Isolation and characterization of Chlamydia felis and its pathogenesis in cats.

Feline upper respiratory tract disease (URTD) is a common but complicated disease that occurs in domestic cats, worldwide. 396 cats in Guangxi Province, China were screened for URTD-associated pathogens from March 2022 to August 2023. Mycoplasma felis was found to be the most prevalent infectious agent with a positivity rate of 24.75 %, followed by feline calicivirus (FCV), Chlamydia felis, feline herpesvirus 1 (FHV-1) and feline influenza A virus (FeIAV) with rates of 15.91, 11.62, 5.56 and 1.52 %, respectively. In particular, C. felis and M. felis were found in 13 of 55 co-infected cats. Of the 46 C. felis-positive samples, one strain, named as GXNN36, was successfully isolated using chicken embryos and it was characterized both in vivo and in vitro. For the cat studies, both high- and low-dose challenged groups showed severe conjunctivitis, accompanied by transient fever and respiratory symptoms. C. felis replicated well in turbinate, trachea and lung tissues with high copy numbers and the infection subsequently spread to the livers, spleens, pancreas, kidneys, hearts and intestines. These findings will help our understanding of the role of C. felis in feline URTD and provide a valuable model to evaluate the efficacy of vaccines and therapeutic remedies in the future.

Metal-bonded perovskite lead hydride with phonon-mediated superconductivity exceeding 46 K under ambient pressure.

In the search for high-temperature superconductivity in hydrides, a plethora of multi-hydrogen superconductors have been theoretically predicted, and some have been synthesized experimentally under ultrahigh pressures of several hundred GPa. However, the impracticality of these high-pressure methods has been a persistent issue. In response, we propose a new approach to achieve high-temperature superconductivity under ambient pressure by implanting hydrogen into lead to create a stable few-hydrogen binary perovskite, Pb4H. This approach diverges from the popular design methodology of multi-hydrogen covalent high critical temperature (Tc) superconductors under ultrahigh pressure. By solving the anisotropic Migdal-Eliashberg equations, we demonstrate that perovskite Pb4H presents a phonon-mediated superconductivity exceeding 46 K with inclusion of spin-orbit coupling, which is six times higher than that of bulk Pb (7.22 K) and comparable to that of MgB2, the highestTcachieved experimentally at ambient pressure under the Bardeen, Cooper, and Schrieffer framework. The highTccan be attributed to the strong electron-phonon coupling strength of 2.45, which arises from hydrogen implantation in lead that induces several high-frequency optical phonon modes with a relatively large phonon linewidth resulting from H atom vibration. The metallic-bonding in perovskite Pb4H not only improves the structural stability but also guarantees better ductility than the widely investigated multi-hydrogen, iron-based and cuprate superconductors. These results suggest that there is potential for the exploration of new high-temperature superconductors under ambient pressure and may reignite interest in their experimental synthesis in the near future.

NHE3 inhibitor tenapanor maintains intestinal barrier function, decreases visceral hypersensitivity, and attenuates TRPV1 signaling in colonic sensory neurons.

The pathogenesis of irritable bowel syndrome (IBS) is multifactorial, characterized in part by increased intestinal permeability, and visceral hypersensitivity. Increased permeability is associated with IBS severity and abdominal pain. Tenapanor is FDA-approved for the treatment of IBS with constipation (IBS-C) and has demonstrated improvements in bowel motility and a reduction in IBS-related pain; however, the mechanism by which tenapanor mediates these functions remains unclear. Here, the effects of tenapanor on colonic pain signaling and intestinal permeability were assessed through behavioral, electrophysiological, and cell culture experiments. Intestinal motility studies in rats and humans demonstrated that tenapanor increased luminal sodium and water retention and gastrointestinal transit versus placebo. A significantly reduced visceral motor reflex (VMR) to colonic distension was observed with tenapanor treatment versus vehicle in two rat models of visceral hypersensitivity (neonatal acetic acid sensitization and partial restraint stress; both P < 0.05), returning VMR responses to that of nonsensitized controls. Whole cell voltage patch-clamp recordings of retrogradely labeled colonic dorsal root ganglia (DRG) neurons from sensitized rats found that tenapanor significantly reduced DRG neuron hyperexcitability to capsaicin versus vehicle (P < 0.05), an effect not mediated by epithelial cell secretions. Tenapanor also attenuated increases in intestinal permeability in human colon monolayer cultures caused by incubation with proinflammatory cytokines (P < 0.001) or fecal supernatants from patients with IBS-C (P < 0.005). These results support a model in which tenapanor reduces IBS-related pain by strengthening the intestinal barrier, thereby decreasing permeability to macromolecules and antigens and reducing DRG-mediated pain signaling.NEW & NOTEWORTHY A series of nonclinical experiments support the theory that tenapanor inhibits IBS-C-related pain by strengthening the intestinal barrier. Tenapanor treatment reduced visceral motor responses to nonsensitized levels in two rat models of hypersensitivity and reduced responses to capsaicin in sensitized colonic nociceptive dorsal root ganglia neurons. Intestinal permeability experiments in human colon monolayer cultures found that tenapanor attenuates increases in permeability induced by either inflammatory cytokines or fecal supernatants from patients with IBS-C.

Reassortant H9N2 canine influenza viruses containing the pandemic H1N1/2009 ribonucleoprotein complex circulating in pigs acquired enhanced virulence in mice.

The reassortment between avian H9N2 and Eurasian avian-like (EA) H1N1 viruses may have potentially changed from avian-to-mammals adaptation. This study generated 20 reassortant viruses with the introduction of H1N1/2009 internal genes from EA H1N1 virus into H9N2 virus. 12 of these recovered the replication capability both in the lungs and turbinate samples. 10 of 12 obtained PA gene segments from the ribonucleoprotein (RNP) complexes of the EA H1N1 virus, and 3 exhibited extreme virulence. Specially, the combination of PB2, PA and NP genes could overcome the species-specific restriction in human cells. Analysis of the polymerase activities found that introduction of the PA gene resulted in increased polymerase activity. These findings indicated that RNP complexes from EA H1N1 virus could confer an adaptation advantage and high compatibility to avian H9N2 virus. This raises new concerns for public health due to the possible coexistence of H9N2 and EA H1N1 viruses in dogs.

Composite Object Relation Modeling for Few-Shot Scene Recognition.

The goal of few-shot image recognition is to classify different categories with only one or a few training samples. Previous works of few-shot learning mainly focus on simple images, such as object or character images. Those works usually use a convolutional neural network (CNN) to learn the global image representations from training tasks, which are then adapted to novel tasks. However, there are many more abstract and complex images in real world, such as scene images, consisting of many object entities with flexible spatial relations among them. In such cases, global features can hardly obtain satisfactory generalization ability due to the large diversity of object relations in the scenes, which may hinder the adaptability to novel scenes. This paper proposes a composite object relation modeling method for few-shot scene recognition, capturing the spatial structural characteristic of scene images to enhance adaptability on novel scenes, considering that objects commonly co- occurred in different scenes. In different few-shot scene recognition tasks, the objects in the same images usually play different roles. Thus we propose a task-aware region selection module (TRSM) to further select the detected regions in different few-shot tasks. In addition to detecting object regions, we mainly focus on exploiting the relations between objects, which are more consistent to the scenes and can be used to cleave apart different scenes. Objects and relations are used to construct a graph in each image, which is then modeled with graph convolutional neural network. The graph modeling is jointly optimized with few-shot recognition, where the loss of few-shot learning is also capable of adjusting graph based representations. Typically, the proposed graph based representations can be plugged in different types of few-shot architectures, such as metric-based and meta-learning methods. Experimental results of few-shot scene recognition show the effectiveness of the proposed method.

Lithiophilic Zn3N2-Modified Cu Current Collectors by a Novel FCVA Technology for Stable Anode-Free Lithium Metal Batteries.

Anode-free lithium metal batteries (AFLMBs) offer high-energy-density battery systems, but their commercial viability is hindered by irregular lithium dendrite growth and "dead Li" formation caused by current collector defects. This study employed filtered cathode vacuum arc (FCVA) technology to fabricate Cu current collectors (CCs) with a lithiophilic Zn3N2 film. This advanced preparation process ensures an evenly distributed film that reduces the nucleation overpotential, homogenizes the interfacial electric field during plating/stripping processes, inhibits lithium dendrite growth, and forms a stable solid-electrolyte interphase (SEI). Our results show that the advanced Zn3N2@Cu CCs exhibit superior performance with a high CE of above 99.3% after 230 cycles at a current density of 0.5 mA cm-2 and an area capacity of 1 mAh cm-2. Additionally, Li-Zn3N2@Cu||Li-Zn3N2@Cu symmetrical cells had a longer stable cycle time of over 1000 h than that of Li||Li and Li-Cu||Li-Cu symmetrical cells at a current density of 1 mA cm-2 and an area capacity of 2 mAh cm-2. Compared with bare Cu CCs, the capacity retention rate is increased from 14.9 to 63.1% after 100 cycles with a 0.5C rate in the AFLMBs with LFP as the cathode. This work provides a pioneering, eco-friendly, and effective solution for the fabrication of anode CCs in AFLMBs, addressing a significant challenge in their commercial application.

Enhancement for phonon-mediated superconductivity up to 37 K in few-hydrogen metal-bonded layered magnesium hydride under atmospheric pressure.

The discovery of superconductivity in layered MgB2 has renewed interest in the search for high-temperature conventional superconductors, leading to the synthesis of numerous hydrogen-dominated materials with high critical temperatures (Tc) under high pressures. However, achieving a high-Tc superconductor under ambient pressure remains a challenging goal. In this study, we propose a novel approach to realize a high-temperature superconductor under ambient pressure by introducing a hexagonal H monolayer into the hexagonal close-packed magnesium lattice, resulting in a new and stable few-hydrogen metal-bonded layered magnesium hydride (Mg4)2H1. This compound exhibits superior ductility compared to multi-hydrogen, cuprate, and iron-based superconductors due to its metallic bonding. Our unconventional strategy diverges from the conventional design principles used in hydrogen-dominated covalent high-temperature superconductors. Using anisotropic Migdal-Eliashberg equations, we demonstrate that the stable (Mg4)2H1 compound is a typical phonon-mediated superconductor, characterized by strong electron-phonon coupling and an excellent Tc of 37 K under ambient conditions, comparable to that of MgB2. Our findings not only present a new pathway for exploring high-temperature superconductors but also provide valuable insights for future experimental synthesis endeavors.

Dataset Bias in Few-Shot Image Recognition.

The goal of few-shot image recognition (FSIR) is to identify novel categories with a small number of annotated samples by exploiting transferable knowledge from training data (base categories). Most current studies assume that the transferable knowledge can be well used to identify novel categories. However, such transferable capability may be impacted by the dataset bias, and this problem has rarely been investigated before. Besides, most of few-shot learning methods are biased to different datasets, which is also an important issue that needs to be investigated deeply. In this paper, we first investigate the impact of transferable capabilities learned from base categories. Specifically, we use the relevance to measure relationships between base categories and novel categories. Distributions of base categories are depicted via the instance density and category diversity. The FSIR model learns better transferable knowledge from relevant training data. In the relevant data, dense instances or diverse categories can further enrich the learned knowledge. Experimental results on different sub-datasets of Imagenet demonstrate category relevance, instance density and category diversity can depict transferable bias from distributions of base categories. Second, we investigate performance differences on different datasets from the aspects of dataset structures and different few-shot learning methods. Specifically, we introduce image complexity, intra-concept visual consistency, and inter-concept visual similarity to quantify characteristics of dataset structures. We use these quantitative characteristics and eight few-shot learning methods to analyze performance differences on multiple datasets. Based on the experimental analysis, some insightful observations are obtained from the perspective of both dataset structures and few-shot learning methods. We hope these observations are useful to guide future few-shot learning research on new datasets or tasks. Our data is available at http://123.57.42.89/dataset-bias/dataset-bias.html.

Synergistic HA and NS mutations enhanced the virulence of a mouse-adapted H1N1 influenza A virus.

H1N1 reassortants between the swine Eurasian avian-like (EA) and H1N1 2009 pandemic (H1N1 pdm/09) viruses have been circulating stably in pig populations for more than ten years, and they may have contributed to increased human infections. Whether these H1N1 viruses acquire adaptive mutations to increase their pathogenicity towards a new host is unknown. To address this problem, mouse-adapted (MA) variants of swine-origin EA H1N1 influenza virus isolated from dogs (A/canine/Guangxi/LZ57/2015[LZ57-MA]) were generated by serial lung-to-lung passages in BALB/c mice. These exhibited greater virulence and replication capability than the wild-type virus (LZ57-WT). Of the six adaptive mutations, two were mapped to the ribonucleoprotein (RNP) complex (PB2-E578D and PA-T97I), two to hemagglutinin (HA-N198D and HA-A227E) and two to the non-structural protein 1 (NS1) and nuclear export protein (NS1-A53D and NEP-R42K, respectively). Reverse genetic substitution of the viral genes and mutation experiments demonstrated that the mutations in PA-T97I could enhance the polymerase activity, but a significant downregulation of activity was seen with PB2-E578D, which was consistent with a decrease in virulence. However, HA and NS, which are genes that act synergistically, were found to be determinants of virulence in mice. The reassortant viruses bearing HA mutations (N198D and A227E) were acquired during adaptation enhanced early-stage viral replication in mammalian cells. The single-point mutations in the NS genes had limited effects on virulence. Furthermore, a combination of HA (N198D and A227E) with NS(A53D) in the rLZ57-WT backbone resulted in efficient replication and a significant increase in virulence. The results suggest that these substitutions could compensate for the polymerase function and contribute to enhanced virulence, which highlights a major role for mutations in the HA and NS genes.

2D Graphene-Like Pb-Free Perovskite Semiconductor CsSb(Br1-xIx)4 with Quasi-linear Electronic Dispersion and Direct Bandgap Close to Germanium.

Thanks to its ultrahigh carrier mobility (∼104-105 cm2 V-1 s-1), graphene shows tremendous application potential in nanoelectronics, but it cannot be applied in effective field-effect transistors (FETs) because of its intrinsic gapless band structure. Thus, introducing a bandgap for graphene is a prerequisite to realize an FET for logic applications. Herein, through first-principles GW calculations, we have predicted a series of novel Dion-Jacobson (DJ) phase halide perovskite semiconductors CsSb(Br1-xIx)4 (x = 0, 0.5, 1) with the quasi-linear (graphene-like) band edge dispersion; as the best one of which, CsSbBr2I2 exhibits a direct bandgap (0.52 eV) as well as a quasi-linear electronic dispersion, yielding an ultrasmall carrier effective mass (0.03 m0) and a high estimated carrier mobility (5 × 103 cm2 V-1 s-1). This gives a significant reference to the exploration of semiconductors with excellent transport properties. Moreover, our calculations also implicate that the DJ perovskites CsSb(Br1-xIx)4 (x = 0, 0.25, 0.5, 0.75, 1) show soft and anisotropic mechanical characteristics as well as excellent electronic, transport, and optical properties, which demonstrate their multifunctional application in infrared optoelectronic, high-speed electronics, and photovoltaics.

High hydrogen production in the InSe/MoSi2N4 van der Waals heterostructure for overall water splitting.

Very recently, the septuple-atomic-layer MoSi2N4 has been successfully synthesized by a chemical vapor deposition method. However, pristine MoSi2N4 exhibits some shortcomings, including poor visible-light harvesting capability and a low separation rate of photo-excited electron-hole pairs, when it is applied in water splitting to produce hydrogen. Fortunately, we find that MoSi2N4 can be considered as a good co-catalyst to be stacked with InSe forming an efficient heterostructure photocatalyst. Here, the electronic and photocatalytic properties of the two-dimensional (2D) InSe/MoSi2N4 heterostructure have been systematically investigated by density functional theory for the first time. The results demonstrate that 2D InSe/MoSi2N4 has a type-II band alignment with a favourable direct bandgap of 1.61 eV and exhibits suitable band edge positions for overall water splitting. Particularly, 2D InSe/MoSi2N4 has high electron mobility (104 cm2 V-1 s-1) and shows a noticeable optical absorption coefficient (105 cm-1) in the visible-light region of the solar spectrum. These brilliant properties declare that 2D InSe/MoSi2N4 is a potential photocatalyst for overall water splitting.

Layered Dion-Jacobson-Type Chalcogenide Perovskite CsLaM2X7 (M = Ta/Nb; X = S/Se) with a Narrow Band Gap of ∼1 eV as a Promising Rear Cell for All-Perovskite Tandem Solar Cells.

Perovskite-perovskite tandem solar cells have bright prospects to improve the power conversion efficiency (PCE) beyond the Shockley-Queisser (SQ) limit of single-junction solar cells. The star lead-based halide perovskites are well-recognized as suitable candidates for the front cell, thanks to their suitable band gap (∼1.8 eV), strong optical absorption, and high certified PCE. However, the toxicity of lead for the front cell and the lack of a narrow band gap (∼1.1 eV) for the rear cell seriously restrict the development of the two-junction tandem cell. To break through this bottleneck, a novel Dion-Jacobson (DJ)-type (n = 2) chalcogenide perovskite CsLaM2X7 (M = Ta, Nb; X = S, Se) has been found based on the powerful first-principles and advanced many-body perturbation GW calculations. Their excellent electronic, transport, and optical properties can be summarized as follows. (1) They are stable and environmentally friendly lead-free materials. (2) The direct band gap of CsLaTa2Se7 (0.96-1.10 eV) is much smaller than those of lead-based halide perovskites and very suitable for the rear cell in the two-junction tandem cell. (3) The carrier mobility in CsLaTa2Se7 reaches 1.6 × 103 cm2 V-1 s-1 at room temperature. (4) The absorption coefficients (3-5 × 105 cm-1) are 1 order higher than that of Si (104 cm-1). (5) The estimated PCEs of the Cs2Sb2Br8-CsLaTa2Se7 tandem cell (33.3%) and the concentrator solar cell (35.8% in 100 suns) are higher than those of the best recorded GaAs-Si tandem cell (32.8%) and the perovskite-perovskite tandem solar cell (24.8%). These energetic results strongly demonstrate that the novel lead-free chalcogenide perovskites CsLaM2X7 are good candidates for the rear cell of tandem cells.

Cadmium Induces Acute Liver Injury by Inhibiting Nrf2 and the Role of NF-κB, NLRP3, and MAPKs Signaling Pathway.

Acute Cadmium (Cd) exposure usually induces hepatotoxicity. It is well known that oxidative stress and inflammation causes Cd-induced liver injury. However, the effect of nuclear factor erythroid 2-related factor 2 (Nrf2) in Cd-induced liver injury is not completely understood. In this study, we observed Cd-induced liver damage and the potential contribution of Nrf2, nuclear factor-κB (NF-κB), Nod-like receptor 3 (NLRP3), and mitogen-activated protein kinases (MAPKs) signaling pathways. Changes in serum transaminases and proinflammatory cytokines expression showed that Cd could induce acute hepatotoxicity. Moreover, Nrf2 and its downstream heme oxygenase 1 (HO-1) were inhibited by Cd exposure, and Kelch-like ECH-associated protein 1 (Keap1), the inhibitory protein of Nrf2, was increased. Furthermore, NF-κB, NLRP3, and MAPKs signaling pathways were all activated by Cd intoxication. In conclusion, the inhibition of Nrf2, HO-1, and the activation of NF-κB, NLRP3, and MAPKs all contribute to Cd-induced liver injury.

Estimation of maize above-ground biomass based on stem-leaf separation strategy integrated with LiDAR and optical remote sensing data.

Above-ground biomass (AGB) is an important indicator for effectively assessing crop growth and yield and, in addition, is an important ecological indicator for assessing the efficiency with which crops use light and store carbon in ecosystems. However, most existing methods using optical remote sensing to estimate AGB cannot observe structures below the maize canopy, which may lead to poor estimation accuracy. This paper proposes to use the stem-leaf separation strategy integrated with unmanned aerial vehicle LiDAR and multispectral image data to estimate the AGB in maize. First, the correlation matrix was used to screen optimal the LiDAR structural parameters (LSPs) and the spectral vegetation indices (SVIs). According to the screened indicators, the SVIs and the LSPs were subjected to multivariable linear regression (MLR) with the above-ground leaf biomass (AGLB) and above-ground stem biomass (AGSB), respectively. At the same time, all SVIs derived from multispectral data and all LSPs derived from LiDAR data were subjected to partial least squares regression (PLSR) with the AGLB and AGSB, respectively. Finally, the AGB was computed by adding the AGLB and the AGSB, and each was estimated by using the MLR and the PLSR methods, respectively. The results indicate a strong correlation between the estimated and field-observed AGB using the MLR method (R 2 = 0.82, RMSE = 79.80 g/m2, NRMSE = 11.12%) and the PLSR method (R 2 = 0.86, RMSE = 72.28 g/m2, NRMSE = 10.07%). The results indicate that PLSR more accurately estimates AGB than MLR, with R 2 increasing by 0.04, root mean square error (RMSE) decreasing by 7.52 g/m2, and normalized root mean square error (NRMSE) decreasing by 1.05%. In addition, the AGB is more accurately estimated by combining LiDAR with multispectral data than LiDAR and multispectral data alone, with R 2 increasing by 0.13 and 0.30, respectively, RMSE decreasing by 22.89 and 54.92 g/m2, respectively, and NRMSE decreasing by 4.46% and 7.65%, respectively. This study improves the prediction accuracy of AGB and provides a new guideline for monitoring based on the fusion of multispectral and LiDAR data.

Optimized band gap and fast interlayer charge transfer in two-dimensional perovskite oxynitride Ba2NbO3N and Sr2NbO3/Ba2NbO3N bonded heterostructure visible-light photocatalysts for overall water splitting.

Searching for promising visible-light photocatalysts for overall water splitting into hydrogen and oxygen is a very challenging task to solve the energy crisis and environment pollution. The widely-used tantalate and niobate perovskite photocatalysts have two drawbacks, i.e., the large energy band gap (∼3.2-4.6 eV) and low electron (hole) mobility 102 (101) cm2 V-1 s-1, which greatly limit their photocatalytic performance. Here, based on the powerful first-principles and accurate GW calculations, we design several novel two-dimensional (2D) Ruddlesden-Popper (RP) type (n = 1) perovskite oxynitrides A2BO3N (A = Ca, Sr, Ba and B = Ta, Nb) and their bonded heterostructures and comprehensively investigate their interlayer coupling, electronic structures, transport and photocatalytic characteristics. We find that 2D A2BO3N oxynitrides have a reduced direct band gap at Γ-point, especially for three-layer (3L) Ba2NbO3N and 1L-Sr2NbO3N/1L-Ba2NbO3N bonded heterostructure with the optimized band gap ∼2.0 eV. Compared with tantalate and niobate perovskite oxides, the electron (hole) mobility increases 1-2 orders of magnitude up to 103-104 (102-103) cm2 V-1 s-1. A fast electron-hole vertical transport across the heterointerface and remarkable electron-hole separation can be realized in 1L-Sr2NbO3N/1L-Ba2NbO3N bonded heterostructure due to its strong interface Ba-O and Sr-O bonds and type-II band offset. Compared with the well-known photocatalysts, such as BiVO4 and MoS2/g-C3N4, an improved optical absorption (8 × 104 cm-1) in A2BO3N is obtained in the visible region. The 2D RP-type perovskite oxynitrides 3L-Ba2NbO3N and 1L-Sr2NbO3N/1L-Ba2NbO3N are powerful visible-light photocatalysts for overall water splitting.

Class Agnostic Image Common Object Detection.

Learning similarity of two images is an important problem in computer vision and has many potential applications. Most of previous works focus on generating image similarities in three aspects: global feature distance computing, local feature matching and image concepts comparison. However, the task of directly detecting class agnostic common objects from two images has not been studied before, which goes one step further to capture image similarities at region level. In this paper, we propose an end-to-end Image Common Object Detection Network (CODN) to detect class agnostic common objects from two images. The proposed method consists of two main modules: locating module and matching module. The locating module generates candidate proposals of each two images. The matching module learns the similarities of the candidate proposal pairs from two images, and refines the bounding boxes of the candidate proposals. The learning procedure of CODN is implemented in an integrated way and a multi-task loss is designed to guarantee both region localization and common object matching. Experiments are conducted on PASCAL VOC 2007 and COCO 2014 datasets. Experimental results validate the effectiveness of the proposed method.

Individual-level modifiers of the acute effects of air pollution on mortality in Wuhan, China.

BACKGROUND: Ambient air pollution has posed negative effects on human health. Individual-level factors may modify this effect, but previous studies have controversial conclusions, and evidence is lacking especially in developing countries. This study aims to examine the modifying effects of sex, age, and education level of individuals on the associated between daily mortality and air pollutants, including particulate matter < 10 µm in aerodynamic diameter (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2). METHODS: Time-series analysis was conducted to investigate the acute effects of the air pollution on daily mortality from January 2002 to December 2010 in Wuhan, China. Generalized Additive Models (GAM) were used to examine the association stratified by sex for non-accidental, cardiovascular, and respiratory mortality. For non-accidental mortality, stratified analysis was also conducted by age and educational level. RESULTS: Outdoor air pollution was associated with daily non-accidental and cardiovascular mortality. An increase of 10 µg/m3 in a 2-day average concentration of PM10, SO2, and NO2 was corresponding to the increase in non-accidental mortality of 0.29% (95%CI: 0.06-0.53%), 1.22% (95%CI: 0.77-1.67%) and 1.60% (95%CI: 1.00-2.19%), respectively. The effects of air pollution were faster in females than males. The magnitude of the estimates was higher for females with low education, aged 65-75 years for PM10 and < 65 years for SO2. To be more specific, we observed that per 10 µg/m3 increase in SO2 was association with increases in non-accidental mortality of 2.03% (95%CI: 1.38-2.67) for all females and 3.10% (95%CI: 2.05-4.16) for females with low education. CONCLUSION: Females and people with low-education are more susceptible to the effect of air pollution, which would provide a sound scientific basis for determination of air pollution standards.

Neuronal Transforming Growth Factor beta Signaling via SMAD3 Contributes to Pain in Animal Models of Chronic Pancreatitis.

BACKGROUND & AIMS: Chronic pancreatitis (CP) is characterized by pancreatic inflammation and fibrosis, associated with increased pancreatic expression of transforming growth factor beta (TGFB). It is not clear how these might contribute to pain. We investigated whether TGFB signaling via SMAD induces sensitization of pancreatic sensory neurons to increase nociception. METHODS: CP was induced in Sprague-Dawley rats by infusion of trinitrobenzene sulfonic acid; some rats were given intrathecal infusions of TGFB1. CP was induced in control mice by administration of cerulein; we also studied ß1glo/Ptf1acre-ER mice, which on induction overexpress TGFB1 in pancreatic acinar cells, and TGFBr1f/f-CGRPcreER mice, which have inducible disruption of TGFBr1 in calcitonin gene-related peptide-positive neurons. Dominant negative forms of human TGFBR2 and SMAD3 were overexpressed from viral vectors in rat pancreas. Some rats were given the SMAD3 inhibitors SIS3 or halofuginone. After induction of CP, mice were analyzed for pain in behavior tests or electrophysiologic studies of sensory neurons. Pancreatic nociceptor excitability was examined by patch-clamp techniques and nociception was measured by Von Frey Filament tests for referred somatic hyperalgesia and behavioral responses to pancreatic electrical stimulation. Pancreata were collected from mice and rats and analyzed histologically and by enzyme-linked immunosorbent assay and immunohistochemistry. RESULTS: Overexpression of TGFB in pancreatic acinar cells of mice and infusion of TGFB1 into rats resulted in sensory neuron hyperexcitability, SMAD3 activation, and increased nociception. This was accompanied by a reduction in the transient A-type current in pancreas-specific sensory neurons in rats, a characteristic of nociceptive sensitization in animal models of CP. Conversely, pancreata from TGFBr1f/f-CGRPcreER mice, rats with pancreatic expression of dominant negative forms of human TGFBR2 or SMAD3, and rats given small molecule inhibitors of SMAD3 had attenuated neuronal sensitization and pain behavior following induction of CP. In contrast to findings from peripheral administration of TGFB1, intrathecal infusion of TGFB1 reduced hyperalgesia in rats with CP. CONCLUSIONS: In pancreata of mice and rats, TGFB promotes peripheral nociceptive sensitization via a direct effect on primary sensory neurons mediated by intra-neuronal SMAD3. This is distinct from the central nervous system, where TGFB reduces nociception. These results provide an explanation for the link between fibrosis and pain in patients with CP. This signaling pathway might be targeted therapeutically to reduce pain in patients with CP.

Modulation of electronic and magnetic properties in InSe nanoribbons: edge effect.

Quite recently, the two-dimensional (2D) InSe nanosheet has become a hot material with great promise for advanced functional nano-devices. In this work, for the first time, we perform first-principles calculations on the structural, electronic, magnetic and transport properties of 1D InSe nanoribbons with/without hydrogen or halogen saturation. We find that armchair ribbons, with various edges and distortions, are all nonmagnetic semiconductors, with a direct bandgap of 1.3 (1.4) eV for bare (H-saturated) ribbons, and have the same high electron mobility of about 103 cm2V-1s-1 as the 2D InSe nanosheet. Zigzag InSe nanoribbons exhibit metallic behavior and diverse intrinsic ferromagnetic properties, with the magnetic moment of 0.5-0.7 µ B per unit cell, especially for their single-edge spin polarization. The edge spin orientation, mainly dominated by the unpaired electrons of the edge atoms, depends sensitively on the edge chirality. Hydrogen or halogen saturation can effectively recover the structural distortion, and modulate the electronic and magnetic properties. The binding energy calculations show that the stability of InSe nanoribbons is analogous to that of graphene and better than in 2D InSe nanosheets. These InSe nanoribbons, with novel electronic and magnetic properties, are thus very promising for use in electronic, spintronic and magnetoresistive nano-devices.