SCAR: Single-cell and Spatially-resolved Cancer Resources.

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.

SCAN: Spatiotemporal Cloud Atlas for Neural cells.

The nervous system is one of the most complicated and enigmatic systems within the animal kingdom. Recently, the emergence and development of spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) technologies have provided an unprecedented ability to systematically decipher the cellular heterogeneity and spatial locations of the nervous system from multiple unbiased aspects. However, efficiently integrating, presenting and analyzing massive multiomic data remains a huge challenge. Here, we manually collected and comprehensively analyzed high-quality scRNA-seq and ST data from the nervous system, covering 10 679 684 cells. In addition, multi-omic datasets from more than 900 species were included for extensive data mining from an evolutionary perspective. Furthermore, over 100 neurological diseases (e.g. Alzheimer's disease, Parkinson's disease, Down syndrome) were systematically analyzed for high-throughput screening of putative biomarkers. Differential expression patterns across developmental time points, cell types and ST spots were discerned and subsequently subjected to extensive interpretation. To provide researchers with efficient data exploration, we created a new database with interactive interfaces and integrated functions called the Spatiotemporal Cloud Atlas for Neural cells (SCAN), freely accessible at http://47.98.139.124:8799 or http://scanatlas.net. SCAN will benefit the neuroscience research community to better exploit the spatiotemporal atlas of the neural system and promote the development of diagnostic strategies for various neurological disorders.

PREDICTING VISUAL OUTCOME AFTER SURGERY IN PATIENTS WITH IDIOPATHIC EPIRETINAL MEMBRANE USING A NOVEL CONVOLUTIONAL NEURAL NETWORK.

PURPOSE: To develop a deep convolutional neural network that enables the prediction of postoperative visual outcomes after epiretinal membrane surgery based on preoperative optical coherence tomography images and clinical parameters to refine surgical decision making. METHODS: A total of 529 patients with idiopathic epiretinal membrane who underwent standard vitrectomy with epiretinal membrane peeling surgery by two surgeons between January 1, 2014, and June 1, 2020, were enrolled. The newly developed Heterogeneous Data Fusion Net was introduced to predict postoperative visual acuity outcomes (improvement ≥2 lines in Snellen chart) 12 months after surgery based on preoperative cross-sectional optical coherence tomography images and clinical factors, including age, sex, and preoperative visual acuity. The predictive accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of the convolutional neural network model were evaluated. RESULTS: The developed model demonstrated an overall accuracy for visual outcome prediction of 88.68% (95% CI, 79.0%-95.7%) with an area under the receiver operating characteristic curve of 97.8% (95% CI, 86.8%-98.0%), sensitivity of 87.0% (95% CI, 67.9%-95.5%), specificity of 92.9% (95% CI, 77.4%-98.0%), precision of 0.909, recall of 0.870, and F1 score of 0.889. The heatmaps identified the critical area for prediction as the ellipsoid zone of photoreceptors and the superficial retina, which was subjected to tangential traction of the proliferative membrane. CONCLUSION: The novel Heterogeneous Data Fusion Net demonstrated high accuracy in the automated prediction of visual outcomes after weighing and leveraging multiple clinical parameters, including optical coherence tomography images. This approach may be helpful in establishing personalized therapeutic strategies for epiretinal membrane management.

Prediction of treatment outcome in neovascular age-related macular degeneration using a novel convolutional neural network.

While prognosis and risk of progression are crucial in developing precise therapeutic strategy in neovascular age-related macular degeneration (nAMD), limited predictive tools are available. We proposed a novel deep convolutional neural network that enables feature extraction through image and non-image data integration to seize imperative information and achieve highly accurate outcome prediction. The Heterogeneous Data Fusion Net (HDF-Net) was designed to predict visual acuity (VA) outcome (improvement ≥ 2 line or not) at 12th months after anti-VEGF treatment. A set of pre-treatment optical coherence tomography (OCT) image and non-image demographic features were employed as input data and the corresponding 12th-month post-treatment VA as the target data to train, validate, and test the HDF-Net. This newly designed HDF-Net demonstrated an AUC of 0.989 (95% CI 0.970-0.999), accuracy of 0.936 [95% confidence interval (CI) 0.889-0.964], sensitivity of 0.933 (95% CI 0.841-0.974), and specificity of 0.938 (95% CI 0.877-0.969). By simulating the clinical decision process with mixed pre-treatment information from raw OCT images and numeric data, HDF-Net demonstrated promising performance in predicting individualized treatment outcome. The results highlight the potential of deep learning to simultaneously process a broad range of clinical data to weigh and leverage the complete information of the patient. This novel approach is an important step toward real-world personalized therapeutic strategy for typical nAMD.

Curcin C inhibit osteosarcoma cell line U2OS proliferation by ROS induced apoptosis, autophagy and cell cycle arrest through activating JNK signal pathway.

Osteosarcoma is a kind of primary bone malignant tumors. Its cure rate has been stagnant in the past decade years. Curcin C belongs to type I ribosome inactivating proteins, extracted from the cotyledons of post-germinated Jatropha curcas seeds. It can inhibit the proliferation of several tumor lines including U2OS cells with extraordinary efficiency. The treated U2OS cells were arrested in both S and G2/M phase, showed typical apoptosis morphological characteristic, formed autophagosomes and increase the ratio of LC3II to LC3I. Meanwhile, the level of ROS in the treated cells was found increasing significantly, with the change of mitochondrial membrane potential and decreased antioxidant enzyme activities. The application of ROS scavenger NAC not only significantly inhibited the toxicity of Curcin C but also prevented the happen of apoptosis and autophagy to some extent. These results suggested that Curcin C may function through ROS pathway. In addition, the Curcin C treatment could activate JNK and inhibit ERK signal pathway. Sp600125, an inhibitor of JNK signaling pathway, can prevent subsequent apoptosis and autophagy events, suggesting that JNK pathway was at least one of the pathways of Curcin C action. Moreover, the relevant including antagonistic among autophagy, apoptosis and cell cycle arresting induced by Curcin C also was found. In summary, it can be speculated that Curcin C may induce S, G2/M phase arrest, apoptosis and autophagy of human osteosarcoma U2OS cells through activating JNK signal pathway and blocking ERK signal pathway by promoting ROS accumulation in cell, thus finally reflected in the effect of inhibiting tumor cell proliferation.

A novel series of benzothiazepine derivatives as tubulin polymerization inhibitors with anti-tumor potency.

In this work, a series of diaryl benzo[b][1,4]thiazepine derivatives D1-D36 were synthesized and screened as tubulin polymerization inhibitors with anti-tumor potency. They were designed by introducing the seven-member ring benzothiazepine as the linker for CA-4 modification for the first time. Among them, the hit compound D8 showed potential on inhibiting the growth of several cancer cell lines (IC50 values: 1.48 µM for HeLa, 1.47 µM for MCF-7, 1.52 µM for HT29 and 1.94 µM for A549), being comparable with the positive controls Colchicine and CA-4P. The calculated IC50 value of D8 as an tubulin polymerization inhibitor was 1.20 µM. The results of the flow cytometry assay revealed that D8 could induce the mitotic catastrophe and the death of living cancer cells. D8 also indicated the anti-vascular activity. The possible binding pattern was implied by docking simulation, inferring the possibility of introducing interactions with the nearby tubulin chain. Since the novel structural trial has been conducted with preliminary discussion, this work might stimulate new ideas in further modification of tubulin-related anti-cancer agents and therapeutic approaches.

Design and Evaluation of LYSO/SiPM LIGHTENING PET Detector with DTI Sampling Method.

Positron emission tomography (PET) has a wide range of applications in the treatment and prevention of major diseases owing to its high sensitivity and excellent resolution. However, there is still much room for optimization in the readout circuit and fast pulse sampling to further improve the performance of the PET scanner. In this work, a LIGHTENING® PET detector using a 13 × 13 lutetium-yttrium oxyorthosilicate (LYSO) crystal array read out by a 6 × 6 silicon photomultiplier (SiPM) array was developed. A novel sampling method, referred to as the dual time interval (DTI) method, is therefore proposed to realize digital acquisition of fast scintillation pulse. A semi-cut light guide was designed, which greatly improves the resolution of the edge region of the crystal array. The obtained flood histogram shown that all the 13 × 13 crystal pixels can be clearly discriminated. The optimum operating conditions for the detector were obtained by comparing the flood histogram quality under different experimental conditions. An average energy resolution (FWHM) of 14.3% and coincidence timing resolution (FWHM) of 972 ps were measured. The experimental results demonstrated that the LIGHTENING® PET detector achieves extremely high resolution which is suitable for the development of a high performance time-of-flight PET scanner.

A tuber mustard AP2/ERF transcription factor gene, BjABR1, functioning in abscisic acid and abiotic stress responses, and evolutionary trajectory of the ABR1 homologous genes in Brassica species.

The AP2/ERF superfamily of transcription factors is one of the largest transcription factor families in plants and plays an important role in plant development processes and stress responses. In this study, BjABR1, an AP2/ERF superfamily gene, from tuber mustard (Brassica juncea var. tumida Tsen et Lee), sharing high amino acid sequence similarity with the AtABR1 (Arabidopsis thaliana AP2-like abscisic acid repressor 1) gene, were performed functional research, and the ABR1 homologous genes in Brassica species were identified and performed phylogenetic analysis. The promoter sequence of BjABR1 contained many phytohormone- and stress-related cis-elements; ABA (abscisic acid) and abiotic stresses can induce BjABR1 expression in tuber mustard; overexpression of BjABR1 in Arabidopsis can alleviate plant sensitivity to ABA and salt and osmotic stresses, and the alleviation may be due to changes in stress/ABA-induced gene expression. These results indicated that BjABR1 functions in ABA and abiotic stress responses. By BLAST searches against the genome database of five Brassica species (three diploids, B. rapa, B. nigra, and B. oleracea, and two allotetraploid, B. juncea and B. napus) using the protein sequence of AtABR1, 3, 3, 3, 6, and 5 ABR1 homologous genes in B. nigra, B. rapa, B. oleracea, B. juncea, and B. napus were identified, respectively, and they shared high sequence similarity. By sequence analysis, annotation mistakes of the protein-coding regions of two ABR1 homologous genes, GSBRNA2T00134741001 and BjuB007684, were found and corrected. Then, the evolution analysis of these ABR1 homologous genes showed that the ancestor of the three diploid species had three ABR1 homologous genes and each diploid inherited all the three genes from their ancestor; then, allotetraploid B. juncea inherited all the six genes from B. rapa and B. nigra with no gene lost, while allotetraploid B. napus inherited all the three genes from B. oleracea and two genes from B. rapa with one gene lost, indicating that ABR1 homologous genes possessed greater hereditary conservation in Brassica species. The ABR1 homologous genes between B. rapa and B. oleracea shared much higher sequence similarity compared to that of B. nigra in diploid species, indicating that ABR1 homologous genes in B. nigra had experienced more rapid evolution, and B. rapa and B. oleracea may share closer relationship compared to B. nigra. Moreover, the spatial and temporal expression analysis of six ABR1 homologous genes of tuber mustard showed that they possessed different expression models. These results imply that ABR1 homologous genes are important to Brassica plants, and they may possess similar function in ABA and abiotic stress responses but play a role in different tissues and growing stages of plant. This study will provide the foundation to the functional research of ABR1 homologous genes in the Brassica species and help to reveal and understand the evolution mechanisms of Brassica species.

Identification of circularRNAs and their targets in Gossypium under Verticillium wilt stress based on RNA-seq.

Circular RNAs (circRNAs), a class of recently discovered non-coding RNAs, play a role in biological and developmental processes. A recent study showed that circRNAs exist in plants and play a role in their environmental stress responses. However, cotton circRNAs and their role in Verticillium wilt response have not been identified up to now. In this study, two CSSLs (chromosome segment substitution lines) of G.barbadense introgressed into G. hirsutum, CSSL-1 and CSSL-4 (a resistant line and a susceptible line to Verticillium wilt, respectively), were inoculated with V. dahliae for RNA-seq library construction and circRNA analysis. A total of 686 novel circRNAs were identified. CSSL-1 and CSSL-4 had similar numbers of circRNAs and shared many circRNAs in common. However, CSSL-4 differentially expressed approximately twice as many circRNAs as CSSL-1, and the differential expression levels of the common circRNAs were generally higher in CSSL-1 than in CSSL-4. Moreover, two C-RRI comparisons, C-RRI-vs-C-RRM and C-RRI-vs-C-RSI, possessed a large proportion (approximately 50%) of the commonly and differentially expressed circRNAs. These results indicate that the differentially expressed circRNAs may play roles in the Verticillium wilt response in cotton. A total of 280 differentially expressed circRNAs were identified. A Gene Ontology analysis showed that most of the 'stimulus response' term source genes were NBS family genes, of which most were the source genes from the differentially expressed circRNAs, indicating that NBS genes may play a role in Verticillium wilt resistance and might be regulated by circRNAs in the disease-resistance process in cotton.

Genome-wide comparative analysis of NBS-encoding genes in four Gossypium species.

BACKGROUND: Nucleotide binding site (NBS) genes encode a large family of disease resistance (R) proteins in plants. The availability of genomic data of the two diploid cotton species, Gossypium arboreum and Gossypium raimondii, and the two allotetraploid cotton species, Gossypium hirsutum (TM-1) and Gossypium barbadense allow for a more comprehensive and systematic comparative study of NBS-encoding genes to elucidate the mechanisms of cotton disease resistance. RESULTS: Based on the genome assembly data, 246, 365, 588 and 682 NBS-encoding genes were identified in G. arboreum, G. raimondii, G. hirsutum and G. barbadense, respectively. The distribution of NBS-encoding genes among the chromosomes was nonrandom and uneven, and was tended to form clusters. Gene structure analysis showed that G. arboreum and G. hirsutum possessed a greater proportion of CN, CNL, and N genes and a lower proportion of NL, TN and TNL genes compared to that of G. raimondii and G. barbadense, while the percentages of RN and RNL genes remained relatively unchanged. The percentage changes among them were largest for TNL genes, about 7 times. Exon statistics showed that the average exon numbers per NBS gene in G. raimondii and G. barbadense were all greater than that in G. arboretum and G. hirsutum. Phylogenetic analysis revealed that the TIR-NBS genes of G. barbadense were closely related with that of G. raimondii. Sequence similarity analysis showed that diploid cotton G. arboreum possessed a larger proportion of NBS-encoding genes similar to that of allotetraploid cotton G. hirsutum, while diploid G. raimondii possessed a larger proportion of NBS-encoding genes similar to that of allotetraploid cotton G. barbadense. The synteny analysis showed that more NBS genes in G. raimondii and G. arboreum were syntenic with that in G. barbadense and G. hirsutum, respectively. CONCLUSIONS: The structural architectures, amino acid sequence similarities and synteny of NBS-encoding genes between G. arboreum and G. hirsutum, and between G. raimondii and G. barbadense were the highest among comparisons between the diploid and allotetraploid genomes, indicating that G. hirsutum inherited more NBS-encoding genes from G. arboreum, while G. barbadense inherited more NBS-encoding genes from G. raimondii. This asymmetric evolution of NBS-encoding genes may help to explain why G. raimondii and G. barbadense are more resistant to Verticillium wilt, whereas G. arboreum and G. hirsutum are more susceptible to Verticillium wilt. The disease resistances of the allotetraploid cotton were related to their NBS-encoding genes especially in regard from which diploid progenitor they were derived, and the TNL genes may have a significant role in disease resistance to Verticillium wilt in G. raimondii and G. barbadense.