Altermagnetism Induced by Sliding Ferroelectricity via Lattice Symmetry-Mediated Magnetoelectric Coupling.

Altermagnets, distinct from conventional ferromagnets or antiferromagnets, have recently attracted attention as the third category of collinear magnets, which exhibit the coexistence of zero net magnetization and spin polarization due to their unique lattice symmetries. Meanwhile, the additional layer degrees of freedom in multilayer sliding ferroelectrics offer opportunities for coupling with lattice symmetries, paving the way for an innovative approach to constructing multiferroic lattices. In this study, altermagnetic tuning in SnS2/MnPSe3/SnS2 heterostructures is achieved by breaking and restoration of lattice inversion symmetry through sliding ferroelectric switching. First-principles calculations reveal that the spin density and corresponding time-reversal symmetry of MnPSe3 can be manipulated by lattice symmetry, triggering phase transitions between antiferromagnetism and altermagnetism. This research establishes a novel form of magnetoelectric coupling mediated by lattice symmetry and provides a theoretical basis for the design of miniature information processing and memory devices based on altermagnetism.

MTFR2-dependent mitochondrial fission promotes HCC progression.

BACKGROUND: The role of mitochondrial dynamics, encompassing fission, fusion, and mitophagy, in cancer progression has been extensively studied. However, the specific impact of mitochondrial dynamics on hepatocellular carcinoma (HCC) is still under investigation. METHODS: In this study, mitochondrial dynamic genes were obtained from the MitoCarta 3.0 database, and gene expression data were collected from The Cancer Genome Atlas (TCGA) database. Based on the expression of these dynamic genes and differentially expressed genes (DEGs), patients were stratified into two clusters. Subsequently, a prognostic model was constructed using univariate COX regression and the least absolute shrinkage and selection operator (LASSO) regression, and the prognostic signature was evaluated. We analyzed the interaction between these model genes and dynamic genes to identify hub genes and reveal mitochondrial status. Furthermore, we assessed immune infiltration, tumor mutational burden (TMB), tumor stemness indices (TSI), and the response to immune checkpoint block (ICB) therapy using the TIDE algorithm and risk scores. Additionally, transmission electron microscopy (TEM), hematoxylin-eosin (H&E) staining, immunohistochemistry (IHC), western blotting (WB), and immunofluorescence (IF) were conducted to afford detailed visualization of the morphology of the mitochondria and the expression patterns of fission-associated proteins. RESULTS: Patients in Cluster 2 exhibited heightened mitochondrial fission and had a worse prognosis. The up-regulated dynamic genes in Cluster 2 were identified as fission genes. GO/KEGG analyses reconfirmed the connection of Cluster 2 to augmented mitochondrial fission activities. Subsequently, a ten-gene prognostic signature based on the differentially expressed genes between the two clusters was generated, with all ten genes being up-regulated in the high-risk group. Moreover, the potential links between these ten signature genes and mitochondrial dynamics were explored, suggesting their involvement in mediating mitochondrial fission through interaction with MTFR2. Further investigation revealed that the high-risk group had an unfavorable prognosis, with a higher mutation frequency of TP53, increased immune checkpoint expression, a higher TIS score, and a lower TIDE score. The mitochondrial imbalance characterized by increased fission and upregulated MTFR2 and DNM1L expression was substantiated in both HCC specimens and cell lines. CONCLUSIONS: In conclusion, we developed a novel MTFR2-related prognostic signature comprising ten mitochondrial dynamics genes. These genes play crucial roles in mitochondrial fission and have the potential to serve as important predictors and therapeutic targets for HCC.

A novel method to select time-varying multivariate time series models for the surveillance of infectious diseases.

BACKGROUND: Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for constructing cross-regional infectious disease transmission networks due to its strengths in interpretability and predictive performance. Nevertheless, the assumption of constant parameters frequently disregards the dynamic shifts in disease transmission rates, thereby compromising the accuracy of early warnings. This study investigated the applicability of time-varying MTS models in multi-regional infectious disease monitoring and explored strategies for model selection. METHODS: This study focused on two prominent time-varying MTS models: the time-varying parameter-stochastic volatility-vector autoregression (TVP-SV-VAR) model and the time-varying VAR model using the generalized additive framework (tvvarGAM), and intended to explore and verify their applicable conditions for the surveillance of infectious diseases. For the first time, this study proposed the time delay coefficient and spatial sparsity indicators for model selection. These indicators quantify the temporal lags and spatial distribution of infectious disease data, respectively. Simulation study adopted from real-world infectious disease surveillance was carried out to compare model performances under various scenarios of spatio-temporal variation as well as random volatility. Meanwhile, we illustrated how the modelling process could help the surveillance of infectious diseases with an application to the influenza-like case in Sichuan Province, China. RESULTS: When the spatio-temporal variation was small (time delay coefficient: 0.1-0.2, spatial sparsity:0.1-0.3), the TVP-SV-VAR model was superior with smaller fitting residuals and standard errors of parameter estimation than those of the tvvarGAM model. In contrast, the tvvarGAM model was preferable when the spatio-temporal variation increased (time delay coefficient: 0.2-0.3, spatial sparsity: 0.6-0.9). CONCLUSION: This study emphasized the importance of considering spatio-temporal variations when selecting appropriate models for infectious disease surveillance. By incorporating our novel indicators-the time delay coefficient and spatial sparsity-into the model selection process, the study could enhance the accuracy and effectiveness of infectious disease monitoring efforts. This approach was not only valuable in the context of this study, but also has broader implications for improving time-varying MTS analyses in various applications.

How does the SARS-CoV-2 reinfection rate change over time? The global evidence from systematic review and meta-analysis.

BACKGROUND: There is a significant increase in the number of SARS-CoV-2 reinfection reports in various countries. However, the trend of reinfection rate over time is not clear. METHODS: We searched PubMed, Web of Science, Medline, Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, and Wanfang for cohort studies, case-control studies, and cross-sectional studies up to March 16, 2023, to conduct a meta-analysis of global SARS-CoV-2 reinfection rate. Subgroup analyses were performed for age, country, study type, and study population, and time-varying reinfection rates of SARS-CoV-2 were estimated using meta-regression. The risk of bias was assessed using the Newcastle-Ottawa Scale and the Joanna Briggs Institute critical appraisal tool. RESULT: A total of 55 studies involving 111,846 cases of SARS-CoV-2 reinfection were included. The pooled SARS-CoV-2 reinfection rate was 0.94% (95% CI: 0.65 -1.35%). In the subgroup analyses, there were statistically significant differences in the pooled reinfection rates by reinfection variant, and study type (P < 0.05). Based on meta-regression, the reinfection rate fluctuated with time. CONCLUSION: Meta-regression analysis found that the overall reinfection rate increased and then decreased over time, followed by a period of plateauing and then a trend of increasing and then decreasing, but the peak of the second wave of reinfection rate was lower than the first wave. SARS-CoV-2 is at risk of reinfection and the Omicron variant has a higher reinfection rate than other currently known variants. The results of this study could help guide public health measures and vaccination strategies in response to the Coronavirus Disease 2019 (COVID-19) pandemic.

Ultra-High-Density Ferroelectric Array Formed by Sliding Ferroelectric Moiré Superlattices.

2D van der Waals (vdW) materials offer infinite possibilities for constructing unique ferroelectrics through simple layer stacking and rotation. In this work, we stack nonferroelectric GeS2 and ferroelectric CuInP2S6 to form heterostructures by combining sliding ferroelectric polarization with displacement ferroelectric polarization to achieve multiple polarization states. First-principles calculations reveal that the polarization reversal of the CuInP2S6 component in the GeS2/CuInP2S6/GeS2 heterostructure can simultaneously drive the switching of sliding ferroelectric polarization, displaying a robust coupling of the two polarizations and leading to the overall polarization switching. Based on this, ferroelectric arrays with a density of 6.55 × 1012 cm-2 (equivalent to a storage density of 0.7 TB cm-2) were constructed in a moiré superlattice, and the polarization strength of array elements was 11.77 pC/m, higher than that of all reported 2D vdW out-of-plane ferroelectrics. High density, large polarization, and electrically switchable array elements in ferroelectric arrays provide unprecedented opportunities to design 2D high-density nonvolatile ferroelectric memories.

NRAMP6 and NRAMP1 cooperatively regulate root growth and manganese translocation under manganese deficiency in Arabidopsis.

The essential micronutrient manganese (Mn) in plants regulates multiple biological processes including photosynthesis and oxidative stress. Some Natural Resistance-Associated Macrophage Proteins (NRAMPs) have been reported to play critical roles in Mn uptake and reutilization in low Mn conditions. NRAMP6 was demonstrated to regulate cadmium tolerance and iron utilization in Arabidopsis. Nevertheless, it is unclear whether NRAMP6 plays a role in Mn nutrition. Here, we report that NRAMP6 cooperates with NRAMP1 in Mn utilization. Mutation of NRAMP6 in nramp1 but not in a wild-type background reduces root growth and Mn translocation from the roots to shoots under Mn deficient conditions. Grafting experiments revealed that NRAMP6 expression in both the roots and shoots is required for root growth and Mn translocation under Mn deficiency. We also showed that NRAMP1 could replace NRAMP6 to sustain root growth under Mn deficiency, but not vice versa. Mn deficiency does not affect the transcript level of NRAMP6, but is able to increase and decrease the protein accumulation of NRAMP6 in roots and shoots, respectively. Furthermore, NRAMP6 can be localized to both the plasma membrane and endomembranes including the endoplasmic reticulum, and Mn deficiency enhances the localization of NRAMP6 to the plasma membrane in Arabidopsis plants. NRAMP6 could rescue the defective growth of the yeast mutant Δsmf2, which is deficient in endomembrane Mn transport. Our results reveal the important role of NRAMP6 in Mn nutrition and in the long-distance signaling between the roots and shoots under Mn deficient conditions.

Optimizing laboratory-based surveillance networks for monitoring multi-genotype or multi-serotype infections.

With the aid of laboratory typing techniques, infectious disease surveillance networks have the opportunity to obtain powerful information on the emergence, circulation, and evolution of multiple genotypes, serotypes or other subtypes of pathogens, informing understanding of transmission dynamics and strategies for prevention and control. The volume of typing performed on clinical isolates is typically limited by its ability to inform clinical care, cost and logistical constraints, especially in comparison with the capacity to monitor clinical reports of disease occurrence, which remains the most widespread form of public health surveillance. Viewing clinical disease reports as arising from a latent mixture of pathogen subtypes, laboratory typing of a subset of clinical cases can provide inference on the proportion of clinical cases attributable to each subtype (i.e., the mixture components). Optimizing protocols for the selection of isolates for typing by weighting specific subpopulations, locations, time periods, or case characteristics (e.g., disease severity), may improve inference of the frequency and distribution of pathogen subtypes within and between populations. Here, we apply the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework to simulate and optimize hand foot and mouth disease (HFMD) surveillance in a high-burden region of western China. We identify laboratory surveillance designs that significantly outperform the existing network: the optimal network reduced mean absolute error in estimated serotype-specific incidence rates by 14.1%; similarly, the optimal network for monitoring severe cases reduced mean absolute error in serotype-specific incidence rates by 13.3%. In both cases, the optimal network designs achieved improved inference without increasing subtyping effort. We demonstrate how the DIOS framework can be used to optimize surveillance networks by augmenting clinical diagnostic data with limited laboratory typing resources, while adapting to specific, local surveillance objectives and constraints.

Prenatal and early-life exposure to the Great Chinese Famine increased the risk of tuberculosis in adulthood across two generations.

Global food security is a major driver of population health, and food system collapse may have complex and long-lasting effects on health outcomes. We examined the effect of prenatal exposure to the Great Chinese Famine (1958-1962)-the largest famine in human history-on pulmonary tuberculosis (PTB) across consecutive generations in a major center of ongoing transmission in China. We analyzed >1 million PTB cases diagnosed between 2005 and 2018 in Sichuan Province using age-period-cohort analysis and mixed-effects metaregression to estimate the effect of the famine on PTB risk in the directly affected birth cohort (F1) and their likely offspring (F2). The analysis was repeated on certain sexually transmitted and blood-borne infections (STBBI) to explore potential mechanisms of the intergenerational effects. A substantial burden of active PTB in the exposed F1 cohort and their offspring was attributable to the Great Chinese Famine, with more than 12,000 famine-attributable active PTB cases (>1.23% of all cases reported between 2005 and 2018). An interquartile range increase in famine intensity resulted in a 6.53% (95% confidence interval [CI]: 1.19-12.14%) increase in the ratio of observed to expected incidence rate (incidence rate ratio, IRR) in the absence of famine in F1, and an 8.32% (95% CI: 0.59-16.6%) increase in F2 IRR. Increased risk of STBBI was also observed in F2. Prenatal and early-life exposure to malnutrition may increase the risk of active PTB in the exposed generation and their offspring, with the intergenerational effect potentially due to both within-household transmission and increases in host susceptibility.

Golgi-localised manganese transporter PML3 regulates Arabidopsis growth through modulating Golgi glycosylation and cell wall biosynthesis.

Golgi is a critical compartment for both the reutilisation of the essential micronutrient manganese (Mn) and its detoxification. However, whether Mn plays a role in the Golgi remains to be demonstrated in plants. We characterised the function of PML3, a member of the Unknown Protein Family UPF0016, in Mn transport and the regulation of plant growth, Golgi glycosylation and cell wall biosynthesis in Arabidopsis. We also investigated the relationship of PML3 with NRAMP2, a trans-Golgi network localised Mn transporter. PML3-GFP is preferentially localised in the cis-Golgi. PML3 can transport Mn to rescue the hypersensitivity of yeast mutant Δpmr1 to excess Mn. Two mutant alleles of PML3 displayed reduced plant growth and impaired seed development under Mn-deficient conditions. The pml3 mutants also showed impaired Golgi glycosylation and cell wall biosynthesis under Mn deficiency. Double mutations of PML3 and NRAMP2 showed improved plant growth compared with that of single mutants under Mn deficiency, implying that PML3 and NRAMP2 play opposite roles in the regulation of Golgi Mn levels. Our results suggest that PML3 mediates Mn uptake into the Golgi compartments, which is required for proper protein glycosylation and cell wall biosynthesis under Mn-deficient conditions.

The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures.

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters-such as the number and placement of surveillance sites, target populations, and case definitions-are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as an optimization problem, acknowledging the many operational constraints under which surveillance systems operate, the many dimensions of surveillance system design, the multiple and competing goals of surveillance, and the complex and dynamic nature of disease systems. We describe an analytical framework-the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework-for the identification of optimal surveillance designs through mathematical representations of disease and surveillance processes, definition of objective functions, and numerical optimization. We then apply the framework to the problem of selecting candidate sites to expand an existing surveillance network under alternative objectives of: (1) improving spatial prediction of disease prevalence at unmonitored sites; or (2) estimating the observed effect of a risk factor on disease. Results of this demonstration illustrate how optimal designs are sensitive to both surveillance goals and the underlying spatial pattern of the target disease. The findings affirm the value of designing surveillance systems through quantitative and adaptive analysis of network characteristics and performance. The framework can be applied to the design of surveillance systems tailored to setting-specific disease transmission dynamics and surveillance needs, and can yield improved understanding of tradeoffs between network architectures.

Spatio-temporal analysis of bacillary dysentery in Sichuan province, China, 2011-2019.

BACKGROUND: Bacillary dysentery (BD) is a common infectious disease in China and causes enormous economic burdens. The purpose of this study was to describe the epidemiological characteristics of BD and to identify its possible hot spots and potentially high-risk areas in Sichuan province of China. METHODS: In this study, we collected monthly BD incidence reports of 181 counties in Sichuan province, China, from January 2011 to December 2019. Descriptive statistics were used to evaluate the epidemic characteristics of BD. Moran's I index was applied to investigate the yearly patterns of the spatial distribution. And spatio-temporal scanning statistics with the spatial unit set as county and the temporal unit set as month were used to investigate the possible high-risk region. Meanwhile, the circular moving windows were also employed in the spatio-temporal scanning to scan the study areas. RESULTS: The annual incidence of BD ranged between 16.13/100,000 and 6.17/100,000 person-years from 2011 to 2019 in Sichuan. The majority of the cases were children aged 5 years or younger. For the descriptive statistics, a peak from May to October was observed in temporal analysis, the epidemics were mainly concentrated in the northwest and southwest of Sichuan in spatial analysis. After 2016, the scope of BD significantly narrowed and severe epidemic areas were relatively stable. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high-high clusters mainly distributed in the northwest and southwest of Sichuan. For the spatio-temporal scanning, the spatiotemporal clusters of BD occurred every year from 2011 to 2019. The most likely cluster areas mainly distributed in the southwest and northwest of Sichuan at the beginning, and then gradually concentrated in the southwest. The secondary cluster mainly concentrated in the northwest and its surrounding areas. Moreover, the 2nd secondary cluster was relatively small and mainly distributed in the central area. No clusters were noted in eastern Sichuan. CONCLUSIONS: Based on our current analysis, BD is still a common challenge in Sichuan, especially for counties in the southwest and northwest in summer and autumn. More disease prevention and control measures should be taken in such higher-risk susceptible areas at a certain time to allocate the public health resources rationally, and finally reduce the spread of BD.

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.

Early Evidence of Inactivated Enterovirus 71 Vaccine Impact Against Hand, Foot, and Mouth Disease in a Major Center of Ongoing Transmission in China, 2011-2018: A Longitudinal Surveillance Study.

BACKGROUND: Enterovirus 71 (EV71) is a major causative agent of hand, foot, and mouth disease (HFMD), associated with severe manifestations of the disease. Pediatric immunization with inactivated EV71 vaccine was initiated in 2016 in the Asia-Pacific region, including China. We analyzed a time series of HFMD cases attributable to EV71, coxsackievirus A16 (CA16), and other enteroviruses in Chengdu, a major transmission center in China, to assess early impacts of immunization. METHODS: Reported HFMD cases were obtained from China's notifiable disease surveillance system. We compared observed postvaccination incidence rates during 2017-2018 with counterfactual predictions made from a negative binomial regression and a random forest model fitted to prevaccine years (2011-2015). We fit a change point model to the full time series to evaluate whether the trend of EV71 HFMD changed following vaccination. RESULTS: Between 2011 and 2018, 279 352 HFMD cases were reported in the study region. The average incidence rate of EV71 HFMD in 2017-2018 was 60% (95% prediction interval [PI], 41%-72%) lower than predicted in the absence of immunization, corresponding to an estimated 6911 (95% PI, 3246-11 542) EV71 cases averted over 2 years. There were 52% (95% PI, 42%-60%) fewer severe HFMD cases than predicted. However, the incidence rate of non-CA16 and non-EV71 HFMD was elevated in 2018. We identified a significant decline in the trend of EV71 HFMD 4 months into the postvaccine period. CONCLUSIONS: We provide the first real-world evidence that programmatic vaccination against EV71 is effective against childhood HFMD and present an approach to detect early vaccine impact or intended consequences from surveillance data.

Natural variation in the promoter of OsHMA3 contributes to differential grain cadmium accumulation between Indica and Japonica rice.

Rice is a major source of cadmium (Cd) intake for Asian people. Indica rice usually accumulates more Cd in shoots and grains than Japonica rice. However, underlying genetic bases for differential Cd accumulation between Indica and Japonica rice are still unknown. In this study, we cloned a quantitative trait locus (QTL) grain Cd concentration on chromosome 7 (GCC7) responsible for differential grain Cd accumulation between two rice varieties by performing QTL analysis and map-based cloning. We found that the two GCC7 alleles, GCC7PA64s and GCC793-11 , had different promoter activity of OsHMA3, leading to different OsHMA3 expression and different shoot and grain Cd concentrations. By analyzing the distribution of different haplotypes of GCC7 among diverse rice accessions, we discovered that the high and low Cd accumulation alleles, namely GCC793-11 and GCC7PA64s , were preferentially distributed in Indica and Japonica rice, respectively. We further showed that the GCC7PA64s allele can be used to replace the GCC793-11 allele in the super cultivar 93-11 to reduce grain Cd concentration without adverse effect on agronomic traits. Our results thus reveal that the QTL GCC7 with sequence variation in the OsHMA3 promoter is an important determinant controlling differential grain Cd accumulation between Indica and Japonica rice.

Targeted resequencing of 358 candidate genes for autism spectrum disorder in a Chinese cohort reveals diagnostic potential and genotype-phenotype correlations.

Autism spectrum disorder (ASD) is a childhood neuropsychiatric disorder with a complex genetic architecture. The diagnostic potential of a targeted panel of ASD genes has only been evaluated in small cohorts to date and is especially understudied in the Chinese population. Here, we designed a capture panel with 358 genes (111 syndromic and 247 nonsyndromic) for ASD and sequenced a Chinese cohort of 539 cases evaluated with the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) as well as 512 controls. ASD cases were found to carry significantly more ultra-rare functional variants than controls. A subset of 78 syndromic and 54 nonsyndromic genes was the most significantly associated and should be given high priority in the future screening of ASD patients. Pathogenic and likely pathogenic variants were detected in 9.5% of cases. Variants in SHANK3 and SHANK2 were the most frequent, especially in females, and occurred in 1.2% of cases. Duplications of 15q11-13 were detected in 0.8% of cases. Variants in CNTNAP2 and MEF2C were correlated with epilepsy/tics in cases. Our findings reveal the diagnostic potential of ASD genetic panel testing and new insights regarding the variant spectrum. Genotype-phenotype correlations may facilitate the diagnosis and management of ASD.

Evidence for heterogeneity in China's progress against pulmonary tuberculosis: uneven reductions in a major center of ongoing transmission, 2005-2017.

BACKGROUND: China contributed 8.9% of all incident cases of tuberculosis globally in 2017, and understanding the spatiotemporal distribution of pulmonary tuberculosis (PTB) in major transmission foci in the country is critical to ongoing efforts to improve population health. METHODS: We estimated annual PTB notification rates and their spatiotemporal distributions in Sichuan province, a major center of ongoing transmission, from 2005 to 2017. Time series decomposition was used to obtain trend components from the monthly incidence rate time series. Spatiotemporal cluster analyses were conducted to detect spatiotemporal clusters of PTB at the county level. RESULTS: From 2005 to 2017, 976,873 cases of active PTB and 388,739 cases of smear-positive PTB were reported in Sichuan Province, China. During this period, the overall reported incidence rate of active PTB decreased steadily at a rate of decrease (3.77 cases per 100,000 per year, 95% confidence interval (CI): 3.28-4.31) that was slightly faster than the national average rate of decrease (3.14 cases per 100,000 per year, 95% CI: 2.61-3.67). Although reported PTB incidence decreased significantly in most regions of the province, incidence was observed to be increasing in some counties with high HIV incidence and ethnic minority populations. Active and smear-positive PTB case reports exhibited seasonality, peaking in March and April, with apparent links to social dynamics and climatological factors. CONCLUSIONS: While PTB incidence rates decreased strikingly in the study area over the past decade, improvements have not been equally distributed. Additional surveillance and control efforts should be guided by the seasonal-trend and spatiotemporal cluster analyses presented here, focusing on areas with increasing incidence rates, and updated to reflect the latest information from real-time reporting.

NRAMP2, a trans-Golgi network-localized manganese transporter, is required for Arabidopsis root growth under manganese deficiency.

To cope with manganese (Mn) deficiency, plants have evolved an efficient transport system to uptake and redistribute Mn. However, the underlying molecular mechanisms remain to be demonstrated. We carried out a forward genetic screen in a root high-affinity Mn transporter nramp1 mutant background in Arabidopsis thaliana and identified an uncharacterized Mn transport NRAMP2. We investigated the effect of nramp2 mutation on root growth and reactive oxygen species (ROS) accumulation and we also examined the NRAMP2 expression pattern, and the subcellular localization and transport activity of NRAMP2. Mutation of NRAMP2 impaired plant growth, while overexpression of NRAMP2 improved plant growth under low Mn conditions. In the nramp2-1nramp1 double mutant, Mn deficiency inhibited root cell elongation and root hair development, which was associated with increased hydrogen peroxide (H2 O2 ) accumulation. NRAMP2 is preferentially localized to the trans-Golgi network. NRAMP2 has Mn influx transport activity in yeast, and mutation of NRAMP2 led to greater Mn retention in roots. Our results suggest that under Mn-deficient conditions, increased accumulation of H2 O2 is partially responsible for the root growth inhibition and NRAMP2 is involved in remobilization of Mn in Golgi for root growth.

Postzygotic single-nucleotide mosaicisms contribute to the etiology of autism spectrum disorder and autistic traits and the origin of mutations.

The roles and characteristics of postzygotic single-nucleotide mosaicisms (pSNMs) in autism spectrum disorders (ASDs) remain unclear. In this study of the whole exomes of 2,361 families in the Simons Simplex Collection, we identified 1,248 putative pSNMs in children and 285 de novo SNPs in children with detectable parental mosaicism. Ultra-deep amplicon resequencing suggested a validation rate of 51%. Analyses of validated pSNMs revealed that missense/loss-of-function (LoF) pSNMs with a high mutant allele fraction (MAF≥ 0.2) contributed to ASD diagnoses (P = 0.022, odds ratio [OR] = 5.25), whereas missense/LoF pSNMs with a low MAF (MAF<0.2) contributed to autistic traits in male non-ASD siblings (P = 0.033). LoF pSNMs in parents were less likely to be transmitted to offspring than neutral pSNMs (P = 0.037), and missense/LoF pSNMs in parents with a low MAF were transmitted more to probands than to siblings (P = 0.016, OR = 1.45). We estimated that pSNMs in probands or de novo mutations inherited from parental pSNMs increased the risk of ASD by approximately 6%. Adding pSNMs into the transmission and de novo association test model revealed 13 new ASD risk genes. These results expand the existing repertoire of genes involved in ASD and shed new light on the contribution of genomic mosaicisms to ASD diagnoses and autistic traits.

Surveillance systems for neglected tropical diseases: global lessons from China's evolving schistosomiasis reporting systems, 1949-2014.

Though it has been a focus of the country's public health surveillance systems since the 1950s, schistosomiasis represents an ongoing public health challenge in China. Parallel, schistosomiasis-specific surveillance systems have been essential to China's decades-long campaign to reduce the prevalence of the disease, and have contributed to the successful elimination in five of China's twelve historically endemic provinces, and to the achievement of morbidity and transmission control in the other seven. More recently, an ambitious goal of achieving nation-wide transmission interruption by 2020 has been proposed. This paper details how schistosomiasis surveillance systems have been structured and restructured within China's evolving public health system, and how parallel surveillance activities have provided an information system that has been integral to the characterization of, response to, and control of the disease. With the ongoing threat of re-emergence of schistosomiasis in areas previously considered to have achieved transmission control, a critical examination of China's current surveillance capabilities is needed to direct future investments in health information systems and to enable improved coordination between systems in support of ongoing control. Lessons drawn from China's experience are applied to the current global movement to reduce the burden of helminthiases, where surveillance capacity based on improved diagnostics is urgently needed.