Atlas-based structural analysis of prefrontal cortex atrophy in major depressive disorder: Correlations with severity and episode frequency.

BACKGROUND: Current models of major depressive disorder (MDD) primarily focus on the structural and functional changes in key prefrontal areas responsible for emotional regulation. Among these regions some sections such as the dorsal prefrontal area, has received limited attention regarding its structural abnormalities in MDD. This study aims to evaluate volumetric abnormalities in brain regions associated with markers of depression severity and episode frequency. METHODS: The study included 33 MDD patients and 33 healthy subjects. Using an atlas-based method, we measured the volumes of several key brain regions based on MRI data. The regions of interest included prefrontal and posterior sections of the middle frontal gyrus (MFG) and superior frontal gyrus (SFG). Additionally, we evaluated the volumes of the dorsal anterior cingulate cortex (dACC), perigenual (rostral) anterior cingulate cortex (pgACC), subgenual cingulate cortex (sgACC), posterior cingulate cortex (PCC), hippocampus (HPC), and parahippocampus (paraHPC). Hamilton Depression Scale (HAM-D) scores and count of the depressive episodes of patients were also obtained. A regression analysis with sex as the confounding factor has been made. RESULTS: Analysis of covariances, controlling for sex, showed significant atrophy in the sgACC in the depression group: F(1, 63) = 4.013, p = 0.049 (left) and F(1, 63) = 8.786, p < 0.004 (right). Poisson regression, also controlling for sex, found that each additional depressive episode was associated with a significant reduction in left posterior MFG volume (0.952 times, 95 % CI, 0.906 to 1.000; p = 0.049). CONCLUSIONS: Findings in this study highlight the structural abnormalities in MDD patients in correlation to either current depression severity or chronicity of the disease.

Integrating network analysis with differential expression to uncover therapeutic and prognostic biomarkers in esophageal squamous cell carcinoma.

Introduction: Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, we used bioinformatics analysis to identify potential biomarkers and therapeutic targets for ESCC. Methodology: Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained by comprehensively analyzing publicly available RNA-seq datasets from the TCGA and GTEX. Gene Ontology (GO) annotation and Reactome pathway analysis identified the biological roles of the DEGs. Moreover, the Cytoscape 3.10.1 platform and subsidiary tools such as CytoHubba were used to visualize the DEGs' protein-protein interaction (PPI) network and identify hub genes, Furthermore our results are validated by using Single-cell RNA analysis. Results: Identification of 2524 genes exhibiting altered expression enriched in pathways including keratinization, epidermal cell differentiation, G alpha(s) signaling events, and biological process of cell proliferation and division, extracellular matrix (ECM) disassembly, and muscle function. Moreover, upregulation of hallmarks E2F targets, G2M checkpoints, and TNF signaling. CytoHubba revealed 20 hub genes that had a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of four genes, CDK1 MAD2L1, PLK1, and TOP2A, were associated with critical dependence for cell survival in ESCC cell lines, as indicated by CRISPR dependency scores, gene expression data, and cell line metadata. We also identify the molecules targeting these essential hub genes, among which GSK461364 is a promising inhibitor of PLK1, BMS265246, and Valrubicin inhibitors of CDK1 and TOP2A, respectively. Moreover, we identified that elevated expression of MMP9 is associated with worse overall survival in ESCC patients, which may serve as potential prognostic biomarker or therapeutic target for ESCC. The single-cell RNA analysis showed MMP9 is highly expressed in myeloid, fibroblast, and epithelial cells, but low in T cells, endothelial cells, and B cells. This suggests MMP9's role in tumor progression and matrix remodeling, highlighting its potential as a prognostic marker and therapeutic target. Discussion: Our study identified key hub genes in ESCC, assessing their potential as therapeutic targets and biomarkers through detailed expression and dependency analyses. Notably, MMP9 emerged as a significant prognostic marker with high expression correlating with poor survival, underscoring its potential for targeted therapy. These findings enhance our understanding of ESCC pathogenesis and highlight promising avenues for treatment.

Single-cell transcriptional atlas of tumor-associated macrophages in breast cancer.

BACKGROUND: The internal heterogeneity of breast cancer, notably the tumor microenvironment (TME) consisting of malignant and non-malignant cells, has been extensively explored in recent years. The cells in this complex cellular ecosystem activate or suppress tumor immunity through phenotypic changes, secretion of metabolites and cell-cell communication networks. Macrophages, as the most abundant immune cells within the TME, are recruited by malignant cells and undergo phenotypic remodeling. Tumor-associated macrophages (TAMs) exhibit a variety of subtypes and functions, playing significant roles in impacting tumor immunity. However, their precise subtype delineation and specific function remain inadequately defined. METHODS: The publicly available single-cell transcriptomes of 49,141 cells from eight breast cancer patients with different molecular subtypes and stages were incorporated into our study. Unsupervised clustering and manual cell annotation were employed to accurately classify TAM subtypes. We then conducted functional analysis and constructed a developmental trajectory for TAM subtypes. Subsequently, the roles of TAM subtypes in cell-cell communication networks within the TME were explored using endothelial cells (ECs) and T cells as key nodes. Finally, analyses were repeated in another independent publish scRNA datasets to validate our findings for TAM characterization. RESULTS: TAMs are accurately classified into 7 subtypes, displaying anti-tumor or pro-tumor roles. For the first time, we identified a new TAM subtype capable of proliferation and expansion in breast cancer-TUBA1B+ TAMs playing a crucial role in TAMs diversity and tumor progression. The developmental trajectory illustrates how TAMs are remodeled within the TME and undergo phenotypic and functional changes, with TUBA1B+ TAMs at the initial point. Notably, the predominant TAM subtypes varied across different molecular subtypes and stages of breast cancer. Additionally, our research on cell-cell communication networks shows that TAMs exert effects by directly modulating intrinsic immunity, indirectly regulating adaptive immunity through T cells, as well as influencing tumor angiogenesis and lymphangiogenesis through ECs. CONCLUSIONS: Our study establishes a precise single-cell atlas of breast cancer TAMs, shedding light on their multifaceted roles in tumor biology and providing resources for targeting TAMs in breast cancer immunotherapy.

Dynamic changes in cellular atlases and communication patterns within yak ovaries across diverse reproductive states unveiled by single-cell analysis.

Yaks (Bos grunniens) exhibit exceptional adaptation to the challenging high-altitude environment of the Qinghai-Tibetan plateau, making them the sole bovine species capable of thriving in such exreme conditions. Investigating the cellular and molecular characteristics of yak ovaries across different reproductive states is crucial for gaining insight into their ovarian functions. Herein, the cellular atlases of yak ovaries in different reproductive states were depicted by single-cell RNA-sequencing (scRNA-seq). The cellular atlases of the ovaries were established by identifying specific gene expression patterns of various cell types, including granulosa cells, theca cells, stromal cells, smooth muscle cells, endothelial cells, glial cell, macrophages, natural killer cells, and proliferating cells. The cellular compositions of the ovaries vary among different reproductive states. Furthermore, the granulosa cells comprise six cell subtypes, while theca cells consist of eight cell subtypes. The granulosa cells and theca cells exhibit distinct biological functions throughout different reproductive states. The two cell types were aligned along their respective pseudotime trajectories. Moreover, a cell-to-cell communication network was constructed among distinct cell types within the ovary, spanning the three reproductive states. Notably, during the estrus period, the granulosa cells demonstrated more prominent interactions with other cell types compared to the remaining reproductive states.

FN1, a reliable prognostic biomarker for thyroid cancer, is associated with tumor immunity and an unfavorable prognosis.

Thyroid cancer (THCA) is a malignant tumor that affects the endocrine system. At present, an effective treatment for THCA remains elusive, particularly for medullary carcinoma and undifferentiated carcinoma, due to the lack of suitable medications and prognostic markers. Patient RNA-sequencing and clinical data were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Protein-protein interaction analyses were performed for differentially expressed genes related to THCA. Moreover, the associations between fibronectin 1 (FN1), clinical data, immune checkpoint genes and immune cell infiltration was assessed. The potential functional role of the FN1 gene was evaluated through gene set enrichment analysis. Immunohistochemistry was used to assess FN1 expression in 103 cases of THCA, comprising 32 with papillary carcinoma, 30 with follicular carcinoma, 35 with medullary carcinoma and 6 with undifferentiated carcinoma. Finally, 11 co-expression modules were constructed and the expression of five identified hub genes (FN1, mucin-1, keratin 19, intracellular adhesion molecule 1 and neural cell adhesion molecule) were evaluated. The results demonstrated that higher FN1 gene expression levels were strongly associated with a higher pathologic stage and tumor stage, and were significantly associated with immune cell infiltration in THCA. Significant increases in FN1 protein expression levels were noted among patients diagnosed with four types of THCA, comprising papillary carcinoma, follicular carcinoma, medullary carcinoma and undifferentiated carcinoma. Patients diagnosed with medullary carcinoma and undifferentiated carcinoma, and with low FN1 expression levels, exhibited a significant survival advantage compared with those with high FN1 expression levels. In conclusion, the present study identified five hub genes involved in the onset and progression of THCA. Furthermore, FN1 could serve as a candidate biomarker and a therapeutic target for THCA and may be a key gene mediating THCA immune infiltration.

Molecular characterization of clinically isolated Pseudomonas aeruginosa with varying resistance to ceftazidime-avibactam and ceftolozane-tazobactam collected as a part of the ATLAS global surveillance program from 2020 to 2021.

Ceftazidime-avibactam (CZA) and ceftolozane-tazobactam (C/T) are important agents for treating multidrug-resistant P. aeruginosa infections. In this study, we evaluated the molecular characteristics of 300 globally collected clinical P. aeruginosa isolates non-susceptible (NS) to CZA, C/T, or both agents. Isolates were CZA-NS and C/T-NS (n = 57), CZA-susceptible (S) and C/T-NS (n = 145), or CZA-NS and C/T-S (n = 98) selected from the Antimicrobial Testing Leadership and Surveillance (ATLAS) surveillance program from 2020 to 2021. Characterization was by whole-genome sequencing. Analysis was performed to identify ß-lactamase genes and mutations that impact efflux regulation, AmpC regulation, and target binding (PBP3). Of the 57 CZA-NS+C/T-NS isolates, 64.9% carried a metallo-ß-lactamase (MBL), and a cumulative 84.2% carried any non-intrinsic ß-lactamase [i.e., not Pseudomonas-derived cephalosporinase (PDC) or OXA-50-like]. Of the 145 CZA-S+C/T-NS isolates, 26.2% carried an extended-spectrum ß-lactamase (ESBL) and no carbapenemase, 17.9% carried a serine-carbapenemase, and 42.1% were negative for non-intrinsic ß-lactamases. Of 98 CZA-NS+C/T-S isolates, 34.7% carried mutations previously described as causing an upregulation of the MexAB-OprM efflux pump, while only 9.2% carried a non-intrinsic ß-lactamase, and no resistance mechanism was identified in 29.6% of these isolates. MBLs were present in most isolates NS to both agents. More than half of the CZA-S+C/T-NS isolates carried serine ß-lactamases. The most frequently identified resistance mechanism identified in CZA-NS+C/T-S isolates was a marker indicating the upregulation of MexAB-OprM. No mechanism was identified that is thought to support resistance to these agents in numerous isolates. This may be due in part to the fact that whole genome sequencing (WGS) cannot directly measure gene expression of chromosomal resistance mechanisms.

Surgical Management of Type II Odontoid Fractures in a Resource-Limited Setting: A Case Series.

Type II odontoid fracture, classified by Anderson and D'Alonzo, is the most common traumatic injury to the odontoid process. Surgical management of this lesion is particularly challenging in underresourced countries. This study aims to report the preliminary experience of the Kinshasa University Teaching Hospital in Kinshasa, Democratic Republic of the Congo, particularly using adaptive techniques. Three patients, aged 22, 30, and 32 years, respectively, were admitted to the neurosurgery department with Anderson and D'Alonzo type II odontoid fractures as confirmed by CT scan imaging. The first two patients underwent anterior odontoid fixation using a non-cannulated orthopaedic screw with an image intensifier. In the third case, partial resection of the C1 posterior arch was performed, followed by immobilisation using a rigid Philadelphia neck brace. Postoperative follow-up in all three cases was uneventful, and neurological outcomes were satisfactory. Odontoid surgery remains challenging for developing countries. The use of a non-cannulated orthopaedic screw for anterior fixation and posterior spinal cord decompression via partial resection of the C1 posterior arch, followed by external cervical immobilisation with a rigid neck brace for neglected fractures, could be effective alternatives to conventional surgical techniques. However, randomised multicentre studies are required to confirm the efficacy and safety of these techniques.

Exosomal transcript cargo and functional correlation with HNSCC patients' survival.

BACKGROUND: HPV status in a subset of HNSCC is linked with distinct treatment outcomes. Present investigation aims to elucidate the distinct clinicopathological features of HPV-positive and HPV-negative HNSCC and investigate their association with the HNSCC patient survival. MATERIALS AND METHODS: The total RNA of exosomes from HPV-positive (93VU147T) and HPV-negative (OCT-1) HNSCC cells was isolated, and the transcripts were estimated using Illumina HiSeq X. The expression of altered transcripts and their clinical relevance were further analyzed using publicly available cancer transcriptome data from The Cancer Genome Atlas (TCGA). RESULTS: Transcriptomic analyses identified 3785 differentially exported transcripts (DETs) in HPV-positive exosomes compared to HPV-negative exosomes. DETs that regulate the protein machinery, cellular redox potential, and various neurological disorder-related pathways were over-represented in HPV-positive exosomes. TCGA database revealed the clinical relevance of altered transcripts. Among commonly exported abundant transcripts, SGK1 and MAD1L1 showed high expression, which has been correlated with poor survival in HNSCC patients. In the top 20 DETs of HPV-negative exosomes, high expression of FADS3, SGK3, and TESK2 correlated with poor survival of the HNSCC patients in the TCGA database. CONCLUSION: Overall, our study demonstrates that HPV-positive and HPV-negative cells' exosomes carried differential transcripts cargo that may be related to pathways associated with neurological disorders. Additionally, the altered transcripts identified have clinical relevance, correlating with patient survival in HNSCC, thereby highlighting their potential as biomarkers and as therapeutic targets.

A Comparison of Two Methods of Dental Age Estimation in a Population of Saudi Children and Adolescents.

This study aimed to compare and evaluate the accuracy of the Demirjian (DE) and the London Atlas (LAE) dental age estimation methods in a Saudi population sample. This retrospective cross-sectional study used digital radiographs from electronic health records in three different dental institutes. In total, 357 male and 354 female (ages 5-15 years) digital orthopantomograms were selected for age estimation. The mean difference between the chronological age (CA) and age estimation method among males and females was 0.03 ± 0.34 and 0.00 ± 0.34, respectively, for LAE and 0.55 ± 0.84 and 0.76 ± 0.51, respectively, for DE. The mean difference between the LAE and DE methods among males and females was 0.52 ± 0.89 and -0.76 ± 0.57, respectively. No statistically significant difference between CA and LAE was found in either males (p = 0.079) or females (p = 0.872). A statistically significant difference was found between CA and DE in both genders (p < 0.001). A statistically significant difference was found between the LAE and DE groups (p < 0.001) in both genders. An overestimation of dental age was observed with DE compared with that in CA. LAE showed higher accuracy than CA, with no clinically significant difference. Although the difference between the LAE and DE methods was insignificant, the LAE method proved to be more accurate.

Prediction models of the aphasia severity after stroke by lesion load of cortical language areas and white matter tracts: An atlas-based study.

OBJECTIVE: To construct relatively objective, atlas-based multivariate models for predicting early aphasia severity after stroke, using structural magnetic resonance imaging. METHODS: We analyzed the clinical and imaging data of 46 patients with post-stroke aphasia. The aphasia severity was identified with a Western Aphasia Battery Aphasia Quotient. The assessments of stroke lesions were indicated by the lesion load of both the cortical language areas (Areas-LL) and four white matter tracts (i.e., the superior longitudinal fasciculus, SLF-LL; the inferior frontal occipital fasciculi, IFOF-LL; the inferior longitudinal, ILF-LL; and the uncinate fasciculi, UF-LL) extracted from human brain atlas. Correlation analyses and multiple linear regression analyses were conducted to evaluate the correlations between demographic, stroke- and lesion-related variables and aphasia severity. The predictive models were then established according to the identified significant variables. Finally, the receiver operating characteristic (ROC) curve was utilized to assess the accuracy of the predictive models. RESULTS: The variables including Areas-LL, the SLF-LL, and the IFOF-LL were significantly negatively associated with aphasia severity (p < 0.05). In multiple linear regression analyses, these variables accounted for 59.4 % of the variance (p < 0.05). The ROC curve analyses yielded the validated area under the curve (AUC) 0.84 both for Areas-LL and SLF-LL and 0.76 for IFOF-LL, indicating good predictive performance (p < 0.01). Adding the combination of SLF-LL and IFOF-LL to this model increased the explained variance to 62.6 % and the AUC to 0.92. CONCLUSIONS: The application of atlas-based multimodal lesion assessment may help predict the aphasia severity after stroke, which needs to be further validated and generalized for the prediction of more outcome measures in populations with various brain injuries.

Development of a novel colon adenocarcinoma m6A-related lncRNA pair prognostic model.

Background: Colon adenocarcinoma (COAD) is among the most prevalent malignancies. Changes to N6-methyladenosine (m6A), the most common RNA modification, can affect how COAD develops. Furthermore, the involvement of long noncoding RNA (lncRNA) in COAD is significant, and it exhibits a close association with m6A modification. Nevertheless, the prognostic significance of lncRNAs that are related to m6A modification in COAD remains unclear. This study aims to establish a m6A-related lncRNA pair signature and reveal its prognostic value in COAD. Methods: The current study utilized data from The Cancer Genome Atlas (TCGA) to investigate the predictive significance of m6A-related lncRNA pair signatures in COAD. The identification of m6A-related lncRNAs was conducted through co-expression analysis using the Pearson correlation coefficient. Then, the lncRNA pairs related to prognosis were identified using univariate Cox regression analysis. Receiver operating characteristic (ROC) curves were produced using the least absolute shrinkage and selection operator (LASSO) penalized with Cox analysis to predict overall survival (OS) in order to build a risk score prognostic model. The relationship among the risk scoring model and clinical characteristics, immune-related variables, and medication sensitivity was examined after identifying independent prognostic factors. Results: Thirty-five of the 319 lncRNA pairings associated with m6A were linked to a pattern that predicted risk ratings. It was verified that the risk score model was a reliable predictor that stood alone from clinicopathological features. Differences between high- and low-risk groups were found in clinicopathological traits, immune-related variables, and medication sensitivity analysis according to correlation analyses. Conclusions: Based on paired differentially expressed m6A-related lncRNAs, the proposed COAD prognostic model demonstrated potential clinical predictive value.

A human brain atlas of χ-separation for normative iron and myelin distributions.

Iron and myelin are primary susceptibility sources in the human brain. These substances are essential for a healthy brain, and their abnormalities are often related to various neurological disorders. Recently, an advanced susceptibility mapping technique, which is referred to as χ-separation (pronounced as "chi"-separation), has been proposed, successfully disentangling paramagnetic iron from diamagnetic myelin. This method provided a new opportunity for generating high-resolution iron and myelin maps of the brain. Utilizing this technique, this study constructs a normative χ-separation atlas from 106 healthy human brains. The resulting atlas provides detailed anatomical structures associated with the distributions of iron and myelin, clearly delineating subcortical nuclei, thalamic nuclei, and white matter fiber bundles. Additionally, susceptibility values in a number of regions of interest are reported along with age-dependent changes. This atlas may have direct applications such as localization of subcortical structures for deep brain stimulation or high-intensity focused ultrasound and also serve as a valuable resource for future research.

Subject-specific atlas for automatic brain tissue segmentation of neonatal magnetic resonance images.

Developing advanced systems for 3D brain tissue segmentation from neonatal magnetic resonance (MR) images is vital for newborn structural analysis. However, automatic segmentation of neonatal brain tissues is challenging due to smaller head size and inverted T1/T2 tissue contrast compared to adults. In this work, a subject-specific atlas based technique is presented for segmentation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) from neonatal MR images. It involves atlas selection, subject-specific atlas creation using random forest (RF) classifier, and brain tissue segmentation using the expectation maximization-Markov random field (EM-MRF) method. To increase the segmentation accuracy, different tissue intensity- and gradient-based features were used. Evaluation on 40 neonatal MR images (gestational age of 37-44 weeks) demonstrated an overall accuracy of 94.3% and an average Dice similarity coefficient (DSC) of 0.945 (GM), 0.947 (WM), and 0.912 (CSF). Compared to multi-atlas segmentation methods like SEGMA and EM-MRF with multiple atlases, our method improved accuracy by up to 4%, particularly in complex tissue regions. Our proposed method allows accurate brain tissue segmentation, a crucial step in brain magnetic resonance imaging (MRI) applications including brain surface reconstruction and realistic head model creation in neonates.

Cerebral blood flow alterations and host genetic association in individuals with long COVID: A transcriptomic-neuroimaging study.

Neuroimaging studies have indicated that altered cerebral blood flow (CBF) was associated with the long-term symptoms of postacute sequelae of SARS-CoV-2 infection (PASC), also known as "long COVID". COVID-19 and long COVID were found to be strongly associated with host gene expression. Nevertheless, the relationships between altered CBF, clinical symptoms, and gene expression in the central nervous system (CNS) remain unclear in individuals with long COVID. This study aimed to explore the genetic mechanisms of CBF abnormalities in individuals with long COVID by transcriptomic-neuroimaging spatial association. Lower CBF in the left frontal-temporal gyrus was associated with higher fatigue and worse cognition in individuals with long COVID. This CBF pattern was spatially associated with the expression of 2,178 genes, which were enriched in the molecular functions and biological pathways of COVID-19. Our study suggested that lower CBF is associated with persistent clinical symptoms in long COVID individuals, possibly as a consequence of the complex interactions among multiple COVID-19-related genes, which contributes to our understanding of the impact of adverse CNS outcomes and the trajectory of development to long COVID.

Single-cell RNA-Seq reveals the heterogeneity of fibroblasts within the tympanojugular paraganglioma microenvironment.

Tympanojugular paragangliomas (TJP) originate from the parasympathetic ganglia in the lateral base of the skull. Although the cellular composition and oncogenic mechanisms of paragangliomas have been evaluated, a comprehensive transcriptomic atlas specific to TJP remains to be established to facilitate further investigations. In this study, single-cell RNA sequencing and whole-exome sequencing were conducted on six surgically excised TJP samples to determine their cellular composition and intratumoral heterogeneity. Fibroblasts were sub-classified into two distinct groups: myofibroblasts and fibroblasts associated with bone remodeling. Additionally, an elaborate regulatory and cell-cell communication network was determined, highlighting the multifaceted role of fibroblasts, which varies depending on expression transitions. The Kit receptor (KIT) signaling pathway mediated interactions between fibroblasts and mast cells, whereas robust connections with endothelial and Schwann cell-like cells were facilitated through the platelet-derived growth factor signaling pathway. These findings establish a foundation for studying the mechanisms underlying protumor angiogenesis and the specific contributions of fibroblasts within the TJP microenvironment. IL6 signaling pathway of fibroblasts interacting with macrophages and endothelial cells may be involved in tumor regrowth. These results enhance our understanding of fibroblast functionality and provide a resource for future therapeutic targeting of TJP.

Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients.

OBJECTIVE: The activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear. METHODS: The cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored. RESULTS: A total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes. CONCLUSION: Through bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.

Atlas-guided brain projection tracts: From regions of interest to tractography 3D rendering.

The use of diffusion tensor imaging (DTI) has seen significant development over the last two decades, in particular with the development of the tractography of association tracts for preoperative planning of surgery. However, projection tracts are difficult to differentiate from one another and tractography studies have failed to reconstruct these ascending/descending pathways from/to the spinal cord. The present study proposes an atlas of regions of interest (ROIs) designed specifically for projection tracts tractography. Forty-nine healthy subjects were included in this prospective study. Brain DTI was acquired using the same 3 T MRI scanner, with 32 diffusion directions. Distortions were corrected using the FSL software package. ROIs were drawn using the anterior commissure (AC)-posterior commissure (PC) line on the following landmarks: the pyramid for the corticospinal tract, the medio-caudal part of the red nucleus for the rubrospinal tract, the pontine reticular nucleus for corticoreticular tract, the superior and inferior cerebellar peduncles for, respectively, the anterior and posterior spinocerebellar tract, the gracilis and cuneatus nucleus for the dorsal columns, and the ventro-posterolateral nucleus for the spinothalamic tract. Fiber tracking was performed using a deterministic algorithm using DSI Studio software. ROI coordinates, according to AC-PC line, were given for each tract. Tractography was obtained for each tract, allowing tridimensional rendering and comparison of tracking metrics between tracts. The present study reports the accurate design of specific ROIs for tractography of each projection tract. This could be a useful tool in order to differentiate projection tracts at the spinal cord level.

Mapping stroke outcomes: A review of brain connectivity atlases.

The brain connectivity-based atlas is a promising tool for understanding neural communication pathways in the brain, gaining relevance in predicting personalized outcomes for various brain pathologies. This critical review examines the robustness of the brain connectivity-based atlas for predicting post-stroke outcomes. A comprehensive literature search was conducted from 2012 to May 2023 across PubMed, Scopus, EMBASE, EBSCOhost, and Medline databases. Twenty-one studies were screened, and through analysis of these studies, we identified 18 brain connectivity atlases employed by the studies for lesion analysis in their predictions. The brain atlases were assessed for study cohorts, connectivity measures, identified brain regions, atlas applications, and limitations. Based on the analysis of these studies, most atlases were based on diffusion tensor imaging and resting-state functional magnetic resonance imaging (MRI). Studies predicting post-stroke functional outcomes relied on the atlases for multivariate lesion analysis and region of interest identification, often employing atlases derived from young, healthy populations. Current brain connectivity-based atlases for stroke applications lack standardized methods to define and map brain connectivity across atlases and cover sensorimotor functional connectivity to a limited extent. In conclusion, this review highlights the need to develop more comprehensive, robust, and adaptable brain connectivity-based atlases specifically tailored to post-stroke populations.

Designing the Australian Cancer Atlas: visualizing geostatistical model uncertainty for multiple audiences.

OBJECTIVE: The Australian Cancer Atlas (ACA) aims to provide small-area estimates of cancer incidence and survival in Australia to help identify and address geographical health disparities. We report on the 21-month user-centered design study to visualize the data, in particular, the visualization of the estimate uncertainty for multiple audiences. MATERIALS AND METHODS: The preliminary phases included a scoping study, literature review, and target audience focus groups. Several methods were used to reach the wide target audience. The design and development stage included digital prototyping in parallel with Bayesian model development. Feedback was sought from multiple workshops, audience focus groups, and regular meetings throughout with an expert external advisory group. RESULTS: The initial scoping identified 4 target audience groups: the general public, researchers, health practitioners, and policy makers. These target groups were consulted throughout the project to ensure the developed model and uncertainty visualizations were effective for communication. In this paper, we detail ACA features and design iterations, including the 3 complementary ways in which uncertainty is communicated: the wave plot, the v-plot, and color transparency. DISCUSSION: We reflect on the methods, design iterations, decision-making process, and document lessons learned for future atlases. CONCLUSION: The ACA has been hugely successful since launching in 2018. It has received over 62 000 individual users from over 100 countries and across all target audiences. It has been replicated in other countries and the second version of the ACA was launched in May 2024. This paper provides rich documentation for future projects.