COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

RDBSB: a database for catalytic bioparts with experimental evidence.

Catalytic bioparts are fundamental to the design, construction and optimization of biological systems for specific metabolic pathways. However, the functional characterization information of these bioparts is frequently dispersed across multiple databases and literature sources, posing significant challenges to the effective design and optimization of specific chassis or cell factories. We developed the Registry and Database of Bioparts for Synthetic Biology (RDBSB), a comprehensive resource encompassing 83 193 curated catalytic bioparts with experimental evidences. RDBSB offers their detailed qualitative and quantitative catalytic information, including critical parameters such as activities, substrates, optimal pH and temperature, and chassis specificity. The platform features an interactive search engine, visualization tools and analysis utilities such as biopart finder, structure prediction and pathway design tools. Additionally, RDBSB promotes community engagement through a catalytic bioparts submission system to facilitate rapid data sharing and utilization. To date, RDBSB has supported the contribution of >1000 catalytic bioparts. We anticipate that the database will significantly enhance the resources available for pathway design in synthetic biology and serve essential tools for researchers. RDBSB is freely available at https://www.biosino.org/rdbsb/.

TRPML3/BK complex promotes autophagy and bacterial clearance by providing a positive feedback regulation of mTOR via PI3P.

TRPML3 is a Ca2+/Na+ release channel residing in both phagophores and endolysosomal membranes. It is activated by PI3P and PI3,5P2. Its activity can be enhanced by high luminal pH and by replacing luminal Na+ with K+. Here, we report that big-conductance Ca2+-activated potassium (BK) channels form a positive feedback loop with TRPML3. Ca2+ release via TRPML3 activates BK, which in turn facilitates TRPML3-mediated Ca2+ release, potentially through removing luminal Na+ inhibition. We further show that TRPML3/BK and mammalian target of rapamycin (mTOR) form another positive feedback loop to facilitate autophagy induction in response to nutrient starvation, i.e., mTOR inhibition upon nutrient starvation activates TRPML3/BK, and this further reduces mTOR activity, thereby increasing autophagy induction. Mechanistically, the feedback regulation between TRPML3/BK and mTOR is mediated by PI3P, an endogenous TRPML3 activator that is enriched in phagophores and is up-regulated by mTOR reduction. Importantly, bacterial infection activates TRPML3 in a BK-dependent manner, and both TRPML3 and BK are required for mTOR suppression and autophagy induction responding to bacterial infection. Suppressing either TRPML3 or BK helps bacteria survival whereas increasing either TRPML3 or BK favors bacterial clearance. Considering that TRPML3/BK is inhibited by low luminal pH but activated by high luminal pH and PI3P in phagophores, we suggest that TRPML3/BK and mTOR form a positive feedback loop via PI3P to ensure efficient autophagy induction in response to nutrient deprivation and bacterial infection. Our study reveals a role of TRPML3-BK coupling in controlling cellular homeostasis and intracellular bacterial clearance via regulating mTOR signaling.

An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation.

Single-cell RNA sequencing (scRNA-seq) detects whole transcriptome signals for large amounts of individual cells and is powerful for determining cell-to-cell differences and investigating the functional characteristics of various cell types. scRNA-seq datasets are usually sparse and highly noisy. Many steps in the scRNA-seq analysis workflow, including reasonable gene selection, cell clustering and annotation, as well as discovering the underlying biological mechanisms from such datasets, are difficult. In this study, we proposed an scRNA-seq analysis method based on the latent Dirichlet allocation (LDA) model. The LDA model estimates a series of latent variables, i.e. putative functions (PFs), from the input raw cell-gene data. Thus, we incorporated the 'cell-function-gene' three-layer framework into scRNA-seq analysis, as this framework is capable of discovering latent and complex gene expression patterns via a built-in model approach and obtaining biologically meaningful results through a data-driven functional interpretation process. We compared our method with four classic methods on seven benchmark scRNA-seq datasets. The LDA-based method performed best in the cell clustering test in terms of both accuracy and purity. By analysing three complex public datasets, we demonstrated that our method could distinguish cell types with multiple levels of functional specialization, and precisely reconstruct cell development trajectories. Moreover, the LDA-based method accurately identified the representative PFs and the representative genes for the cell types/cell stages, enabling data-driven cell cluster annotation and functional interpretation. According to the literature, most of the previously reported marker/functionally relevant genes were recognized.

Acetyl-CoA Carboxylase1 Influences ECERIFERUM2 Activity to Mediate the Synthesis of Very-Long-Chain Fatty Acid Past C28.

Cuticular wax is a protective layer on the aerial surfaces of land plants. In Arabidopsis (Arabidopsis thaliana), cuticular wax is mainly constituted of compounds derived from very-long-chain fatty acids (VLCFAs) with chain lengths longer than C28. CER2-LIKE (ECERIFERUM2-LIKE) proteins interact with CER6/KCS6 (ECERIFERUM6/ß-Ketoacyl-CoA Synthase6), the key enzyme of the fatty acid elongase complex, to modify its substrate specificity for VLCFA elongation past C28. However, the molecular regulatory mechanism of CER2-LIKE proteins remains unclear. Arabidopsis eceriferum19 (cer19) mutants display wax-deficient stems caused by loss of waxes longer than C28, indicating that CER19 may participate in the CER2-LIKE-mediated VLCFA elongation past C28. Using positional cloning and genetic complementation, we showed that CER19 encodes Acetyl-CoA Carboxylase1 (ACC1), which catalyzes the synthesis of malonyl-CoA, the essential substrate for the CER6/KCS6-mediated condensation reaction in VLCFA synthesis. We demonstrated that ACC1 physically interacts with CER2-LIKE proteins via split-ubiquitin yeast two-hybrid (SUY2H) and firefly luciferase complementation imaging (LCI) analysis. Additionally, heterologous expression in yeast and genetic analysis in Arabidopsis revealed that ACC1 affects CER2 activity to influence VLCFA elongation past C28. These findings imply that CER2-LIKE proteins might function as a link between ACC1 and CER6/KCS6 and subsequently enhance CER6/KCS6 binding to malonyl-CoA for further utilization in VLCFA elongation past C28. This information deepens our understanding of the complex mechanism of cuticular wax biosynthesis.

Tolerogenic CD11c+dendritic cells regulate CD4+Tregs in replacing delayed ischemic preconditioning to alleviate ischemia-reperfusion acute kidney injury.

Ischemia-reperfusion injury (IRI) is one of the primary clinical causes of acute kidney injury (AKI). The key to IRI lies in immune-inflammatory damage, where dendritic cells (DCs) play a central role in eliciting immune responses within the context of inflammation induced by ischemia-reperfusion. Our previous study has confirmed that delayed ischemic preconditioning (DIPC) can reduce the kidney injury by mediating DCs to regulate T-cells. However, the clinical feasibility of DIPC is limited, as pre-clamping of the renal artery is not applicable for the prevention and treatment of ischemia-reperfusion acute kidney injury (I/R-AKI) in clinical patients. Therefore, the infusion of DCs as a substitute for DIPC presents a more viable strategy for preventing renal IRI. In this study, we further evaluated the impact and mechanism of infused tolerogenic CD11c+DCs on the kidneys following IRI by isolating bone marrow-derived dendritic cells and establishing an I/R-AKI model after pre-infusion of DCs. Renal function was significantly improved in the I/R-AKI mouse model after pre-infused with CD11c+DCs. The pro-inflammatory response and oxidative damage were reduced, and the levels of T helper 2 (Th2) cells and related anti-inflammatory cytokines were increased, which was associated with the reduction of autologous DCs maturation mediated by CD11c+DCs and the increase of regulatory T-cells (Tregs). Next, knocking out CD11c+DCs, we found that the reduced immune protection of tolerogenic CD11c+DCs reinfusion was related to the absence of own DCs. Together, pre-infusion of tolerogenic CD11c+DCs can replace the regulatory of DIPC on DCs and T-cells to alleviate I/R-AKI. DC vaccine is expected to be a novel avenue to prevent and treat I/R-AKI.

SIRT1-mediated deacetylation of FOXO3 enhances mitophagy and drives hormone resistance in endometrial cancer.

BACKGROUND: The complex interplay between Sirtuin 1 (SIRT1) and FOXO3 in endometrial cancer (EC) remains understudied. This research aims to unravel the interactions of deacetylase SIRT1 and transcription factor FOXO3 in EC, focusing on their impact on mitophagy and hormone resistance. METHODS: High-throughput sequencing, cell experiments, and bioinformatics tools were employed to investigate the roles and interactions of SIRT1 and FOXO3 in EC. Co-immunoprecipitation (Co-IP) assay was used to assess the interaction between SIRT1 and FOXO3 in RL95-2 cells. Functional assays were used to assess cell viability, proliferation, migration, invasion, apoptosis, and the expression of related genes and proteins. A mouse model of EC was established to evaluate tumor growth and hormone resistance under different interventions. Immunohistochemistry and TUNEL assays were used to assess protein expression and apoptosis in tumor tissues. RESULTS: High-throughput transcriptome sequencing revealed a close association between SIRT1, FOXO3, and EC development. Co-IP showed a protein-protein interaction between SIRT1 and FOXO3. Overexpression of SIRT1 enhanced FOXO3 deacetylation and activity, promoting BNIP3 transcription and PINK1/Parkin-mediated mitophagy, which in turn promoted cell proliferation, migration, invasion, and inhibited apoptosis in vitro, as well as increased tumor growth and hormone resistance in vivo. These findings highlighted SIRT1 as an upstream regulator and potential therapeutic target in EC. CONCLUSION: This study reveals a novel molecular mechanism underlying the functional relevance of SIRT1 in regulating mitophagy and hormone resistance through the deacetylation of FOXO3 in EC, thereby providing valuable insights for new therapeutic strategies.

Impact of mutations in SARS-COV-2 spike on viral infectivity and antigenicity.

Since the outbreak of SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, the viral genome has acquired numerous mutations with the potential to alter the viral infectivity and antigenicity. Part of mutations in SARS-CoV-2 spike protein has conferred virus the ability to spread more quickly and escape from the immune response caused by the monoclonal neutralizing antibody or vaccination. Herein, we summarize the spatiotemporal distribution of mutations in spike protein, and present recent efforts and progress in investigating the impacts of those mutations on viral infectivity and antigenicity. As mutations continue to emerge in SARS-CoV-2, we strive to provide systematic evaluation of mutations in spike protein, which is vitally important for the subsequent improvement of vaccine and therapeutic neutralizing antibody strategies.

Identification of alternative splicing-derived cancer neoantigens for mRNA vaccine development.

Messenger RNA (mRNA) vaccines have shown great potential for anti-tumor therapy due to the advantages in safety, efficacy and industrial production. However, it remains a challenge to identify suitable cancer neoantigens that can be targeted for mRNA vaccines. Abnormal alternative splicing occurs in a variety of tumors, which may result in the translation of abnormal transcripts into tumor-specific proteins. High-throughput technologies make it possible for systematic characterization of alternative splicing as a source of suitable target neoantigens for mRNA vaccine development. Here, we summarized difficulties and challenges for identifying alternative splicing-derived cancer neoantigens from RNA-seq data and proposed a conceptual framework for designing personalized mRNA vaccines based on alternative splicing-derived cancer neoantigens. In addition, several points were presented to spark further discussion toward improving the identification of alternative splicing-derived cancer neoantigens.

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data.

MOTIVATION: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify CCIs from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity. RESULTS: Here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively. Powered by the flexible and easy-to-use software, DeepCCI can provide the one-stop solution to discover meaningful intercellular interactions and build CCI networks from scRNA-seq data. AVAILABILITY AND IMPLEMENTATION: The source code of DeepCCI is available online at https://github.com/JiangBioLab/DeepCCI.

Targeted inhibition of DHODH is synergistic with BCL2 blockade in HGBCL with concurrent MYC and BCL2 rearrangement.

High-grade B-cell lymphoma (HGBCL), the subtype of non-Hodgkin lymphoma, to be relapsed or refractory in patients after initial therapy or salvage chemotherapy. Dual dysregulation of MYC and BCL2 is one of the important pathogenic mechanisms. Thus, combined targeting of MYC and BCL2 appears to be a promising strategy. Dihydroorotate dehydrogenase (DHODH) is the fourth rate-limiting enzyme for the de novo biosynthesis of pyrimidine. It has been shown to be a potential therapeutic target for multiple diseases. In this study, the DHODH inhibitor brequinar exhibited growth inhibition, cell cycle blockade, and apoptosis promotion in HGBCL cell lines with MYC and BCL2 rearrangements. The combination of brequinar and BCL2 inhibitors venetoclax had a synergistic inhibitory effect on the survival of DHL cells through different pathways. Venetoclax could upregulate MCL-1 and MYC expression, which has been reported as a resistance mechanism of BCL2 inhibitors. Brequinar downregulated MCL-1 and MYC, which could potentially overcome drug resistance to venetoclax in HGBCL cells. Furthermore, brequinar could downregulate a broad range of genes, including ribosome biosynthesis genes, which might contribute to its anti-tumor effects. In vivo studies demonstrated synergetic tumor growth inhibition in xenograft models with brequinar and venetoclax combination treatment. These results provide preliminary evidence for the rational combination of DHODH and BCL2 blockade in HGBCL with abnormal MYC and BCL2.

Enabling AI-Generated Content for Gadolinium-Free Contrast-Enhanced Breast Magnetic Resonance Imaging.

BACKGROUND: There is increasing interest in utilizing AI-generated content for gadolinium-free contrast-enhanced breast MRI. PURPOSE: To develop a generative model for gadolinium-free contrast-enhanced breast MRI and evaluate the diagnostic utility of the generated scans. STUDY TYPE: Retrospective. POPULATION: Two hundred seventy-six women with 304 breast MRI examinations (49 ± 13 years, 243/61 for training/testing). FIELD STRENGTH/SEQUENCE: ZOOMit diffusion-weighted imaging (DWI), T1-weighted volumetric interpolated breath-hold examination (T1W VIBE), and axial T2 3D SPACE at 3.0 T. ASSESSMENT: A generative model was developed to generate contrast-enhanced scans using precontrast T1W VIBE and DWI images. The generated and real images were quantitatively compared using the structural similarity index (SSIM), mean absolute error (MAE), and Dice similarity coefficient. Three radiologists with 8, 5, and 5 years of experience independently rated the image quality and lesion visibility on AI-generated and real images within various subgroups using a five-point scale. Four breast radiologists, with 8, 8, 5, and 5 years of experience, independently and blindly interpreted four reading protocols: unenhanced MRI protocol alone and combined with AI-generated scans, abbreviated MRI protocol, and full-MRI protocol. STATISTICAL ANALYSIS: Results were assessed using t-tests and McNemar tests. Using pathology diagnosis as reference standard, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each reading protocol. A P value <0.05 was considered significant. RESULTS: In the test set, the generated images showed similarity to the real images (SSIM: 0.935 ± 0.047 [SD], MAE: 0.015 ± 0.012 [SD], and Dice coefficient: 0.726 ± 0.177 [SD]). No significant difference in lesion visibility was observed between real and AI-generated scans of the mass, non-mass, and benign lesion subgroups. Adding AI-generated scans to the unenhanced MRI protocol slightly improved breast cancer detection (sensitivity: 92.86% vs. 85.71%, NPV: 76.92% vs. 70.00%); achieved non-inferior diagnostic utility compared to the AB-MRI protocol and full-protocol (sensitivity: 92.86%, 95.24%; NPV: 75.00%, 81.82%). DATA CONCLUSION: AI-generated gadolinium-free contrast-enhanced breast MRI has potential to improve the sensitivity of unenhanced MRI in detecting breast cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

Achieving Dual Emission of Fluorescence and Phosphorescence from Anti-Kasha's Metal-Organic Halides for Information Encryption.

Luminescent materials typically emit their fluorescence or phosphorescence at a specific wavelength with different excitation energies via the so-called Kasha's rule. If fluorescence or phosphorescence emission via anti-Kasha's rule could be achieved, it will hold great promise for applications in many fields. In this work, we report the synthesis and characterization of new metal-organic halide materials with dual emission of efficient room-temperature phosphorescence and fluorescence, which obey anti-Kasha's rule. Here, three emitting metal-organic halides with formula [ZnX2(bidpe)] (X = Cl for 1, X = Br for 2, X = I for 3, bidpe = 4,4'-bis(imidazol-1-yl)diphenyl ether) were prepared and their photophysical properties were investigated. The complexes exhibit dual emission of fluorescence and phosphorescence via anti-Kasha's rule, and their RTP properties of resultant products are modulated by halide substitution synthesis. DFT calculations indicate that the singlet states exhibit a halide-ligand charge transfer (XLCT) character while the triplet states are dominated by the intraligand π-π* transitions. Furthermore, the multilevel information encryption and anticounterfeiting applications are developed by virtue of anti-Kasha's rule emission.

Suppressing the Thermal Quenching Effect via a Cluster Conformer in Copper(I)-Iodide Coordination Polymeric Phosphors for High-Power White LED Lighting.

High-power LED lighting is a crucial challenge due to the notorious thermal quenching (TQ) effect of traditional phosphors at high operating currents, which would result in poor device performance and hamper practical optoelectronic application. Herein, we demonstrate ligand engineering of a cubane- versus staircase-like [Cu4I4] conformer as a node in coordination polymers, which remarkably suppresses the TQ effect of cluster-based photoluminescence. For complex 1 (the formula [Cu4I4(bbimb)2]n) with the cubane-like [Cu4I4] conformer as a node, the metallophilicity interaction enables ultrabright triplet emission with a photoluminescence quantum yield over 82%, and the phonon-assisted detrapping process of excitons effectively suppresses the TQ effect in the wide temperature range. In contrast, the staircase-like [Cu4I4] conformer as a node in complex 2 (the formula [Cu4I4(bbtmb)2]n) exhibits a serious TQ effect over the investigated temperature. Phosphor-converted white LEDs (pc-wLEDs) were fabricated by integrating the cluster-based coordination polymers as a color converter, and their electroluminescence performances were investigated under high bias currents. The prototype pc-wLED device by incorporating the phosphor with the suppressed TQ effect exhibits a continuous rise in brightness under a high bias current of 300 mA. The results demonstrate that ligand engineering of the cluster conformer via suppressing the TQ effect proves efficient in designing an ideal color converter for high-power pc-wLED lighting.

Long- and Intermediate-Term Ambient Particulate Pollution Is Associated with Increased Osteoarthritis Risk: A Population-Based Prospective Analysis.

Recent studies found the intrusion and retention of exogenous fine particles into joints, but epidemiological data for long- and intermediate-term exposure associations are scare. Here, all urban working, retired employee, and rural residents (16.78 million) in Beijing from January 1, 2011 to December 31, 2019 were included to investigate the effects of long- and intermediate-term ambient particulate exposure on development of osteoarthritis. We identified 1,742,067 participants as first-visit patients with osteoarthritis. For each interquartile range increase in annual PM2.5 (23.32 µg/m3) and PM10 (23.92 µg/m3) exposure concentration, the pooled hazard ratios were respectively 1.238 (95% CI: 1.228, 1.249) and 1.178 (95% CI: 1.168, 1.189) for first osteoarthritis outpatient visits. Moreover, age at first osteoarthritis outpatient visits significantly decreased by 4.52 (95% CI: 3.45 to 5.40) days per µg/m3 for annual PM2.5 exposure at below 67.85 µg/m3. Finally, among the six constituents analyzed, black carbon appears to be the most important component associated with the association between PM2.5 exposure and the three osteoarthritis-related outcomes.

Analysis of the epidemic characteristics of common respiratory pathogens infection in children in a 3A special hospital.

OBJECTIVE: To analyze the epidemic characteristics of common respiratory tract infection pathogens in children with respiratory tract infection, and provide scientific basis for the prevention and control of respiratory tract infection. METHODS: A retrospective collection of clinical data was conducted on 11,538 children with respiratory tract infections at Luoyang Maternal and Child Health Hospital from December 2022 to November 2023. The types of respiratory tract infections, including upper and lower respiratory tract infections, as well as five respiratory pathogens: influenza A virus (influenza A), influenza B virus (influenza B virus, adenovirus (ADV), respiratory syncytial virus (RSV), and Mycoplasma pneumoniae (MP) infections, were analyzed and compared for different genders, ages, temperatures, and air quality in different months; And the changes of five pathogens in children with respiratory tract infections of different disease severity. RESULTS: From December 2022 to November 2023, a total of 11,538 children with respiratory infections were included in the analysis, including 6436 males and 5102 females, with an age of 4.92 ± 2.03 years. The proportion of upper respiratory tract infections is as high as 72.17%, and lower respiratory tract infections account for 27.83%. Among them, 2387 were positive for Flu A antigen, with a positive rate of 20.69%, 51 cases were positive for Flu B antigen, and the positive rate was 0.4%, 1296 cases were positive for adv antigen, with a positive rate of 11.23%, 868 cases were positive for RSV antigen, with a positive rate of 7.52%, 2481 cases were positive for MP IgM antibody or MP antigen, and the positive rate was 21.50%. Flu B in male children The infection rate of ADV and MP was higher than that of female children (p < 0.05); Among children in different age groups, the older the age, the older the Flu A The higher the infection rate of MP (p < 0.05), the higher the positive rate of RSV in children with younger age (p < 0.05). The positive rate of ADV in children aged 3-6 years and > 6 years was higher than that in children aged 0-3 years (p < 0.05); Flu A and MP are popular throughout the year, and the positive rate peaks during the period of temperature rise and air quality decline from February to March, and during the period of temperature drop and air quality index rise from August to November, The positive rate of RSV peaked after the turning point of temperature rise from March to April. The infection rate was higher during the period of sharp decline in air quality from March to May and sharp decline in temperature in November, The positive rate of ADV was higher at the turning point of temperature rise from February to March, and then the infection rate decreased. During the period of sharp temperature drop from August to November, the positive rate increased sharply, and the peak of infection occurred; As the disease worsens, The positive rates of Flu A, Flu B, RSV, MP and combined infection with more than two pathogens were all increased (p < 0.05). CONCLUSION: After the new coronavirus epidemic in 2022, Flu A and MP have the highest infection rate of respiratory pathogens in children, showing a peak growth in general, with epidemic characteristics changing with environmental temperature, air quality and seasons. The main disease type is upper respiratory tract infection, MP and adv infections were mainly in male children, Flu A, MP and ADV infections are more common in older children, RSV infection was more common in younger children; Flu A, Flu B, RSV and MP infection and the co infection of more than two pathogens may more easily lead to the occurrence of severe pneumonia.

The global patent landscape of emerging infectious disease monkeypox.

BACKGROUND: Monkeypox is an emerging infectious disease with confirmed cases and deaths in several parts of the world. In light of this crisis, this study aims to analyze the global knowledge pattern of monkeypox-related patents and explore current trends and future technical directions in the medical development of monkeypox to inform research and policy. METHODS: A comprehensive study of 1,791 monkeypox-related patents worldwide was conducted using the Derwent patent database by descriptive statistics, social network method and linear regression analysis. RESULTS: Since the 21st century, the number of monkeypox-related patents has increased rapidly, accompanied by increases in collaboration between commercial and academic patentees. Enterprises contributed the most in patent quantity, whereas the initial milestone patent was filed by academia. The core developments of technology related to the monkeypox include biological and chemical medicine. The innovations of vaccines and virus testing lack sufficient patent support in portfolios. CONCLUSIONS: Monkeypox-related therapeutic innovation is geographically limited with strong international intellectual property right barriers though it has increased rapidly in recent years. The transparent licensing of patent knowledge is driven by the merger and acquisition model, and the venture capital, intellectual property and contract research organization model. Currently, the patent thicket phenomenon in the monkeypox field may slow the progress of efforts to combat monkeypox. Enterprises should pay more attention to the sharing of technical knowledge, make full use of drug repurposing strategies, and promote innovation of monkeypox-related technology in hotspots of antivirals (such as tecovirimat, cidofovir, brincidofovir), vaccines (JYNNEOS, ACAM2000), herbal medicine and gene therapy.

DeepST: identifying spatial domains in spatial transcriptomics by deep learning.

Recent advances in spatial transcriptomics (ST) have brought unprecedented opportunities to understand tissue organization and function in spatial context. However, it is still challenging to precisely dissect spatial domains with similar gene expression and histology in situ. Here, we present DeepST, an accurate and universal deep learning framework to identify spatial domains, which performs better than the existing state-of-the-art methods on benchmarking datasets of the human dorsolateral prefrontal cortex. Further testing on a breast cancer ST dataset, we showed that DeepST can dissect spatial domains in cancer tissue at a finer scale. Moreover, DeepST can achieve not only effective batch integration of ST data generated from multiple batches or different technologies, but also expandable capabilities for processing other spatial omics data. Together, our results demonstrate that DeepST has the exceptional capacity for identifying spatial domains, making it a desirable tool to gain novel insights from ST studies.

A Prospective Study on Different Doses of Gammaglobulin Plus Aspirin in the Pediatric Kawasaki Disease and the Impacts on CRP and WBC Levels.

OBJECTIVE: To evaluate the efficacy of different doses of gammaglobulin combined with aspirin in treating pediatric Kawasaki disease and its impact on C-reactive protein (CRP) and white blood cell (WBC) levels. METHODS: A prospective study was conducted with 150 children (3groups) diagnosed with Kawasaki disease. Group A received a higher dose of intravenous gammaglobulin (2.5 g/kg) combined with aspirin, Group B received a standard dose of intravenous gammaglobulin (2 g/kg) combined with aspirin, and Group C received a lower dose of intravenous gammaglobulin (1 g/kg) combined with aspirin. All groups received oral aspirin therapy (30 mg/kg/day) for a standard duration. The time to symptom improvement, treatment efficacy, laboratory parameters, and adverse reactions were monitored and analyzed. RESULTS: Group B showed a shorter time to symptom relief compared to Groups A and C, particularly in fever reduction, mucosal congestion, cervical lymph node enlargement, and limb symptoms. The total effective rate was higher in Group B compared to Groups A and C. Group B showed improvements in WBC, CRP, ESR, and PLT levels. CONCLUSION: Standard-dose intravenous gammaglobulin combined with aspirin was more effective in treating pediatric Kawasaki disease compared to higher and lower doses. The treatment regimen in Group B resulted in shorter time to symptom relief, higher total effective rate, improved biochemical markers. Incidence of adverse reactions was similar among the three groups, demonstrating the safety of standard dosage.