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Background: For patients with resectable locally advanced esophageal squamous cell carcinoma (ESCC), the current standard treatment is neoadjuvant chemoradiotherapy (nCRT) plus radical surgery. Objective: This study aimed to establish a predictive model, based on computed tomography (CT) radiomics features and clinical parameters, to predict sensitivity to nCRT in patients with ESCC pre-treatment. The goal was to provide risk stratification and decision-making recommendations for clinical treatments and offer more valuable information for developing personalized therapies. Methods: This retrospective study involved 102 patients diagnosed with ESCC through biopsy who underwent nCRT. To select radiomics features, we used the least absolute shrinkage and selection operator (LASSO) algorithm. A combined model was constructed, integrating the selected clinically relevant parameters with the Rad-Score. To assess the performance of this combined model, we utilized calibration curves and receiver operating characteristic (ROC) curves. Results: Nine optimal radiomics features were selected using the LASSO algorithm. The support vector machine (SVM) classifier was identified as having the best predictive performance. The area under the curve (AUC) of the SVM training group was 0.937 (95% CI: 0.856-1.000), and of the validation group was 0.831 (95% CI: 0.679-0.983). Smoking and alcohol history, neutrophil to lymphocyte ratio, serum aspartate aminotransferase to alanine aminotransferase ratio, and carcinoembryonic antigen and fibrinogen levels were independent predictors of sensitivity to nCRT in patients with ESCC. The AUCs of the combined model for the training and validation groups were 0.870 (95% CI: 0.774-0.964) and 0.821 (95% CI: 0.669-0.972), respectively. The calibration curve showed that the nomogram’s predictions were close to the actual clinical observations, indicating that the model exhibited good predictive performance. Conclusion: Our combined model based on Rad-Score and clinical characteristics showed high predictive performance for predicting sensitivity to nCRT in patients with ESCC. It may be useful for predicting treatment effects in clinical practice and demonstrates the significant potential of radiomics in predicting and optimizing treatment decisions.

Abstract Background Asia’s inflammatory bowel disease (IBD) burden has rapidly increased recently, but the epidemiological trends in Asia remain unclear. We report IBD’s incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALY) in 52 Asian countries from 1990 to 2019. Methods Data from the Global Burden of Disease 2019 were analyzed for IBD burden across 52 countries, using metrics like incidence, prevalence, mortality rates, and DALY. The epidemiological trend of IBD from 1990 to 2019 was assessed with the Joinpoint and APC methods. Decomposition and frontier analyses examined factors behind IBD case and death changes. The NORPRED forecasted Asia's morbidity and mortality trends from 2019 to 2044. Results From 1990 to 2019, The incidence and prevalence of IBD increased in Asia, while mortality and DALY decreased. East Asia had the highest increase in disease burden. IBD incidence was highest among the 30–34 age group, with prevalence peaking in the 45–49 age group. In high-income regions, IBD peak age shifted to younger groups. Decompose analysis showed population growth as the primary factor for the increasing IBD cases in Asia. NORDPRED model predicted a continued IBD burden increase in Asia over the next 25 years. Conclusions Between 1990 and 2019, ASIR and ASPR of IBD in Asia increased, while ASMR and ASDR decreased. Due to population growth and aging, the IBD burden is expected to rise over the next 25 years, particularly in East Asia.

The purpose of this study was to explore and verify genes that regulate the reproductive traits of Tibetan pigs at the mRNA level. The ovarian tissues of Tibetan pigs (TPs) and Yorkshire pigs (YPs) were selected as research objects, and cDNA libraries of the ovarian tissue transcripts of Tibetan pigs and Yorkshire pigs were successfully constructed by the RNA-Seq technique. A total of 651 differentially expressed genes (DEGs) were screened, including 414 up-regulated genes and 237 down-regulated genes. Through GO and KEGG enrichment analysis, it was found that these differentially expressed genes were significantly enriched in cell process, reproductive process, reproduction, cell proliferation, binding, and catalytic activity, as well as oxidative phosphorylation, endocrine resistance, thyroid hormone, Notch, and other signal transduction pathways. Genes significantly enriched in pathways closely related to reproductive regulation were analyzed and selected, and the AR, CYP11A1, CYP17A1, INHBA, ARRB2, EGFR, ETS1, HSD17B1, IGF1R, MIF, SCARB1, and SMAD4 genes were identified as important candidate genes. Twelve differentially expressed genes related to reproduction were verified by RT-qPCR. The results showed that the expression of the AR, CYP17A1, EGFR, ETS1, IGF1R, and SMAD4 genes was significantly higher in Tibetan pigs than in Yorkshire pigs, while the expression of the CYP11A1, INHBA, ARRB2, HSD17B, MIF, and SCARB1 genes in Tibetan pigs was significantly lower than in Yorkshire pigs. The purpose of this study is to provide a theoretical basis for exploring the molecular mechanism of reproductive trait effect genes and the application of molecular breeding in Tibetan pigs.

Cancer stem cells (CSCs), also known as tumor-initiating cells (TICs), are a subset of tumor cells that persist within tumors as a distinct population. They drive tumor initiation, relapse, and metastasis through self-renewal and differentiation into multiple cell types, similar to typical stem cell processes. Despite their importance, the morphological features of CSCs have been poorly understood. Recent advances in artificial intelligence (AI) technology have provided automated recognition of biological images of various stem cells, including CSCs, leading to a surge in deep learning research in this field. This mini-review explores the emerging trend of deep learning research in the field of CSCs. It introduces diverse convolutional neural network (CNN)-based deep learning models for stem cell research and discusses the application of deep learning for CSC research. Finally, it provides perspectives and limitations in the field of deep learning-based stem cell research.

Abstract Background Antibodies against myelin-oligodendrocyte-glycoprotein (MOG-Abs) associated disease (MOGAD) has been recognized as a disease entity. Optic neuritis (ON) is the most common symptom in MOGAD. To demonstrate the differences in retinal microvascular characteristics between patients with MOGAD-ON and aquaporin-4 antibody (AQP4-Ab) positive ON. Methods In a prospective study, optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) were used to measure retinal and microvascular parameters. Results Twenty-six MOGAD-ON eyes, 40 AQP4-ON eyes, and 60 control eyes were included in the study. The thickness of RNFL and GCC in MOGAD-ON eyes was significantly lower than that of HC (p

With the continuous expansion of system scale, the parameter coupling of the system is prominent. Due to limitations in knowledge and experience, it is difficult for designers to objectively analyze the interaction relationship between parameters, resulting in the low accuracy of engineering parameter selection, hence affecting conflict solving. In order to improve the accuracy of engineering parameter selection and the efficiency of conflict solving, this paper proposes a conflict solving process based on mapping between physical parameters and engineering parameters. First, the physical parameters related to the components of the system function model are extracted, and dimensional analysis is used to construct a physical parameter logical network. Secondly, the physical parameter change path related to the problem in the physical parameter logical network is found, and the physical parameter sets corresponding to both conflicting parties are obtained. Then, the engineering parameters corresponding to conflicts can be selected through the mapping model between physical parameters and engineering parameters, which is trained by a neural network with the sample data of physical parameter sets and engineering parameters in existing cases. Finally, Theory of Inventive Problem Solving (TRIZ) tools are used to solve conflicts, and the final design scheme is obtained through evaluation. The feasibility and effectiveness of the proposed method are verified by redesigning a bulk traditional Chinese medicine dispenser.

Abstract Objective Deep venous thrombosis (DVT) is a severe complication in longitudinally extensive transverse myelitis (LETM) patients. It may interfere with LETM treatment and delay the recovery of the spinal dysfunction. However, there is less data about the prevalence and risk factors of DVT in patients with LETM. We analyzed data retrospectively to ascertain the prevalence of DVT and the clinical risk factors for DVT. Methods Clinical data on 255 LETM patients were collected from medical records. All patients were performed color Doppler ultrasound(US) to screen DVT in both lower extremities when admitted. Clinical characteristics of LETM patients with DVT were compared with those without DVT using corresponding statistical methods. Multivariate logistic regression was performed to identify risk factors related to DVT. Results DVT were found in 11.8% patients with LETM. Univariate analysis showed that age, muscle force and elevated baseline D-dimer were risk factors for DVT. After multivariate logistic regression, age, dyslipidemia, segments of lesions, and elevated baseline D-dimer remained significant independent risk factors. Conclusions DVT is common in patients with LETM and related to patient’s age, dyslipidemia, segments of lesions, and elevated baseline D-dimer. Early recognition of DVT and thrombosis prophylaxis are appropriate in patients with LETM.

Abstract Background Neuromyelitis optica spectrum disorders (NMOSD) are demyelinating autoimmune diseases in the central nervous system (CNS) that are characterized by a high relapse rate and the presence of anti-aquaporin 4 antibodies (AQP4-IgG) in the serum. Azathioprine (AZA) is a first-line immunomodulatory drug that is widely used for the treatment of patients with NMOSD. However, the efficacy and safety of AZA vary in different individuals. Method Thirty-two patients with NMOSD who regularly took AZA were enrolled in the study at Beijing Tiantan Hospital, Capital Medical University. The efficacy of AZA was evaluated using the expanded disability status scale (EDSS) and the annual relapse rate (ARR). The erythrocyte concentrations of AZA metabolites were detected using an LC-MS/MS method. Results The erythrocyte concentrations of 6-thioguanine nucleotides (6-TGNs) and 6-methylmercaptopurine nucleotides (6-MMPNs) were 202.03 ± 63.35 pmol/8*108 RBC and 1618.90 ± 1607.06 pmol/8*108 RBC, respectively. After the patients had received AZA therapy for more than one year, the EDSS score decreased from 5.21 ± 0.24 to 2.57 ± 0.33 (p

Objective: To extract the computed tomography (CT) imaging features of the primary lesions in patients with advanced esophageal squamous cell carcinoma (ESCC) and to study whether these imaging features can predict the short-term outcome after concurrent chemoradiotherapy (CCRT). Methods: From January 2014 to December 2015, a total of 49 patients with locally advanced ESCC who underwent CCRT were analyzed retrospectively. They were randomly categorized into the training and validation groups. Collection of CT imaging of patients before and intermediate stage undergoing radiotherapy. The correlations between imaging characteristics and short-term outcome were analyzed. The accuracy of cutoff value was verified by imaging characteristics of patients in validation group. Result: There were 38 patients in the training group and 11 patients in the validation group. 13 patients in the training group were classified as responders and 25 patients as nonresponders. According to the CT imaging before radiotherapy, there are no significant differences between responders and nonresponders. According to the CT imaging in the middle stage of radiotherapy, responders showed significantly higher Roundness than nonresponders ( P = .004, 95% confidence interval [CI] = 0.0419-0.212). The areas under the ROC curves for the ability to predict significantly tumor response were 0.768 for Roundness ( P = .001, 95% CI = 0.603-0.889). The cutoff value of Roundness is 0.3099. Roundness showed no significant associations with survival parameters. Conclusions: Computed tomography imaging in the middle stage of radiotherapy can predict the short-term outcome of concurrent chemoradiotherapy for patients with locally advanced ESCC but have no predictive effect on the total survival time.

Objective: To evaluated the prognostic ability of several serum cytokines in clinically isolated syndrome (CIS) patients regarding second events and conversion to multiple sclerosis (MS) or neuromyelitis optica spectrum disorder (NMOSD).Methods: We enrolled 69 CIS patients whose serum samples were collected during the acute phase of the first onset before immunotherapy. Fifteen other non-inflammatory neurological disorder (OND) patients were also included. The serum levels of interleukin (IL)-2, IL-4, IL-6, IL-10, IL-13, IL-17A, IL-21, IL-23, interferon-γ (IFN-γ), and transforming growth factor beta 1 (TGF-β1) were measured using the human cytokine multiplex assay or ELISA. Patients were seen every 3–6 months. Unscheduled visits occur in case of exacerbations. Clinical measures of disease progression were recorded.Results: Twenty CIS cases had second events during follow-up at a mean time of 15.3 ± 9.9 months. Serum IL-10 levels were significantly lower in CIS patients who relapsed compared to patients who did not. Low serum IL-10 levels were associated with higher risk and shorter times to second events. In clinical correlations, a significantly higher CSF white blood cells count, number of T2 lesions, and gadolinium-enhancing (Gd+) lesions in baseline MRI were found in the low serum IL-10 level group. Of the 20 relapsed cases, seven converted to MS, and eight converted to NMOSD. No significant differences were found in any cytokine levels between these patients at first onset.Conclusions: These findings support using serum IL-10 as a biomarker associated with the risk of relapse and the time to second events in patients with CIS. However, serum cytokine levels can not differentiate between the conversion from CIS to MS or NMOSD.

The application of design knowledge determines the innovativeness of a technical scheme obtained by trimming (a tool for problem analysis and solving in TRIZ). However, limitations in the knowledge, experience and expertise of designers constrain the range of design knowledge that they can apply, thus reducing the effectiveness of trimming. In this paper, biological strategies are introduced to the trimming process to compensate for limitations imposed by the insufficient professional knowledge of designers, thereby improving design innovation. Therefore, this paper proposes a new design method that combines the trimming method and bio-inspired design (BID). First, a trimming analysis of the target system is carried out. Taking the missing functions of the trimmed system as a potential breakthrough point, a keyword search mode based on “V(verb)O(object)P(property) + the effect/features of the associated function” is used to search for biological prototypes in the biological knowledge base. Second, a fuzzy comprehensive evaluation method is used to analyze the biological prototypes from three dimensions, namely, compatibility, completeness and feasibility, and the best-matching biological prototype is selected. Finally, the biological solution is transformed into an engineering design scheme through a resource derivation process based on structure–function–attribute analogies. The proposed method can expand the range of design solutions by adding biological strategies as a new resource to solve trimming problems. The feasibility and effectiveness of the method are verified by redesigning a steel tape armoring machine.

Numerous studies have been focusing on breeding tomato plants with enhanced lycopene accumulation, considering its positive effects of fruits on the visual and functional properties. In this study, we used a bidirectional strategy: promoting the biosynthesis of lycopene, while inhibiting the conversion from lycopene to β- and α-carotene. The accumulation of lycopene was promoted by knocking down some genes associated with the carotenoid metabolic pathway. Finally, five genes were selected to be edited in genome by CRISPR/Cas9 system using Agrobacterium tumefaciens-mediated transformation. Our findings indicated that CRISPR/Cas9 is a site-specific genome editing technology that allows highly efficient target mutagenesis in multiple genes of interest. Surprisingly, the lycopene content in tomato fruit subjected to genome editing was successfully increased to about 5.1-fold. The homozygous mutations were stably transmitted to subsequent generations. Taken together, our results suggest that CRISPR/Cas9 system can be used for significantly improving lycopene content in tomato fruit with advantages such as high efficiency, rare off-target mutations, and stable heredity.

To address the limitations of traditional untunable multi-wing chaotic systems in terms of stability and security, this study proposes a novel method for constructing a tunable multi-wing complex chaotic system. The proposed method is applied to investigate a three-dimensional self-excited chaotic system featuring two nonlinear terms. The key contributions of this work are threefold: First, the characteristics of the new three-dimensional chaotic system are analyzed, and its basic chaotic properties are proved. Second, a new method for constructing tunable multi-wing chaotic systems is proposed. By utilizing the rotational symmetry of the system, a chaotic attractor with an adjustable number of wings (2n wings) is generated, enhancing the system’s adaptability and complexity. As n approaches infinity, the attractor trajectory converges to a circular shape, showcasing the system’s flexibility and application potential. Finally, the practicability of the system is verified through circuit simulation design using Multisim software and physical implementation on a breadboard. FPGA implementation is also discussed, highlighting the system’s potential in real-world applications. Overall, the methods and results presented in this paper contribute significantly to the exploration of complex dynamical systems and offer potential application value in secure communication, image encryption, and related fields.

ABSTRACT Background Micturition desire‐awakening (MDA) function plays a pivotal role in the development of primary nocturnal enuresis (PNE); however, its neural correlates remain largely unexplored. Consequently, this study aimed to identify specific brain regional activities associated with MDA function. Methods Neuroimaging data were collected from 173 children with varying MDA functional grade scores at the Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, from July 2018 to November 2022. Resting‐state images were analyzed using whole‐brain correlation techniques and AlphaSim correction to identify brain regional activities and resting‐state functional connectivity (RSFC) associated with MDA functional grade scores. Results Whole‐brain correlation analysis demonstrated that the fractional amplitude of low‐frequency fluctuations in the right angular gyrus (AG) exhibited a negative correlation with MDA functional grade scores (rs = −0.336, p < 0.001), indicating reduced neural activity in this region with MDA dysfunction. Conversely, RSFC between the right middle frontal gyrus and the right AG was positively correlated with MDA functional grade scores (rs = 0.274, p < 0.001), suggesting increased connectivity in these areas associated with worse MDA functionality. Conclusion These findings provide preliminary insights into the neural underpinnings of MDA functionality.

ABSTRACT: Odor emission during livestock manure treatment poses a threat to the environment and human health. However, the odor emission profiles and related factors of commonly employed poultry manure treatments have rarely been studied. Here, we explored the odor emission profiles of 3 common poultry manure treatments in China, namely, ectopic fermentation beds (EFB), annular composting troughs (ACT) and air-drying rooms (ADR). The results revealed that the total odor concentrations in the EFB, ACT and ADR groups were 2407.67 ± 512.94, 13444.00 ± 1269.92 and 621.33 ± 59.27, respectively. The ACT had the greatest number of odorants (31), followed by the ADR (27) and the EFB (24). Methyl mercaptan, acetic acid, acetaldehyde, hydrogen sulfide, ammonia and acrolein were the key odorous compounds detected in all the treatments. ACT contained the greatest number of key odorants (11) and exhibited an extensive co-occurrence relationship with the bacterial community. The 3 poultry manure treatments exhibited significant differences in the beta diversities of the bacterial community. The phylum of most bacteria associated with key odorants was Firmicutes, and Enterococcus and Oceanobacillus were significantly positively correlated with methyl mercaptan. The bacterial functional groups were enriched in carbohydrate metabolism, amino acid metabolism and energy metabolism, and the functional genes shaped the odor emission patterns in the poultry manure treatments. Redundancy analysis demonstrated that odor emission in the 3 treatments was positively correlated with Firmicutes abundance, pH, electrical conductivity and moisture. Thus, our study provides a good understanding of odor emission profiles in poultry manure treatments and data for precise odor emission control during livestock production.

ABSTRACT: Intestinal microbial metabolism has an important impact on the health of laying hens, and microbes are also important hosts for ARGs. However, the relationship between intestinal microbes and antibiotic resistance in laying hens is unclear. In this study, a slaughtering experiment, an in vitro fermentation experiment and a single-bacteria culture experiment were carried out, and metagenomic and metabolomic analyses were used to investigate the relationships between microbial metabolism and the antibiotic resistome in the cecum of laying hens. The results showed that there were different types of ARGs in the intestines of laying hens, and the risk scores of the ARGs tended to decrease with growth stage. A total of 1142 metagenome-assembled genomes (MAGs) were obtained, and Escherichia coli was found to be the dominant ARG host, carrying 62 ARGs. Metabolomics revealed that indole and its derivatives, such as indole-3-lactic acid, were negatively correlated with a variety of ARGs. Moreover, in vitro fermentation experiment and single-bacteria culture experiment demonstrated that indole-3-lactic acid reduced the abundance and risk of multiple ARGs in the intestine and inhibited the growth of the ARG host Escherichia coli. In the context of high concern about intestinal microbial metabolism and antibiotic resistance, this is the first study to focus on the relationship between intestinal microbial metabolism and antibiotic resistance in laying hens. These findings have important implications for healthy farming and antibiotic resistance control.

Abstract Background Autism Spectrum Disorder (ASD) is a pervasive neurodevelopmental disorder that can significantly impact an individual’s ability to socially integrate and adapt. It’s crucial to identify key factors associated with ASD. Recent studies link both birth asphyxia (BA) and febrile seizures (FS) separately to higher ASD prevalence. However, investigations into the interplay of BA and FS and its relationship with ASD are yet to be conducted. The present study mainly focuses on exploring the interactive effect between BA and FS in the context of ASD. Methods Utilizing a multi-stage stratified cluster sampling, we initially recruited 84,934 Shanghai children aged 3–12 years old from June 2014 to June 2015, ultimately including 74,251 post-exclusion criteria. A logistic regression model was conducted to estimate the interaction effect after controlling for pertinent covariates. The attributable proportion (AP), the relative excess risk due to interaction (RERI), the synergy index (SI), and multiplicative-scale interaction were computed to determine the interaction effect. Results Among a total of 74,251 children, 192 (0.26%) were diagnosed with ASD. The adjusted odds ratio for ASD in children with BA alone was 3.82 (95% confidence interval [CI] 2.42–6.02), for FS alone 3.06 (95%CI 1.48–6.31), and for comorbid BA and FS 21.18 (95%CI 9.10–49.30), versus children without BA or FS. The additive interaction between BA and FS showed statistical significance (P 0.05). Limitations This study can only demonstrate the relationship between the interaction of BA and FS with ASD but cannot prove causation. Animal brain experimentation is necessary to unravel its neural mechanisms. A larger sample size, ongoing monitoring, and detailed FS classification are needed for confirming BA-FS interaction in ASD. Conclusion In this extensive cross-sectional study, both BA and FS were significantly linked to ASD. The coexistence of these factors was associated with an additive increase in ASD prevalence, surpassing the cumulative risk of each individual factor.

The impact of antibiotic therapy on the spread of antibiotic resistance genes (ARGs) and its relationship to gut microbiota remains unclear. This study investigated changes in ARGs, mobile genetic elements (MGEs), and gut microbial composition following tilmicosin administration in pigs. Thirty pigs were randomly divided into control (CK), low-concentration (0.2 g/kg; L), and high-concentration (0.4 g/kg; H) groups. Tilmicosin concentration in manure peaked on day 16 of dosing and dropped below detectable levels by day 13 of the withdrawal period. While tilmicosin did not significantly affect the total abundance of macrolide resistance genes (MRGs) (p > 0.05), it significantly increased the abundance of the multidrug resistance gene tolC in the H group compared with the L and CK groups during the withdrawal period (p < 0.05). This increase was associated with a coincidental rise in the abundance of MGEs (e.g., int1 and int2) and the growth of potential tolC-hosting bacteria such as Paenalcaligenes and Proteiniclasticum. Redundancy analysis showed gut microbial composition as the primary driver of MRG abundance, with MGEs, tilmicosin concentration, and manure physicochemical properties playing secondary roles. These findings suggest that high-dose tilmicosin may alter the gut microbiota and promote ARG spread via MGE-mediated transfer.

Abstract Research on switchable chaotic systems with a large range of parameters is scarce. To explore the chaotic characteristics of such systems, this paper proposes new switchable methods by modifying the nonlinear term in the system, resulting in a chaotic system with different nonlinear terms. The unknown parameters in the nonlinear term exhibit different numerical relationships under various combined conditions, and some parameters may tend towards positive infinity. The chaos characteristics are verified by applying a specific switching method to the unified chaotic system. The pseudo-randomness of the random sequence generated by the dissipative system is verified using the NIST test. Finally, the circuit simulation of the system under various switching conditions is performed by selecting different circuit components and adjusting the resistance values.The switching chaotic system is implemented physically on FPGA and breadboard, and the effectiveness of the system is verified.

Abstract Monitoring extent and severity is vital in the ulcerative colitis (UC) follow-up, however, current assessment is complex and low cost-effectiveness. We aimed to develop a routine blood-based clinical decision support tool, Jin’s model, to investigate the extent and severity of UC. The multicentre retrospective cohort study recruited 975 adult UC inpatients and sub-grouped into training, internal validation and external validation set. Model was developed by logistics regression for the extent via Montreal classification and for the severity via Mayo score, Truelove and Witts score (TWS), Mayo endoscopic score (MES) and Degree of Ulcerative colitis Burden of Luminal Inflammation (DUBLIN) score. In Montreal classification, left-sided and extensive versus proctitis model achieved area under the receiver operating characteristic curve (AUROC) of 0.78 and 0.81 retrospectively. For severity, Mayo score model, TWS model, MES model and DUBLIN score model achieved an AUROC of 0.81, 0.70, 0.74 and 0.70 retrospectively. The models also were evaluated with satisfactory calibration and clinical unity. Jin’s model was free with open access at http://jinmodel.com:3000/ . Jin’s model is a noninvasive, convenient, and efficient approach to assess the extent and severity of UC.

Abstract Background Companion animals can contribute to the physical and mental health of people and often live in very close association with their owners. However, the antibiotic resistome carried by companion animals and the impact they have on their owners and living environment remain unclear. In this study, we compared the ARG profiles of cats, humans, and their living environments using metagenomic analysis to identify the core ARGs in the cat and human gut and explore the potential impact of cats on ARGs in the human gut through the environment. Results Results showed that the abundance of ARGs in the cat gut was significantly higher than that in the human gut (P 0.05). However, the abundance of aminoglycoside resistance genes including APH(2'')-IIa and AAC(6')-Im was significantly higher in cat owners than that in non-cat owners (P

The spread of antibiotic resistance genes (ARGs) in agroecosystems through the application of animal manure is a global threat to human and environmental health. However, the adaptability and colonization ability of animal manure-derived bacteria determine the spread pathways of ARG in agroecosystems, which have rarely been studied. Here, we performed an invasion experiment by creating a synthetic communities (SynCom) with ten isolates from pig manure and followed its assembly during gnotobiotic cultivation of a soil-Arabidopsis thaliana (A. thaliana) system. We found that Firmicutes in the SynCom were efficiently filtered out in the rhizosphere, thereby limiting the entry of tetracycline resistance genes (TRGs) into the plant. However, Proteobacteria and Actinobacteria in the SynCom were able to establish in all compartments of the soil–plant system thereby spreading TRGs from manure to soil and plant. The presence of native soil bacteria prevented the establishment of manure-borne bacteria and effectively reduced the spread of TRGs. Achromobacter mucicolens and Pantoea septica were the main vectors for the entry of tetA into plants. Furthermore, doxycycline stress promoted the horizontal gene transfer (HGT) of the conjugative resistance plasmid RP4 within the SynCom in A. thaliana by upregulating the expression of HGT-related mRNAs. Therefore, this study provides evidence for the dissemination pathways of ARGs in agricultural systems through the invasion of manure-derived bacteria and HGT by conjugative resistance plasmids and demonstrates that the priority establishment of soil bacteria in the rhizosphere limited the spread of TRGs from pig manure to soil-plant systems.