Invoking Interfacial Engineering Boosts Structural Stability Empowering Exceptional Cyclability of Ni-Rich Cathode.

The cycling stability of LiNi0.8Co0.1Mn0.1O2 under high voltages is hindered by the occurrence of hybrid anion- and cation-redox processes, leading to oxygen escape and uncontrolled phase collapse. In this study, we propose an interfacial engineering strategy involving a straightforward mechanical ball milling and low-temperature calcination, employing a Se-doped and FeSe2&Fe2O3-modified approach to design a stable Ni-rich cathode. Se2- are selectively adsorbed within oxygen vacancies to form O-TM-Se bond, effectively stabilizing lattice oxygen, and preventing structural distortion. Simultaneously, the Se-NCM811//FeSe2//Fe2O3 self-assembled electric field is activated, improving interfacial charge transfer and coupling. Furthermore, FeSe2 accelerates Li+ diffusion and reacts with oxygen to form Fe2O3 and SeO2. The Fe2O3 coating mitigates HF erosion and acts as an electrostatic shield layer, limiting the outward migration of oxygen anions. Impressively, the modified materials exhibit significantly improved electrochemical performance, with a capacity retention of 79.7% after 500 cycles at 1C under 4.5 V. Furthermore, it provides an extraordinary capacity retention of 94.6% in 3 - 4.25 V after 550 cycles in pouch-type full battery. This dual-modification approach demonstrates its feasibility and opens new perspectives for the development of stable lithium-ion batteries operating at high voltages. This article is protected by copyright. All rights reserved.

Superionic Conduction in K3SbS4 Enabled by Cl-Modified Anion Lattice.

All-solid-state potassium batteries emerge as promising alternatives to lithium batteries, leveraging their high natural abundance and cost-effectiveness. Developing potassium solid electrolytes (SEs) with high room-temperature ionic conductivity is critical for realizing efficient potassium batteries. In this study, we present the synthesis of K2.98Sb0.91S3.53Cl0.47, showcasing a room-temperature ionic conductivity of 0.32 mS/cm and a low activation energy of 0.26 eV. This represents an increase of over two orders of magnitude compared to the parent compound K3SbS4, marking the highest reported ionic conductivity for non-oxide potassium SEs. Solid-state 39K magic-angle-spinning nuclear magnetic resonance on K2.98Sb0.91S3.53Cl0.47 reveals an increased population of mobile K+ ions with fast dynamics. Ab initio molecular dynamics (AIMD) simulations further confirm a delocalized K+ density and significantly enhanced K+ diffusion. This work demonstrates diversification of the anion sublattice as an effective approach to enhance ion transport and highlights K2.98Sb0.91S3.53Cl0.47 as a promising SE for all-solid-state potassium batteries.

Cognitive function of children with biliary atresia after primary living donor liver transplantation.

BACKGROUND: The survival rate of children with biliary atresia (BA) after liver transplantation (LT) is significantly improved, and their quality of life has attracted much attention.This study aimed to investigate the cognition and its influencing factors in children with BA after primary living donor LT (BA-pLDLT) during infancy. METHODS: Children with BA were recruited 6 months after pLDLT at Children's Hospital of Chongqing Medical University (2018-2022). Demographic and clinical data were collected from the health information system. Cognition was assessed using the Chinese version of the Griffiths Mental Development scale (GMDS-C). Multivariate linear regression were used to analyze the influencing factors of their cognitive function. RESULTS: In total, 57 children with BA-pLDLT, aged 5.00(3.90-9.30) months at transplantation and 25.00(14.00-60.80) months at evaluation were included. The general developmental quotient (89.02 ± 12.07) and motor, language, eye-hand coordination, performance, and practical reasoning quotients of these children were significantly lower than the normative mean values of GMDS-C(P < 0.05). Of the 57 children, 16 (28.07%) had borderline developmental delay (DQ between 70 and 84), 3 (5.26%) had developmental delay (DQ < 70), and 11(19.29%) had language delay. Reoperation for biliary or vascular complications after pLDLT was a risk factor for decreased general development quotient and motor quotient and lower ZW at assessment was associated with decline motor quotient. CONCLUSION: Children with BA-pLDLT have varying degrees of developmental delays in early life. Reoperation and nutritional deficiencies had adverse effects on cognitive development.

A Study of Biomedical Relation Extraction Using GPT Models.

Relation Extraction (RE) is a natural language processing (NLP) task for extracting semantic relations between biomedical entities. Recent developments in pre-trained large language models (LLM) motivated NLP researchers to use them for various NLP tasks. We investigated GPT-3.5-turbo and GPT-4 on extracting the relations from three standard datasets, EU-ADR, Gene Associations Database (GAD), and ChemProt. Unlike the existing approaches using datasets with masked entities, we used three versions for each dataset for our experiment: a version with masked entities, a second version with the original entities (unmasked), and a third version with abbreviations replaced with the original terms. We developed the prompts for various versions and used the chat completion model from GPT API. Our approach achieved a F1-score of 0.498 to 0.809 for GPT-3.5-turbo, and a highest F1-score of 0.84 for GPT-4. For certain experiments, the performance of GPT, BioBERT, and PubMedBERT are almost the same.

Me-LLaMA: Foundation Large Language Models for Medical Applications.

Recent advancements in large language models (LLMs) such as ChatGPT and LLaMA have hinted at their potential to revolutionize medical applications, yet their application in clinical settings often reveals limitations due to a lack of specialized training on medical-specific data. In response to this challenge, this study introduces Me-LLaMA, a novel medical LLM family that includes foundation models - Me-LLaMA 13/70B, along with their chat-enhanced versions - Me-LLaMA 13/70B-chat, developed through continual pre-training and instruction tuning of LLaMA2 using large medical datasets. Our methodology leverages a comprehensive domain-specific data suite, including a large-scale, continual pre-training dataset with 129B tokens, an instruction tuning dataset with 214k samples, and a new medical evaluation benchmark (MIBE) across six critical medical tasks with 12 datasets. Our extensive evaluation using the MIBE shows that Me-LLaMA models achieve overall better performance than existing open-source medical LLMs in zero-shot, few-shot and supervised learning abilities. With task-specific instruction tuning, Me-LLaMA models outperform ChatGPT on 7 out of 8 datasets and GPT-4 on 5 out of 8 datasets. In addition, we investigated the catastrophic forgetting problem, and our results show that Me-LLaMA models outperform other open-source medical LLMs in mitigating this issue. Me-LLaMA is one of the largest open-source medical foundation LLMs that use both biomedical and clinical data. It exhibits superior performance across both general and medical tasks compared to other open-source medical LLMs, rendering it an attractive choice for medical AI applications. We release our models, datasets, and evaluation scripts at: https://github.com/BIDS-Xu-Lab/Me-LLaMA.

Structure-activity relationship between gold nanoclusters and human serum albumin: Effects of ligand isomerization.

The interactions between gold nanoclusters (AuNCs) and proteins have been extensively investigated. Nevertheless, the structure-activity relationship between gold nanoclusters and proteins in terms of ligand isomerization remained unclear. Here, interactions between Au25NCs modified with para-, inter- and ortho-mercaptobenzoic acid (p/m/o-MBA-Au25NCs) and human serum albumin (HSA) were analyzed. The results of the multispectral approach showed that all three gold nanoclusters bound to the site I in dynamic modes to increase the stability of HSA. There were significant differences in the binding intensity, thermodynamic parameters, main driving forces, and binding ratios between these three gold nanoclusters and HSA, which might be related to the existence forms of the three ligands on the surface of AuNCs. Due to the different polarities of AuNCs themselves, the impact of three AuNCs on the microenvironment of amino acid residues in HSA was also different. It could be seen that ligand isomerization significantly affected the interactions between gold nanoclusters and proteins. This work will provide theoretical guidance for ligand selection and biological applications of metal nanoclusters.

Exploring Infantile Epileptic Spasm Syndrome: A Proteomic Analysis of Plasma Using the Data-Independent Acquisition Approach.

This study aimed to identify characteristic proteins in infantile epileptic spasm syndrome (IESS) patients' plasma, offering insights into potential early diagnostic biomarkers and its underlying causes. Plasma samples were gathered from 60 patients with IESS and 40 healthy controls. Data-independent acquisition proteomic analysis was utilized to identify differentially expressed proteins (DEPs). These DEPs underwent functional annotation through Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Gene set enrichment analysis (GSEA) was employed for both GO (GSEA-GO) and KEGG (GSEA-KEGG) analyses to examine the gene expression profiles. Receiver operating characteristic (ROC) curves assessed biomarkers' discriminatory capacity. A total of 124 DEPs were identified in IESS patients' plasma, mainly linked to pathways, encompassing chemokines, cytokines, and oxidative detoxification. GSEA-GO and GSEA-KEGG analyses indicated significant enrichment of genes associated with cell migration, focal adhesion, and phagosome pathways. ROC curve analysis demonstrated that the combination of PRSS1 and ACTB, PRSS3, ACTB, and PRSS1 alone exhibited AUC values exceeding 0.7. This study elucidated the significant contribution of cytokines, chemokines, oxidative detoxification, and phagosomes to the IESS pathogenesis. The combination of PRSS1 and ACTB holds promise as biomarkers for the early diagnosis of IESS.

AKI-Pro score for predicting progression to severe acute kidney injury or death in patients with early acute kidney injury after cardiac surgery.

BACKGROUND: No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. METHODS: In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. RESULTS: The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P < 0.05). CONCLUSIONS: The AKI-Pro score is a new clinical tool that could assist clinicians to identify early AKI patients at high risk for AKI progression or death.

Cross-modal attention network for retinal disease classification based on multi-modal images.

Multi-modal eye disease screening improves diagnostic accuracy by providing lesion information from different sources. However, existing multi-modal automatic diagnosis methods tend to focus on the specificity of modalities and ignore the spatial correlation of images. This paper proposes a novel cross-modal retinal disease diagnosis network (CRD-Net) that digs out the relevant features from modal images aided for multiple retinal disease diagnosis. Specifically, our model introduces a cross-modal attention (CMA) module to query and adaptively pay attention to the relevant features of the lesion in the different modal images. In addition, we also propose multiple loss functions to fuse features with modality correlation and train a multi-modal retinal image classification network to achieve a more accurate diagnosis. Experimental evaluation on three publicly available datasets shows that our CRD-Net outperforms existing single-modal and multi-modal methods, demonstrating its superior performance.

Pyramid Pixel Context Adaption Network for Medical Image Classification With Supervised Contrastive Learning.

Spatial attention (SA) mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency modeling. However, it may perform poorly in medical image analysis. Unfortunately, the existing efforts are often unaware that long-range dependency modeling has limitations in highlighting subtle lesion regions. To overcome this limitation, we propose a practical yet lightweight architectural unit, pyramid pixel context adaption (PPCA) module, which exploits multiscale pixel context information to recalibrate pixel position in a pixel-independent manner dynamically. PPCA first applies a well-designed cross-channel pyramid pooling (CCPP) to aggregate multiscale pixel context information, then eliminates the inconsistency among them by the well-designed pixel normalization (PN), and finally estimates per pixel attention weight via a pixel context integration. By embedding PPCA into a DNN with negligible overhead, the PPCA network (PPCANet) is developed for medical image classification. In addition, we introduce supervised contrastive learning to enhance feature representation by exploiting the potential of label information via supervised contrastive loss (CL). The extensive experiments on six medical image datasets show that the PPCANet outperforms state-of-the-art (SOTA) attention-based networks and recent DNNs. We also provide visual analysis and ablation study to explain the behavior of PPCANet in the decision-making process.

Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease.

Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.

Linking the relationship between dietary folic acid intake and risk of osteoporosis among middle-aged and older people: A nationwide population-based study.

Among middle-aged and older people, balanced and nutritious diets are the foundation for maintaining bone health and preventing osteoporosis. This study is aimed at investigating the link between dietary folic acid intake and the risk of osteoporosis among middle-aged and older people. A total of 20,686 people from the National Health and Nutritional Examination Survey (NHANES) 2007-2010 are screened and included, and 5312 people aged ≥45 years with integral data are ultimately enrolled in evaluation. Demographics and dietary intake-related data are gathered and analyzed, and the odds ratio (OR) and 95% confidence interval (CI) of each tertile category of dietary folic acid intake and each unit increase in folic acid are assessed via multivariate logistic regression models. On this basis, the receiver operating characteristic (ROC) curve is used to identify the optimal cutoff value of dietary folic acid intake for indicating the risk of osteoporosis. Of 5312 people with a mean age of 62.4 ± 11.0 years old, a total of 513 people with osteoporosis are screened, and the dietary folic acid intake amount of the osteoporosis group is significantly lower than that of the non-osteoporosis group (p < .001). The lowest tertile category is then used to act as a reference category, and a higher dietary folic acid intake amount is observed to be positively related to lower odds for risk of osteoporosis. This trend is also not changed in adjustments for combinations of different covariates (p all < .05). Based on this, a dietary folic acid intake of 475.5 µg/day is identified as an optimal cutoff value for revealing osteoporosis. Collectively, this nationwide population-based study reveals that a higher daily dietary folic acid intake has potential protective effects on osteoporosis in middle-aged and older people.

Altered vaginal cervical microbiota diversity contributes to HPV-induced cervical cancer via inflammation regulation.

Background: Cancer has surpassed infectious diseases and heart ailments, taking the top spot in the disease hierarchy. Cervical cancer is a significant concern for women due to high incidence and mortality rates, linked to the human papillomavirus (HPV). HPV infection leads to precancerous lesions progressing to cervical cancer. The cervix's external os, near the vagina, hosts various microorganisms. Evidence points to the link between vaginal microbiota and HPV-induced cervical cancer. Cervical cancer onset aligns with an imbalanced Th1/Th2 immune response, but the role of vaginal microbiota in modulating this imbalance is unclear. Methods: In this study, we collected vaginal samples from 99 HPV-infected patients across varying degrees of lesions, alongside control groups. These samples underwent bacterial DNA sequencing. Additionally, we employed Elisa kits to quantify the protein expression levels of Th1/Th2 cytokines IL2, IL12, IL5, IL13, and TNFa within the centrifuged supernatant of vaginal-cervical secretions from diverse research subjects. Subsequently, correlation analyses were conducted between inflammatory factors and vaginal microbiota. Results: Our findings highlighted a correlation between decreased Lactobacillus and increased Gardenerella presence with HPV-induced cervical cancer. Functionally, our predictive analysis revealed the predominant enrichment of the ABC transporter within the vaginal microbiota of cervical cancer patients. Notably, these microbiota alterations exhibited correlations with the production of Th1/Th2 cytokines, which are intimately tied to tumor immunity. Conclusions: This study suggests the potential involvement of vaginal microbiota in the progression of HPV-induced cervical cancer through Th1/Th2 cytokine regulation. This novel insight offers a fresh perspective for early cervical cancer diagnosis and future prevention strategies.

miR-181a Expressed in the Dorsal Hippocampus Regulates the Reinstatement of Cocaine CPP by Targeting PRKAA1.

Neuroadaptive changes in the hippocampus underlie addictive-like behaviors in humans or animals chronically exposed to cocaine. miR-181a, which is widely expressed in the hippocampus, acts as a regulator for synaptic plasticity, while its role in drug reinstatement is unclear. In this study, we found that miR-181a regulates the reinstatement of cocaine conditioned place preference(CPP), and altered miR-181a expression changes the complexity of hippocampal neurons and the density and morphology of dendritic spines. By using a luciferase gene reporter, we found that miR-181a targets PRKAA1, an upstream molecule in the mTOR pathway. High miR-181a expression reduced the expression of the PRKAA1 mRNA and promoted mTOR activity and the reinstatement of cocaine CPP. These results indicate that miR-181a is involved in neuronal structural plasticity induced by reinstatement of cocaine CPP, possibly through the activation of the mTOR signaling pathway. This study provides new microRNA targets and a theoretical foundation for the prevention of cocaine-induced reinstatement.

The emerging role of regulated cell death in ischemia and reperfusion-induced acute kidney injury: current evidence and future perspectives.

Renal ischemia‒reperfusion injury (IRI) is one of the main causes of acute kidney injury (AKI), which is a potentially life-threatening condition with a high mortality rate. IRI is a complex process involving multiple underlying mechanisms and pathways of cell injury and dysfunction. Additionally, various types of cell death have been linked to IRI, including necroptosis, apoptosis, pyroptosis, and ferroptosis. These processes operate differently and to varying degrees in different patients, but each plays a role in the various pathological conditions of AKI. Advances in understanding the underlying pathophysiology will lead to the development of new therapeutic approaches that hold promise for improving outcomes for patients with AKI. This review provides an overview of the recent research on the molecular mechanisms and pathways underlying IRI-AKI, with a focus on regulated cell death (RCD) forms such as necroptosis, pyroptosis, and ferroptosis. Overall, targeting RCD shows promise as a potential approach to treating IRI-AKI.

Unilateral pulmonary edema after minimally-invasive bentall procedure - Case report.

Introduction: Unilateral pulmonary edema (UPE), a life-threatening complication of cardiac surgery, often occurs after prolonged cardiopulmonary bypass and lung collapse, especially in minimally-invasive cardiac surgery (MICS). The present study reported a young patient with severe UPE after the surgery as well as corresponding clinical treatments. In addition to the supportive treatment of extracorporeal membrane oxygenation (ECMO), monitoring changes in cardiopulmonary function and early clinical interventions are crucial. Conclusion: By weighing the beneficial and detrimental effects of the treatment, it calls for early diagnosis and new therapeutic strategies for the complication.

Comparative transcriptomic analysis provides insights into the genetic networks regulating oil differential production in oil crops.

BACKGROUND: Plants differ more than threefold in seed oil contents (SOCs). Soybean (Glycine max), cotton (Gossypium hirsutum), rapeseed (Brassica napus), and sesame (Sesamum indicum) are four important oil crops with markedly different SOCs and fatty acid compositions. RESULTS: Compared to grain crops like maize and rice, expanded acyl-lipid metabolism genes and relatively higher expression levels of genes involved in seed oil synthesis (SOS) in the oil crops contributed to the oil accumulation in seeds. Here, we conducted comparative transcriptomics on oil crops with two different SOC materials. In common, DIHYDROLIPOAMIDE DEHYDROGENASE, STEAROYL-ACYL CARRIER PROTEIN DESATURASE, PHOSPHOLIPID:DIACYLGLYCEROL ACYLTRANSFERASE, and oil-body protein genes were both differentially expressed between the high- and low-oil materials of each crop. By comparing functional components of SOS networks, we found that the strong correlations between genes in "glycolysis/gluconeogenesis" and "fatty acid synthesis" were conserved in both grain and oil crops, with PYRUVATE KINASE being the common factor affecting starch and lipid accumulation. Network alignment also found a conserved clique among oil crops affecting seed oil accumulation, which has been validated in Arabidopsis. Differently, secondary and protein metabolism affected oil synthesis to different degrees in different crops, and high SOC was due to less competition of the same precursors. The comparison of Arabidopsis mutants and wild type showed that CINNAMYL ALCOHOL DEHYDROGENASE 9, the conserved regulator we identified, was a factor resulting in different relative contents of lignins to oil in seeds. The interconnection of lipids and proteins was common but in different ways among crops, which partly led to differential oil production. CONCLUSIONS: This study goes beyond the observations made in studies of individual species to provide new insights into which genes and networks may be fundamental to seed oil accumulation from a multispecies perspective.

Streptomyces virginiae XDS1-5, an antagonistic actinomycete, as a biocontrol to peach brown rot caused by Monilinia fructicola.

BACKGROUND: Peach brown rot, caused by the pathogen Monilinia fructicola, represents a significant postharvest infectious disease affecting peach fruit. This disease is responsible for a substantial increase in fruit decay rates, leading to significant economic losses, often exceeding 50%. Currently, there is a growing interest in identifying biocontrol agents to mitigate peach brown rot, with a predominant interest in Bacillus species. RESULTS: In this investigation, we isolated 410 isolates of actinomycetes from non-farmland ecosystem soil samples. Subsequently, 27 isolates exhibiting superior inhibitory capabilities were selected. Among these, strain XDS1-5 demonstrated the most robust fungistatic effect against brown rot disease, achieving an 80% inhibition rate in vitro and a 66% inhibition rate in vivo. XDS1-5 was identified as belonging to the Streptomyces virginiae species. Furthermore, a fermentation filtrate of XDS1-5 exhibited the ability to metabolize 34.21% of the tested carbon sources and 7.37% of the tested nitrogen sources. Particularly noteworthy was its capacity to disrupt the cell membrane structure directly, leading to increased cell membrane permeability and cytoplasmic leakage. Additionally, our investigation indicated that indoline, a metabolite produced by XDS1-5, played a pivotal role in inhibiting the growth of M. fructicola. CONCLUSION: In summary, our study has identified a biocontrol actinomycete, XDS1-5, with the potential to effectively inhibit postharvest brown rot disease in peaches. This finding holds great significance for the biological control of peach brown rot, offering promising prospects for mitigating the economic losses associated with this devastating disease. © 2024 Society of Chemical Industry.

SARS-CoV-2 Antibodies in Human Milk After mRNA and Adenovector-Based Vaccination: A Systematic Review and Meta-Analysis.

BACKGROUND: SARS-CoV-2 specific antibodies exist in human milk expressed by lactating parents after vaccination. In the existing research, the effects of vaccine types on human milk are inconsistent. RESEARCH AIM: This study aims to perform a systematic review and meta-analysis of the existing observational studies to compare the positive rates of SARS-CoV-2 specific antibodies in human milk according to mRNA and adenovector-based vaccination. METHODS: PubMed, Web of Science, Elsevier Science Direct and Cochrane Library databases were systematically searched for relevant articles published from December 30, 2019 to February 15, 2023. Observational studies were considered eligible provided they reported data on SARS-CoV-2 specific antibodies in human milk. The risk of bias in non-randomized studies of interventions (ROBINS-I) tool, the Newcastle-Ottawa Scale (NOS), and the Agency for Healthcare Research and Quality (AHRQ) were used to assess risk of bias. Seven studies, including 511 lactating participants, were included in this review and meta-analysis. RESULTS: The positive rate of SARS-CoV-2 IgA is higher in mRNA vaccine groups than in adenovector-based vaccine groups (OR = 4.80, 95% CI [3.04, 7.58], p < 0.001). The positive rate of SARS-CoV-2 IgG was higher in mRNA vaccines than in adenovector-based vaccines. CONCLUSIONS: Compared to adenovector-based vaccines, mRNA vaccines present a higher positivity rate of IgA and IgG in human milk after vaccination. In other words, mRNA vaccinations may offer breastfed children a higher level of protection than adenovector-based vaccinations. Further high-quality data is still required to substantiate these findings.