Immune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening post-infectious complication occurring unpredictably weeks after mild or asymptomatic SARS-CoV-2 infection. We profiled MIS-C, adult COVID-19, and healthy pediatric and adult individuals using single-cell RNA sequencing, flow cytometry, antigen receptor repertoire analysis, and unbiased serum proteomics, which collectively identified a signature in MIS-C patients that correlated with disease severity. Despite having no evidence of active infection, MIS-C patients had elevated S100A-family alarmins and decreased antigen presentation signatures, indicative of myeloid dysfunction. MIS-C patients showed elevated expression of cytotoxicity genes in NK and CD8+ T cells and expansion of specific IgG-expressing plasmablasts. Clinically severe MIS-C patients displayed skewed memory T cell TCR repertoires and autoimmunity characterized by endothelium-reactive IgG. The alarmin, cytotoxicity, TCR repertoire, and plasmablast signatures we defined have potential for application in the clinic to better diagnose and potentially predict disease severity early in the course of MIS-C.

tRFtarget 2.0: expanding the targetome landscape of transfer RNA-derived fragments.

tRFtarget 1.0 (http://trftarget.net/) is a platform consolidating both computationally predicted and experimentally validated binding sites between transfer RNA-derived fragments (tRFs) and target genes (or transcripts) across multiple organisms. Here, we introduce a newly released version of tRFtarget 2.0, in which we integrated 6 additional tRF sources, resulting in a comprehensive collection of 2614 high-quality tRF sequences spanning across 9 species, including 1944 Homo sapiens tRFs and one newly incorporated species Rattus norvegicus. We also expanded target genes by including ribosomal RNAs, long non-coding RNAs, and coding genes >50 kb in length. The predicted binding sites have surged up to approximately 6 billion, a 20.5-fold increase than that in tRFtarget 1.0. The manually curated publications relevant to tRF targets have increased to 400 and the gene-level experimental evidence has risen to 232. tRFtarget 2.0 introduces several new features, including a web-based tool that identifies potential binding sites of tRFs in user's own datasets, integration of standardized tRF IDs, and inclusion of external links to contents within the database. Additionally, we enhanced website framework and user interface. With these improvements, tRFtarget 2.0 is more user-friendly, providing researchers a streamlined and comprehensive platform to accelerate their research progress.

A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy.

Computational cell type deconvolution on bulk transcriptomics data can reveal cell type proportion heterogeneity across samples. One critical factor for accurate deconvolution is the reference signature matrix for different cell types. Compared with inferring reference signature matrices from cell lines, rapidly accumulating single-cell RNA-sequencing (scRNA-seq) data provide a richer and less biased resource. However, deriving cell type signature from scRNA-seq data is challenging due to high biological and technical noises. In this article, we introduce a novel Bayesian framework, tranSig, to improve signature matrix inference from scRNA-seq by leveraging shared cell type-specific expression patterns across different tissues and studies. Our simulations show that tranSig is robust to the number of signature genes and tissues specified in the model. Applications of tranSig to bulk RNA sequencing data from peripheral blood, bronchoalveolar lavage and aorta demonstrate its accuracy and power to characterize biological heterogeneity across groups. In summary, tranSig offers an accurate and robust approach to defining gene expression signatures of different cell types, facilitating improved in silico cell type deconvolutions.

PTMint database of experimentally verified PTM regulation on protein-protein interaction.

MOTIVATION: Post-translational modification (PTM) is an important biochemical process. which includes six most well-studied types: phosphorylation, acetylation, methylation, sumoylation, ubiquitylation and glycosylation. PTM is involved in various cell signaling pathways and biological processes. Abnormal PTM status is closely associated with severe diseases (such as cancer and neurologic diseases) by regulating protein functions, such as protein-protein interactions (PPIs). A set of databases was constructed separately for PTM sites and PPI; however, the resource of regulation for PTM on PPI is still unsolved. RESULTS: Here, we firstly constructed a public accessible database of PTMint (PTMs that are associated with PPIs) (https://ptmint.sjtu.edu.cn/) that contains manually curated complete experimental evidence of the PTM regulation on PPIs in multiple organisms, including Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Currently, the first version of PTMint encompassed 2477 non-redundant PTM sites in 1169 proteins affecting 2371 protein-protein pairs involving 357 diseases. Various annotations were systematically integrated, such as protein sequence, structure properties and protein complex analysis. PTMint database can help to insight into disease mechanism, disease diagnosis and drug discovery associated with PTM and PPI. AVAILABILITY AND IMPLEMENTATION: PTMint is freely available at: https://ptmint.sjtu.edu.cn/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Clinical sonochemotherapy of inoperable pancreatic cancer using diagnostic ultrasound and microbubbles: a multicentre, open-label, randomised, controlled trial.

OBJECTIVES: Sonochemotherapy, which uses microbubble (MB)-assisted ultrasound (US) to deliver chemotherapeutic agents, has the potential to enhance tumour chemotherapy. The combination of US and MB has been demonstrated to prolong the survival of patients with pancreatic cancer. This phase 2 clinical trial aimed to determine the clinical efficacy and safety of sonochemotherapy for inoperable pancreatic ductal adenocarcinoma by using US and MB. METHODS: Eighty-two patients with stage III or IV pancreatic cancer were recruited from July 2018 to March 2021 and followed up until September 2022. US treatment was performed with a modified diagnostic US scanner for 30 min after chemotherapeutic infusion. The primary endpoint was overall survival (OS), and the secondary endpoints were Eastern Cooperative Oncology Group (ECOG) status < 2, progression-free survival (PFS), disease control rate (DCR), and adverse events. RESULTS: Seventy-eight patients were randomly allocated (40 to chemotherapy and 38 to sonochemotherapy). The median OS was longer with sonochemotherapy than with chemotherapy (9.10 vs. 6.10 months; p = 0.037). The median PFS with sonochemotherapy was 5.50 months, compared with 3.50 months (p = 0.080) for chemotherapy. The time of ECOG status < 2 was longer with sonochemotherapy (7.20 months) than with chemotherapy (5.00 months; p = 0.029). The DCR was 73.68% for sonochemotherapy compared with 42.50% for the control (p = 0.005). The incidence of overall adverse events was balanced between the two groups. CONCLUSIONS: The use of sonochemotherapy can extend the survival and well-being time of stage III or IV pancreatic cancer patients without any increase in serious adverse events. TRIAL REGISTRATION: ChineseClinicalTrials.gov ChiCTR2100044721 CLINICAL RELEVANCE STATEMENT: This multicentre, randomised, controlled trial has proven that sonochemotherapy, namely, the combination of diagnostic ultrasound, microbubbles, and chemotherapy, could extend the overall survival of patients with end-stage pancreatic ductal adenocarcinoma from 6.10 to 9.10 months without increasing any serious adverse events. KEY POINTS: • This is the first multicentre, randomised, controlled trial of sonochemotherapy for clinical pancreatic cancer treatment using ultrasound and a commercial ultrasound contrast agent. • Sonochemotherapy extended the median overall survival from 6.10 (chemotherapy alone) to 9.10 months. • The disease control rate increased from 42.50% with chemotherapy to 73.68% with sonochemotherapy.

Ultrasound-Induced Tumor Perfusion Changes and Doxorubicin Delivery: A Study on Pulse Length and Pulse Repetition Frequency.

OBJECTIVES: To investigate the appropriate combination of pulse length (PL) and pulse repetition frequency (PRF) when performing ultrasound stimulated microbubble (USMB) to enhance doxorubicin (DOX) delivery to tumors. METHODS: A total of 48 tumor-bearing mice were divided into four groups, namely groups A-D. The mice in groups B-D were treated with chemotherapy and USMB treatment with different combinations of PL and PRF, and group A was control. Contrast-enhanced ultrasound imaging was conducted to analyze tumor blood perfusion. Fluorescence microscopy and high-performance liquid chromatography were used to qualitatively and quantitatively analyse DOX release. The structural changes of tumors were observed under light microscope and transmission electron microscope. Furthermore, another 24 tumor-bearing mice were treated with sonochemotherapy and some related inflammatory factors were measured to explore the underlying mechanism. RESULTS: With PL of three cycles and PRF of 2 kHz, the tumor perfusion area ratio increased by 26.67%, and the DOX concentration was 4.69 times higher than the control (P < .001). With PL of 34.5 cycles and PRF of 200 Hz, the tumor perfusion area ratio decreased by 12.7% and DOX did not exhibit increased extravasation compared with the control. Microvascular rupture and hemorrhage were observed after long PL and low PRF treatment. While vasodilation and higher levels of some vasodilator inflammatory factors were found after treatment with short PL and high PRF. CONCLUSIONS: USMB treatment using short PL and high PRF could enhance tumor blood perfusion and increase DOX delivery, whereas long PL and low PRF could not serve the same purpose.

tRFtarget: a database for transfer RNA-derived fragment targets.

Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs and play important roles in biological and physiological processes. Prediction of tRF target genes and binding sites is crucial in understanding the biological functions of tRFs in the molecular mechanisms of human diseases. We developed a publicly accessible web-based database, tRFtarget (http://trftarget.net), for tRF target prediction. It contains the computationally predicted interactions between tRFs and mRNA transcripts using the two state-of-the-art prediction tools RNAhybrid and IntaRNA, including location of the binding sites on the target, the binding region, and free energy of the binding stability with graphic illustration. tRFtarget covers 936 tRFs and 135 thousand predicted targets in eight species. It allows researchers to search either target genes by tRF IDs or tRFs by gene symbols/transcript names. We also integrated the manually curated experimental evidence of the predicted interactions into the database. Furthermore, we provided a convenient link to the DAVID® web server to perform downstream functional pathway analysis and gene ontology annotation on the predicted target genes. This database provides useful information for the scientific community to experimentally validate tRF target genes and facilitate the investigation of the molecular functions and mechanisms of tRFs.

Integrated Analysis of Tracheobronchial Fluid from Before and After Cardiopulmonary Bypass Reveals Activation of the Integrated Stress Response and Altered Pulmonary Microvascular Permeability.

Objective: We aim to comprehensively describe the transcriptional activity and signaling of pulmonary parenchymal and immune cells before and after cardiopulmonary bypass (CPB) by using a multi-omic approach coupled with functional cellular assays. We hypothesize that key signaling pathways from specific cells within the lung alter pulmonary endothelial cell function resulting in worsening or improving disease. Methods: We collected serial tracheobronchial lavage samples from intubated patients less than 2-years-old undergoing surgery with CPB. Samples were immediately processed for single cell RNA sequencing (10x Genomics). Cell clustering, cell-type annotation, and visualization were performed, and differentially expressed genes (DEG) between serial samples were identified. Metabolomic and proteomic analyses were performed on the supernatant using mass spectrometry and a multiplex assay (SomaScan) respectively. Functional assays were done using electric cell-substrate impedance sensing to measure resistance across human pulmonary microvascular endothelial cells (HPMECs). Results: Analysis of eight patients showed a heterogeneous mixture of pulmonary parenchymal and immune cells. Cell clustering demonstrated time-dependent changes in the transcriptomic signature indicating altered cellular phenotypes after CPB. DEG analysis was represented by genes involved in host defense, innate immunity, and the mitochondrial respiratory transport chain. Ingenuity pathway analysis showed upregulation of the integrated stress response across all cell types after CPB. Metabolomic analysis demonstrated upregulation of ascorbate and aldarate metabolism. Unbiased proteomic analysis revealed upregulation of proteins involved in cytokine and chemokine pathways. Post-CPB patient supernatant improved HMPEC barrier function, suggesting a protective cellular response to CPB. Conclusion: Children who undergo CPB for cardiac surgery have distinct cell populations, transcriptional activity, and metabolism that change over time. The response to ischemia-reperfusion injury in the lower airway of children appears to be protective, with the need to identify potential targets through future investigations.

Improving accuracy of estimating glomerular filtration rate using artificial neural network: model development and validation.

BACKGROUND: The performance of previously published glomerular filtration rate (GFR) estimation equations degrades when directly used in Chinese population. We incorporated more independent variables and using complicated non-linear modeling technology (artificial neural network, ANN) to develop a more accurate GFR estimation model for Chinese population. METHODS: The enrolled participants came from the Third Affiliated Hospital of Sun Yat-sen University, China from Jan 2012 to Jun 2016. Participants with age < 18, unstable kidney function, taking trimethoprim or cimetidine, or receiving dialysis were excluded. Among the finally enrolled 1952 participants, 1075 participants (55.07%) from Jan 2012 to Dec 2014 were assigned as the development data whereas 877 participants (44.93%) from Jan 2015 to Jun 2016 as the internal validation data. We in total developed 3 GFR estimation models: a 4-variable revised CKD-EPI (chronic kidney disease epidemiology collaboration) equation (standardized serum creatinine and cystatin C, age and gender), a 9-variable revised CKD-EPI equation (additional auxiliary variables: body mass index, blood urea nitrogen, albumin, uric acid and hemoglobin), and a 9-variable ANN model. RESULTS: Compared with the 4-variable equation, the 9-variable equation could not achieve superior performance in the internal validation data (mean of difference: 5.00 [3.82, 6.54] vs 4.67 [3.55, 5.90], P = 0.5; interquartile range (IQR) of difference: 18.91 [17.43, 20.48] vs 20.11 [18.46, 21.80], P = 0.05; P30: 76.6% [73.7%, 79.5%] vs 75.8% [72.9%, 78.6%], P = 0.4), but the 9-variable ANN model significantly improve bias and P30 accuracy (mean of difference: 2.77 [1.82, 4.10], P = 0.007; IQR: 19.33 [17.77, 21.17], P = 0.3; P30: 80.0% [77.4%, 82.7%], P < 0.001). CONCLUSIONS: It is suggested that using complicated non-linear models like ANN could fully utilize the predictive ability of the independent variables, and then finally achieve a superior GFR estimation model.

Echocardiographic and pathomorphological features in fetuses with ductal-dependent congenital heart diseases.

OBJECTIVE: To individually analyze echocardiographic features in fetuses with ductal-dependent congenital heart diseases (DDCHD) and to verify the anatomical characteristics corresponding to the echocardiogram scan views. BACKGROUND: Ductal-dependent congenital heart diseases depends on the ductus arteriosus (DA) remaining open to maintain suitable pulmonary or systemic circulation after birth. An accurate diagnosis using prenatal echocardiography has important clinical significance in evaluating disease prognosis and ensuring timely treatment. METHODS: Fetuses were followed in the prenatal and postpartum periods via echocardiography. The results of postpartum echocardiography or autopsy specimens were compared with the prenatal echocardiography findings. RESULTS: One hundred and eight fetuses displayed various types of DDCHD including 66 fetuses with ductal-dependent pulmonary circulation, and 42 fetuses with ductal-dependent systemic circulation. Prenatal echocardiography revealed the typical characteristics of no forward flow signal from right ventricular outflow tract to the pulmonary trunk proximally and a reverse flow in the DA in most fetuses for ductal-dependent pulmonary circulation, a reverse flow in the transverse aortic arch for aorta atresia, and a loss of continuity between aortic arch and descending aorta for interruption of the aortic arch (IAA). All 108 fetuses displayed various types of complex CHD, including right ventricular dysplasia with pulmonary atresia (PA), severe Ebstein anomaly, double outlet right ventricle with PA, tetralogy of fallot with PA, single ventricle with PA or aorta atresia, hypoplastic left heart syndrome, and IAA. CONCLUSIONS: The identification of reverse flow in the aortic arch or DA aids in the subsequent accurate diagnosis of DDCHD associated with complex malformation of the heart.

Improving precision of glomerular filtration rate estimating model by ensemble learning.

BACKGROUND: Accurate assessment of kidney function is clinically important, but estimates of glomerular filtration rate (GFR) by regression are imprecise. METHODS: We hypothesized that ensemble learning could improve precision. A total of 1419 participants were enrolled, with 1002 in the development dataset and 417 in the external validation dataset. GFR was independently estimated from age, sex and serum creatinine using an artificial neural network (ANN), support vector machine (SVM), regression, and ensemble learning. GFR was measured by 99mTc-DTPA renal dynamic imaging calibrated with dual plasma sample 99mTc-DTPA GFR. RESULTS: Mean measured GFRs were 70.0 ml/min/1.73 m2 in the developmental and 53.4 ml/min/1.73 m2 in the external validation cohorts. In the external validation cohort, precision was better in the ensemble model of the ANN, SVM and regression equation (IQR = 13.5 ml/min/1.73 m2) than in the new regression model (IQR = 14.0 ml/min/1.73 m2, P < 0.001). The precision of ensemble learning was the best of the three models, but the models had similar bias and accuracy. The median difference ranged from 2.3 to 3.7 ml/min/1.73 m2, 30% accuracy ranged from 73.1 to 76.0%, and P was > 0.05 for all comparisons of the new regression equation and the other new models. CONCLUSIONS: An ensemble learning model including three variables, the average ANN, SVM, and regression equation values, was more precise than the new regression model. A more complex ensemble learning strategy may further improve GFR estimates.

A comparison of the performances of an artificial neural network and a regression model for GFR estimation.

BACKGROUND: Accurate estimation of glomerular filtration rate (GFR) is important in clinical practice. Current models derived from regression are limited by the imprecision of GFR estimates. We hypothesized that an artificial neural network (ANN) might improve the precision of GFR estimates. STUDY DESIGN: A study of diagnostic test accuracy. SETTING & PARTICIPANTS: 1,230 patients with chronic kidney disease were enrolled, including the development cohort (n=581), internal validation cohort (n=278), and external validation cohort (n=371). INDEX TESTS: Estimated GFR (eGFR) using a new ANN model and a new regression model using age, sex, and standardized serum creatinine level derived in the development and internal validation cohort, and the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) 2009 creatinine equation. REFERENCE TEST: Measured GFR (mGFR). OTHER MEASUREMENTS: GFR was measured using a diethylenetriaminepentaacetic acid renal dynamic imaging method. Serum creatinine was measured with an enzymatic method traceable to isotope-dilution mass spectrometry. RESULTS: In the external validation cohort, mean mGFR was 49±27 (SD) mL/min/1.73 m2 and biases (median difference between mGFR and eGFR) for the CKD-EPI, new regression, and new ANN models were 0.4, 1.5, and -0.5 mL/min/1.73 m2, respectively (P<0.001 and P=0.02 compared to CKD-EPI and P<0.001 comparing the new regression and ANN models). Precisions (IQRs for the difference) were 22.6, 14.9, and 15.6 mL/min/1.73 m2, respectively (P<0.001 for both compared to CKD-EPI and P<0.001 comparing the new ANN and new regression models). Accuracies (proportions of eGFRs not deviating >30% from mGFR) were 50.9%, 77.4%, and 78.7%, respectively (P<0.001 for both compared to CKD-EPI and P=0.5 comparing the new ANN and new regression models). LIMITATIONS: Different methods for measuring GFR were a source of systematic bias in comparisons of new models to CKD-EPI, and both the derivation and validation cohorts consisted of a group of patients who were referred to the same institution. CONCLUSIONS: An ANN model using 3 variables did not perform better than a new regression model. Whether ANN can improve GFR estimation using more variables requires further investigation.

Estimation of glomerular filtration rate by a radial basis function neural network in patients with type-2 diabetes mellitus.

BACKGROUND: Accurate and precise estimates of glomerular filtration rate (GFR) are essential for clinical assessments, and many methods of estimation are available. We developed a radial basis function (RBF) network and assessed the performance of this method in the estimation of the GFRs of 207 patients with type-2 diabetes and CKD. METHODS: Standard GFR (sGFR) was determined by (99m)Tc-DTPA renal dynamic imaging and GFR was also estimated by the 6-variable MDRD equation and the 4-variable MDRD equation. RESULTS: Bland-Altman analysis indicated that estimates from the RBF network were more precise than those from the other two methods for some groups of patients. However, the median difference of RBF network estimates from sGFR was greater than those from the other two estimates, indicating greater bias. For patients with stage I/II CKD, the median absolute difference of the RBF network estimate from sGFR was significantly lower, and the P50 of the RBF network estimate (n = 56, 87.5%) was significantly higher than that of the MDRD-4 estimate (n = 49, 76.6%) (p < 0.0167), indicating that the RBF network estimate provided greater accuracy for these patients. CONCLUSIONS: In patients with type-2 diabetes mellitus, estimation of GFR by our RBF network provided better precision and accuracy for some groups of patients than the estimation by the traditional MDRD equations. However, the RBF network estimates of GFR tended to have greater bias and higher than those indicated by sGFR determined by (99m)Tc-DTPA renal dynamic imaging.

Sononeoperfusion: a new therapeutic effect to enhance tumour blood perfusion using diagnostic ultrasound and microbubbles.

BACKGROUND: Hypoperfusion or resultant hypoxia in solid tumours is a main reason for therapeutic resistance. Augmenting the blood perfusion of hypovascular tumours might improve both hypoxia and drug delivery. Cavitation is known to result in microstreaming and sonoporation and to enhance drug diffusion into tumours. Here, we report the ability to enhance both tumour blood perfusion and doxorubicin (Dox) delivery using a new sononeoperfusion effect causing a cavitation effect on tumour perfusion in subcutaneous Walker-256 tumours of rats using ultrasound stimulated microbubble (USMB). METHODS: To induce the sononeoperfusion effect, USMB treatment was performed with a modified diagnostic ultrasound (DUS) system and SonoVue® microbubbles. The therapeutic pulse was operated with a peak negative pressure of 0.26 to 0.32 MPa and a pulse repetition frequency (PRF) of 50 Hz to 2 kHz. Contrast-enhanced ultrasound (CEUS) was used for tumour perfusion assessment. RESULTS: The USMB treatment of 0.26 MPa and 1 kHz could significantly enhance tumour perfusion with a 20.29% increase in the CEUS peak intensity and a 21.42% increment in the perfusion area for more than 4 hours (P < 0.05). The treatment also increased Dox delivery to tumours by approximately 3.12-fold more than that of the control (P < 0.05). Furthermore, ELISAs showed that vasodilators and inflammatory factors increased 4 hours after treatment (P < 0.05), suggesting that the inflammatory response plays an important role in the sononeoperfusion effect. CONCLUSION: The USMB-induced sononeoperfusion effect could significantly enhance the blood perfusion of Walker-256 tumours and promote drug delivery. It might be a novel physical method for overcoming the therapeutic resistance of hypoperfused or hypoxic tumours.

Mechanical destruction using a minimally invasive Ultrasound Needle induces anti-tumor immune responses and synergizes with the anti-PD-L1 blockade.

Immune checkpoint inhibitors (ICIs) have been widely used in treating various tumors; however, the objective response rate of ICIs is less than 40%. In this study, we attempted to induce anti-tumor immune responses using an improved ultrasonic horn device, Ultrasound Needle (UN). We tested its synergistic anti-tumor efficacy with an anti-PD-L1 antibody in a mouse tumor model. Under different parameters, UN treatment selectively induced mechanical destruction and thermal ablation effects on tumor tissues. The mechanical destruction effect of UN treatment increased the infiltration of CD8+ T cells in tumors and relieved the immunosuppressive tumor microenvironment. It also induced systemic anti-tumor immune responses and enhanced the therapeutic efficacy of the anti-PD-L1 antibody in both local and abscopal tumors. The mechanical destruction effect of UN treatment resulted in the release of damage-associated molecular patterns and promoted dendritic cells (DCs)-based antigen presentation. Depletion of DCs or CD8+ T cells eliminated the anti-tumor immune responses induced by UN treatment and weakened the synergistic anti-tumor efficacy with anti-PD-L1 antibody. Therefore, minimally invasive UN may provide a new therapeutic modality for ultrasound-assisted immunotherapy.

Alteration of the gut microbiota profile in children with autism spectrum disorder in China.

Background: Autism spectrum disorder (ASD) is associated with alterations in the gut microbiome. However, there are few studies on gut microbiota of children with ASD in China, and there is a lack of consensus on the changes of bacterial species. Purpose: Autism spectrum disorder (ASD) is associated with alterations in the gut microbiome. However, there are few studies on gut microbiota of children with ASD in China, and there is a lack of consensus on the changes of bacterial species. Methods: We used 16S rRNA sequencing to analyze ASD children (2 to 12 years), HC (2 to 12 years). Results: Our findings showed that the α-diversity, composition, and relative abundance of gut microbiota in the ASD group were significantly different from those in the HC groups. Compared with the HC group, the α-diversity in the ASD group was significantly decreased. At the genus level, the relative abundance of g_Faecalibacterium, g_Blautia, g_Eubacterium_eligens_group, g_Parasutterella, g_Lachnospiraceae_NK4A136_group and g_Veillonella in ASD group was significantly increased than that in HC groups, while the relative abundance of g_Prevotella 9 and g_Agathobacter was significantly decreased than that in HC groups. In addition, KEGG pathway analysis showed that the microbial functional abnormalities in ASD patients were mainly concentrated in metabolic pathways related to fatty acid, amino acid metabolism and aromatic compound metabolism, and were partially involved in neurotransmitter metabolism. Conclusion: This study revealed the characteristics of gut microbiota of Chinese children with ASD and provided further evidence of gut microbial dysbiosis in ASD.

A hybrid machine learning and regression method for cell type deconvolution of spatial barcoding-based transcriptomic data.

Spatial barcoding-based transcriptomic (ST) data require cell type deconvolution for cellular-level downstream analysis. Here we present SDePER, a hybrid machine learning and regression method, to deconvolve ST data using reference single-cell RNA sequencing (scRNA-seq) data. SDePER uses a machine learning approach to remove the systematic difference between ST and scRNA-seq data (platform effects) explicitly and efficiently to ensure the linear relationship between ST data and cell type-specific expression profile. It also considers sparsity of cell types per capture spot and across-spots spatial correlation in cell type compositions. Based on the estimated cell type proportions, SDePER imputes cell type compositions and gene expression at unmeasured locations in a tissue map with enhanced resolution. Applications to coarse-grained simulated data and four real datasets showed that SDePER achieved more accurate and robust results than existing methods, suggesting the importance of considering platform effects, sparsity and spatial correlation in cell type deconvolution.

High-throughput functional analysis of autism genes in zebrafish identifies convergence in dopaminergic and neuroimmune pathways.

Advancing from gene discovery in autism spectrum disorders (ASDs) to the identification of biologically relevant mechanisms remains a central challenge. Here, we perform parallel in vivo functional analysis of 10 ASD genes at the behavioral, structural, and circuit levels in zebrafish mutants, revealing both unique and overlapping effects of gene loss of function. Whole-brain mapping identifies the forebrain and cerebellum as the most significant contributors to brain size differences, while regions involved in sensory-motor control, particularly dopaminergic regions, are associated with altered baseline brain activity. Finally, we show a global increase in microglia resulting from ASD gene loss of function in select mutants, implicating neuroimmune dysfunction as a key pathway relevant to ASD biology.

US/MR Bimodal Imaging-Guided Bio-Targeting Synergistic Agent for Tumor Therapy.

Purpose: Breast cancer is detrimental to the health of women due to the difficulty of early diagnosis and unsatisfactory therapeutic efficacy of available breast cancer therapies. High intensity focused ultrasound (HIFU) ablation is a new method for the treatment of breast tumors, but there is a problem of low ablation efficiency. Therefore, the improvement of HIFU efficiency to combat breast cancer is immediately needed. This study aimed to describe a novel anaerobic bacteria-mediated nanoplatform, comprising synergistic HIFU therapy for breast cancer under guidance of ultrasound (US) and magnetic resonance (MR) bimodal imaging. Methods: The PFH@CL/Fe3O4 nanoparticles (NPs) (Perfluorohexane (PFH) and superparamagnetic iron oxides (SPIO, Fe3O4) with cationic lipid (CL) NPs) were synthesized using the thin membrane hydration method. The novel nanoplatform Bifidobacterium bifidum-mediated PFH@CL/Fe3O4 NPs were constructed by electrostatic adsorption. Thereafter, US and MR bimodal imaging ability of B. bifidum-mediated PFH@CL/Fe3O4 NPs was evaluated in vitro and in vivo. Finally, the efficacy of HIFU ablation based on B. bifidum-PFH@CL/Fe3O4 NPs was studied. Results: B. bifidum combined with PFH@CL/Fe3O4 NPs by electrostatic adsorption and enhanced the tumor targeting ability of PFH@CL/Fe3O4 NPs. US and MR bimodal imaging clearly displayed the distribution of the bio-targeting nanoplatform in vivo. It was conducive for accurate and effective guidance of HIFU synergistic treatment of tumors. Furthermore, PFH@CL/Fe3O4 NPs could form microbubbles by acoustic droplet evaporation and promote efficiency of HIFU ablation under guidance of bimodal imaging. Conclusion: A bio-targeting nanoplatform with high stability and good physicochemical properties was constructed. The HIFU synergistic agent achieved early precision imaging of tumors and promoted therapeutic effect, monitored by US and MR bimodal imaging during the treatment process.

Optimal treatment occasion for ultrasound stimulated microbubbles in promoting gemcitabine delivery to VX2 tumors.

Ultrasound stimulated microbubbles (USMB) is a widely used technology that can promote chemotherapeutic delivery to tumors yet the best treatment occasion for USMB is unknown or ignored. We aimed to determine the optimal treatment occasion for USMB treatment to enhance tumor chemotherapy to achieve the highest drug concentration in tumors. Experiments were conducted on VX2 tumors implanted in 60 rabbits. Gemcitabine (GEM) was intravenously infused as a chemotherapeutic agent and USMB was administered before, during or after chemotherapy. USMB was conducted with a modified diagnostic ultrasound at 3 MHz employing short bursts (5 cycles and 0.125% duty cycle) at 0.26 MPa in combination with a lipid microbubble. Subsequently, tumor blood perfusion quantitation, drug concentration detection, and fluorescence microscopy were performed. The results showed that the group that received USMB treatment immediately after GEM infusion had the highest drug concentration in tumors, which was 2.83 times that of the control group. Fifteen tumors were then treated repeatedly with the optimal USMB-plus-GEM combination, and along with the GEM and the control groups, were studied for tumor growth, tumor cell proliferation, apoptosis, and related cytokine contents. The combined treatment significantly inhibited tumor growth and promoted apoptosis. The levels of related cytokines, including HIF-1α, decreased after six combination therapies. These results suggest that the optimal treatment occasion for USMB occurs immediately after chemotherapy and tumor hypoxia improves after multiple combination therapies.