Public awareness, emotional reactions and human mobility in response to the COVID-19 outbreak in China - a population-based ecological study.

BACKGROUND: The outbreak of COVID-19 generated severe emotional reactions, and restricted mobility was a crucial measure to reduce the spread of the virus. This study describes the changes in public emotional reactions and mobility patterns in the Chinese population during the COVID-19 outbreak. METHODS: We collected data on public emotional reactions in response to the outbreak through Weibo, the Chinese Twitter, between 1st January and 31st March 2020. Using anonymized location-tracking information, we analyzed the daily mobility patterns of approximately 90% of Sichuan residents. RESULTS: There were three distinct phases of the emotional and behavioral reactions to the COVID-19 outbreak. The alarm phase (19th-26th January) was a restriction-free period, characterized by few new daily cases, but a large amount public negative emotions [the number of negative comments per Weibo post increased by 246.9 per day, 95% confidence interval (CI) 122.5-371.3], and a substantial increase in self-limiting mobility (from 45.6% to 54.5%, changing by 1.5% per day, 95% CI 0.7%-2.3%). The epidemic phase (27th January-15th February) exhibited rapidly increasing numbers of new daily cases, decreasing expression of negative emotions (a decrease of 27.3 negative comments per post per day, 95% CI -40.4 to -14.2), and a stabilized level of self-limiting mobility. The relief phase (16th February-31st March) had a steady decline in new daily cases and decreasing levels of negative emotion and self-limiting mobility. CONCLUSIONS: During the COVID-19 outbreak in China, the public's emotional reaction was strongest before the actual peak of the outbreak and declined thereafter. The change in human mobility patterns occurred before the implementation of restriction orders, suggesting a possible link between emotion and behavior.

Spatial transmission network construction of influenza-like illness using dynamic Bayesian network and vector-autoregressive moving average model.

BACKGROUND: Although vaccination is one of the main countermeasures against influenza epidemic, it is highly essential to make informed prevention decisions to guarantee that limited vaccination resources are allocated to the places where they are most needed. Hence, one of the fundamental steps for decision making in influenza prevention is to characterize its spatio-temporal trend, especially on the key problem about how influenza transmits among adjacent places and how much impact the influenza of one place could have on its neighbors. To solve this problem while avoiding too much additional time-consuming work on data collection, this study proposed a new concept of spatio-temporal route as well as its estimation methods to construct the influenza transmission network. METHODS: The influenza-like illness (ILI) data of Sichuan province in 21 cities was collected from 2010 to 2016. A joint pattern based on the dynamic Bayesian network (DBN) model and the vector autoregressive moving average (VARMA) model was utilized to estimate the spatio-temporal routes, which were applied to the two stages of learning process respectively, namely structure learning and parameter learning. In structure learning, the first-order conditional dependencies approximation algorithm was used to generate the DBN, which could visualize the spatio-temporal routes of influenza among adjacent cities and infer which cities have impacts on others in influenza transmission. In parameter learning, the VARMA model was adopted to estimate the strength of these impacts. Finally, all the estimated spatio-temporal routes were put together to form the final influenza transmission network. RESULTS: The results showed that the period of influenza transmission cycle was longer in Western Sichuan and Chengdu Plain than that in Northeastern Sichuan, and there would be potential spatio-temporal routes of influenza from bordering provinces or municipalities into Sichuan province. Furthermore, this study also pointed out several estimated spatio-temporal routes with relatively high strength of associations, which could serve as clues of hot spot areas detection for influenza surveillance. CONCLUSIONS: This study proposed a new framework for exploring the potentially stable spatio-temporal routes between different places and measuring specific the sizes of transmission effects. It could help making timely and reliable prediction of the spatio-temporal trend of infectious diseases, and further determining the possible key areas of the next epidemic by considering their neighbors' incidence and the transmission relationships.

[Missing Data Replacement Methods in Different Scenarios].

OBJECTIVE: To compare the effect of different approaches of missing data replacement on the regression coefficient estimates r of "length of stay" on "hospital expenditure". METHODS: Data were extracted from the medical records of patients with head and neck neoplasms who were admitted to Sichuan Cancer Hospital. R 3.4.1 was used for generating and processing simulated datasets. Various scenarios were established by setting up different proportions of missing data and missing mechanisms using Monte Carlo method. Three strategies were tested for replacing missing data: Complete Case method,Expectation Maximization (EM),and Markov Chain Monte Carlo method (MCMC). The regression coefficient estimates r of standardized "length of stay" on standardized logarithmic "hospital expenditure" were calculated using these strategies and compared with that of the original complete dataset,in terms of their accuracy (magnitude of differences in r) and precision (differences in the standard error of r). RESULTS: The three replacement methods were all acceptable (within the limit rc±0.5 sc) when missing data were generated using MAR (2∶1) mechanism,or less than 30% data were simulated as missing using the MCAR and MAR (1∶2) mechanism. The EM method had the best estimation precision. CONCLUSION: Missing data replacement should consider the proportion of missing data and potential mechanisms involved.

Effects of a 12-hour neuromuscular electrical stimulation treatment program on the recovery of upper extremity function in sub-acute stroke patients: a randomized controlled pilot trial.

[Purpose] This study investigated the effects of a 12-hour neuromuscular electrical stimulation program in the evening hours on upper extremity function in sub-acute stroke patients. [Subjects and Methods] Forty-five subjects were randomized to one of three groups: 12-hour neuromuscular electrical stimulation group (n=15), which received 12 hours of neuromuscular electrical stimulation and conventional rehabilitation for the affected upper extremity; neuromuscular electrical stimulation group (n=15), which received 30 min of neuromuscular electrical stimulation and conventional rehabilitation; and control group (n=15), which received conventional rehabilitation only. The Fugl-Meyer assessment, Action Research Arm Test, and modified Ashworth scale were used to evaluate the effects before and after intervention, and 4 weeks later. [Results] The improvement in the distal (wrist-hand) components of the Fugl-Meyer assessment and Action Research Arm Test in the 12-hour neuromuscular electrical stimulation group was more significant than that in the neuromuscular electrical stimulation group. No significant difference was found between the two groups in the proximal component (shoulder-elbow) of the Fugl-Meyer assessment. [Conclusion] The 12-hour neuromuscular electrical stimulation group achieved better improvement in upper extremity motor function, especially in the wrist-hand function. This alternative therapeutic approach is easily applicable and can be used in stroke patients during rest or sleep.

Steam Explosion-Assisted Extraction of Polysaccharides from Pleurotus eryngii and Its Influence on Structural Characteristics and Antioxidant Activity.

Pleurotus eryngii (PE) has been sought after for its various health benefits and high content of phenolic compounds. This study explored the feasibility of steam explosion (SE)-assisted extraction of polysaccharides with high antioxidant capacities from PE. An orthogonal experimental design (OED) was used to optimize the SE-assisted extraction of PE. The influence of the optimized SE-assisted extraction on the physicochemical properties of PE polysaccharides was determined by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), monosaccharide compositional analysis and antioxidant capacity assays. Under optimal SE conditions, SE-assisted extraction increased the polysaccharide yield by 138% compared to extraction without SE-assistance. In addition, SEM demonstrated that SE-assisted extraction markedly altered the spatial structure of Pleurotus eryngii polysaccharides (PEP), and monosaccharide compositional analysis revealed that this pretreatment significantly increased the proportions of some monosaccharides, such as glucose, rhamnose and arabinose, in the isolated PEP. FTIR spectra indicated no change in the major chemical functional groups of PEP. PEP extracted by SE-assisted extraction had significantly increased free radical scavenging and antioxidant capacities. In conclusion, SE-assisted extraction appears to be a novel polysaccharide extraction technology, which markedly increases extraction yields and efficiency and can increase the biological activity of polysaccharide extracts.

Linoleic acid exhibits anti-proliferative and anti-invasive activities in endometrial cancer cells and a transgenic model of endometrial cancer.

Emerging evidence has provided considerable insights into the integral function of reprogramming fatty acid metabolism in the carcinogenesis and progression of endometrial cancer. Linoleic acid, an essential fatty acid with the highest consumption in the Western diet regimen, has shown pro-tumorigenic or anti-tumorigenic effects on tumor cell growth and invasion in multiple types of cancer. However, the biological role of linoleic acid in endometrial cancer remains unclear. In the present study, we aimed to investigate the functional impact of linoleic acid on cell proliferation, invasion, and tumor growth in endometrial cancer cells and in a transgenic mouse model of endometrial cancer. The results showed that Linoleic acid significantly inhibited the proliferation of endometrial cancer cells in a dose-dependent manner. The treatment of HEC-1A and KLE cells with linoleic acid effectively increased intracellular reactive oxygen species (ROS) production, decreased mitochondrial membrane potential, caused cell cycle G1 arrest, and induced intrinsic and extrinsic apoptosis pathways. The anti-invasive ability of linoleic acid was found to be associated with the epithelial-mesenchymal transition process in both cell lines, including the decreased expression of N-cadherin, snail, and vimentin. Furthermore, treatment of Lkb1fl/flp53fl/fl transgenic mice with linoleic acid for four weeks significantly reduced the growth of endometrial tumors and decreased the expression of VEGF, vimentin, Ki67, and cyclin D1 in tumor tissues. Our findings demonstrate that linoleic acid exhibits anti-proliferative and anti-invasive activities in endometrial cancer cell lines and the Lkb1fl/flp53fl/fl mouse model of endometrial cancer, thus providing a pre-clinical basis for future dietary interventions with linoleic acid in endometrial cancer.

The VDR gene FokI polymorphism and ovarian cancer risk.

The polymorphism of vitamin D receptor (VDR) gene is demonstrated to affect the activity of its encoding protein and the subsequent downstream effects mediated by vitamin D. Mutations in VDR gene FokI have been suggested in the development of various cancers. Whether the polymorphism of the VDR gene FokI confers risk to ovarian cancer still remains controversial across the published studies in different ethnicity. The aim of this meta-analysis was to determine the role of VDR gene FokI variant in the susceptibility to ovarian cancer. Six publications with 14 individual case-control studies involving a total of 10,964 subjects were finally included into our study after a comprehensive literature search of the PubMed, Embase, Web of Science, and Wanfang databases. The strength of the association between the VDR gene FokI polymorphism and ovarian cancer risk was estimated under the allelic (T vs. C), homozygous (TT vs. CC), additive (CT vs. CC), recessive (TT vs. CC + CT), and dominant (CT + TT vs. CC) gene models. The overall odds ratios (ORs) for the contrast models of T vs. C, TT vs. CC, CT vs. CC, and CT + TT vs. CC indicated that the VDR gene FokI variant was related to an increased risk of ovarian cancer (OR(T vs. C) = 1.09, 95 % confidence interval (CI) 1.03-1.15, P(OR) = 0.004; OR(TT vs. CC) = 1.17, 95 % CI 1.04-1.32, P(OR) = 0.011; OR(CT vs. CC) = 1.10, 95 % CI 1.01-1.20, P(OR) = 0.027; OR(CT + TT vs. CC) = 1.12, 95 % CI 1.03-1.21, P(OR) = 0.007). The stratified analysis among the Caucasians also identified a significant association between the VDR gene FokI polymorphism and the susceptibility to ovarian cancer. The present meta-analysis with large available published data has revealed that the VDR gene FokI polymorphism confers susceptibility to ovarian cancer, particularly among the Caucasian population.

A comparative study of diagnostic accuracy in 3026 pleural biopsies and matched pleural effusion cytology with clinical correlation: A methodological issue.

AIM: After reading the article by Ivan K. Poon et al. Certain issues regarding the methodology must be addressed. RESULT: First, it was not sufficient using only sensitivity and specificity. Second, we think the receiver operator characteristic curve (ROC) as well as the index of area under curve (AUC) could better be demonstrated in this, it was not sufficient using only sensitivity and specificity. Second, we think the receiver operator characteristic curve (ROC) as well as the index of area under curve (AUC) could better be demonstrated in this article for a more comprehensive understanding of this diagnostic test accuracy when comparing different tests. CONCLUSION: With using more comprehensive indexes including Youden's index, LR and AUC, the conclusions of Ivan K. Poon and his colleagues would be sodified.

TIPE2 acts as a tumor suppressor and correlates with tumor microenvironment immunity in epithelial ovarian cancer.

BACKGROUND: Epithelial ovarian cancer (EOC) is one of the deadliest gynecologic cancers. The etiology of EOC has still not been elucidated thoroughly. Tumor necrosis factor-α-induced protein 8-like2 (TNFAIP8L2, TIPE2), an important regulator of inflammation and immune homeostasis, plays a critical role in the progression of various cancers. This study aims to investigate the role of TIPE2 in EOC. METHODS: Expression of TIPE2 protein and mRNA in EOC tissues and cell lines was examined using Western blot and quantitative real-time PCR (qRT-PCR). The functions of TIPE2 in EOC were investigated by cell proliferation assay, colony assay, transwell assay, and apoptosis analysis in vitro. To further investigate the regulatory mechanisms of TIPE2 in EOC, RNA-seq and western blot were performed. Finally, the CIBERSORT algorithm and databases including Tumor Immune Single-cell Hub (TISCH), Tumor Immune Estimation Resource (TIMER), Tumor-Immune System Interaction (TISIDB), and The Gene Expression Profiling Interactive Analysis (GEPIA) were used to elucidate its potential role in regulating tumor immune infiltration in the tumor microenvironment (TME). RESULTS: TIPE2 expression was shown to be considerably lower in both EOC samples and cell lines. Overexpression of TIPE2 suppressed EOC cell proliferation, colony formation, and motility in vitro. Mechanistically, TIPE2 suppressed EOC by blocking the PI3K/Akt signaling pathway, according to bioinformatics analysis and western blot in TIPE2 overexpression EOC cell lines, and the anti-oncogenic potentials of TIPE2 in EOC cells could be partially abrogated by the PI3K agonist, 740Y-P. Finally, TIPE2 expression was positively associated with various immune cells and possibly involved in the regulation of macrophage polarization in ovarian cancer. CONCLUSIONS: We detail the regulatory mechanism of TIPE2 in EOC carcinogenesis, as well as how it correlates with immune infiltration, emphasizing its potential as a therapeutic target in ovarian cancer.

Comparison of Primary B/NKT Non-Hodgkin Lymphomas in Nasopharynx, Nasal Cavity, and Paranasal Sinuses.

OBJECTIVE: We aimed to compare clinical and survival differences between B-cell (B-NHL) and NKT-cell non-Hodgkin lymphomas (NKT-NHL) located in the nasal cavity (NC), nasopharynx, and paranasal sinuses, which are always categorized as one sinonasal type. STUDY DESIGN: Patients diagnosed with primary B-NHL and NKT-NHL in the nasal cavity, nasopharynx, and paranasal sinuses from Surveillance, Epidemiology, and End Results (SEER) database were included (1975-2017). SETTING: Population-based cohort study. METHODS: We conducted univariate and multivariate Cox regressions and Kaplan-Meier analysis to examine survival outcomes of B/NKT-NHL in the nasal cavity, nasopharynx, and paranasal sinuses, respectively. RESULTS: Overall, most B-NHL cases originated from the nasopharynx, while the majority of NKT-NHL cases occurred in the nasal cavity. Notably, the cancer-special survival (CSS) outcomes improved significantly in all sinonasal B-NHL cases over time, whereas no such improvement trend was observed in each sinonasal NKT-NHL type. Additionally, increasing age was linked with an elevated risk of death in B-NHL, particularly in the nasal cavity (Hazard ratio [HR]: 3.37), rather than in NKT-NHL. Compared with B-NHL, the adverse effect of a higher stage on CSS was more evident in NKT-NHL, particularly in its nasopharynx site (HR: 5.12). Furthermore, radiotherapy was beneficial for survival in patients with sinonasal B-NHL and NKT-NHL, except in the nasopharynx NKT-NHL. However, chemotherapy has only been beneficial for CSS in patients with paranasal sinuses B-NHL (HR: 0.42) since 2010, rather than in other types of B/NKT-NHL. CONCLUSION: Although B-NHL and NKT-NHL in the nasal cavity, nasopharynx and paranasal sinuses have similar anatomical locations, their clinicodemographics and prognoses are largely different and should be treated and studied as distinct diseases.

A novel dopamine receptor D2 antagonist (ONC206) potentiates the effects of olaparib in endometrial cancer.

Poly ADP-ribose polymerase (PARP) inhibitors are effective therapies for cancer patients with homologous recombination (HR) deficient tumors. The imipridone ONC206 is an orally bioavailable dopamine receptor D2 antagonist and mitochondrial protease ClpP agonist that has anti-tumorigenic effects in endometrial cancer via induction of apoptosis, activation of the integrated stress response and modulation of PI3K/AKT signaling. Both PARP inhibitors and imipridones are being evaluated in endometrial cancer clinical trials but have yet to be explored in combination. In this manuscript, we evaluated the effects of the PARP inhibitor olaparib in combination with ONC206 in human endometrioid endometrial cancer cell lines and in a genetically engineered mouse model of endometrial cancer. Our results showed that simultaneous exposure of endometrial cancer cells to olaparib and ONC206 resulted in synergistic anti-proliferative effects and increased cellular stress and apoptosis in both cell lines, compared to either drug alone. The combination treatment also decreased expression of the anti-apoptotic protein Bcl-2 and reduced phosphorylation of AKT and S6, with greater effects compared to either drug alone. In the transgenic model of endometrial cancer, the combination of olaparib and ONC206 resulted in a more significant reduction in tumor weight in obese and lean mice compared to ONC206 alone or olaparib alone, together with a considerably decreased Ki-67 and enhanced H2AX expression in obese and lean mice. These results suggest that this novel dual therapy may be worthy of further exploration in clinical trials.

Fetal Congenital Cardiac and Vascular Disorders Associated with Sertraline Treatment during Pregnancy: Analysis of FAERS Data.

Objective: Sertraline is one of the most commonly used antidepressants worldwide and is one of the first-choice treatments for depression during pregnancy. This study is aimed at testing the possible association between sertraline intrauterine exposure and congenital cardiac and vascular disorder occurrences by assessing the publicly available US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: Disproportionality analysis and Bayesian analysis were used to mine FAERS for suspected congenital cardiac and vascular disorder data for sertraline intrauterine exposure from the first quarter of 2004 to the second quarter of 2021. Results: Among the 914 cases of sertraline used with congenital cardiovascular disease in the FAERS database, the reporting areas were mainly in the United States and Europe. The number of adverse events reported every year since 2004 has no many differences. Congenital anomalies are the most frequently reported serious clinical outcome. Among the 69 positive signals detected from 914 cases, 31 were invalid signals, and 38 were valid signals according to criteria. The most common ones are heart disease congenital, atrial septal defect, ventricular septal defect, patent ductus arteriosus, and persistent fetal circulation. Conclusions: Mining FAERS data can analyze and study the adverse reactions of sertraline in a more comprehensive and in-depth manner, thereby effectively reducing the risk of clinical medication.

Applying the Spatial Transmission Network to the Forecast of Infectious Diseases Across Multiple Regions.

Objective: Timely and accurate forecast of infectious diseases is essential for achieving precise prevention and control. A good forecasting method of infectious diseases should have the advantages of interpretability, feasibility, and forecasting performance. Since previous research had illustrated that the spatial transmission network (STN) showed good interpretability and feasibility, this study further explored its forecasting performance for infectious diseases across multiple regions. Meanwhile, this study also showed whether the STN could overcome the challenges of model rationality and practical needs. Methods: The construction of the STN framework involved three major steps: the spatial kluster analysis by tree edge removal (SKATER) algorithm, structure learning by dynamic Bayesian network (DBN), and parameter learning by the vector autoregressive moving average (VARMA) model. Then, we evaluated the forecasting performance of STN by comparing its accuracy with that of the mechanism models like susceptible-exposed-infectious-recovered-susceptible (SEIRS) and machine-learning algorithm like long-short-term memory (LSTM). At the same time, we assessed the robustness of forecasting performance of STN in high and low incidence seasons. The influenza-like illness (ILI) data in the Sichuan Province of China from 2010 to 2017 were used as an example for illustration. Results: The STN model revealed that ILI was likely to spread among multiple cities in Sichuan during the study period. During the whole study period, the forecasting accuracy of the STN (mean absolute percentage error [MAPE] = 31.134) was significantly better than that of the LSTM (MAPE = 41.657) and the SEIRS (MAPE = 62.039). In addition, the forecasting performance of STN was also superior to those of the other two methods in either the high incidence season (MAPE = 24.742) or the low incidence season (MAPE = 26.209), and the superiority was more obvious in the high incidence season. Conclusion: This study applied the STN to the forecast of infectious diseases across multiple regions. The results illustrated that the STN not only had good accuracy in forecasting performance but also indicated the spreading directions of infectious diseases among multiple regions to a certain extent. Therefore, the STN is a promising candidate to improve the surveillance work.

Curcumin-Mediated Sono-Photodynamic Treatment Inactivates Listeria monocytogenes via ROS-Induced Physical Disruption and Oxidative Damage.

Sono-photodynamic sterilization technology (SPDT) has become a promising non-thermal food sterilization technique because of its high penetrating power and outstanding microbicidal effects. In this study, Listeria monocytogenes (LMO) was effectively inactivated using curcumin as the sono-photosensitizer activated by ultrasound and blue LED light. The SPDT treatment at optimized conditions yielded a 4-log reduction in LMO CFU. The reactive oxygen species (ROS) production in LMO upon SPDT treatment was subsequently investigated. The results demonstrated SPDT treatment-induced excessive ROS generation led to bacterial cell deformation and membrane rupture, as revealed by the scanning electron microscope (SEM) and cytoplasmic material leakage. Moreover, agarose gel electrophoresis and SDS-PAGE further revealed that SPDT also triggered bacterial genomic DNA cleavage and protein degradation in LMO, thus inducing bacterial apoptosis-like events, such as membrane depolarization.