Individual Treatment Research Articles

Combined treatment with Aronia berry extract and oligomeric proanthocyanidins exhibit a synergistic anticancer efficacy through LMNB1-AKT signaling pathways in colorectal cancer.

Colorectal cancer (CRC) is one of the most prevalent and highly recurrent malignancies worldwide and currently ranks as the second leading cause of cancer-related deaths. The high degree of morbidity and mortality associated with CRC is primarily attributed to the limited effectiveness of current therapeutic approaches and the emergence of chemoresistance to standard treatment modalities. Recent research indicates that several natural products, including Aronia berry extracts (ABE) and oligomeric proanthocyanidins (OPCs), might offer a safe, cost-effective, and multitargeted adjunctive role to cancer treatment. Herein, we hypothesized a combined treatment with ABE and OPCs could synergistically modulate multiple oncogenic pathways in CRC, thereby enhancing their anticancer activity. We initially conducted a series of in vitro experiments to assess the synergistic anticancer effects of ABE and OPCs on CRC cell lines. We demonstrate that these two compounds exhibited a superior synergistic anticancer potential versus individual treatments in enhancing the ability to inhibit cell viability, suppress colony formation, and induce apoptosis (p < 0.05). Consistent with our in vitro findings, we validated this combinatorial anticancer effect in tumor-derived 3D organoids (PDOs; p < 0.01). Using genome-wide transcriptomic profiling, we identified that a specific gene, LMNB1, associated with the cell apoptosis pathway, was found to play a crucial role in exhibiting anticancer effects with these two products. Furthermore, the combined treatment of ABE and OPCs significantly impacted the expression of key proteins involved in apoptosis, including suppressed expression levels of LMNB1 in CRC cell lines (p < 0.05), which resulted in inhibiting downstream AKT phosphorylation. In conclusion, our study provides novel evidence of the synergistic anticancer effects of ABE and OPCs in CRC cells, partially mediated through the regulation of apoptosis and the oncogene LMNB1 within the AKT signaling pathway. These findings have the potential to better appreciate the anticancer potential of natural products in CRC and help improve treatment outcomes in this malignancy.

Patient Preferences for Surgical Treatments for Benign Prostatic Hyperplasia: A Discrete Choice Experiment

Purpose: When symptoms of benign prostatic hyperplasia cannot or can no longer be treated by conservative treatment options adequately, various surgical treatment options are available. Different risks and benefits are associated with each type of surgery; the optimal choice depends on the patient's preference. This study analyzes patients' preferences and investigates patient characteristics that might influence patient preferences in Germany. Materials and Methods: We conducted an online discrete choice experiment based on 9 treatment attributes related to risks (probability of ejaculatory dysfunction, permanent incontinence, needing surgery again, and erectile dysfunction) and efficacy (frequency of daytime and nighttime urination, urgency and duration of urination, and time until symptoms improve) of surgeries. To estimate preferences, we applied a mixed-logit model. Subgroup analyses based on patients' characteristics were conducted. Results: Three hundred thirty participants completed the discrete choice experiment. Overall, participants preferred a lower risk of ejaculatory dysfunction, lower urgency and duration of urination, lower probability of permanent incontinence, lower frequency of nighttime and daytime urination, and lower probability of needing another surgery. Moreover, a faster onset of overall symptom reduction was preferred. Several patient characteristics especially characteristics related to a patient's sexual life seem to influence patients' preferences. Conclusions: Significant preference heterogeneity could be observed in this study, and subgroup analyses suggest differences in preferences in relation to patients' characteristics. These findings highlight the need for individualized treatment decisions. Physicians should evaluate patients' clinical but also inquire about a patient's personal situation and preferences to select the optimal treatment in collaboration with the individual patient.

Machine Learning Model for Early Prediction of Survival in Gallbladder Adenocarcinoma: A comparison Study

The prognosis for gallbladder adenocarcinoma (GBAC), a highly malignant cancer, is not good. In order to facilitate individualized risk stratification and improve clinical decision-making, this study set out to create and validate a machine learning model that could accurately predict early survival outcomes in GBAC patients. Five models—RSF, Cox regression, GBM, XGBoost, and Deepsurv—were compared using data from the SEER database (2010–2020). The dataset was divided into training (70%) and validation (30%) sets, and the C-index, ROC curves, calibration curves, and decision curve analysis (DCA) were used to assess the model's performance. At 1, 2, and 3-year survival intervals, the RSF model performed better than the others in terms of calibration, discrimination, and clinical net benefit. The most important predictor of survival, according to SHAP analysis, is AJCC stage. Patients were divided into high, medium, and low-risk groups according to RSF-derived risk scores, which revealed notable variations in survival results. These results demonstrate the RSF model's potential as an early survival prediction tool for GBAC patients, which could enhance individualized treatment and decision-making.

The Differential Diagnosis of Leg Ulcers.

Chronic wounds on the leg (below the knee) are called leg ulcers. They have many causes, and thus patients with leg ulcers are treated by many different kinds of medical specialist. Appproximately 80% of sufferers have chronic venous insufficiency (CVI) and/or peripheral arterial occlusive disease (PAOD). Knowledge of the relevant differential diagnoses is important for appropriate treatment, particularly for patients with atypical findings or an intractable course. This article is based on publications retrieved by a selective search in PubMed, including current guidelines and expert recommendations. The diagnostic evaluation of a leg ulcer can be structured according to the ABCDE rule. This involves individualized, targeted history-taking (anamnesis); bacteriological testing; clinical examination; ancillary testing, particularly for perfusion (defective vascular system); and extras, such as biopsies. Specifically, we present in this article the main aspects of the complex diagnostic evaluation of venous leg ulcers, arterial leg ulcers, vasculitis, vasculopathy, calciphylaxis, pyoderma gangrenosum, necrobiosis lipoidica, ecthyma, and squamous cell carcinoma. There remain many unsolved problems, including interactions between the various areas of clinical treatment and the relative paucity of relevant high-quality research. A timely differential-diagnostic evaluation for the many diseases that can cause leg ulcers, which require treatment from representatives of many different medical specialties and health professions, is a prerequisite for their effective individualized treatment.

Predicting Early Treatment Effectiveness in Bell's Palsy Using Machine Learning: A Focus on Corticosteroids and Antivirals.

Facial nerve paralysis, particularly Bell's palsy, manifests as a rapid onset of unilateral facial weakness or paralysis. Despite most patients recovering within three to six months, a significant proportion experience poor recovery. This study utilized six machine learning models to investigate the effectiveness of early treatment in Bell's palsy. We applied data from 17hospitals in Scotland to predict treatment outcomes. Patients were randomized into four groups: Prednisolone (corticosteroids), Acyclovir (antivirals), both, and placebo. Outcomes, defined as full resolution of symptoms, were assessed using the House-Brackmann scale at 3 and 9 months post-treatment. We employed six different machine learning models to predict recovery outcomes and evaluated model performance using AUC, precision, recall, and F1-score. Among 493 patients, 72.6% recovered after three months and 89.5% after nine months. Logistic regression demonstrated the highest predictive performance for both 3-month (AUC = 0.751) and 9-month recovery (AUC = 0.720). Additionally, several models achieved Precision levels exceeding 0.9. We further employed the best-performing logistic regression for feature ranking, indicating that the patient's age and prednisolone administration are the most significant predictors of recovery. The results highlight the potential of machine learning models in predicting the effectiveness of early treatment. This study conducted a comprehensive comparison of six different machine learning models, with the logistic regression showing the highest predictive performance for both 3-month and 9-month recovery. Additionally, feature ranking using logistic regression supported the importance of Prednisolone in treatment. Notably, our findings revealed the significance of age in prognosis evaluation for the first time. This suggests that future research should further develop age-specific prognostic models, enabling clinicians to tailor individualized treatment strategies more effectively. This previously unrecognized discovery provides a foundation for prognostic analysis in Bell's palsy patients.

Uncovering Disease Mechanisms through AI and Visual Computing: A Multi-Scale Approach to Biological Data Interpretation

This research focuses on uncovering complex disease mechanisms by employing artificial intelligence (AI) and visual computing to interpret multi-scale biological data. By analyzing data from molecular to organ-level systems, this study aims to bridge the gap between cellular insights and clinical applications, offering new perspectives on diseases such as cancer, neurodegenerative disorders, and cardiovascular diseases. Through a comprehensive approach to data integration, the project compiles omics and imaging data to enable holistic analysis across biological scales. The use of hierarchical neural networks, graph neural networks (GNNs), and convolutional neural networks (CNNs) allows for multi-dimensional modeling and the extraction of disease-related patterns. The findings are validated with clinical data to support actionable insights, laying the groundwork for personalized disease models and precision therapeutic strategies. Expected outcomes include breakthroughs in disease understanding, advancements in precision medicine, and the establishment of a robust AI framework that will contribute to future biomedical applications. This multidisciplinary approach promises to transform diagnostics, prognosis, and treatment, facilitating a deeper understanding of disease mechanisms and their translation into clinical practice. The integration of multi-scale data enables a nuanced view of disease, capturing interactions that may be obscured in single-level analyses. By employing advanced visual computing techniques, the project highlights structural abnormalities within tissue samples, linking cellular changes to systemic disease pathways. This approach not only aids in identifying novel biomarkers but also supports the development of individualized treatment models that predict patient-specific responses. With validation from clinical datasets, the AI framework is poised to enhance clinical decision-making, offering insights tailored to the unique biological profiles of patients. The project’s multi-scale methodology serves as a foundation for future biomedical research, setting a new standard for AI-driven disease analysis.

Integrated machine learning developed a prognosis-related gene signature to predict prognosis in oesophageal squamous cell carcinoma.

The mortality rate of oesophageal squamous cell carcinoma (ESCC) remains high, and conventional TNM systems cannot accurately predict its prognosis, thus necessitating a predictive model. In this study, a 17-gene prognosis-related gene signature (PRS) predictive model was constructed using the random survival forest algorithm as the optimal algorithm among 99 machine-learning algorithm combinations based on data from 260 patients obtained from TCGA and GEO. The PRS model consistently outperformed other clinicopathological features and previously published signatures with superior prognostic accuracy, as evidenced by the receiver operating characteristic curve, C-index and decision curve analysis in both training and validation cohorts. In the Cox regression analysis, PRS score was an independent adverse prognostic factor. The 17 genes of PRS were predominantly expressed in malignant cells by single-cell RNA-seq analysis via the TISCH2 database. They were involved in immunological and metabolic pathways according to GSEA and GSVA. The high-risk group exhibited increased immune cell infiltration based on seven immunological algorithms, accompanied by a complex immune function status and elevated immune factor expression. Overall, the PRS model can serve as an excellent tool for overall survival prediction in ESCC and may facilitate individualized treatment strategies and predction of immunotherapy for patients with ESCC.

Comprehensive mapping of somatotroph pituitary neuroendocrine tumour heterogeneity using spatial and single-cell transcriptomics.

Pituitary neuroendocrine tumours (PitNETs) are common intracranial tumours that are highly heterogeneous with unpredictable growth patterns. The driver genes and mechanisms that are crucial for tumour progression in somatotroph PitNETs are poorly understood. In this study, we performed integrative spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) analysis on somatotroph tumours and normal pituitary samples to comprehensively characterize the differences in cellular characteristics. By analyzing combined copy number variations (CNVs), tumour tissues were divided into two regions, which included the CNVhigh and CNVlow areas. The protumour genes DLK1 and RCN1 were highly expressed in the CNVhigh area, which might be related to tumour progression and could be targeted for precision therapy. We also found that the transforming growth factor beta signalling pathway participated in tumour progression and identified heterogeneity in the expression profiles of key genes. We assessed the intertumoral and intratumoral heterogeneity in somatotroph PitNETs and emphasized the importance of individualized treatment. In summary, we visualized the cellular distribution and transcriptional differences in normal pituitary and somatotroph PitNETs by ST and scRNA-seq for the first time. This study provides a strong theoretical foundation to comprehensively understand the crucial mechanisms involved in tumour progression and develop new strategies to treat somatotroph PitNETs. The first-ever visualization of cellular distributions in normal and tumor pituitary tissues. The inter- and intra-tumoral transcriptomic heterogeneity of somatotroph PitNETs was comprehensively revealed. Identification of potential protumor factors and critical signaling pathways, opening new avenues for therapeutic intervention.

Reduction of masseter muscle prominence after treatment with onabotulinumtoxinA: primary results from a randomized phase 2 study

OnabotulinumtoxinA is used to treat masseter muscle prominence (MMP). To assess the safety and efficacy of onabotulinumtoxinA for MMP in a randomized study. This 12-month, multicenter, double-blind, placebo-controlled, phase 2 study randomized adults (18-50 years of age) with marked/very marked bilateral MMP (≥4 on the Masseter Muscle Prominence Scale [MMPS]) to onabotulinumtoxinA (24, 48, 72, or 96 U) or placebo; retreatment occurred at day 180 if MMPS ≥4. Lower facial volume at day 90 was measured using Vectra 3-dimensional photography. Safety assessments included computed tomography and dental exams. Evaluations occurred monthly through day 360. Among 187 randomized subjects, significant lower facial volume reductions and percentage of responders (MMPS grade ≤3) were greater with onabotulinumtoxinA versus placebo at day 90 (P < .001 and ≤ .008, respectively). Similar efficacy was observed with retreatment. No dose-related safety trends or clinically relevant changes in the mandible or teeth occurred. Localized impact on smile was reported with 96 U onabotulinumtoxinA (n=4). Limited sample size per individual treatment group. OnabotulinumtoxinA administered in 1 or 2 treatments over 1 year was associated with significant reductions in masseter muscle volume and MMP severity, with an acceptable safety profile.

A Systematic Review of Comparative Effectiveness of Interventions for Low Anterior Resection Syndrome: Impacts on Bowel Function and Quality of Life.

Low anterior resection syndrome (LARS) is a common complication following sphincter-preserving surgical resection for rectal cancer, characterized by symptoms such as fecal incontinence, urgency, and altered bowel habits, which significantly affect patients' quality of life. This cluster of symptoms not only limits their day-to-day physical activity but also has a debilitating effect on their emotional and mental well-being, undermining their integration and overall psychological health. This systematic review aimed to evaluate the effectiveness of invasive and non-invasive interventions for LARS, including pelvic floor rehabilitation, transanal irrigation, and various surgical options such as sacral neuromodulation and stoma formation, either as part of primary surgery or as a definitive treatment option for refractory cases. We systematically searched relevant databases for studies published in the last decade, focusing on adult patients diagnosed with LARS post-low anterior resection (LAR), with outcomes assessed through bowel function and quality of life metrics. The review identified six studies that met our eligibility criteria; a pooled cohort of 794 patients was identified, with sample sizes ranging from 37 to 430 participants. Our analysis revealed that pelvic floor rehabilitation significantly improves bowel function and quality of life in patients with LARS; yet, the optimal management approach remains unclear due to variability in patient responses. These findings highlight the inherent complexity and heterogeneity of LARS management, underscoring the necessity for multifaceted and individualized treatment strategies. Although pelvic floor rehabilitation shows promise, especially among motivated patients, its long-term sustainability remains uncertain. Surgical options are typically reserved for severe cases and carry significant risks and psychological impacts. For patients identified as being at high risk for LARS, treatment options must be considered and discussed at an earlier phase of their care. Our review concludes with the need for a tailored, patient-centered approach to managing LARS, highlighting the importance of ongoing research to fill existing evidence gaps. There is a need for translational research across various treatment modalities, comparing their effects, cost-effectiveness, implementation strategies, and the consequent effects on patients' quality of life and mental health.

036. Sclerotic Therapy as The Management Of Arteriovenous Malformation on Hand: A Case Report

Background: An arteriovenous malformation (AVM) is an abnormal connection between arteries and veins, bypassing the capillary system. There are a number of consequences associated with this illness, such as bleeding and neurological impairments. The situation is complex, which emphasizes the necessity for individualized treatment plans. This case report a 18 years old female with AVM condition. Case: A 18 years old female was admitted to to Prof. IGNG Ngoerah General Hospital with a chief complaint of lump on the left finger. The lump on the left finger has been felt since &gt;10 years ago. The lump appeared suddenly and went bigger each day. Complaints worsened until the patient felt pain in the left finger. On examination of the local status, multiple masses were found on third and fourth digits of the left hand, with unclear border and vein ectasis. MSCT Angiography of the left superior extremity found a soft tissue image of hemangioma on the palmar aspect and interdigiti III-IV to the palmar-dorsal aspect of digit III and the palmar aspect of digiti IV of the left hand and multiple non-suspicious lymphadenopathy in the left axilla region. The scleroterapy treatment was performed and 3 months results shown decreased size of the masses without any complication. Conclusion: An arteriovenous malformation (AVM) of the left hand fingers is a rare case found in Prof Ngoerah Hospital. The sclerotic therapy found to be an effective management for this case.

Synergistic effects of human umbilical cord mesenchymal stem cells/neural stem cells and epidural electrical stimulation on spinal cord injury rehabilitation

Spinal cord injury (SCI) is a severe neurological condition marked by a complex pathology leading to irreversible functional loss, which current treatments fail to improve. Epidural electrical stimulation (EES) shows promise in alleviating pathological pain, regulating hemodynamic disturbances, and enhancing motor function by modulating residual interneurons in the lower spinal cord. Cell transplantation (CT), especially using human umbilical cord mesenchymal stem cells (hUCMSCs) and neural stem cells (NSCs), has significantly improved sensory and motor recovery in SCI. However, the limitations of single treatments have driven the exploration of a multifaceted strategy, combining various modalities to optimize recovery at different stages. To comprehensively investigate the effectiveness of in situ transplantation of hUCMSCs/NSCs combined with subacute epidural electrical stimulation in a murine spinal cord crush injury model, providing valuable references for future animal studies and clinical research. In this study, we first examined neural stem cell changes via mRNA sequencing in an in vitro Transwell co-culture model. We then explored cell interaction mechanisms using proliferation assays, differentiation assays, and neuron complexity analysis. For animal experiments, 40 C57BL/6 mice were assigned to four groups (Injury/EES/CT/Combination). Histological evaluations employed HE and immunofluorescence staining, while electrophysiological and behavioral tests assessed motor recovery. Quantitative data were reported as mean ± standard error, with statistical analyses performed using GraphPad Prism and SPSS. Initially, we found that NSCs in the in vitro co-culture model showed a unique expression profile of differentially expressed genes (DEGs) compared to controls. GO/KEGG analysis indicated these DEGs were mainly linked to cell differentiation and growth factor secretion pathways. Neuronal and astrocytic markers further confirmed enhanced NSC differentiation and neuronal maturation in the co-culture model. In vivo, live imaging and human nuclei immunofluorescence staining revealed that transplanted cells persisted for some time post-transplantation. Histological analysis showed that during acute inflammation, both the stem cell and combined therapy groups significantly inhibited microglial polarization. In the chronic phase, these groups reduced fibrotic scar formation and encouraged astrocytic bridging. Behavioral tests, including swimming and gait analysis, demonstrated that combined CT and EES therapy was more effective than either treatment alone. In summary, the combined therapy offers a promising approach for spinal cord injury treatment, providing superior outcomes over individual treatments. Our findings underscore the potential of a combined treatment approach utilizing stem cells transplantation and EES as an effective strategy for the comprehensive management of spinal cord crush injury in mice. This integrated approach holds promise for enhancing functional recovery and improving the quality of life for individuals with spinal cord injury (SCI).

The Thoughtful program: a randomized controlled study of a mentalization-based mental health education intervention in a psychiatric outpatient population

Background P-factor and mentalizing theory and research set perspectives for transdiagnostic psychiatric treatments. Aims To test the effects of a low-cost mentalization-based health education program (the Thoughtful program) in an unselected waiting list population, from a psychiatric outpatient clinic in North Norway. Methods Waiting list patients were randomized (1:1 allocation): 79 patients in the control group were offered standard individual assessment and treatment. Seventy-nine patients in the intervention group were offered a one-day (six-hour) group-based Thoughtful course, plus individual assessment, and treatment. Results During a 6-month follow-up period, the number of patients in active assessment and treatment was 66% higher in the control group than in the intervention group. Self-reported patient questionnaire scores on mentalizing, well-being and suicidal ideation scores showed no significant changes in the control group. In the intervention group, significant changes were reported: Mentalizing scores improved by 72% and well-being scores improved by 55%. Suicidal ideation scores were not significantly changed. No adverse effects were registered. Limitations The results from this study should be interpreted with caution because of a small population size and low questionnaire response rate. The follow up period was limited to 6 months. Transfer of program information from intervention group patients to control group patients could not be guaranteed. It may be considered a limitation that diagnostic pattern analysis was not included in the study. Conclusions A low-cost transdiagnostic mentalization-based educational program in an outpatient psychiatry clinic may improve patient mentalizing and wellbeing without adverse effects and reduce the use of hospital services.

Synergistic Antihyperglycemic Effects of Soursop Leaves and Garlic in Alloxan-Induced Rats

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by elevated blood glucose levels due to impaired insulin production. Natural remedies, such as soursop leaves (Annona muricata) (SL) and garlic (Allium sativum) (GAR), are known for their antihyperglycemic properties. This study aimed to investigate the effects of SL and GAR extracts, individually and in combination, on reducing blood glucose levels in alloxan-induced diabetic rats. A total of 24 male Wistar rats were divided into six groups, receiving treatments of either metformin, SL, GAR, or their combination for seven days following alloxan administration to induce hyperglycemia. Blood glucose levels were measured before and after induction, and post-treatment on day 15. The results showed that the combined extracts exhibited better antihyperglycemic activity compared to individual treatments, with the most effective dose being 26.3 mg/kg BW SL + 31.5 mg/kg BW GAR.

Managing atropine-induced psychosis in organophosphate poisoning: A case report

Atropine-induced psychosis, though rare, is a critical adverse effect that can arise during the treatment of organophosphate (OP) poisoning, necessitating swift recognition for optimal patient care. This case report describes the presentation of a 45-year-old male with a history of chronic alcoholism and smoking, admitted for OP intoxication, who developed acute psychosis after atropine administration. The symptoms included hallucinations, agitation, and delirium, with diagnostic evaluation confirming atropine-induced psychosis according to DSM-IV-TR criteria. The treatment approach involved discontinuing atropine and providing supportive care, which resulted in symptom resolution within several days. In addition, benzodiazepines were administered to manage agitation and anxiety. This case highlights the need for careful monitoring of drug reactions, particularly in patients with risk factors, such as chronic alcoholism. It underscores the importance of individualized treatment strategies and the critical role of healthcare professionals in recognizing and addressing atropine-induced psychosis. Further research is warranted to better understand the underlying mechanisms and risk factors associated with this complication.

Nanomedicine in Cancer Treatment: Mechanisms, Applications, and Future Directions

Nanomedicine, an emerging field at the intersection of nanotechnology and medicine, holds significant promise for revolutionizing cancer treatment. By utilizing materials at the nanoscale, ranging from 1 to 100 nanometers, nanomedicine offers a versatile platform for targeting tumors, improving drug delivery, and minimizing side effects. This paper explores the design and preparation of nanoparticles, including common materials like liposomes, polymers, metals, and quantum dots, as well as their mechanisms of targeted delivery through both passive and active methods. Key applications of nanomedicine are discussed, particularly in chemotherapy, immunotherapy, and imaging. Clinical progress is highlighted through examples such as FDA-approved drugs like Onivyde for pancreatic cancer and experimental treatments like BIND-014 for metastatic prostate cancer. Despite rapid advancements, significant challenges remain, particularly in scaling up production and ensuring batch consistency. Safety concerns, such as nanoparticle toxicity and unintended accumulation in organs, must be addressed through rigorous testing and design improvements. Ethical considerations and regulatory hurdles also pose obstacles to the widespread clinical adoption of nanomedicine. Looking forward, multifunctionalization and personalized nanomedicine represent key areas of future growth, offering the potential for highly individualized treatments that combine therapeutic and diagnostic capabilities. Continued research and collaboration across scientific disciplines will be crucial in overcoming current limitations and unlocking the full potential of nanomedicine for cancer treatment.

Identifying Prostatic Utricle Translucent Membrane in Hematospermia Patients Using a Novel Nomogram.

Aims/Background Hematospermia, characterized by blood in the ejaculate, is a common and distressing condition in urology. Identifying the underlying causes, including translucent membranes in the prostatic utricle, is crucial for effective management. Despite advancements in diagnostic techniques, reliable predictive tools are needed to enhance preoperative planning and patient outcomes. This study aimed to develop a novel nomogram to predict the presence of translucent membranes in the prostatic utricle of hematospermia patients. Methods In total, 284 patients were selected from The Second People's Hospital of Hefei database based on inclusion and exclusion criteria. The cohort was divided into a training set (198 patients) and a validation set (86 patients). To identify risk factors associated with the prostatic utricle translucent membrane, multivariable logistic regression analysis was employed. The identified risk factors were then used to construct a predictive nomogram model. The performance of the nomogram was evaluated using several statistical tools: receiver operating characteristic (ROC) curves to assess discriminative ability, calibration curves to evaluate prediction accuracy, and decision curve analysis (DCA) to determine clinical utility. Results The findings revealed that age, duration of disease, history of seminal vesiculitis, and seminal vesicle dimensions (width, length, and thickness) were independent risk factors for the presence of a prostatic utricle translucent membrane in patients with hematospermia. Using these variables, a nomogram was developed. The nomogram demonstrated strong predictive capability, as evidenced by its performance in ROC and calibration curve analyses. Furthermore, the DCA indicated that the nomogram offered significant clinical net benefits in predicting the presence of a translucent membrane. Conclusion Clinical use of the developed nomogram can assist clinicians in identifying patients with hematospermia who have translucent membrane in the prostatic utricle and in developing individualized treatment.

Gestational diabetes and pregnancy outcome in Kurdish, Somali and general population in Finland

Abstract Gestational diabetes (GDM) increases the risk of type II diabetes and cardiovascular morbidity later in life but GDM incidence in women from different cultural backgrounds varies. This study aims to examine treatment of GDM and pregnancy outcomes in Somali, Kurdish and general population women. Patient data of 312 Kurdish, 254 Somali and 508 general population women was collected from Turku University Hospital records from 2008 to 2019. The general population was selected by randomization with matching year, BMI, age, and parity. Singleton deliveries after 34th gestational week with no prior diabetes mellitus were included. Descriptive and comparison analyses (SPSS, version 29.0) were used to identify associations between ethnic background and pregnancy outcomes in women with GDM. The incidence of GDM was 22 % (CI 95 % 17-27) in Somali, 36 % (CI 95 % 31-42) in Kurdish, and 16 % (CI 95 % 13-19) in the general population women. Kurdish women had medication for GDM more often (43 % CI 95 % 34-53) than the Somali (22 % CI 95 % 11-33) and general population women (18 % CI 95 % 9-26). Metformin was more commonly used among Kurdish (30 % CI 95 % 22-39) compared to the general population (12 % CI 95 % 4-18) and Somali women (13 % CI 95 % 4-22). There was no difference in insulin or combined metformin and insulin treatment between the groups. In GDM group, vaginal deliveries were more common in general population (89 % CI % 81-95) than in Somali women (67 % CI % 64-81). Induction of labour (indication GDM or other) and instrumental vaginal delivery rates were similar between the groups. Newborns of all Somali women had a lower weight (SD -0.3 CI 95 % -0.7 - -0.2) compared to the general population (SD 0 CI 95 % -0.1 - 0.3). The prevalence of GDM was increased and dietary treatment decreased in Kurdish women compared to the general population in Finland. In the future, the treatment of GDM should be adjusted to better optimize the care for different cultural background women. Key messages • Kurdish women have increased incidence of GDM and less dietary treatment compared to the general population with similar risk factors. The pregnancy outcomes remain good in all groups. • With Somali women, the birth weight of the child is lower despite GDM status. This might direct clinicians to underestimate the effect of GDM when considering individual treatment.

Estimation of individual lifetime cardiovascular disease risk and treatment benefit in patients with established atherosclerotic cardiovascular disease: the updated SMART-REACH2 model

Abstract Background The 2021 ESC Guidelines on Cardiovascular Disease (CVD) Prevention in Clinical Practice recommend using (lifetime) risk to guide preventive treatment intensification. Purpose Updating and systematically recalibrating the SMART-REACH lifetime prediction model for the estimation of lifetime risk of recurrent CVD in patients with established atherosclerotic CVD (ASCVD) to various European and international risk regions. Methods The updated SMART-REACH (i.e., SMART-REACH2) model was derived using data from 9,477 individuals between 40-90 years with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms included in the UCC-SMART cohort in whom 2,090 ASCVD events were observed during a median follow-up of 8.9 years (interquartile range 4.5–14.1). Coefficients for type of CVD, estimated glomerular filtration rate, non-high density lipoprotein cholesterol, systolic blood pressure, duration of CVD, C-reactive protein, current smoking, and presence of diabetes were derived using sex-stratified cause-specific Cox models with age as the time axis, adjusted for the competing risk of non-CVD mortality. Lifetables were used to estimate 10-year and lifetime CVD-risk and CVD-free life expectancy. The SMART-REACH2 model was externally validated in 121,701 patients from the NOR-COR, Nor-COAST, HUNT3, SWEDEHEART, Bialystok PLUS/Polaspire, REACH-EU, and REACH non-EU (Asia, Japan, Latin America, North America) covering 43 countries. The model was recalibrated to specific risk regions based on the expected-observed ratios from representative cohorts. Performance was assessed by calibration of predicted and observed risk and Harrel’s C-statistic for discrimination. Results 16,689ASCVD events were observed in the external validation cohorts. The model was visually well calibrated for the various risk regions. The pooled C-statistic across risk regions was 0.665 [95% confidence interval 0.640-0.691], with adequate performance in the separate regions (Figure 1). Using SMART-REACH2 to estimate potential gain in CVD-free life expectancy upon treatment initiation showed varying projections. For example, two comparable 55-year-old males from the low-risk region and very high-risk region would gain an estimated 2.2 and 3.9 CVD-free life years as a result of smoking cessation (Figure 2). Conclusion(s) By using larger and more contemporary data sources, considering geographical differences, and extending the age range, the updated SMART-REACH2 model provides an improved algorithm for the estimation of lifetime risk and CVD-free life expectancy for individuals with established ASCVD, facilitating shared decision-making for cardiovascular prevention as recommended by the 2021 ESC Prevention of CVD guidelines.C-statistics across global risk regionsCase vignette

Comparative Analysis of Digital Transcriptomics Between Pre- and Post-Treatment Samples of Patients with Locally Advanced Cervical Cancer: A Preliminary Study

Cervical cancer remains a leading cause of cancer-related deaths in women worldwide, with limited treatment options for advanced stages and therapy-resistant cases. Despite advances in treatment, the variability in the patient response to standard therapies underscores the need for molecular biomarkers to guide personalized treatment strategies. This study aimed to explore the transcriptomic changes associated with the therapeutic response in locally advanced cervical cancer, focusing on 770 immune-related genes. We employed a digital multiplexed gene expression analysis, comparing gene expression profiles between matching pre- and post-treatment samples. The results revealed the significant upregulation of C7 and EGR2 in the post-treatment samples, suggesting that enhanced immune activity is a key factor in therapeutic success. Conversely, IL17RB, S100A7, and SAA1 were upregulated in the pre-treatment samples, potentially indicating resistance mechanisms. Pathway enrichment analysis highlighted that the immune response and apoptosis pathways are crucial to post-treatment changes. These findings suggest that C7, EGR2, and IL17RB may serve as biomarkers for predicting therapeutic outcomes and could inform the development of more effective, individualized treatment strategies for cervical cancer. This study provides new insights into the molecular mechanisms underlying treatment response and resistance.