OR-003 Time-sequential Changes of Myocardial AMPK and PGC-1α Expression during Detraining between High-intensity Interval Training and Moderate-intensity Continuous Training on Wistar Rats

Objective Without appropriate training stimulus, the athlete experiences a loss of the physiological adaptations brought about by exercise. In most of highly trained athletes, short of training induces a rapid decline in VO2max, but it remains above control values. However, there is no specific information for normal people about the effects of detraining during certain period aerobic training. Therefore, the purpose of this study was to examine the effects of detraining between high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on myocardial AMPK and PGC-1α expression characterization time-sequential changes in Wistar rats, as well as the changing characteristics between AMPK and PGC-1α expression characterization and cardiacrespiratory fitness (CRF). Moreover, the potential mechanism for exercise arrangement was also investigated. Methods In this study, 27 four-month-old male Wistar rats were randomly divided into the sedentary control group (C), MICT group (M) and HIIT group (H).Animals in the training groups ran on a treadmill 5 days/week during 6 weeks. HIIT group (70%-90%-50%VO2max) and MICT (50%VO2max) group was ran for 50min exercise every training day. All the rats free to gather the food and drinking water. All rats were measured the VO2max after a week adaptive training and then the M group and H group began to exercise intervention. After 6 weeks of training, rats were randomly selected from each group at the 24h, the 3rd day, the 7th day and the 10th day. The Maximal oxygen uptake test was carried out before the samples were taken, and the abdominal aortic blood, myocardium and other tissues were collected after anesthesia. The expression characterization of AMPK and PGC-1α was tested by Western blotting analysis. All statistical analyses were performed using SPSS 17.0 and GraphPad Prism 5.01 for Windows. Data was presented as mean and standard deviation（SD), unless otherwise stated. The two-way ANOVA (intervention × time) with repeated measures were used to analyze differences of HIIT and MICT with time-sequential. One-way ANOVA was used to compare the difference between time-sequential among the groups for each variable. The relationship between variables was assessed using the Pearson correlation coefficient. The expression characterization of the detraining effect was also assessed using Cohen’s d effect sizes (ES) and thresholds (<0.5=small; 0.5~0.79=moderate;≥0.8=large). The level of significance was set at P<0.05 and the confidence intervals at 95%. Results VO2max showed a gradual downward trend in both H and M groups throughout the 10 days detraining periods. Detraining in the 10th day, training cessation resulted in the VO2max of H and M group were significantly lower than detraining 24h. (P<0.05). Detraining in 3rd day, myocardial AMPK and PGC-1α increased in H group, it was significantly higher than the C group (P<0.05), but there is no differences in the other detraining days(P>0.05). Furthermore, detraining in the 7th day myocardial PGC-1α decreased in H group, this value was significantly lower than detraining 24h (P<0.05). Detraining in 7th day, myocardial AMPK and PGC-1α started decreasing, but it was not significant than C group or other detraining days (P>0.05). Conclusions (1)The present data suggest that 6 weeks HIIT and MICT can increase the expression of myocardial AMPK and PGC-1α, the VO2max training effects disappeared after 10 days detraining. (2)Detraining during the 3rd day and the 7th day was the critical time point for retraining, endurance training intervention should be arranging among these days. (3)The VO2max time-sequential changes was partially consistent with AMPK and PGC-1α expression characterization, but AMPK and PGC-1α expression characterization was more sensitive than VO2max

Differentially Private Learning with Per-Sample Adaptive Clipping

Privacy in AI remains a topic that draws attention from researchers and the general public in recent years. As one way to implement privacy-preserving AI, differentially private learning is a framework that enables AI models to use differential privacy (DP). To achieve DP in the learning process, existing algorithms typically limit the magnitude of gradients with a constant clipping, which requires carefully tuned due to its significant impact on model performance. As a solution to this issue, latest works NSGD and Auto-S innovatively propose to use normalization instead of clipping to avoid hyperparameter tuning. However, normalization-based approaches like NSGD and Auto-S rely on a monotonic weight function, which imposes excessive weight on small gradient samples and introduces extra deviation to the update. In this paper, we propose a Differentially Private Per-Sample Adaptive Clipping (DP-PSAC) algorithm based on a non-monotonic adaptive weight function, which guarantees privacy without the typical hyperparameter tuning process of using a constant clipping while significantly reducing the deviation between the update and true batch-averaged gradient. We provide a rigorous theoretical convergence analysis and show that with convergence rate at the same order, the proposed algorithm achieves a lower non-vanishing bound, which is maintained over training iterations, compared with NSGD/Auto-S. In addition, through extensive experimental evaluation, we show that DP-PSAC outperforms or matches the state-of-the-art methods on multiple main-stream vision and language tasks.Comment: To appear in AAAI 2023, Revised acknowledgments and citation

Implementation strategies to promote linkage to care for key populations after HIV self-testing: a scoping review

# Background In human immunodeficiency virus (HIV) care, key populations are sex workers, people who inject drugs, prisoners, transgender people, and men who have sex with men (MSM), who are at high risk and burden of HIV infection but face barriers to HIV prevention, treatment, and health services. HIV self-testing (HIVST) is effective in scaling up HIV testing uptake among key populations due to its cost-effective, confidential, and convenient feature. However, lacking linkage to care support remains a key challenge. This scoping synthesised the global evidence regarding implementing strategies to promote linkage to care for key populations after HIVST. # Methods This scoping review was conducted according to the Joanna Briggs Institute Manual for Evidence Synthesis. A data search was conducted on September 1, 2021. The searched databases were PubMed, Embase, EBSCOhost, Cochrane Library, Wan Fang Data (Chinese), China National Knowledge Infrastructure (Chinese), and Japan Medical Abstracts Society (Japanese). # Results Twenty studies from 2011 records met the eligibility criteria and were included for review. The study populations were MSM (9), mixed high-risk populations (7), female sex workers (3), and transgender youth (1). Implementation strategies to promote linkage to care for key populations after HIVST were classified into seven categories: 1) HIVST kits with linkage-to-care information, 2) web-based or mobile app-guided HIVST, 3) remote HIVST counselling, 4) intensive follow-up, 5) HIVST promotion through social media and key opinion leaders, 6) community engagement in HIVST and 7) financial incentive. The digital-supported intervention mainly targeted MSM in high-income settings, and the community-based approach and financial incentive strategies were mainly implemented in low and middle-income settings. Comparison of linkage outcomes between studies is problematic due to mixed interpretation and measurement of linkage to care after HIVST. # Conclusions Implementation strategies to promote linkage to care for key populations are diverse and should be incorporated in different settings and backgrounds. Innovative digital-supported HIVST research for female sex workers and high-risk populations in low and middle-income settings is warranted. A standardised definition of linkage to care following HIVST and a unified measurement of linkage outcomes should be developed and applied in future research

R2DE: a NLP approach to estimating IRT parameters of newly generated questions

The main objective of exams consists in performing an assessment of students' expertise on a specific subject. Such expertise, also referred to as skill or knowledge level, can then be leveraged in different ways (e.g., to assign a grade to the students, to understand whether a student might need some support, etc.). Similarly, the questions appearing in the exams have to be assessed in some way before being used to evaluate students. Standard approaches to questions' assessment are either subjective (e.g., assessment by human experts) or introduce a long delay in the process of question generation (e.g., pretesting with real students). In this work we introduce R2DE (which is a Regressor for Difficulty and Discrimination Estimation), a model capable of assessing newly generated multiple-choice questions by looking at the text of the question and the text of the possible choices. In particular, it can estimate the difficulty and the discrimination of each question, as they are defined in Item Response Theory. We also present the results of extensive experiments we carried out on a real world large scale dataset coming from an e-learning platform, showing that our model can be used to perform an initial assessment of newly created questions and ease some of the problems that arise in question generation

Universally composable RFID mutual authentication

A*Star SERC in SingaporeAvailable online May 2015</p

Serum metabolic profiling of rats infected with Clonorchis sinensis using LC-MS/MS method

BackgroundClonorchiasis is an important foodborne parasitic disease. The omics-based-techniques could illuminate parasite biology and further make innovations in the research for parasitic diseases. However, knowledge about the serum metabolic profiles and related metabolic pathways in clonorchiasis is very limited.MethodsA untargeted ultra-high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS) was used to profile the serum metabolites of rats at both 4 and 8 weeks post infection (wpi) with Clonorchis sinensis (C. sinensis). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, serum amino acids and phosphatidylcholines (PCs) levels were determined by targeted metabolomics analysis.ResultA total of 10530 and 6560 ions were identified in ESI+ and ESI− modes. The levels of phosphatidylcholines, glycerophosphocholine and choline were significantly changed, with the shift in lipid metabolism. Significant changes were also observed in amino acids (isoleucine, valine, leucine, threonine, glutamate and glutamine). Targeted analysis showed that BCAAs (isoleucine, valine, leucine) levels significantly increased at 4 wpi and decreased at 8 wpi; threonine was increased at 8 wpi, whereas glutamate and glutamine showed a decreasing trend at 8 wpi. Additionally, the level of 17 PCs were significantly changed in infected rats. Marked metabolic pathways were involved in clonorchiasis, including glycerophospholipid metabolism, alanine, aspartate and glutamate metabolism, histidine metabolism and pyrimidine metabolism.ConclusionThese results show that C. sinensis infection can cause significant changes in the rat serum metabolism, especially in amino acids and lipids. The metabolic signature together with perturbations in metabolic pathways could provide more in depth understanding of clonorchiasis and further make potential therapeutic interventions

Metabolites Identification of Bioactive Compounds Daturataturin A, Daturametelin I, N-Trans-Feruloyltyramine, and Cannabisin F From the Seeds of Datura metel in Rats

Datura metel L. is a widely used traditional herbal medicine, and withanolides and amides are the two groups of main bioactive constituents in Datura metel seeds. This study aimed to elucidate the metabolism of four representative bioactive compositions containing daturataturin A (1), daturametelin I (2), N-trans-feruloyltyramine (3), and cannabisin F (4) in rats. After separately oral administration of 20 mg/kg withanolides (1, 2) and amides (3, 4) to rats, a total of 12, 24, and 21 metabolites were detected in the plasma, urine, and fecal samples, respectively. Among them, three hydroxylated metabolites, 1-M3, 2-M2, and 3-M5, were detected in plasma and rat liver microsome incubation system in high abundance. Two metabolites of 1 and 2 were unambiguously identified by comparing with reference standards. Particularly, the methylated metabolite 27α-methoxy-(22R)-22,26-epoxy-27-[(β-D-glucopyranosyl)oxy]ergosta-2,4,6,24-tetraene-1,26-dione (daturametelin L) is a new compound. The withanolides could readily get hydroxylation or methylation metabolism. Meanwhile, the phase II metabolism (glucuronidation or sulfation) was the major reaction for the amides. This is the first study on in vivo metabolism of these active compounds in seeds of Datura metel

Comparative analysis of bile metabolic profile in patients with biliary obstruction complicated by Clonorchis sinensis infection

BackgroundClonorchiasis is an important foodborne parasitic disease. However, eggs of Clonorchis sinensis (C. sinensis) cannot be detected in feces during biliary obstruction. Moreover, many diseases can cause biliary obstruction, such as gallstones, adenocarcinoma, cholangiocarcinoma and Ascaris lumbricoides infection. Therefore, it is of great significance to distinguish between patients of biliary obstruction and biliary obstruction with C. sinensis infection.MethodsA total of 48 biliary obstruction patients were enrolled, including 23 infected with C. sinensis (C. sinensis) (OB+C.s) and 25 non-infected subjects (OB). The bile samples were collected by endoscopic retrograde cholangiopancreatography and analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, bile amino acid levels were determined by targeted metabolomics analysis.ResultA total of 146 and 132 significant metabolites were identified in electrospray ionization (ESI)+ and ESI− modes, respectively. The levels of amino acids (asparagine, glutamate, ornithine) and polyamines (spermidine and spermine) were significantly changed. Targeted analysis showed that the levels of amino acids (such as L-arginine, L-glutamine, L-lysine, L-propionic, and L-tyrosine) were lower in OB+C.s patients compared to those in OB patients. Marked metabolic pathways were involved in “Glutathione metabolism”, “Caffeine metabolism”, “Alanine, aspartate and glutamate metabolism”, “Arginine and proline metabolism”, “Purine metabolism”, “Beta-Alanine metabolism”, and “D-glutamine and D-glutamate metabolism”.ConclusionThese results show that there were significant differences between OB+C.s and OB patients, especially in amino acids. The metabolic signature and perturbations in metabolic pathways may help to better distinguish OB+C.s and OB patients