A bibliometric and visual analysis of research trends and hotspots of familial hypertrophic cardiomyopathy: A review.

Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce sudden cardiac death. So, this paper summarized the current knowledge on FHCM, and displayed the analysis via bibliometrics method. The relevant literature on FHCM were screened searched via the Web of Science Core Collection database from 2012 to 2022. The literatures were was summarized and analyzed via the bibliometrics method analyzed via CiteSpace and VOSviewer according to topic categories, distribution of spatiotemporal omics and authors, as well as references. Since 2012, there are 909 research articles and reviews related to FHCM. The number of publication for the past 10 years have shown that the development of FHCM research has been steady, with the largest amount of literature in 2012. The most published papers were from the United States, followed by the United Kingdom and Italy. The University of London (63 papers) was the institution that published the most research articles, followed by Harvard University (45 papers) and University College London (45 papers). Keywords formed 3 clusters, focused on the pathogenesis of FHCM, the diagnosis of FHCM, FHCM complications, respectively. The bibliometric analysis and visualization techniques employed herein highlight key trends and focal points in the field, predominantly centered around FHCM's pathogenesis, diagnostic approaches, and its complications. These insights are instrumental in steering future research directions in this area.

Learning A Single Network for Robust Medical Image Segmentation with Noisy Labels.

Robust segmenting with noisy labels is an important problem in medical imaging due to the difficulty of acquiring high-quality annotations. Despite the enormous success of recent developments, these developments still require multiple networks to construct their frameworks and focus on limited application scenarios, which leads to inflexibility in practical applications. They also do not explicitly consider the coarse boundary label problem, which results in sub-optimal results. To overcome these challenges, we propose a novel Simultaneous Edge Alignment and Memory-Assisted Learning (SEAMAL) framework for noisy-label robust segmentation. It achieves single-network robust learning, which is applicable for both 2D and 3D segmentation, in both Set-HQ-knowable and Set-HQ-agnostic scenarios. Specifically, to achieve single-model noise robustness, we design a Memory-assisted Selection and Correction module (MSC) that utilizes predictive history consistency from the Prediction Memory Bank to distinguish between reliable and non-reliable labels pixel-wisely, and that updates the reliable ones at the superpixel level. To overcome the coarse boundary label problem, which is common in practice, and to better utilize shape-relevant information at the boundary, we propose an Edge Detection Branch (EDB) that explicitly learns the boundary via an edge detection layer with only slight additional computational cost, and we improve the sharpness and precision of the boundary with a thinning loss. Extensive experiments verify that SEAMAL outperforms previous works significantly.

Factors Impacting One-year Follow-up Visit Adherence after Bariatric Surgery in West China: A Mixed Methods Study.

PURPOSE: Quality follow-up (FU) is crucial after bariatric surgery. However, poor adherence after surgery is prevalent. This research aimed to explore the factors related to FU adherence after bariatric surgery in West China. MATERIALS AND METHODS: This study used a sequential explanatory mixed-methods research design. Participants (n = 177) were identified from the West China Hospital. Demographic information, disease profile, treatment information, and post-surgery FU information were obtained from the bariatric surgery database of the Division of Gastrointestinal Surgery of the West China Hospital. The survey data were analyzed using logistic regression. Semi-structured interviews with participants (n = 10) who had low adherence were conducted. The recording was transcribed verbatim and entered into qualitative data analysis software. Qualitative data were analyzed using a content analysis approach. RESULTS: Multiple logistic regression revealed that living in Chengdu (OR, 2.308), being employed (OR, 2.532), non-smoking (OR, 2.805), and having less than five years of obesity (OR, 2.480) were positive predictors of FU adherence within one year. Semi-structured interviews suggested that factors related to adherence to FU were lack of motivation, lack of opportunity, insufficient ability, and beliefs regarding consequences. CONCLUSION: Factors impacting one-year FU visit adherence after bariatric surgery include not only demographic and disease-related factors but also social and family factors. These results will provide evidence to support healthcare professionals in developing personalized postoperative FU management strategies.

Discovery and validation of anti-arthritic ingredients and mechanisms of Qingfu Juanbi Tang, a Chinese herbal formulation, on rheumatoid arthritis.

ETHNOPHARMACOLOGICAL RELEVANCE: Qingfu Juanbi Tang (QFJBT), a novel and improved Chinese herbal formulation, has surged in recent years for its potential in the therapy of rheumatoid arthritis (RA). Anti-arthritic effects and underlying molecular mechanisms of QFJBT have increasingly become a focal point in research. AIM OF THE STUDY: This study utilized network pharmacology, molecular docking, and experimental validation to elucidate effective ingredients and anti-arthritic mechanisms of QFJBT. MATERIALS AND METHODS: Targets associated with QFJBT and RA were identified from relevant databases and standardized using the Uniprot for gene nomenclature. A "QFJBT-ingredient-target network" and a "Venn diagram of QFJBT and RA targets" were created from the data. The overlap in the Venn diagram highlighted potential targets of QFJBT in the treatment of RA. These targets were subjected to PPI network, GO, and KEGG pathway analysis. The findings were subsequently confirmed through molecular docking and pharmacological experiments to propose the mechanism of action of QFJBT. RESULTS: The study identified 236 active ingredients in QFJBT, with 120 predicted to be effective against RA. Molecular docking showed high binding affinity of key targets (JUN, PTGS2, and TNF-α) with bioactive compounds (rhein, sinomenine, calycosin, and paeoniflorin) of QFJBT. Pharmacodynamic evaluation demonstrated the effects of QFJBT at the dose of 4.56 g/kg in ameliorating symptoms of AIA rats and in reducing levels of JUN, PTGS2, and TNF-α in synovial tissues. In vitro studies further exhibited that rhein, paeoniflorin, sinomenine, calycosin, and QFJBT-containing serum significantly inhibited abnormal proliferation of RA fibroblast-like synoviocytes. Interestingly, rhein and paeoniflorin specifically decreased p-JUN/JUN expression and TNF-α release, respectively, while sinomenine and calycosin selectively increased PTGS2 expression. Consistently, QFJBT-containing serum demonstrated similar effects as those active ingredients identified in QFJBT did. CONCLUSIONS: QFJBT, QFJBT-containing serum, and its active ingredients (rhein, paeoniflorin, sinomenine, and calycosin) suppress inflammatory responses in RA. Anti-arthritic effects of QFJBT and its active ingredients are likely linked to their modulatory impact on identified hub targets.

Immune Characteristic Genes and Neutrophil Immune Transformation Studies in Severe COVID-19.

As a disease causing a global pandemic, the progression of symptoms to severe disease in patients with COVID-19 often has adverse outcomes, but research on the immunopathology of COVID-19 severe disease remains limited. In this study, we used mRNA-seq data from the peripheral blood of COVID-19 patients to identify six COVID-19 severe immune characteristic genes (FPR1, FCGR2A, TLR4, S100A12, CXCL1, and L TF), and found neutrophils to be the critical immune cells in COVID-19 severe disease. Subsequently, using scRNA-seq data from bronchoalveolar lavage fluid from COVID-19 patients, neutrophil subtypes highly expressing the S100A family were found to be located at the end of cellular differentiation and tended to release neutrophil extracellular traps. Finally, it was also found that alveolar macrophages, macrophages, and monocytes with a high expression of COVID-19 severe disease immune characteristic genes may influence neutrophils through intercellular ligand-receptor pairs to promote neutrophil extracellular trap release. This study provides immune characteristic genes, critical immune pathways, and immune cells in COVID-19 severe disease, explores intracellular immune transitions of critical immune cells and pit-induced intercellular communication of immune transitions, and provides new biomarkers and potential drug targets for the treatment of patients with COVID-19 severe disease.

Bibliometric and visualized analysis of type 2 diabetic osteoporosis from 2013 to 2022.

Type 2 diabetic osteoporosis (T2DOP) has received increasing attention from researchers. In this study, a total of 453 publications related to T2DOP from 2013 to 2022 were analyzed using bibliometric and visual analysis to identify the research trends and research hotspots in the field of T2DOP. PURPOSE: The objective of this study was to conduct a comprehensive bibliometric analysis of T2DOP-related publications from 2013 to 2022 to determine global research trends in T2DOP in terms of number of publications, countries/regions, institutions, authors, journals, funding agencies, and keywords. METHODS: All data were collected from the Web of Science Core Collection (WoSCC). All original research publications regarding T2DOP from 2013 to 2022 were retrieved. VOSviewer and Microsoft Office Excel were used to conduct the bibliometric and visual analysis. RESULTS: From 2013 to 2022, 515 relevant publications were published, with a peak in 2022 in the annual number of publications. The countries leading the research were USA and China. Sugimoto was the most influential authors. Capital Medical University and Nanjing Medical University were the most prolific institutions. Osteoporosis International was the most productive journal concerning T2DOP research. National Natural Science Foundation of China was the primary funding source for this research area. "Bone-mineral density", "fracture risk", and "postmenopausal women" were the most high-frequency keywords over the past 10 years. CONCLUSION: This was the first bibliometric study of diabetes mellitus and osteoporosis to exclusively examine type 2 diabetes mellitus. Our findings would provide guidance to understand the research frontiers and hot directions in the near future.

How dyadic appraisal moderate the association between dyadic coping and diabetes management efficacy.

To explore the moderating role of dyadic appraisal in the association between dyadic coping and diabetes management efficacy. Two hundred seventy six middle-aged and older couple pairs with one spouse who had diabetes were recruited from 14 community healthcare centers across Guangzhou. The moderating role of dyadic appraisal was investigated using the actor-partner interdependence moderation model. When both couples considered diabetes to be a shared condition, statistically-significant associations were found between patients' negative (ß = -22.7, p = 0.008) and neutral behaviors (ß = 13.6, p = 0.017), plus spouses' positive behaviors (ß = 22.8, p = 0.009) on their own diabetes management efficacy, respectively (i.e. actor effects); as well as between spouses' positive (ß = 16.8, p = 0.028), negative (ß = -28.5, p < 0.001), and neutral behaviors (ß = 16.9, p = 0.006) on patient's diabetes management efficacy (i.e. partner effects). Dyadic appraisal moderates the association between dyadic coping and diabetes management efficacy.

Heavy metal contamination in duck eggs from a mercury mining area, southwestern China.

Objective: Mercury (Hg) contamination in the environment around mercury mines is often accompanied by heavy metal contamination. Methods: Here, we determined concentrations of chromium (Cr), zinc (Zn), strontium (Sr), barium (Ba), and lead (Pb) in duck eggs from a Hg mining area in Southwest China to assess the contamination and health risk. Results: Duck eggs obtained from the mining area exhibit higher concentrations of Cr, Zn, Sr, Ba, and Pb compared to those from the background area, with egg yolks containing higher metal levels than egg whites. Specifically, the mean Cr, Zn, Sr, Ba, and Pb concentrations of duck eggs from the Hg mining area are 0.38, 63.06, 4.86, 10.08, and 0.05 µg/g, respectively, while those from the background area are only 0.21, 24.65, 1.43, 1.05, and 0.01 µg/g. Based on the single-factor contamination index and health risk assessment, heavy metal contamination in duck eggs poses an ecological risk and health risk. Conclusion: This study provides important insight into heavy metal contamination in duck eggs from Hg mining areas.

Robust Model Watermarking for Image Processing Networks via Structure Consistency.

The intellectual property of deep networks can be easily "stolen" by surrogate model attack. There has been significant progress in protecting the model IP in classification tasks. However, little attention has been devoted to the protection of image processing models. By utilizing consistent invisible spatial watermarks, the work [1] first considered model watermarking for deep image processing networks and demonstrated its efficacy in many downstream tasks. Its success depends on the hypothesis that if a consistent watermark exists in all prediction outputs, that watermark will be learned into the attacker's surrogate model. However, when the attacker uses common data augmentation attacks (e.g., rotate, crop, and resize) during surrogate model training, it will fail because the underlying watermark consistency is destroyed. To mitigate this issue, we propose a new watermarking methodology, "structure consistency", based on which a new deep structure-aligned model watermarking algorithm is designed. Specifically, the embedded watermarks are designed to be aligned with physically consistent image structures, such as edges or semantic regions. Experiments demonstrate that our method is more robust than the baseline in resisting data augmentation attacks. Besides that, we test the generalization ability and robustness of our method to a broader range of adaptive attacks.

Effects of haemodiafiltration or haemofiltration compared with haemodialysis on prognosis in patients with end-stage renal disease: protocol an updated systematic review and meta-analysis of randomised trials with trial sequential analysis.

INTRODUCTION: Haemodialysis is the most common treatment option for patients with life-sustaining end-stage kidney disease (ESKD). In recent years, haemodiafiltration or haemofiltration has been widely used in patients with ESKD, and there are still conflicting findings as to whether both are superior to traditional haemodialysis. This systematic review and meta-analysis were designed to determine whether haemodiafiltration or haemofiltration is more effective than haemodialysis in reducing all-cause mortality risk in patients with ESKD. METHODS AND ANALYSIS: We will perform a systematic PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library and Scopus search, including studies published before September 2023. Randomised controlled trials will be included exploring the effects of haemodiafiltration or haemofiltration compared with haemodialysis on prognosis in patients with ESKD. Outcomes of interest include all-cause mortality, cardiovascular events, dialysis adequacy and adverse effects. The Cochrane Collaboration tools (ROB-2) will assess the bias risk. Available data will be used to calculate effect sizes. Heterogeneity between studies will be evaluated with I2. The trial sequential analysis will be used to eliminate false-positive results. The certainty of the evidence will be assessed using Grading of Recommendations, Assessment, Development and Evaluation criteria. ETHICS AND DISSEMINATION: This systematic review and meta-analysis was deemed exempt from ethics review. Results will be disseminated through publication in peer-reviewed journals and research conferences. PROSPERO REGISTRATION NUMBER: CRD42023464509.

A Review of Chloride Penetration of Recycled Concrete with Enhancement Treatment and Service Life Prediction.

The application of recycled coarse aggregate (RA) in structural concrete can save non-renewable resources and reduce land occupation. Developing comprehensive knowledge of chloride penetration and service life modeling of recycled coarse aggregate concrete (RAC) is a prerequisite for practice. However, compared with the natural aggregate concrete (NAC), the inferior durability performance, especially chloride penetration resistance, of RAC hinders its application in structural concrete. Therefore, many RAC performance enhancement methods have been proposed. This paper presents a holistic review focused on the chloride penetration of RAC with/without enhancement methods and service life prediction. The current RAC performance enhancement methods are introduced. The improvement effect of the corresponding enhancement methods on the chloride penetration resistance of RAC are discussed and analyzed in turn. Based on the reviewed data on the chloride diffusion coefficient, the modification efficiencies of assorted enhancement methods are summarized. With the hope of promoting RAC application in structural concrete, the current literature on chloride-ingress-based service life prediction for RAC is also overviewed. In addition, the typical influencing factors on chloride transport properties are also discussed, i.e., RA quality. It can be concluded that enhancement techniques can effectively improve the chloride penetration resistance of RAC. The old mortar enhancement or removal methods can improve the chloride penetration resistance by 15-30%, depending on the specific treatment measures. The modification efficiency of the modifier material depends on the specific type and content of the incorporated substance, which ranges from approximately 5% to 95%. The estimated service life of RAC structures decreases with the increasing RA replacement ratio. Finally, concluding remarks are provided concerning future research on the chloride transport behavior of RAC.

Broad-spectrum hydrocarbon-degrading microbes in the global ocean metagenomes.

Understanding the diversity and functions of hydrocarbon-degrading microorganisms in marine environments is crucial for both advancing knowledge of biogeochemical processes and improving bioremediation methods. In this study, we leveraged nearly 20,000 metagenome-assembled genomes (MAGs), recovered from a wide array of marine samples across the global oceans, to map the diversity of aerobic hydrocarbon-degrading microorganisms. A broad bacterial diversity was uncovered, with a notable preference for degrading aliphatic hydrocarbons over aromatic ones, primarily within Proteobacteria and Actinobacteriota. Three types of broad-spectrum hydrocarbon-degrading bacteria were identified for their ability to degrade various hydrocarbons and possession of multiple copies of hydrocarbon biodegradation genes. These bacteria demonstrate extensive metabolic versatility, aiding their survival and adaptability in diverse environmental conditions. Evidence of gene duplication and horizontal gene transfer in these microbes suggested a potential enhancement in the diversity of hydrocarbon-degrading bacteria. Positive correlations were observed between the abundances of hydrocarbon-degrading genes and environmental parameters such as temperature (-5 to 35 °C) and salinity (20 to 42 PSU). Overall, our findings offer valuable insights into marine hydrocarbon-degrading microorganisms and suggest considerations for selecting microbial strains for oil pollution remediation.

BMX deletion mitigates neuroinflammation induced by retinal ischemia/reperfusion through modulation of the AKT/ERK/STAT3 signaling cascade.

Aims: Retinal ischemia/reperfusion (I/R) injury is implicated in the etiology of various ocular disorders. Prior research has demonstrated that bone marrow tyrosine kinase on chromosome X (BMX) contributes to the advancement of ischemic disease and inflammatory reactions. Consequently, the current investigation aims to evaluate BMX's impact on retinal I/R injury and clarify its implied mechanism of action. Main methods: This study utilized male and female systemic BMX knockout (BMX-/-) mice to conduct experiments. The utilization of Western blot assay and immunofluorescence labeling techniques was employed to investigate variations in the expression of protein and tissue localization. Histomorphological changes were observed through H&E staining and SD-OCT examination. Visual function changes were assessed through electrophysiological experiments. Furthermore, apoptosis in the retina was identified using the TUNEL assay, as well as the ELISA technique, which has been utilized to determine the inflammatory factors level. Key findings: Our investigation results revealed that the knockdown of BMX did not yield a significant effect on mouse retina. In mice, BMX knockdown mitigated the negative impact of I/R injury on retinal tissue structure and visual function. BMX knockdown effectively reduced apoptosis, suppressed inflammatory responses, and decreased inflammatory factors subsequent to I/R injury. The outcomes of the current investigation revealed that BMX knockdown partially protected the retina through downregulating phosphorylation of AKT/ERK/STAT3 pathway. Significance: Our investigation showed that BMX-/- reduces AKT, ERK, and STAT3 phosphorylation, reducing apoptosis and inflammation. Thus, this strategy protected the retina from structural and functional damage after I/R injury.

Transcriptome-based analysis reveals a crucial role of the 20E/HR3 pathway in the diapause of Pieris rapae.

Pieris rapae is among the most damaging pests globally, and diapause makes it highly resistant to environmental stresses, playing a crucial role in the survival and reproduction of P. rapae while exacerbating the challenges of pest management and control. However, the mechanisms of its diapause regulation remain poorly understood. This research used RNA sequencing to profile the transcriptomes of three diapause phases (induction and preparation, initiation, maintenance) and synchronous nondiapause phases in P. rapae. During each comparison phase, 759, 1045, and 4721 genes were found to be differentially expressed. Among these, seven clock genes and seven pivotal hormone synthesis and metabolism genes were identified as having differential expression patterns in diapause type and nondiapause type. The weighted gene co-expression network analysis (WGCNA) revealed the red and blue modules as pivotal for diapause initiation, while the grey module was identified to be crucial to diapause maintenance. Meanwhile, the hub genes HDAC11, METLL16D, Dyw-like, GST, and so on, were identified within these hub modules. Moreover, an ecdysone downstream nuclear receptor gene, HR3, was found to be a shared transcription factor across all three phases. RNA interference of HR3 resulted in delayed pupal development, indicating its involvement in regulating pupal dipause in P. rapae. The further hormone assays revealed that the 20-hydroxyecdysone (20E) titer in diapause type pupae was lower than that in nondiapause type pupae, which exhibited a similar trend to HR3. When 20E was injected into diapause pupae, the HR3 expression levels were improved, and the pupal diapause were broken. These results indicate that the 20E/HR3 pathway is a critical pathway for the diapause regulation of P. rapae, and perturbing this pathway by ecdysone treatment or RNAi would result in the disruption of diapause. These findings provide initial insights into the molecular mechanisms of P. rapae diapause and suggest the potential use of ecdysone analogs and HR3 RNAi pesticides, which specifically target to diapause, as a means of pest control in P. rapae.

Prevalence of depressive tendencies among college students and the influence of attributional styles on depressive tendencies in the post-pandemic era.

Introduction: Depression symptoms are prevalent globally, including China, with a notable impact on college students. This study aims to not only estimate the prevalence of depressive tendencies and attributional styles among college students in the post-pandemic era but also explore the relationship between the two factors. The findings of this study can provide new insights into early intervention and support services for individuals exhibiting tendencies toward depression. Methods: The survey was administered to college students from various academic backgrounds at a specific university in southern Jiangxi Province by employing two scales to investigate depressive tendencies and attributional styles. Depressive tendency was evaluated using the Patient Health Questionnaire-9 (PHQ-9), while the attributional styles were assessed using the Multidimensional-Multiattributional Causality Scale (MMCS). Univariate analysis and multiple logistic regressions were conducted to identify the related factors of depressive tendency. Results: A relatively high (48.9%) prevalence of depression among college students was found in this study. College students with higher grades (OR = 1.574, 95%CI: 1.369-1.810), profession of medicine and allied health sciences (OR = 1.779, 95%CI: 1.203-2.629), experiencing higher study stress (OR = 2.006, 95%CI: 1.601-2.514), and having poor physical condition (OR = 1.527, 95%CI: 1.247-1.869) were identified as risk factors for depressive tendency. The correlation between higher grades and increased learning pressure, coupled with poorer physical condition, heightens the vulnerability of college students to depression. Moreover, the more they attribute these experiences to achievement effort (OR = 0.897, 95%CI: 0.828-0.972), achievement ability (OR = 0.903, 95%CI: 0.838-0.972), and affiliation context (OR = 0.919, 95%CI: 0.860-0.982), the less likely they are to develop depression. Conclusion: In the group of college students, especially those in higher grades, profession of medicine and allied health sciences or experiencing high learning pressure and poor physical condition, emphasizing the significance of their mental well-being becomes crucial. Offering suitable support and assistance is essential. Additionally, fostering the cultivation of positive attributional and coping strategies by attributing difficulties to controllable factors and instilling a belief in their ability to overcome challenges can help reduce the risk of depression.

Chloramphenicol Binding Sites of Acinetobacter baumannii Chloramphenicol Acetyltransferase CatB8.

Acinetobacter baumannii is a multidrug-resistant pathogen that has become one of the most challenging pathogens in global healthcare. Several antibiotic-resistant genes, including catB8, have been identified in the A. baumannii genome. CatB8 protein, one of the chloramphenicol acetyltransferases (Cats), is encoded by the catB8 gene. Cats can convert chloramphenicol (chl) to 3-acetyl-chl, leading to bacterial resistance to chl. Here, we present the high-resolution cocrystal structure of CatB8 with chl. The structure that we resolved showed that each monomer of CatB8 binds to four chl molecules, while its homologous protein only binds to one chl molecule. One of the newly discovered chl binding site overlaps with the site of another substrate, acetyl-CoA. Through structure-based biochemical analyses, we identified key residues for chl recruiting and acetylation of chl in CatB8. Our work is of significant importance for understanding the drug resistance of A. baumannii and the effectiveness of antibiotic treatment.

A Comprehensive Study of the Effects by Sequence Truncation within Inverted Terminal Repeats (ITRs) on the Productivity, Genome Packaging, and Potency of AAV Vectors.

One of the primary challenges in working with adeno-associated virus (AAV) lies in the inherent instability of its inverted terminal repeats (ITRs), which play vital roles in AAV replication, encapsidation, and genome integration. ITRs contain a high GC content and palindromic structure, which occasionally results in truncations and mutations during plasmid amplification in bacterial cells. However, there is no thorough study on how these alterations in ITRs impact the ultimate AAV vector characteristics. To close this gap, we designed ITRs with common variations, including a single B, C, or D region deletion at one end, and dual deletions at both ends of the vector genome. These engineered ITR-carrying plasmids were utilized to generate AAV vectors in HEK293 cells. The crude and purified AAV samples were collected and analyzed for yield, capsid DNA-filled percentage, potency, and ITR integrity. The results show that a single deletion had minor impact on AAV productivity, packaging efficiency, and in vivo potency. However, deletions on both ends, except A, showed significant negative effects on the above characteristics. Our work revealed the role of ITR regions, A, B, C, and D for AAV production and DNA replication, and proposes a new strategy for the quality control of ITR-bearing plasmids and final AAV products.

Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields.

Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D generation methods are limited to producing 3D objects with simple geometries and dreamlike styles that lack realism. In this work, we present Text2NeRF, which is able to generate a wide range of 3D scenes with complicated geometric structures and high-fidelity textures purely from a text prompt. To this end, we adopt NeRF as the 3D representation and leverage a pre-trained text-to-image diffusion model to constrain the 3D reconstruction of the NeRF to reflect the scene description. Specifically, we employ the diffusion model to infer the text-related image as the content prior and use a monocular depth estimation method to offer the geometric prior. Both content and geometric priors are utilized to update the NeRF model. To guarantee textured and geometric consistency between different views, we introduce a progressive scene inpainting and updating strategy for novel view synthesis of the scene. Our method requires no additional training data but only a natural language description of the scene as the input. Extensive experiments demonstrate that our Text2NeRF outperforms existing methods in producing photo-realistic, multi-view consistent, and diverse 3D scenes from a variety of natural language prompts. Our code and model will be available upon acceptance.

Sirpα on tumor-associated myeloid cells restrains antitumor immunity in colorectal cancer independent of its interaction with CD47.

Immunosuppressive myeloid cells hinder immunotherapeutic efficacy in tumors, but the precise mechanisms remain undefined. Here, by performing single-cell RNA sequencing in colorectal cancer tissues, we found tumor-associated macrophages and granulocytic myeloid-derived suppressor cells increased most compared to their counterparts in normal tissue and displayed the highest immune-inhibitory signatures among all immunocytes. These cells exhibited significantly increased expression of immunoreceptor tyrosine-based inhibitory motif-bearing receptors, including SIRPA. Notably, Sirpa-/- mice were more resistant to tumor progression than wild-type mice. Moreover, Sirpα deficiency reprogramed the tumor microenvironment through expansion of TAM_Ccl8hi and gMDSC_H2-Q10hi subsets showing strong antitumor activity. Sirpa-/- macrophages presented strong phagocytosis and antigen presentation to enhance T cell activation and proliferation. Furthermore, Sirpa-/- macrophages facilitated T cell recruitment via Syk/Btk-dependent Ccl8 secretion. Therefore, Sirpα deficiency enhances innate and adaptive immune activation independent of expression of CD47 and Sirpα blockade could be a promising strategy to improve cancer immunotherapy efficacy.