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Abstract The RAB interacting factor (RABIF) is a putative guanine nucleotide exchange factor that also functions as a RAB-stabilizing holdase chaperone. It has been implicated in pathogenesis of several cancers. However, the functional role and molecular mechanism of RABIF in hepatocellular carcinoma (HCC) are not entirely known. Here, we demonstrate an upregulation of RABIF in patients with HCC, correlating with a poor prognosis. RABIF inhibition results in decreased HCC cell growth both in vitro and in vivo. Our study reveals that depleting RABIF attenuates the STOML2-PARL-PGAM5 axis-mediated mitophagy. Consequently, this reduction in mitophagy results in diminished mitochondrial reactive oxygen species (mitoROS) production, thereby alleviating the HIF1α-mediated downregulation of glycolytic genes HK1, HKDC1, and LDHB. Additionally, we illustrate that RABIF regulates glucose uptake by controlling RAB10 expression. Importantly, the knockout of RABIF or blockade of mitophagy sensitizes HCC cells to sorafenib. This study uncovers a previously unrecognized role of RABIF crucial for HCC growth and identifies it as a potential therapeutic target.

Abstract Light‐harvesting is of vital importance for many events, such as photosynthesis. To efficiently gather and transfer solar energy, delicate antenna is needed, which has been achieved by algae and plants. However, construction of efficient light‐harvesting systems using multiple, artificial building blocks is still challenging. Here, blue‐emitting organosilicone capsules containing carbon dots (denoted as CDs‐Si) in ethanol are prepared, which can effectively transfer energy to green‐emitting (silicone‐functionalized bodipy, Si‐BODIPY) or red‐emitting (rhodamine b, RhB) dyes. In ternary system, sequential Förster resonance energy transfer from CDs‐Si to Si‐BODIPY and further to RhB is realized, which is accompanied with a less pronounced, parallel FRET directly from CDs‐Si to RhB. The overall efficiency of energy transfer reaches ≈86%. By introducing a photoswitch (1,2‐bis(2,4‐dimethyl‐5‐phenyl‐3‐thienyl)‐3,3,4,4,5,5‐hexafluoro‐1‐cyclopentene, DAE) to the system, the emission becomes switchable under alternative illumination with UV and visible light, leading to the formation of smart artificial light‐harvesting systems.

This research presents the design, manufacturing, and macroscopic characterization of flexible mechanical metamaterials with tunable elastic properties. The elastic constants were given using the energy principle and Castigliano's second theorem, and the results were validated through static simulations and tensile experiments, showing good agreement. Then the complete parametric study was conducted to demonstrate the possibility of extensively customizing the Poisson effect and stiffness. Additionally, the comparison between the developed metamaterials and star-shaped cellular structures on the mechanical properties was conducted using six groups of samples. The results demonstrated that the developed metamaterials exhibited remarkable superiority in deformability, sensitivity, and auxeticity. Furthermore, an innovative experiment is devised to characterize the mechanical responses of the developed coupling metamaterials system complemented with numerical modeling, the similar phenomenon was also observed in other metamaterials. The proposed design offered a way to induce the metamaterials system’s profile occurring the wavy deformation.

ObjectiveThis study focuses on enhancing the precision of epidemic time series data prediction by integrating Gated Recurrent Unit (GRU) into a Graph Neural Network (GNN), forming the GRGNN. The accuracy of the GNN (Graph Neural Network) network with introduced GRU (Gated Recurrent Units) is validated by comparing it with seven commonly used prediction methods.MethodThe GRGNN methodology involves multivariate time series prediction using a GNN (Graph Neural Network) network improved by the integration of GRU (Gated Recurrent Units). Additionally, Graphical Fourier Transform (GFT) and Discrete Fourier Transform (DFT) are introduced. GFT captures inter-sequence correlations in the spectral domain, while DFT transforms data from the time domain to the frequency domain, revealing temporal node correlations. Following GFT and DFT, outbreak data are predicted through one-dimensional convolution and gated linear regression in the frequency domain, graph convolution in the spectral domain, and GRU (Gated Recurrent Units) in the time domain. The inverse transformation of GFT and DFT is employed, and final predictions are obtained after passing through a fully connected layer. Evaluation is conducted on three datasets: the COVID-19 datasets of 38 African countries and 42 European countries from worldometers, and the chickenpox dataset of 20 Hungarian regions from Kaggle. Metrics include Average Root Mean Square Error (ARMSE) and Average Mean Absolute Error (AMAE).ResultFor African COVID-19 dataset and Hungarian Chickenpox dataset, GRGNN consistently outperforms other methods in ARMSE and AMAE across various prediction step lengths. Optimal results are achieved even at extended prediction steps, highlighting the model’s robustness.ConclusionGRGNN proves effective in predicting epidemic time series data with high accuracy, demonstrating its potential in epidemic surveillance and early warning applications. However, further discussions and studies are warranted to refine its application and judgment methods, emphasizing the ongoing need for exploration and research in this domain.

Abstract Human papillomavirus (HPV) infection poses a significant threat to public health worldwide. Targeting the function of HPV E6 and E7 proteins and activating the host immune response against these proteins represent promising therapeutic strategies for combating HPV-related diseases. Consequently, the efficient production of soluble, high-purity E6 and E7 proteins is crucial for function and host immune response studies. In this context, we selected the pMCSG19 protein expression vector for Escherichia coli to produce soluble MBP-His6 tagged HPV11/16 E6/E7 proteins, achieving relatively high purity and yield. Notably, these proteins exhibited low toxicity to peripheral blood mononuclear cells (PBMCs) and did not compromise their viability. Additionally, the recombinant proteins were capable of inducing the secretion of multiple cytokines by immune cells in peripheral blood, indicating their potential to elicit immune responses. In conclusion, our study offers a novel approach for the production of HPV11/16 E6/E7 fusion proteins with relatively high purity and yield. The fusing HPV11/16 E6/E7 proteins to MBP-His6 tag may serve as a valuable method for large-scale protein production in future research endeavors.

Abstract The conventional star-shaped honeycomb (CSSH) structure is inherently rich in mechanical properties. Based on the CSSH structure, the Poisson's ratio and Young’s modulus can be improved by adding the tip re-entrant angle (ISSH). In this paper, a new concave four-arc honeycomb (CFAH) structure is proposed by designing the straight rod as a curved rod and retaining the tip re-entrant angle from the ISSH structure. The Young's modulus, specific stiffness and Poisson’s ratio of CFAH structures are derived from Castigliano’s second theorem and Moore’s theorem. The theoretical results show good agreement with the numerical and experimental results. The results show that the normalized effective specific stiffness and normalized effective Young’s modulus of the CFAH structure are further improved by about 12.95% and 16.86%, respectively, compared with the ISSH structure, and more significant auxiliary effects are obtained. CFAH structures show good promise in aerospace, construction and other applications due to their enhanced mechanical property. Meanwhile, the present work provides guidance for the study of concave four-arc honeycomb structures.

Soil salinization significantly impacts the ecological environment and agricultural production, posing a threat to plant growth. Currently, there are over 400 varieties of Bougainvillea with horticultural value internationally. However, research on the differences in salt tolerance among Bougainvillea varieties is still insufficient. Therefore, this study aims to investigate the physiological responses and tolerance differences of various Bougainvillea varieties under different concentrations of salt stress, reveal the effects of salt stress on their growth and physiology, and study the adaptation mechanisms of these varieties related to salt stress. The experimental materials consisted of five varieties of Bougainvillea. Based on the actual salinity concentrations in natural saline-alkali soils, we used a pot-controlled salt method for the experiment, with four treatment concentrations set: 0.0% (w/v) (CK), 0.2% (w/v), 0.4% (w/v), and 0.6% (w/v). After the Bougainvillea plants grew stably, salt stress was applied and the growth, physiology, and salt tolerance of the one-year-old plants were systematically measured and assessed. The key findings were as follows: Salt stress inhibited the growth and biomass of the five varieties of Bougainvillea; the ‘Dayezi’ variety showed severe salt damage, while the ‘Shuihong’ variety exhibited minimal response. As the salt concentration and duration of salt stress increase, the trends of the changes in antioxidant enzyme activity and osmotic regulation systems in the leaves of the five Bougainvillea species differ. Membrane permeability and the production of membrane oxidative products showed an upward trend with stress severity. The salt tolerance of the five varieties of Bougainvillea was comprehensively evaluated through principal component analysis. It was found that the ‘Shuihong’ variety exhibited the highest salt tolerance, followed by the ‘Lvyehuanghua’, ‘Xiaoyezi’, ‘Tazi’, and ‘Dayezi’ varieties. Therefore, Bougainvillea ‘Shuihong’, ‘Lvyehuanghua’, and ‘Xiaoyezi’ are recommended for extensive cultivation in saline-alkali areas. The investigation focuses primarily on how Bougainvillea varieties respond to salt stress from the perspectives of growth and physiological levels. Future research could explore the molecular mechanisms behind the responses to and tolerance of different Bougainvillea varieties as to salt stress, providing a more comprehensive understanding and basis for practical applications.

Objective To explore the role of urinary osteopontin (uOPN) in predicting clinical responses to induction therapy and renal prognosis in adults with lupus nephritis (LN). Methods A total of 53 type Ⅲ/Ⅳ LN adults were recruited. At the same time, 24 healthy volunteers visiting our hospital for physical examination in the same period were selected as healthy control group. Levels of uOPN were determined by enzyme-linked immunosorbent assay (ELISA). Renal biopsies were performed at baseline and after induction therapy. According to the criteria of American College of Rheumatology (ACR), they were divided into two groups of clinical response or non-response. Patients with ≥50% improvement in renal activity index scores were selected as histological response group. Results Baseline and post-treatment levels of uOPN were significantly higher in LN patients than those in healthy controls [2.33(1.84, 2.83)mg/L, 2.07(1.55, 2.72)mg/L vs 0.94(0.70, 1.46)mg/L](P0.05). Multivariate Logistic regression analysis revealed that baseline uOPN was an independent predictor of histological response to LN induction therapy (P

Abstract Small RNAs (sRNAs) within 15-30 nt such as miRNA, tsRNA, srRNA with 3’-OH have been identified. However, whether these sRNAs are the major 15-30 nt sRNAs is still unknown. Here we show about 90% mammalian sRNAs within 15-30 nt end with 2’,3’-cyclic phosphate (3’-cP). TANT-seq was developed to simultaneously profile sRNAs with 3’-cP (sRNA-cPs) and sRNA-OHs, and huge amount of sRNA-cPs were detected. Surprisingly, sRNA-cPs and sRNA-OHs usually have distinct sequences. The data from TANT-seq were validated by a novel method termed TE-qPCR, and Northern blot. Furthermore, we found that Angiogenin and RNase 4 contribute to the biogenesis of sRNA-cPs. Moreover, much more sRNA-cPs than sRNA-OHs bind to Ago2, and can regulate gene expression. Particularly, snR-2-cP regulates Bcl2 by targeting to its 3’UTR dependent on Ago2, and subsequently regulates apoptosis. In addition, sRNA-cPs can guide the cleavage of target RNAs in Ago2 complex as miRNAs without the requirement of 3’-cP. Our discovery greatly expands the repertoire of mammalian sRNAs, and provides strategies and powerful tools towards further investigation of sRNA-cPs.

Abstract Background Children under five are the vulnerable population most at risk of being infected with Plasmodium parasites, especially in the Sahel region. Seasonal malaria chemoprevention (SMC) recommended by World Health Organization (WHO), has proven to be a highly effective intervention to prevent malaria. Given more deaths reported during the COVID-19 pandemic than in previous years due to the disruptions to essential medical services, it is, therefore, necessary to seek a more coordinated and integrated approach to increasing the pace, coverage and resilience of SMC. Towards this end, fully leverage the resources of major players in the global fight against malaria, such as China could accelerate the SMC process in Africa. Methods We searched PubMed, MEDLINE, Web of Science, and Embase for research articles and the Institutional Repository for Information Sharing of WHO for reports on SMC. We used gap analysis to investigate the challenges and gaps of SMC since COVID-19. Through the above methods to explore China’s prospective contribution to SMC. Results A total of 68 research articles and reports were found. Through gap analysis, we found that despite the delays in the SMC campaign, 11.8 million children received SMC in 2020. However, there remained some challenges: (1) a shortage of fully covered monthly courses; (2) lack of adherence to the second and third doses of amodiaquine; (3) four courses of SMC are not sufficient to cover the entire malaria transmission season in areas where the peak transmission lasts longer; (4) additional interventions are needed to consolidate SMC efforts. China was certified malaria-free by WHO in 2021, and its experience and expertise in malaria elimination can be shared with high-burden countries. With the potential to join the multilateral cooperation in SMC, including the supply of quality-assured health commodities, know-how transfer and experience sharing, China is expected to contribute to the ongoing scale-up of SMC. Conclusions A combination of necessary preventive and curative activities may prove beneficial both for targeted populations and for health system strengthening in the long run. More actions are entailed to promote the partnership and China can be one of the main contributors with various roles.

Abstract Background Anti-NMDA receptor (NMDAR) encephalitis is an autoimmune disease characterized by complex neuropsychiatric syndrome and cerebrospinal fluid (CSF) NMDAR antibodies. Triggering receptor expressed on myeloid cells 2 (TREM2) has been reported to be associated with inflammation of the central nervous system (CNS). Matrix metalloproteinase-9 (MMP9) and cluster of differentiation (CD44) were measured to evaluate blood‒brain barrier (BBB) permeability in anti-NMDAR encephalitis. The roles of microglial activation and BBB disruption in anti-NMDAR encephalitis are not well known. Findings In this work, we detected increased expression levels of CSF sTREM2, CSF and serum CD44, and serum MMP9 in anti-NMDAR encephalitis patients compared with controls. CSF sTREM2 levels were positively related to both CSF CD44 levels (r = 0.702, p

Abstract Obesity and diabetes are risk factors for hepatocellular carcinoma (HCC); however, the underlying mechanisms are yet to be elucidated. Adeno‐associated virus (AAV) frequently infects humans and has been widely used in gene therapy, but the risk of AAV infection such as HCC should be further evaluated. Here, we show that recombinant AAV injection caused liver injury, hepatic necroptosis, and HCC in db/db or high‐fat diet‐induced hyperglycemic and obese mice, but not in mice with only hyperglycemia or obesity. Prednisone administration or knockdown of Pebp1, highly expressed in db/db mice, alleviated hepatic injury and necroptosis induced by recombinant AAV in mice with diabetes and obesity. Inhibition of Pebp1 pathway also attenuated inflammation and necroptosis in vitro. Our findings show that AAV infection is a critical risk factor for HCC in patients with diabetes and obesity, and AAV gene therapy for these patients should be carefully evaluated. Both prednisone treatment and targeting Pebp1 pathway are promising strategies to alleviate inflammation and necroptosis that occurred in AAV gene therapy or related diseases.

Several configurations of the Canadian Precipitation Analysis system (CaPA) currently produce precipitation analyses at Environment and Climate Change Canada (ECCC). To improve CaPA’s performance during the winter season, the impact of assimilating the IMERG V06 product (IMERG: Integrated Multi-satellitE Retrievals for GPM—Global Precipitation Measurement mission) into CaPA is examined in this study. Tests are conducted with CaPA’s 10 km deterministic version, evaluated over Canada and the northern part of the United States (USA). Maps from a case study show that IMERG plays a contradictory role in the production of CaPA’s precipitation analyses for a synoptic-scale winter storm over North America’s eastern coast. While its contribution appears to be physically correct over southern portions of the meteorological system, and early in its intensification phase, IMERG displays unrealistic spatial structures over land later in the system’s life cycle when it is located over northern (colder) areas. Objective evaluation of CaPA’s analyses when IMERG is assimilated without any restrictions shows an overall decrease in precipitation, which has a mixed effect (positive and negative) on the bias indicators. But IMERG’s influence on the Equitable Threat Score (ETS), a measure of CaPA’s analyses accuracy, is clearly negative. Using IMERG’s quality index (QI) to filter out areas where it is less accurate improves CaPA’s objective evaluation, leading to better ETS versus the control experiment in which no IMERG data are assimilated. Several diagnostics provide insight into the nature of IMERG’s contribution to CaPA. For the most successful configuration, with a QI threshold of 0.3, IMERG’s impact is mostly found in the warmer parts of the domain, i.e., in northern US states and in British Columbia. Spatial means of the temporal sums of absolute differences between CaPA’s analyses with and without IMERG indicate that this product also contributes meaningfully over land areas covered by snow, and areas where air temperature is below −2 °C (where precipitation is assumed to be in solid phase).

Abstract Objective Compared with other regions in the world, the transmission characteristics of the COVID-19 epidemic in Africa are more obvious, has a unique transmission mode in this region; At the same time, the data related to the COVID-19 epidemic in Africa is characterized by low data quality and incomplete data coverage, which makes the prediction method of COVID-19 epidemic suitable for other regions unable to achieve good results in Africa. In order to solve the above problems, this paper proposes a prediction method that nests the in-depth learning method in the mechanism model. From the experimental results, it can better solve the above problems and better adapt to the transmission characteristics of the COVID-19 epidemic in African countries. Methods Based on the SIRV model, the COVID-19 transmission rate and trend from September 2021 to January 2022 of the top 15 African countries (South Africa, Morocco, Tunisia, Libya, Egypt, Ethiopia, Kenya, Zambia, Algeria, Botswana, Nigeria, Zimbabwe, Mozambique, Uganda, and Ghana) in the accumulative number of COVID-19 confirmed cases was fitted by using the data from Worldometer. Non-autoregressive (NAR), Long-short term memory (LSTM), Autoregressive integrated moving average (ARIMA) models, Gaussian and polynomial functions were used to predict the transmission rate β in the next 7, 14, and 21 days. Then, the predicted transmission rate βs were substituted into the SIRV model to predict the number of the COVID-19 active cases. The error analysis was conducted using root-mean-square error (RMSE) and mean absolute percentage error (MAPE). Results The fitting curves of the 7, 14, and 21 days were consistent with and higher than the original curves of daily active cases (DAC). The MAPE between the fitted and original 7-day DAC was only 1.15% and increased with the longer of predict days. Both the predicted β and DAC of the next 7, 14, and 21 days by NAR and LSTM nested models were closer to the real ones than other three ones. The minimum RMSEs for the predicted number of COVID-19 active cases in the next 7, 14, and 21 days were 12,974, 14,152, and 12,211 people, respectively when the order of magnitude for was 106, with the minimum MAPE being 1.79%, 1.97%, and 1.64%, respectively. Conclusion Nesting the SIRV model with NAR, LSTM, ARIMA methods etc. through functionalizing β respectively could obtain more accurate fitting and predicting results than these models/methods alone for the number of confirmed COVID-19 cases in Africa in which nesting with NAR had the highest accuracy for the 14-day and 21-day predictions. The nested model was of high significance for early understanding of the COVID-19 disease burden and preparedness for the response.

Abstract The concept design evaluation phase of the new product launch is extremely important. However, current evaluation information relies mainly on the a priori knowledge of decision makers and is subjective and ambiguous. For this reason, a conceptual design solution decision model based on Pythagorean fuzzy sets in a big data environment is proposed. Firstly, we use the ability of big data to mine and analyze information to construct a new standard for product concept design evaluation in the big data environment. Secondly, the Pythagorean fuzzy set (PFS), Analytic Hierarchy Process (AHP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are integrated into a decision model. AHP, extended by the Pythagorean fuzzy set, is used to determine the weights of new conceptual design criteria in a big data environment. The Pythagorean fuzzy TOPSIS is used to prioritize alternative conceptual design solutions. The feasibility of the approach is proven with a practical case, the generalizability of the method is confirmed with two descriptive digital cases, and the reliability, validity, and superiority of the process are demonstrated with sensitivity analysis, comparative analysis, and computational complexity analysis.

Abstract Background Aberrant cytokeratin 7 expression by hepatocytes (CK7+Hs) is the hallmark characteristic of cholestasis diseases, especially in ductopenia diseases such as primary biliary cholangitis (PBC). This study attempted to evaluate the differences and relationships between the clinical and histological features of aberrant cytokeratin 7 (CK7) expression by hepatocytes in PBC patients. Methods The clinicopathological data of patients diagnosed with PBC at the Second Hospital of Nanjing between January 2016 and September 2018 were analysed with SPSS 20.0. Results Eighty-nine PBC patients who underwent liver biopsy were enrolled in this study, and 15, 29 and 45 patients had aberrant CK7 expression by hepatocytes (CK7+Hs (2 +), CK7+Hs (1 +), and CK7−Hs, respectively). There were significant differences in TB, DB, ALP, TA, IgM, interface activity, and ductopenia grade between patients with CK7−Hs and CK7+Hs (2 +) (P

IntroductionHuman Papillomavirus (HPV) infection is a risk factor for cervical cancer, the fourth most common cancer among women globally. Its burden is the highest in sub-Saharan Africa, with over 90% mortality. Interventions may fail without evidence-based data on stratified prevalence and risk factors among most at-risk women across Nigeria.MethodsA cross-sectional comparative study, with participants recruited from the Nigerian Institute of Medical Research’s Clinics, NGO outreaches, a cancer screening centre and a university teaching hospital. Questionnaires were self-administered. Trained medics performed sampling at healthcare facilities, and self-sampling was used at outreaches.ResultsNine hundred eighty-five study participants were recruited. About 37% and 27% of the women knew about HPV and its vaccines, respectively, but only 6% confirmed vaccination with HPV vaccines. HPV prevalence was highest among women with unknown marital status (35.9%), single women (33.8%), widowed/divorced/separated women (30.3%), and married/cohabiting women (19.6%). HPV infection was significantly higher among women who take alcohol (odds=1.7 [95% CI: 1.2-2.4]) and women who smoke (odds=2.6 [95% CI: 1.4 - 4.6]. HPV strains detected included HPV16 (1.3%), HPV18 (1.5%), Low Risk (0.2%) and Other High-Risk groups (19.7%).ConclusionThe inverse relationship between prevalence and education suggests interventions improving awareness and prevention would be impactful. Such interventions could also target HIV-positive women, women presenting with sexually-transmitted infections, who smoke and frequently drink alcohol.

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

IntroductionWe explored the impact of a temporary tobacco-free public policy for the 2008 Summer Olympics on the smoking prevalence and secondhand smoke exposure among the population of a co-hosting city, Qingdao, China.MethodsThe Qingdao Diabetes Survey was analyzed for 2006 (n = 4599) and 2009 (n = 4680), which are survey years before and after the tobacco-free Olympics public policy period (July 2007 to January 2009). We analyzed the differences in self-reported smoking prevalence and exposure to secondhand smoke at home and/or workplace, and compared odds of smoking by survey year and of exposure to secondhand smoke among nonsmokers.ResultsFrom 2006 to 2009, the male smoking prevalence declined from 51.4% (95% confidence interval [CI] = 49.0% to 53.9%) to 42.6% (95% CI = 40.2% to 45.1%), and the proportion of lighter smokers decreased more. Among nonsmokers, the secondhand smoke exposure rate declined from 62.2% (95% CI = 60.5% to 63.9%) to 56.8% (95% CI = 55.1% to 58.6%). Regression analyses show 34% lower odds of men smoking after Olympics (OR = 0.66, 95% CI = 0.57% to 0.77%). Rural residents and individuals who are not retired were more likely to smoke. Female nonsmokers report 17% less exposure to secondhand smoke after Olympics (OR = 0.83, 95% CI = 0.70% to 0.98%). Urban nonsmokers were more likely to be exposed than their rural counterparts.ConclusionsSmoking prevalence among men and secondhand smoke exposure among women significantly decreased in Qingdao, China, after the tobacco-free Olympics public policy period. As only the proportion of lighter smokers decreased, this may help explain why urban nonsmokers reported increased exposure. Unintended increased secondhand smoke exposure and cessation support need to be addressed in large-scale policy campaigns.ImplicationsHosting the Olympic Games can help to initiate large-scale tobacco-free public policies for hosting cities. Although previous studies have demonstrated reduction in nonsmoker exposure to secondhand smoke, the impact on the hosting city's smoking prevalence or exposure rates is unclear. After the Olympic Games in Qingdao, China, smoking prevalence among men significantly decreased, mostly due to light smokers. Secondhand smoke exposure at home and/or workplace significantly decreased among female nonsmokers. Urban nonsmokers had an unintended consequence of increased secondhand smoke exposure after the tobacco-free Olympic policy period. Concurrent promotion of cessation support for heavier smokers may be needed.

Abstract Objective To evaluate the feasibility and performance of self-collected vaginal swab samples for HPV screening among women in Lagos, Nigeria. Methods A cross-sectional study was implemented from March to August 2020 among sexually active women. Study participants provided same-day paired vaginal swab samples. Medic-sampling and poster-directed self-sampling methods were used to collect the two samples per participant. A real-time PCR assay detected HPV 16, HPV 18, other-high-risk (OHR) HPV, and the human β-globin gene. The self-collected samples’ sensitivity, specificity, and accuracy were determined against the medic-collected samples using the MedCalc Online Diagnostic Calculator. Results Of the 213 women aged 16 ~ 63-year-old recruited, 187 (88%) participants had concordant results, while 26 (12%) participants had discordant results. Among the 187 concordant results, 35 (19%) were HPV positive, 150 (80%) participants were HPV negative, and two (1%) were invalid. 18 (69%) out of the 26 discordant samples were invalid. The self-collected sample was invalid for 14 (54%) participants. Two (8%) medic-collected samples were invalid. Compared to the medic-collected sample, the self-collected sample was 89.80% (95% CI: 77.77 ~ 96.60%) sensitive and 98.21% (95% CI: 94.87 ~ 99.63%) specific, with an accuracy of 96.31% (95% CI: 92.87 ~ 98.40%). The mean age for HPV positive and negative participants were 39 and 40, respectively, with an ANOVA p-value of 0.3932. The stratification of HPV infection by the age group was not statistically significant (P > 0.05). Conclusions With high accuracy of 96%, self-collected sampling is adequate when tested with real-time PCR and may increase the uptake of HPV testing. Though more self-collected samples were invalid than medic-collected samples, most likely due to poor collection, they could be identified for repeat testing. Future implementation can avoid this error with improved guidance and awareness.

Abstract Background The increasing of exchange activities among public health institutes and experts globally calls for a standardized operation to construct public health field investigation and short-term study hub (Field Study Hub). This can funcion as a platform to share experience in public health development in an accurate and comprehensive manner that would benefit global practices. This research aims to establish a supportive indicator system to guide the construction work. Methods Delphi method including two rounds of surveys were conducted among 82 senior public health experts. A structured questionnaire was designed to collect the opinions of the experts on the necessity of setting and feasibility of measurement for proposed 5 dimensions of 49 indicators and 7 additionally proposed ones. Percentage and score were used to describe the assessments, χ2 and t tests to compare differences, Kappa and Cronbach’s alpha values to assess intra-rater and inter-rater reliabilities. Significance level α was 0.05. Bonferroni adjustment was used in the comparison of experts’ judgment basis. Results The percentages of experts choosing “Very good” or “Good” for necessity and feasibility in rounds 1 and 2 were 73.1–97.6% (85.8% ± 7.5%), 64.6–93.9% (82.8% ± 6.7%), 73.8–100% (91.0% ± 6.2%) and 72.5–100% (89.2% ± 7.3%) respectively. The scores of necessity were higher than those of feasibility, and the differences in the dimensions of “Key experience”, “Capacity for logistic support” and the total were statistically significant (t11 = 2.920, t12 = 3.035, t31 = 4.448, t32 = 2.664, tt1 = 3.794, tt2 = 3.007, P

Abstract The frozen section (FS) diagnoses of pathology experts are used in China to determine whether sentinel lymph nodes of breast cancer have metastasis during operation. Direct implementation of a deep neural network (DNN) in clinical practice may be hindered by misdiagnosis of the algorithm, which affects a patient's treatment decision. In this study, we first obtained the prediction result of the commonly used patch-DNN, then we present a relative risk classification and regression tree (RRCART) to identify the misdiagnosed whole-slide images (WSIs) and recommend them to be reviewed by pathologists. Applying this framework to 2362 WSIs of breast cancer lymph node metastasis, test on frozen section results in the mean area under the curve (AUC) reached 0.9851. However, the mean misdiagnosis rate (0.0248), was significantly higher than the pathologists’ misdiagnosis rate (p 0.01). However, the other low-accuracy group included most of the misdiagnoses of DNN models. Our research shows that the misdiagnosis from deep learning model can be further enriched by our method, and that the low-accuracy WSIs must be selected for pathologists to review and the high-accuracy ones may be ready for pathologists to give diagnostic reports.