CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses.

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.

Superantigen-fused T cell engagers for tumor antigen-mediated robust T cell activation and tumor cell killing.

Inadequate T cell activation has severely limited the success of T cell engager (TCE) therapy, especially in solid tumors. Enhancing T cell activity while maintaining the tumor specificity of TCEs is the key to improving their clinical efficacy. However, currently, there needs to be more effective strategies in clinical practice. Here, we design novel superantigen-fused TCEs that display robust tumor antigen-mediated T cell activation effects. These innovative drugs are not only armed with the powerful T cell activation ability of superantigens but also retain the dependence of TCEs on tumor antigens, realizing the ingenious combination of the advantages of two existing drugs. Superantigen-fused TCEs have been preliminarily proven to have good (>30-fold more potent) and specific (>25-fold more potent) antitumor activity in vitro and in vivo. Surprisingly, they can also induce the activation of T cell chemotaxis signals, which may promote T cell infiltration and further provide an additional guarantee for improving TCE efficacy in solid tumors. Overall, this proof-of-concept provides a potential strategy for improving the clinical efficacy of TCEs.

CanDriS: posterior profiling of cancer-driving sites based on two-component evolutionary model.

Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored. Due to the over-excess mutations unrelated to cancer, the great challenge is to identify somatic mutations that are cancer-driven. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model: while the ground component corresponds to passenger mutations, the rapidly evolving component corresponds to driver mutations. Then, we implemented an empirical Bayesian procedure to calculate the posterior probability of a site being cancer-driven. Based on these, we developed a software CanDriS (Cancer Driver Sites) to profile the potential cancer-driving sites for thousands of tumor samples from the Cancer Genome Atlas and International Cancer Genome Consortium across tumor types and pan-cancer level. As a result, we identified that approximately 1% of the sites have posterior probabilities larger than 0.90 and listed potential cancer-wide and cancer-specific driver mutations. By comprehensively profiling all potential cancer-driving sites, CanDriS greatly enhances our ability to refine our knowledge of the genetic basis of cancer and might guide clinical medication in the upcoming era of precision medicine. The results were displayed in a database CandrisDB (http://biopharm.zju.edu.cn/candrisdb/).

A case report and literature review on a rare subtype of triple-negative breast cancer in children.

BACKGROUND: Triple-negative breast cancer (TNBC) is a type of breast tumor with a poor prognosis because it lacks or expresses low levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2). TNBC is more common in middle-aged and older women, and cases of TNBC in children are rarely reported. This is the only case of childhood SBC in our hospital in more than 70 years, and the disease is extremely rare internationally. We analyzed and studied the disease and TNBC from both clinical and pathological aspects and found that SBC is very different from TNBC. CASE PRESENTATION: We report a case of secretory breast cancer (SBC), a subtype of TNBC, in an 8-year-old girl from our institution. The child presented with a single mass in the left breast only, with no skin rupture and no enlargement of the surrounding lymph nodes. The child underwent two surgeries and was followed up for one year with a good prognosis. CONCLUSIONS: SBC is highly prevalent among the multiple pathological types of pediatric breast cancer. Almost all pediatric SBC patients are characterized by the ETV6-NTRK3 fusion gene, which has a good prognosis and a 10-year survival rate of more than 90% when compared with other TNBC subtypes. According to the patient, we performed local mass resection and a postoperative pathological diagnosis of SBC (a subtype of BL-TNBC). The TNBC case had a good prognosis and differed from basal TNBC in several aspects, including clinical presentation, treatment, and prognosis. It is necessary to exclude SBC from BL-type TNBC, enhance understanding of the disease, and individualize the treatment plan, so as to avoid medical errors.

Integrated Tandem Electrochemical-chemical-electrochemical Coupling of Biomass and Nitrate to Sustainable Alanine.

Alanine is widely employed for synthesizing polymers, pharmaceuticals, and agrochemicals. Electrocatalytic coupling of biomass molecules and waste nitrate is attractive for the nitrate removal and alanine production under ambient conditions. However, the reaction efficiency is relatively low due to the activation of the stable substrates, and the coupling of two reactive intermediates remains challenging. Herein, we realize the integrated tandem electrochemical-chemical-electochemical synthesis of alanine from the biomass-derived pyruvic acid (PA) and waste nitrate (NO3 - ) catalyzed by PdCu nano-bead-wires (PdCu NBWs). The overall reaction pathway is demonstrated as a multiple-step catalytic cascade process via coupling the reactive intermediates NH2 OH and PA on the catalyst surface. Interestingly, in this integrated tandem electrochemical-chemical-electrochemical catalytic cascade process, Cu facilitates the electrochemical reduction of nitrate to NH2 OH intermediates, which chemically couple with PA to form the pyruvic oxime, and Pd promotes the electrochemical reduction of pyruvic oxime to the desirable alanine. This work provides a green strategy to convert waste NO3 - to wealth and enriches the substrate scope of renewable biomass feedstocks to produce high-value amino acids.

Anodic Cross-Coupling of Biomass Platform Chemicals to Sustainable Biojet Fuel Precursors.

Electrocatalytic conversion of biomass platform chemicals to jet fuel precursors is a promising approach to alleviate the energy crisis caused by the excessive exploitation and consumption of non-renewable fossil fuels. However, an aqueous electrolyte has been rarely studied. In this study, we demonstrate an anodic electrocatalysis route for producing jet fuel precursors from biomass platform chemicals on Ni-based electrocatalysts in an aqueous electrolyte at room temperature and atmosphere pressure. The desired product exhibited high selectivity for the jet fuel precursor (95.4%) and an excellent coulombic efficiency of 210%. A series of in situ characterizations demonstrated that Ni2+ species were the active sites for the coupling process. In addition, the coupling reaction could be achieved by generating radical cations and inhibiting the side reaction. First, the electrochemical process could activate the furfural (FF) molecule and generate radical cations, resulting in an average of 2.0 times chain propagation. The levulinic acid (LA) molecules played a vital role in the coupling reaction. The adsorption strength of LA on Ni3N was higher than that of FF, which could inhibit the side reaction (the oxidation of FF) and achieve high selectivity. Meanwhile, the LA molecules were adsorbed on the Ni3N surface and then disrupted the formation of Ni3+ species, thus favoring the coupling reaction. This work demonstrates an efficient route to produce jet fuel precursors directly from biomass platform chemicals and provides a comprehensive understanding of the anodic coupling process.

Salting-Out Aldehyde from the Electrooxidation of Alcohols with 100 % Selectivity.

Selective electrocatalytic oxidation of alcohols to value-added aldehydes has attracted increasing attention. However, due to its higher reactivity than alcohol, the aldehyde is easily over-oxidized to acid in alkaline electrolytes. Herein we realize the selective electrooxidation of alcohol to aldehyde on NiO by tuning the local microenvironment to salt out the aldehyde from the reaction system. The origin of the high selectivity was found to be the inhibition of the hydration of aldehydes, which is the result of the decreased alkalinity and the increased cation and substrate concentration. This strategy could salt out the aldehyde at the gas|electrolyte interface from the electrooxidation of alcohol with 100 % selectivity and be easily extended to other selective oxidation reactions, such as 5-hydroxymethyl furfural (HMF) to 2,5-furandicarboxaldehyde (DFF) and amine to an imine.

Association Between Cardiovascular Risk Factors and Serum Thyrotropin Concentration Among Healthy Chinese Subjects and Subjects with Unsuspected Subclinical Hypothyroidism.

BACKGROUND: Even within the reference range, thyrotropin (TSH) levels were found to be positively associated with the risk of cardiovascular disease (CVD). However, the underlying mechanism of TSH remains ambiguous. This study investigated the association of TSH with cardiovascular risk factors among healthy Chinese subjects and subjects with unsuspected subclinical hypothyroidism (SCH). METHODS: A total of 741 subjects were included in this cross-sectional study. The subjects were grouped into four, including tertile groups for the TSH reference range and an SCH group based on the TSH level. All the participants underwent physical examination and fasting blood analyses to determine the levels of TSH, free thyroxine, free triiodothyronine, plasma glucose, triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1, apolipoprotein B (ApoB), lipoprotein(a), homocysteine (Hcy), and high sensitivity C-reactive protein (hs-CRP). RESULTS: The TSH subgroups exhibited a significant increasing trend in terms of LDL-C, ApoB, and Hcy levels (p = 0.01, p < 0.01, and p = 0.01, respectively), whereas the HDL-C levels exhibited a decreasing trend (p = 0.03). After adjusting for gender, age, and smoking status, the TSH levels were found to be positively correlated with body mass index, waist circumference, diastolic blood pressure (DBP), and TG, TC, LDL-C, ApoB, Hcy, and hs-CRP levels (p < 0.05 for all), but negatively correlated with the HDL-C levels (p < 0.01). Multiple linear regression analysis showed that the TSH levels were independently positively associated with the female gender (ß = 0.21, p < 0.01), DBP (ß = 0.14, ß = 0.01), and Hcy levels (ß = 0.10, p = 0.01), and negatively associated with the HDL-C (ß = -0.11, p = 0.01) and FT4 levels (ß = -0.15, p < 0.01). CONCLUSIONS: The TSH levels were independently associated with several cardiovascular risk factors in an apparently healthy Chinese population, and thus may increase the risk of CVD.

Thyroid function is associated with non-alcoholic fatty liver disease in euthyroid subjects.

OBJECTIVES: This study was designed to test the hypothesis that normal thyroid function is associated with non-alcoholic fatty liver disease (NAFLD) in euthyroid general subjects. METHODS: A total of 739 euthyroid subjects were enrolled in this cross-sectional study. Using ultrasound, a diagnosis of NAFLD was made in subjects without a history of excessive alcohol consumption or liver diseases. Fasting serum samples were collected for determining thyroid function [thyroid-stimulating hormone (TSH), free thyroxine (FT4), and free triiodothyronine (FT3) levels] and other biochemical parameters. RESULTS: Among the enrolled subjects, 196 (26.5%) satisfied the diagnostic criteria for NAFLD. Subjects with NAFLD had significantly higher TSH levels and lower FT4 levels than those without NAFLD (p < 0.01 for both). NAFLD prevalence increased gradually with increasing quartiles of TSH levels and decreasing quartiles of FT4 levels. After adjustment for gender and age, TSH levels were found to correlate positively with body mass index (BMI), waist circumference (WC), and LDL-cholesterol levels (p < 0.05 for all) and negatively with HDL-cholesterol levels (p < 0.01). FT4 levels correlated negatively with both BMI and WC (p < 0.05 for both). Multiple logistic regression analysis showed that TSH and FT4 levels were independent risk factors for NAFLD [odds ratio (OR): 2.21, 95% confidence interval (CI): 1.21-4.02, p = 0.01, for TSH levels; OR: 0.39, 95% CI: 0.17-0.87, p = 0.02, for FT4 levels]. CONCLUSION: Our findings suggest that serum FT4 and TSH levels, even those within the reference range, are associated with NAFLD in the general population, independent of known metabolic risk factors.

DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.

Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA binding affinity. In this chapter, we introduce a user-friendly tool named DeepHLApan, which utilizes deep learning techniques to predict neoantigens by considering both peptide-HLA binding affinity and immunogenicity. We provide the application of DeepHLApan, along with the source code, docker version, and web-server. These resources are freely available at https://github.com/zjupgx/deephlapan and http://pgx.zju.edu.cn/deephlapan/ .

In Situ Formation of Hydrogel Wound Dressing Based on Carboxymethyl Chitin/Tannic Acid for Promoting Skin Wound Healing.

Triggering the healing process of drug-resistant bacteria-infected wounds has attracted great attention due to global morbidity that may induce gangrene, amputation, and even death. Here, a chitin derivative, carboxymethyl chitosan (CMC), tannic acid (TA), and Cu2+ were used for hydrogel engineering. Using sodium bicarbonate as the neutralizer and reductant, hydrogen bonds between CMC and TA and in situ Cu(OH)2 generation via ion coordination force between Cu2+ and TA facilitated the synthesis of CMC/TA/Cu hydrogel. Cu2+ and TA release, cytotoxicity, in vitro cell migration, angiogenesis, and antidrug-resistant bacteria were measured. Besides, wound closure was evaluated in vivo using the methicillin-resistant Staphylococcus aureus (MRSA)-infected excisional dermal wound mouse model. Negligible toxicity was observed both in vitro and in vivo. Dermal cell migration and angiogenesis were significantly enhanced. In vivo, the CMC/TA/Cu hydrogel induced effective re-epithelialization, collagen deposition, inflammatory alleviation, and MRSA inhibition during wound repair in mice. All these results confirmed that the CMC/TA/Cu hydrogel is a promising novel dressing for chronic wound healing in clinic.

Optimal Irreversible Electroporation Combined with Nano-Enabled Immunomodulatory to Boost Systemic Antitumor Immunity.

In this work, we proposed nµPEF, a novel pulse configuration combining nanosecond and microsecond pulses (nµPEF), to enhance tumor ablation in irreversible electroporation (IRE) for oncological therapy. nµPEF demonstrated improved efficacy in inducing immunogenic cell death, positioning it as a potential candidate for next-generation ablative therapy. However, the immune response elicited by nµPEF alone was insufficient to effectively suppress distant tumors. To address this limitation, we developed PPR@CM-PD1, a genetically engineered nanovesicle. PPR@CM-PD1 employed a polyethylene glycol-polylactic acid-glycolic acid (PEG-PLGA) nanoparticle encapsulating the immune adjuvant imiquimod and coated with a genetically engineered cell membrane expressing programmed cell death protein 1 (PD1). This design allowed PPR@CM-PD1 to target both the innate immune system through toll-like receptor 7 (TLR7) agonism and the adaptive immune system through programmed cell death protein 1/programmed cell death-ligand 1 (PD1/PDL1) checkpoint blockade. In turn, nµPEF facilitated intratumoral infiltration of PPR@CM-PD1 by modulating the tumor stroma. The combination of nµPEF and PPR@CM-PD1 generated a potent and systemic antitumor immune response, resulting in remarkable suppression of both nµPEF-treated and untreated distant tumors (abscopal effects). This interdisciplinary approach presents a promising perspective for oncotherapy and holds great potential for future clinical applications.

Combining anodic alcohol oxidative coupling for C-C bond formation with cathodic ammonia production.

Electrocatalytic oxidation of alcohols using heterogeneous catalysts is a promising aqueous, energy-efficient and environmentally friendly approach, especially for coupling different alcohols to prolong the carbon chain via co-oxidation. Precisely regulating critical steps to tailor electrode materials and electrolyte composition is key to selectively coupling alcohols for targeted synthesis. However, selectively coupling different alcohols remains challenging due to the lack of effective catalyst and electrolyte design promoting specific pathways. Herein, we demonstrate a paired electrolysis strategy for combining anodic oxidative coupling of ethanol (EtOH) and benzyl alcohol (PhCH2OH) to synthesize cinnamaldehyde (CAL) and cathodic ammonia production. The strategies involve: (i) utilizing the salt-out effect to balance selective oxidation and coupling rates; (ii) developing platinum-loaded nickel hydroxide electrocatalysts to accelerate intermediate coupling kinetics; (iii) introducing thermodynamically favorable nitrate reduction at the cathode to improve coupling selectivity by avoiding hydrogenation of products while generating valuable ammonia instead of hydrogen. We achieved 85% coupling selectivity and 278 µmol/h NH3 productive rate at 100 mA/cm2 with a low energy input (∼1.63 V). The membrane-free, low energy, scalable approach with a wide substrate scope highlights promising applications of this methodology. This work advances heterogeneous electrocatalytic synthesis through rational design principles that integrate anodic oxidative coupling with cathodic nitrate reduction reactions, having synergistic effects on efficiency and selectivity.

STING Agonist-Loaded Nanoparticles Promotes Positive Regulation of Type I Interferon-Dependent Radioimmunotherapy in Rectal Cancer.

Hypoxia-associated radioresistance in rectal cancer (RC) has severely hampered the response to radioimmunotherapy (iRT), necessitating innovative strategies to enhance RC radiosensitivity and improve iRT efficacy. Here, a catalytic radiosensitizer, DMPtNPS, and a STING agonist, cGAMP, are integrated to overcome RC radioresistance and enhance iRT. DMPtNPS promotes efficient X-ray energy transfer to generate reactive oxygen species, while alleviating hypoxia within tumors, thereby increasing radiosensitivity. Mechanistically, the transcriptomic and immunoassay analysis reveal that the combination of DMPtNPS and RT provokes bidirectional regulatory effects on the immune response, which may potentially reduce the antitumor efficacy. To mitigate this, cGAMP is loaded into DMPtNPS to reverse the negative impact of DMPtNPS and RT on the tumor immune microenvironment (TiME) through the type I interferon-dependent pathway, which promotes cancer immunotherapy. In a bilateral tumor model, the combination treatment of RT, DMPtNPS@cGAMP, and αPD-1 demonstrates a durable complete response at the primary site and enhanced abscopal effect at the distant site. This study highlights the critical role of incorporating catalytic radiosensitizers and STING agonists into the iRT approach for RC.

TSNAD and TSNAdb: The Useful Toolkit for Clinical Application of Tumor-Specific Neoantigens.

Tumor-specific neoantigens play important roles in tumor immunotherapy. How to predict neoantigens accurately and efficiently has attracted much attention. TSNAD is the first one-stop neoantigen prediction tool from next-generation sequencing data, and TSNAdb provides both predicted and validated neoantigens based on pan-cancer immunogenomics analyses. In this chapter, we describe the usage of TSNAD and TSNAdb for the clinical application of neoantigens. The latest version of TSNAD is available at https://pgx.zju.edu.cn/tsnad , and the latest version of TSNAdb is available at https://pgx.zju.edu.cn/tsnadb .

DeepCIP: A multimodal deep learning method for the prediction of internal ribosome entry sites of circRNAs.

Circular RNAs (circRNAs) have been found to have the ability to encode proteins through internal ribosome entry sites (IRESs), which are essential RNA regulatory elements for cap-independent translation. Identification of IRES elements in circRNA is crucial for understanding its function. Previous studies have presented IRES predictors based on machine learning techniques, but they were mainly designed for linear RNA IRES. In this study, we proposed DeepCIP (Deep learning method for CircRNA IRES Prediction), a multimodal deep learning approach that employs both sequence and structural information for circRNA IRES prediction. Our results demonstrate the effectiveness of the sequence and structure models used by DeepCIP in feature extraction and suggest that integrating sequence and structural information efficiently improves the accuracy of prediction. The comparison studies indicate that DeepCIP outperforms other comparative methods on the test set and real circRNA IRES dataset. Furthermore, through the integration of an interpretable analysis mechanism, we elucidate the sequence patterns learned by our model, which align with the previous discovery of motifs that facilitate circRNA translation. Thus, DeepCIP has the potential to enhance the study of the coding potential of circRNAs and contribute to the design of circRNA-based drugs. DeepCIP as a standalone program is freely available at https://github.org/zjupgx/DeepCIP.

Early outcomes of the "Chimney" commando procedure in the small aortic and mitral annuli.

Background: Commando procedure, the surgical replacement of the mitral and aortic valves combined with reconstruction of the fibrosa fibrous body, is a technical challenge in patients with small aortic and mitral annuli. In this study, we evaluated the safety and early outcomes of the "Chimney" modality of the Commando procedure, in patients with small aortic and mitral annuli, after prior valve surgery, using a self-assembled valved conduit. Methods: From April 2021 to April 2022, 30 consecutive cases of the "Chimney" Commando procedure, with a self-assembled valved conduit and other combined cardiac procedures, were fully performed for re-operative patients with small aortic roots. Data were obtained through a medical record review, at the Asian Heart Hospital in Wuhan, China. Results: The patient's mean age was 52.7 ± 13.53 years, with 93.3% females. All patients had a previous heart valve surgery, 90% of which had double valve replacement (DVR). Hospital death occurred in 3.3% (n = 1) of the patients, due to malignant arrhythmias and multiorgan failure. Postoperative echocardiogram exams showed that the sizes of the aortic and mitral valve prostheses were 24.23 ± 1.60 mm and 28.33 ± 1.21 mm, respectively. All patients had intact intervalvular fibrosa (IVF) repair and no patient had any aberration in the left heart chamber communication. With the exception of one postoperative sick sinus syndrome and one re-sternotomy for bleeding, there were no significant postoperative complications, such as mortality, renal failure requiring ongoing dialysis, or mediastinitis. Echocardiography exams in the sixth postoperative month showed that the mean gradients of the aortic and mitral valves were 16.26 ± 6.44 mmHg and 11.24 ± 4.90 mmHg, respectively. Conclusions: In comparison with the standard Commando operation, the early outcomes and safety of the "Chimney" Commando procedure proved to be a feasible therapeutic option for patients with small aortic and mitral annuli, after prior valve operations. This approach enables the enlargement of the aortic and mitral annuli and the implantation of the necessary valve prosthesis.

DeepTAP: An RNN-based method of TAP-binding peptide prediction in the selection of tumor neoantigens.

The transport of peptides from the cytoplasm to the endoplasmic reticulum (ER) by transporters associated with antigen processing (TAP) is a critical step in the intracellular presentation of cytotoxic T lymphocyte (CTL) epitopes. The development and application of computational methods, especially deep learning methods and new neural network strategies that can automatically learn feature representations with limited knowledge, provide an opportunity to develop fast and efficient methods to identify TAP-binding peptides. Herein, this study presents a comprehensive analysis of TAP-binding peptide sequences to derive TAP-binding motifs and preferences for N-terminal and C-terminal amino acids. A novel recurrent neural network (RNN)-based method called DeepTAP, using bidirectional gated recurrent unit (BiGRU), was developed for the accurate prediction of TAP-binding peptides. Our results demonstrated that DeepTAP achieves an optimal balance between prediction precision and false positives, outperforming other baseline models. Furthermore, DeepTAP significantly improves the prediction accuracy of high-confidence neoantigens, especially the top-ranked ones, making it a valuable tool for researchers studying antigen presentation processes and T-cell epitope screening. DeepTAP is freely available at https://github.com/zjupgx/deeptap and https://pgx.zju.edu.cn/deeptap.

TSNAdb v2.0: The Updated Version of Tumor-specific Neoantigen Database.

In recent years, neoantigens have been recognized as ideal targets for tumor immunotherapy. With the development of neoantigen-based tumor immunotherapy, comprehensive neoantigen databases are urgently needed to meet the growing demand for clinical studies. We have built the tumor-specific neoantigen database (TSNAdb) previously, which has attracted much attention. In this study, we provide TSNAdb v2.0, an updated version of the TSNAdb. TSNAdb v2.0 offers several new features, including (1) adopting more stringent criteria for neoantigen identification, (2) providing predicted neoantigens derived from three types of somatic mutations, and (3) collecting experimentally validated neoantigens and dividing them according to the experimental level. TSNAdb v2.0 is freely available at https://pgx.zju.edu.cn/tsnadb/.

Comprehensive analysis of the fates and risks of veterinary antibiotics in a small ecosystem comprising a pig farm and its surroundings in Northeast China.

This study investigated the behavior of veterinary antibiotics (VAs) in a small farm ecosystem. Manure and environmental samples were collected around a large pig farm in northeast China. Thirty-four VAs in six categories were analyzed. Then, a multimedia fugacity model was used to estimate the fates of VAs in the environment. The results showed that VAs were prevalent in manure, soil, water, and sediment, but not in crops. Compared with fresh manure, VA levels were significantly lower in surface manure piles left in the open air for 3-6 months. The main VAs, tetracyclines and quinolones, decreased by 427.12 and 158.45 µg/kg, respectively. VAs from manure piles were transported to the surroundings and migrated vertically into deep soil. The concentrations of ∑VAs detected in agricultural soils were 0.03-4.60 µg/kg; > 94% of the mass inventory of the VAs was retained in soil organic matter (SOM), suggesting that SOM is the main reservoir for antibiotics in soil. Risk assessment and model analysis indicated that the negative impact of mixed antibiotics at low concentrations in farmland on crops may be mediated by indirect effects, rather than direct effects. Our findings highlight the environmental fates and risks of antibiotics from livestock farms.