Background: Feline mammary carcinoma (FMC) is one of the most prevalent malignancies of female cats. FMC is highly metastatic and thus leads to poor disease outcomes. Among all metastases, liver metastasis occurs in about 25% of FMC patients. However, the mechanism underlying hepatic metastasis of FMC remains largely uncharacterized. Results: Herein, we demonstrate that FMC-derived extracellular vesicles (FMC-EVs) promotes the liver metastasis of FMC by activating hepatic stellate cells (HSCs) to prime a hepatic premetastatic niche (PMN). Moreover, we provide evidence that sphingosine kinase 1 (SK1) delivered by FMC-EV was pivotal for the activation of HSC and the formation of hepatic PMN. Depletion of SK1 impaired cargo sorting in FMC-EV and the EV-potentiated HSC activation, and abol‑ ished hepatic colonization of FMC cells. Conclusions Taken together, our findings uncover a previously uncharacterized mechanism underlying liver-metas‑ tasis of FMC and provide new insights into prognosis and treatment of this feline malignancy.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

OBJECTIVE: The study investigated to compare health care utilization and expenditures between diabetic patients with and without depression in Taiwan. METHODS: Health care utilization and expenditure among diabetic patients with and without depression disorder during 2000 and 2004 were examined using Taiwan's population-based National Health Insurance claims database. Health care utilization included outpatient visits and the use of inpatient services, and health expenditures were outpatient, inpatient, and total medical expenditures. Moreover, general estimation equation models were used for analyzing the factors associated with outpatient visits and expenditures. Multiple logistic regression analysis was applied for identifying the factors associated with hospitalization. RESULTS: The average annual outpatient visits and annual total medical expenditures in the study period were 44.23–52.20; NT$87,496–133,077 and 30.75–32.92; NT$64,411–80,955 for diabetic patients with and without depression. After adjustment for covariates, our results revealed that gender and complication were associated with out-patient visits. Moreover, the time factor was associated with the total medical expenditure, and residential urbanization and complication factors were associated with hospitalization. CONCLUSION: Health care utilization and expenditures for diabetic patients with depression were significantly higher than those without depression. Sex, complications, time, and urbanization are the factors associated with health care utilization and expenditures.
Cohort Studies* ; Delivery of Health Care* ; Depression* ; Health Expenditures* ; Hospitalization ; Humans ; Inpatients ; Logistic Models ; National Health Programs ; Outpatients ; Patient Acceptance of Health Care* ; Taiwan ; Time Factors ; Urbanization

Background: Liver regeneration is dependent on the proliferation of hepatocytes. Hepatic progenitorcells are intra-hepatic precursor cells capable of differentiating into hepatocytes or biliary cells.Although liver progenitor cell proliferation during the regenerative process has been observed in animalmodels of severe liver injury, it has never been observed in vivo in humans because it is unethicalto take multiple biopsy specimens for the purpose of studying the proliferation of liver progenitorcells and the roles they play in liver regeneration. Associating liver partition and portal vein ligationfor staged hepatectomy (ALPPS) is a staged procedure for inducing remnant liver hypertrophy sothat major hepatectomy can be performed safely. This staged procedure allows for liver biopsyspecimens to be taken before and after the liver begins to regenerate. Case presentation: The liverprogenitor cell proliferation is observed in a patient undergoing ALPPS for a metastatic hepatictumour. Liver biopsy is acquired before and after ALPPS for the calculation of average number ofliver progenitor cell under high magnification examination by stain of immunomarkers. This is thefirst in vivo evidence of growing liver progenitor cells demonstrated in a regenerating human liver.

Objective: Limited evidence exists regarding real-world 3-monthly paliperidone palmitate (PP3M) treatment retention and associated factors. Methods: We conducted a retrospective, nationwide cohort study using the Taiwan National Health Insurance Research Database between October 2017 and December 2019. Adult patients with schizophrenia initiated on PP3M were enrolled. The primary outcomes were time to PP3M discontinuation, time to psychiatric hospitalization, and the proportions of patients receiving the next PP3M dose within 120 days among first-, second-, and third-dose completers. Key covariates included prior PP1M duration and adequate PP3M initiation. Results: The PP3M treatment retention rates were 79.7%, 66.3%, and 52.5% after 6, 12, and 24 months, respectively, with 86.4%, 90.6%, and 90.0% of respective first-, second-, and third-dose completers receiving the next PP3M dose. Adequate PP3M initiation and prior PP1M treatment duration ＞ 180 days were associated with favorable PP3M treatment retention. In multivariate analyses, PP1M durations of 180−360 days (adjusted relative risk [aRR], 1.76) or ＜ 180 days (aRR, 2.79) were associated with PP3M discontinuation at the second dose. Inadequate PP3M initiation was associated with discontinuation at the third dose (aRR, 2.18). Patients fully adherent to PP3M treatment in the first year had a higher probability of being free from psychiatric hospitalization (86.7% at 2 years), compared with those partially adherent or non-adherent to PP3M in the first year. Conclusion Prior PP1M duration and adequate PP3M initiation are major factors affecting PP3M treatment retention. Higher PP3M treatment retention is associated with a lower risk of psychiatric hospitalization.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.