Modulation of antigen delivery and lymph node activation in non-human primates by saponin adjuvant SMNP.

Saponin-based vaccine adjuvants are potent in preclinical animal models and humans, but their mechanisms of action remain poorly understood. Here, using a stabilized HIV envelope trimer immunogen, we carried out studies in non-human primates (NHPs) comparing the most common clinical adjuvant alum with Saponin/MPLA Nanoparticles (SMNP), a novel ISCOMs-like adjuvant. SMNP elicited substantially stronger humoral immune responses than alum, including 7-fold higher peak antigen-specific germinal center B cell responses, 18-fold higher autologous neutralizing antibody titers, and higher levels of antigen-specific plasma and memory B cells. PET-CT imaging in live NHPs showed that, unlike alum, SMNP promoted rapid antigen accumulation in both proximal and distal lymph nodes (LNs). SMNP also induced strong type I interferon transcriptional signatures, expansion of innate immune cells, and increased antigen presenting cell activation in LNs. These findings indicate that SMNP promotes multiple facets of the early immune response relevant for enhanced immunity to vaccination.

Humeral Head Preservation after Neglected Glenohumeral Dislocation by Latarjet and Infraspinatus Remplissage-A Case Report.

Background: Neglected anterior glenohumeral dislocations provide a challenging problem for physicians. For many patients with these injuries, reverse shoulder arthroplasty has been the treatment of choice, although the preservation of the patient's own humeral head might have significant advantages. Methods: We present a case of a 66-year-old male with a neglected anterior glenohumeral dislocation that he sustained 6 weeks prior when he was hit by a car as a pedestrian. Radiographic imaging revealed a large off-track Hill-Sachs deformity and a fracture of the greater tuberosity in addition to the persisting glenohumeral dislocation. We performed open reduction and to aid stability, an infraspinatus tendon remplissage and a Latarjet procedure were performed. Results: Apart from minor and self-limiting neuropraxia, recovery was without complications. At 24 month follow-up, the patient had no impairment in general activities, had no residual pain, and had a good active range of motion. Conclusions: The authors, therefore, believe that a combination of infraspinatus tendon remplissage and the Latarjet procedure seems a feasible alternative for reverse shoulder arthroplasty and can preserve the patient's own humeral head.

Fibrocartilaginous lipoma: a clinicopathological analysis of six cases / 中华病理学杂志

Objective: To investigate the clinicopathological characteristics, immunophenotype, molecular genetics and differential diagnoses of fibrocartilaginous lipomas which consist of adipose tissue, fibrocartilage and fibrous elements. Methods: The clinicopathological features, immunohistochemical profiles and molecular profiles in six cases of fibrocartilaginous lipomas diagnosed at Foshan Traditional Chinese Medicine Hospital, Fudan University Shanghai Cancer Center, the Fifth Affiliated Hospital of Zhengzhou University and the Fourth Affiliated Hospital of Harbin Medical University from January 2017 to February 2022 were included. The follow-up information, diagnosis and differential diagnoses were evaluated. Results: There were three males and three females with a median age of 53 years (range 36-69 years) at presentation. Tumors were located in the extremities, the head and neck region and trunk; and presented as painless masses that were located in the subcutaneous tissue or deep soft tissue. Grossly, three cases were well defined with thin capsule, one case was well circumscribed without capsule, two cases were surrounded by some skeletal muscle. The tumors were composed of fatty tissue with intermingled gray-white area. The tumors ranged from 1.50-5.50 cm (mean 2.92 cm). Microscopically, the hallmark of these lesions was the complex admixture of mature adipocytes, fibrocartilage and fibrous element in varying proportions; the fibrocartilage arranged in a nodular, sheet pattern with some adipocytes inside. Tumor cells had a bland appearance without mitotic activity. Immunohistochemical analysis using antibodies to SMA, desmin, S-100, SOX9, HMGA2, RB1, CD34, adipopholin was performed in six cases; the fibrocartilage was positive for S-100 and SOX9, adipocytes were positive for S-100, adipopholin and HMGA2; CD34 was expressed in the fibroblastic cells, while desmin and SMA were negative. Loss of nuclear RB1 expression was not observed. Other genetic abnormalities had not been found yet in four cases. Follow-up information was available in six cases; there was no recurrence in five, and one patient only underwent biopsy of the mass. Conclusions: Fibrocartilaginous lipoma is a benign lipomatous tumor with mature adipocytes, fibrocartilage and fibrous elements. By immunohistochemistry, they show the expression of fat and cartilage markers. No specific molecular genetics changes have been identified so far. Familiarity with its clinicopathological features helps the distinction from its morphologic mimics.

Structural analysis of spike proteins from SARS-CoV-2 variants of concern highlighting their functional alterations.

Aim: Mutations in the SARS-CoV-2 spike (S) protein have dramatically changed the transmissibility and pathogenicity of the virus. Therefore, we studied the binding affinity of Omicron spike-receptor binding domain (S-RBD) with human ACE2 receptor. Materials & methods: We used pyDockWEB and HADDOCK 2.4 docking for our study. Results: Computational docking indicated higher binding affinity of Omicron S-RBD as compared with wild-type SARS-CoV-2 and Delta S-RBD with ACE2. Interface analysis suggested four mutated residues of Omicron S-RBD for its enhanced binding. We also showed decreased binding affinity of Omicron and Delta S-RBDs with monoclonal antibodies. Conclusion: Compared with wild-type SARS-CoV-2, Omicron S-RBD exhibit higher binding with ACE2 and lower affinity against monoclonal antibodies.

In Vitro Evaluation and Mitigation of Niclosamide Liabilities as a COVID-19 Treatment.

Niclosamide, an FDA-approved oral anthelmintic drug, has broad biological activity including anticancer, antibacterial, and antiviral properties. Niclosamide has also been identified as a potent inhibitor of SARS-CoV-2 infection in vitro, generating interest in its use for the treatment or prevention of COVID-19. Unfortunately, there are several potential issues with using niclosamide for COVID-19, including low bioavailability, significant polypharmacology, high cellular toxicity, and unknown efficacy against emerging SARS-CoV-2 variants of concern. In this study, we used high-content imaging-based immunofluorescence assays in two different cell models to assess these limitations and evaluate the potential for using niclosamide as a COVID-19 antiviral. We show that despite promising preliminary reports, the antiviral efficacy of niclosamide overlaps with its cytotoxicity giving it a poor in vitro selectivity index for anti-SARS-CoV-2 inhibition. We also show that niclosamide has significantly variable potency against the different SARS-CoV-2 variants of concern and is most potent against variants with enhanced cell-to-cell spread including B.1.1.7. Finally, we report the activity of 33 niclosamide analogs, several of which have reduced cytotoxicity and increased potency relative to niclosamide. A preliminary structure-activity relationship analysis reveals dependence on a protonophore for antiviral efficacy, which implicates nonspecific endolysosomal neutralization as a dominant mechanism of action. Further single-cell morphological profiling suggests niclosamide also inhibits viral entry and cell-to-cell spread by syncytia. Altogether, our results suggest that niclosamide is not an ideal candidate for the treatment of COVID-19, but that there is potential for developing improved analogs with higher clinical translational potential in the future. ImportanceThere is still an urgent need for effective anti-SARS-CoV-2 therapeutics due to waning vaccine efficacy, the emergence of variants of concern, and limited efficacy of existing antivirals. One potential therapeutic option is niclosamide, an FDA approved anthelmintic compound that has shown promising anti-SARS-CoV-2 activity in cell-based assays. Unfortunately, there are significant barriers for the clinical utility of niclosamide as a COVID-19 therapeutic. Our work emphasizes these limitations by showing that niclosamide has high cytotoxicity at antiviral concentrations, variable potency against variants of concern, and significant polypharmacology as a result of its activity as a nonspecific protonophore. Some of these clinical limitations can be mitigated, however, through structural modifications to the niclosamide scaffold, which we demonstrate through a preliminary structure activity relationship analysis. Overall, we show that niclosamide is not a suitable candidate for the treatment of COVID-19, but that structural analogs with improved drug properties may have higher clinical-translational potential.

A novel consensus-based computational pipeline for rapid screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including omicron variant

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike proteins receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with three-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero-dimeric and -trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concern (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variants RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118) -- that may likely neutralize the recently emerged omicron variant -- facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes

Understanding the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unsolved challenge for the scientific communities across the world. A key to dissect the susceptibility profiles of animal species to SARS-CoV-2 is to understand how virus enters into the cells. The interaction of SARS-CoV-2 ligands (RBD on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the spike protein of SARS-CoV-2 can bind to many vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Additionally, the present study facilitated the identification of genetic determinants that may differentiate susceptible from the resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified susceptibility of bat species to SARS-CoV-2. The findings from current study highlight the importance of intensive surveillance programs aimed at identifying susceptible hosts, particularly those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

The vaccinia-based Sementis Copenhagen Vector COVID-19 vaccine induces broad and durable cellular and humoral immune responses

The ongoing COVID-19 pandemic perpetuated by SARS-CoV-2 variants, has highlighted the continued need for broadly protective vaccines that elicit robust and durable protection. Here, the vaccinia virus-based, replication-defective Sementis Copenhagen Vector (SCV) was used to develop a first-generation COVID-19 vaccine encoding the spike glycoprotein (SCV-S). Vaccination of mice rapidly induced polyfunctional CD8 T cells with cytotoxic activity and robust Th1-biased, spike-specific neutralizing antibodies, which are significantly increased following a second vaccination, and contained neutralizing activity against the alpha and beta variants of concern. Longitudinal studies indicated neutralizing antibody activity was maintained up to 9 months post-vaccination in both young and aging mice, with durable immune memory evident even in the presence of pre-existing vector immunity. This immunogenicity profile suggests a potential to expand protection generated by current vaccines in a heterologous boost format, and presents a solid basis for second-generation SCV-based COVID-19 vaccine candidates incorporating additional SARS-CoV-2 immunogens.

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

Objective@#To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. @*Materials and Methods@#Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. @*Results@#Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. @*Conclusion@#CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

Objective@#To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. @*Materials and Methods@#Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. @*Results@#Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. @*Conclusion@#CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Fructose and metabolic diseases: too much to be good / 中华医学杂志(英文版)

Excessive consumption of fructose, the sweetest of all naturally occurring carbohydrates, has been linked to worldwide epidemics of metabolic diseases in humans, and it is considered an independent risk factor for cardiovascular diseases. We provide an overview about the features of fructose metabolism, as well as potential mechanisms by which excessive fructose intake is associated with the pathogenesis of metabolic diseases both in humans and rodents. To accomplish this aim, we focus on illuminating the cellular and molecular mechanisms of fructose metabolism as well as its signaling effects on metabolic and cardiovascular homeostasis in health and disease, highlighting the role of carbohydrate-responsive element-binding protein in regulating fructose metabolism.

Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 17 dose-responsive compounds with in vitro antiviral efficacy in human liver Huh7 cells and confirmed antiviral efficacy in human colon carcinoma Caco-2, human prostate adenocarcinoma LNCaP, and in a physiologic relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein classically found in secretory fluids, including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19. IMPORTANCESince its emergence in China in December 2019, SARS-CoV-2 has caused a global pandemic. Repurposing of FDA-approved drugs is a promising strategy for identifying rapidly deployable treatments for COVID-19. Herein, we developed a pipeline for quantitative high-throughput image-based screening of SARS-CoV-2 infection in human cells that led to the identification of several FDA-approved drugs and clinical candidates with in vitro antiviral activity.

High Throughput Designing and Mutational Mapping of RBD-ACE2 Interface Guide Non-Conventional Therapeutic Strategies for COVID-19

Considering the current status of the SARS-CoV-2 pandemic, sequence variations and possibly structural changes in the rapidly evolving SARS-CoV-2 is highly expected in the coming months. The SARS-CoV-2 spike (S) protein is responsible for mediating viral attachment and fusion with cell membranes. Mutations in the receptor-binding domain (RBD) of the S-protein occur at the most variable part of the SARS-CoV-2 genome, and specific sites of S-protein have undergone positive selection impacting the viral pathogenicity. In the present work, we used high-throughput computation to design 100,000 mutants in RBD interfacial residues and identify novel affinity-enhancing and affinity-weakening mutations. Our data suggest that SARS-CoV-2 can establish a higher rate of infectivity and pathogenesis when it acquires combinatorial mutations at the interfacial residues in RBD. Mapping of the mutational landscape of the interaction site suggests that a few of these residues are the hot-spot residues with a very high tendency to undergo positive selection. Knowledge of the affinity-enhancing mutations may guide the identification of potential cold-spots for this mutation as targets for developing a possible therapeutic strategy instead of hot-spots, and vice versa. Understanding of the molecular interactions between the virus and host protein presents a detailed systems view of viral infection mechanisms. The applications of the present research can be explored in multiple antiviral strategies, including monoclonal antibody therapy, vaccine design, and importantly in understanding the clinical pathogenesis of the virus itself. Our work presents research directions for the exploitation of non-conventional solutions for COVID-19.

Thermal Disinfection Inactivates SARS-CoV-2 in N95 Respirators while Maintaining Their Protective Function

BackgroundThe unprecedented demand and consequent global shortage of N95 respirators during the COVID-19 pandemic have left frontline workers vulnerable to infection. To potentially expand the supply, we validated a rapidly applicable low-cost decontamination protocol in compliance with regulatory standards to enable the safe reuse of personalized, disposable N95-respirators. MethodsFour common models of N95-respirators were disinfected for 60 minutes at 70{degrees}C either at 0% or 50% relative humidity (RH). Effective inactivation of SARS-CoV-2 and E. coli was evaluated in inoculated masks. The N95 filter integrity was examined with scanning electron microscopy. The protective function of disinfected N95 respirators was tested against US NIOSH standards for particle filtration efficiency, breathing resistance and respirator fit. ResultsA single heat treatment inactivated both SARS-CoV-2 (undetectable, detection limit: 100 TCID50/ml) and E. coli (0 colonies at 50%RH) in all four respirator models. Even N95-respirators that underwent ten decontamination cycles maintained their integrity and met US-governmental criteria for approval regarding fit, filtration efficiency and breathing resistance. Scanning electron microscopy demonstrated maintained N95 fiber diameter compared to baseline. InterpretationThermal disinfection enables large-scale, low cost decontamination of existing N95 respirators using commonly sourced equipment during the COVID-19 pandemic. This process could be used in hospitals and long term care facilities and also provides a feasible approach to expand the N95 supply in low- and middle-income regions.

Microfluidic continuous flow synthesis of functional hollow spherical silica with hierarchical sponge-like large porous shell.

Microfluidics brings unique opportunities for engineering micro-/nanomaterials with well-controlled physicochemical properties. Herein, using a miniaturized multi-run spiral-shaped microreactor, we develop a flow synthesis strategy to continuously produce hollow spherical silica (HSS) with hierarchical sponge-like pore sizes ranging from several nanometers to over one hundred nanometers. The formation of HSS is realized by mixing two reactant flows, one containing cetyltrimethylammonium bromide (CTAB) and diluted ammonia and the other 1,3,5-trimethylbenzene (TMB) and diluted tetraethyl orthosilicate (TEOS), at a flow rate as high as 5 mL/min. The effect of the reactant concentration and the flow rate on the structural change of the resultant materials is examined. Functional small-sized nanoparticles (magnetic nanoparticle, quantum dot, and silver nanoparticle) can be separately assembled into HSS and high molecular weight protein (bovine serum albumin) can be successfully loaded into HSS and delivered into cancer cells afterward, making them promising in the fields of separation and purification, bioimaging, catalysis, and theranostics.

Quantitative Proteomic Analysis of Low Linolenic Acid Transgenic Soybean Reveals Perturbations of Fatty Acid Metabolic Pathways.

To understand the effect of fatty acid desaturase gene (GmFAD3) silencing on perturbation of fatty acid (FA) metabolic pathways, the changes are compared in protein profiling in control and low linolenic acid transgenic soybeans using tandem mass tag based mass spectrometry. Protein profiling of the transgenic line unveiled changes in several key enzymes of FA metabolism. This includes enzymes of lower abundance; fabH, fabF, and thioestrase associated with FA initiation, elongation, and desaturation processes and LOX1_5, ACOX, ACAA1, MFP2 associated with ß-oxidation of α-linolenic acids pathways. In addition, the GmFAD3 silencing results in a significant reduction in one of the major allergens, Gly m 4 (C6T3L5). These results are important for exploring how plants adjust in their biological processes when certain changes are induced in the genetic makeup. A complete understanding of these processes will aid researchers to alter genes for developing value-added soybeans.

Trend of epidemics and variation of pathogens of hand, foot and mouth disease in China: a dynamic series analysis, 2008-2017 / 中华流行病学杂志

Objective: To understand the trend of epidemics and variation of pathogens on hand, foot and mouth diseases (HFMD) in China for setting up appropriate intervention measures. Methods: Data related to reported cases and outbreaks of HFMD from the National Notifiable Disease Surveillance Reporting System of China, 2008 to 2017, was collected and analyzed. Based on the geographical location and types of climate, the total 31 provinces, autonomous regions and municipalities in the mainland of China, were divided into seven regions: north-west, north, mid-north, east, mid-south, south, and south-west regions, with epidemic trends and variation of pathogens analyzed. The average speed of growth on the dynamic series from 2008 to 2017 was calculated, using the Geometric Average method. Results: The overall reported incidence rate of HFMD during 2008-2017 was 134.59 per 100 000 population with an average increase of 15.92%. The proportion of severe cases was 0.84%, with 9.56% increase. The reported mortality rate of HFMD was 0.03/100 000, with an average decrease of 3.49%. The case fatality rate was 0.02% and with a decrease of 16.86%. A total of 6 000 outbreaks were reported during the decade. Except for 1.09% decrease on the incidence rate in the north region, all the other regions showed an increase on the morbidity rates, with the highest as25.20% in the south region. Mortality rates showed 27.53% and 0.60% increases in both the south-west and mid-north regions, respectively. Mortality rates in the other regions all showed a decreasing trend. In terms of case fatality rate, it increased 4.15% in the south-west region while all decreased in the other regions. Two higher age-special morbidity rates appeared in the 1 year olds as 3 184.19/100 000 and in the 2 year olds as 2 547.47/100 000, with the most increase seen in both 0 year (26.08%) and 1 year age groups (23.35%). High age-specific mortality rates were noticed in both the 1-year group as 0.86/100 000 and the 2-year group as 0.54/100 000, however with reductions as 1.21% and 10.70% respectively. As for the case fatalities, the 0 year olds and 1 year olds accounted for 0.039% and 0.027% but both of them had decreased by 19.12% and 19.91%, respectively. Case fatality rates decreased by 16.93% and 16.75%, in males and females. Proportions of EV71 and Cox A16 decreased by 4.28% and 3.07%, but the proportion of other entero-viruses increased by 16.07%. EV71 was responsible for the high frequency of epidemics in both mid-north and the mid-south regions. However, in other five regions, other strains of EV's were responsible for the epidemics. Conclusions: The characteristics of HFMD in China showed that the morbidity of HFMD and proportion of severe cases were both in increasing trends but both the mortality and case fatality of HFMD were decreasing. Children younger than 3 years old showed both high infection and death rates for HFMD. Epidemics caused by other enteroviruses of non-EV71 and non-Cox A16 were seen more. Variance and pathogens related to the epidemic cycles appeared different in the seven regions.

Application of miniSTR Loci and Its Detection System for Degraded Materials in Forensic Medicine / 法医学杂志

OBJECTIVES@#To establish multiplex system of 16 miniSTR loci, and explore its application value for the degraded materials in forensic medicine.@*METHODS@#The multiplex system of 16 miniSTR loci was established using a six-dye fluorescence labeling technology and its application value in forensic medicine was assessed.@*RESULTS@#A six-dye fluorescence labeling miniSTR amplification kit was developed, which enabled 15 autosomal STR loci, Amelogenin locus and DYS391 to be typed simultaneously. This method showed good specificity and could provide stable and accurate typing results with a sensitivity of 50 pg. This system also provided a good test result for the normal biological sample of actual cases.@*CONCLUSIONS@#The multiplex system of 16 miniSTR loci has application value for degraded and trace materials with the advantages of high sensitivity and database compatibility, which can be used for forensic casework.

Temporal-spatial analysis of bacillary dysentery in the Three Gorges Area of China, 2005-2016 / 中华流行病学杂志

Objective: To analyze the spatial and temporal distributions of bacillary dysentery in Chongqing, Yichang and Enshi (the Three Gorges Area) from 2005 to 2016, and provide evidence for the disease prevention and control. Methods: The incidence data of bacillary dysentery in the Three Gorges Area during this period were collected from National Notifiable Infectious Disease Reporting System. The spatial-temporal scan statistic was conducted with software SaTScan 9.4 and bacillary dysentery clusters were visualized with software ArcGIS 10.3. Results: A total of 126 196 cases were reported in the Three Gorges Area during 2005-2016, with an average incidence rate of 29.67/100 000. The overall incidence was in a downward trend, with an average annual decline rate of 4.74%. Cases occurred all the year round but with an obvious seasonal increase between May and October. Among the reported cases, 44.71% (56 421/126 196) were children under 5-year-old, the cases in children outside child care settings accounted for 41.93% (52 918/126 196) of the total. The incidence rates in districts of Yuzhong, Dadukou, Jiangbei, Shapingba, Jiulongpo, Nanan, Yubei, Chengkou of Chongqing and districts of Xiling and Wujiagang of Yichang city of Hubei province were high, ranging from 60.20/100 000 to 114.81/100 000. Spatial-temporal scan statistic for the spatial and temporal distributions of bacillary dysentery during this period revealed that the temporal distribution was during May-October, and there were 12 class Ⅰ clusters, 35 class Ⅱ clusters, and 9 clusters without statistical significance in counties with high incidence. All the class Ⅰ clusters were in urban area of Chongqing (Yuzhong, Dadukou, Jiangbei, Shapingba, Jiulongpo, Nanan, Beibei, Yubei, Banan) and surrounding counties, and the class Ⅱ clusters transformed from concentrated distribution to scattered distribution. Conclusions: Temporal and spatial cluster of bacillary dysentery incidence existed in the three gorges area during 2005-2016. It is necessary to strengthen the bacillary dysentery prevention and control in urban areas of Chongqing and Yichang.

Bibliometrics and visualization analysis of land use regression models in ambient air pollution research / 中华流行病学杂志

Objective: To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies. Methods: Relevant literature from the PubMed database before June 30, 2017 was analyzed, using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0). Keywords co-occurrence networks, cluster mapping and timeline mapping were generated, using the CiteSpace 5.1.R5 software. Relevant literature identified in three Chinese databases was also reviewed. Results: Four hundred sixty four relevant papers were retrieved from the PubMed database. The number of papers published showed an annual increase, in line with the growing trend of the index. Most papers were published in the journal of Environmental Health Perspectives. Results from the Co-word cluster analysis identified five clusters: cluster#0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution; cluster#1 referred to land use regression modeling and exposure assessment; cluster#2 was related to the epidemiology on traffic exposure; cluster#3 dealt with the exposure to ultrafine particles and related health effects; cluster#4 described the exposure to black carbon and related health effects. Data from Timeline mapping indicated that cluster#0 and#1 were the main research areas while cluster#3 and#4 were the up-coming hot areas of research. Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling. Conclusion: In order to better assess the health-related risks of ambient air pollution, and to best inform preventative public health intervention policies, application of LUR models to environmental epidemiology studies in China should be encouraged.