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Para cross‐country (XC) skiers compete in race courses with different terrains (uphill, downhill, and undulated) across several classes in three categories (visually, standing, and sitting impaired). The objectives were to investigate (1) the distribution of distance and relative race time spent in different terrains (%RTTerr) across different races, and (2) the association of class with %RTTerr while adjusting for sex and final rank. Sixty‐eight Para XC skiers were tracked with GNSS sensors during middle‐ and long‐distance races at two World Championships. Linear mixed models were used to investigate the association of class with %RTTerr while adjusting for sex and final rank. The relative distance covered in each terrain (uphill: 17%–42%, downhill: 27%–46%, and undulated: 12%–56%) and corresponding %RTTerr (uphill: 20%–58%, downhill: 16%–30%, and undulated: 12%–57%) varied across races. Nevertheless, individual %RTTerr was relatively consistent among the Para cross‐country skiers within each race. There was no significant effect of class on %RTTerr for sitting and standing skiers, indicating that the differences between classes are similar or smaller than those between individual skiers within a class. In contrast, there was a significant effect of class on %RTTerr for the visually impaired skiers (p < 0.019). Furthermore, lower ranked skiers spent ∼0.1–0.25%pt more time in the uphill terrain per rank (p < 0.001 for all categories) and ∼0.05–0.25%pt less time in the downhill terrain per rank (p < 0.01). Finally, women skiers spent significantly more of their %RTTerr in the uphill terrain (∼1.3–2.3%pt, p < 0.04) and less in the downhill terrain (∼1.0–2%pt, p < 0.01). Given the small sample size within most classes, our findings need to be interpreted with caution.

The concentration of dissolved oxygen in aquatic systems helps to regulate biodiversity(1,2), nutrient biogeochemistry(3), greenhouse gas emissions(4), and the quality of drinking water(5). The long-term declines in dissolved oxygen concentrations in coastal and ocean waters have been linked to climate warming and human activity(6,7), but little is known about the changes in dissolved oxygen concentrations in lakes. Although the solubility of dissolved oxygen decreases with increasing water temperatures, long-term lake trajectories are difficult to predict. Oxygen losses in warming lakes may be amplified by enhanced decomposition and stronger thermal stratification(8,9) or oxygen may increase as a result of enhanced primary production(10). Here we analyse a combined total of 45,148 dissolved oxygen and temperature profiles and calculate trends for 393 temperate lakes that span 1941 to 2017. We find that a decline in dissolved oxygen is widespread in surface and deep-water habitats. The decline in surface waters is primarily associated with reduced solubility under warmer water temperatures, although dissolved oxygen in surface waters increased in a subset of highly productive warming lakes, probably owing to increasing production of phytoplankton. By contrast, the decline in deep waters is associated with stronger thermal stratification and loss of water clarity, but not with changes in gas solubility. Our results suggest that climate change and declining water clarity have altered the physical and chemical environment of lakes. Declines in dissolved oxygen in freshwater are 2.75 to 9.3 times greater than observed in the world's oceans(6,7) and could threaten essential lake ecosystem services(2,3,5,11).

In order to receive efficient personalized recommendation, users have to provide personal information to service providers. However, in this process, personal private data are in an extremely dangerous situation. Personalized recommendation technology based on privacy protection can enable users to enjoy personalized recommendations, while private data are also protected. In this paper, an efficient privacy-preserving collaborative filtering algorithm is proposed, which is based on differential privacy protection and time factor. The proposed method used the MovieLens data set in the experiment. Experimental results showed that the proposed method can effectively protect the private data, but the accuracy of recommendation is slightly inferior than the traditional collaborative filtering algorithm.

Abnormal transaction order detection plays an important role in identifying transaction data changes and abnormal transaction behaviors of users. The existing abnormal order detection methods have low generalization ability in different transaction time series, and the exception itself has a variety of patterns. In addition, the positive sample points with a large proportion carry much more information than the abnormal sample points, which will cause the classifier to be disturbed in the learning process and inaccurate classification. The research proposes an unsupervised abnormal transaction order detection method based on the depth learning time factor. By processing the original data column, the first feature sequence is obtained, and then the later feature sequence is trained through the depth learning model. The abnormal order is detected by comparing the differences between the two feature sequences. The results show that the research effectively solves the practical problem of too few abnormal transaction samples, can be applied to the transaction process of different modes, reduces the noise in the original transaction data, and has obvious improvement in each evaluation index compared with the traditional method.

Cancer may be a complication of inflammatory bowel disease (IBD) or its treatment. In elderly onset IBD patients the risk of malignancy is of particular concern. We studied this risk in a population-based cohort of elderly onset IBD patients. In a French population-based cohort, we identified 844 patients aged >60 years at IBD diagnosis from 1988 to 2006, including 370 Crohn's disease (CD) and 474 ulcerative colitis (UC). We compared incidence of cancer among IBD patients with that observed in the French Network of population-based Cancer Registries (FRANCIM). Confidence interval (CI) was estimated assuming a Poisson-specific law for rare events. Results were expressed using the standardized incidence ratios (SIRs) and their CI 95%. Median age at IBD diagnosis was 70 (65-76) years in CD and 69 (64-74) in UC. Median follow-up was 6 (2-11) years for both diseases with a number of person-years of 5,598. Among the 844 elderly onset IBD cases, 98 (11.6%; 42 CD and 56 UC) developed a cancer after IBD diagnosis (67 men and 31 women) corresponding to an overall SIR of 0.97 (0.80-1.18). These cancers occurred at a median age of 77 years (71-80) and 75 years (71-81) in patients with CD and UC, respectively. Median time between IBD diagnosis and cancers was 78 months (40-121). There was no significant increased risk of colorectal cancer in IBD (SIR=1.03 (0.62-1.70), CD (SIR=1.20 (0.57-2.52) nor in UC (SIR=0.91 (0.45-1.82) without significant protective role of 5-aminosalicylic acid (hazard ratio (HR)=0.7 (0.2-2.6)). No significant risk for other intestinal cancers was found, especially for small bowel carcinoma. An increased risk of malignant lymphoproliferative disorders was found in all IBD and in CD: SIR=2.49 (1.25-4.99) and SIR=3.09 (1.16-8.23), respectively. An increased risk of myeloproliferative disorders was found in all IBD (SIR=2.18 (1.09-4.35)). Thiopurines exposure, using a time-dependant Cox model, was not found as associated with an increased risk to develop cancer, HR=0.90 (0.48-1.68). There is no increased risk for developing intestinal cancer among patients with elderly onset IBD in this population-based cohort. There are increased risks of developing lymphoproliferative and myeloproliferative disorders in all IBD. Thiopurines exposure was not found as associated with an increased risk to lymphoproliferative disorders. These data reinforce the difference between elderly onset IBD as compared with patients with younger age at IBD onset.

Homologous recombination is essential for the accurate repair of double-stranded DNA breaks (DSBs) 1 . Initially, the RecBCD complex 2 resects the ends of the DSB into 3′ single-stranded DNA on which a RecA filament assembles 3 . Next, the filament locates the homologous repair template on the sister chromosome 4 . Here we directly visualize the repair of DSBs in single cells, using high-throughput microfluidics and fluorescence microscopy. We find that, in Escherichia coli , repair of DSBs between segregated sister loci is completed in 15 ± 5 min (mean ± s.d.) with minimal fitness loss. We further show that the search takes less than 9 ± 3 min (mean ± s.d) and is mediated by a thin, highly dynamic RecA filament that stretches throughout the cell. We propose that the architecture of the RecA filament effectively reduces search dimensionality. This model predicts a search time that is consistent with our measurement and is corroborated by the observation that the search time does not depend on the length of the cell or the amount of DNA. Given the abundance of RecA homologues 5 , we believe this model to be widely conserved across living organisms. Observations of rapid repair of double-stranded DNA breaks in sister choromosomes in Escherichia coli are consistent with a reduced-dimensionality-search model of RecA-mediated repair.

Conventional exposure–response (E–R) analyses, such as logistic regression and time‐to‐event analysis using summary exposure metrics, are often conducted in oncology using data from the pivotal trial(s) with a single dose level to support dosing decisions. However, these E–R analyses, affected by multiple confounding factors, may mischaracterize true E–R relationships, potentially limiting their utility in dosing decisions. This study investigates potential mischaracterization in such analyses influenced by the following time‐dependent confounding factors: exposure accumulation, dose modification patterns, and event onset time. We used a simulation‐based approach to evaluate two E–R scenarios: ER1, where event time generated with a Weibull distribution is not affected by drug exposure, and ER2, where the response is driven by drug exposure via a joint PK‐tumor size model. Our analyses indicate that when using time‐dependent exposure metrics (e.g., average concentration till event/censoring), exposure accumulation tends to induce an inverse E–R trend, while dose modifications (interruptions/reductions) likely induce a positive E–R trend. Simulations suggest that employing static exposure metrics (e.g., first‐cycle or steady‐state) minimizes these biases. Additionally, adopting an Emax model aligned with the underground truth in ER2 in the E–R analyses could reduce bias. When significant dose modifications are present, including relevant data from a dose‐range study and employing modified methods for time‐dependent exposure derivation may help mitigate bias. Overall, using multiple exposure metrics (including static ones) to assess E–R consistency and interpreting the potential causal effects with totality of evidence (including dose–response results) should be implemented to better inform dosing decisions. Scheme of evaluation and mitigation of time‐dependent confounding effects in conventional exposure‐response analyses for oncology drugs.

Background Favorable survival in malignant cutaneous melanoma (melanoma) has increased the likelihood of second primary cancer (SPC). We assess the influence of patient characteristics at diagnosis of first melanoma and the type of SPC (second melanoma and other SPC) on overall survival. Methods We used the Swedish Cancer Registry data to assess overall survival in melanoma for the period 1990 to 2015. Kaplan-Meier curves were plotted and hazard ratios (HRs) were estimated with Cox regression models by considering SPC diagnosis as a time-dependent variable. Results A total of 46,726 patients were diagnosed with melanoma, and 15.3% of them developed SPC, among which, two thirds were other SPCs. Second melanomas were diagnosed early (31% during the first year) compared to non-melanoma SPCs (9.5%). Survival for women with second melanoma or other SPC (56 and 21% alive after 25 years of follow-up, respectively) exceeded the male rates (21 and 10%, respectively) but all these figures were lower than for females (60% alive) or males (48%) without SPC. Time dependent analysis showed vastly increased HRs for cancer types that are fatal also as first cancers, but SPC-specific HRs remained relatively uniform, irrespective of SPC diagnosed soon or late after first melanoma. In early-onset melanoma, SPC diagnosis after 10 years may not negatively influence overall survival. Conclusions As the overall survival of patients with many types of SPCs is unfavorable, advice about health lifestyle should benefit smoking patients and early detection methods may be recommended for SPCs of the breast, prostate and colorectum.

Background Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED. Methods Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants ( n  = 156) and independently on data from a subset of U-BIOPRED asthma participants ( n  = 82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset ( n  = 397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13. Results Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was “mild, good lung function, early onset”, with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a “moderate, hyper-responsive, eosinophilic” phenotype , with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a “mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic” phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a “severe uncontrolled, severe reversible obstruction, mixed granulocytic” phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort. Conclusions Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies. Trial registration NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013.