Purpose: Metastatic rectal cancer (mRC) is a highly lethal and complex disease that demands a multidisciplinary treatment approach. However, the clinical effectiveness of radiotherapy (RT) for de novo mRC remains controversial and uncertain. Methods: This retrospective cohort study examined medical records from Kaohsiung Chang Gung Memorial Hospital for patients with histologically confirmed de novo mRC diagnosed between January 2015 and December 2020. All patients received standard systemic therapy and radical surgery when feasible. The primary outcome, overall survival (OS), was assessed using the Kaplan-Meier method. Multivariable analysis was performed using a Cox regression model. Results: Among 271 patients included in the analysis, 117 received RT and 154 did not. The median OS was significantly longer in the RT group compared with the non-RT group (27.8 months vs. 21.9 months; P=0.046). Multivariate analysis identified several independent predictors of OS: age ≥65 years (hazard ratio [HR], 1.69; 95% confidence interval [CI], 1.26–2.27; P=0.001), primary tumor resection (HR, 2.62; 95% CI, 1.90–3.61; P<0.001), M1b or M1c disease (HR, 1.97; 95% CI, 1.44–2.69; P<0.001), and receipt of RT (HR, 1.41; 95% CI, 1.02–1.94; P=0.036). Conclusion RT significantly improves OS in patients with mRC, underscoring its role in treatment strategies. These findings support its inclusion in therapeutic protocols and highlight the need for larger, multicenter trials to confirm and extend these results.

Background: Cerebral hypoxia-ischemia impairs brain development in extremely preterm infants and is associated with poor neurological outcomes. Near-infrared spectroscopy (NIRS) is a noninvasive continuous monitoring method for regional cerebral oxygen saturation (rcSO2).Purpose: This study evaluated the clinical feasibility and neurological impact of a neurocritical care bundle that incorporates prolonged multidisciplinary hemodynamic monitoring and a stepwise management algorithm. Methods: Preterm infants with a gestational age (GA) ≤28 weeks or birth weight (BW) ≤1,000 g were prospectively enrolled in a bundle group subjected to NIRS for rcSO2, electrical cardiometry for cardiac output, and daily brain and cardiac echography during the first 72 hours of life. Monitoring was repeated weekly in the first month and then monthly until discharge or the term-equivalent age (TEA) was reached. We implemented a stepwise management algorithm for treating cerebral hypoxia. The primary outcome was a composite of mortality and adverse neurological events (structural abnormalities or electroencephalogram-confirmed seizures) before discharge. The secondary outcomes were the physiological pattern of rcSO2 within the initial 72 hours and up to discharge or TEA. Results: Thirty preterm infants (GA, 27.1±2.0 weeks; BW, 830±225 g) were enrolled in the bundle group. The mean time-averaged rcSO2 (66.8%±10.3%) was not associated with GA or BW. However, postnatal age appeared to influence physiological rcSO2 changes, given that rcSO2 values were higher during the initial 72 hours than at subsequent intervals. Seven infants (23.3%) had poor outcomes and significantly lower time-averaged rcSO2 (51.1% [50.0%–65.2%] vs. 71.8% [67.1%–73.1%], P=0.002). Multivariate regression indicated that a lower rcSO2 was an independent risk factor, and a 65% threshold showed an optimal predictive value for poor outcomes. Conclusion The neurocritical care bundle helped identify preterm infants at risk of cerebral hypoxia, and lower rcSO2 was an independent risk factor for composite mortality and adverse neurological outcomes.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

OBJECTIVE: To evaluate the short-term clinical efficacy of external fixation and internal fixation with steel plate in the treatment of unstable distal radius fractures (AO-23C type), based on the principles of Chinese osteosynthesis (CO). METHODS: Forty-eight patients with unstable distal radius fractures between January 2022 and February 2023 were retrospectively analyzed and divided into the CO external fixation group and internal fixation group. CO external fixation group consisted of 25 patients, including 7 males and 18 females, aged from 37 to 56 years old with an average of ( 52.6±11.3) years old. Among them, there were 7 patients of traffic accidents and 18 patients of falls, resulting in a total of 25 patients of closed fractures and no open fractures, the treatment was conducted using closed reduction and CO external fixation. The internal fixation group consisted of 23 patients, comprising 8 males and 15 females, age ranged from 41 to 59 years old, with an average age of(53.3±13.7) years old. Among them, 8 patients resulted from car accidents while the remaining 15 patients were caused by falls. All 23 patients were closed fractures without any open fractures observed. The technique of open reduction and internal fixation with steel plate was employed. The perioperative data, including injury-operation time, operation duration, blood loss, and length of hospital stay, were assessed in both groups. Additionally, the QuickDASH score and visual analogue scale (VAS) were evaluated. Range of motion and grip strength assessment, imaging findings such as palmar inclination angle, ulnar declination angle, radius length, articular surface step, intra-articular space measurements were also examined along with any complications. RESULTS: The follow-up duration ranged from 0 to 24 months, with an average duration of (16.0±3.8) months. The CO external fixation exhibited significantly shorter time from injury to operation (2.4±3.3) d vs (7.4±3.7) d, shorter operation duration (56.27±15.23) min vs (74.10±5.26) min, lower blood loss (14.52±6.54) ml vs (32.32±10.03) ml, and reduced hospitalization days (14.04±3.24 )d vs (16.45±3.05) d compared to the internal fixation group (P<0.05). The QuickDASH score at 12 months post-operation was (8.21±1.64) in the CO external fixation group, while no significant difference was observed in the internal fixation group (7.04±3.64), P>0.05. There were no statistically significant differences in VAS between two groups at 6 weeks, as well as 1 and 3 months post-surgery (P>0.05). Additionally, there were no significant disparities observed in terms of range of motion and grip strength between two groups at the 2-year follow-up after the operation (P>0.05). After 12 months of surgery, the CO external fixation group exhibited a significantly smaller palmar inclination angle (17.90±2.18) ° vs (19.87±3.21) °, reduced articular surface step (0.11±0.03) mm vs (0.17±0.02) mm, and shorter radius length (8.16±1.11) mm compared to the internal fixation group (9.59±1.02) mm, P<0.05. The ulnar deviation angle and intra-articular space did not show any significant difference between two groups (P>0.05). The reduced fell within the allowable range between the CO external fixation group (23 out of 25 cases) and the internal fixation group (21 out of 23 cases) was not statistically significant (P=0.29). There was no significant difference in complications between the two groups(P>0.05). CONCLUSION Both the CO external fixation and open reduction with plate internal fixation demonstrate clinical efficacy in managing unstable distal radius fractures. The CO external fixation offers advantages in shorter injury-to-operation times, reduced intraoperative blood loss, and decreased surgical durations, while radial shortening is more effectively controlled by internal fixation.
Humans ; Male ; Female ; Middle Aged ; Radius Fractures/physiopathology* ; Adult ; Bone Plates ; Fracture Fixation, Internal/methods* ; External Fixators ; Retrospective Studies ; Fracture Fixation/methods* ; Wrist Fractures

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare and worsened quality of life (QOL). Advanced esophageal cancer is often accompanied by malnutrition and poor QOL; chemoradiotherapy (CRT) remains the mainstay of treatment.We evaluated nutrition and QOL pre- and post-CRT immediately before and during the pandemic. Methods: Patients with esophageal cancer who underwent neoadjuvant or definitive CRT between April 2019 and December 2020 were enrolled. Disease severity, treatment timing, and outcomes were compared for cohorts treated pre-COVID-19 and during COVID-19. Nutritional status was measured with the Patient-Generated Subjective Global Assessment (PG-SGA). QOL was measured with the Mandarin Chinese version of the European Organization for Research and Treatment of Cancer core questionnaire (EORTC QLQ-C30) and the esophageal site-specific module (QLQ-OES18). In the pandemic cohort, pre-/post-CRT paired analyses were performed. Results: Eighty-four patients were enrolled. The median diagnosis to treatment interval lengthened during COVID-19 (17.8 days vs. 24.2 days, p=0.04). Among the patients treated during the COVID-19 pandemic, nutritional status improved significantly following CRT (p=0.003). In the EORTC QLQ-C30, post-CRT scores for global health status (p<0.01) and emotional functioning (p<0.01) showed significant improvement. Additionally, symptom scores, including fatigue (p=0.02) and nausea and vomiting (p=0.02), decreased. However, financial difficulties worsened after CRT (p=0.02). In the EORTC QLQ-OES18, post-CRT symptom scores for eating (p<0.01), reflux (p=0.03), and pain (p<0.01) showed significant improvement. Conclusion Despite COVID-19-related delays, CRT enhanced nutrition, global health, and symptom control in esophageal cancer, although financial burdens increased. Integrating socioeconomic support with oncologic care is vital during health crises.

ObjectiveTo explore the scientific connotation of fried charcoal survivability of Lonicerae Japonicae Flos（LJF） by analyzing the correlation between the color change and the intrinsic components during the processing of LJF Carbonisata（LJFC）， and taking pH， charcoal adsorption and microscopic characteristics as indexes. MethodLJFC samples with different degrees of processing were prepared according to the stir-frying time of 0.0， 1.5， 3.0， 4.5， 6.0， 7.5， 9.0， 10.5 min（numbered S1-S8）， and the contents of gallic acid， chlorogenic acid， cryptochlorogenic acid， rutin， luteoloside， isochlorogenic acid A and isochlorogenic acid C were determined by high performance liquid chromatography（HPLC）， and the L^*（brightness）， a^*（red-greenness） and b^*（yellow-blueness） of LJFC samples with different degrees of processing were determined by spectrophotometer， and the correlation analysis and principal component analysis（PCA） between the contents of seven representative components and the color of the samples were carried out by SPSS 26. 0 and SIMCA-P 14.1. Then pH， adsorption force and characteristic structure of different samples of LJFC were detected and the processing pattern of LJFC was analyzed. ResultThe results of quantitative analysis revealed that the contents of luteoloside， rutin， chlorogenic acid and isochlorogenic acid A gradually decreased， and the contents of cryptochlorogenic acid， isochlorogenic acid C and gallic acid firstly increased and then decreased. The L^* and b^* of the sample powders decreased， and a^* showed a trend of increasing and then decreasing. The L^* and b^* were positively correlated with the contents of chlorogenic acid， rutin， luteoloside， isochlorogenic acid A， b^* was positively correlated with the content of gallic acid， and a^* was positively correlated with the contents of cryptochlorogenic acid and isochlorogenic acid C. PCA revealed that samples could be clearly divided into 3 groups， S1-S2 as one group， S3-S5 as one group， and S6-S8 as one group， with S3 having the highest score. The results of regression analysis showed that only isochlorogenic acid C could be used to predict the contents of components by colorimetric values combined with regression equations. Physicochemical analysis showed that pH of LJFC increased with the increase of degree of charcoal stir-frying， while adsorption force showed a tendency of increasing and then decreasing， with the highest adsorption force in the S5 sample， and the non-glandular hairs， calcium oxalate clusters and pollen grains had a varying degree of decreasing with the deepening of processing degree， and the microstructures of S6-S8 samples were obviously charred with pollen grains almost invisible. ConclusionThe changes in chemical composition and color characteristics of LJFC during the processing have certain correlations， combined with the changes in physicochemical properties， S5 sample is found to be the optimal processed products， which can provide a reference for the processing standardization and quality evaluation of LJFC， and enrich the scientific connotation of fried charcoal survivability of LJF.