Intraoperative mapping of epileptogenic foci and tumor infiltration in neuro-oncology patients with epilepsy.

Background: Epileptogenesis and glioma growth have a bidirectional relationship. We hypothesized people with gliomas can benefit from the removal of epileptic tissue and that tumor-related epileptic activity may signify tumor infiltration in peritumoral regions. We investigated whether intraoperative electrocorticography (ioECoG) could improve seizure outcomes in oncological glioma surgery, and vice versa, what epileptic activity (EA) tells about tumor infiltration. Methods: We prospectively included patients who underwent (awake) ioECoG-assisted diffuse-glioma resection through the oncological trajectory. The IoECoG-tailoring strategy relied on ictal and interictal EA (spikes and sharp waves). Brain tissue, where EA was recorded, was assigned for histopathological examination separate from the rest of the tumor. Weibull regression was performed to assess how residual EA and extent of resection (EOR) related to the time-to-seizure recurrence, and we investigated which type of EA predicted tumor infiltration. Results: Fifty-two patients were included. Residual spikes after resection were associated with seizure recurrence in patients with isocitrate dehydrogenase (IDH) mutant astrocytoma or oligodendroglioma (HR = 7.6[1.4-40.0], P-value = .01), independent from the EOR. This was not observed in IDH-wildtype tumors. All tissue samples resected based on interictal spikes were infiltrated by tumor, even if the MRI did not show abnormalities. Conclusions: Complete resection of epileptogenic foci in ioECoG may promote seizure control in IDH-mutant gliomas. The cohort size of IDH-wildtype tumors was too limited to draw definitive conclusions. Interictal spikes may indicate tumor infiltration even when this area appears normal on MRI. Integrating electrophysiology guidance into oncological tumor surgery could contribute to improved seizure outcomes and precise guidance for radical tumor resection.

Combined MediaPipe and YOLOv5 range of motion assessment system for spinal diseases and frozen shoulder.

Spinal diseases and frozen shoulder are prevalent health problems in Asian populations. Early assessment and treatment are very important to prevent the disease from getting worse and reduce pain. In the field of computer vision, it is a challenging problem to assess the range of motion. In order to realize efficient, real-time and accurate assessment of the range of motion, an assessment system combining MediaPipe and YOLOv5 technologies was proposed in this study. On this basis, Convolutional Block Attention Module (CBAM) is introduced into the YOLOv5 target detection model, which can enhance the extraction of feature information, suppress background interference, and improve the generalization ability of the model. In order to meet the requirements of large-scale computing, a client/server (C/S) framework structure is adopted. The evaluation results can be obtained quickly after the client uploads the image data, providing a convenient and practical solution. In addition, a game of "Picking Bayberries" was developed as an auxiliary treatment method to provide patients with interesting rehabilitation training.

Single-cell omics: experimental workflow, data analyses and applications.

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Spatial and temporal properties of intra-operatively recorded spikes and high frequency oscillations in focal cortical dysplasia.

OBJECTIVE: Focal cortical dysplasias (FCD) are characterized by distinct interictal spike patterns and high frequency oscillations (HFOs; ripples: 80-250 Hz; fast ripples: 250-500 Hz) in the intra-operative electrocorticogram (ioECoG). We studied the temporal relation between intra-operative spikes and HFOs and their relation to resected tissue in people with FCD with a favorable outcome. METHODS: We included patients who underwent ioECoG-tailored epilepsy surgery with pathology confirmed FCD and long-term Engel 1A outcome. Spikes and HFOs were automatically detected and visually checked in 1-minute pre-resection-ioECoG. Channels covering resected and non-resected tissue were compared using a logistic mixed model, assessing event numbers, co-occurrence ratios, and time-based properties. RESULTS: We found pre-resection spikes, ripples in respectively 21 and 20 out of 22 patients. Channels covering resected tissue showed high numbers of spikes and HFOs, and high ratios of co-occurring events. Spikes, especially with ripples, have a relatively sharp rising flank with a long descending flank and early ripple onset over resected tissue. CONCLUSIONS: A combined analysis of event numbers, ratios, and temporal relationships between spikes and HFOs may aid identifying epileptic tissue in epilepsy surgery. SIGNIFICANCE: This study shows a promising method for clinically relevant properties of events, closely associated with FCD.

Discovery and Optimization of the First ATP Competitive Type-III c-MET Inhibitor.

Recent clinical reports have highlighted the need for wild-type (WT) and mutant dual inhibitors of c-MET kinase for the treatment of cancer. We report herein a novel chemical series of ATP competitive type-III inhibitors of WT and D1228V mutant c-MET. Using a combination of structure-based drug design and computational analyses, ligand 2 was optimized to a highly selective chemical series with nanomolar activities in biochemical and cellular settings. Representatives of the series demonstrate excellent pharmacokinetic profiles in rat in vivo studies with promising free-brain exposures, paving the way for the design of brain permeable drugs for the treatment of c-MET driven cancers.

TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment.

The Tumor Immune Single Cell Hub 2 (TISCH2) is a resource of single-cell RNA-seq (scRNA-seq) data from human and mouse tumors, which enables comprehensive characterization of gene expression in the tumor microenvironment (TME) across multiple cancer types. As an increasing number of datasets are generated in the public domain, in this update, TISCH2 has included 190 tumor scRNA-seq datasets covering 6 million cells in 50 cancer types, with 110 newly collected datasets and almost tripling the number of cells compared with the previous release. Furthermore, TISCH2 includes several new functions that allow users to better utilize the large-scale scRNA-seq datasets. First, in the Dataset module, TISCH2 provides the cell-cell communication results in each dataset, facilitating the analyses of interacted cell types and the discovery of significant ligand-receptor pairs between cell types. TISCH2 also includes the transcription factor analyses for each dataset and visualization of the top enriched transcription factors of each cell type. Second, in the Gene module, TISCH2 adds functions for identifying correlated genes and providing survival information for the input genes. In summary, TISCH2 is a user-friendly, up-to-date and well-maintained data resource for gene expression analyses in the TME. TISCH2 is freely available at http://tisch.comp-genomics.org/.

Evaluation of cell-cell interaction methods by integrating single-cell RNA sequencing data with spatial information.

BACKGROUND: Cell-cell interactions are important for information exchange between different cells, which are the fundamental basis of many biological processes. Recent advances in single-cell RNA sequencing (scRNA-seq) enable the characterization of cell-cell interactions using computational methods. However, it is hard to evaluate these methods since no ground truth is provided. Spatial transcriptomics (ST) data profiles the relative position of different cells. We propose that the spatial distance suggests the interaction tendency of different cell types, thus could be used for evaluating cell-cell interaction tools. RESULTS: We benchmark 16 cell-cell interaction methods by integrating scRNA-seq with ST data. We characterize cell-cell interactions into short-range and long-range interactions using spatial distance distributions between ligands and receptors. Based on this classification, we define the distance enrichment score and apply an evaluation workflow to 16 cell-cell interaction tools using 15 simulated and 5 real scRNA-seq and ST datasets. We also compare the consistency of the results from single tools with the commonly identified interactions. Our results suggest that the interactions predicted by different tools are highly dynamic, and the statistical-based methods show overall better performance than network-based methods and ST-based methods. CONCLUSIONS: Our study presents a comprehensive evaluation of cell-cell interaction tools for scRNA-seq. CellChat, CellPhoneDB, NicheNet, and ICELLNET show overall better performance than other tools in terms of consistency with spatial tendency and software scalability. We recommend using results from at least two methods to ensure the accuracy of identified interactions. We have packaged the benchmark workflow with detailed documentation at GitHub ( https://github.com/wanglabtongji/CCI ).

Tertiary lymphoid structure and decreased CD8+ T cell infiltration in minimally invasive adenocarcinoma.

Knowledge of the tumor microenvironment (TME) in patients with early lung cancer, especially in comparison with the matched adjacent tissues, remains lacking. To characterize TME of early-stage lung adenocarcinoma, we performed RNA-seq profiling on 58 pairs of minimally invasive adenocarcinoma (MIA) tumors and matched adjacent normal tissues. MIA tumors exhibited an adaptive TME characterized by high CD4+ T cell infiltration, high B-cell activation, and low CD8+ T cell infiltration. The high expression of markers for B cells, activated CD4+ T cells, and follicular helper T (Tfh) cells in bulk MIA samples and three independent single-cell RNA-seq datasets implied tertiary lymphoid structures (TLS) formation. Multiplex immunohistochemistry staining validated TLS formation and revealed an enrichment of follicular regulatory T cells (Tfr) in TLS follicles, which may explain the lower CD8+ T cell infiltration and attenuated anti-tumor immunity in MIA. Our study demonstrates how integrating transcriptome and pathology characterize TME and elucidate potential mechanisms of tumor immune evasion.

STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing.

The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity in the spatial context. However, the current limitations of spatial technologies hamper the exploration of cellular localizations and interactions at single-cell level. Here, we present spatial transcriptomics deconvolution by topic modeling (STRIDE), a computational method to decompose cell types from spatial mixtures by leveraging topic profiles trained from single-cell transcriptomics. STRIDE accurately estimated the cell-type proportions and showed balanced specificity and sensitivity compared to existing methods. We demonstrated STRIDE's utility by applying it to different spatial platforms and biological systems. Deconvolution by STRIDE not only mapped rare cell types to spatial locations but also improved the identification of spatially localized genes and domains. Moreover, topics discovered by STRIDE were associated with cell-type-specific functions and could be further used to integrate successive sections and reconstruct the three-dimensional architecture of tissues. Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics and is publicly available at https://github.com/wanglabtongji/STRIDE.

Discovery of a Potent and Selective ATAD2 Bromodomain Inhibitor with Antiproliferative Activity in Breast Cancer Models.

ATAD2 is an epigenetic bromodomain-containing target which is overexpressed in many cancers and has been suggested as a potential oncology target. While several small molecule inhibitors have been described in the literature, their cellular activity has proved to be underwhelming. In this work, we describe the identification of a novel series of ATAD2 inhibitors by high throughput screening, confirmation of the bromodomain region as the site of action, and the optimization campaign undertaken to improve the potency, selectivity, and permeability of the initial hit. The result is compound 5 (AZ13824374), a highly potent and selective ATAD2 inhibitor which shows cellular target engagement and antiproliferative activity in a range of breast cancer models.

High frequency oscillations associate with neuroinflammation in low-grade epilepsy associated tumors.

OBJECTIVE: High frequency oscillations (HFOs) in intraoperative electrocorticography (ioECoG) are thought to be generated by hyperexcitable neurons. Inflammation may promote neuronal hyperexcitability. We investigated the relation between HFOs and inflammation in tumor-related epilepsy. METHODS: We identified HFOs (ripples 80-250 Hz, fast ripples 250-500 Hz) in the preresection ioECoG of 32 patients with low-grade tumors. Localization of recorded HFOs was classified based on magnetic resonance imaging reconstructions: in tumor, in resected non-tumorous area and outside the resected area. We tested if the following inflammatory markers in the tumor or peritumoral tissue were related to HFOs: activated microglia, cluster of differentiation 3 (CD3)-positive T-cells, interleukin 1-beta (IL1ß), toll-like receptor 4 (TLR4) and high mobility group box 1 protein (HMGB1). RESULTS: Tumors that generated ripples were infiltrated by more CD3-positive cells than tumors without ripples. Ripple rate outside the resected area was positively correlated with IL1ß/TLR4/HMGB1 pathway activity in peritumoral area. These two areas did not directly overlap. CONCLUSIONS: Ripple rates may be associated with inflammatory processes. SIGNIFICANCE: Our findings support that ripple generation and spread might be associated with synchronized fast firing of hyperexcitable neurons due to certain inflammatory processes. This pilot study provides arguments for further investigations in HFOs and inflammation.

Single-layer multitasking vortex-metalens for ultra-compact two-photon excitation STED endomicroscopy imaging.

With the novel capabilities of engineering the optical wavefront at the nanoscale, the dielectric metalens has been utilized for fluorescence microscopy imaging system. However, the main technical difficulty is how to realize the achromatic focusing and light modulation simultaneously by a single-layer metalens in the two-photon excitation STED (TPE-STED) endomicroscopy imaging system. Herein, by combining the spatial multiplexing technology and vortex phase modulation, a single-layer multitasking vortex-metalens as a miniature microscopy objective on the end of fiber was proposed. The multitasking vortex-metalens with 36-sectors interleaving (diameter of 100 µm) could focus the excitation beam (1050 nm) and depletion beam (599 nm) to the same focal distance, modulate a doughnut-shaped depletion spot with vortex phase and reshape the focal spots to further make improvement in the quality and symmetry. According to the TPE-STED theory, a symmetrical effective fluorescent spot with the lateral resolution of 30 nm was obtained by the proposed metalens. Thus, with the advantage of ultra-compact and lightweight, we prospect that the subminiature multitasking metalens will help guide future developments in high-performance metalenses toward high-resolution and real-time images for deep biological tissue in vivo and enable scientific high-end miniature endomicroscopy imaging system.

TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment.

Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors but posed computational challenges on integrating and utilizing the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly 2 million cells from 76 high-quality tumor datasets across 27 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, clustering, cell-type annotation, malignant cell classification, differential expression analysis and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.

Excitation and emission dual-wavelength confocal metalens designed directly in the biological tissue environment for two-photon micro-endoscopy.

With the advantages of completely controlling the phase, amplitude, and polarization in subwavelength range, metalenses have drawn intensive attentions in high resolution two-photon micro-endoscopic fluorescence imaging system. However, chromatic dispersion and severe scattering of biological tissue significantly reduce excitation-collection efficiency in the traditional two-photon imaging system based on traditional metalenses designed in the air background. Here, an excitation and emission dual-wavelength confocal and polarization-insensitive metalens designed in the biological tissue environment was proposed by adopting the composite embedding structure and spatial multiplexing approach. The metalens with numerical aperture (NA) of 0.895 can focus the excitation (915 nm) and emission (510 nm) beams to the same focal spot in the mouse cortex. According to the theoretical simulation of two-photon fluorescence imaging, the lateral resolution of the collected fluorescent spots via the proposed metalens can be up to 0.42 µm. Compared to the metalens designed in the air environment, the collection efficiency of fluorescent spot is improved from 5.92% to 14.60%. Our investigation has opened a new window of high resolution and minimally invasive imaging in deep regions of biological tissues.

Integrative analyses of single-cell transcriptome and regulome using MAESTRO.

We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses of single-cell RNA-seq (scRNA-seq) and ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions for pre-processing, alignment, quality control, expression and chromatin accessibility quantification, clustering, differential analysis, and annotation. By modeling gene regulatory potential from chromatin accessibilities at the single-cell level, MAESTRO outperforms the existing methods for integrating the cell clusters between scRNA-seq and scATAC-seq. Furthermore, MAESTRO supports automatic cell-type annotation using predefined cell type marker genes and identifies driver regulators from differential scRNA-seq genes and scATAC-seq peaks.

High frequency oscillations relate to cognitive improvement after epilepsy surgery in children.

OBJECTIVE: To investigate how high frequency oscillations (HFOs; ripples 80-250 Hz, fast ripples (FRs) 250-500 Hz) and spikes in intra-operative electrocorticography (ioECoG) relate to cognitive outcome after epilepsy surgery in children. METHODS: We retrospectively included 20 children who were seizure free after epilepsy surgery using ioECoG and determined their intelligence quotients (IQ) pre- and two years postoperatively. We analyzed whether the number of HFOs and spikes in pre- and postresection ioECoGs, and their change in the non-resected areas relate to cognitive improvement (with ≥ 5 IQ points increase considered to be clinically relevant (=IQ+ group) and < 5 IQ points as irrelevant (=IQ- group)). RESULTS: The IQ+ group showed significantly more FRs in the resected tissue (p = 0.01) and less FRs in the postresection ioECoG (p = 0.045) compared to the IQ- group. Postresection decrease of ripples on spikes was correlated with postoperative cognitive improvement (correlation coefficient = -0.62 with p = 0.01). CONCLUSIONS: Postoperative cognitive improvement was related to reduction of pathological HFOs signified by removing FR generating areas with subsequently less residual FRs, and decrease of ripples on spikes in the resection edge of the non-resected area. SIGNIFICANCE: HFOs recorded in ioECoG could play a role as biomarkers in the prediction and understanding of cognitive outcome after epilepsy surgery.

Spatial organization of the transcriptional regulatory network of Saccharomyces cerevisiae.

A transcriptional regulatory network (TRN) is a complex network composed of all of the regulatory interactions between transcription factors and the corresponding target genes. Recently, three-dimensional (3D) genomic studies have shown that the 3D structure of the genome may influence the regulation of gene transcription, which provides us with a novel perspective. In the present study, we constructed the TRN of the budding yeast Saccharomyces cerevisiae and placed it in the context of a 3D genome model. We analyzed the spatial organization of the yeast TRN on four levels: global features, central nodes, hierarchical structure and network motifs. The results obtained suggest that the TRN of S. cerevisiae presents an optimized structure in space to adapt to functional requirements.

(15-Crown-5-κO)[S-(E)-1,2-dichloro-vinyl thio-sulfato-κO]sodium.

In the title complex, [Na(C(2)HCl(2)O(3)S(2))(C(10)H(20)O(5))], there are two independent complex units in the asymmetric unit, one of which has a 55:45% disorder in the 15-crown-5 component. The coordination sphere about the Na atom in each complex unit comprises five bonds to O atoms of the crown ether [Na-O = 2.390 (7)-2.466 (6) Å] and one to a thio-sulfate O atom [Na-O = 2.305 (4) and 2.447 (3) Å].