Exploring the therapeutic potential of DV-B-120 as an inhibitor of dengue virus infection.

Dengue fever, an infectious disease prevalent in subtropical and tropical regions, currently lacks effective small-molecule drugs as treatment. In this study, we used a fluorescence peptide cleavage assay to screen seven compounds to assess their inhibition of the dengue virus (DENV) NS2B-NS3 protease. DV-B-120 demonstrated superior inhibition of NS2B-NS3 protease activity and lower toxicity compared to ARDP0006. The selectivity index of DV-B-120 was higher than that of ARDP0006. In vivo assessments of the antiviral efficacy of DV-B-120 against DENV replication demonstrated delayed mortality of suckling mice treated with the compound, with 60-80% protection against life-threatening effects, compared to the outcomes of DENV-infected mice treated with saline. The lower clinical scores of DENV-infected mice treated with DV-B-120 indicated a reduction in acute-progressive illness symptoms, underscoring the potential therapeutic impact of DV-B-120. Investigations of DV-B-120's ability to restore the antiviral type I IFN response in the brain tissue of DENV-infected ICR suckling mice demonstrated its capacity to stimulate IFN and antiviral IFN-stimulated gene expression. DV-B-120 not only significantly delayed DENV-2-induced mortality and illness symptoms but also reduced viral numbers in the brain, ultimately restoring the innate antiviral response. These findings strongly suggest that DV-B-120 holds promise as a therapeutic agent against DENV infection and highlight its potential contribution in addressing the current lack of effective treatments for this infectious disease.IMPORTANCEThe prevalence of dengue virus (DENV) infection in tropical and subtropical regions is escalating due to factors like climate change and mosquito vector expansion. With over 300 million annual infections and potentially fatal outcomes, the urgent need for effective treatments is evident. While the approved Dengvaxia vaccine has variable efficacy, there are currently no antiviral drugs for DENV. This study explores seven compounds targeting the NS2B-NS3 protease, a crucial protein in DENV replication. These compounds exhibit inhibitory effects on DENV-2 NS2B-NS3, holding promise for disrupting viral replication and preventing severe manifestations. However, further research, including animal testing, is imperative to assess therapeutic efficacy and potential toxicity. Developing safe and potent treatments for DENV infection is critical in addressing the rising global health threat posed by this virus.

FGF signalling is involved in cumulus migration in the common house spider Parasteatoda tepidariorum.

Cell migration is a fundamental component during the development of most multicellular organisms. In the early spider embryo, the collective migration of signalling cells, known as the cumulus, is required to set the dorsoventral body axis. Here, we show that FGF signalling plays an important role during cumulus migration in the spider Parasteatoda tepidariorum. Spider embryos with reduced FGF signalling show reduced or absent cumulus migration and display dorsoventral patterning defects. Our study reveals that the transcription factor Ets4 regulates the expression of several FGF signalling components in the cumulus. In conjunction with a previous study, we show that the expression of fgf8 in the germ-disc is regulated via the Hedgehog signalling pathway. We also demonstrate that FGF signalling influences the BMP signalling pathway activity in the region around cumulus cells. Finally, we show that FGFR signalling might also influence cumulus migration in basally branching spiders and we propose that fgf8 might act as a chemo-attractant to guide cumulus cells towards the future dorsal pole of the spider embryo.

Valuing the SF-6Dv2 in the capital of Iran using a discrete choice experiment with duration.

BACKGROUND: The second version of the Short-Form 6-Dimension (SF-6Dv2) classification system has recently been developed. The objective of this study was to develop a value set for SF-6Dv2 based on the societal preferences of a general population in the capital of Iran. METHODS: A representative sample of the capital of Iran (n = 3061) was recruited using a stratified multistage quota sampling technique. Face-to-face interviews were conducted using binary choice sets from the international valuation protocol of the discrete choice experiment with duration. The conditional logit was used to estimate the final value set, and a latent class model was employed to assess heterogeneity of preferences. RESULTS: Coefficients generated from the models were logically consistent and significant. The best model was the one that included an additional interaction term for cases where one or more dimensions reached their most severe levels. It provides a value set with logical consistent coefficients and the lowest percentage of worse than death health states. Predicted values for the SF-6Dv2 were within the range of - 0.796-1. Pain dimension had the largest impact on utility decrement, whereas vitality had the least impact. The presence of preference heterogeneity was evident, and the Bayesian Information Criterion indicated the optimal fit for a latent class model with two classes. CONCLUSION: This study provided the SF-6Dv2 value set for application in the context of Iran. This value set will facilitate the use of the SF-6Dv2 instrument in health economic evaluations and clinical settings.

Cancer population norms using a new value set for the SF-6Dv2 based on the preferences of patients with breast or colorectal cancer in Quebec.

BACKGROUND: Because health resources are limited, health programs should be compared to allow the most efficient ones to emerge. To that aim, health utility instruments have been developed to allow the calculation of quality-adjusted life-year (QALY). However, generic instruments, which can be used by any individual regardless of their health profile, typically consider the preferences of the general population when developing their value set. Consequently, they are often criticized for lacking sensitivity in certain domains, such as cancer. In response, the latest version of the Short Form 6-Dimension (SF-6Dv2) has been adapted to suit the preferences of patients with breast or colorectal cancer in the Canadian province of Quebec. By extension, our study's aim was to determine cancer population norms of utility among patients with breast or colorectal cancer in Quebec using the SF-6Dv2. METHOD: To determine the cancer population norms, we exploited the data that were used in the development of a new value set for the SF-6Dv2. This value set was developed considering the preferences of patients with breast or colorectal cancer. Stratification by time of data collection (i.e., T1 and T2), sociodemographic variables (i.e., age, sex, body mass index, and self-reported health problems affecting quality of life), and clinical aspects (i.e., cancer site, histopathological classification, cancer stage at diagnosis, modality, and treatment characteristics) was performed. RESULTS: In 353 observations, patients were more likely to have negative utility scores at T1 than at T2. Males had higher mean utility scores than females considering type of cancer and comorbidities. Considering the SF-6Dv2's dimensions, more females than males reported having health issues, most which concerned physical functioning. Significant differences by sex surfaced for all dimensions except "Role Limitation" and "Mental health." Patients with multifocal cancer had the highest mean and median utility values in all cancer sites considered. CONCLUSION: Cancer population norms can serve as a baseline for interpreting the scores obtained by a given population in comparison to the situation of another group. In this way, our results can assist in comparing utility scores among cancer patients with different sociodemographic groups to other patients/populations groups. To our knowledge, our identified utility norms are the first for patients with breast or colorectal cancer from Quebec.

Mapping IWQOL-Lite onto EQ-5D-5L and SF-6Dv2 among overweight and obese population in China.

PURPOSE: To develop the mapping functions from the Impact of Weight on Quality of Life-Lite (IWQOL-Lite) scores onto the EQ-5D-5L and SF-6Dv2 utility values among the overweight and obese population in China. METHODS: A representative sample of the overweight and obese population in China stratified by age, sex, body mass index (BMI), and area of residence was collected by online survey and the sample was randomly divided into development (80%) and validation (20%) datasets. The conceptual overlap between the IWQOL-Lite and the EQ-5D-5L or SF-6Dv2 was evaluated by Spearman's correlation coefficients. Five models, including OLS, Tobit, CLAD, GLM, and PTM were explored to derive mapping functions using the development dataset. The model performance was assessed using MAE, RMSE, and the percentage of AE > 0.05 and AE > 0.1 in the validation dataset. RESULTS: A total of 1000 respondents (48% female; mean [SD] age: 51.7 [15.3]; mean [SD] BMI: 27.4 [2.8]) were included in this study. The mean IWQOL-Lite scores and the utility values of EQ-5D-5L and SF-6Dv2 were 78.5, 0.851, and 0.734, respectively. The best-performing models predicting EQ-5D-5L and SF-6Dv2 utilities both used IWQOL-Lite total score as a predictor in the CLAD model (MAE: 0.083 and 0.076 for the EQ-5D-5L and SF-6Dv2; RMSE: 0.125 and 0.103 for the EQ-5D-5L and SF-6Dv2; AE > 0.05: 20.5% and 27.5% for the EQ-5D-5L and SF-6Dv2; AE > 0.10: 9.5% and 15.0% for the EQ-5D-5L and SF-6Dv2). CONCLUSION: CLAD models with the IWQOL-Lite total score can be used to predict both the EQ-5D-5L and SF-6Dv2 utility values among overweight and obese population in China.

Comparison of the measurement properties of the EQ-5D-5L and SF-6Dv2 among overweight and obesity populations in China.

OBJECTIVE: To evaluate and compare the measurement properties of the EQ-5D-5L and SF-6Dv2 among Chinese overweight and obesity populations. METHODS: A representative sample of Chinese overweight and obesity populations was recruited stratified by age, gender, body mass index (BMI), and area of residence. Social-demographic characteristics and self-reported EQ-5D-5L and SF-6Dv2 responses were collected through the online survey. The agreement was assessed using intraclass correlation coefficients (ICC). Convergent validity and known-group validity were examined using Spearman's rank correlation and effect sizes, respectively. The test-retest reliability was assessed using among a subgroup of the total sample. Sensitivity was compared using relative efficiency and receiver operating characteristic. RESULTS: A total of 1000 respondents (52.0% male, mean age 51.7 years, 67.7% overweight, 32.3% obesity) were included in this study. A higher ceiling effect was observed in EQ-5D-5L than in SF-6Dv2 (30.6% vs. 2.1%). The mean (SD) utility was 0.851 (0.195) for EQ-5D-5L and 0.734 (0.164) for SF-6Dv2, with the ICC of the total sample was 0.639 (p < 0.001). The Spearman's rank correlation (range: 0.186-0.739) indicated an acceptable convergent validity between the dimensions of EQ-5D-5L and SF-6Dv2. The EQ-5D-5L showed basically equivalent discriminative capacities with the SF-6Dv2 (ES: 0.517-1.885 vs. 0.383-2.329). The ICC between the two tests were 0.939 for EQ-5D-5L and 0.972 for SF-6Dv2 among the subgroup (N = 150). The SF-6Dv2 had 3.7-170.1% higher efficiency than the EQ-5D-5L at detecting differences in self-reported health status, while the EQ-5D-5L was found to be 16.4% more efficient at distinguishing between respondents with diabetes and non-diabetes. CONCLUSIONS: Both the EQ-5D-5L and SF-6Dv2 showed comparable reliability, validity, and sensitivity when used in Chinese overweight and obesity populations. The two measures may not be interchangeable given the systematic difference in utility values between the EQ-5D-5L and SF-6Dv2. More research is needed to compare the responsiveness.

Psychometric performance of EQ-5D-5L and SF-6DV2 in measuring health status of populations in Chinese university staff and students.

AIMS: To compare measurement properties of EQ-5D-5L and SF-6DV2 in university staff and students in China. METHODS: A total of 291 staff and 183 undergraduates or postgraduates completed the two instruments assigned in a random order. The health utility scores (HUS) of EQ-5D-5L and SF-6DV2 were calculated using the respective value sets for Chinese populations. The agreement of HUSs was examined using intraclass correlation coefficients (ICC) and Bland-Altman plot. Convergent validity of their HUSs and similar dimensions were assessed using Spearman's correlation coefficient. Known-group validity of the HUSs and EQ-VAS score was assessed by comparing the scores of participants with and without three conditions (i.e., disease, symptom or discomfort, and injury), as well as number of any of the three conditions; their sensitivity was also compared. RESULTS: The ICCs between the two HUSs were 0.567 (staff) and 0.553 (students). Bland-Altman plot found that EQ-5D-5L HUSs were generally higher. Strong correlation was detected for two similar dimensions (pain/discomfort of EQ-5D-5L and pain of SF-6DV2; anxiety/depression of EQ-5D-5L and mental health of SF-6DV2) in both samples. The correlation between the two HUSs were strong (0.692 for staff and 0.703 for students), and were stronger than their correlations with EQ-VAS score. All the three scores could discriminate the difference in three known-groups (disease, symptom or discomfort, number of any of the three conditions). The two HUSs were more sensitive than EQ-VAS score; and either of them was not superior than the other. CONCLUSIONS: Both EQ-5D-5L and SF-6DV2 HUSs have acceptable measurement properties (convergent validity, known-groups validity, sensitivity) in Chinese university staff and students. Nevetheless, only EQ-5D-5L (PD and AD) and SF-6DV2 (PN and MH) showed indicated good convergent validity as expected. Two types of HUSs cannot be used interchangeably, and each has its own advantages in sensitivity.

Enhancing Localization Efficiency and Accuracy in Wireless Sensor Networks.

Accuracy is the vital indicator in location estimation used in many scenarios, such as warehousing, tracking, monitoring, security surveillance, etc., in a wireless sensor network (WSN). The conventional range-free DV-Hop algorithm uses hop distance to estimate sensor node positions but has limitations in terms of accuracy. To address the issues of low accuracy and high energy consumption of DV-Hop-based localization in static WSNs, this paper proposes an enhanced DV-Hop algorithm for efficient and accurate localization with reduced energy consumption. The proposed method consists of three steps: first, the single-hop distance is corrected using the RSSI value for a specific radius; second, the average hop distance between unknown nodes and anchors is modified based on the difference between actual and estimated distances; and finally, the least-squares approach is used to estimate the location of each unknown node. The proposed algorithm, named Hop-correction and energy-efficient DV-Hop (HCEDV-Hop), is executed and evaluated in MATLAB to compare its performance with benchmark schemes. The results show that HCEDV-Hop improves localization accuracy by an average of 81.36%, 77.99%, 39.72%, and 9.96% compared to basic DV-Hop, WCL, improved DV-maxHop, and improved DV-Hop, respectively. In terms of message communication, the proposed algorithm reduces energy usage by 28% compared to DV-Hop and 17% compared to WCL.

A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks.

Wireless sensor networks (WSNs) are applied in many fields, among which node localization is one of the most important parts. The Distance Vector-Hop (DV-Hop) algorithm is the most widely used range-free localization algorithm, but its localization accuracy is not high enough. In this paper, to solve this problem, a hybrid localization algorithm for an adaptive strategy-based distance vector-hop and improved sparrow search is proposed (HADSS). First, an adaptive hop count strategy is designed to refine the hop count between all sensor nodes, using a hop count correction factor for secondary correction. Compared with the simple method of using multiple communication radii, this mechanism can refine the hop counts between nodes and reduce the error, as well as the communication overhead. Second, the average hop distance of the anchor nodes is calculated using the mean square error criterion. Then, the average hop distance obtained from the unknown nodes is corrected according to a combination of the anchor node trust degree and the weighting method. Compared with the single weighting method, both the global information about the network and the local information about each anchor node are taken into account, which reduces the average hop distance errors. Simulation experiments are conducted to verify the localization performance of the proposed HADSS algorithm by considering the normalized localization error. The simulation results show that the accuracy of the proposed HADSS algorithm is much higher than that of five existing methods.

DV-Hop Algorithm Based on Multi-Objective Salp Swarm Algorithm Optimization.

The localization of sensor nodes is an important problem in wireless sensor networks. The DV-Hop algorithm is a typical range-free algorithm, but the localization accuracy is not high. To further improve the localization accuracy, this paper designs a DV-Hop algorithm based on multi-objective salp swarm optimization. Firstly, hop counts in the DV-Hop algorithm are subdivided, and the average hop distance is corrected based on the minimum mean-square error criterion and weighting. Secondly, the traditional single-objective optimization model is transformed into a multi-objective optimization model. Then, in the third stage of DV-Hop, the improved multi-objective salp swarm algorithm is used to estimate the node coordinates. Finally, the proposed algorithm is compared with three improved DV-Hop algorithms in two topologies. Compared with DV-Hop, The localization errors of the proposed algorithm are reduced by 50.79% and 56.79% in the two topology environments with different communication radii. The localization errors of different node numbers are decreased by 38.27% and 56.79%. The maximum reductions in localization errors are 38.44% and 56.79% for different anchor node numbers. Based on different regions, the maximum reductions in localization errors are 56.75% and 56.79%. The simulation results show that the accuracy of the proposed algorithm is better than that of DV-Hop, GWO-DV-Hop, SSA-DV-Hop, and ISSA-DV-Hop algorithms.

Measuring Up: A Comparison of TapeStation 4200 and Bioanalyzer 2100 as Measurement Tools for RNA Quality in Postmortem Human Brain Samples.

The determination of RNA integrity is a critical quality assessment tool for gene expression studies where the experiment's success is highly dependent on the sample quality. Since its introduction in 1999, the gold standard in the scientific community has been the Agilent 2100 Bioanalyzer's RNA integrity number (RIN), which uses a 1-10 value system, from 1 being the most degraded, to 10 being the most intact. In 2015, Agilent launched 4200 TapeStation's RIN equivalent, and reported a strong correlation of r2 of 0.936 and a median error < ±0.4 RIN units. To evaluate this claim, we compared the Agilent 4200 TapeStation's RIN equivalent (RINe) and DV200 to the Agilent 2100 Bioanalyzer's RIN for 183 parallel RNA samples. In our study, using RNA from a total of 183 human postmortem brain samples, we found that the RIN and RINe values only weakly correlate, with an r2 of 0.393 and an average difference of 3.2 RIN units. DV200 also only weakly correlated with RIN (r2 of 0.182) and RINe (r2 of 0.347). Finally, when applying a cut-off value of 6.5 for both metrics, we found that 95.6% of samples passed with RIN, while only 23.5% passed with RINe. Our results suggest that even though RIN (Bioanalyzer) and RINe (TapeStation) use the same 1-10 value system, they should not be used interchangeably, and cut-off values should be calculated independently.

Capital, change and Elsie's Place: Understanding the history of safe accommodation in Australia.

Gendered violence, specifically, domestic violence, continues to be a global issue impacting the health and well-being of women despite the improvements to women's rights and the expansion of women's health and well-being services in the 1970s. While considerable attention has been given to this period of time, scant attention has been given to understanding the resources and change processes involved in the opening of Australia's feminist-led women's health and wellbeing services from a theoretical perspective. During a Visiting Scholar appointment at the State Library of New South Wales, Sydney, Australia I undertook a review of historical documentation and academic literature search pertaining to the opening of Australia's first feminist-led safe accommodation for women fleeing domestic violence: Elsie's Place. The concepts of Bourdieu (1977) Theory of Practice informed my understanding of resources, while Lewin (1947) Change Theory provided a conceptual lens through which to view change within the textual and graphical documents. The findings from this project point to the importance of capital, particularly social capital, in the forms of cooperation, collaboration, and networking, in the supporting of change within this sector during the opening of foundational services for women in Australia.

Mapping the Food Allergy Quality of Life Questionnaire Parent Form onto the Short-Form Six-Dimensions version 2.

BACKGROUND: The Food Allergy Quality of Life Questionnaire Parent Form (FAQLQ-PF) is the most widely used quality of life questionnaire in food allergy. The objective of this study was to develop a mapping algorithm to convert FAQLQ-PF scores into health state utilities. METHODS: The Short-Form Six-Dimensions version 2 (SF-6Dv2) and FAQLQ-PF questionnaires were collected from an academic center oral immunotherapy referral cohort. Utility estimates were derived from the SF-6Dv2 using the food allergy preference set. Candidate mapping algorithm models were developed using seven regression methods starting from either the total average score, the average scores of each of the three domains or the individual item scores of FAQLQ-PF. The process was repeated twice, including only section A, common to all age groups, or including all age-applicable sections of the FAQLQ-PF. The mean absolute error (MAE) and root mean squared error (RMSE) were used to select the best fitting model. An independent cohort from a previous national online survey was used for external validation. RESULTS: In the index cohort, 1000 of 1257 respondents had completed both questionnaires. The lowest MAE (0.0791) and RMSE (0.1020) were recorded when entering individual item scores in a categorical regression model. The model including only FAQLQ-PF section A was found to be most consistent when tested in the external validation cohort (n = 248) (MAE of 0.0898). CONCLUSION: The FAQLQ-PF was mapped onto SF-6Dv2 utilities with good predictive accuracy in two independent cohorts. This will enable calculation of health utility for cost-effectiveness analyses in food allergy.

Deciding Between SF-6Dv2 Health States: A Think-Aloud Study of Decision-Making Strategies Used in Discrete Choice Experiments.

OBJECTIVE: This study aimed to gain insight into decision-making strategies individuals used when evaluating pairs of SF-6Dv2 health states in discrete choice experiments (DCEs). METHODS: This qualitative, cross-sectional, noninterventional study asked participants to use a think-aloud approach to compare SF-6Dv2 health states in DCEs. Thematic analysis focused on comprehension and cognitive strategies used to compare health states and make decisions. RESULTS: Participants (N = 40) used 3 main strategies when completing DCEs: (1) trading, (2) reinterpretation, and (3) relying on previous experience. Trading was the most common strategy, used by everyone at least once, and involved prioritizing key attributes, such as preferring a health state with significant depression but no bodily pain. Reinterpretation was used by 17 participants and involved reconstructing health states by changing underlying assumptions (eg, rationalizing selecting a health state with significant pain because they could take pain medications). Finally, some (n = 13) relied on previous experience when making decisions on some choice tasks. Participants with experience dealing with pain, for instance, prioritized health states with the least impact in this dimension. CONCLUSIONS: Qualitatively evaluating the decision-making strategies used in DCEs allows researchers to evaluate whether the tasks and attributes are interpreted accurately. The findings from this study add to the understanding of the generation of SF-6Dv2 health utility weights and the validity of these weights (e.g., reinterpreting health states could undermine the validity of DCEs and utility weights), and the overall usefulness of the SF-6Dv2. The methodology described in this study can and should be carried forth in valuing other health utility measures, not just the SF-6Dv2.

Mapping the Minnesota Living with Heart Failure Questionnaire (MLHFQ) to SF-6Dv2 in Chinese patients with heart failure.

PURPOSE: Mapping the Minnesota Living with Heart Failure Questionnaire (MLHFQ) to SF-6Dv2 in Chinese patients with chronic heart failure, and to obtain the health utility value for health economic assessment. METHODS: Four statistical algorithms, including ordinary least square method (OLS), Tobit model, robust MM estimator (MM) and censored least absolute deviations (CLAD), were used to establish the alternative model. Models were validated by using a tenfold cross-validation technique. The mean absolute error (MAE) and root mean square error (RMSE) were used to evaluate the prediction performance of the model. The Spearman correlation coefficient and Intraclass Correlation Coefficients (ICC) were used to examine the relationship between the predicted and observed SF-6Dv2 values. RESULTS: A total of 195 patients with chronic heart failure were recruited from 3 general hospitals in Beijing. The MLHFQ summary score and domain scores of the study sample were negatively correlated with SF-6Dv2 health utility value. The OLS regression model established based on the MLHFQ domain scores was the optimal fitting model and the predicted value was highly positively correlated with the observed value. CONCLUSION: The MLHFQ can be mapped to SF-6Dv2 by OLS, which can be used for health economic assessment of cardiovascular diseases such as chronic heart failure.

Comparison of the measurement properties of SF-6Dv2 and EQ-5D-5L in a Chinese population health survey.

BACKGROUND: SF-6Dv2, the latest version of SF-6D, has been developed recently, and its measurement properties remain to be evaluated and compared with the EQ-5D-5L. The aim of this study was to assess and compare the measurement properties of the SF-6Dv2 and the EQ-5D-5L in a large-sample health survey among the Chinese population. METHODS: Data were obtained from the 2020 Health Service Survey in Tianjin, China. Respondents were randomly selected and invited to complete both the EQ-5D-5L and SF-6Dv2 through face-to-face interviews or self-administration. Health utility values were calculated by the Chinese value sets for the two measures. Ceiling and floor effects were firstly evaluated. Convergent validity and discriminate validity were examined using Spearman's rank correlation and effect sizes, respectively. The agreement was assessed using intraclass correlation coefficients (ICC). Sensitivity was compared using relative efficiency and receiver operating characteristic. RESULTS: Among 19,177 respondents (49.3% male, mean age 55.2 years, ranged 18-102 years) included in this study, the mean utility was 0.939 (0.168) for EQ-5D-5L and 0.872 (0.184) for SF-6Dv2. A higher ceiling effect was observed in EQ-5D-5L than in SF-6Dv2 (72.8% vs. 36.1%). The Spearman's rank correlation (range: 0.30-0.69) indicated an acceptable convergent validity between the dimensions of EQ-5D-5L and SF-6Dv2. The SF-6Dv2 showed slightly better discriminative capacities than the EQ-5D-5L (ES: 0.126-2.675 vs. 0.061-2.256). The ICC between the EQ-5D-5L and SF-6Dv2 utility values of the total sample was 0.780 (p < 0.05). The SF-6Dv2 had 29.0-179.2% higher efficiency than the EQ-5D-5L at distinguishing between respondents with different external health indicators, while the EQ-5D-5L was found to be 8.2% more efficient at detecting differences in self-reported health status than the SF-6Dv2. CONCLUSIONS: Both the SF-6Dv2 and EQ-5D-5L have been demonstrated to be comparably valid and sensitive when used in Chinese population health surveys. The two measures may not be interchangeable given the moderate ICC and the systematic difference in utility values between the SF-6Dv2 and EQ-5D-5L. Further research is warranted to compare the test-retest reliability and responsiveness.

Chiral organic stereochemistry: Chiral HPLC, chiral auxiliaries, CD spectroscopy, X-ray crystallography, and light-powered chiral molecular motors.

In the studies of chiral organic stereochemistry, it is important to use enantiopure compounds. For this purpose, the chiral HPLC (High-Pressure Liquid Chromatography) columns containing chiral stationary phases were invented by Y. Okamoto and coworkers for enantio-separating various racemic compounds. In addition, the use of chiral auxiliaries is also useful for preparing enantiopure compounds and also for determining their absolute configurations, where covalent-bonded diastereomers are separated by HPLC on silica gel. In this review article, these HPLC methods will be discussed together with the applications to some interesting organic compounds including light-powered chiral molecular motors.

Ventilation indices for evaluation of airborne infection risk control performance of air distribution.

Air distribution is an effective engineering measure to fight against respiratory infectious diseases like COVID-19. Ventilation indices are widely used to indicate the airborne infection risk of respiratory infectious diseases due to the practical convenience. This study investigates the relationships between the ventilation indices and airborne infection risk to suggest the proper ventilation indices for the evaluation of airborne infection risk control performance of air distribution. Besides the commonly used ventilation indices of the age of air (AoA), air change effectiveness (ACE), and contaminant removal effectiveness (CRE), this study introduces two ventilation indices, i.e., the air utilization effectiveness (AUE) and contaminant dispersion index (CDI). CFD simulations of a hospital ward and a classroom served by different air distributions, including mixing ventilation, displacement ventilation, stratum ventilation and downward ventilation, are validated to calculate the ventilation indices and airborne infection risk. A three-step correlation analysis based on Spearman's rank correlation coefficient, Pearson correlation coefficient, and goodness of fit and a min-max normalization-based error analysis are developed to qualitatively and quantitatively test the validity of ventilation indices respectively. The results recommend the integrated index of AUE and CDI to indicate the overall airborne infection risk, and CDI to indicate the local airborne infection risk respectively regardless of the effects of air distribution, supply airflow rate, infectivity intensity, room configuration and occupant distribution. This study contributes to airborne transmission control of infectious respiratory diseases with air distribution.

C-type lectins and extracellular vesicles in virus-induced NETosis.

Dysregulated formation of neutrophil extracellular traps (NETs) is observed in acute viral infections. Moreover, NETs contribute to the pathogenesis of acute viral infections, including those caused by the dengue virus (DV) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Furthermore, excessive NET formation (NETosis) is associated with disease severity in patients suffering from SARS-CoV-2-induced multiple organ injuries. Dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN) and other members of C-type lectin family (L-SIGN, LSECtin, CLEC10A) have been reported to interact with viral glycans to facilitate virus spreading and exacerbates inflammatory reactions. Moreover, spleen tyrosine kinase (Syk)-coupled C-type lectin member 5A (CLEC5A) has been shown as the pattern recognition receptor for members of flaviviruses, and is responsible for DV-induced cytokine storm and Japanese encephalomyelitis virus (JEV)-induced neuronal inflammation. Moreover, DV activates platelets via CLEC2 to release extracellular vesicles (EVs), including microvesicles (MVs) and exosomes (EXOs). The DV-activated EXOs (DV-EXOs) and MVs (DV-MVs) stimulate CLEC5A and Toll-like receptor 2 (TLR2), respectively, to enhance NET formation and inflammatory reactions. Thus, EVs from virus-activated platelets (PLT-EVs) are potent endogenous danger signals, and blockade of C-type lectins is a promising strategy to attenuate virus-induced NETosis and intravascular coagulopathy.

Research on Location Algorithm Based on Beacon Filtering Combining DV-Hop and Multidimensional Support Vector Regression.

The DV-Hop algorithm is widely used because of its simplicity and low cost, but it has the disadvantage of a large positioning error. In recent years, although some improvement measures have been proposed, such as hop correction, distance-weighted correction, and improved coordinate solution, there is room for improvement in location accuracy, and the accuracy is affected in anisotropic networks. A location algorithm based on beacon filtering combining DV-Hop and multidimensional support vector regression (MSVR) is proposed in this paper. In the process of estimating the coordinates of unknown nodes, received signal strength indication (RSSI), MSVR, and weighted least squares method are combined. In addition, the verification error of beacon nodes is proposed, which can select the beacon nodes with smaller errors to reduce the location error. Simulation results show that in different distributions, the location accuracy of the proposed algorithm is at least 34% higher than that of the classical DV-Hop algorithm and at least 28% higher than that of the localization based on multidimensional support vector regression (LMSVR) algorithm. The proposed algorithm has the potential of application in small-scale anisotropic networks.