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The β-Lactam antibiotics represent a widely used class of antibiotics, yet the latent and often overlooked risk of coagulation dysfunction associated with their use underscores the need for proactive assessment. Machine learning methodologies can offer valuable insights into evaluating the risk of coagulation dysfunction associated with β-lactam antibiotics. This study aims to identify the risk factors associated with coagulation dysfunction related to β-lactam antibiotics and to develop machine learning models for estimating the risk of coagulation dysfunction with real-world data. A retrospective study was performed using machine learning modeling analysis on electronic health record data, employing five distinct machine learning methods. The study focused on adult inpatients discharged from 1 January 2018, to 31 December 2021, at the First Affiliated Hospital of Shandong First Medical University. The models were developed for estimating the risk of coagulation dysfunction associated with various β-lactam antibiotics based on electronic health record feasibility. The dataset was divided into training and test sets to assess model performance using metrics such as total accuracy and area under the curve. The study encompassed risk-factor analysis and machine learning model development for coagulation dysfunction in inpatients administered different β-lactam antibiotics. A total of 45,179 participants were included in the study. The incidence of coagulation disorders related to cefazolin sodium, cefoperazone/sulbactam sodium, cefminol sodium, amoxicillin/sulbactam sodium, and piperacillin/tazobactam sodium was 2.4%, 5.4%, 1.5%, 5.5%, and 4.8%, respectively. Machine learning models for estimating coagulation dysfunction associated with each β-lactam antibiotic underwent validation with 5-fold cross-validation and test sets. On the test set, the optimal models for cefazolin sodium, cefoperazone/sulbactam sodium, cefminol sodium, amoxicillin/sulbactam sodium, and piperacillin/tazobactam sodium yielded AUC values of 0.798, 0.768, 0.919, 0.783, and 0.867, respectively. The study findings suggest that machine learning classifiers can serve as valuable tools for identifying patients at risk of coagulation dysfunction associated with β-lactam antibiotics and intervening based on high-risk predictions. Enhanced access to administrative and clinical data could further enhance the predictive performance of machine learning models, thereby expanding pharmacovigilance efforts.

BackgroundPrecise preoperative evaluation of lymph node metastasis (LNM) is crucial for ensuring effective treatment for rectal cancer (RC). This research aims to develop a clinical-radiomics nomogram based on deep learning techniques, preoperative magnetic resonance imaging (MRI) and clinical characteristics, enabling the accurate prediction of LNM in RC.Materials and methodsBetween January 2017 and May 2023, a total of 519 rectal cancer cases confirmed by pathological examination were retrospectively recruited from two tertiary hospitals. A total of 253 consecutive individuals were selected from Center I to create an automated MRI segmentation technique utilizing deep learning algorithms. The performance of the model was evaluated using the dice similarity coefficient (DSC), the 95th percentile Hausdorff distance (HD95), and the average surface distance (ASD). Subsequently, two external validation cohorts were established: one comprising 178 patients from center I (EVC1) and another consisting of 88 patients from center II (EVC2). The automatic segmentation provided radiomics features, which were then used to create a Radscore. A predictive nomogram integrating the Radscore and clinical parameters was constructed using multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate the discrimination capabilities of the Radscore, nomogram, and subjective evaluation model, respectively.ResultsThe mean DSC, HD95 and ASD were 0.857 ± 0.041, 2.186 ± 0.956, and 0.562 ± 0.194 mm, respectively. The nomogram, which incorporates MR T-stage, CEA, CA19-9, and Radscore, exhibited a higher area under the ROC curve (AUC) compared to the Radscore and subjective evaluation in the training set (0.921 vs. 0.903 vs. 0.662). Similarly, in both external validation sets, the nomogram demonstrated a higher AUC than the Radscore and subjective evaluation (0.908 vs. 0.735 vs. 0.640, and 0.884 vs. 0.802 vs. 0.734).ConclusionThe application of the deep learning method enables efficient automatic segmentation. The clinical-radiomics nomogram, utilizing preoperative MRI and automatic segmentation, proves to be an accurate method for assessing LNM in RC. This approach has the potential to enhance clinical decision-making and improve patient care.Research registration unique identifying number (UIN)Research registry, identifier 9158, https://www.researchregistry.com/browse-the-registry#home/registrationdetails/648e813efffa4e0028022796/.

Left atrial (LA) fibrosis is a major arrhythmogenic substrate for atrial fibrillation (AF). The purpose of this study was to assess whether isoproterenol (ISO) induces LA fibrosis and increases susceptibility to AF, exploring the underlying mechanisms. Male Sprague-Dawley rats were subcutaneously injected ISO once per day for 2 days. Five weeks after injection, the ISO group had higher susceptibility AF and prolonged AF duration compared with the control group. ISO decreased LA conduction velocity (CV) and increased LA conduction heterogeneity. ISO increased fibrosise areas and the protein levels of collagen types I and III in the left atrium. Antifibrosis drug pirfenidone decreased AF occurrence and reduced LA fibrosis in ISO treated rats. ISO injection induced atrial ischemia infarction by increasing heart rate and decreasing diastolic and systolic blood pressures. These findings demonstrated that ISO increases susceptibility to AF by increasing LA fibrosis and LA conduction abnormalities 5 weeks after injection. ISO injection induces atrial ischemic injury is the main cause of fibrosis. Rats with ISO-induced LA fibrosis may be used in further AF research.

The increasing incidence and mortality of prostate cancer worldwide significantly impact the life span of male patients, emphasizing the urgency of understanding its pathogenic mechanism and associated molecular changes that regulate tumor progression for effective prevention and treatment. RNA modification, an important post-transcriptional regulatory process, profoundly influences tumor cell growth and metabolism, shaping cell fate. Over 170 RNA modification methods are known, with prominent research focusing on N6-methyladenosine, N7-methylguanosine, N1-methyladenosine, 5-methylcytidine, pseudouridine, and N4-acetylcytidine modifications. These alterations intricately regulate coding and non-coding RNA post-transcriptionally, affecting the stability of RNA and protein expression levels. This article delves into the latest advancements and challenges associated with various RNA modifications in prostate cancer tumor cells, tumor microenvironment, and core signaling molecule androgen receptors. It aims to provide new research targets and avenues for molecular diagnosis, treatment strategies, and improvement of the prognosis in prostate cancer.

BackgroundRadical cystectomy and urinary diversion (UD) are gold standards for non-metastatic muscle-invasive bladder cancer. Orthotopic neobladder (or Studer), ileal conduit (or Bricker) and cutaneous ureterostomy (CU) are mainstream UD types. Little is known about urinary microbiological changes after UD. MethodsIn this study, urine samples were collected from healthy volunteers and patients with bladder cancer who had received aforementioned UD procedures. Microbiomes of samples were analyzed using 16S ribosomal RNA gene sequencing, and microbial diversities, distributions and functions were investigated and compared across groups. ResultsHighest urine microbial richness and diversity were observed in healthy controls, followed by Studer patients, especially those without hydronephrosis or residual urine, α-diversity indices of whom were remarkably higher than those of Bricker and CU groups. Studer UD type was the only independent factor favoring urine microbial diversity. The urine microflora structure of the Studer group was most similar to that of the healthy individuals while that of the CU group was least similar. Studer patients and healthy volunteers shared many similar urine microbial functions, while Bricker and CU groups exhibited opposite characteristics. ConclusionOur study first presented urinary microbial landscapes of UD patients and demonstrated the microbiological advantage of orthotopic neobladder. Microbiota might be a potential tool for optimization of UD management.

The piRNA (PIWI-interacting RNA) is P-Element induced wimpy testis (PIWI)-interacting RNA which is a small molecule, non-coding RNA with a length of 24-32nt. It was originally found in germ cells and is considered a regulator of germ cell function. It can interact with PIWI protein, a member of the Argonaute family, and play a role in the regulation of gene transcription and epigenetic silencing of transposable factors in the nucleus. More and more studies have shown that piRNAs are abnormally expressed in a variety of cancer tissues and patient fluids, and may become diagnostic tools, therapeutic targets, staging markers, and prognostic evaluation tools for cancer. This article reviews the recent research on piRNA and summarizes the structural characteristics, production mechanism, applications, and its role in urological tumors, to provide a reference value for piRNA to regulate urological tumors.

PurposeThis study aimed to develop a nomogram to predict the recovery of immediate urinary continence in laparoscopic radical prostatectomy (LRP) patients.MethodsA prediction model was developed based on a dataset of 154 LRP patients. Immediate urinary continence was defined as free from using pads within 7 days after the removal of the urinary catheter. The least absolute shrinkage and selection operator regression (LASSO) model was applied to screen the features. Multivariate logistic regression analysis was used to establish prediction model integrating the features selected from the LASSO regression analysis. Receiver operating curve (ROC), calibration and decision curve analysis (DCA) were used to assess the model's discrimination, calibration and clinical utility.ResultsThe identified features of the prediction model included age, body mass index (BMI) and three pelvic anatomic parameters measured by MRI: membranous urethral length (MUL), intravesical prostatic protrusion length (IPPL) and puborectalis muscle width (PMW). The nomogram showed good discrimination with an are under the curve(AUC) of 0.914 (95% CI, 0.865–0.959, p

BackgroundClear cell adenocarcinoma (CCA) is considered a relatively rare tumor with a glycogen-rich phenotype. The prognosis of CCA patients is unclear. In this study, recent trends in the epidemiological and prognostic factors of CCA were comprehensively investigated.MethodsPatients with CCA from years 2000 to 2016 were identified from the Surveillance, Epidemiological, and End Results (SEER) database. Relevant population data were used to analyze the rates age-adjusted incidence, age-standardized 3-year and 5-year relative survivals, and overall survival (OS).ResultsThe age-adjusted incidence of CCA increased 2.7-fold from the year 2000 (3.3/100,000) to 2016 (8.8/100,000). This increase occurred across all ages, races, stages, and grades. Of all these subgroups, the increase was largest in the grade IV group. The age-standardized 3-year and 5-year relative survivals increased during this study period, rising by 9.1% and 9.5% from 2000 to 2011, respectively. Among all the stages and grades, the relative survival increase was greatest in the grade IV group. According to multivariate analysis of all CCA patients, predictors of OS were: age, gender, year of diagnosis, marital status, race, grade, stage, and primary tumor site (P < 0.001). The OS of all CCA patients during the period 2008 to 2016 was significantly higher than that from 2000 to 2007 (P < 0.001).ConclusionsThe incidence of CCA and survival of these patients improved over time. In particular, the highest increases were reported for grade IV CCA, which may be due to an earlier diagnosis and improved treatment.

The progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) increases the risk of death. It is therefore important to find new relevant molecular models that will allow for effective prediction of the progression and prognosis of bladder cancer (BC). Using RNA-Sequence data of 49 BC patients in Shanghai tenth people’s hospital (STPH) and weighted gene co-expression network analysis methods, a co-expression network of genes was developed and three key modules associated with malignant progression were selected. Based on the genes in three key modules, an eight-gene risk signature was established using univariate Cox regression and the Least absolute shrinkage and selection operator Cox model in The Cancer Genome Atlas Program (TCGA) and validated in validation sets. Subsequently, a nomogram based on the risk signature was constructed for prognostic prediction. The mRNA and protein expression levels of eight genes in cell lines and tissues were further investigated. The novel eight-gene risk signature was closely related to the malignant clinical features of BC and could predict the prognosis of patients in the training dataset (TCGA) and four validation sets (GSE32894, GSE13507, IMvigor210 trial, and STPH). The nomogram showed good prognostic prediction and calibration. The mRNA and protein expression levels of the eight genes were differentially expressed in cell lines and tissues. In our study, we established a novel eight-gene risk signature that could predict the progression and prognoses of BC patients.

ObjectiveThe malignant progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) is common and has detrimental effect on patients. We aimed to elucidate the underlying mechanisms of the malignant progression from an immunological perspective and establish a reliable signature for prognostic prediction and immunotherapeutic strategies.MethodsThe Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm was applied to the GSE32894 data set to identify the different tumor-infiltrating immune cells involved in NMIBC and MIBC. Using weighted gene correlation network analysis, survival analysis and least absolute shrinkage and selection operator Cox analysis, we established an immune prognostic signature (IPS) based on 14 overall survival-associated immune genes in The Cancer Genome Atlas (TCGA). Functional enrichment analyses and nomogram were performed to explore the potential effects and prognostic performance of the IPS. Furthermore, the RNA-sequence data from our center were used to validate the expression levels of the selected immune genes in BLCA samples.ResultsDiverse proportions of macrophage subtypes were observed between NMIBC and MIBC. Patients with high risk scores had a worse prognosis than patients with low risk scores in training (TCGA) and validation data sets (GSE32894, GSE13507, and GSE48277). The IPS was a useful prognostic factor for patients treated with immunotherapy in the IMvigor210 trial. Hallmarks of multiple oncogenic pathways were significantly enriched in the high risk group. A novel nomogram model was established for prognostic predictions. The dysregulated expression of the selected immune genes between NMIBC and MIBC was also validated in BLCA samples.ConclusionDysregulation of the immune microenvironment promoted the malignant progression from NMIBC to MIBC. The IPS can stratify patients into different risk groups with distinct prognoses and immunotherapeutic susceptibility, thus facilitating personalized immunotherapy.

Objective: The prognosis of patients with prostate cancer (PCa) has improved in recent years, but treatment-related cardiotoxicity remains unclear. This study investigated the heart-specific mortality and prognostic factors of patients with PCa after radiotherapy (RT) or radical prostatectomy (RP), and compared their long-term heart-specific mortality with that of the general male population.Materials and Methods: Data were taken from the Surveillance, Epidemiology, and End Result (SEER) database. Patients with PCa were included who underwent RT or RP from 2000 to 2012, and were followed through 2015. A cumulative mortality curve and a competitive risk regression model were applied to assess the prognostic factors of heart-specific mortality. Standardized mortality rates (SMRs) were calculated.Results: Of 389,962 men, 49.7% and 50.3% received RP and RT, respectively. The median follow-up was 8.3 years. For patients given RT, in about 9 years postdiagnosis, the cumulative mortality due to heart-specific disease exceeded that due to PCa. In patients who underwent RP, cumulative mortality from heart-specific disease or PCa was comparable. Relative to the general male population, overall, the heart-specific mortality of patients with PCa receiving RT or RP was not higher, but in patients aged 70 to 79 years, those given RT experienced slightly higher heart-specific mortality than the age-matched general population.Conclusions: Patients with PCa treated with RT or RP overall do not incur risk of heart-specific mortality higher than that of the general male population, except for patients aged 70–74 years receiving RT.

Background: Currently, the diagnosis of non-organ-confined bladder cancer (NOCBCa) has a very poor prognosis. For patients with NOCBCa, treatments such as radical cystectomy (RC) and systemic chemotherapy have shown survival benefits. However, the relative survival benefits of trimodal therapy (TMT) are unclear.Methods: Patients diagnosed with NOCBCa (cT4bN0M0, cTxN1-3M0, or TxNxM1) were identified in the Surveillance, Epidemiology, and End Results (SEER) database (2004–2015). Patients were grouped based on their definitive treatment for bladder cancer (RC or TMT with maximal transurethral resection, chemotherapy, or radiotherapy). All-cause mortality (ACM) and bladder cancer-specific mortality (BCSM) were assessed by Cox proportional hazard regression and competitive risk models.Results: A total of 2,988 patients met the inclusion criteria and were treated with RC (83.5%) or TMT (16.5%). Patients who underwent TMT had higher 5-year ACM (91.3%) and BCSM (88.8%) results compared to patients who underwent RC (82.6 and 75.0%, respectively) (P < 0.001). Adjusted hazard rate (AHR) analysis showed that TMT was associated with higher ACM (AHR: 1.33, 95% CI: 1.15–1.54, P < 0.001) and higher BCSM (AHR: 1.32, 95% CI: 1.13–1.54, P = 0.001). Subgroup analysis revealed not statistically significant between RC and TMT among patients aged ≥80 years (P > 0.05).Conclusions: Compared with TMT, RC is associated with a significant reduction in ACM and BCSM. However, the risks and survival benefits of RC should be weighed, especially in older patients, and our results further suggest that there may be no difference in the prognosis of RC and TMT in patients ≥80 years of age. These results are preliminary and emphasize the need for randomized controlled trials to compare TMT and RC.

Background: Metastasis is the primary cause of cancer deaths, warranting further investigation. This study assessed microRNA-153 (miR-153) expression in bladder cancer tissues and investigated the underlying molecular mechanism of miR-153-mediated regulation of bladder cancer cells.Methods: Paired tissue specimens from 45 bladder cancer patients were collected for qRT-PCR. The Cancer Genome Atlas (TCGA) dataset was used to identify associations of miR-153 with bladder cancer prognosis. Bladder cancer tissues and immortalized cell lines were used for the following experiments: miR-153 mimics and indoleamine 2,3-dioxygenase 1 (IDO1) siRNA transfection; Western blot, cell viability, colony formation, and Transwell analyses; nude mouse xenograft; and chicken embryo chorioallantoic membrane angiogenesis (CAM) assays. Human umbilical vein endothelial cells (HUVECs) were co-cultured with bladder cancer cells for the tube formation assay. The luciferase reporter assay was used to confirm miR-153-targeting genes.Results: miR-153 expression was downregulated in bladder cancer tissues and cell lines, and reduced miR-153 expression was associated with advanced tumor stage and poor overall survival of patients. Moreover, miR-153 expression inhibited bladder cancer cell growth by promoting tumor cell apoptosis, migration, invasion, and endothelial mesenchymal transition (EMT) in vitro and tumor xenograft growth in vivo, while miR-153 expression suppressed HUVEC and CAM angiogenesis. At the gene level, miR-153 targeted IDO1 expression and inhibited bladder cancer cell tryptophan metabolism through inhibiting IL6/STAT3/VEGF signaling.Conclusions: Collectively, our data demonstrate that miR-153 exerts anti-tumor activity in bladder cancer by targeting IDO1 expression. Future studies will investigate miR-153 as a novel therapeutic target for bladder cancer patients.

Objective: This study compared survival of prostate cancer patients with low prostate specific antigen level (PSA ≤ 10 ng/ml) and high-grades of Gleason score (GS) of 8–10 with different treatment options (i.e., radical prostatectomy [RP], external beam radiotherapy [EBRT], or external beam radiotherapy with brachytherapy [EBRT+BT]).Materials and Methods: The Surveillance, Epidemiology and End Results (SEER) database data (2004–2013), and overall survival (OS) and prostate cancer-specific mortality (PCSM), were evaluated using the Cox proportional hazards regression model and Fine and Gray competing risk model.Results: The SEER data contained 9,114 patients, 4,175 of whom received RP, 4,114 received EBRT, and 825 received EBRT+BT with a median follow-up duration of 47 months. RP patients had significantly better OS than patients with EBRT and EBRT+BT (adjusted HR [AHR]: 3.36, 95% CI: 2.43–4.64, P < 0.001; AHR: 2.15, 95% CI: 1.32–3.48, P = 0.002; respectively). There was no statistical difference in PCSM between RP and EBRT+BT (AHR: 1.31, 95% CI: 0.61–2.80, P = 0.485), while EBRT had worse OS (P < 0.05). The subgroup analysis revealed that there was no statistical difference in prognosis of patients with age of >70 years old, or PSA levels of ≤ 2.5 ng/ml between RP and EBRT+BT (P > 0.05).Conclusion: RP patients with low PSA levels and high GS had better OS compared to either EBRT or EBRT+BT, while RP and EBRT+BT resulted in significantly lower PCSM, compared to EBRT. Moreover, EBRT+BT and RP were associated with similar survival of patients with age of > 70 years old, or PSA levels of ≤ 2.5 ng/ml.