Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Protein liquid-liquid phase separation (LLPS), a pivotal phenomenon intricately linked to cellular processes, is regulated by various other proteins. However, there is still a lack of high-throughput methods for screening protein regulators of LLPS in target proteins. Here, we developed a CRISPR/Cas9-based screening method to identify protein phase separation regulators by integrating bimolecular fluorescence complementation (BiFC) and fluorescence-activated cell sorting (FACS). Using this newly developed method, we screened the RNA-binding proteins that regulate PABPN1 phase separation and identified the tumor suppressor QKI as a promoter of PABPN1 phase separation. Furthermore, QKI exhibits decreased expression levels and diminished nuclear localization in colorectal cancer cells, resulting in reduced PABPN1 phase separation, which, in turn, promotes alternative polyadenylation (APA), cell proliferation, and migration in colorectal cancer.
Humans ; Colorectal Neoplasms/genetics* ; RNA-Binding Proteins/genetics* ; Poly(A)-Binding Protein I/genetics* ; CRISPR-Cas Systems ; Flow Cytometry ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Diagnosis of isolated laryngopharyngeal reflux symptoms (ILPRS), ie, without concomitant typical reflux symptoms (CTRS), remains difficult. Mean nocturnal baseline impedance (MNBI) reflects impaired mucosal integrity. We determined whether esophageal MNBI could predict pathological esophagopharyngeal reflux (pH+) in patients with ILPRS. Methods: In this cross-sectional study conducted in Taiwan, non-erosive or low-grade esophagitis patients with predominant laryngopharyngeal reflux symptoms underwent combined hypopharyngeal multichannel intraluminal impedance-pH monitoring when off acid suppressants. Participants were divided into the ILPRS (n = 94) and CTRS (n = 63) groups. Asymptomatic subjects without esophagitis (n = 25) served as healthy controls. The MNBI values at 3 cm and 5 cm above the lower esophageal sphincter (LES) and the proximal esophagus were measured. Results: Distal but not proximal esophageal median MNBI values were significantly lower in patients with pH+ than in those with pH– (ILPRS in pH+ vs pH–: 1607 Ω vs 2709 Ω and 1885 Ω vs 2563 Ω at 3 cm and 5 cm above LES, respectively; CTRS in pH+ vs pH–: 1476 vs 2307 Ω and 1500 vs 2301 Ω at 3 cm and 5 cm above LES, respectively, P < 0.05 for all). No significant differences of any MNBI exist between any pH– subgroups and healthy controls. The areas under the receiver operating characteristic curve in the ILPRS group were 0.75 and 0.80, compared to the pH– subgroup and healthy controls (P < 0.001 for both), respectively. Interobserver reproducibility was good (Spearman correlation 0.93, P < 0.0001). Conclusion Distal esophageal MNBI predicts pathological reflux in patients with ILPRS.

Background/Aims: Hypopharyngeal multichannel intraluminal impedance-pH (HMII-pH) technology incorporating 2 trans-upper esophageal sphincter impedance channels has been developed to detect pharyngeal reflux. We used the HMII-pH technique to validate the candidate pharyngeal acid reflux (PAR) episodes based on the dual-pH tracings and determined the interobserver reproducibility. Methods: We conducted a cross-sectional study in tertiary centers in Taiwan. Ninety patients with suspected laryngopharyngeal reflux and 28 healthy volunteers underwent HMII-pH test when off acid suppressants. Candidate PAR episodes were characterized by pharyngeal pH drops of at least 2 units and reaching a nadir pH of 5 within 30 seconds during esophageal acidification. Two experts manually independently identified candidate PAR episodes based on the dual-pH tracings. By reviewing the HMII-pH tracings, HMII-pH-proven PAR episodes were subsequently confirmed. The consensus reviews of HMII-pH-proven PAR episodes were considered to be the reference standard diagnosis. The interobserver reproducibility was assessed. Results: A total of 105 candidate PAR episodes were identified. Among them 84 (80.0%; 95% CI, 71.0-87.0%) were HMII-pH-proven PAR episodes (82 in 16 patients and 2 in 1 healthy subject). Patients tended to have more HMII-pH-proven PAR episodes than healthy controls (median and percentile values [25th, 75th, and 95th percentiles]: 0 [0, 0, 3] vs 0 [0, 0, 0], P = 0.067). The concordance rate in diagnosing HMII-pH-proven PAR episodes between 2 independent observers was 92.2%. Conclusion Our preliminary data showed that 80.0% (71.0-87.0%) of the proposed candidate PAR episodes were HMII-pH-proven PAR episodes, among which the interobserver reproducibility was good.

In this study, the crude polysaccharides was extracted from Shengfupian and purified by Sevag deproteinization. Then, the purified neutral polysaccharide fragment was obtained by the DEAE-52 cellulose chromatography column and Sephadex G-100 co-lumn. The structure of polysaccharides was characterized by ultraviolet spectroscopy, infrared spectroscopy, ion chromatography, and gel permeation chromatography. To investigate the anti-inflammatory activity of Shengfupian polysaccharides, LPS was used to induce inflammation in RAW264.7 cells. The expression of the CD86 antibody on surface of M1 cells, the function of macrophages, and the content of NO and IL-6 in the supernatant were examined. An immunodepression model of H22 tumor-bearing mice was established, and the immunomodulatory activity of Shengfupian polysaccharides was evaluated based on the tumor inhibition rate, immune organ index and function, and serum cytokine levels. Research indicated that Shengfupian polysaccharides(80 251 Da) was composed of arabinose, galactose, glucose, and fructose with molar ratio of 0.004∶0.018∶0.913∶0.065. It was smooth and lumpy under the scanning electron microscope. In the concentration range of 25-200 μg·mL~(-1), Shengfupian polysaccharides exhibited little or no toxicity to RAW264.7 cells and could inhibit the polarization of cells to the M1 type and reduce the content of NO and IL-6 in the cell supernatant. It could suppress the phagocytosis of cells at the concentration of 25 μg·mL~(-1), while enhancing the phagocytosis of RAW264.7 cells within the concentration range of 100-200 μg·mL~(-1). The 200 mg·kg~(-1) Shengfupian polysaccharides could alleviate the spleen injury caused by cyclophosphamide, increase the levels of IL-1β and IL-6, and decrease the level of TNF-α in the serum of mice. In conclusion, Shengfupian polysaccharides has anti-inflammatory effect and weak immunomodulatory effect, which may the material basis of Aconm Lateralis Radix Praeparaia for dispelling cold and relieving pain.
Animals ; Mice ; Interleukin-6/genetics* ; Cytokines/metabolism* ; Polysaccharides/chemistry* ; RAW 264.7 Cells ; Anti-Inflammatory Agents/chemistry* ; Spectrophotometry, Infrared