Ynamide Coupling Reagents: Origin and Advances.

Since the pioneering work of Curtius and Fischer, chemical peptide synthesis has witnessed a century's development and evolved into a routine technology. However, it is far from perfect. In particular, it is challenged by sustainable development because the state-of-the-art of peptide synthesis heavily relies on legacy reagents and technologies developed before the establishment of green chemistry. Over the past three decades, a broad range of efforts have been made for greening peptide synthesis, among which peptide synthesis using unprotected amino acid represents an ideal and promising strategy because it does not require protection and deprotection steps. Unfortunately, C → N peptide synthesis employing unprotected amino acids has been plagued by undesired polymerization, while N → C inverse peptide synthesis with unprotected amino acids is retarded by severe racemization/epimerization owing to the iterative activation and aminolysis of high racemization/epimerization susceptible peptidyl acids. Consequently, there is an urgent need to develop innovative coupling reagents and strategies with novel mechanisms that can address the long-standing notorious racemization/epimerization issue of peptide synthesis.This Account will describe our efforts in discovery of ynamide coupling reagents and their application in greening peptide synthesis. Over an eight-year journey, ynamide coupling reagents have evolved into a class of general coupling reagents for both amide and ester bond formation. In particular, the superiority of ynamide coupling reagents in suppressing racemization/epimerization enabled them to be effective for peptide fragment condensation, and head-to-tail cyclization, as well as precise incorporation of thioamide substitutions into peptide backbones. The first practical inverse peptide synthesis using unprotected amino acids was successfully accomplished by harnessing such features and taking advantage of a transient protection strategy. Ynamide coupling reagent-mediated ester bond formation enabled efficient intermolecular esterification and macrolactonization with preservation of α-chirality and the configuration of the conjugated α,ß-C-C double bond. To make ynamide coupling reagents readily available with reasonable cost and convenience, we have developed a scalable one-step synthetic method from cheap starting materials. Furthermore, a water-removable ynamide coupling reagent was developed, offering a column-free purification of the target coupling product. In addition, the recycle of ynamide coupling reagent was accomplished, thereby paving the way for their sustainable industrial application.As such, this Account presents the whole story of the origin, mechanistic insights, preparation, synthetic applications, and recycle of ynamide coupling reagents with a perspective that highlights their future impact on peptide synthesis.

Inverse Peptide Synthesis Using Transient Protected Amino Acids.

Peptide therapeutics have experienced a rapid resurgence over the past three decades. While a few peptide drugs are biologically produced, most are manufactured via chemical synthesis. The cycle of prior protection of the amino group of an α-amino acid, activation of its carboxyl group, aminolysis with the free amino group of a growing peptide chain, and deprotection of the N-terminus constitutes the principle of conventional C → N peptide chemical synthesis. The mandatory use of the Nα-protecting group invokes two additional operations for incorporating each amino acid, resulting in poor step- and atom-economy. The burgeoning demand in the peptide therapeutic market necessitates cost-effective and environmentally friendly peptide manufacturing strategies. Inverse peptide chemical synthesis using unprotected amino acids has been proposed as an ideal and appealing strategy. However, it has remained unsuccessful for over 60 years due to severe racemization/epimerization during N → C peptide chain elongation. Herein, this challenge has been successfully addressed by ynamide coupling reagent employing a transient protection strategy. The activation, transient protection, aminolysis, and in situ deprotection were performed in one pot, thus offering a practical peptide chemical synthesis strategy formally using unprotected amino acids as the starting material. Its robustness was exemplified by syntheses of peptide active pharmaceutical ingredients. It is also amenable to fragment condensation and inverse solid-phase peptide synthesis. The compatibility to green solvents further enhances its application potential in large-scale peptide production. This study offered a cost-effective, operational convenient, and environmentally benign approach to peptides.

Progress of Polymer Electrolytes Worked in Solid-State Lithium Batteries for Wide-Temperature Application.

Solid-state Li-ion batteries have emerged as the most promising next-generation energy storage systems, offering theoretical advantages such as superior safety and higher energy density. However, polymer-based solid-state Li-ion batteries face challenges across wide temperature ranges. The primary issue lies in the fact that most polymer electrolytes exhibit relatively low ionic conductivity at or below room temperature. This sensitivity to temperature variations poses challenges in operating solid-state lithium batteries at sub-zero temperatures. Moreover, elevated working temperatures lead to polymer shrinkage and deformation, ultimately resulting in battery failure. To address this challenge of polymer-based solid-state batteries, this review presents an overview of various promising polymer electrolyte systems. The review provides insights into the temperature-dependent physical and electrochemical properties of polymers, aiming to expand the temperature range of operation. The review also further summarizes modification strategies for polymer electrolytes suited to diverse temperatures. The final section summarizes the performance of various polymer-based solid-state batteries at different temperatures. Valuable insights and potential future research directions for designing wide-temperature polymer electrolytes are presented based on the differences in battery performance. This information is intended to inspire practical applications of wide-temperature polymer-based solid-state batteries.

Factors Affecting the Situational Awareness of Armored Vehicle Occupants.

In the field of armored vehicles, up to 70% of accidents are associated with low levels of situational awareness among the occupants, highlighting the importance of situational awareness in improving task performance. In this study, we explored the mechanisms influencing situational awareness by simulating an armored vehicle driving platform with 14 levels of experimentation in terms of five factors: experience, expectations, attention, the cueing channel, and automation. The experimental data included SART and SAGAT questionnaire scores, eye movement indicators, and electrocardiographic and electrodermal signals. Data processing and analysis revealed the following conclusions: (1) Experienced operators have higher levels of situational awareness. (2) Operators with certain expectations have lower levels of situational awareness. (3) Situational awareness levels are negatively correlated with information importance affiliations and the frequency of anomalous information in non-primary tasks. (4) Dual-channel cues lead to higher levels of situational awareness than single-channel cues. (5) Operators' situational awareness is lower at high automation levels.

De-Escalation Dual Antiplatelet Therapy Prevail over Potent P2Y12 Inhibitor Monotherapy in Patients with Acute Coronary Syndrome Undergone Percutaneous Coronary Intervention: A Network Meta-Analysis.

Background: Dual antiplatelet therapy (DAPT) with potent P2Y12 inhibitor is the cornerstone of acute coronary syndrome (ACS) management. Balancing the effects of different strategies of antiplatelet therapy including DAPT de-escalation, potent P2Y12 inhibitor monotherapy, and conventional DAPT is a hot topic. Methods: A systematic search was conducted from the MEDLINE, PubMed, and Embase through October 2021 to identify various DAPT strategies in randomized controlled trials (RCTs) for treatment of ACS patients after undergoing PCI with drug-eluting stent (DES). The network meta-analysis was performed to investigate the net clinic benefit of the DAPT de-escalation, potent P2Y12 inhibitor monotherapy, as well as conventional DAPT. The primary outcome was net adverse clinical events, defined as a composite of major bleeding and cardiac death, myocardial infarction, stroke, stent thrombosis, or target-vessel revascularization. The secondary outcomes include major adverse cardiac events and trial-defined major or minor bleeding. Results: A total of 14 RCTs with 63,982 patients were included. The DAPT de-escalation was associated with a lower risk of the primary outcome compared with potent P2Y12 inhibitor monotherapy (De-escalation vs monotherapy odds ratio (OR): 0.72 95% confidence interval (CI): 0.55-0.96), and other antiplatelet strategies (De-escalation vs clopidogrel + aspirin OR: 0.49 95% CI: 0.39-0.63; De-escalation vs prasugrel + aspirin OR: 0.76 95% CI: 0.59-0.98; De-escalation vs ticagrelor + aspirin OR: 0.76 95% CI: 0.55-0.90). There were no statistical differences in the incidence of bleeding (DAPT de-escalation vs P2Y12 inhibitor monotherapy OR: 0.73 95% CI: 0.47-1.12) and major adverse cardiac events (DAPT de-escalation vs P2Y12 inhibitor monotherapy OR: 0.79 95% CI: 0.59-1.08) between DAPT de-escalation and potent P2Y12 inhibitor monotherapy. Conclusions: This network meta-analysis showed that DAPT de-escalation would reduce the net adverse clinical events, compared with potent P2Y12 inhibitor monotherapy, for ACS patients undergone PCI treatment.

Edge-enhanced infrared image super-resolution reconstruction model under transformer.

Infrared images have important applications in military, security and surveillance fields. However, limited by technical factors, the resolution of infrared images is generally low, which seriously limits the application and development of infrared images in various fields. To address the problem of difficult recovery of edge information and easy ringing effect in the super-resolution reconstruction process of infrared images, an edge-enhanced infrared image super-resolution reconstruction model TESR under transformer is proposed. The main structure of this model is transformer. First, in view of the problem of difficult recovery of edge information of infrared images, an edge detection auxiliary network is designed, which can obtain more accurate edge information from the input low-resolution images and enhance the edge details during image reconstruction; then, the CSWin Transformer is introduced to compute the self-attention of horizontal and vertical stripes in parallel, so as to increase the receptive field of the model and enable it to utilize features with higher semantic levels. The super-resolution reconstruction model proposed in this paper can extract more comprehensive image information, and at the same time, it can obtain more accurate edge information to enhance the texture details of super-resolution images, and achieve better reconstruction results.

Carbon emissions of power transmission and transformation projects in the whole life cycle for smart sustainable energy systems.

The study investigates the optimization of life cycle carbon emissions in smart sustainable energy systems through power transformation and transmission project power load predictions. Firstly, a multi-task learning-based short-term user load forecasting technique is developed, where the power load curves of multiple residential customers are grouped and classified using the K-means clustering method. Additionally, the Bidirectional Long Short-Term Memory (BiLSTM) technique is introduced to anticipate the power load intelligently. Secondly, a life cycle carbon emission assessment model for the power transmission and transformation project (PTTP) is constructed based on the life cycle assessment (LCA) method, which divides the project's life cycle into four stages: production, installation and construction, operation and maintenance, and demolition. Finally, an experimental evaluation of this model is conducted. The results demonstrate that compared with the baseline model Long Short-Term Memory (LSTM), this model achieves a significantly lower average Mean Absolute Error (MAE) at 3.62% while achieving significantly higher accuracy in power load forecasting at 94.34%. A comprehensive examination of carbon emissions across all four phases reveals that overall carbon emissions are highest during the operation and maintenance stage followed by the equipment production stage and installation/construction stage, with the lowest overall carbon emissions observed. Hence, this study endeavors to forecast power load demand with precision and identify the principal determinants of carbon emissions in power engineering. By discerning and managing these key factors, an optimal, energy-efficient intelligent power load scheme can be derived.

JIMR: Joint Semantic and Geometry Learning for Point Scene Instance Mesh Reconstruction.

Point scene instance mesh reconstruction is a challenging task since it requires both scene-level instance segmentation and instance-level mesh reconstruction from partial observations simultaneously. Previous works either adopt a detection backbone or a segmentation one, and then directly employ a mesh reconstruction network to produce complete meshes from incomplete instance point clouds. To further boost the mesh reconstruction quality with both local details and global smoothness, in this work, we propose JIMR, a joint framework with two cascaded stages for semantic and geometry understanding. In the first stage, we propose to perform both instance segmentation and object detection simultaneously. By making both tasks promote each other, this design facilitates subsequent mesh reconstruction by providing more precisely-segmented instance points and better alignment benefiting from predicted complete bounding boxes. In the second stage, we propose a complete-then-reconstruct procedure, where the completion module explicitly disentangles completion from reconstruction, and enables the usage of pre-trained weights of existing powerful completion and reconstruction networks. Moreover, we propose a comprehensive confidence score to filter proposals considering the quality of instance segmentation, bounding box detection, semantic classification, and mesh reconstruction at the same time. Experiments show that our proposed JIMR outperforms state-of-the-art methods regarding instance reconstruction qualitatively and quantitatively.

Nosocomial surveillance of multidrug-resistant Acinetobacter baumannii: a genomic epidemiological study.

Acinetobacter baumannii is a major opportunistic pathogen causing hospital-acquired infections, and it is imperative to comprehend its evolutionary and epidemiological dynamics in hospitals to prevent and control nosocomial transmission. Here, we present a comprehensive genomic epidemiological study involving the genomic sequencing and antibiotic resistance profiling of 634 A. baumannii strains isolated from seven intensive care units (ICUs) of a Chinese general hospital over 2 consecutive years. Our study reveals that ST2 is highly dominant (90.54%) in the ICUs, with 98.90% of the ST2 exhibiting multidrug resistant or extensively drug resistant. Phylogenetic analyses of newly sequenced genomes and public data suggest that nosocomial isolates originated outside the hospital but evolved inside. The major lineages appear to be stable, with 9 of the 28 identified nosocomial epidemic clones infecting over 60% of the affected patients. However, outbreaks of two highly evolved clones have been observed in different hospitals, suggesting significant inter-hospital transmission chains. By coupling patient medical records and genomic divergence of the ST2, we found that cross-ward patient transfer played a crucial role in pathogen's nosocomial transmission. Additionally, we identified 831 potential adaptive evolutionary loci and 44 associated genes by grouping and comparing the genomes of clones with different prevalence. Overall, our study provides a comprehensive and contemporary survey on the epidemiology and genomic evolution of A. baumannii in a large Chinese general hospital. These findings shed light on the nosocomial evolution and transmission of A. baumannii and offers valuable information for transmission prevention and antibiotic therapy.IMPORTANCEThis study delved into the genomic evolution and transmission of nosocomial Acinetobacter baumannii on a large scale, spanning both an extended time period and the largest sample size to date. Through molecular epidemiological investigations based on genomics, we can directly trace the origin of the pathogen, detecting and monitoring outbreaks of infectious diseases in a timely manner, and ensuring public health safety. In addition, this study also collects a large amount of genomic and antibiotic resistance detection data, which is helpful for phenotype prediction based on genomic sequencing. It enables patients to receive personalized antibiotic treatment quickly, helps doctors select antibiotics more accurately, and contributes to reducing the use of antibiotics and lowering the risk of antibiotic resistance development.

Potential therapeutic role of spermine via Rac1 in osteoporosis: Insights from zebrafish and mice.

Osteoporosis is a prevalent metabolic bone disease. While drug therapy is essential to prevent bone loss in osteoporotic patients, current treatments are limited by side effects and high costs, necessitating the development of more effective and safer targeted therapies. Utilizing a zebrafish ( Danio rerio) larval model of osteoporosis, we explored the influence of the metabolite spermine on bone homeostasis. Results showed that spermine exhibited dual activity in osteoporotic zebrafish larvae by increasing bone formation and decreasing bone resorption. Spermine not only demonstrated excellent biosafety but also mitigated prednisolone-induced embryonic neurotoxicity and cardiotoxicity. Notably, spermine showcased protective attributes in the nervous systems of both zebrafish embryos and larvae. At the molecular level, Rac1 was identified as playing a pivotal role in mediating the anti-osteoporotic effects of spermine, with P53 potentially acting downstream of Rac1. These findings were confirmed using mouse ( Mus musculus) models, in which spermine not only ameliorated osteoporosis but also promoted bone formation and mineralization under healthy conditions, suggesting strong potential as a bone-strengthening agent. This study underscores the beneficial role of spermine in osteoporotic bone homeostasis and skeletal system development, highlighting pivotal molecular mediators. Given their efficacy and safety, human endogenous metabolites like spermine are promising candidates for new anti-osteoporotic drug development and daily bone-fortifying agents.

Phase stabilization via A-site ion anchoring for ultra-stable perovskite light emitting diodes.

A novel ion anchoring strategy stabilizes the perovskite phase, yielding ambient stable perovskite films and ultra-stable perovskite light-emitting diodes (PeLEDs) with an unprecedented operational half-lifetime over 37.2 years at 100 cd m-2 and exceeding 27% efficiency, marking a new stability benchmark for next-generation display and lighting applications.

Multi-Interface Engineering of MXenes for Self-Powered Wearable Devices.

Self-powered wearable devices with integrated energy supply module and sensitive sensors have significantly blossomed for continuous monitoring of human activity and the surrounding environment in healthcare sectors. The emerging of MXene-based materials has brought research upsurge in the fields of energy and electronics, owing to their excellent electrochemical performance, large surface area, superior mechanical performance, and tunable interfacial properties, where their performance can be further boosted via multi-interface engineering. Herein, a comprehensive review of recent progress in MXenes for self-powered wearable devices is discussed from the aspects of multi-interface engineering. The fundamental properties of MXenes including electronic, mechanical, optical, and thermal characteristics are discussed in detail. Different from previous review works on MXenes, multi-interface engineering of MXenes from termination regulation to surface modification and their impact on the performance of materials and energy storage/conversion devices are summarized. Based on the interfacial manipulation strategies, potential applications of MXene-based self-powered wearable devices are outlined. Finally, proposals and perspectives are provided on the current challenges and future directions in MXene-based self-powered wearable devices.

Enhanced Piezocatalytic Performance of Li-doped BaTiO3 Through a Facile Sonication-Assisted Precipitation Approach.

Piezocatalysis-induced dye degradation has garnered significant attention as an effective method for addressing wastewater treatment challenges. In our study, we employed a room-temperature sonochemical method to synthesize piezoelectric barium titanate nanoparticles (BaTiO3: BTO) with varying levels of Li doping. This approach not only streamlined the sample preparation process but also significantly reduced the overall time required for synthesis, making it a highly efficient and practical method. One of the key findings was the exceptional performance of the Li-doped BTO nanoparticles. With 20 mg of Li additive, we achieved 90 % removal of Rhodamine B (RhB) dye within a relatively short timeframe of 150 minutes, all while subjecting the sample to ultrasonic vibration. This rapid and efficient dye degradation was further evidenced by the calculated kinetic rate constant, which indicated seven times faster degradation rate compared to pure BTO. The enhanced piezoelectric performance observed in the Li-doped BTO nanoparticles can be attributed to the strategic substitution of Li atoms, which facilitated a more efficient transfer of charge charges at the interface. Overall, our study underscores the potential of piezocatalysis coupled with advanced materials like Li-doped BTO nanoparticles as a viable and promising solution for wastewater treatment, offering both efficiency and environmental sustainability.

One-Step Synthesis of Graphene-Covered Silver Nanowires with Enhanced Stability for Heating and Strain Sensing.

Solution-processed silver nanowire (AgNW) networks have been considered as promising electrode candidates for next-generation electronic devices. However, they suffer from poor thermal and electrical stability and low mechanical properties, hindering their practical applications. In this work, graphene nanosheets are successfully introduced into AgNW via a facile one-step solvothermal process. Benefiting from increased conductive paths, the resultant AgNW/graphene films exhibit high electrical conductivity. More importantly, the interlocking NW morphology can be maintained under high temperature and applied voltage due to suppressed Ag migration, which is enabled by the introduction of graphene. This feature leads to enhanced thermal and electrical stability, making them suitable for use as transparent heaters. Furthermore, the composite films present excellent mechanical performance, and negligible resistance change is observed after 10 000 repeated bending cycles. To demonstrate their feasibility toward sensor applications, sandwiched strain sensors are designed, which can endure larger tensile strains and show higher sensitivity and repeatability compared with pure AgNW-based device. Furthermore, various hand gestures can be easily recognized by the resultant sensors based on unique combinations of sensing response. This work not only provides a low-cost method to realize large-scale synthesis of AgNW/graphene composites but also offers guidance to prepare high-performance electrodes for advanced electronics.

Efficient Crowd Counting via Dual Knowledge Distillation.

Most researchers focus on designing accurate crowd counting models with heavy parameters and computations but ignore the resource burden during the model deployment. A real-world scenario demands an efficient counting model with low-latency and high-performance. Knowledge distillation provides an elegant way to transfer knowledge from a complicated teacher model to a compact student model while maintaining accuracy. However, the student model receives the wrong guidance with the supervision of the teacher model due to the inaccurate information understood by the teacher in some cases. In this paper, we propose a dual-knowledge distillation (DKD) framework, which aims to reduce the side effects of the teacher model and transfer hierarchical knowledge to obtain a more efficient counting model. First, the student model is initialized with global information transferred by the teacher model via adaptive perspectives. Then, the self-knowledge distillation forces the student model to learn the knowledge by itself, based on intermediate feature maps and target map. Specifically, the optimal transport distance is utilized to measure the difference of feature maps between the teacher and the student to perform the distribution alignment of the counting area. Extensive experiments are conducted on four challenging datasets, demonstrating the superiority of DKD. When there are only approximately 6% of the parameters and computations from the original models, the student model achieves a faster and more accurate counting performance as the teacher model even surpasses it.

MultiPrime: A reliable and efficient tool for targeted next-generation sequencing.

We present multiPrime, a novel tool that automatically designs minimal primer sets for targeted next-generation sequencing, tailored to specific microbiomes or genes. MultiPrime enhances primer coverage by designing primers with mismatch tolerance and ensures both high compatibility and specificity. We evaluated the performance of multiPrime using a data set of 43,016 sequences from eight viruses. Our results demonstrated that multiPrime outperformed conventional tools, and the primer set designed by multiPrime successfully amplified the target amplicons. Furthermore, we expanded the application of multiPrime to 30 types of viruses and validated the work efficacy of multiPrime-designed primers in 80 clinical specimens. The subsequent sequencing outcomes from these primers indicated a sensitivity of 94% and a specificity of 89%.

Retrograde nerve growth factor signaling modulates tooth mechanical hyperalgesia induced by orthodontic tooth movement via acid-sensing ion channel 3 / 国际口腔科学杂志·英文版

Orthodontic tooth movement elicits alveolar bone remodeling and orofacial pain that is manifested by tooth mechanical hyperalgesia. Nerve growth factor (NGF) is upregulated in periodontium and may modulate tooth mechanical hyperalgesia. The objectives were to examine the role of NGF in tooth mechanical hyperalgesia and to elucidate the underlying mechanisms. Tooth mechanical hyperalgesia was induced by ligating closed coil springs between incisors and molars in Sprague-Dawley rats. Retrograde labeling was performed by periodontal administration of fluor-conjugated NGF and the detection of fluorescence in trigeminal ganglia (TG). Lentivirus vectors carrying NGF shRNA were employed to knockdown the expression of NGF in TG. The administration of agonists, antagonists, and virus vectors into TG and periodontium was conducted. Tooth mechanical hyperalgesia was examined through the threshold of biting withdrawal. Our results revealed that tooth movement elicited tooth mechanical hyperalgesia that could be alleviated by NGF neutralizing antibody and that NGF was upregulated in periodontium (mainly in periodontal fibroblasts) and TG. Retrograde labeling revealed that periodontal NGF was retrogradely transported to TG after day 1. Acid-sensing ion channel 3 (ASIC3) and NGF were co-expressed in trigeminal neurons and the percentage of co-expression was significantly higher following tooth movement. The administration of NGF and NGF neutralizing antibody into TG could upregulate and downregulate the expression of ASIC3 in TG, respectively. NGF aggravated tooth mechanical hyperalgesia that could be alleviated by ASIC3 antagonist (APETx2). Moreover, NGF neutralizing antibody mitigated tooth mechanical hyperalgesia that could be recapitulated by ASIC3 agonist (GMQ). NGF-based gene therapy abolished tooth mechanical hyperalgesia and downregulated ASIC3 expression. Taken together, in response to force stimuli, periodontal fibroblasts upregulated the expressions of NGF that was retrogradely transported to TG, where NGF elicited tooth mechanical hyperalgesia through upregulating ASIC3. NGF-based gene therapy is a viable method in alleviating tooth-movement-induced mechanical hyperalgesia.

Epidemiological characteristics of human infection with avian influenza A (H7N9) in Guilin / 中华微生物学和免疫学杂志

Objective To analyze the epidemiological characteristics of human infection with H7N9 avian influenza in Guilin in recent years and to provide on-site data and data support for scientific pre-vention and control of the epidemic of H7N9 avian influenza infection. Methods A descriptive epidemio-logical method was used to collect the data about human infection with H7N9 avian influenza form three as-pects, which were human infection cases in 2017, environmental monitoring for H7N9 avian influenza virus and sentinel surveillance of influenza-like cases. The epidemiological characteristics of human infection with H7N9 avian influenza in Guilin in 2017 were analyzed. Chi-square test was used to compare the positive rates of H7N9 avian influenza virus in environmental specimens. Results A total of six cases of confirmed human H7N9 infection including three deaths were reported in Guilin city in 2017. These cases were from five counties and districts and all occurred in winter and spring. The patients were middle-aged and old men. Most of them were farmers and had a clear history of poultry exposure before the onset of infection. No human H7N9 infection was reported in close contacts or in influenza-like cases. Conclusions H7N9 avian influen-za infection in Guilin was characterized by high sporadicity, high incidence in winter and spring, and pre-dominantly middle-aged and elderly men. Avian exposure history was a high risk factor for human infection with H7N9 avian influenza virus. All of the studied cases were severe cases. No human-to-human transmis-sion was reported. Farmers, having a history of poultry slaughter, and underlying diseases were potential risks causing death. Live poultry markets were the main sources of infection, hence closing market could re-duce the detection rate of H7N9 avian influenza virus. Strengthen the management of live poultry market and poultry environmental monitoring, closing live poultry markets when viral detection was positive, and suspen-ding live poultry trading were effective measures to control the epidemic of H7N9 avian influenza infection and prevent transmission.

Transient receptor potential Vanilloid 1-based gene therapy alleviates orthodontic pain in rats / 国际口腔科学杂志·英文版

Orthodontic pain that is induced by tooth movement is an important sequela of orthodontic treatment and has a significant effect on patient quality of life. Studies have shown that the high expression of transient receptor potential vanilloid 1 (TRPV1) in trigeminal ganglions plays a vital role in the transmission and modulation of orofacial pain. However, little is known about the role of TRPV1 in orthodontic pain. In this study, male Sprague-Dawley rats were randomly assigned to six groups to study the role of TRPV1 in the modulation of tooth-movement pain. The expression levels of TRPV1 mRNA and protein were determined by real-time PCR and western blot, respectively. Moreover, pain levels were assessed using the rat grimace scale (RGS). The role of TRPV1 in modulating tooth-movement pain was examined by injecting a TRPV1 antagonist into the trigeminal ganglia of rats. A lentivirus containing a TRPV1 shRNA sequence was constructed and transduced into the rats' trigeminal ganglia. The results showed that the expression levels of TRPV1 protein and mRNA were elevated following tooth-movement pain. Pain levels increased rapidly on the 1 day, peaked on the 3 day and returned to baseline on the 14 day. The TRPV1 antagonist significantly reduced tooth-movement pain. The lentivirus containing a TRPV1 shRNA sequence was able to inhibit the expression of TRPV1 and relieved tooth-movement pain. In conclusion, TRPV1-based gene therapy may be a treatment strategy for the relief of orthodontic pain.