Pyroptosis Signature Gene CHMP4B Regulates Microglia Pyroptosis by Inhibiting GSDMD in Alzheimer's Disease.

In this study, we aimed to work through the key genes involved in the process of pyroptosis in Alzheimer's disease (AD) to identify potential biomarkers using bioinformatics technology and further explore the underlying molecular mechanisms. The transcriptome data of brain tissue in AD patients were screened from the GEO database, and pyroptosis-related genes were analyzed. The functions of differential genes were analyzed by enrichment analysis and protein-protein interaction. The diagnostic model was established using LASSO and logistic regression analysis, and the correlation of clinical data was analyzed. Based on single-cell analysis of brain tissues of patients with AD, immunofluorescence and western blotting were used to explore the key cells affected by the hub gene. After GSEA, qRT-PCR, western blotting, LDH, ROS, and JC-1 were used to investigate the potential mechanism of the hub gene on pyroptosis. A total of 15 pyroptosis differentially expressed genes were identified. A prediction model consisting of six genes was established by LASSO and logistic regression analysis, and the area under the curve was up to 0.81. As a hub gene, CHMP4B was negatively correlated with the severity of AD. CHMP4B expression was decreased in the hippocampal tissue of patients with AD and mice. Single-cell analysis showed that CHMP4B was downregulated in AD microglia. Overexpression of CHMP4B reduced the release of LDH and ROS and restored mitochondrial membrane potential, thereby alleviating the inflammatory response during microglial pyroptosis. In summary, CHMP4B as a hub gene provides a new strategy for the diagnosis and treatment of AD.

Pathogen detection via inductively coupled plasma mass spectrometry analysis with nanoparticles.

Infections caused by viruses and bacteria pose a significant threat to global public health, emphasizing the critical importance of timely and precise detection methods. Inductively coupled plasma mass spectrometry (ICP-MS), a contemporary approach for pathogen detection, offers distinct advantages such as high sensitivity, a wide linear range, and multi-index capabilities. This review elucidates the underexplored application of ICP-MS in conjunction with functional nanoparticles (NPs) for the identification of viruses and bacteria. The review commences with an elucidation of the underlying principles, procedures, target pathogens, and NP requirements for this innovative approach. Subsequently, a thorough analysis of the advantages and limitations associated with these techniques is provided. Furthermore, the review delves into a comprehensive examination of the challenges encountered when utilizing NPs and ICP-MS for pathogen detection, culminating in a forward-looking assessment of the potential pathways for advancement in this domain. Thus, this review contributes novel perspectives to the field of pathogen detection in biomedicine by showcasing the promising synergy of ICP-MS and NPs.

STAT3-induced lncRNA GNAS-AS1 accelerates keloid formation by mediating the miR-196a-5p/CXCL12/STAT3 axis in a feedback loop.

Keloids are pathological scar tissue resulting from skin trauma or spontaneous formation, often accompanied by itching and pain. Although GNAS antisense RNA 1 (GNAS-AS1) shows abnormal upregulation in keloids, the underlying molecular mechanism is unclear. The levels of genes and proteins in clinical tissues from patients with keloids and human keloid fibroblasts (HKFs) were measured using quantitative reverse transcription PCR, western blot and enzyme-linked immunosorbent assay. The features of HKFs, including proliferation and migration, were evaluated using cell counting kit 8 and a wound healing assay. The colocalization of GNAS-AS1 and miR-196a-5p in HKFs was measured using fluorescence in situ hybridization. The relationships among GNAS-AS1, miR-196a-5p and C-X-C motif chemokine ligand 12 (CXCL12) in samples from patients with keloids were analysed by Pearson correlation analysis. Gene interactions were validated by chromatin immunoprecipitation and luciferase reporter assays. GNAS-AS1 and CXCL12 expression were upregulated and miR-196a-5p expression was downregulated in clinical tissues from patients with keloids. GNAS-AS1 knockdown inhibited proliferation, migration, and extracellular matrix (ECM) accumulation of HKFs, all of which were reversed by miR-196a-5p downregulation. Signal transducer and activator of transcription 3 (STAT3) induced GNAS-AS1 transcription through GNAS-AS1 promoter interaction, and niclosamide, a STAT3 inhibitor, decreased GNAS-AS1 expression. GNAS-AS1 positively regulated CXCL12 by sponging miR-196-5p. Furthermore, CXCL12 knockdown restrained STAT3 phosphorylation in HKFs. Our findings revealed a feedback loop of STAT3/GNAS-AS1/miR-196a-5p/CXCL12/STAT3 that promoted HKF proliferation, migration and ECM accumulation and affected keloid progression.

Nano-enzyme hydrogels for cartilage repair effectiveness based on ternary strategy therapy.

Designing artificial nano-enzymes for scavenging reactive oxygen species (ROS) in chondrocytes (CHOs) is considered the most feasible pathway for the treatment of osteoarthritis (OA). However, the accumulation of ROS due to the amount of nano-enzymatic catalytic site exposure and insufficient oxygen supply seriously threatens the clinical application of this therapy. Although metal-organic framework (MOF) immobilization of artificial nano-enzymes to enhance active site exposure has been extensively studied, artificial nano-enzymes/MOFs for ROS scavenging in OA treatment are still lacking. In this study, a biocompatible lubricating hydrogel-loaded iron-doped zeolitic imidazolate framework-8 (Fe/ZIF-8/Gel) centrase was engineered to scavenge endogenous overexpressed ROS synergistically generating dissolved oxygen and enhancing sustained lubrication for CHOs as a ternary artificial nano-enzyme. This property enabled the nano-enzymatic hydrogels to mitigate OA hypoxia and inhibit oxidative stress damage successfully. Ternary strategy-based therapies show excellent cartilage repair in vivo. The experimental results suggest that nano-enzyme-enhanced lubricating hydrogels are a potentially effective OA treatment and a novel strategy.

A Top-Down Design Approach for Generating a Peptide PROTAC Drug Targeting Androgen Receptor for Androgenetic Alopecia Therapy.

While large-scale artificial intelligence (AI) models for protein structure prediction and design are advancing rapidly, the translation of deep learning models for practical macromolecular drug development remains limited. This investigation aims to bridge this gap by combining cutting-edge methodologies to create a novel peptide-based PROTAC drug development paradigm. Using ProteinMPNN and RFdiffusion, we identified binding peptides for androgen receptor (AR) and Von Hippel-Lindau (VHL), followed by computational modeling with Alphafold2-multimer and ZDOCK to predict spatial interrelationships. Experimental validation confirmed the designed peptide's binding ability to AR and VHL. Transdermal microneedle patching technology was seamlessly integrated for the peptide PROTAC drug delivery in androgenic alopecia treatment. In summary, our approach provides a generic method for generating peptide PROTACs and offers a practical application for designing potential therapeutic drugs for androgenetic alopecia. This showcases the potential of interdisciplinary approaches in advancing drug development and personalized medicine.

Satellite Tracking Reveals the Speed Up of the Lacustrine Algal Bloom Drift in Response to Climate Change.

Satellite evidence indicates a global increase in lacustrine algal blooms. These blooms can drift with winds, resulting in significant changes of the algal biomass spatial distribution, which is crucial in bloom formation. However, the lack of long-term, large-scale observational data has limited our understanding of bloom drift. Here, we have developed a novel method to track the drift using multi-source remote sensing satellites and presented a comprehensive bloom drift data set for four typical lakes: Lake Taihu (China, 2011-2021), Lake Chaohu (China, 2011-2020), Lake Dianchi (China, 2003-2021), and Lake Erie (North America, 2003-2021). We found that blooms closer to the water surface tend to drift faster. Higher temperatures and lower wind speeds bring blooms closer to the water surface, therefore accelerating drift and increasing biomass transportation. Under ongoing climate change, algal blooms are increasingly likely to spread over larger areas and accumulate in downwind waters, thereby posing a heightened risk to water resources. Our research greatly improves the understanding of algal bloom dynamics and provides new insights into the driving factors behind the global expansion of algal blooms. Our bloom-drift-tracking methodology also paves the way for the development of high-precision algal bloom prediction models.

MISD-IR: material-image subspace decomposition-based iterative reconstruction with spectrum estimation for dual-energy computed tomography.

Background: Dual-energy computed tomography (DECT) is a promising technique, which can provide unique capability for material quantification. The iterative reconstruction of material maps requires spectral information and its accuracy is affected by spectral mismatch. Simultaneously estimating the spectra and reconstructing material maps avoids extra workload on spectrum estimation and the negative impact of spectral mismatch. However, existing methods are not satisfactory in image detail preservation, edge retention, and convergence rate. The purpose of this paper was to mine the similarity between the reconstructed images and the material images to improve the imaging quality, and to design an effective iteration strategy to improve the convergence efficiency. Methods: The material-image subspace decomposition-based iterative reconstruction (MISD-IR) with spectrum estimation was proposed for DECT. MISD-IR is an optimized model combining spectral estimation and material reconstruction with fast convergence speed and promising noise suppression capability. We proposed to reconstruct the material maps based on extended simultaneous algebraic reconstruction techniques and estimation of the spectrum with model spectral. To stabilize the iteration and alleviate the influence of errors, we introduced a weighted proximal operator based on the block coordinate descending algorithm (WP-BCD). Furthermore, the reconstructed computed tomography (CT) images were introduced to suppress the noise based on subspace decomposition, which relies on non-local regularization to prevent noise accumulation. Results: In numerical experiments, the results of MISD-IR were closer to the ground truth compared with other methods. In real scanning data experiments, the results of MISD-IR showed sharper edges and details. Compared with other one-step iterative methods in the experiment, the running time of MISD-IR was reduced by 75%. Conclusions: The proposed MISD-IR can achieve accurate material decomposition (MD) without known energy spectrum in advance, and has good retention of image edges and details. Compared with other one-step iterative methods, it has high convergence efficiency.

Genus_Ruminococcus and order_Burkholderiales affect osteoporosis by regulating the microbiota-gut-bone axis.

Background: This study aimed to clarify the relationship between the gut microbiota and osteoporosis combining Mendelian randomization (MR) analysis with animal experiments. Methods: We conducted an analysis on the relationship between differential bacteria and osteoporosis using open-access genome-wide association study (GWAS) data on gut microbe and osteoporosis obtained from public databases. The analysis was performed using two-sample MR analysis, and the causal relationship was examined through inverse variance weighting (IVW), MR Egger, weighted median, and weighted mode methods. Bilateral oophorectomy was employed to replicate the mouse osteoporosis model, which was assessed by micro computed tomography (CT), pathological tests, and bone transformation indexes. Additionally, 16S rDNA sequencing was conducted on fecal samples, while SIgA and indexes of IL-6, IL-1ß, and TNF-α inflammatory factors were examined in colon samples. Through immunofluorescence and histopathology, expression levels of tight junction proteins, such as claudin-1, ZO-1, and occludin, were assessed, and conduct correlation analysis on differential bacteria and related environmental factors were performed. Results: A positive correlation was observed between g_Ruminococcus1 and the risk of osteoporosis, while O_Burkholderiales showed a negative correlation with the risk of osteoporosis. Furthermore, there was no evidence of heterogeneity or pleiotropy. The successful replication of the mouse osteoporosis model was assessed, and it was found that the abundance of the O_Burkholderiales was significantly reduced, while the abundance of g_Ruminococcus was significantly increased in the ovariectomized (OVX)-mice. The intestinal SIgA level of OVX mice decreased, the expression level of inflammatory factors increased, barrier damage occurred, and the content of LPS in the colon and serum significantly increased. The abundance level of O_Burkholderiales is strongly positively correlated with bone formation factors, gut barrier indicators, bone density, bone volume fraction, and trabecular bone quantity, whereas it was strongly negatively correlated with bone resorption factors and intestinal inflammatory factors, The abundance level of g_Ruminococcus shows a strong negative correlation with bone formation factors, gut barrier indicators, and bone volume fraction, and a strong positive correlation with bone resorption factors and intestinal inflammatory factors. Conclusion: O_Burkholderiales and g_Ruminococcus may regulate the development of osteoporosis through the microbiota-gut-bone axis.

Multidimensional biological characteristics of ground glass nodules.

The detection rate of ground glass nodules (GGNs) has increased in recent years because of their malignant potential but relatively indolent biological behavior; thus, correct GGN recognition and management has become a research focus. Many scholars have explored the underlying mechanism of the indolent progression of GGNs from several perspectives, such as pathological type, genomic mutational characteristics, and immune microenvironment. GGNs have different major mutated genes at different stages of development; EGFR mutation is the most common mutation in GGNs, and p53 mutation is the most abundant mutation in the invasive stage of GGNs. Pure GGNs have fewer genomic alterations and a simpler genomic profile and exhibit a gradually evolving genomic mutation profile as the pathology progresses. Compared to advanced lung adenocarcinoma, GGN lung adenocarcinoma has a higher immune cell percentage, is under immune surveillance, and has less immune escape. However, as the pathological progression and solid component increase, negative immune regulation and immune escape increase gradually, and a suppressive immune environment is established gradually. Currently, regular computer tomography monitoring and surgery are the main treatment strategies for persistent GGNs. Stereotactic body radiotherapy and radiofrequency ablation are two local therapeutic alternatives, and systemic therapy has been progressively studied for lung cancer with GGNs. In the present review, we discuss the characterization of the multidimensional molecular evolution of GGNs that could facilitate more precise differentiation of such highly heterogeneous lesions, laying a foundation for the development of more effective individualized treatment plans.

Vapor Deposition of Bilayer 3R MoS2 with Room-Temperature Ferroelectricity.

Two-dimensional ultrathin ferroelectrics have attracted much interest due to their potential application in high-density integration of non-volatile memory devices. Recently, two-dimensional van der Waals ferroelectric based on interlayer translation has been reported in twisted bilayer h-BN and TMDs. However, sliding ferroelectricity has not well been studied in non-twisted homo-bilayer TMD grown directly by CVD. In this paper, for the first time, we reported experimental observation of a room-temperature out-of-plane ferroelectric switch in semiconducting bilayer 3R MoS2 synthesized by reverse-flow CVD. PFM hysteretic loops and first principle calculations demonstrate that the ferroelectric nature and polarization switching processes are based on interlayer sliding. The vertical Au/3R MoS2/Pt device exhibits a switchable diode effect. Polarization modulated Schottky barrier height and polarization coupling of interfacial deep states trapping/detrapping might serve in coordination to determine switchable diode effect.The room-temperature ferroelectricity of CVD-grown MoS2 will proceed with the potential wafer-scale integration of 2D TMDs in the logic circuit. This article is protected by copyright. All rights reserved.

The role of aryl hydrocarbon receptors in nutrient metabolism and immune regulation at the maternal-fetal interface.

The maternal-fetal interface is composed of the placenta, which is affiliated with the fetus, and the maternal decidua. During pregnancy, the placenta is mainly responsible for nutrient transport and immune tolerance maintenance, which plays a key role in fetal growth and development and pregnancy maintenance. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that exists in various cell types at the maternal-fetal interface and is involved in multiple cellular processes. Recent studies have highlighted the role of AhR in regulating various physiological processes, including glucose and lipid metabolism, as well as tryptophan metabolism and immune responses, within non-pregnant tissues. This review shifts focus towards understanding how AhR modulation impacts metabolism and immune regulation at the maternal-fetal interface. This may implicate the development of pregnancy-related complications and the potential target of the AhR pathway for therapeutic strategies against poor pregnancy outcomes.

A hybrid demultiplexing strategy that improves performance and robustness of cell hashing.

Cell hashing, a nucleotide barcode-based method that allows users to pool multiple samples and demultiplex in downstream analysis, has gained widespread popularity in single-cell sequencing due to its compatibility, simplicity, and cost-effectiveness. Despite these advantages, the performance of this method remains unsatisfactory under certain circumstances, especially in experiments that have imbalanced sample sizes or use many hashtag antibodies. Here, we introduce a hybrid demultiplexing strategy that increases accuracy and cell recovery in multi-sample single-cell experiments. This approach correlates the results of cell hashing and genetic variant clustering, enabling precise and efficient cell identity determination without additional experimental costs or efforts. In addition, we developed HTOreader, a demultiplexing tool for cell hashing that improves the accuracy of cut-off calling by avoiding the dominance of negative signals in experiments with many hashtags or imbalanced sample sizes. When compared to existing methods using real-world datasets, this hybrid approach and HTOreader consistently generate reliable results with increased accuracy and cell recovery.

Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) have led to groundbreaking advancements in life sciences. To develop bioinformatics tools for scRNA-seq and SRT data and perform unbiased benchmarks, data simulation has been widely adopted by providing explicit ground truth and generating customized datasets. However, the performance of simulation methods under multiple scenarios has not been comprehensively assessed, making it challenging to choose suitable methods without practical guidelines. RESULTS: We systematically evaluated 49 simulation methods developed for scRNA-seq and/or SRT data in terms of accuracy, functionality, scalability, and usability using 152 reference datasets derived from 24 platforms. SRTsim, scDesign3, ZINB-WaVE, and scDesign2 have the best accuracy performance across various platforms. Unexpectedly, some methods tailored to scRNA-seq data have potential compatibility for simulating SRT data. Lun, SPARSim, and scDesign3-tree outperform other methods under corresponding simulation scenarios. Phenopath, Lun, Simple, and MFA yield high scalability scores but they cannot generate realistic simulated data. Users should consider the trade-offs between method accuracy and scalability (or functionality) when making decisions. Additionally, execution errors are mainly caused by failed parameter estimations and appearance of missing or infinite values in calculations. We provide practical guidelines for method selection, a standard pipeline Simpipe ( https://github.com/duohongrui/simpipe ; https://doi.org/10.5281/zenodo.11178409 ), and an online tool Simsite ( https://www.ciblab.net/software/simshiny/ ) for data simulation. CONCLUSIONS: No method performs best on all criteria, thus a good-yet-not-the-best method is recommended if it solves problems effectively and reasonably. Our comprehensive work provides crucial insights for developers on modeling gene expression data and fosters the simulation process for users.

Cytological diagnosis of patients with embryonal rhabdomyosarcoma of the cervix: case report and literature review.

Cervical embryonal rhabdomyosarcoma(ERMS) is a rare malignancy. To date, no cases of ERMS diagnosed by cervical cytology have been reported. In this study, we report a case of cervical ERMS identified by a liquid-based cytology test and cell blocks in a 46-year-old postmenopausal woman. We describe the cytological features of ERMS, with the aim of helping cytopathologists recognize this rare cervical tumor.

The relationship between childhood adversity and sleep quality among rural older adults in China: the mediating role of anxiety and negative coping.

BACKGROUND: Studies have revealed the effects of childhood adversity, anxiety, and negative coping on sleep quality in older adults, but few studies have focused on the association between childhood adversity and sleep quality in rural older adults and the potential mechanisms of this influence. In this study, we aim to evaluate sleep quality in rural older adults, analyze the impact of adverse early experiences on their sleep quality, and explore whether anxiety and negative coping mediate this relationship. METHODS: Data were derived from a large cross-sectional study conducted in Deyang City, China, which recruited 6,318 people aged 65 years and older. After excluding non-agricultural household registration and lack of key information, a total of 3,873 rural older adults were included in the analysis. Structural equation modelling (SEM) was used to analyze the relationship between childhood adversity and sleep quality, and the mediating role of anxiety and negative coping. RESULTS: Approximately 48.15% of rural older adults had poor sleep quality, and older adults who were women, less educated, widowed, or living alone or had chronic illnesses had poorer sleep quality. Through structural equation model fitting, the total effect value of childhood adversity on sleep quality was 0.208 (95% CI: 0.146, 0.270), with a direct effect value of 0.066 (95% CI: 0.006, 0.130), accounting for 31.73% of the total effect; the total indirect effect value was 0.142 (95% CI: 0.119, 0.170), accounting for 68.27% of the total effect. The mediating effects of childhood adversity on sleep quality through anxiety and negative coping were significant, with effect values of 0.096 (95% CI: 0.078, 0.119) and 0.024 (95% CI: 0.014, 0.037), respectively. The chain mediating effect of anxiety and negative coping between childhood adversity and sleep quality was also significant, with an effect value of 0.022 (95% CI: 0.017, 0.028). CONCLUSIONS: Anxiety and negative coping were important mediating factors for rural older adult's childhood adversity and sleep quality. This suggests that managing anxiety and negative coping in older adults may mitigate the negative effects of childhood adversity on sleep quality.

The microRNA408-plantacyanin module balances plant growth and drought resistance by regulating reactive oxygen species homeostasis in guard cells.

The conserved microRNA (miRNA) miR408 enhances photosynthesis and compromises stress tolerance in multiple plants, but the cellular mechanism underlying its function remains largely unclear. Here, we show that in Arabidopsis (Arabidopsis thaliana), the transcript encoding the blue copper protein PLANTACYANIN (PCY) is the primary target for miR408 in vegetative tissues. PCY is preferentially expressed in the guard cells, and PCY is associated with the endomembrane surrounding individual chloroplasts. We found that the MIR408 promoter is suppressed by multiple abscisic acid (ABA)-responsive transcription factors, thus allowing PCY to accumulate under stress conditions. Genetic analysis revealed that PCY elevates reactive oxygen species (ROS) levels in the guard cells, promotes stomatal closure, reduces photosynthetic gas exchange, and enhances drought resistance. Moreover, the miR408-PCY module is sufficient to rescue the growth and drought tolerance phenotypes caused by gain- and loss-of-function of MYB44, an established positive regulator of ABA responses, indicating that the miR408-PCY module relays ABA signaling for regulating ROS homeostasis and drought resistance. These results demonstrate that miR408 regulates stomatal movement to balance growth and drought resistance, providing a mechanistic understanding of why miR408 is selected during land plant evolution and insights into the long-pursued quest of breeding drought-tolerant and high-yielding crops.

Differentiation and Regulation of Bovine Th2 Cells In Vitro.

Bovine Th2 cells have usually been characterized by IL4 mRNA expression, but it is unclear whether their IL4 protein expression corresponds to transcription. We found that grass-fed healthy beef cattle, which had been regularly exposed to parasites on the grass, had a low frequency of IL4+ Th2 cells during flow cytometry, similar to animals grown in feedlots. To assess the distribution of IL4+ CD4+ T cells across tissues, samples from the blood, spleen, abomasal (draining), and inguinal lymph nodes were examined, which revealed limited IL4 protein detection in the CD4+ T cells across the examined tissues. To determine if bovine CD4+ T cells may develop into Th2 cells, naïve cells were stimulated with anti-bovine CD3 under a Th2 differentiation kit in vitro. The cells produced primarily IFNγ proteins, with only a small fraction (<10%) co-expressing IL4 proteins. Quantitative PCR confirmed elevated IFNγ transcription but no significant change in IL4 transcription. Surprisingly, GATA3, the master regulator of IL4, was highest in naïve CD4+ T cells but was considerably reduced following differentiation. To determine if the differentiated cells were true Th2 cells, an unbiased proteomic assay was carried out. The assay identified 4212 proteins, 422 of which were differently expressed compared to those in naïve cells. Based on these differential proteins, Th2-related upstream components were predicted, including CD3, CD28, IL4, and IL33, demonstrating typical Th2 differentiation. To boost IL4 expression, T cell receptor (TCR) stimulation strength was reduced by lowering anti-CD3 concentrations. Consequently, weak TCR stimulation essentially abolished Th2 expansion and survival. In addition, extra recombinant bovine IL4 (rbIL4) was added during Th2 differentiation, but, despite enhanced expansion, the IL4 level remained unaltered. These findings suggest that, while bovine CD4+ T cells can respond to Th2 differentiation stimuli, the bovine IL4 pathway is not regulated in the same way as in mice and humans. Furthermore, Ostertagia ostertagi (OO) extract, a gastrointestinal nematode in cattle, inhibited signaling via CD3, CD28, IL4, and TLRs/MYD88, indicating that external pathogens can influence bovine Th2 differentiation. In conclusion, though bovine CD4+ T cells can respond to IL4-driven differentiation, IL4 expression is not a defining feature of differentiated bovine Th2 cells.

Bactericidal and sterilizing activity of sudapyridine-clofazimine-TB47 combined with linezolid or pyrazinamide in a murine model of tuberculosis.

As an obligate aerobe, Mycobacterium tuberculosis relies on its branched electron transport chain (ETC) for energy production through oxidative phosphorylation. Regimens targeting ETC exhibit promising potential to enhance bactericidal activity against M. tuberculosis and hold the prospect of shortening treatment duration. Our previous research demonstrated that the bacteriostatic drug candidate TB47 (T) inhibited the growth of M. tuberculosis by targeting the cytochrome bc1 complex and exhibited synergistic activity with clofazimine (C). Here, we found synergistic activities between C and sudapyridine (S), a structural analog of bedaquiline (B). S has shown similar anti-tuberculosis efficacy and may share a mechanism of action with B, which inhibits ATP synthesis and the energy metabolism of bacteria. We evaluated the efficacy of SCT in combination with linezolid (L) or pyrazinamide (Z) using a well-established murine model of tuberculosis. Compared to the BPa(pretomanid)L regimen, SCT and SCTL demonstrated similar bactericidal and sterilizing activities. There was no significant difference in activity between SCT and SCTL. In contrast, SCZ and SCTZ showed much higher activities, with none of the 15 mice experiencing relapse after 2 months of treatment with either SCZ or SCTZ. However, T did not contribute to the activity of the SCZ. Our findings emphasize the efficacy and the potential clinical significance of combination therapy with ETC inhibitors. Additionally, cross-resistance exists not only between S and B but also between S/B and C. This is supported by our findings, as spontaneous S-resistant mutants exhibited mutations in Rv0678, which are associated with cross-resistance to B and C.

An Artificial Intelligence-Driven Approach for Automatic Evaluation of Right-to-Left Shunt Grades in Saline-Contrasted Transthoracic Echocardiography.

BACKGROUND: Intracardiac or pulmonary right-to-left shunt (RLS) is a common cardiac anomaly associated with an increased risk of neurological disorders, specifically cryptogenic stroke. Saline-contrasted transthoracic echocardiography (scTTE) is often used for RLS diagnosis. However, the identification of saline microbubbles in the left heart can be challenging for novice residents, potentially leading to a delay in diagnosis and treatment. In this study, we proposed an artificial intelligence (AI)-based algorithm designed to automatically detect microbubbles in scTTE images and evaluate right-to-left shunt grades. This tool aims to support residency training and decrease the workload of cardiologists. METHODS: A dataset of 23,665 scTTE images obtained from 174 individuals was included in this study. This dataset was partitioned into a training set (n = 20,475) and an internal validation set (n = 3,190) on a patient-level basis. An additional cohort of 33 patients diagnosed with cryptogenic ischemic stroke was enrolled as an external validation set. The proposed algorithm for right-to-left shunt degree classification employed the EfficientNet-b4 model, and the model's performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity, and compared to the performance of residents. RESULTS: Our AI model demonstrated robust performance with an accuracy of 0.926, sensitivity of 0.827, and specificity of 0.951 on the internal testing dataset. In the external validation set, our AI model exhibited diagnostic accuracy, sensitivity, and specificity of 0.864, 0.818, and 0.909, respectively. In comparison, residents achieved values of 0.727, 0.636, and 0.818, respectively. CONCLUSION: Our AI model provides a swift, precise, and easily deployable methodology for grading the degree of right-to-left shunt in scTTE, carrying substantial implications for routine clinical practice. Residents can benefit from our artificial intelligence-based algorithm, enhancing both the accuracy and efficiency of RLS diagnosis.