Assessing the antiviral activity of antimicrobial peptides Caerin1.1 against PRRSV in Vitro and in Vivo.

The Porcine reproductive and respiratory syndrome (PRRS) causes severe financial losses to the global swine industry. Due to continuous virus evolution, the protection against the PRRS provided by current vaccines is limited. In order to find new antiviral strategies, this study investigated the antiviral potential of antimicrobial peptides (AMPs) against PRRSV. Given the diversity of PRRSV strains and the limited effectiveness of existing vaccines in controlling PRRSV, this study evaluated the inhibitory effects of KLAK, Cecropin B, Piscidin1, and Caerin1.1 on 3 strains of PRRSV (lineage 5 classical strain, lineage 8 highly pathogenic strain, and lineage 1 NADC30-like strain). Caerin1.1 exhibited significant dose-dependent antiviral activity, with an effective concentration (EC50) of 7.5 µM. Caerin1.1 effectively inhibited PRRSV replication when added before or in early infection but showed reduced effectiveness when added in late infection, indicating its potential involvement in targeting early transcription mechanisms of viral RNA polymerase and significantly upregulating cytokine gene expression. In the NADC30 strain-based animal infection model, Caerin1.1 treatment significantly reduced lung viral loads and inflammation in the lungs of PRRSV-infected pigs, with a mortality rate of 0 % (0/5) in the treated group compared to 66.67 % (4/6) in the untreated group, indicating a reduction in the mortality rate. Additionally, compared with the untreated group, the Caerin1.1-treated group showed significant improvements, such as lighter fever, more daily weight gain, less clinical symptoms, less viral load in blood, and less virus oral shedding (P < 0.05). These findings reveal the potential of antimicrobial peptides as PRRSV therapeutic agents and suggest that Caerin1.1 is a promising candidate for a novel anti-PRRSV drug.

Research on disturbance influence of goaf residual deformation on simply supported beam bridge.

In order to analyze the stability of the bridge above the goaf, the disturbance influence of goaf residual deformation on the bridge is studied. Firstly, an equivalent numerical simulation method of goaf residual deformation evolution process is studied by quantitative analysis the sensitivity of residual subsidence to the rock parameters using the OAT (one-variable-at-a-time). Then, the collaborative deformation of ground, pile, and bridge floor is studied under the condition of a simply-supported beam bridge above the goaf center. Finally, the mechanism of collaborative deformation of ground, pile, and bridge floor is revealed. The results show that the goaf residual deformation process can be obtained by weakening the elastic modulus of fractured rock in the caving zone. At the final residual deformation stage, the subsidence ratio of ground to pile is about 10, and the subsidence ratio of pile to bridge floor is about 2, while the ground horizontal movement ratio of ground to pile is about 7, and the bridge floor horizontal movement can be ignored. The bridge floor is always in the positive curvature influence zone, and the pile has an inhibitory effect on the curvature deformation of the bridge floor. The compression deformation occurs between the piles locations, while the tensile deformation occurs at the pile location. The evolution of negative frictional resistance derived from goaf residual deformation is the main reason for the change in the collaborative deformation law among the ground, pile and bridge floor. This research can provide scientific support and theoretical basis for the design, construction, and protection of the bridge above the goaf center, and can also provide reference for the stability evaluation of bridge above goaf under other conditions.

Integrated high-precision monitoring method for surface subsidence in mining areas using D-InSAR, SBAS, and UAV technologies.

The use of unmanned operations to monitor mining induced land subsidence is increasing. This study conducts a detailed comparative analysis of accuracy of measured ground deformation provided by Differential Interferometric Synthetic Aperture Radar (D-InSAR), Small Baseline Subset (SBAS), and Unmanned Aerial Vehicle (UAV) tilt photogrammetry with respect to levelling measurements. Based on such analysis we propose an integrated approach that combines multiple remote sensing methods to achieve a better global accuracy in the land subsidence monitoring in mining areas. Conducted at the Banji Coal Mine, this study collected subsidence data from April 10, 2021, to June 28, 2022, through D-InSAR, SBAS, and UAV techniques. After segmenting the subsidence basin into distinct zones, we qualitatively assessed each area with UAV-derived 3D models and quantitatively evaluated the precision of all applied techniques, benchmarking against leveling data. Our findings indicate that integrating D-InSAR, SBAS, and UAV technologies significantly enhances monitoring accuracy over any single method, demonstrating their combined effectiveness in different subsidence areas. Consequently, the synergistic integration of D-InSAR, SBAS, and UAV technologies, capitalizing on their complementary strengths, enables the achievement of intuitive, comprehensive, and high-precision monitoring of subsidence basins in mining areas.

A porcine kidney-derived clonal cell line with clear genetic annotation is highly susceptible to African swine fever virus.

African Swine Fever virus (ASFV), the causative agent of African swine fever, is a highly lethal hemorrhagic virus affecting domestic pigs and wild boars. The primary target cells for ASFV infection are porcine alveolar macrophages (PAMs), which are difficult to obtain and maintain in vitro, and less subjective to genetic editing. To overcome these issues and facilitate ASFV research, we obtained a subclonal cell line PK1-C5 by subcloning LLC-PK1 cells that support stable ASFV proliferation. This consequential cell line exhibited high ASFV infection levels and similar viral growth characteristics to PAMs, while also allowing high-efficiency genomic editing through transfection or lentivirus transduction of Cas9. Taken together, our study provided a valuable tool for research aspects including ASFV-host interactions, pathogenicity, and vaccine development.

Improving Indoor Pedestrian Dead Reckoning for Smartphones under Magnetic Interference Using Deep Learning.

As micro-electro-mechanical systems (MEMS) technology continues its rapid ascent, a growing array of smart devices are integrating lightweight, compact, and cost-efficient magnetometers and inertial sensors, paving the way for advanced human motion analysis. However, sensors housed within smartphones frequently grapple with the detrimental effects of magnetic interference on heading estimation, resulting in diminished accuracy. To counteract this challenge, this study introduces a method that synergistically employs convolutional neural networks (CNNs) and support vector machines (SVMs) for adept interference detection. Utilizing a CNN, we automatically extract profound features from single-step pedestrian motion data that are then channeled into an SVM for interference detection. Based on these insights, we formulate heading estimation strategies aptly suited for scenarios both devoid of and subjected to magnetic interference. Empirical assessments underscore our method's prowess, boasting an impressive interference detection accuracy of 99.38%. In indoor environments influenced by such magnetic disturbances, evaluations conducted along square and equilateral triangle trajectories revealed single-step heading absolute error averages of 2.1891° and 1.5805°, with positioning errors averaging 0.7565 m and 0.3856 m, respectively. These results lucidly attest to the robustness of our proposed approach in enhancing indoor pedestrian positioning accuracy in the face of magnetic interferences.

A Fusion Positioning Method for Indoor Geomagnetic/Light Intensity/Pedestrian Dead Reckoning Based on Dual-Layer Tent-Atom Search Optimization-Back Propagation.

Indoor positioning using smartphones has garnered significant research attention. Geomagnetic and sensor data offer convenient methods for achieving this goal. However, conventional geomagnetic indoor positioning encounters several limitations, including low spatial resolution, poor accuracy, and stability issues. To address these challenges, we propose a fusion positioning approach. This approach integrates geomagnetic data, light intensity measurements, and inertial navigation data, utilizing a hierarchical optimization strategy. We employ a Tent-ASO-BP model that enhances the traditional Back Propagation (BP) algorithm through the integration of chaos mapping and Atom Search Optimization (ASO). In the offline phase, we construct a dual-resolution fingerprint database using Radial Basis Function (RBF) interpolation. This database amalgamates geomagnetic and light intensity data. The fused positioning results are obtained via the first layer of the Tent-ASO-BP model. We add a second Tent-ASO-BP layer and use an improved Pedestrian Dead Reckoning (PDR) method to derive the walking trajectory from smartphone sensors. In PDR, we apply the Biased Kalman Filter-Wavelet Transform (BKF-WT) for optimal heading estimation and set a time threshold to mitigate the effects of false peaks and valleys. The second-layer model combines geomagnetic and light intensity fusion coordinates with PDR coordinates. The experimental results demonstrate that our proposed positioning method not only effectively reduces positioning errors but also improves robustness across different application scenarios.

Development and Implementation of a Quadruple RT-qPCR Method for the Identification of Porcine Reproductive and Respiratory Syndrome Virus Strains.

BACKGROUND: Porcine reproductive and respiratory syndrome virus (PRRSV) causes porcine reproductive and respiratory syndrome (PRRS), leading to abortion in sows and respiratory distress in breeding pigs. In China, PRRSV1 and PRRSV2 are the two circulating genotypes in swine herds, with distinct virulence. PRRSV2 further consists of classical (C-PRRSV2), highly pathogenic (HP-PRRSV2), and NADC30-Like (N-PRRSV2) subtypes. The diversity of PRRSV poses challenges for control and eradication, necessitating reliable detection assays for differentiating PRRSV genotypes. METHODS: A new TaqMan-based RT-qPCR assay with four sets of primers and probes targeting conserved regions of the ORF7 and NSP2 genes of PRRSV was developed, optimized, and evaluated by us. Reaction conditions such as annealing temperature, primer concentration, and probe concentration were optimized for the assay. Specificity, sensitivity, repeatability, stability, limit of detection (LOD), concordance with the reference method were evaluated for the assay. RESULTS: The assay could detect and type PRRSV1, C-PRRSV2, HP-PRRSV2, and N-PRRSV2 simultaneously with 97.33% specificity, 96.00% sensitivity, 12 copies/µL LOD, 97.00% concordance with reference assays. We applied the assay to 321 clinical samples from swine farms in China. The assay successfully detected and typed 230 PRRSV-positive samples, with 24.78% (57/230) of them further confirmed by ORF5 gene sequencing. The prevalence of PRRSV subtypes among the positive samples was as follows: C-PRRSV2 (15.22%), HP-PRRSV2 (23.48%), and N-PRRSV2 (61.30%). Two samples showed coinfection with different PRRSV subtypes. CONCLUSION: The quadruple RT-qPCR assay is a powerful tool for detecting and typing the currently circulating PRRSV strains in Chinese swine populations. It can assist in the surveillance of PRRSV prevalence and the implementation of prevention and control strategies.

The Extraction and Characterization of Pseudorange Multipath Based on BDS-3 Multi-Frequency Observations.

Global Navigation Satellite System (GNSS) observations are subject to various errors during their propagation process. A reasonable correction of these errors can improve the positioning, navigation, and timing (PNT) service capability. The impact of multipaths on pseudorange observations can reach a decimeters or even meters level. However, their mechanism is complex and there is currently no universally accepted high-precision correction model. The correlation between the pseudorange multipaths (MP) of BDS-2 satellites and satellite elevation has been confirmed, while there have been fewer analyses of the MP characteristics for different frequencies of BDS-3 satellites. The broadcasting of multi-frequency observations in BDS-3 should theoretically make the extracted MP more accurate compared to traditional methods. Based on this, in this contribution, a multi-frequency MP extraction algorithm based on the least squares principle is proposed, which can simultaneously eliminate the influence of higher-order ionospheric delay. The analytical expression for only eliminating first-order ionospheric delay is successfully derived. Subsequently, the characteristics of the MPs extracted from different frequency combinations and the impact of combination noise on the extraction accuracy are discussed. The influence of second-order ionospheric delay on the MPs for each frequency under different combination noises, as well as the periodic behavior exhibited in long-term observations of the BDS-3 medium earth orbit (MEO) and inclined geosynchronous orbit (IGSO) satellites, are also analyzed. Finally, the correlations between the MPs of each frequency of BDS satellite and elevation are quantitatively analyzed based on observations from 35 stations. Overall, this work has positive implications for the study of the MP characteristics of BDS-3 and subsequent modeling efforts.

Research on Pedestrian Indoor Positioning Based on Two-Step Robust Adaptive Cubature Kalman Filter with Smartphone MEMS Sensors.

With the development of location-based service (LBS), indoor positioning based on pedestrian dead reckoning (PDR) has become a hot research topic. Smartphones are becoming more popular for indoor positioning. This paper proposes a two-step robust-adaptive-cubature Kalman filter (RACKF) algorithm based on smartphone micro-electro-mechanical-system (MEMS) sensor fusion for indoor positioning. To estimate pedestrian heading, a quaternion-based robust-adaptive-cubature Kalman filter algorithm is proposed. Firstly, the model noise parameters are adaptively corrected based on the fading-memory-weighting method and the limited-memory-weighting method. The memory window of the limited-memory-weighting algorithm is modified based on the characteristics of pedestrian walking. Secondly, an adaptive factor is constructed based on the partial state inconsistency to overcome filtering-model deviation and abnormal disturbances. Finally, to identify and control the measurement outliers, the robust factor based on maximum-likelihood estimation is introduced into the filtering to enhance the robustness of heading estimation and support more robust dynamic-position estimation. In addition, based on the accelerometer information, a nonlinear model is constructed and the empirical model is used to estimate the step length. Combining heading and step length, the two-step robust-adaptive-cubature Kalman filter is proposed to improve the pedestrian-dead-reckoning method, which enhances the adaptability and robustness of the algorithm and further improves the accuracy of the plane-position solution. The adaptive factor based on the prediction residual and the robust factor based on the maximum-likelihood estimation are introduced into the filter to improve the adaptability and robustness of the filter, reduce the positioning error, and improve the accuracy of the pedestrian-dead-reckoning method. Three different smartphones are used to validate the proposed algorithm in an indoor environment. Additionally, the experimental results confirm the algorithm's effectiveness. From the results of the three smartphones, the root mean square error (RMSE) of the indoor-positioning results obtained by the proposed method is about 1.3-1.7 m.

Epidemiological and genetic characteristics of porcine circovirus 3 in 15 provinces and municipalities of China between 2016 and 2020.

Porcine circovirus 3 (PCV3) is a newly emerging virus and has been found associated with porcine dermatitis and nephropathy syndrome in pigs. Compared with PCV2, research into PCV3 cap gene sequencing is deficient. To investigate the prevalence and genotype distribution of PCV3, we collected 1291 samples from 211 pig farms throughout 15 provinces and municipalities. 312 out of 1291 samples were tested positive by PCR. We further sequenced and analyzed 164 PCR-positive samples. The majority (61.8%) of isolates we sequenced belong to genotype PCV3c. PCV3c is also the dominant genotype in Hubei, Hunan, Hebei province and Chongqing city. We found 3 sites under positive selection and located in predicted epitope peptide, revealing that the pig's immunity may be a reason those sites are undergoing highly positive selection.

Investigation and analysis of etiology associated with porcine respiratory disease complex in China from 2017 to 2021.

Porcine respiratory diseases complex (PRDC) is a highly serious threat to the pig industry. In the present study, we investigated and analyzed the etiology associated with PRDC and explored the role of viruses in respiratory bacterial infections. From 2017 to 2021, clinical samples were collected from 1,307 pigs with typical respiratory symptoms in 269 farms in China and screened for pathogens related to PRDC by PCR and bacterial isolation. The results indicated that PRRSV (41.16%, 95%CI: 38.49~43.83%), PCV2 (21.58%,95%CI: 19.35~23.81%), S. suis (63.50%, 95%CI: 60.89~66.11%), and G. parasuis (28.54%, 95%CI: 26.09~30.99%) were the most commonly detected pathogens in pigs with PRDC in China. The dominant epidemic serotypes (serogroups) of S. suis, G. parasuis, and P. multocida were serotype 2, serotype 1, and capsular serogroups D, respectively. Pigs of different ages exhibited different susceptibilities to these pathogens, e.g., PRRSV, PCV2, and G. parasuis had the highest detection rates in nursery pigs, whereas fattening pigs had the highest detection rates of P. multocida and A. pleuropneumoniae. Among the 1,307 pigs, the detection rates of S. suis, G. parasuis, P. multocida, and B. bronchiseptica were higher in virus-positive pigs, especially G. parasuis and P. multocida were significantly (p < 0.01) higher than in virus-negative pigs. In addition, a strong positive correlation was found between coinfection by PRRSV and G. parasuis (OR = 2.33, 95%CI: 1.12~2.14), PRRSV and P. multocida (OR = 1.55, 95%CI: 1.12~2.14), PCV2 and P. multocida (OR = 2.27, 95%CI: 1.33~3.87), PRRSV-PCV2 and S. suis (OR = 1.83, 95%CI: 1.29~2.60), PRRSV-PCV2 and G. parasuis (OR = 3.39, 95%CI: 2.42~4.74), and PRRSV-PCV2 and P. multocida (OR = 2.09, 95%CI: 1.46~3.00). In summary, PRRSV, PCV2, S. suis, and G. parasuis were the major pathogens in pigs with PRDC, and coinfections of two or more PRDC-related pathogens with strong positive correlations were common in China, such as PRRSV and G. parasuis, PRRSV and P. multocida, PCV2 and P. multocida, and also PRRSV-PCV2 and G. parasuis and PRRSV-PCV2 and P. multocida.

Low-host double MDA workflow for uncultured ASFV positive blood and serum sample sequencing.

African swine fever (ASF) is a highly lethal and contagious disease caused by African swine fever virus (ASFV). Whole-genome sequencing of ASFV is necessary to study its mutation, recombination, and trace its transmission. Uncultured samples have a considerable amount of background DNA, which causes waste of sequencing throughput, storage space, and computing resources. Sequencing methods attempted for uncultured samples have various drawbacks. In this study, we improved C18 spacer MDA (Multiple Displacement Amplification)-combined host DNA exhaustion strategy to remove background DNA and fit NGS and TGS sequencing. Using this workflow, we successfully sequenced two uncultured ASFV positive samples. The results show that this method can significantly reduce the percentage of background DNA. We also developed software that can perform real-time base call and analyses in set intervals of ASFV TGS sequencing reads on a cloud server.

Recombinant Pseudorabies Virus with TK/gE Gene Deletion and Flt3L Co-Expression Enhances the Innate and Adaptive Immune Response via Activating Dendritic Cells.

Owing to viral evolution and recombination, emerging pseudorabies virus (PRV) strains have caused unprecedented outbreaks in swine farms even when the pigs were previously vaccinated, which might indicate that traditional vaccines were unable to provide effective protection. The development of safe and efficacious vaccines presents prospects to minimize the clinical signs and eventually eradicate the infection. In this study, we used an emerging PRV strain, HNX, as the parental strain to construct a recombinant PRV with TK/gE gene deletion and Fms-related tyrosine kinase 3 ligand (Flt3L) expression, named HNX-TK-/gE--Flt3L. HNX-TK-/gE--Flt3L enhanced the maturation of bone marrow derived dendritic cells (DCs) in vitro. Significantly more activated DCs were detected in HNX-TK-/gE--Flt3L-immunized mice compared with those immunized with HNX-TK-/gE-. Subsequently, a remarkable increase of neutralizing antibodies, gB-specific IgG antibodies, and interferon-gamma (IFN-γ) was observed in mice vaccinated with HNX-TK-/gE--Flt3L. In addition, a lower mortality and less histopathological damage were observed in HNX-TK-/gE--Flt3L vaccinated mice with upon PRV lethal challenge infection. Taken together, our results revealed the potential of Flt3L as an ideal adjuvant that can activate DCs and enhance protective immune responses and support the further evaluation of HNX-TK-/gE--Flt3L as a promising PRV vaccine candidate.

Untargeted LC-MS based metabolomic profiling of iPAMs to investigate lipid metabolic pathways alternations induced by different Pseudorabies virus strains.

Owing to viral recombination, interspecies transmission, and evolution, variant pseudorabies virus (PRV) strains exhibit different biological characteristics and pathogenicity. To improve the understanding of common and specific metabolic changes that occur upon infection by different PRV strains, we herein describe the comprehensive analysis of metabolites of PRV vaccine strain (Bartha K61), classical strain (EA) and variant strain (HNX) infection in immortalized porcine alveolar macrophage cells. Compared with uninfected cells, cells infected with Bartha K61, EA and HNX had 246, 225, and 272 differing metabolites, respectively. In the three types of PRV-strain-infected cells, lipids and lipid-like molecules accounted for over 50 % of the altered metabolites. As these viruses are enveloped, viral replication, assembly and release occur on cellular membranes primed through the manipulation of the host metabolism. We analyzed the potential relationship between virus replication and the virus-mediated host metabolism. Our study resulted in the first reconstruction of the major lipid metabolic pathways involved in PRV infection, including those of glycerophospholipids, sphingolipids, glycerolipids, and fatty acyls. In addition, the metabolic perturbations caused by different PRV strain infections are consistent across many species, however, our results also revealed many specific metabolic alterations during HNX infection, such as the enrichment of phosphatidylinositol and 15R-PGE2 methyl ester 15-acetate, and the diminishment of phosphatidylethanolamine, phosphatidic acid, and ceramides. These strain-specific altered metabolites may be linked to the unique biological characteristics and pathogenicity of the HNX strain.

Establishment of a Blocking ELISA Detection Method for Against African Swine Fever Virus p30 Antibody.

African swine fever (ASF) is a highly lethal hemorrhagic viral disease of domestic pigs caused by African swine fever virus (ASFV). A sensitive and reliable serological diagnostic assay is required, so laboratories can effectively and quickly detect ASFV infection. The p30 protein is abundantly expressed early in cells and has excellent antigenicity. Therefore, this study aimed to produce and characterize p30 monoclonal antibodies with an ultimate goal of developing a monoclonal antibody-based enzyme-linked immunosorbent assay (ELISA) for ASFV antibody detection. Three monoclonal antibodies against p30 protein that were expressed in E. coli were generated, and their characterizations were investigated. Furthermore, a blocking ELISA based on a monoclonal antibody was developed. To evaluate the performance of the assay, 186 sera samples (88 negative and 98 positive samples) were analyzed and a receiver-operating characteristic (ROC) analysis was applied to determine the cutoff value. Based on the ROC analysis, the area under the curve (AUC) was 0.997 (95% confidence interval: 99.2 to 100%). Besides, a diagnostic sensitivity of 97.96% (95% confidence interval: 92.82 to 99.75%) and a specificity of 98.96% (95% confidence interval: 93.83 to 99.97%) were achieved when the cutoff value was set to 38.38%. Moreover, the coefficients of inter- and intra-batches were <10%, indicating the good repeatability of the method. The maximum dilution of positive standard serum detected by this ELISA method was 1:512. The blocking ELISA was able to detect seroconversion in two out of five pigs at 10 Dpi and the p30 response increasing trend through the time course of the study (0-20 Dpi). In conclusion, the p30 mAb-based blocking ELISA developed in this study demonstrated a high repeatability with maximized diagnostic sensitivity and specificity. The assay could be a useful tool for field surveillance and epidemiological studies in swine herd.

The epidemiological investigation of co-infection of major respiratory bacteria with pseudorabies virus in intensive pig farms in China.

Porcine respiratory disease complex (PRDC), a respiratory disease caused by a variety of factors, is one of the most common problems in the intensive pig farms. To investigate the mixed infection incidence of wild-type pseudorabies virus (WT PRV) and respiratory bacteria, a total of 1,293 clinical samples were collected from pigs with typical respiratory signs from 14 different provinces of China from September 2016 to February 2018. The WT PRV was detected by ELISA targeting gE antibody while the bacteria were detected by bacterial isolation and serotyping by PCR. The results revealed that the detection rate of A. pleuropneumoniae and B. bronchiseptica infection associated with WT PRV infection were 6.30% and 15.99%, respectively, which were significantly higher than those without WT PRV infection (3.41% and 4.41%) at the farm level (p < .05). There were no significant differences in the detection rate of H. parasuis, S. suis or P. multocida between WT PRV positive and negative farms (p > .05). However, the detection rate of attenuated H. parasuis and S. suis strains were 68.19% and 64.75%, respectively, in WT PRV infected farms, which were significantly higher than those (41.56% and 52.25%) in WT PRV free farms (p < .05). The prevalent serotypes of H. parasuis-5/12 and S. suis-2 were also investigated by multiplex PCR. These results indicated that the presence of WT PRV increased the chance of bacterial infection and the number of pathogenic strains in the respiratory system of pigs. Therefore, the eradication of pseudorabies is an effective approach to prevent and control the bacterial respiratory diseases in the intensive pig farms in China.

Effects of Specific Exercise Therapy on Adolescent Patients With Idiopathic Scoliosis: A Prospective Controlled Cohort Study.

STUDY DESIGN: A prospective controlled cohort study. OBJECTIVE: The aim of this study was to explore the interventional effect of exercise therapy on idiopathic scoliosis (IS) and identify an optimal intervention window. SUMMARY OF BACKGROUND DATA: Early conservative treatment is helpful for IS. In addition to bracing, current evidence suggests that exercise can play an important role. METHODS: We included 99 patients with IS who were treated at the Guangdong Xinmiao Scoliosis Center from August 2013 to September 2017. The inclusion criteria were: new IS diagnosis, Cobb angle 10° to 25°, Risser 0 to 3 grade, only treated with the Xinmiao treatment system (XTS; >3 days/week, >1 h/day), and follow-up >1 year. Patients were divided into three age groups: A, <10 years (n = 29); B, 10 to 12 years (n = 24); and C, 13 to 15 years (n = 46). The percentages of curve improvement (Cobb angle decrease ≥5°), stability (Cobb angle change × ±5°), and progression (Cobb angle increase ≥5°) were compared. RESULTS: The groups showed significant differences for major curve correction, Risser sign, first referral, and final follow-up of the main curve (all P < 0.05). The major curve in group A decreased significantly by 6.8° (44% correction), compared to 3.1° (18% correction) and 1.5° (9% correction) in groups B and C, respectively. In group A, 69.0% (20/29) had curve improvement, 27.6% (8/29) stabilized and 3.4% (1/29) progressed. In group B, 45.8% (11/24) improved, 50% (12/24) stabilized, and 4.2% (1/24) progressed. In group C, 26.1% (12/46) improved, 63.0% (29/46) stabilized, and 10.9% (5/46) progressed. There was also a significant difference in final Risser grade among the groups (P < 0.05). CONCLUSION: For IS patients with Cobb angles between 10° and 25°, our exercise protocol can effectively control or improve curve progression. Younger patients with a lower Risser grade are most likely to respond. LEVEL OF EVIDENCE: 2.

Development and validation of deep learning algorithms for scoliosis screening using back images.

Adolescent idiopathic scoliosis is the most common spinal disorder in adolescents with a prevalence of 0.5-5.2% worldwide. The traditional methods for scoliosis screening are easily accessible but require unnecessary referrals and radiography exposure due to their low positive predictive values. The application of deep learning algorithms has the potential to reduce unnecessary referrals and costs in scoliosis screening. Here, we developed and validated deep learning algorithms for automated scoliosis screening using unclothed back images. The accuracies of the algorithms were superior to those of human specialists in detecting scoliosis, detecting cases with a curve ≥20°, and severity grading for both binary classifications and the four-class classification. Our approach can be potentially applied in routine scoliosis screening and periodic follow-ups of pretreatment cases without radiation exposure.

Establishment and application of a multiplex RT-PCR to differentiate wild-type and vaccine strains of porcine epidemic diarrhea virus.

Due to outbreaks of porcine epidemic diarrhea (PED) and the wide use of attenuated live vaccine, both wild-type and vaccine strains (CV777) are believed to circulate in Chinese pig farms. Thus, identification of different PEDV strains is of epidemiological importance. In this study, a multiplex RT-PCR method was established based on the sequence features of spike (S) gene and ORF3 gene of PEDVs. The method could identify PEDV variant strains, classical wild-type strains and classical vaccine strains. The limit of detection of the RT-PCR was 1.51 × 104 copies/uL for plasmids and 1 × 101.7 TCID50/100 u L for PEDV, respectively. There were no cross-detections among three different PEDVs and no false detections among six swine pathogens. This assay was used to test 940 samples from China of which 303 samples were PEDV positive, and 289, 5, 10 were positive for variant, classical wild, classical vaccine, respectively. One sample was positive for both variant and classical vaccine PEDV. The variant PEDVs could be detected in samples from 13 provinces, while classical PEDVs were detected from nine provinces, supporting the prevalence of variant PEDV in China. In summary, this multiplex RT-PCR was a useful tool for the clinical detection and epidemiological survey of PEDV.

Prevalence and antimicrobial susceptibilities of bacterial pathogens in Chinese pig farms from 2013 to 2017.

Bacterial diseases of swine are a kind of multifactorial and uncontrollable diseases that commonly exist in pig farms all over the world and will lead to huge economic losses every year. In this study, a detailed and overall survey was carried out to better understand the prevalence and antimicrobial susceptibilities of bacterial diseases from 2013 to 2017 in China. A total of 19673 bacterial strains were isolated from 44175 samples collected from 9661 pig farms that distributed in 16 Chinese major pig breeding provinces. The results showed that the average isolation rates of Streptococcus suis (SS), Haemophilus parasuis (HPS), Escherichia coli (E. coli), Pasteurella multocida (Pm), Actinobacillus pleuropneumoniae (APP), Brodetella bronchiseptica (Bb), Salmonella enteria (SE), Erysipelothrix rhusiopathiae (E. rhusiopathiae) were 16.9%, 9.7%, 6.3%, 3.4%, 0.3%, 1.5%, 2.3% and 0.9%, respectively. The isolate rates of E. coli, APP and SE showed an increasing trend from 2013 to 2017. The seasonal prevalence characteristics of SS, HPS and Pm were obviously higher from April to August for first two bacteria and higher at February, March, April, and October for Pm. The dominant serotypes for SS, HPS were serotype 2 and serotype 5 (changed from serotype 4), respectively. The SS, HPS, and Pm showed very high antibiotic resistance rates to almost 8 common antibiotics (ß-lactam, aminoglycoside, macrolides, lincomycin, tetracycline, quinolone, polymyxin, and sulfonamide) and an obvious increasing trend of antibiotic resistance rates from 2013 to 2017. In conclusion, the study provides detailed information on the prevalence and antimicrobial susceptibilities of different bacterial pathogens of swine from 2013 to 2017 in China. These data can provide a foundation for monitoring epidemiological patterns of bacterial diseases in the Chinese swine herds, as well as provide insight into potential antibiotic resistance profiles in these pathogens.