Search

Thyroid cancer (TC) is the most common endocrine malignancy. Recently, the global incidence of TC has increased rapidly. Differentiated thyroid cancer includes papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC), which are the most common types of TC. Although PTCs and FTCs exert good prognoses and high survival rates, FTCs tend to be more aggressive than PTCs. There is an urgent need to improve patient outcomes by developing effective therapeutic agents for FTCs. Piperlongumine exerts anti-cancer effects in various human carcinomas, including human anaplastic TCs and PTCs. However, the anti-cancer effects of piperlongumine in FTCs and the underlying mechanisms are yet to be elucidated. Therefore, in the present study, we evaluated the effect of piperlongumine on cell proliferation, cell cycle, apoptosis, and autophagy in FTC cells with flowcytometry and Western blot. We observed that piperlongumine caused growth inhibition, cell cycle arrest, apoptosis induction, and autophagy elevation in FTC cells. Activities of reactive oxygen species and the downstream PI3K/Akt pathway were the underlying mechanisms involved in piperlongumine mediated anti-FTC effects. Advancements in our understanding of the effects of piperlongumine in FTC hold promise for the development of novel therapeutic strategies.

Many studies have revealed that statin therapy reduced mortality in cancer patients, especially in breast cancer, but the effect for second cancer was unclear. We, therefore, performed a comparable cohort study to determine the risk of second cancer in breast cancer patients with statin therapy. Using claims data from Taiwan’s National Health Insurance Program, this study enrolled newly diagnosed breast cancer patients from 2000 to 2007 with and without statin therapy as the statin (n = 1222) and nonstatin (n = 4888) cohorts, respectively. The nonstatin cohort was propensity score matched by cohort entry year, age, and randomly selected comorbidities. These two cohorts were followed up until the diagnosis of second cancer, death, or the end of 2011. Cox proportional hazard models were used to estimate the hazard ratios. The statin cohort had a lower incidence rate than the nonstatin cohort for second cancer (7.37 vs. 8.36 per 1000 person-years), although the difference was not significant (adjusted hazard ratio [aHR] 0.90, 95% confidence interval [CI] 0.65–1.26). Compared with the nonstatin cohort, the second cancer risk was significantly higher for patients taking pravastatin (aHR 2.71, 95% CI 1.19–6.19) but lower for those receiving multiple statin treatment (aHR 0.45, 95% CI 0.25–0.81) and combined lipophilic and hydrophilic type of statin (aHR 0.42, 95% CI 0.20–0.89). The risk was lower for patients receiving a cumulative defined daily dose (cDDD) of > 430 (aHR 0.41, 95% CI 0.19–0.86). This study showed that there is little association between statin use and second cancer risk in breast cancer patients.

Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder which is quite common in childhood, with an estimated prevalence of 5–8%, and often persists into adolescence and adulthood. It is further characterized as inappropriate developmentally symptoms of inattention, impulsiveness, motor over-activity and restlessness. The aim of this study is to evaluate the feasibility of diagnosing ADHD by analyzing the resting-state functional magnetic resonance imaging (fMRI) data. In addition to confirming the previously observed three areas including anterior cingulate cortex (ACC), posterior cingulated cortex (PCC) and ventro medial prefrontal cortex (vmPFC), we also found significant differences in cerebellum, motor cortex and temporal lobe between ADHD and normal humans based on regional homogeneity analysis of the dataset from 73 children with ADHD and 76 normal children. Extracting features from these seven brain areas and utilizing the LDA classifier, the average accuracy of distinguishing normal and ADHD children reaches 80.08% though 50 times of 2-fold validation. Experimental results demonstrate the feasibility of ADHD diagnosis based on the combination of functional connectivity of resting-state fMRI and machine learning technique.

Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short detection latency, and (4) energy-efficient design for hardware implementation.