Hsa-microRNA-370-3p targeting Snail and Twist1 suppresses IL-8/STAT3-driven hepatocellular carcinoma metastasis.

The pro-inflammatory factor interleukin-8 (IL-8) is related to poor prognosis in hepatocellular carcinoma (HCC) patients. Interleukin-8 enhanced HCC invasion by upregulating Snail and Twist1, whether this modulation relies on microRNAs (miR) is unclear. In this study, hsa-miR-370-3p was screened as candidate miRNA targeting Snail and Twist1, and its expression was downregulated by IL-8. Luciferase assays and RNA electrophoretic mobility shift assays were used to evaluate the interaction between miR-370-3p and targeted mRNAs. Coimmunoprecipitation, luciferase, and ChIP assays were undertaken to investigate the mechanisms underlying IL-8-mediated modification of miR-370-3p. Gain- and loss-of-function studies, Transwell assays, and a xenograft nude mouse model were used to investigate pro- and antitumor activities. Interleukin-8 and miR-370-3p levels were analyzed for clinical relevance in HCC patients. Our results showed that HCC patients with high levels of IL-8 experienced more metastasis and shorter survival. Interleukin-8 induced epithelial-mesenchymal transition and promoted liver cancer cell migration, invasion, and metastasis both in vitro and in vivo. MicroRNA-370-3p interacted with its cognate mRNA within the 3'-UTR regions of Twist1 and Snail mRNA directly and specifically and attenuated IL-8 protumoral effects on liver cancer cells. Interleukin-8 negatively modulated miR-370-3p through signal transducer and activator of transcription 3 (STAT3) activation by recruiting histone deacetylase 1 (HDAC1) to miR-370-3p promoter. The STAT3 and HDAC antagonists inhibited liver cancer cell migration and invasion. Patients with high miR-370-3p and low IL-8 levels had longer overall survival. In conclusion, our study elucidated a novel axis IL-8/STAT3/miR-370-3p/Twist1 and Snail relying on HDAC1 recruitment, which showed both diagnostic and therapeutic potentials of miR-370-3p in HCC metastasis.

Integrated System for On-Site Rapid and Safe Screening of COVID-19.

Since the outbreak of coronavirus disease 2019 (COVID-19), the epidemic has been spreading around the world for more than 2 years. Rapid, safe, and on-site detection methods of COVID-19 are in urgent demand for the control of the epidemic. Here, we established an integrated system, which incorporates a machine-learning-based Fourier transform infrared spectroscopy technique for rapid COVID-19 screening and air-plasma-based disinfection modules to prevent potential secondary infections. A partial least-squares discrimination analysis and a convolutional neural network model were built using the collected infrared spectral dataset containing 857 training serum samples. Furthermore, the sensitivity, specificity, and prediction accuracy could all reach over 94% from the results of the field test regarding 968 blind testing samples. Additionally, the disinfection modules achieved an inactivation efficiency of 99.9% for surface and airborne tested bacteria. The proposed system is conducive and promising for point-of-care and on-site COVID-19 screening in the mass population.

Progression of Antiviral Agents Targeting Viral Polymerases.

Viral DNA and RNA polymerases are two kinds of very important enzymes that synthesize the genetic materials of the virus itself, and they have become extremely favorable targets for the development of antiviral drugs because of their relatively conserved characteristics. There are many similarities in the structure and function of different viral polymerases, so inhibitors designed for a certain viral polymerase have acted as effective universal inhibitors on other types of viruses. The present review describes the development of classical antiviral drugs targeting polymerases, summarizes a variety of viral polymerase inhibitors from the perspective of chemically synthesized drugs and natural product drugs, describes novel approaches, and proposes promising development strategies for antiviral drugs.

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR.

The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 µL) of the serum sample and a shorter detection time (several minutes). The distinct spectral differences and the separability between normal control and COVID-19 were investigated using multivariate and statistical analysis. Results showed that ATR-FT-IR coupled with partial least squares discriminant analysis was effective to differentiate COVID-19 from normal controls and some common respiratory viral infections or inflammation, with the area under the receiver operating characteristic curve (AUROC) of 0.9561 (95% CI: 0.9071-0.9774). Several serum constituents including, but not just, antibodies and serum phospholipids could be reflected on the infrared spectra, serving as "chemical fingerprints" and accounting for good model performances.

RNA-Seq based transcriptome analysis in oral lichen planus.

OBJECTIVES: Oral lichen planus (OLP) is a T cell-mediated autoimmune disease recognized as an oral potential malignant disorder (OPMD) with the precise mechanism unknown. This study focused on the transcriptional profiles of OLP to elucidate its potential pathogenesis. METHODS: We conducted RNA sequencing on matched 6 OLP tissues and 6 normal oral mucosal tissues. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and weighted gene co-expression network analysis (WGCNA) were performed on differentially expressed genes (DEGs). We utilized qRT-PCR to validated the top dysregulated genes and hub genes in another 10 pairs of specimens. RESULTS: A total of 153 DEGs (p-values< 0.05) were detected from RNA-Seq. According to GO and KEGG analysis, the dysregulated genes were mainly related to T cell related pathway and Wnt signaling. Based on the WGCNA analysis, 5 modules with high intramodular connectivity and hub genes in each module were gained. CONCLUSIONS: RNA-Seq and bioinformatic methods offered a valuable understanding of the biological pathways and key genes in the regulation of OLP. The identified DEGs and hub genes categorized into 2 groups including T cell regulation and inflammation and Wnt signaling pathway may serve as potential novel molecular targets for therapy.

IgG deposits in the mesangium and capillary loops predict poor renal outcome in patients with IgA nephropathy: a single-center retrospective study.

BACKGROUND: Glomerular IgG deposition in patients with IgA nephropathy (IgAN) has been shown to be associated with poor renal survival; however, most published studies to date are too small-scale and inconsistent to provide guidance for clinical practice. METHODS: Based on renal biopsy findings, 742 patients were divided into the following groups: (i) IgA deposition alone (IgA) vs IgA + IgG deposition (IgA + IgG) and (ii) IgG co-deposition confined to the mesangium vs mesangium + capillary loops (CLs). The clinicopathological variables at biopsy and renal outcome were assessed. RESULTS: Of the 742 patients, 182 had IgG co-deposition and 51 had IgG deposits in the mesangium + CLs. Patients with IgG co-deposition were associated with severe clinical and pathological lesions, especially those with a location of IgG deposits in the mesangium +CLs. Kaplan-Meier analysis revealed that a lower renal cumulative survival rate was present in both patients with IgG co-deposition and those with a location of IgG deposits in the mesangium + CLs (all p < 0.05). Moreover, patients with a higher intensity of glomerular IgG deposits or C3 deposits or C1q deposits were also associated with a lower survival rate. A multivariate Cox regression model identified the location of IgG deposits in the mesangium + CLs as an independent risk factor for poor prognosis (HR, 2.11; 95% CI: 1.06-4.18; p = 0.005). CONCLUSIONS: Glomerular IgG co-deposition and the location of glomerular IgG deposits in the mesangium + CLs were both associated with adverse renal outcomes, but only the location of glomerular IgG deposits in the CLs was an independent risk factor for poor prognosis in IgAN.

Predictive value of intratumour inflammatory cytokine mRNA levels of hepatocellular carcinoma patients and activation of two distinct pathways govern IL-8 induced epithelial-mesenchymal transition in human hepatic cancer cell lines.

Hepatocellular carcinoma (HCC) is always accompanied by persistent inflammation of liver tissues, which is considered to exert protumourigenic effects by promoting cancer growth, progression, and metastasis. However, the tumour-promoting roles and predictive value of intratumoural inflammatory cytokines remain unclear. In the present study, we used database analysis, clinical pathological studies, and in vitro biological experiments on human hepatic cancer cell lines to assess the prognostic potential of the primary tumour cytokine mRNA levels and underlying mechanisms in HCC. First, we assessed the prognostic value of several cytokines from the TCGA database and found that IL-8 is a unique cytokine that is associated with poor overall survival of HCC patients. Then, we collected 87 HCC tumour and adjacent non-tumour specimens from patients and confirmed that patients with low IL-8 expression exhibited less intrahepatic invasion or distant metastasis, a lower recurrence rate and longer overall survival time compared to patients with high IL-8 expression. Wound healing, transwell, and western blotting assay results showed that IL-8 promotes the migration and invasion of Huh-7 and HepG2 cells, and the underlying mechanism is that IL-8 induces the EMT of HCC cells via the IL-8/ERK1/2/SNAI1 and IL-8/STAT3/TWIST1 signalling pathways. These results provide valuable biological IL-8 information which needs to be further investigated in liver cancer target therapy research. Furthermore, the intratumoural cytokine expression at the mRNA level may provide insight into hepatocarcinoma prognosis.

BERT4FCA: A method for bipartite link prediction using formal concept analysis and BERT.

Link prediction in bipartite networks finds practical applications in various domains, including friend recommendation in social networks and chemical reaction prediction in metabolic networks. Recent studies have highlighted the potential for link prediction by maximal bi-cliques, which is a structural feature within bipartite networks that can be extracted using formal concept analysis (FCA). Although previous FCA-based methods for bipartite link prediction have achieved good performance, they still have the problem that they cannot fully capture the information of maximal bi-cliques. To solve this problem, we propose a novel method for link prediction in bipartite networks, utilizing a BERT-like transformer encoder network to enhance the contribution of FCA to link prediction. Our method facilitates bipartite link prediction by learning more information from the maximal bi-cliques and their order relations extracted by FCA. Experimental results on five real-world bipartite networks demonstrate that our method outperforms previous FCA-based methods, a state-of-the-art Graph Neural Network(GNN)-based method, and classic methods such as matrix-factorization and node2vec.

Review of Personalized Medicine and Pharmacogenomics of Anti-Cancer Compounds and Natural Products.

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborates the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation-aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarize chemical drugs, such as lorlatinib, osimertinib, and other natural products, that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Impact of refining on phytochemicals and anti-inflammatory activity of papaya (Carica papaya L.) seed oil in LPS-stimulated THP-1 cells.

This study investigated the changes in phytochemical composition and inflammatory response of crude papaya (Carica papaya L.) seed oil (CPO) and its refined forms (degummed, PDG; deacidified, PDA; decolorized, PDC; deodorized, PDO). Oils were analyzed for their phytochemical composition, oil quality parameters, antioxidant activity, and their inflammatory response in LPS-stimulated THP-1 macrophages. At higher refining degrees, particularly after deacidification, the contents of phytochemicals (sterols, tocopherols, and polyphenols) decreased while oxidation products increased. Both CPO (0.1-1.0 mg/mL) and PDG reduced the secretion and mRNA expression of LPS-stimulated inflammatory cytokines and mediators and also blocked the activation of the NF-κB pathway. PDA, PDC, and PDO showed low anti-inflammatory or even pro-inflammatory activity. Correlation analysis showed that 4 polyphenols and 2 phytosterols were responsible for the oil's anti-inflammatory effects. These findings indicated that moderate refining is suggested for papaya seed oil processing for retaining bioactive ingredients and anti-inflammatory ability.

Dual circuits originating from the ventral hippocampus independently facilitate affective empathy.

Affective empathy enables social mammals to learn and transfer emotion to conspecifics, but an understanding of the neural circuitry and genetics underlying affective empathy is still very limited. Here, using the naive observational fear between cagemates as a paradigm similar to human affective empathy and chemo/optogenetic neuroactivity manipulation in mouse brain, we investigate the roles of multiple brain regions in mouse affective empathy. Remarkably, two neural circuits originating from the ventral hippocampus, previously unknown to function in empathy, are revealed to regulate naive observational fear. One is from ventral hippocampal pyramidal neurons to lateral septum GABAergic neurons, and the other is from ventral hippocampus pyramidal neurons to nucleus accumbens dopamine-receptor-expressing neurons. Furthermore, we identify the naive observational-fear-encoding neurons in the ventral hippocampus. Our findings highlight the potentially diverse regulatory pathways of empathy in social animals, shedding light on the mechanisms underlying empathy circuity and its disorders.

STING agonist diABZI enhances the cytotoxicity of T cell towards cancer cells.

Antigen-specific T cell receptor-engineered T cell (TCR-T) based immunotherapy has proven to be an effective method to combat cancer. In recent years, cross-talk between the innate and adaptive immune systems may be requisite to optimize sustained antigen-specific immunity, and the stimulator of interferon genes (STING) is a promising therapeutic target for cancer immunotherapy. The level of expression or presentation of antigen in tumor cells affects the recognition and killing of tumor cells by TCR-T. This study aimed at investigating the potential of innate immune stimulation of T cells and engineered T cells to enhance immunotherapy for low-expression antigen cancer cells. We systematically investigated the function and mechanism of cross-talk between STING agonist diABZI and adaptive immune systems. We established NY-ESO-1 full knockout Mel526 cells for this research and found that diABZI activated STING media and TCR signaling pathways. In addition, the results of flow cytometry showed that antigens presentation from cancer cells induced by STING agonist diABZI also improved the affinity of TCR-T cells function against tumor cells in vitro and in vivo. Our findings revealed that diABZI enhanced the immunotherapy efficacy of TCR-T by activating STING media and TCR signaling pathways, improving interferon-γ expression, and increasing antigens presentation of tumor cells. This indicates that STING agonist could be used as a strategy to promote TCR-T cancer immunotherapy.

Quantitative and Qualitative Parameters of DCE-MRI Predict CDKN2A/B Homozygous Deletion in Gliomas.

RATIONALE AND OBJECTIVES: Homozygous deletion (HD) of CDKN2A/B holds important prognostic value in gliomas. This study aimed to explore the predictive potential of conventional MRI characteristics combined with dynamic contrast-enhanced MRI parameters in predicting CDKN2A/B HD status in gliomas. MATERIALS AND METHODS: Preoperative MRI data of 105 patients (69 without CDKN2A/B HD, and 36 with CDKN2A/B homozygous deletion) with gliomas were retrospectively collected. Conventional MRI features and dynamic contrast-enhanced-MRI qualitative parameter time-intensity curve type, quantitative parameters Ktrans, Kep, Ve, Vp, and iAUC were obtained. Logistic regression models for prediction of CDKN2A/B HD status were constructed in all types of gliomas and both subtypes of IDH-mutant and IDH-wild gliomas. RESULTS: Multivariate analysis for all patients demonstrated that age (OR=1.103, p = 0.002) and Ktrans (OR=1.051, p < 0.001) independently predicted CDKN2A/B HD. In IDH-mutant subgroup, multivariate analysis results indicated that Ktrans (OR=1.098, p = 0.031) emerged as autonomous predictors of CDKN2A/B HD. In IDH-wild subgroup, age (OR=1.111, p = 0.002) and Ktrans (OR=1.032, p = 0.001) were independent predictors of CDKN2A/B HD according to the multivariate analysis. The areas under the receiver operating characteristic curve of the corresponding models were 0.90, 0.95 and 0.84, respectively. CONCLUSION: Ktrans can serve as valuable predictive parameters for identifying CDKN2A/B HD status in all types of gliomas and both subtypes of IDH-mutant and IDH-wild gliomas. These findings provide a foundation for precise preoperative non-invasive diagnosis and personalized treatment approaches for glioma patients.

Hydrophobic core evolution of major histocompatibility complex class I chain-related protein A for dramatic enhancing binding affinity.

Interface residues at sites of protein-protein interaction (PPI) are the focus for affinity optimisation. However, protein hydrophobic cores (HCs) play critical roles and shape the protein surface. We hypothesise that manipulating protein HCs can enhance PPI interaction affinities. A cell stress molecule, major histocompatibility complex class I chain-related protein A (MICA), binds to the natural killer group 2D (NKG2D) homodimer to form three molecule interactions. MICA was used as a study subject to support our hypothesis. We redesigned MICA HCs by directed mutagenesis and isolated high-affinity variants through a newly designed partial-denature panning (PDP) method. A few mutations in MICA HCs increased the NKG2D-MICA interaction affinity by 325-5613-fold. Crystal structures of the NKG2D-MICA variant complexes indicated that mutagenesis of MICA HCs stabilised helical elements for decreasing intermolecular interactive free energy (ΔG) of the NKG2D-MICA heterotrimer. The repacking of MICA HC mutants maintained overall surface residues and the authentic binding specificity of MICA. In conclusion, this study provides a new method for MICA redesign and affinity optimisation through HC manipulation without mutating PPI interface residues. Our study introduces a novel approach to protein manipulation, potentially expanding the toolkit for protein affinity optimisation.

Telitacicept Treatment Refractory Lupus Nephritis: A Case Report.

Introduction: Refractory lupus nephritis (LN) causes kidney disease progression and increases the risk of loss of renal function. Due to the high specificity and few side effects of biological agents, they are recommended for the treatment of systemic lupus erythematosus. There are few data on telitacicept for the treatment of refractory LN. Case Presentation: Here, we report the efficacy and safety of telitacicept in the treatment of refractory LN in a 25-year-old female patient. This patient with refractory lupus developed Pneumocystis jirovecii pneumonia while using multitargeted therapy, and the patient's urine protein was rapidly relieved after telitacicept combination with low-dose mycophenolate mofetil (MMF). Conclusion: This result suggests that telitacicept has a positive effect on refractory LN with no significant side effects. Further reports and a registry are necessary to confirm that telitacicept with low-dose MMF should be preferred in refractory LN.

Link prediction on bipartite networks using matrix factorization with negative sample selection.

We propose a new method for bipartite link prediction using matrix factorization with negative sample selection. Bipartite link prediction is a problem that aims to predict the missing links or relations in a bipartite network. One of the most popular solutions to the problem is via matrix factorization (MF), which performs well but requires reliable information on both absent and present network links as training samples. This, however, is sometimes unavailable since there is no ground truth for absent links. To solve the problem, we propose a technique called negative sample selection, which selects reliable negative training samples using formal concept analysis (FCA) of a given bipartite network in advance of the preceding MF process. We conduct experiments on two hypothetical application scenarios to prove that our joint method outperforms the raw MF-based link prediction method as well as all other previously-proposed unsupervised link prediction methods.

Identification of novel targets and pathways to distinguish suicide dependent or independent on depression diagnosis.

In recent years, postmortem brain studies have revealed that some molecular, cellular, and circuit changes associated with suicide, have an independent or additive effect on depression. The aim of the present study is to identify potential phenotypic, tissue, and sex-specific novel targets and pathways to distinguish depression or suicide from major depressive disorder (MDD) comorbid with suicide. The mRNA expression profiling datasets from two previous independent postmortem brain studies of suicide and depression (GSE102556 and GSE101521) were retrieved from the GEO database. Machine learning analysis was used to differentiate three regrouped gene expression profiles, i.e., MDD with suicide, MDD without suicide, and suicide without depression. Weighted correlation network analysis (WGCNA) was further conducted to identify the key modules and hub genes significantly associated with each of these three sub-phenotypes. TissueEnrich approaches were used to find the essential brain tissues and the difference of tissue enriched genes between depression with or without suicide. Dysregulated gene expression cross two variables, including phenotypes and tissues, were determined by global analysis with Vegan. RRHO analysis was applied to examine the difference in global expression pattern between male and female groups. Using the optimized machine learning model, several ncRNAs and mRNAs with higher AUC and MeanDecreaseGini, including GCNT1P1 and AC092745.1, etc., were identified as potential molecular targets to distinguish suicide with, or without MDD and depression without suicide. WGCNA analysis identified some key modules significantly associated with these three phenotypes, and the gene biological functions of the key modules mainly relate to ncRNA and miRNA processing, as well as oxidoreductase and dehydrogenase activity. Hub genes such as RP11-349A22.5, C20orf196, MAPK8IP3 and RP11-697N18.2 were found in these key modules. TissueEnrich analysis showed that nucleus accumbens and subiculum were significantly changed among the 6 brain regions studied. Global analysis with Vegan and RRHO identified PRS26, ARNT and SYN3 as the most significantly differentially expressed genes across phenotype and tissues, and there was little overlap between the male and female groups. In this study, we have identified novel gene targets, as well as annotated functions of co-expression patterns and hub genes that are significantly distinctive between depression with suicide, depression without suicide, and suicide without depression. Moreover, global analysis across three phenotypes and tissues confirmed the evidence of sex difference in mood disorders.

A new AAV tool for highly preferentially targeting hippocampal CA2.

Mice hippocampus contains three prominent subregions, CA1, CA3 and DG and is well regarded as an essential multiple task processor for learning, memory and cognition based on tremendous studies on these three subregions. The narrow region sandwiched between CA1 and CA3 called CA2 has been neglected for a long time. But it raises great attentions recently since this region manifests the indispensable role in social memory. Its unique physical position connecting CA1 and CA3 suggests the potential novel functions besides social memory regulation. But the CA2 is too small to be accurately targeted. A flexible AAV tool capable of accurately and efficiently targeting this region is highly demanded. To fill this gap, we generate an AAV expressing Cre driven by the mini Map3k15 promoter, AAV/M1-Cre, which can be easily utilized to help tracing and manipulating CA2 pyramidal neurons. However, M1-Cre labeled a small percentage of M1+RGS14- neurons that do not colocalize with any RGS14+/STEP+/PEP4+/Amigo2+ pyramidal neurons. They are proved to be the mixture of normal CA2 pyramidal neurons, CA3-like neurons in CA2-CA3 mixed border, some CA2 interneurons and rarely few CA1-like neurons, which are probably the ones projecting to the revealed CA2 downstream targets, VMH, STHY and PMV in WT mice injecting this AAV/M1-Cre virus but not in Amigo2-Cre mice. Though it is still challenging to get a pure CA2 tracking and manipulation system, this tool provides a new, more flexible and extended strategy for in-depth CA2 functional study in the future.

AAV11 enables efficient retrograde targeting of projection neurons and enhances astrocyte-directed transduction.

Viral tracers that enable efficient retrograde labeling of projection neurons are powerful vehicles for structural and functional dissections of the neural circuit and for the treatment of brain diseases. Currently, some recombinant adeno-associated viruses (rAAVs) based on capsid engineering are widely used for retrograde tracing, but display undesirable brain area selectivity due to inefficient retrograde transduction in certain neural connections. Here we developed an easily editable toolkit to produce high titer AAV11 and demonstrated that it exhibits potent and stringent retrograde labeling of projection neurons in adult male wild-type or Cre transgenic mice. AAV11 can function as a powerful retrograde viral tracer complementary to AAV2-retro in multiple neural connections. In combination with fiber photometry, AAV11 can be used to monitor neuronal activities in the functional network by retrograde delivering calcium-sensitive indicator under the control of a neuron-specific promoter or the Cre-lox system. Furthermore, we showed that GfaABC1D promoter embedding AAV11 is superior to AAV8 and AAV5 in astrocytic tropism in vivo, combined with bidirectional multi-vector axoastrocytic labeling, AAV11 can be used to study neuron-astrocyte connection. Finally, we showed that AAV11 allows for analyzing circuit connectivity difference in the brains of the Alzheimer's disease and control mice. These properties make AAV11 a promising tool for mapping and manipulating neural circuits and for gene therapy of some neurological and neurodegenerative disorders.

Validation of metagenomic next-generation sequencing of bronchoalveolar lavage fluid for diagnosis of suspected pulmonary infections in patients with systemic autoimmune rheumatic diseases receiving immunosuppressant therapy.

Background: The accuracy and sensitivity of conventional microbiological tests (CMTs) are insufficient to identify opportunistic pathogens in patients with systemic autoimmune rheumatic diseases (SARDs). The study aimed to assess the usefulness of metagenomic next-generation sequencing (mNGS) vs. CMTs for the diagnosis of pulmonary infections in patients with SARDs receiving immunosuppressant therapy. Methods: The medical records of 40 patients with pulmonary infections and SARDs treated with immunosuppressants or corticosteroids were reviewed retrospectively. Bronchoalveolar lavage fluid (BALF) samples were collected from all patients and examined by mNGS and CMTs. Diagnostic values of the CMTs and mNGS were compared with the clinical composite diagnosis as the reference standard. Results: Of the 40 patients included for analysis, 37 (92.5%) were diagnosed with pulmonary infections and 3 (7.5%) with non-infectious diseases, of which two were considered primary diseases and one an asthma attack. In total, 15 pathogens (7 bacteria, 5 fungi, and 3 viruses) were detected by CMTs as compared to 58 (36 bacteria, 12 fungi, and 10 viruses) by mNGS. Diagnostic accuracy of mNGS was superior to that of the CMTs for the detection of co-infections with bacteria and fungi (95 vs. 53%, respectively, p < 0.01), and for the detection of single infections with fungi (97.5 vs. 55%, respectively, p < 0.01). Of the 31 patients diagnosed with co-infections, 4 (12.9%) were positive for two pathogens and 27 (87.1%) for three or more. The detection rate of co-infection was significantly higher for mNGS than CMTs (95 vs. 16%, respectively, p < 0.01). Conclusion: The accuracy of mNGS was superior to that of the CMTs for the diagnosis of pulmonary infections in patients with SARDs treated with immunosuppressants. The rapid diagnosis by mNGS can ensure timely adjustment of treatment regimens to improve diagnosis and outcomes.