Fast inverse planning in radiosurgery planning is limited by an excessive number of isocenters, which is clinically hypothesized to be driven by the morphological irregularity of the target volume. This retrospective cross-sectional study aimed to empirically evaluate this hypothesis in vestibular schwannoma cases.

Consecutive patients diagnosed with vestibular schwannoma and receiving Gamma Knife radiosurgery in 2023 were included, and their treatment plans designed using the GammaPlan planning system were collected. Morphological irregularity–related parameters, including standard sphericity (SS), volume ratio sphericity (VRS), and the coefficient of variance of diameters (DCV), were calculated based on parameters provided by the system. Basic demographic and clinical data were collected to evaluate their impact on sphericity. The effects of different sphericity assessment methods on common treatment plan parameters were analyzed.

Treatment plans of 280 patients with vestibular schwannoma were collected. The SS, VRS, and DCV of the tumors were 0.85 (0.77–0.91), 0.46 ± 0.16, and 0.22 (0.14–0.34), respectively. Multivariate analysis showed that lesion volume, acoustic neuroma consensus on systems for reporting results grade, and age were significant factors influencing sphericity. All other planning parameters, except prescription dose and homogeneity index, were significantly correlated with sphericity. DCV was more closely correlated with SS than with VRS.

DCV may serve as a simple quantitative metric of target morphological irregularity, showing strong consistency with SS. Incorporating morphological irregularity into Gamma Knife treatment plan evaluation may help improve future planning strategies and support optimization of isocenter utilization.

The intestinal barrier, a critical interface between the body and the external environment, is essential for maintaining internal homeostasis. Comprising mechanical, chemical, immune, and biological components, its dysfunction underpins multiple gastrointestinal pathologies. Circular RNAs (circRNAs), covalently closed non-coding RNAs, have emerged as central regulators of gut barrier homeostasis. This review synthesizes advances in circRNA roles in intestinal stem cell renewal, apoptosis-proliferation balance, microbiome interactions, and immune regulation. Key findings highlight circRNA networks operating via competitive endogenous RNA mechanisms, protein interactions, and translational potential to influence barrier function. We further discuss circRNAs as diagnostic biomarkers in inflammatory bowel disease and their therapeutic potential in barrier-related pathologies. Advances in RNA nanotechnology (e.g., lipid nanoparticles) and synthetic biology position engineered circRNAs as next-generation therapies for precision intervention in gastrointestinal disorders. Importantly, this review also critically examines the current limitations of these translational approaches, including delivery challenges, safety considerations, and the preliminary nature of many preclinical findings, providing a balanced perspective on the path from bench to bedside.

Normalization can standardize and improve machine learning (ML) performance on omics data. However, it is unclear whether normalization is associated with overfitting (i.e., worse cross-dataset performance than intra-dataset performance). Therefore, we aimed to examine associations of normalization and regularization with overfitting of ML on omics data.

Using three paired transcriptomic and clinical datasets (lung adenocarcinoma: the Cancer Genome Atlas (TCGA)/Oncology Singapore; melanoma: TCGA/Dana-Farber Cancer Institute; glioblastoma: TCGA/Clinical Proteomic Tumor Analysis Consortium), we applied ANOVA-based gene selection methods, six normalization methods, and six ML models to classify cancer patients’ deaths. Balanced accuracy (BA) and area under the curve (AUC) in intra- and cross-dataset settings were compared using inferential analyses.

Normalization consistently improved intra-dataset performance (median BA/AUC changes: 0.035–0.214/0.115–0.279) on all data, particularly with Z_Raw, but decreased or slightly increased cross-dataset performance (median BA/AUC changes: −0.029–0.079/0.029–0.064). Least Absolute Shrinkage and Selection Operator (LASSO) model without normalization consistently outperformed most of the ML models in cross-dataset testing across cancer types. ML models on all and molecular-alone data showed similar best performances.

Normalization increases ML’s intra-dataset performance and overfitting in three paired cancer transcriptomic and clinical datasets. Regularized models such as LASSO appear to mitigate overfitting and achieve robust cross-dataset performance. Therefore, cross-dataset evaluation and regularized models are recommended to assess and reduce overfitting, while normalization should be used cautiously. Adding clinical data seems to have little impact on ML models’ performance. However, future work on other diseases and datasets is warranted.

Mild traumatic brain injury (mTBI) represents the majority of head injury presentations in emergency departments (EDs), yet only a minority of patients have acute intracranial lesions on computed tomography (CT). This leads to widespread use of unnecessary CT scans. Point-of-care (POC) biosensing, defined as analytical testing performed at or near the site of patient care, offers a promising solution to this dilemma by enabling rapid biomarker quantification to inform CT decision-making. This review aims to evaluate POC-compatible biosensing strategies for ultra-early mTBI triage, with emphasis on platforms, matrix effects, and benchmarking aligned with CT-based decision-making. Two key precedents support this approach: (1) the integration of S100B into Scandinavian Neurotrauma Committee guidelines, which has demonstrated the potential for safe reduction of CT scans, and (2) the regulatory clearance of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) testing to rule out the need for head CT in adults with suspected mTBI (Glasgow Coma Scale 13–15) when serum is collected within 12 hours of injury. Accordingly, this review focuses on the most implementable use case for mTBI, namely CT triage/rule-out. It synthesizes the current biomarker landscape (S100B, GFAP, UCH-L1), analyzes POC-suitable sensing modalities, and proposes a practical validation and benchmarking framework aligned with this intended use. A critical component is interference testing and real-world sample robustness, including vulnerabilities such as hemolysis-related elevation of UCH-L1. In conclusion, the most reliable path for biosensor translation in mTBI is to anchor development and validation to the ED CT-triage use case, emphasizing decision-point robustness and resilience to real-world sample variability over pure analytical sensitivity.

Glioblastoma remains a highly challenging malignancy with a pronounced tendency for recurrence. The hypoxic microenvironment is a key contributor to its therapy resistance. Hyperbaric oxygen therapy (HBOT), which elevates tissue oxygen pressure and reverses hypoxia, exhibits a “dual effect” in glioblastoma management. This review aims to evaluate the therapeutic potential of HBOT in glioblastoma by examining its multifaceted effects on tumor biology and treatment response. On one hand, it enhances radiosensitivity through reactive oxygen species generation, increases chemotherapy efficacy by augmenting cytotoxicity and improving vascular perfusion, and remodels the tumor microenvironment via vessel normalization, edema reduction, and immune cell modulation. Furthermore, HBOT attenuates cancer stem cell properties by downregulating stemness markers and inhibiting self-renewal capacity. On the other hand, HBOT may also promote tumor progression: oxidative stress can induce genomic instability, while concomitant activation of HIF-, NF-κB-, and VEGF-mediated pro-survival pathways may facilitate malignant cell adaptation and proliferation. Given these opposing considerations, the clinical application of HBOT in glioblastoma management remains exploratory. In conclusion, future research should focus on optimizing HBOT protocols. In addition, exploring combination with other therapeutic approaches is equally important. These efforts are essential for the safe and effective integration of HBOT into comprehensive treatment strategies for glioblastoma.

Development of mixed histiocytosis (Langerhans cell histiocytosis (LCH))/Erdheim–Chester disease (ECD)) after treatment in patients with an initial skull LCH lesion has not been well recognized. An elderly woman initially developed LCH at the left temporal bone, preceded by polyuria and polydipsia five years earlier; the lesion was surgically removed. Two years thereafter, she experienced her first LCH relapse with a right parietal skull lesion, in which a BRAF V600E mutation was confirmed, and chemotherapy was initiated. After a second LCH relapse involving the left parietal bone, the patient presented with a third relapse at the L2 vertebra. This lesion was pathologically diagnosed as mixed histiocytosis (LCH/ECD), resulting in refractoriness to conventional chemotherapy, and was successfully treated with targeted therapy using BRAF and MEK inhibitors. Spinal mixed histiocytosis (LCH/ECD) may develop following relapses of skull LCH after chemotherapy, for which targeted therapy could be effective.

Vulvovaginal candidiasis, an infection caused by an abnormal proliferation of Candida species in the vagina and vulva, is particularly relevant, affecting up to 75% of women of reproductive age. Because of antifungal drug resistance, a significant number of plants are used to treat vaginal candidoses in Cameroon. Thus, the scientific validation of the use of these plants in treating candidiasis is valuable. This study sought to identify medicinal plants used to treat vaginal infections in the Dschang district and evaluate the antifungal activity of the most promising plants on five Candida species.

The ethnobotanical survey was conducted in Dschang (Menoua Division, West Cameroon) through individual interviews using a semi-structured questionnaire. Extracts from seventeen plants were obtained by maceration using water or a water–ethanol solution (3:7; v/v). Antifungal activity was evaluated using the microdilution method.

Forty-eight plants belonging to 33 families were identified as treating vaginal infections. Decoction and formulation of ovules were the prevalent modes of plant preparation, with leaves and bark being the predominant plant organs used. Out of thirty-four extracts tested, two (CSEHAlc and MIEHAlc) showed antifungal activity, with minimum inhibitory concentrations ranging from 0.315 to 2.5 mg/mL. The determination of the minimum fungicidal concentrations revealed the fungicidal orientation of these bioactive extracts.

This study identifies medicinal plants used to treat vaginal infections in Dschang and their modes of preparation. The in vitro antifungal screening of selected plants indicated Mangifera indica and Canarium schweinfurthii as the anti-Candida plants that can be further exploited for antifungal drug discovery.

The bromodomain and extra-terminal domain (BET) protein family, particularly BRD4, is critical for the control of oncogenic transcriptional programs in solid tumors. Although initial-generation BET inhibitors, such as JQ1, molibresib, and birabresib, have demonstrated preclinical efficacy in repressing MYC-dependent pathways, their clinical translation has been hampered by low monotherapy activity, pharmacokinetic heterogeneity, and dose-limiting toxicities. This review aims to update the mechanistic foundations, clinical trial results, and development of therapeutic approaches to BET inhibition in solid tumors, outlining its evolving role in the next generation of cancer treatment strategies. Various clinical trials in different phases have demonstrated heterogeneous responses among solid tumor types, with greater effects in NUT carcinoma and castration-resistant prostate cancer. Resistance mechanisms, including BRD4 isoform switching and compensatory signaling activation, emphasize the need for advanced and innovative BET-targeting modalities. BD2-selective BET inhibitors and proteolysis-targeting chimeras are likely to overcome these limitations by increasing target specificity and reducing systemic side effects. In addition, combination strategies, such as PARP inhibitors, AR antagonists, and immune checkpoint blockade, have synergistic potential to augment anticancer activity. In conclusion, this review provides a comprehensive overview of the advances, challenges, and future directions of BET bromodomain inhibition in solid tumors.