Association of Compensatory Mechanisms in Prefrontal Cortex and Impaired Anatomical Correlates in Semantic Verbal Fluency: A Functional Near-Infrared Spectroscopy Study.

OBJECTIVE: Semantic verbal fluency (SVF) engages cognitive functions such as executive function, mental flexibility, and semantic memory. Left frontal and temporal lobes, particularly the left inferior frontal gyrus (IFG), are crucial for SVF. This study investigates SVF and associated neural processing in older adults with mild SVF impairment and the relationship between structural abnormalities in the left IFG and functional activation during SVF in those individuals. METHODS: Fifty-four elderly individuals with modest level of mild cognitive impairment whose global cognition were preserved to normal but exhibited mild SVF impairment were participated. Prefrontal oxyhemoglobin (HbO2) activation and frontal cortical thickness were collected from the participants using functional near-infrared spectroscopy (fNIRS) and brain MRI, respectively. We calculated the ß coefficient of HbO2 activation induced by tasks, and performed correlation analysis between SVF induced HbO2 activation and cortical thickness in frontal areas. RESULTS: We observed increased prefrontal activation during SVF task compared to the resting and control task. The activation distinct to SVF was identified in the midline superior and left superior prefrontal regions (p<0.05). Correlation analysis revealed an inverse relationship between SVF-specific activation and cortical thickness in the left IFG, particularly in pars triangularis (r(54)=-0.304, p=0.025). CONCLUSION: The study contributes to understanding the relationship between reduced cortical thickness in left IFG and increased functional activity in cognitively normal individuals with mild SVF impairment, providing implications on potential compensatory mechanisms for cognitive preservation.

Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI.

BACKGROUND: Physiologic MRI-based tumor habitat analysis has the potential to predict patient outcomes by identifying the spatiotemporal habitats of glioblastoma. This study aims to prospectively validate the cut-off for tumor progression obtained from tumor habitat analysis based on physiologic MRI in ascertaining time-to-progression (TTP) and the site of progression in glioblastoma patients following concurrent chemoradiotherapy (CCRT). METHODS: In this prospective study (ClinicalTrials.gov ID: NCT02613988), we will recruit patients with IDH-wild type glioblastoma who underwent CCRT and obtained immediate post-operative and three serial post-CCRT MRI scans within a three-month interval, conducted using diffusion-weighted imaging and dynamic susceptibility contrast imaging. Voxels from cerebral blood volume and apparent diffusion coefficient maps will be grouped using k-means clustering into three spatial habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue). The spatiotemporal habitats of the tumor will be evaluated by comparing changes in each habitat between the serial MRI scans (post-operative and post-CCRT #1, #2, and #3). Associations between spatiotemporal habitats and TTP will be analyzed using cox proportional hazard modeling. The site of progression will be matched with spatiotemporal habitats. DISCUSSION: The perfusion- and diffusion-derived tumor habitat in glioblastoma is expected to stratify TTP and may serve as an early predictor for tumor progression in patients with IDH wild-type glioblastoma. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02613988.

Rhabdomyosarcoma of the skull with EWSR1 fusion and ALK and cytokeratin expression: a case report.

Rhabdomyosarcoma (RMS) comprises of heterogeneous group of neoplasms that occasionally express epithelial markers on immunohistochemistry (IHC). We herein report the case of a patient who developed RMS of the skull with EWSR1 fusion and anaplastic lymphoma kinase (ALK) and cytokeratin expression as cytomorphologic features. A 40-year-old man presented with a mass in his forehead. Surgical resection was performed, during which intraoperative frozen specimens were obtained. Squash cytology showed scattered or clustered spindle and epithelioid cells. IHC revealed that the resected tumor cells were positive for desmin, MyoD1, cytokeratin AE1/ AE3, and ALK. Although EWSR1 rearrangement was identified on fluorescence in situ hybridization, ALK, and TFCP2 rearrangement were not noted. Despite providing adjuvant chemoradiation therapy, the patient died of tumor progression 10 months after diagnosis. We emphasize that a subset of RMS can express cytokeratin and show characteristic histomorphology, implying the need for specific molecular examination.

Endometrial E-cadherin and N-cadherin Expression during the Mid-Secretory Phase of Women with Ovarian Endometrioma or Uterine Fibroids.

BACKGROUND: Endometriosis and uterine fibroids are benign conditions frequently linked to subfertility/infertility. Recent research has highlighted the importance of epithelial-mesenchymal transition between embryonic and endometrial cells in the context of embryo implantation. Additionally, the adverse endometrial environment during implantation has been proposed as a mechanism contributing to infertility in endometriosis. Nevertheless, the role of cadherin molecule alterations in relation to endometrial receptivity and embryo invasion remains a subject of controversy. METHODS: We investigated the expression patterns of E-cadherin and N-cadherin in the endometria of women with ovarian endometrioma or uterine fibroids and assessed whether they differed from those of healthy women. We enrolled 17 women with ovarian endometrioma, 16 with uterine fibroids, and 6 healthy women. Endometrial tissues were obtained at the mid-secretory phase on days 19-24 of the menstrual cycle. The E-cadherin and N-cadherin mRNA and protein expression levels were measured using quantitative reverse transcriptase polymerase chain reaction and Western blot analysis, respectively. RESULTS: The E-cadherin and N-cadherin mRNA expression levels were higher and lower, respectively, in the endometrium of women with ovarian endometrioma than in those of the controls. In the endometrium of women with uterine fibroids, similar patterns with higher E-cadherin and lower N-cadherin levels were observed compared with that of the controls. Protein expression showed similar patterns. CONCLUSIONS: Our findings revealed higher E-cadherin expression and lower N-cadherin expression in the endometria of women with infertility-related diseases than in those of healthy women in the mid-secretory phase. This suggests a resistance to endometrial receptivity, potentially reflecting mesenchymal-epithelial transition properties.

PD-L1 as a Biomarker for the Efficacy of Durvalumab in Stage III EGFR Mutant NSCLC.

BACKGROUND/AIM: Durvalumab consolidation is less effective in patients with epidermal growth factor receptor mutant (EGFR M+) NSCLC. Studies of durvalumab on EGFR M+ NSCLC as an expression of programmed death-ligand 1 (PD-L1) expression are limited. The purpose of this study was to determine the effect of durvalumab on PD-L1 expression in EGFR M+ patients. PATIENTS AND METHODS: This study included 249 unresectable stage III NSCLC patients treated with durvalumab. The primary outcome was progression-free survival (PFS). Cox multivariate analysis was performed based on EGFR and PD-L1 statuses: EGFR M-, PD-L1 ≥50% (cohort A); EGFR M-, PD-L1 <50% (cohort B); EGFR M+, PD-L1 ≥50% (cohort C); and EGFR M+, PD-L1 <50% (cohort D). RESULTS: Overall, 31 of 249 (12.4%) and 218 of the 249 (87.6%) patients had EGFR M+ and EGFR M- NSCLC, respectively. Median PFSs and OSs did not differ (PFS: 16.6 vs. 18.7 months, p=0.591; OS: 37.4 vs. 35.7 months, p=0.271). Median PFS of cohort A did not significantly differ from the median PFSs of cohorts B and C, but it was significantly longer than the median PFS of cohort D (23.7 vs. 15.2 months, p=0.045). Cox multivariate analysis revealed that cohort D exhibited a worse PFS (adjusted hazard ratio=2.27, 95% confidence interval=1.11-4.66, p=0.025) compared with cohort A. Median OSs were not different between the four cohorts. CONCLUSION: Durvalumab consolidation provided similar benefit in EGFR M+ patients with PD-L1 ≥50% compared with EGFR M- patients. A therapeutic role of durvalumab in patients with EGFR M+, high PD-L1 unresectable stage III NSCLC should be considered.

Clinical application of whole-genome sequencing of solid tumors for precision oncology.

Genomic alterations in tumors play a pivotal role in determining their clinical trajectory and responsiveness to treatment. Targeted panel sequencing (TPS) has served as a key clinical tool over the past decade, but advancements in sequencing costs and bioinformatics have now made whole-genome sequencing (WGS) a feasible single-assay approach for almost all cancer genomes in clinical settings. This paper reports on the findings of a prospective, single-center study exploring the real-world clinical utility of WGS (tumor and matched normal tissues) and has two primary objectives: (1) assessing actionability for therapeutic options and (2) providing clarity for clinical questions. Of the 120 patients with various solid cancers who were enrolled, 95 (79%) successfully received genomic reports within a median of 11 working days from sampling to reporting. Analysis of these 95 WGS reports revealed that 72% (68/95) yielded clinically relevant insights, with 69% (55/79) pertaining to therapeutic actionability and 81% (13/16) pertaining to clinical clarity. These benefits include the selection of informed therapeutics and/or active clinical trials based on the identification of driver mutations, tumor mutational burden (TMB) and mutational signatures, pathogenic germline variants that warrant genetic counseling, and information helpful for inferring cancer origin. Our findings highlight the potential of WGS as a comprehensive tool in precision oncology and suggests that it should be integrated into routine clinical practice to provide a complete image of the genomic landscape to enable tailored cancer management.

Enhancing Prognostication and Treatment Response Evaluation in Primary CNS Lymphoma with 18F-FDG PET/CT.

BACKGROUND: The role of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) in the prognostication and response evaluation of primary central nervous system lymphoma (PCNSL) remains inadequately defined. METHODS: We conducted a retrospective analysis of 268 consecutive newly diagnosed patients with PCNSL between 2006 and 2020. Of these patients, 105 and 110 patients were included to evaluate the prognostic value of baseline and post-treatment 18F-FDG-PET/CT scans, respectively. Tumor uptake was considered positive when it exceeded that of the contralateral brain upon visual assessment. Quantitative analysis of baseline 18F-FDG-PET/CT included measurement of the maximal standardized uptake value (SUVmax), total metabolic tumor volume (TMTV), and total lesion glycolysis (TLG). RESULTS: The median age of the 268 patients was 62 years (range: 17-85), with 55% being male. The median progression-free survival (PFS) was 24.5 months (95% confidence interval [CI], 19.9-29.1), and the median overall survival (OS) was 34.5 months (95% CI, 22.9-46.1). The average SUVmax was 15.3 ± 5.7 and the mean TMTV and TLG were 12.6 ± 13.9 cm3 and 135.0 ± 152.7 g, respectively. Patients with a baseline TMTV ≥17.0 cm3 had significantly shorter OS (12.5 vs. 74.0 months, p=0.011). Post-treatment metabolic response by 18F-FDG-PET/CT significantly predicted PFS (median: 10.5 vs. 46.0 months, p=0.001) and OS (median: 21.0 vs. 62.0 months, p=0.002), whereas anatomic response by contrast-enhanced MRI showed no statistically significant differences in PFS (p=0.130) or OS (p=0.540). CONCLUSION: Baseline TMTV and post-treatment metabolic response, as assessed by 18F-FDG-PET/CT, are significant prognostic factors in patients with PCNSL.

Age at Menarche and Its Association With Adult-Onset Metabolic Syndrome and Related Disorders in Women: A Cross-Sectional Study of a Nationally Representative Sample Over 10 Years.

The prevalence of metabolic syndrome (MetS) as well as related social costs and efforts is increasing. The purpose of this study was to investigate the association between age at menarche and the risk of MetS, obesity, diabetes, and cardiovascular disease (CVD) in women over 30 years, using data from the Korean National Health and Nutrition Examination Survey (2010-2020). The analysis of 30 916 participants showed that early menarche (before 11 years) significantly increased the risk of obesity, diabetes, and MetS compared with the median age of 14 years. Late menarche (after 17 years) was also linked to MetS and related disorders. The relationship between age at menarche (at <10 years and >19 years) and the risk of MetS and related disorders exhibited a reversed J-shaped (し) pattern characterized by a pronounced increased risk among those who experience early menarche, whereas the increased risk associated with late menarche was less consistent. These results will help to decrease the risk of MetS and related disorders by enabling early intervention in early and late menarche age groups.

Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain.

ABSTRACT: Recent technological advancements have revolutionized routine brain magnetic resonance imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease evaluation. This review explores 2 pivotal breakthrough areas: deep learning reconstruction (DLR) and quantitative MRI techniques beyond conventional structural imaging. DLR using deep neural networks facilitates accelerated imaging with improved signal-to-noise ratio and spatial resolution, enhancing image quality with short scan times. DLR focuses on supervised learning applied to clinical implementation and applications. Quantitative MRI techniques, exemplified by 2D multidynamic multiecho, 3D quantification using interleaved Look-Locker acquisition sequences with T2 preparation pulses, and magnetic resonance fingerprinting, enable precise calculation of brain-tissue parameters and further advance diagnostic accuracy and efficiency. Potential DLR instabilities and quantification and bias limitations will be discussed. This review underscores the synergistic potential of DLR and quantitative MRI, offering prospects for improved brain imaging beyond conventional methods.

Mapping Tumor Habitats in IDH-Wild Type Glioblastoma: Integrating MR Imaging, Pathologic, and RNA Data from Ivy Glioblastoma Atlas Project.

BACKGROUND: To spatially validate intratumoral subregions (tumor habitat) using physiologic MRI on pathology of the isocitrate dehydrogenase (IDH)-wildtype whole-glioblastoma sample. METHODS: Data of 20 patients (168 slides) were obtained from the Ivy Glioblastoma Atlas Project. On MRI, tumor habitats were defined using voxel-wise clustering of apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps for contrast-enhancing lesion (CEL) and non-enhancing lesion (NEL). On pathology slides, normalized areas of leading edge (LE), infiltrating tumor (IT), cellular tumor (CT), hypervascular lesion (CThypervascular), and perinecrotic lesion (CTperinecrotic) were obtained. Gross specimen was co-registered on MRI and correlation between pathology-MRI habitats was calculated. RNA sequencing of 67 samples was assessed using 4 Neftel subtypes and further correlated with pathology. RESULTS: Six tumor habitats were identified: hypervascular, hypovascular cellular, and hypovascular hypocellular habitats for CEL and NEL. CT was correlated with hypovascular cellular habitat in CEL (r= 0.238, p =.005). IT was correlated with hypovascular cellular habitat in NEL (r= 0.294, p =.017). CThypervascular was correlated with hypervascular habitat in NEL (r= 0.195, p = .023). CTperinecrotic was correlated with imaging necrosis (r= 0.199, p =.005). Astrocyte-like subtypes were correlated with IT (r= 0.256, p <.001), while mesenchymal-like subtypes were correlated with CTperinecrotic area (r= 0.246, p <.001). CONCLUSION: Pathologically matched tumor subregions were cellular tumor with hypovascular cellular habitat in CEL and infiltrative tumor with hypovascular cellular habitat in NEL. Identification of the most aggressive as well as infiltrative tumor portion can be achieved using non-invasive MRI tumor habitats.

Aster × chusanensis Growth and Phenolic Acid Composition under Different Cultivation Temperatures.

Plants of the Asteraceae family have been cultivated worldwide for economic, medicinal, and ornamental purposes, including genera such as Aster, Helianthus, and Cosmos. Numerous studies examined their secondary metabolites; however, those of Aster × chusanensis, which is a natural hybrid species in South Korea, are unclear, and optimized propagation methods should be identified. We analyzed phenolic acid concentrations in each part of Aster × chusanensis through HPLC. Further, we investigated the growth characteristics and secondary metabolite concentrations under various growth temperatures using division propagation, followed by growing at 20, 25, and 30 °C in a growth chamber. Chlorogenic acid was the primary compound, which was particularly high in the leaves. The growth characteristics did not differ significantly between temperatures, and 30 °C was most efficient for phenolic acid biosynthesis. Our results provide valuable information on optimized propagation and secondary metabolite concentrations under different temperatures of Aster × chusanensis.

Diagnostic and prognostic implications of bacteremia in patients with complicated pleural infection.

Objectives: The clinical significance of bacteremia in patients with complicated pleural infection is still uncertain. We aimed to examine the incidence and clinical significance of bacteremia in patients with complicated pleural infection. Methods: This retrospective study comprised of consecutive patients who received pleural drainage due to complicated parapneumonic effusion or empyema. The clinical, laboratory, and radiologic data and clinical outcome were compared between patients with and without bacteremia. Additionally, the factors associated with overall mortality were evaluated in these patients. Results: Of 341 patients included in the analysis, 25 (7 %) had a positive blood culture. Blood culture testing added 2 % identification of causative pathogen compared to pleural fluid culture alone. By multivariable analysis, radiologic features of cavitary lesion, a RAPID score≥5, and a positive microbial culture in pleural fluid were independently associated with bacteremia. Despite these clinical distinctions, there was ultimately no significant difference in in-hospital mortality between patients with and without bacteremia (3 vs. 4 %, p=1.0). The only factor significantly associated with overall mortality among patients with complicated pleural infections was a higher RAPID score [HR=1.96 (95 % CI=1.35-2.84)]. Conclusions: The rate of bacteremia in patients with complicated pleural infection was 7 %. Blood culture testing demonstrated limited diagnostic yield and had minimal impact on clinical outcomes compared to pleural fluid culture. Therefore, it seems that blood culture testing is more advantageous for specific patients with suspected pleural infection who have cavitary lesions or a RAPID score≥5.

Assessment of imaging risks for recurrence after stereotactic radiosurgery for brain metastases (IRRaS-BM).

BACKGROUND: The identification of viable tumors and radiation necrosis after stereotactic radiosurgery (SRS) is crucial for patient management. Tumor habitat analysis involving the grouping of similar voxels can identify subregions that share common biology and enable the depiction of areas of tumor recurrence and treatment-induced change. This study aims to validate an imaging biomarker for tumor recurrence after SRS for brain metastasis by conducting tumor habitat analysis using multi-parametric MRI. METHODS: In this prospective study (NCT05868928), patients with brain metastases will undergo multi-parametric MRI before SRS, and then follow-up MRIs will be conducted every 3 months until 24 months after SRS. The multi-parametric MRI protocol will include T2-weighted and contrast-enhanced T1-weighted imaging, diffusion-weighted imaging, and dynamic susceptibility contrast imaging. Using k-means voxel-wise clustering, this study will define three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) on T1- and T2-weighted images and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable) on apparent diffusion coefficient maps and cerebral blood volume maps. Using RANO-BM criteria as the reference standard, via Cox proportional hazards analysis, the study will prospectively evaluate associations between parameters of the tumor habitats and the time to recurrence. The DICE similarity coefficients between the recurrence site and tumor habitats will be calculated. DISCUSSION: The tumor habitat analysis will provide an objective and reliable measure for assessing tumor recurrence from brain metastasis following SRS. By identifying subregions for local recurrence, our study could guide the next therapeutic targets for patients after SRS. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov (NCT05868928).

Incorporating Supramaximal Resection into Survival Stratification of IDH-Wildtype Glioblastoma: A Refined Multi-institutional Recursive Partitioning Analysis.

PURPOSE: To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. EXPERIMENTAL DESIGN: This multicenter cohort study included a developmental cohort of 622 patients with IDH-wildtype glioblastomas from a single institution (Severance Hospital) and validation cohorts of 536 patients from three institutions (Seoul National University Hospital, Asan Medical Center, and Heidelberg University Hospital). All patients completed standard treatment including concurrent chemoradiotherapy and underwent testing to determine their IDH mutation and MGMTp methylation status. EORs were categorized into either supramaximal, total, or non-total resections. A novel RPA model was then developed and compared to a previous RTOG RPA model. RESULTS: In the developmental cohort, the RPA model included age, MGMTp methylation status, KPS, and EOR. Younger patients with MGMTp methylation and supramaximal resections showed a more favorable prognosis (class I: median overall survival [OS] 57.3 months), while low-performing patients with non-total resections and without MGMTp methylation showed the worst prognosis (class IV: median OS 14.3 months). The prognostic significance of the RPA was subsequently confirmed in the validation cohorts, which revealed a greater separation between prognostic classes for all cohorts compared to the previous RTOG RPA model. CONCLUSIONS: The proposed RPA model highlights the impact of supramaximal versus total resections and incorporates clinical and molecular factors into survival stratification. The RPA model may improve the accuracy of assessing prognostic groups.

Development of a Simple Scoring System for Predicting Discharge Safety from the Medical ICU to Low-Acuity Wards: The Role of the Sequential Organ Failure Assessment Score, Albumin, and Red Blood Cell Distribution Width.

Despite advancements in artificial intelligence-based decision-making, transitioning patients from intensive care units (ICUs) to low-acuity wards is challenging, especially in resource-limited settings. This study aimed to develop a simple scoring system to predict ICU discharge safety. We retrospectively analyzed patients admitted to a tertiary hospital's medical ICU (MICU) between July 2016 and December 2021. This period was divided into two phases for model development and validation. We identified risk factors associated with unexpected death within 14 days of MICU discharge and developed a predictive scoring system that incorporated these factors. We verified the system's performance using validation data. In the development cohort, 522 patients were discharged from the MICU, and 42 (8.04%) died unexpectedly. In multivariate analysis, the Sequential Organ Failure Assessment (SOFA) score (odds ratio [OR] 1.26, 95% confidence interval [CI] 1.13-1.41), red blood cell distribution width (RDW) (OR 1.20, 95% CI 1.07-1.36), and albumin (OR 0.37, 95% CI 0.16-0.84) were predictors of unexpected death. Each variable was assigned a weighted point in the scoring system, and the area under the curve (AUC) was 0.788 (95% CI 0.714-0.855). The scoring system was performed using an AUC of 0.738 (95% CI 0.653-0.822) in the validation cohort of 343 patients with 9.62% of unexpected deaths. When a cut-off of 0.032 was applied, a sensitivity and a specificity of 81.8% and 55.2%, respectively, were achieved. This simple bedside predictive score for ICU discharge uses the SOFA score, albumin level, and RDW to aid in timely decision-making and optimize critical care facility allocation in resource-limited settings.

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology.

OBJECTIVE: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). MATERIALS AND METHODS: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. RESULTS: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. CONCLUSION: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

The tidyomics ecosystem: enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. Here we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

The tidyomics ecosystem: Enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.