Paraptosis, a distinct form of programmed cell death, has attracted significant attention in cell biology due to its unique characteristics and potential therapeutic implications. Unlike classical apoptosis or necrosis, paraptosis is induced by specific stimuli and is marked by cell swelling, organelle distension, and the absence of nuclear condensation. This review explores the morphological changes in intracellular small organelles during paraptosis, including mitochondria, endoplasmic reticulum (ER), Golgi apparatus, lysosomes, and autophagosomes. Mitochondria undergo swelling and cristae loss, which impair adenosine triphosphate production and disrupt calcium homeostasis. The ER expands and experiences calcium ion imbalance, triggering ER stress and the unfolded protein response. The Golgi apparatus undergoes vasicularization and structural disassembly, impacting protein glycosylation and secretion. Lysosomal membrane instability leads to the release of acidic hydrolases, exacerbating cellular damage, while autophagosome formation is characterized by the development of double-membrane vesicles and their fusion with lysosomes. These organelle-specific changes are tightly regulated by complex intracellular signaling pathways and provide valuable insights into the mechanisms underlying paraptosis. Understanding these processes offers a theoretical foundation for developing novel therapeutic strategies targeting diseases characterized by dysregulated cell death. In tumor therapy, paraptosis, as a form of immunogenic cell death, can overcome tumor cell resistance to traditional apoptosis-inducing drugs and enhance the efficacy of immunotherapy. In neurodegenerative diseases, mild paraptosis is linked to tumorigenesis, whereas severe paraptosis is associated with neurodegenerative diseases such as Alzheimer’s disease. The mechanisms of action and potential therapeutic value of paraptosis in these disease contexts continue to be actively investigated.

IntroductionBone metastases are a hallmark of castration-resistant prostate cancer (CRPC), occurring in approximately 84% of patients. These metastases result in severe skeletal-related events (SREs), such as pathological fractures, spinal cord compression, and the need for radiation therapy or surgery.

Objective: This meta-analysis evaluates the impact of bisphosphonates (zoledronic acid [ZA]) and receptor activator of nuclear factor-κB ligand-inhibitors (denosumab) as adjunctive therapies for patients with prostate cancer who have developed bone metastases.

Methods: A systematic and rigorous methodology was followed by adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines to ensure transparency and reliability. A comprehensive search was conducted across medical databases and relevant publications to identify studies comparing denosumab and ZA in managing skeletal complications in patients with CRPC. Inclusion criteria required studies to report outcomes such as SREs, symptomatic skeletal events (SSEs), bone metastasis-free survival (BMFS), progression-free survival (PFS), adverse events, and cost implications. Data extraction was performed using standardized templates to collect demographic, clinical, and economic data.

Results: The meta-analysis demonstrated that denosumab was superior to ZA in reducing SREs and SSEs in patients with CRPC. The total incidence of SREs was significantly lower with denosumab (40.7%) compared to ZA (59.3%, p=0.009). Similarly, the incidence of SSEs was reduced to 47.2% with denosumab, compared to 52.8% with ZA (p=0.029). In addition, denosumab extended BMFS by 4.2 months (33.2 vs. 29.5 months, p=0.031) and PFS by 2.4 months (21.7 vs. 19.3 months, p=0.027). However, overall survival was comparable between the two treatments. Adverse events were slightly more frequent with denosumab (93.1% vs. 91.4%), as well as higher rates of hypocalcemia (2.2% vs. 1.46%) and osteonecrosis of the jaw (ONJ) (2.8% vs. 2.41%).

Conclusion: This meta-analysis demonstrates that denosumab is superior to ZA in reducing the incidence and delaying the onset of SREs and SSEs in patients with CRPC and bone metastases. Denosumab also extends BMFS, providing an additional clinical advantage. However, these benefits come with a higher risk of adverse events such as hypocalcemia and ONJ, as well as significantly increased costs. While ZA remains an effective treatment, denosumab may be the preferred option for patients at higher risk of SREs or those who can tolerate its adverse effects and cost.

Lung cancer is a malignant tumor originating in the bronchi, trachea, or other lung tissues. Despite significant advances in treatment, clinical outcomes remain unsatisfactory due to factors such as chemotherapy and heterogeneity. Natural killer (NK) cells are a key component of the innate immune system. A reduction in NK cell number or dysfunction can lead to immune evasion by tumor cells, contributing to malignant progression. In lung cancer, NK cell imbalance is closely associated with tumor immune escape mechanisms, making the modulation of NK cell activity a promising therapeutic strategy. This review examines the role of NK cell dysfunction in lung cancer immune escape and highlights recent advances in NK cell-based immunotherapy. Therapeutic approaches include cell-based NK therapies, cytokine stimulation, immune checkpoint inhibitors, monoclonal antibodies mediating antibody-dependent cell-mediated cytotoxicity, signal pathway-targeted agents, and bioactive compounds derived from medicinal and edible plants. Furthermore, emerging clinical evidence demonstrates the effectiveness of NK cell immunotherapy in improving treatment outcomes in lung cancer patients. This article aims to provide a comprehensive overview of current strategies to enhance NK cell function and presents novel therapeutic avenues to support future lung cancer interventions.

Defective viral genomes (DVGs) are altered forms of viral genomes generated during error-prone replication, particularly in RNA viruses. This review examines the current understanding of DVG biology, its mechanisms of action, and its translational potential as an antiviral agent, in vector control strategies, zoonotic disease spillover prevention, and vaccine development. DVGs modulate virus-host interactions by interfering with the replication of full-length viruses and/or activating innate immune responses. Both naturally occurring and synthetic DVGs could suppress viral loads, reduce disease severity, and enhance the efficacy of inactivated and live attenuated vaccines. DVG-derived particles, such as defective interfering particles and therapeutic interfering particles, have shown broad-spectrum antiviral activity against numerous viruses in vitro and in vivo. By reducing viral replication in both insect and animal hosts, DVGs may block the vector transmission cycle and prevent spillover between species, thus playing a key role in controlling arthropod-borne viruses and zoonotic diseases. However, DVGs could contribute to viral persistence, which may hamper their clinical application. Additional challenges include standardizing DVGs production, understanding their effects on adaptive immunity, and ensuring their safety profile as vaccines or vaccine adjuvants.

The evident concordance between tissue and liquid biopsies in hepatocellular carcinoma (HCC), a prevalent and lethal cancer worldwide, has positioned liquid biopsy as a valuable non-invasive tool for the clinical management of HCC. Among its analytes, circulating cell-free DNA (cfDNA) has recently gained significant attention as a key biomarker for HCC. This review provides an overview of recent advancements in the use of cfDNA for the detection and diagnosis, treatment decision-making, and recurrence surveillance of HCC. The various merits of cfDNA underscore its strong potential for clinical integration in HCC. However, there is also an emerging imperative that arises from the varying cfDNA-related methodologies, which demonstrate disparate outcomes across studies, emphasizing the importance of systematic evaluation and standardization to ensure consistent and equitable patient care.

Autologous fat grafting is commonly used in breast reconstruction due to its biocompatibility and ability to restore natural contours. However, unpredictable fat resorption often requires multiple procedures. Platelet-rich plasma (PRP) has been introduced as a biological enhancer to improve graft retention, but the evidence regarding its efficacy remains inconsistent. To systematically evaluate and compare the clinical and esthetic outcomes of PRP-enhanced autologous fat grafting versus fat grafting alone in breast reconstruction procedures. This meta-analysis included four clinical studies published between 2011 and 2024, encompassing a total of 242 female patients (108 in the PRP group and 134 in the fat-only group). Data were extracted on tumor grade, prior radiation therapy, number of grafting sessions, fat necrosis, and satisfaction levels. PRP-enhanced fat grafting demonstrated significantly better fat retention, with 66.1% of patients requiring only one grafting session compared to 44% in the control group (p=0.016). Surgeon and patient satisfaction scores were notably higher in the PRP group (p<0.05). However, the incidence of fat necrosis was elevated in the PRP group (39.25%) compared to the control group (24.7%, p=0.006), particularly in irradiated tissues. Subgroup analysis showed optimal outcomes in non-irradiated, centrally located graft sites and patients with Grade II tumors. PRP-enhanced autologous fat grafting significantly improves fat retention and overall satisfaction in breast reconstruction, especially in non-irradiated tissues. Nonetheless, the increased risk of fat necrosis warrants cautious application and further refinement in PRP preparation techniques and patient selection.

Introduction: Breast cancer is rising among younger women, many of whom have dependent children.

Objective: The purpose of this scoping review is to synthesize evidence on the dynamics and impacts of breast cancer on the maternal/parental role and the dependent children of affected women.

Method: A review of 19 qualitative and quantitative studies from 2002 to 2023 was conducted using PubMed and Scopus, supplemented by Google Scholar searches, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Extension for Scoping Reviews protocol. Included studies examined the maternal role and the experiences of dependent children.

Results: Mothers with breast cancer experience increased anxiety and emotional burden. Children and adolescents exhibit emotional and behavioral reactions, with adolescents bearing a greater burden. Open communication and psychosocial support reduce distress. However, only a small proportion receives family-centered support.

Conclusion: Breast cancer significantly affects both the patient and her family. This reinforces the need to strengthen psychosocial support services with a family-focused approach. Early assessment of psychological needs and integration of family-centered interventions in psycho-oncological care are essential for improving patients’ emotional well-being and treatment outcomes.

Introduction: Etomidate is a widely used anesthetic agent. Although its abuse had been reported in scant reports, there has been a recent surge in cases, raising concerns for public safety.

Objective: This review aims to retrospectively analyze case reports of fatal etomidate abuse.

Methods: A literature search on MEDLINE/PubMed, Web of Science, Scopus, the Chinese Biomedical Database, and Google Scholar was conducted. Search terms were developed in relation to the review’s aim, and reports were restricted to the English language.

Results: This review did not identify any published reports of overdose leading to hospital admission and/or treatment. Seven reports of overdose and incidental use were identified and included for evaluation. All cases, except one, occurred in young-to-middle-aged adults, with a dominant male pattern (71%). Three cases occurred in healthcare professionals, and four cases had prior mental illness. Blood concentrations at postmortem and attributed to death ranged from 0.4 to 3.6 μg/mL.

Conclusion: This review identified that ease of access to etomidate among registered healthcare professionals, male gender, young adult age, and history of mental illness were associated with etomidate abuse. However, more research is needed to explore these factors in larger samples. Improved methods to detect and diagnose etomidate misuse are needed to guide clinical and toxicology practices. Active surveillance of misuse is also needed to inform primary and secondary prevention efforts.

Introduction: Bladder cancer (BC) ranks as the 10^th most common cancer globally, predominantly affecting older adults. Non-muscle invasive BC (NMIBC) are known for high recurrence and progression rates despite standard treatments.

Objective: This study assesses the efficacy of chemohyperthermia with epirubicin in Bacillus Calmette-Guérin (BCG)-naïve patients with either primary or recurrent NMIBC.

Methods: We conducted a prospective pilot study on this cohort using the bladder wall thermochemotherapy - UniThermia platform, with a follow-up period of 24 months. Nine NMIBC patients (88.89% male; mean age: 70.22 ± 11.82 years) were prospectively enrolled. Inclusion criteria were NMIBC stage Ta-T1 with BCG-naïve status; patients with carcinoma in situ(CIS) were excluded.

Results: Tumor staging revealed pTa in six patients and pT1 in three patients; tumor grading included G1 (11.11%) and G2 (88.89%). No CIS was detected. All patients received six weekly chemohyperthermia instillations. At the 24-month follow-up, four patients (44.4%) achieved a complete response with no recurrences; all remained alive with no disease progression. All recurrences were low-grade pTa.

Conclusion: These findings suggest that chemohyperthermia with epirubicin may offer therapeutic advantages over intravesical BCG or conventional chemotherapy, especially for BCG-intolerant or refractory patients. Study limitations include the small sample size and limited follow-up duration. Further multicenter studies are warranted to validate these preliminary results. Overall, chemohyperthermia with epirubicin appears to be a promising alternative for the management of recurrent NMIBC when standard BCG treatment is ineffective or unavailable.

Introduction: : Research on the impact of ultraviolet (UV)-related genes on the prognosis of melanoma is rare.

Objective: This study aimed to explore the role of UV-associated genes in skin melanoma and their impact on prognosis.

Methods: We evaluated the prognostic implications of UV-associated genes in cutaneous melanoma and developed a predictive model for patient outcomes utilizing skin melanoma datasets sourced from The Cancer Genome Atlas. Subsequently, we investigated the correlation between UV-associated genes and the local immune environment within cutaneous melanoma.

Results: The developed prognostic model for cutaneous melanoma holds significant value for clinicians in assessing patient outcomes. The expression levels of UV-associated genes appear to influence the infiltration degree of various immune cells within the tumor microenvironment, including T cells and M1 macrophages. In addition, the model was able to predict melanoma prognosis and stratify melanoma patients, with patients in the high-risk group having a worse prognosis. Results also indicated that the high-risk group exhibited reduced infiltration of cytotoxic immune cells in the tumor tissue than the low-risk group.

Conclusion: The findings from this novel study have the potential to identify new therapeutic targets in treating cutaneous melanoma.

Introduction: Colorectal cancer (CRC) is a heterogeneous and multifactorial malignancy driven by a series of genetic and epigenetic alterations. In this field, telomere/telomerase dysfunction contributes to CRC carcinogenesis by impairing genomic stability and cellular replication.

Objective: This study aimed to evaluate genetic and epigenetic alterations in CRC by examining mutation rates in the human telomerase reverse transcriptase (hTERT) promoter region, relative telomere length (RTL), hTERT gene expression, and DNA methylation in the TERThypermethylated oncological region (THOR).

Methods: A total of 45 CRC and 34 adjacent normal tissue samples from Moroccan patients were analyzed using molecular approaches, such as Sanger sequencing, quantitative PCR (qPCR), reverse transcription qPCR (RT-qPCR), and methylation-specific PCR (MSP).

Results: No mutations in the hTERT promoter region were identified. However, hypermethylation in the THOR region was reported in 82.2% of CRC samples and 79.4% of adjacent normal tissues. High hTERT expression was detected in 50% of CRC patients. In addition, telomere length was significantly shorter (p=0.002) in cancerous tissues (1.41 [1.36 - 1.43]) compared to normal mucosa (1.559 [1.46 - 1.63]), with an RTL ratio less than 1 (0.90 [0.86 - 0.95]). No significant differences were found between clinicopathological features and hTERT expression, THOR methylation, or RTL, except for a significant correlation between THOR hypermethylation and smaller tumor size (p=0.017) and between THOR methylation and RTL in CRC tissues (p=0.034).

Conclusion: These results suggest that telomere lengthening is crucial for CRC initiation and progression, and cancer cells tend to shorten telomeres to maintain the chromosomal instability (CIN) required for tumor progression. Further research is needed to elucidate the mechanisms underlying telomere shortening in CRC and understand the role of telomerase/telomere complex in CRC initiation and progression, which could provide new diagnostic, prognostic, and therapeutic targets.

Introduction: Malignant tumors represent a significant public health threat, and the integration of artificial intelligence in health care is increasingly becoming a priority. Many oncology institutions are already considering the use of DeepSeek-R1 to assist doctors in making complex medical decisions. However, there remains a lack of sufficient evidence regarding the accuracy, consistency, and cost-efficiency of DeepSeek-R1 and its distilled models in oncology decision-making. This study aims to fill this gap by evaluating the performance and cost-effectiveness of DeepSeek-R1 and its distilled models in oncology, providing critical insights into their potential for clinical integration.

Objectives: This study aimed to systematically evaluate the performance, consistency, and cost-efficiency of the open-source large language model (LLM) DeepSeek-R1 and its distilled variants in the context of oncology decision-making, using a benchmark derived from the MedQA dataset.

Methods: A custom oncology question set containing 1,206 multiple choice questions was curated from MedQA. Seven models, including DeepSeek-R1 and six distilled versions, were evaluated using an automated testing framework. Accuracy, consistency, latency, and token consumption were compared across models. Statistical tests, including McNemar and Wilcoxon signed-rank, were used to assess differences in performance. Questions were also categorized into clinical task types (diagnosis, treatment, triage, and follow-up) for subgroup analysis.

Results: DeepSeek-R1 achieved the highest performance (accuracy: 91.38%; consistency: 90.47%), whereas DeepSeek-R1-Distill-Qwen-32B was the only distilled model to exceed both metrics at the 0.8 threshold (accuracy: 88.72%; consistency: 81.44%). DeepSeek-R1 demonstrated significantly higher accuracy than its distilled counterpart (p<0.05), particularly in diagnosis- and treatment-related tasks (p<0.05). However, it also exhibited significantly greater latency and token consumption. A Cohen’s kappa value of 0.575 indicated moderate agreement between the two models.

Conclusion: DeepSeek-R1 is more suitable for high-stakes oncology tasks requiring high accuracy and consistency, whereas DeepSeek-R1-Distill-Qwen-32B offers a cost-effective alternative for use in outpatient or resource-limited settings. These findings support a task- and resource-adaptive deployment strategy for LLMs in clinical oncology.

Introduction: In vitrofertilization (IVF) and frozen-thawed embryo transfer (FET) are vital components of assisted reproductive technology. However, predicting pregnancy outcomes remains challenging due to various biological and clinical factors. Recent advances in artificial intelligence (AI) and machine learning (ML) have shown the potential in offering innovative solutions for forecasting reproductive success.

Objective: This study explores the use of large language models, specifically ChatGPT-4o, to optimize ML models for predicting pregnancy outcomes in IVF.

Methods: The clinical dataset comprised 1061 IVF patients who underwent FET from 2014 to 2017, including variables such as age, body mass index, infertility duration, endometrial thickness, and serum beta-human chorionic gonadotrophin (β-HCG) levels on the 7^th day after FET. ChatGPT-4o was tasked with preprocessing the data, evaluating several ML models, and optimizing performance.

Results: The random forest model emerged as the best-performing model, achieving an accuracy of 85.45% and an area under the receiver operating characteristic curve of 0.8287 after applying the optimal threshold of 0.548, indicating strong predictive capability. Feature importance analysis revealed that serum β-HCG levels on the 7^th day after FET were the most influential predictor of pregnancy outcomes. Despite these promising results, the study noted potential overfitting, likely due to the limited training dataset, a constraint largely attributable to the computational limitations of ChatGPT-4o.

Conclusion: ChatGPT-4o shows potential in enhancing ML models in IVF outcome prediction. While AI-driven models can significantly aid clinical decision-making, clinicians should maintain a central role in patient outcome predictions. Future work will focus on improving model generalization with larger datasets and enhanced computational resources.

Introduction: Financial toxicity disproportionately burdens rural and semi-urban cancer populations in resource-limited settings, yet evidence from district/county-level hospitals remains scarce.

Objective: This study aimed to investigate the prevalence and determinants of financial toxicity among cancer patients hospitalized in district- and county-level medical institutions, with a focus on identifying modifiable factors to alleviate economic burdens in this vulnerable population.

Methods: A cross-sectional study was conducted using cluster sampling to recruit hospitalized cancer patients. Validated questionnaires were administered to assess financial toxicity, social support (including subjective, objective, and support utilization dimensions), and psychological resilience. Descriptive statistics were utilized to characterize the prevalence of financial toxicity, while (analysis of variance and t-tests were performed to compare differences across demographic and socioeconomic subgroups. Multivariable linear regression models were subsequently developed to identify independent predictors of financial toxicity severity, controlling for potential confounding variables.

Results: The study included 300 participants, predominantly characterized by low socioeconomic status: 82.34% had attained a junior high school education or less, and 94.66% reported an annual personal income below 50,000 CNY (approximately 7,000 USD). The mean financial toxicity score was 15.54 ± 4.64 (range: 5 - 25), indicating a moderate-to-severe economic strain. Income level emerged as a critical determinant, with lower annual income correlating significantly with heightened financial toxicity (F = 5.406, p=0.001). Multivariable regression analysis identified four protective factors: advanced age (β = −0.18, p<0.05), higher personal income (β = −0.32, p<0.01), greater objective social support (β = −0.21, p<0.05), and enrollment in commercial insurance (β = −0.25, p<0.01), all independently associated with reduced financial toxicity.

Conclusion: The findings highlight a high prevalence of financial toxicity among low-income, less-educated cancer patients receiving care in regional healthcare settings. Structural socioeconomic disparities, particularly limited income and inadequate insurance coverage, significantly contribute to treatment-related financial hardships. Policy interventions to expand commercial insurance accessibility, coupled with community-based support programs to strengthen objective social support networks, may effectively mitigate financial toxicity in this population. Future longitudinal studies are warranted to validate these associations and evaluate targeted intervention strategies.

Introduction: Super-enhancers play crucial roles in tumor development as key transcriptional regulatory elements, yet their prognostic value in bladder cancer (BLCA) remains to be systematically elucidated.

Objective: This study aimed to comprehensively analyze the regulatory mechanisms of super-enhancer-related genes (SERGs) in predicting BLCA prognosis and immune therapy response.

Methods: This study integrated BLCA RNA sequencing data from the cancer genome atlas (training set) and gene expression omnibus (validation set) databases and obtained SERG sets from the SEdb database. Using 101 machine learning ensemble frameworks, we screened and validated SERG sets with significant prognostic value and constructed a risk score model was constructed based on based on CoxBoost and plsRcox. Model performance was evaluated through nomograms. We conducted an in-depth analysis of the association between the risk model and tumor immune microenvironment, identified key hub genes through differential expression analysis, survival analysis, and receiver operating characteristic curve analysis, and performed multi-dimensional validation using immunohistochemistry and single-cell sequencing data.

Results: Through machine learning algorithm optimization, we identified eight core genes (AHNAK, NT5DC3, NFIC, MTHFD1L, C1QTNF6, SLC45A3, QRICH2, KRT8). High-risk group patients exhibited poor prognosis and elevated immune and tumor immune dysfunction and exclusion scores, suggesting potential immune therapy resistance. The single-sample gene set enrichment analysis analysis revealed significant positive correlations between risk scores and multiple key signaling pathways, including extracellular matrix-receptor interaction, regulation of actin cytoskeleton, and pathogenic Escherichia coliinfection, focal adhesion, melanoma, and gap junction pathways. Further analysis indicated that C1QTNF6and MTHFD1Ldisplayed significant potential as biomarkers based on expression profiles across cell types.

Conclusion: This study pioneered the construction of a prognostic prediction model for BLCA based on SERGs, revealing the crucial role of super-enhancers in regulating the tumor immune microenvironment and identifying potential therapeutic targets and prognostic markers. This research provides a new molecular typing strategy for the precision treatment of BLCA while establishing a theoretical foundation for personalized immunotherapy.

Introduction: Glioblastoma (GBM) is a highly malignant tumor of the nervous system, posing serious threats to patient survival and quality of life. However, current treatment options remain limited in both availability and effectiveness.

Objective: This study analyzes the gene expression data related to GBM to support the development of improved therapeutic strategies.

Methods: Two gene expression datasets were selected for statistical analysis. Differentially expressed genes (DEGs) related to GBM were screened based on predefined criteria. Enrichment analysis was performed to explore the biological processes and pathways involved. A protein-protein interaction (PPI) network was constructed to identify central genes, which were further analyzed for expression patterns and their potential roles in GBM pathology.

Results: A total of 1,151 overlapping DEGs were identified. Enrichment analysis revealed their involvement in several key biological processes and pathways. From the PPI network, central genes, including signal transducer and activator of transcription 3 (STAT3), CAML1, clathrin assembly lymphoid myeloid 2, and protein kinase CAMP-activated catalytic subunit beta were identified as playing crucial roles in GBM development. Immune cell subtype analysis indicated interactions between these genes and the tumor microenvironment. The diagnostic value highlighted STAT3 as a potential biomarker for GBM. In vivoexperiments confirmed that gene expression patterns were consistent with database predictions. Molecular docking analysis identified valproic acid as a promising therapeutic candidate, targeting five central genes. In vitrostudies demonstrated that valproic acid effectively induced GBM cell death and modulated the expression of these genes, with high safety observed.

Conclusion: Identifying DEGs and central genes is essential in understanding GBM pathology. This study establishes STAT3 as a diagnostic marker and highlights valproic acid as a potential multi-target therapeutic agent. These findings lay the groundwork for more effective and targeted treatment strategies for GBM.

Introduction: Benign prostatic hyperplasia (BPH) is a common condition in aging men that can significantly impact quality of life. Prostatic artery embolization (PAE) has emerged as a minimally invasive treatment option.

Objective: This study aimed to evaluate the clinical efficacy of super-selective PAE using microspheres of different sizes on BPH patients and investigate its correlation with serum prostate-specific antigen (PSA) expression.

Methods: A prospective, single-blind randomized study was performed on 80 eligible patients treated between January 2020 and October 2022. Patients were randomly assigned to Group A (100 - 300 μm microspheres) or Group B (300 - 500 μm microspheres), with 40 patients each. Follow-ups were conducted at 1, 3, and 6 months post-embolization using ultrasound and/or computed tomography/magnetic resonance imaging, alongside PSA testing. Data collection covered prostate volume (PV), maximum urinary flow rate (Q_max), post-void residual (PVR), international prostate symptom score (IPSS), quality of life (QoL), clinical symptoms, obstruction relief, and PSA levels.

Results: Significant improvements were observed in all parameters (IPSS, QoL, PV, PVR, and Q_max) at each follow-up point (all p<0.05). Group A showed superior outcomes at 6 months in both subjective (IPSS, QoL) and objective (PV, PVR, Q_max, PSA) parameters (all p<0.05). The PSA-PV correlation demonstrated a dose-response relationship. Minor complications occurred in Group A (20.0%) and Group B (12.5%), with no severe adverse events.

Conclusion: PAE using 100 - 300 μm microspheres demonstrated superior outcomes and PSA reductions compared to larger particles, supporting its safety and efficacy as a treatment option for BPH.

Introduction: Timely administration of analgesia is fundamental to emergency musculoskeletal trauma care. Delays contribute to suboptimal outcomes, patient dissatisfaction, and the potential progression to chronic pain.

Objective: This study aims to assess door-to-analgesia time (DTAT) in the emergency department (ED) and to identify factors contributing to delays.

Methods: A prospective observational study was conducted over 5 months, enrolling 90 adult patients with musculoskeletal trauma at an urban tertiary ED. Pain intensity was recorded using a numerical rating scale at triage, pre- and post-analgesia, and discharge. Patients were stratified into Group A (DTAT ≤30 min) and Group B (DTAT >30 min). Statistical analyses were performed to identify predictors of delayed analgesia and to evaluate pain relief efficacy.

Results: The mean DTAT was 40.6 min, with 45% of patients receiving analgesia within 30 min. Older age (>45 years) was a significant predictor of prolonged DTAT (>45 min; p<0.05). No significant differences in DTAT were observed across triage categories (T2: 34.4 min vs. T3: 43.6 min; p>0.05). Analgesia administration led to a 50% reduction in mean pain score; however, DTAT was not significantly associated with patient satisfaction.

Conclusion: Delayed analgesia remains a challenge, particularly among older patients. Strategies such as nurse-initiated analgesia, enhanced triage protocols, and optimized resource allocation may improve DTAT and patient outcomes. Multicenter studies are warranted to validate and refine pain management protocols in ED settings.

Introduction: Pulmonary fibrosis is a progressive and life-threatening condition frequently associated with chemotherapeutic agents, such as bleomycin (BLE). Aronia melanocarpaextract (AME), a potent antioxidant derived from black chokeberry, has shown promising anti-inflammatory and anti-fibrotic effects in various pre-clinical models.

Objective: This study aims to evaluate the protective and therapeutic effects of AME in a rat model of BLE-induced pulmonary fibrosis.

Methods: A total of 60 rats were divided into six groups: control, fibrosis (BLE only), positive control (BLE + methylprednisolone), AME-only, AME + BLE (AME administered concurrently with BLE), and BLE + AME (AME administered after fibrosis induction). Lung tissues were analyzed histologically and biochemically for inflammation, fibrosis, and oxidative stress markers.

Results: AME administration significantly reduced alveolar wall thickening, hemorrhage, cellular infiltration, and collagen deposition. These effects were more pronounced in the AME + BLE group, indicating a potential prophylactic advantage. In addition, AME restored antioxidant enzyme levels and suppressed lipid peroxidation.

Conclusion: AME exhibits both preventive and therapeutic effects against BLE-induced lung injury. Its polyphenol-rich composition and antioxidative properties support its potential as a low-cost, low-toxicity candidate in pulmonary fibrosis management.

Introduction: Multiple sclerosis (MS) is one of the chronic demyelinating diseases of the nervous system that leads to a wide spectrum of clinical symptoms and significantly affects the quality of life (QoL).

Objective: This study evaluated the role of depression, functional status, level of self-care, and other socio-demographic and clinical factors in patients with MS.

Methods: This cross-sectional study was conducted among 349 patients with MS. This study employed a questionnaire designed by the authors to capture socio-demographic and clinical characteristics, along with the following standardized instruments: the Activities of Daily Living questionnaire, the Expanded Disability Status Scale, the Beck Depression Inventory, and the MS QoL Questionnaire-54.

Results: Using regression analysis, we found that the most important factors influencing physical QoL included age (p<0.01), occupation (p<0.01), and educational attainment (p<0.001). Among the clinical variables, the following were significantly associated with the QoL: functional ability (p<0.001), level of self-care (p<0.001), presence of depressive symptomatology (p<0.001), presence of relapses (p<0.001), and type of MS (p<0.001). The most important factors that were associated with psychological QoL included educational attainment (p<0.001), functional ability (p<0.001), level of self-care (p<0.05), presence of depressive symptomatology (p<0.001), presence of relapses (p<0.05), and progressive form of the disease (p<0.001).

Conclusion: Since the course of MS varies and is sometimes unpredictable, it is crucial to monitor the factors associated with the QoL of these patients and to conduct the necessary interventions to improve it.

Introduction: Bladder cancer (BCa) represents a significant uro-oncological challenge due to its aggressive nature and high recurrence rates. Although magnetic resonance imaging (MRI) is a cornerstone modality in BCa management, the manual segmentation of lesions is time-consuming and suffers from low reproducibility due to inter- and intra-observer variability, morphological heterogeneity, and MRI artifacts.

Objective: This study aims to address these limitations by conducting a rigorous comparative evaluation of four distinct U-Net-based deep learning architectures.

Methods: The models were evaluated using the publicly available, multi-center FedBCa dataset, comprising 275 T2-weighted MRI scans from 228 patients. Using a standardized training protocol, performance was rigorously assessed with a suite of quantitative metrics, including the Dice coefficient, intersection over union (IoU), and Hausdorff distance, supplemented by qualitative visual comparison.

Results: Cross-scale mixer U-Net (CMUNet) achieved the best overall performance, yielding the highest Dice coefficient (0.7937), IoU (0.7033), and boundary delineation accuracy (Hausdorff distance: 8.4550 mm. Architectural trade-offs were evident: CMUNeXt was the most computationally efficient and offered the highest lesion sensitivity (0.9656), whereas Attention U-Net recorded the highest precision (0.8380).

Conclusion: CMUNet provides the most balanced and accurate performance for BCa segmentation. However, the optimal architecture choice is application-dependent; high-sensitivity models such as CMUNeXt are ideal for screening, while high-precision models like Attention U-Net are better suited for treatment planning. Deep learning models serve as powerful assistive tools to improve efficiency and objectivity in clinical workflows, though expert oversight remains essential. The top model’s accuracy approached, but did not surpass, the inter-rater reliability of human experts (Dice: 0.870).

Introduction: The integration of data analytics into health informatics has become vital for transforming raw clinical information into actionable insights that improve patient care and pharmaceutical outcomes.

ObjectivesThis study uses the Medical Information Mart for Intensive Care IV (MIMIC-IV) electronic health record dataset to examine differences in pharmaceutical prescription patterns and their relationship to clinical outcomes. We investigate how demographic characteristics, including age, gender, and race, affect prescribing patterns for three major drug classes: opioids, antibiotics, and antipsychotics.

Methods: We analyzed the MIMIC-IV intensive care unit dataset, incorporating preprocessing of demographic and prescription data to support fairness and outcome analysis. A decision tree model was trained to predict in-hospital mortality and evaluated using standard performance metrics.

Results: We examined the relationship between drug type and patient outcomes, finding that antibiotic prescriptions were associated with shorter hospital stays, whereas antipsychotic prescriptions were linked to longer hospitalizations. Our findings reveal statistically significant differences in prescribing patterns, where men were more likely to receive opioids, whereas women were more likely to receive antibiotics. In addition, considerable racial disparities suggest possible systemic inequities. Nevertheless, there was no statistically significant correlation between drug type and in-hospital mortality, indicating that underlying clinical conditions may play a more substantial role. The model achieved an area under the receiver operating characteristic curve of 0.9337 and an F1-score of 0.8235, outperforming several complex algorithms whereas remaining easily interpretable—an important advantage in clinical practice.

Conclusion: These results demonstrate the potential of transparent machine learning models to support enhanced medical decision-making and highlight the need for prescription strategies that prioritize fairness and equity.

Introduction: : Breast cancer (BC) is heterogeneous and remains a major health priority. Robust biomarkers are needed to improve early detection and guide therapy.

Objective: This study investigates the molecular mechanisms underlying BC development (normal versus cancer) and progression (early versus late).

Methods: A meta-analysis of 51 microarray studies comparing BC and normal cells, as well as early- and late-stage BC cells, was conducted using microarray data obtained from the Gene Expression Omnibus and ArrayExpress databases. Five meta-analysis methods, each based on different statistical approaches, were applied, and the overlapping results were identified.

Results: A total of 3,362 and 95 differentially expressed genes (DEGs) associated with BC development and progression were identified. Among these DEGs, the upregulation of COL10A1, COL11A1, TOP2A, CDK1, MMP11, and S100Pand the downregulation of ADH1B, SFRP1, DST, LEP, ADIPOQ, and CHRDL1were the most significantly associated with BC development. DEGs such as DHTKD1and CBX3(upregulated) and MAP3K20(downregulated) were found to be among the most significantly differentially expressed in BC progression. The top gene ontology terms enriched in BC development included regulation of signaling receptor activity and cytokine-mediated signaling pathway. In addition, the cellular macromolecule biosynthetic process and response to organic substances were significantly enriched in BC progression.

Conclusion: Many of the DEGs may serve as potential therapeutic targets for BC.

Introduction: Candidaspecies are increasingly recognized as significant nosocomial pathogens. In patients hospitalized in the intensive care units (ICUs), the risk of candidemia is particularly high due to the coexistence of multiple risk factors.

Objective: In this study, we investigated the distribution of Candidaspecies, antifungal susceptibility, risk factors, and mortality in ICU patients with nosocomial Candidainfections.

Methods: This retrospective study included 63 adult patients with candidemia hospitalized in the ICU between January 2021 and March 2023. Demographic, clinical, and laboratory data were analyzed. Statistical analysis was performed using the Chi-square test, Mann-Whitney Utest, and logistic regression.

Results: Non-albicans Candida(NAC) species accounted for 61.9% of all isolates, with Candida parapsilosis(42.8%) being the most common. Gastrointestinal surgery significantly increased the risk of NAC infection (p=0.038). Higher serum albumin levels were associated with a reduced risk of mortality (odds ratio [OR]: 0.86, 95% confidence interval [CI]: 0.77-0.97, p=0.013), and elevated urea levels were associated with an increased risk of mortality (OR: 1.023, 95% CI: 1.008-1.038, p=0.002). All of the 16 tested isolates were susceptible to anidulafungin, while 66.6% of C. parapsilosisisolates were resistant to fluconazole. The overall mortality rate was 66.7%.

Conclusions: NAC species should be considered in empirical treatment strategies, particularly for patients hospitalized in ICUs where this species is prevalent and for those with a history of gastrointestinal surgery. Low albumin and elevated urea may serve as potential predictors of mortality and should be carefully monitored. Echinocandins remain the most appropriate empirical agents given the high fluconazole resistance observed among C. parapsilosisisolates.

Introduction: Obesity is a well-established risk factor for endometrial cancer (EC). Postmenopausal women with EC frequently present with obesity-related comorbidities or develop them after diagnosis, which may impact survival.

Objectives: This study aimed to identify modifiable comorbidities (diabetes, cardiovascular disease, hypertension, and fractures) among postmenopausal EC survivors and evaluate the relationship between obesity-related comorbidities and all-cause mortality after an EC diagnosis.

DesignProspective cohort analysis of overall mortality risk in relation to obesity-related comorbidities in women diagnosed with EC.

Population and SettingPostmenopausal women recruited across 40 clinical sites within the Women’s Health Initiative (WHI) observational and clinical trials and experiencing a new diagnosis of EC.

Methods: Adjusted Cox proportional hazards regression models were used to evaluate the relationship between comorbidities and all-cause mortality among women with incident EC.

Results: A total of 1,661 incident cases of EC were identified. The overall mortality rate was 55.5%. The prevalence of each comorbidity increased from baseline to 18 years of follow-up. Regression analyses for incident EC indicated that severe obesity (hazard ratio [HR] = 2.13; 95% confidence interval [CI]: 1.52-2.97), cardiovascular disease (HR = 1.50; 95% CI: 1.26-1.78), and fracture (HR = 1.17; 95% CI: 1.07-1.27) were associated with greater overall mortality.

Conclusion: Obesity-associated comorbidities are common and associated with higher mortality in postmenopausal women diagnosed with EC. Interventions to reduce the risk of comorbidity among EC survivors may improve survival and should be evaluated (ClinicalTrial.gov identifier: NCT00000611).

Introduction: During the COVID-19 pandemic, the prolonged use of face masks became necessary for infection control. However, this widespread practice may have unintentionally impacted communication, particularly in children at critical stages of speech and language development.

Objective: This study aims to examine parental perceptions regarding the effect of prolonged face-mask use on speech and language development in children aged 2-8 years during the COVID-19 pandemic.

Methods: A cross-sectional study was conducted using a 14-item online questionnaire completed voluntarily by parents or legal guardians. The survey explored perceived speech and language changes, recovery following discontinuation of mask use, and whether professional intervention (e.g., speech therapy) was sought.

Results: A total of 60 participants were recruited. Language delays were more frequently reported in children under 3 years of age (38%) than in older children (22%). Following the end of mask use, 43.1% of parents reported no change in language development, 29.3% perceived no association, and 27.6% observed improvement. Among those who noticed delays, 30.8% consulted a speech therapist, 61.5% reported spontaneous recovery, and 7.7% reported no recovery. Overall, 77.3% of children showed significant language recovery after stopping mask use, 13.6% recovered partially, and 9.1% did not recover.

Conclusion: Parental perceptions suggest that prolonged mask use may have interfered with language development in some children, especially the youngest. While many children improved spontaneously, a notable proportion required professional intervention. These findings highlight the importance of early detection and support for children potentially affected by communication while wearing masks during critical developmental periods. Further research using clinician-assessed measures is needed to validate these perceptions.

Introduction: Psychological adaptation to cancer is thought to reflect the joint influence of dispositional traits and defensive functioning on resilience and trauma-related symptoms.

Objective: This pilot study explores associations among Big Five traits, defense mechanisms, psychological resilience, and post-traumatic stress symptoms (PTSS) in adult oncology patients.

Methods: Sixteen consecutively recruited patients with histologically confirmed cancer completed validated self-report measures: 10-item big five inventory (personality), defense mechanisms rating scales-self-report (30-item, assessing overall defensive functioning and defense levels/mechanisms), 14-item resilience scale (resilience), and impact of event scale-revised (PTSS). Primary analyses estimated Spearman’s ρwith bias-corrected and accelerated 95% confidence intervals; family-wise error was controlled using Holm adjustment (two-tailed α= 0.05).

Results: After controlling for multiple comparisons, no associations remained statistically significant, and confidence intervals were wide.

Conclusion: Findings are hypothesis-generating and consistent with a psychodynamically informed, multidimensional model in which defensive style and personality dispositions shape resilience and PTSS. Definitive inferences require larger, prospectively characterized cohorts, psychometrically stronger trait measures, and multivariate modeling (e.g., structural equation modeling), with pre-registered analytic plans and longitudinal follow-up to test mechanism-focused interventions that target defense restructuring and resilience enhancement.

Geranylgeranoic acid (GGA) is an acyclic diterpenoid that functions as a ligand for retinoic acid receptors and promotes differentiation in human hepatoma cell lines. Unlike natural retinoids, GGA induces apoptotic-like cell death at micromolar concentrations. In the early 2000s, GGA was identified as a naturally occurring diterpenoid in plants, including turmeric (Curcuma longa). Based on its chemical structure, GGA is presumed to be biosynthesized from the metabolic intermediate geranylgeranyl pyrophosphate (GGPP), which is derived from either the mevalonate or non-mevalonate pathways. GGPP is dephosphorylated to geranylgeraniol, which is subsequently oxidized in two steps to produce GGA. Our previous work demonstrated that GGA is endogenously synthesized in mammals through the mevalonate pathway, with monoamine oxidase B and CYP3A4 involved in its hepatic metabolism. Notably, in a spontaneous hepatoma mouse model, hepatic GGA levels were markedly depleted by 23 months of age. However, oral supplementation with GGA at 11 months significantly suppressed hepatocellular carcinoma development. These findings suggest that age-related declines in endogenous GGA levels may be associated with tumorigenesis and that dietary supplementation may contribute to cancer prevention. This review outlines the biochemical pathways of GGA biosynthesis, its dietary origins, and its known biological functions, with particular emphasis on its tumor-suppressive effects in animal models. We also discuss the potential nutritional relevance of GGA-containing foods in disease prevention. By integrating previous findings with recent analytical data, we propose future research directions to clarify the physiological roles of GGA and its potential applications in functional-food science.