatory bowel diseases (IBD). The coexistence of intestinal and articular inflammation advocates the need for a multidisciplinary management of patients with IBD-associated spondyloarthritis. METHODS: Consecutive IBD patients were evaluated jointly by the gastroenterologist and the rheumatologist in a combined clinic. All the patients were assessed and screened for articular involvement, disease activity and health related quality of life. After the prescription of a shared treatment, patients with spondyloarthritis were followed up for 24 months. RESULTS: Two hundred sixty-two IBD patients, including 80 who were classified as affected by spondyloarthritis according to the ASAS criteria, were included in the study. At baseline, patients with both IBD and spondyloarthritis showed worse quality of life in both the physical and mental domains. The multidisciplinary management provided a significant improvement of gastrointestinal and articular manifestations, as well as the health-related quality of life. Moreover, global and gastrointestinal-specific quality of life significantly correlated with articular disease activity. CONCLUSION: The multidisciplinary management significantly improves both articular and gastrointestinal disease activities and the quality of life of patients with IBD-associated spondyloarthritis. An appropriate screening strategy and the integrated management of these patients should be encouraged and employed in clinical practice.