Recent advancement of sonogenetics: A promising noninvasive cellular manipulation by ultrasound.

Recent advancements in biomedical research have underscored the importance of noninvasive cellular manipulation techniques. Sonogenetics, a method that uses genetic engineering to produce ultrasound-sensitive proteins in target cells, is gaining prominence along with optogenetics, electrogenetics, and magnetogenetics. Upon stimulation with ultrasound, these proteins trigger a cascade of cellular activities and functions. Unlike traditional ultrasound modalities, sonogenetics offers enhanced spatial selectivity, improving precision and safety in disease treatment. This technology broadens the scope of non-surgical interventions across a wide range of clinical research and therapeutic applications, including neuromodulation, oncologic treatments, stem cell therapy, and beyond. Although current literature predominantly emphasizes ultrasonic neuromodulation, this review offers a comprehensive exploration of sonogenetics. We discuss ultrasound properties, the specific ultrasound-sensitive proteins employed in sonogenetics, and the technique's potential in managing conditions such as neurological disorders, cancer, and ophthalmic diseases, and in stem cell therapies. Our objective is to stimulate fresh perspectives for further research in this promising field.

Progress of SGLT2 inhibitors in the treatment of common immune-related nephropathies.

The immune system can lead to a variety of renal diseases through direct or indirect mechanisms. In immune-mediated nephropathy, though standardized treatment, there are still a small number of patients with further decline in renal function, which may even progress to renal failure; sodium-glucose cotransporter protein 2 (SLC5A2,SGLT2) inhibitors not only can significantly reduce blood glucose, but also have an additional protective effect on the kidneys and the heart; this review concludes the potential mechanism of the renal protective effect of SGLT2i and the new advances in the recent years in common immune-mediated nephropathies, which can provide new theoretical references to optimize the therapeutic strategy of common immune-mediated nephropathies.

Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering.

Mutations in amino acid sequences can provoke changes in protein function. Accurate and unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but remains a fundamental challenge. To resolve this challenge, here we present Protein Mutational Effect Predictor (ProMEP), a general and multiple sequence alignment-free method that enables zero-shot prediction of mutation effects. A multimodal deep representation learning model embedded in ProMEP was developed to comprehensively learn both sequence and structure contexts from ~160 million proteins. ProMEP achieves state-of-the-art performance in mutational effect prediction and accomplishes a tremendous improvement in speed, enabling efficient and intelligent protein engineering. Specifically, ProMEP accurately forecasts mutational consequences on the gene-editing enzymes TnpB and TadA, and successfully guides the development of high-performance gene-editing tools with their engineered variants. The gene-editing efficiency of a 5-site mutant of TnpB reaches up to 74.04% (vs 24.66% for the wild type); and the base editing tool developed on the basis of a TadA 15-site mutant (in addition to the A106V/D108N double mutation that renders deoxyadenosine deaminase activity to TadA) exhibits an A-to-G conversion frequency of up to 77.27% (vs 69.80% for ABE8e, a previous TadA-based adenine base editor) with significantly reduced bystander and off-target effects compared to ABE8e. ProMEP not only showcases superior performance in predicting mutational effects on proteins but also demonstrates a great capability to guide protein engineering. Therefore, ProMEP enables efficient exploration of the gigantic protein space and facilitates practical design of proteins, thereby advancing studies in biomedicine and synthetic biology.

Antibacterial effect of the metal nanocomposite on Escherichia coli.

Ag nanocomposites (NAs) have been found to induce irreversible harm to pathogenic bacteria, however, NAs tend to aggregate easily when used alone. These nanocomposites also show increased toxicity and their underlying antibacterial mechanism is still unknown. In short, practical applications of NA materials face the following obstacles: elucidating the mechanism of antibacterial action, reducing cytotoxicity to body cells, and enhancing antibacterial activity. This study synthesized a core-shell structured ZnFe2O4 @Cu-ZIF-8 @Ag (FUA) nanocomposite with high antibacterial activity and low cytotoxicity. The nanocomposites achieved a 99.99 % antibacterial rate against Escherichia coli (E. coli) and tetracycline-resistant E. coli (T - E. coli), in under 20 min at 100 µg/mL. The nanocomposites were able to inactivate E. coli due to the gradual release of Cu2+, Zn2+, and Ag+ ions, which synergistically form •OH from FUA in an aerobic environment. The presence of •OH has significant effects on the antibacterial activity. The released metal ions combine with •OH to cause damage to the bacterial cell wall, resulting in the leakage of electrolytes and ions. Moreover, in comparison to NA, the toxicity of FUA is considerably reduced. This study is expected to inspire the development of other silver-based nanocomposite materials for the inactivation of drug-resistant bacteria.

Baló's concentric sclerosis with spontaneous remission and favorable prognosis.

Introduction: Baló's concentric sclerosis (BCS) is a rare type of central nervous system demyelinating disorder. Most patients with BCS are treated with corticosteroids, and spontaneous remission has seldom been described. Case presentation: A 46-year-old man presented with a subacute-onset headache and memory loss. Brain magnetic resonance imaging (MRI) revealed multiple onion-shaped ring lesions with mild enhancement in the outermost ring. A brain biopsy revealed significant myelin loss. The diagnosis of BCS was established based on the MRI results and pathological findings. Interestingly, the patient recovered almost completely without immunotherapy, with repeated brain MRI at the 1-year follow-up showing an obvious reduction in the extent of the lesions. Conclusion: Neurologists should improve the recognition of the typical MRI features of BCS to avoid unnecessary biopsies. Although rare, spontaneous remission can be observed in clinical practice.

Fabrication of cysteine-modified antibodies with Fc-specific conjugation for covalent and oriented immobilization of native antibodies.

Covalent and oriented immobilization of antibodies (Abs) can substantially improve the sensitivity and stability of solid-phase immunoassays. By modifying the natural Abs with functional groups that provide unique handles for further conjugation, Abs could be immobilized onto the solid matrices with uniform orientation. Herein, an effective approach for Fc-specific modification of Abs was developed for the oriented and covalent immobilization of Abs. Twelve photoreactive Z-domain variants, incorporated with a photoactivable probe (p-benzoyl-L-phenylalanine, Bpa) at different positions and carrying a C-terminal Cys-tag (i.e. ZBpa-Cys variants), were individually constructed and produced in Escherichia coli and tested for photo-cross-linking to various IgGs. The different ZBpa-Cys variants demonstrated large differences in photo-conjugation efficiency for the tested IgGs. The conjugation efficiencies of 17thZBpa-Cys ranged from 90 % to nearly 100 % for rabbit IgG and mouse IgG2a, IgG2b and IgG3. Other variants, including 5thZBpa-Cys, 18thZBpa-Cys, 32thZBpa-Cys, and 35thZBpa-Cys, also displayed conjugation efficiencies of 61 %-83 % for mouse IgG1, IgG2a and IgG3. Subsequently, the photo-modified Abs, namely IgG-Cys conjugates, were covalently immobilized onto a maleimide group-functionalized solid-phase carrier on the basis of the reaction of sulfhydryl and maleimide. Thus, a generic platform for the controlled and oriented immobilization of Abs was developed, and the efficacy and potential of the proposed approach for sensitive immunoassays was demonstrated by detecting human α-fetoprotein.

nCas9 Engineering for Improved Target Interaction Presents an Effective Strategy to Enhance Base Editing.

Base editors (BEs) are a recent generation of genome editing tools that couple a cytidine or adenosine deaminase activity to a catalytically impaired Cas9 moiety (nCas9) to enable specific base conversions at the targeted genomic loci. Given their strong application potential, BEs are under active developments toward greater levels of efficiency and safety. Here, a previously overlooked nCas9-centric strategy is explored for enhancement of BE. Based on a cytosine BE (CBE), 20 point mutations associated with nCas9-target interaction are tested. Subsequently, from the initial positive X-to-arginine hits, combinatorial modifications are applied to establish further enhanced CBE variants (1.1-1.3). Parallel nCas9 modifications in other versions of CBEs including A3A-Y130F-BE4max, YEE-BE4max, CGBE, and split-AncBE4max, as well as in the context of two adenine BEs (ABE), likewise enhance their respective activities. The same strategy also substantially improves the efficiencies of high-fidelity nCas9/BEs. Further evidence confirms that the stabilization of nCas9-substrate interactions underlies the enhanced BE activities. In support of their translational potential, the engineered CBE and ABE variants respectively enable 82% and 25% higher rates of editing than the controls in primary human T-cells. This study thus demonstrates a highly adaptable strategy for enhancing BE, and for optimizing other forms of Cas9-derived tools.

A landscape of methodology and implementation of adaptive designs in cancer clinical trials.

BACKGROUND: The use of adaptive designs in cancer trials has considerably increased worldwide in recent years, along with the release of various guidelines for their application. This systematic review aims to comprehensively summarize the key methodological and executive features of adaptive designs in cancer clinical trials. METHODS: A comprehensive search from PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials was conducted to screen eligible clinical trials that employed adaptive designs and were conducted in cancer patients. The methodological and executive characteristics of adaptive designs were the main measurements extracted. Descriptive analyses, primarily consisting of frequency and percentage, were employed to analyzed and reported the data. RESULTS: A total of 180 cancer clinical trials with adaptive designs were identified. The first three most common type of adaptive design was the group sequential design (n=114, 63.3 %), adaptive dose-finding design (n=22, 12.2 %), and adaptive platform design (n=16, 8.9 %). The results showed that 4.4 % (n=8) of trials conducted post hoc modifications, and around 29.4 % (n=53) did not provide the methods for controlling type I errors. Among phase II or above trials, 79.9 % (112/140) applied the surrogate endpoint as the primary outcome in these trials. Importantly, 27.2 % (49/180) of trials did not report clear information on the independent data monitoring committee (iDMC), and 13.3 % (n=24) without clear information on interim analyses. Interim analyses suggested 34.4 % (62/180) of trials being stopped for futility, 10.6 % (n=19) for efficacy, and 2.2 % (n=4) for safety concerns in the early stage. CONCLUSIONS: This study emphasizes adaptive designs in cancer trials face significant challenges in their design or strict implementation according to protocol, which might significantly compromise the validity and integrity of trials. It is thus important for researchers, sponsors, and policymakers to actively oversee and guide their application.

Cross-Modal Object Tracking via Modality-Aware Fusion Network and a Large-Scale Dataset.

Visual object tracking often faces challenges such as invalid targets and decreased performance in low-light conditions when relying solely on RGB image sequences. While incorporating additional modalities like depth and infrared data has proven effective, existing multimodal imaging platforms are complex and lack real-world applicability. In contrast, near-infrared (NIR) imaging, commonly used in surveillance cameras, can switch between RGB and NIR based on light intensity. However, tracking objects across these heterogeneous modalities poses significant challenges, particularly due to the absence of modality switch signals during tracking. To address these challenges, we propose an adaptive cross-modal object tracking algorithm called modality-aware fusion network (MAFNet). MAFNet efficiently integrates information from both RGB and NIR modalities using an adaptive weighting mechanism, effectively bridging the appearance gap and enabling a modality-aware target representation. It consists of two key components: an adaptive weighting module and a modality-specific representation module. The adaptive weighting module predicts fusion weights to dynamically adjust the contribution of each modality, while the modality-specific representation module captures discriminative features specific to RGB and NIR modalities. MAFNet offers great flexibility as it can effortlessly integrate into diverse tracking frameworks. With its simplicity, effectiveness, and efficiency, MAFNet outperforms state-of-the-art methods in cross-modal object tracking. To validate the effectiveness of our algorithm and overcome the scarcity of data in this field, we introduce CMOTB, a comprehensive and extensive benchmark dataset for cross-modal object tracking. CMOTB consists of 61 categories and 1000 video sequences, comprising a total of over 799K frames. We believe that our proposed method and dataset offer a strong foundation for advancing cross-modal object-tracking research. The dataset, toolkit, experimental data, and source code will be publicly available at: https://github.com/mmic-lcl/ Datasets-and-benchmark-code.

NEATmap: a high-efficiency deep learning approach for whole mouse brain neuronal activity trace mapping.

Quantitative analysis of activated neurons in mouse brains by a specific stimulation is usually a primary step to locate the responsive neurons throughout the brain. However, it is challenging to comprehensively and consistently analyze the neuronal activity trace in whole brains of a large cohort of mice from many terabytes of volumetric imaging data. Here, we introduce NEATmap, a deep learning-based high-efficiency, high-precision and user-friendly software for whole-brain neuronal activity trace mapping by automated segmentation and quantitative analysis of immunofluorescence labeled c-Fos+ neurons. We applied NEATmap to study the brain-wide differentiated neuronal activation in response to physical and psychological stressors in cohorts of mice.

Optimizing multicopy chromosomal integration for stable high-performing strains.

The copy number of genes in chromosomes can be modified by chromosomal integration to construct efficient microbial cell factories but the resulting genetic systems are prone to failure or instability from triggering homologous recombination in repetitive DNA sequences. Finding the optimal copy number of each gene in a pathway is also time and labor intensive. To overcome these challenges, we applied a multiple nonrepetitive coding sequence calculator that generates sets of coding DNA sequence (CDS) variants. A machine learning method was developed to calculate the optimal copy number combination of genes in a pathway. We obtained an engineered Yarrowia lipolytica strain for eicosapentaenoic acid biosynthesis in 6 months, producing the highest titer of 27.5 g l-1 in a 50-liter bioreactor. Moreover, the lycopene production in Escherichia coli was also greatly improved. Importantly, all engineered strains of Y. lipolytica, E. coli and Saccharomyces cerevisiae constructed with nonrepetitive CDSs maintained genetic stability.

Freeprotmap: waiting-free prediction method for protein distance map.

BACKGROUND: Protein residue-residue distance maps are used for remote homology detection, protein information estimation, and protein structure research. However, existing prediction approaches are time-consuming, and hundreds of millions of proteins are discovered each year, necessitating the development of a rapid and reliable prediction method for protein residue-residue distances. Moreover, because many proteins lack known homologous sequences, a waiting-free and alignment-free deep learning method is needed. RESULT: In this study, we propose a learning framework named FreeProtMap. In terms of protein representation processing, the proposed group pooling in FreeProtMap effectively mitigates issues arising from high-dimensional sparseness in protein representation. In terms of model structure, we have made several careful designs. Firstly, it is designed based on the locality of protein structures and triangular inequality distance constraints to improve prediction accuracy. Secondly, inference speed is improved by using additive attention and lightweight design. Besides, the generalization ability is improved by using bottlenecks and a neural network block named local microformer. As a result, FreeProtMap can predict protein residue-residue distances in tens of milliseconds and has higher precision than the best structure prediction method. CONCLUSION: Several groups of comparative experiments and ablation experiments verify the effectiveness of the designs. The results demonstrate that FreeProtMap significantly outperforms other state-of-the-art methods in accurate protein residue-residue distance prediction, which is beneficial for lots of protein research works. It is worth mentioning that we could scan all proteins discovered each year based on FreeProtMap to find structurally similar proteins in a short time because the fact that the structure similarity calculation method based on distance maps is much less time-consuming than algorithms based on 3D structures.

An automated method for assessing condyle head changes in patients with skeletal class II malocclusion based on Cone-beam CT images.

OBJECTIVES: Currently, there is no reliable automated measurement method to study the changes in the condylar process after orthognathic surgery. Therefore, this study proposes an automated method to measure condylar changes in patients with skeletal class II malocclusion following surgical-orthodontic treatment. METHODS: Cone-beam CT (CBCT) scans from 48 patients were segmented using the nnU-Net network for automated maxillary and mandibular delineation. Regions unaffected by orthognathic surgery were selectively cropped. Automated registration yielded condylar displacement and volume calculations, each repeated three times for precision. Logistic regression and linear regression were used to analyse the correlation between condylar position changes at different time points. RESULTS: The Dice score for the automated segmentation of the condyle was 0.971. The intraclass correlation coefficients (ICCs) for all repeated measurements ranged from 0.93 to 1.00. The results of the automated measurement showed that 83.33% of patients exhibited condylar resorption occurring six months or more after surgery. Logistic regression and linear regression indicated a positive correlation between counterclockwise rotation in the pitch plane and condylar resorption (P < .01). And a positive correlation between the rotational angles in both three planes and changes in the condylar volume at six months after surgery (P ≤ .04). CONCLUSIONS: This study's automated method for measuring condylar changes shows excellent repeatability. Skeletal class II malocclusion patients may experience condylar resorption after bimaxillary orthognathic surgery, and this is correlated with counterclockwise rotation in the sagittal plane. ADVANCES IN KNOWLEDGE: This study proposes an innovative multi-step registration method based on CBCT, and establishes an automated approach for quantitatively measuring condyle changes post-orthognathic surgery. This method opens up new possibilities for studying condylar morphology.

Anomalous Structural Transformation of Cu(I) Clusters into Multifunctional CuAg Nanoclusters.

We report an anomalous structural transformation of a Cu(I) cluster into two different types of copper-silver (CuAg) alloy nanoclusters. Different from previous reports, we demonstrate that under specifically designed reaction conditions, the Ag-doping could induce a substantial growth of the starting Cu15 and a Ag13Cu20 nanocluster was obtained via the unexpected insertion of an Ag13 kernel inside the Cu(I)-S shell. Ag13Cu20 demonstrates high activity to initiate the photopolymerization of previously hard-to-print inorganic polymers in 3D laser microprinting. Interestingly, a slight modification of the reaction condition leads to the formation of another Ag18-xCuxS (8≤x) nanocluster templated by a central S2- anion, which possesses a unique electronic structure compared to conventional template-free CuAg nanoclusters. Overall, this work unveils the intriguing doping chemistry of Cu clusters, as well as their capability to create different types of alloy nanoclusters with previously unobtainable structures and multifunctionality.

Genetic characterization of plasmid-borne blaOXA-58 and blaOXA-72 in Acinetobacter pittii in Shaanxi, China.

OBJECTIVES: Acinetobacter pittii has emerged as an opportunistic nosocomial pathogen associated with hospital-acquired infections. The purpose of this study was to investigate the genetic structures of plasmids carrying carbapenemase genes blaOXA-58 and blaOXA-72 in A. pittii strains AR3676 and AR3651 isolated from patients. METHODS: Antimicrobial susceptibility testing was performed using broth microdilution. Whole-genome sequencing and bioinformatics analysis were performed to characterize the genome of A. pittii AR3676 and AR3651. Conjugation experiments were conducted to evaluate plasmid transferability. Phylogenetic and comparative genomic analysis were performed to explore the characteristics of carbapenem-resistant A. pittii isolates worldwide. RESULTS: The AR3676 strain showed resistance to imipenem. The 19 700-bp plasmid pAR3676-OXA-58 harboured blaOXA-58 with genetic contexts consisting of a truncated ISAba3-like-blaOXA58-ISAba3. Additionally, the AR3651 strain showed resistance to imipenem and meropenem. The AR3651 genome comprised one 9,837-bp RepA_AB plasmid pAR3651-OXA-72 harbouring blaOXA-72. This blaOXA-72 was flanked by XerC/XerD recombination sites. The conjugation of plasmids pAR3676-OXA-58 and pAR3651-OXA-72 from A. pittii to Acinetobacter baumannii ATCC 17978RIFR failed three independent times. Phylogenetic analysis of A. pittii strains AR3676, AR3651, and a further 504 A. pittii strains collected between 1966 and 2022 from various geographic localities revealed genetic diversity with a heterogeneous distribution of carbapenemase genes. CONCLUSIONS: A. pittii strains with a plasmid carrying blaOXA-58 or blaOXA-72 may serve as an important reservoir of carbapenemase genes. Carbapenemase genes on a single plasmid may facilitate their dissemination and persistence. Additionally, pdif sites and mobile elements play an important role in the mobilization of resistance genes and plasmid evolution.

Streptomyces albipurpureus sp. nov., a novel actinobacterium with antimicrobial activity isolated from the rhizospheric soil of Fritillaria cirrhosa D. Don.

A novel actinobacterium, designated strain CWNU-1T, was isolated from the rhizospheric soil of Fritillaria cirrhosa D. Don and examined using a polyphasic taxonomic approach. The organism developed pale blue aerial mycelia that was simply branched and terminated in open or closed coils of three or more volutions on International Streptomyces Project 3 agar. Spores were ellipsoidal to cylindrical with wrinkled surfaces. The strain showed high 16S rRNA gene sequence similarity to Streptomyces kurssanovii NBRC 13192T (98.8 %), Streptomyces xantholiticus NBRC 13354T (98.7 %) and Streptomyces peucetius JCM 9920T (98.6 %). The phylogenetic result based on 16S rRNA gene and genome sequences clearly demonstrated that strain CWNU-1T formed an independent phylogenetic lineage. On the basis of orthologous average nucleotide identity, CWNU-1T was most closely related to Streptomyces inusitatus NBRC 13601T with 79.3 % identity. The results of the digital DNA-DNA hybridization analysis also indicated low levels of relatedness with other species, as the highest value was observed with S. inusitatus NBRC 13601T (25.3 %). With reference to phenotypic characteristics, phylogenetic data, orthologous average nucleotide identity and digital DNA-DNA hybridization results, strain CWNU-1T was readily distinguished from its most closely related strains and classified as representing a novel species, for which the name Streptomyces albipurpureus sp. nov. is proposed. The type strain is CWNU-1T (=CGMCC 4.7758T=MCCC 1K07402T=JCM 35391T).

Specific convulsions and brain damage in children hospitalized for Omicron BA.5 infection: an observational study using two cohorts.

BACKGROUND: SARS-CoV-2 continues to mutate over time, and reports on children infected with Omicron BA.5 are limited. We aimed to analyze the specific symptoms of Omicron-infected children and to improve patient care. METHODS: We selected 315 consecutively hospitalized children with Omicron BA.5 and 16,744 non-Omicron-infected febrile children visiting the fever clinic at our hospital between December 8 and 30, 2022. Specific convulsions and body temperatures were compared between the two cohorts. We analyzed potential associations between convulsions and vaccination, and additionally evaluated the brain damage among severe Omicron-infected children. RESULTS: Convulsion rates (97.5% vs. 4.3%, P < 0.001) and frequencies (median: 2.0 vs. 1.6, P < 0.001) significantly differed between Omicron-infected and non-Omicron-infected febrile children. The body temperatures of Omicron-infected children were significantly higher during convulsions than when they were not convulsing and those of non-Omicron-infected febrile children during convulsions (median: 39.5 vs. 38.2 and 38.6 °C, both P < 0.001). In the three Omicron-subgroups, the temperature during convulsions was proportional to the percentage of patients and significantly differed ( P < 0.001), while not in the three non-Omicron-subgroups ( P = 0.244). The convulsion frequency was lower in the 55 vaccinated children compared to the 260 non-vaccinated children (average: 1.8 vs. 2.1, P < 0.001). The vaccination dose and convulsion frequency in Omicron-infected children were significantly correlated ( P < 0.001). Fifteen of the 112 severe Omicron cases had brain damage. CONCLUSIONS: Omicron-infected children experience higher body temperatures and frequencies during convulsions than those of non-Omicron-infected febrile children. We additionally found evidence of brain damage caused by infection with omicron BA.5. Vaccination and prompt fever reduction may relieve symptoms.

Diagnostic Role of Metagenomic Next-Generation Sequencing in Tubercular Orthopedic Implant-Associated Infection.

Objective: The diagnosis of tubercular orthopedic implant-associated infection (TB-IAI) is challenging. This study evaluated the value of metagenomic next-generation sequencing (mNGS) for the diagnosis of TB-IAI and developed a standardized diagnostic procedure for TB-IAI. Methods: The records of all patients with TB-IAI diagnosed and treated at our institution between December 2018 and September 2022 were retrospectively reviewed. Patient demographic characteristics, medical history, laboratory test, microbial culture, histopathology, and mNGS results, and time to diagnosis were recorded. The diagnostic efficiency of mNGS for TB-IAI was assessed by comparing the results and diagnostic time with that of other diagnostic modalities. Results: Ten patients were included in the analysis, including eight with prosthetic joint infections and two with fracture-related infections. The mNGS positivity rate was 100% (10/10), which was higher than that of TB-antibody (11%, 1/9), real-time quantitative polymerase chain reaction (22%, 2/9), T-SPOT.TB (25%, 2/8), purified protein derivative (50%, 4/8), microbial culture (50%, 5/10), and histopathology (20%, 2/10). mNGS shortened the time to diagnosis of TB-IAI. A standardized diagnostic procedure for TB-IAI was developed based on the findings. Conclusion: mNGS is useful for the diagnosis of TB-IAI. mNGS is recommended in cases where it is difficult to identify a pathogen using routine diagnostic tests. The standardized diagnostic procedure might improve TB-IAI diagnosis. Importance: TB-IAI is a rare infection, which occurs after orthopedic surgery and hard to diagnose microbiologically. mNGS is a new detection technique not yet discussed in current literature as a means for TB-IAI diagnostics. Here we describe a cohort of patients with TB-IAI diagnosed by mNGS show high efficiency of mNGS for detection of this pathology and present a clinical algorithm supplementing conventional methods for TB-IAI assessment.