Intraosseous (ectopic) meningiomas are rare extradural tumors arising within the calvarial bone and account for <1% of all meningiomas. Because their imaging appearance may range from osteolytic to sclerotic or mixed patterns, they can mimic primary bone tumors or metastatic lesions and lead to diagnostic uncertainty.

A 50-year-old woman presented with a gradually enlarging right temporoparietal scalp mass associated with mild headache for 5 years. The lesion caused marked cosmetic asymmetry without neurological deficit.

Serial cranial computed tomography demonstrated an expansile right temporoparietal intraosseous calvarial lesion that enlarged from 5.8 × 5.1 × 1.8 cm in 2019 to 17.6 × 14.3 × 4.4 cm in 2024. The mass showed a heterogeneous mixed osteolytic-sclerotic pattern with diploic expansion, cortical thinning, and irregular inner table extension abutting the dura, without a definite intradural component. Histopathological and immunohistochemical evaluation established the diagnosis of ectopic intraosseous meningioma.

The patient underwent right temporoparietal craniectomy with complete excision of the involved calvarial bone. The dura appeared uninvolved intraoperatively and was preserved.

Postoperative recovery was uneventful, with no neurological deficit and marked cosmetic improvement. Histopathological analysis showed a benign meningothelial neoplasm with epithelial membrane antigen and progesterone receptor positivity and a low Ki-67 labeling index of approximately 1%. At 1-year follow-up, imaging showed no evidence of recurrence or regrowth.

Giant intraosseous meningiomas may demonstrate striking radiologic aggressiveness and rapid calvarial expansion despite benign histology and a low proliferative index. They should be considered in the differential diagnosis of large calvarial masses. Complete surgical excision with preservation of intact dura, when appropriate, may provide favorable early clinical and cosmetic outcomes, although longer follow-up is required to assess long-term tumor control.

The aim of this study was to compare the clinical characteristics, treatments and outcomes of immunocompromised patients with viral severe acute respiratory infections (SARI), to those of immunocompetent patients admitted to an intensive care unit (ICU) across Australia.

Retrospective analysis of a prospective, nation-wide, observational registry of 46 ICUs from June 2022 to August 2025. Critically ill adults (age ≥ 18) with laboratory-confirmed viral SARI were included. Immunocompromised status was defined by the presence of any one of the following: chronic immunosuppression, malignant neoplasm, AIDS/HIV, or organ transplantation. Associations between immunocompromised status and in-hospital mortality were evaluated using mixed-effects logistic regression models. Competing risks regression (Fine and Gray models) was used to assess the association between immunocompromised status and risk of hospital discharge within 30 days.

Among 4,703 patients with viral SARI who were admitted to ICUs, immunocompromised patients accounted for 908 (19.3%) cases. Immunocompromised patients were older (median age 67 vs. 62 years), more comorbid (31.4% vs. 22.5% with ≥ 3 comorbidities), and more frequently admitted with COVID-19 (51.1% vs. 34.5%); (p < 0.001 for all). Immunocompromised patients received more treatment, including antivirals (67.3% vs. 57.7%), and corticosteroids (81.7% vs. 72%) and had higher in-hospital mortality (22.7% vs. 13.1%); (p < 0.01 for all). After adjusting for demographics, comorbidities, vaccination status (where available), ICU interventions and treatments, immunocompromised status was independently associated with nearly double the odds of in-hospital mortality (adjusted OR 1.93, 95% CI 1.57-2.37).

In this study, we found that immunocompromised patients accounted for approximately one-fifth of critically ill viral SARI patients and had nearly twice the odds of in-hospital mortality, when compared to those that were immunocompetent. Targeted public health campaigns and improved treatment strategies may be warranted for this population.

Ovarian steroid cell tumors-not otherwise specified (SCT-NOS) is a rare category of sex cord-stromal tumor, however, its pathophysiology is unclear. A comprehensive cellular atlas of ovarian SCT-NOS remains lacking.

We reported a case of a 41-year-old woman with hyperandrogenism for whom histopathological analysis confirmed the presence of ovarian SCT-NOS. This study utilized single-cell RNA sequencing in a case of ovarian SCT-NOS.

Seven cell types, including four keratin 19 (KRT19)⁺ steroidogenic cell subtypes, were identified in the tumor microenvironment. We detected aberrant gene expression across various cell types in ovarian SCT-NOS. KRT19⁺ steroidogenic cells were enriched in genes involved in ovarian steroidogenesis and steroid biosynthesis pathways, which was consistent with the pathobiology of hyperandrogenism. Moreover, we revealed distinct immune cell types in the tumor microenvironment. Five immune cell types within the tumor microenvironment were identified, among which tumor-associated macrophage (TAM) and dendritic cell (DC) were the predominant immune cells.

This transcriptomic analysis revealed distinct cell types and key genes within the tumor microenvironment, offering insights into the cellular heterogeneity and molecular mechanisms of ovarian SCT-NOS, thereby enhancing the understanding and encouraging further investigations into ovarian SCT-NOS.

The treatment with immune checkpoint inhibitors is not universally effective, and the efficacy is challenging to predict using a single biomarker. Breast cancer (BC) cells develop within a complex microenvironment, which includes tumor cells, immune cells, and extracellular matrix, and they may interact through paracrine signaling. Elucidating the mechanisms of immune microenvironment regulation and intercellular interactions in BC is fundamental for screening efficacy markers and developing new immunotherapeutic targets. Based on the immune phenotype cellular infiltration characteristics and transcriptomic changes, we constructed a two-way orthogonal partial least square (O2PLS) model to identify immune cell infiltration (ICI) genes, quantitatively characterizing the immune microenvironment within BC to predict patient prognosis, select sensitive populations for immunotherapy, and provide a theoretical basis for the combination of immunotherapy with radiotherapy and chemotherapy. We described the T cell differentiation trajectories and intercellular communication landscapes and revealed the synergistic effects of receptors and ligands (CXCL9-CXCR3, CCL5-ACKR1, and GZMA-F2R) on the immune microenvironment and prognosis. These findings may contribute to elucidating the factors that shape the immune microenvironment and identifying new therapeutic targets.

Brg1 is a core ATPase subunit of the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodeling complex that regulates DNA accessibility for RNA polymerase II (Pol II), transcription factors, and DNA repair enzymes. Phosphoproteomic profiling of highly malignant ovarian clear cell carcinoma (OCCC) cell lines revealed reduced levels of several SWI/SNF components and decreased Brg1 phosphorylation within its histone-binding region. Prior work showed that phosphorylation-mimic and phosphorylation-deficient mutants alter chromatin-silencing factors, producing chromatin condensation and decondensation, respectively. Here, we performed RNA-seq in Brg1-deficient JHOC-5 cells and in isogenic cells expressing Brg1-WT, phosphorylation-mimic brg1-S¹⁴⁵²D, or phosphorylation-deficient brg1-S¹⁴⁵²A. PCA and hierarchical clustering separated brg1-S¹⁴⁵²A from the other lines, indicating a strong transcriptional impact of Ser¹⁴⁵² dephosphorylation. JHOC-5 and brg1-S¹⁴⁵²A shared altered expression of Pol II-promoter-regulated genes. Apoptosis genes (BCL2, FGFR2, ZC3H12A, and NFKBIA) showed reciprocal expression between brg1-S¹⁴⁵²D and brg1-S¹⁴⁵²A, consistent with increased and decreased apoptosis, respectively. Genes linked to cell adhesion/migration and neuronal development also differed, accompanied by reduced cell circularity in brg1-S¹⁴⁵²A. Overall, Brg1 phosphorylation at Ser¹⁴⁵² shapes SWI/SNF-mediated chromatin remodeling to regulate transcriptional programs controlling apoptosis and cell morphology.

To enable early warning of severe 2019 coronavirus disease in elderly patients, this study collected routine laboratory indicators and clinical parameters to construct and validate clinical models to predict the risk of severe disease. A total of 123 elderly 2019 coronavirus disease patients (68 non-severe and 55 severe) were retrospectively enrolled and randomly split into training and test sets. Predictive variables were selected via univariate analysis and stepwise logistic regression (LR) with variance inflation factor testing. Four models - LR, Random Forest, Support Vector Machine (SVM), and eXtreme Gradient Boosting Tree - were built. Model stability was assessed with 100 rounds of Bootstrap resampling. Performance was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis in the test set. Five variables were selected: lymphocyte percentage, red blood cell count, total iron-binding capacity, unsaturated iron-binding capacity, and red cell distribution width. Multivariate LR identified lymphocyte percentage, red blood cell count, and total iron-binding capacity as protective factors, while unsaturated iron-binding capacity and red cell distribution width as risk factors. Bootstrap showed SVM and LR had superior stability. In the test set, SVM achieved the highest area under the curve (best discrimination); Random Forest showed best calibration; LR and eXtreme Gradient Boosting yielded slightly higher net benefits. Based on routine laboratory indicators, 4 prediction models were constructed and compared. These models can quantify severe risk using routine data early after admission, demonstrating strong clinical application potential.

Although pulse oximetry (SpO2) is useful for real-time monitoring of oxygen saturation, it may not predict which patients will subsequently develop hypoxemia and require oxygen therapy. Laboratory biomarkers collected at admission may therefore facilitate earlier risk stratification and guide clinical decision-making. This study aimed to evaluate the association between the lactate dehydrogenase-to-albumin ratio (LAR) and oxygen therapy requirement in hospitalized patients with COVID-19. This retrospective study included hospitalized patients with COVID-19 admitted to the ICU of the Cancer Center of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, between February and March 2020. Patients were categorized into a non-oxygen therapy group (n = 40) and a group requiring oxygen therapy (n = 21) according to the requirement for supplemental oxygen therapy (SpO2 < 93%). Univariate and multivariate logistic regression analyses were performed to identify factors associated with oxygen therapy requirement. Receiver operating characteristic (ROC) curves were used to assess the predictive performance of the identified factors. Sixty-one hospitalized patients with COVID-19 (mean age 63.18 ± 11.01 years; 22 males [36.07%]) were included, among whom 21 required oxygen therapy. Multivariable logistic regression analysis showed that the lactate dehydrogenase-to-albumin ratio (LAR; OR = 2.06, 95% CI: 1.00-4.21, P = .049) was independently associated with oxygen therapy requirement. ROC analysis demonstrated that LAR had an area under the curve (AUC) of 0.762 with 81.0% sensitivity and 72.5% specificity at an optimal cutoff value of 5.240. A combined model incorporating LAR, lymphocyte count, cough, d-dimer, bilateral lung involvement, chest tightness, and shortness of breath achieved an AUC of 0.818 with 76.2% sensitivity and 80.0% specificity. LAR was independently associated with oxygen therapy requirement in hospitalized patients with COVID-19 and may help clinicians identify patients at higher risk of requiring oxygen therapy, thereby supporting early triage and optimal allocation of medical resources.

Chronic obstructive pulmonary disease (COPD) is a leading cause of global mortality and has been linked to systemic inflammation and insulin resistance. The C-reactive protein-triglyceride-glucose index (CTI), a composite biomarker integrating inflammatory and metabolic components, may reflect these intertwined pathways. However, its association with COPD in the general population remains unclear. In this cross-sectional study, we analyzed data from 3442 adults aged ≥20 years participating in the National Health and Nutrition Examination Survey 2015 to 2018. Weighted multivariable logistic regression models were used to assess the association between CTI and self-reported COPD. Dose-response relationships were evaluated using restricted cubic splines. Subgroup and interaction analyses were performed across demographic and socioeconomic factors. Receiver operating characteristic (ROC) curves were constructed to compare the discriminatory ability of CTI with individual biomarkers. Mean CTI levels were higher among participants with COPD compared to those without COPD (9.29 vs 8.95; P < .001). After adjustment for potential confounders, participants in the highest CTI quartile had a modestly increased likelihood of COPD compared with those in the lowest quartile (odds ratio = 1.04, 95% confidence interval: 1.02-1.07). A linear dose-response association was observed (P for nonlinearity = .319). A statistically significant interaction by sex was identified, with a stronger association observed in males. In ROC curve analysis, CTI demonstrated slightly higher discriminatory ability (area under the ROC curve = 0.630) than individual biomarkers, although overall predictive performance remained limited. In this nationally representative cross-sectional analysis, higher CTI levels were independently associated with COPD prevalence, with a modest effect size. While CTI showed slightly improved discriminatory performance compared with single biomarkers, its overall predictive capacity was limited. Prospective studies are warranted to clarify its potential role in COPD risk assessment.

Sepsis, acute kidney injury (AKI), and acute respiratory distress syndrome (ARDS) are severe conditions commonly seen in the intensive care unit (ICU). The study was designed to evaluate the influence of single-organ dysfunction (AKI or ARDS) and 2-organ dysfunction (AKI combined with ARDS) on the 30-day mortality risk in patients with sepsis. Data originated from a prospective multicenter cohort involving 18 Chinese ICUs, which enrolled patients with sepsis following ICU admission. Patients were stratified into 4 groups according to their organ status within 7 days of sepsis onset: those who did not develop AKI or ARDS (non-AKI and non-ARDS group), those who developed AKI but not ARDS (AKI and non-ARDS group), those who developed ARDS but not AKI (ARDS and non-AKI group), and those who developed both AKI and ARDS (AKI and ARDS group). The primary endpoint was defined as mortality within 30 days of sepsis diagnosis. Furthermore, a survival analysis was conducted among the 4 groups. A total of 2175 septic patients were eligible, including 273 cases (12.6%) in the non-AKI and non-ARDS group, 435 cases (20.0%) in the AKI and non-ARDS group, 560 cases (25.7%) in the ARDS and non-AKI group, and 907 cases (41.7%) in the AKI and ARDS group. Kaplan-Meier analysis revealed that the survival probabilities of the 4 groups at 30 days after sepsis diagnosis were 85.6%, 70.6%, 58.9%, and 50.8%, respectively (P < .001). Compared with the patients in the non-AKI and non-ARDS group, a landmark analysis showed that the average adjusted hazard ratios for the 30-day mortality risk for the AKI and non-ARDS, ARDS and non-AKI, and AKI and ARDS groups were 2.19 (95% confidence interval [CI]: 1.26-3.82, P = .006), 2.92 (95% CI: 1.73-4.93, P < .001), and 3.09 (95% CI: 1.85-5.15, P < .001), respectively. Septic patients complicated with AKI and ARDS had a poor prognosis, with a 30-day survival rate of only 50.8% after the diagnosis of sepsis.

Traumatic pneumothorax (TP) is considered a prevalent pathology involved in chest trauma. Higher the number of accompanying pathologies, higher the rates of prolonged length of hospital stays and mortality. This study aimed to investigate the effect of accompanying pathologies on mortality in patients with TP. This study followed a single-center retrospective design. Patients with trauma who were diagnosed with pneumothorax in a tertiary emergency department in Turkey between January 1, 2022 and December 31, 2023, were included in the study. Logistic regression analysis was used to investigate the factors affecting mortality. During the study period, 252 patients were diagnosed with TP. The median age of these patients was 56 years, and the median length of hospital stay was 4 days. The most prevalent accompanying pathologies in patients with TP included rib fracture, hemothorax, and fracture of any of the extremities. The most prevalent pathologies associated with mortality were hemothorax, lung contusion, lower extremity fracture, traumatic brain injury and abdominal injury (P = .007, P = .036, P = .027, P = .005, and P = .002, respectively). Accompanying pathologies associated with an increased risk of mortality included bilateral pneumothorax, traumatic brain injury and abdominal injury (P < .001, P = .035, and P = .001, respectively). TP is considered one of the most prevalent chest traumas that can cause mortality. While accompanying pathologies such as hemothorax, lung contusion, and lower extremity fractures are associated with higher mortality in univariate analyses, they do not independently predict death. The independent predictors that substantially increase the risk of mortality in patients with TP are bilateral pneumothorax, traumatic brain injury, and abdominal injury.