Effectiveness of Traditional Chinese Medicine for Liver Protection and Chemotherapy Completion among Cancer Patients

While traditional Chinese medicine (TCM) is widely used among Chinese patients with cancer, studies evaluating the effectiveness of TCM using objective indicators are rare. We examined the effectiveness of TCM for liver protection and completion of chemotherapy among patients with cancer receiving chemotherapy. We used a case-control design to examine the medical records of patients with cancer who received chemotherapy in a teaching hospital in Taipei in 2004. A total of 184 courses of chemotherapy among 89 patients were studied. Of the 184 courses, 42 used TCM jointly with chemotherapy served as cases, while the remaining 142 courses served as controls. Outcome variables included counts of cancelled or delayed chemotherapies and liver function (aspartate aminotransferase, AST and alanine aminotransferase, ALT) 1 week before, during and 2 weeks after chemotherapy. Generalized estimating equations were used to analyze the data. Patients who had concomitant TCM with chemotherapy had lower serum ALT and AST during chemotherapy than the controls given that the age, sex, cancer stage, radiotherapy sites, cancer diagnosis and potential hepatotoxicity of the chemotherapeutic drugs were controlled for in the model [β  = −3.48, 95% confidence interval (CI) −10.08 to 3.11 for AST; β  = −5.95, 95% CI: −11.47 to −0.44 for ALT]. There was no significant difference between the case and control groups for odds of completing one course of chemotherapy. Use of TCM with chemotherapy resulted in protection of the liver during chemotherapy, as manifested by lower serum AST and ALT levels

Illiquidity Premium and Monetary Conditions in Emerging Markets: An Empirical Examination of Taiwan Stock Markets

This study empirically examines the illiquidity premium of Taiwan stock markets and its relationship with monetary policies. We find that commonly used illiquidity measures are generally sensitive and capable of capturing market illiquidity, particularly during the most volatile periods. Evidence shows that unconditional illiquidity is significantly priced across three illiquidity measures during the sample period. Aggregate market illiquidity innovations are noticeably affected by monetary policies. The results of Granger causality tests reveal that expansive monetary policy improves market illiquidity, whereas restrictive policy adversely affects market liquidity. Keywords: Illiquidity; illiquidity premium; monetary policy; asset pricing; Granger's causality tests JEL Classifications: G11, G12, G15 DOI: https://doi.org/10.32479/ijefi.895

Efficacy of Sanfujiu to Treat Allergies: Patient Outcomes at 1 Year after Treatment

Sanfujiu is a treatment method of applying herbal paste onto the acupoints Fengmen and Feishu during the three hottest days of summer to treat patients with allergies. The objectives of this study were to determine the treatment efficacy at 1 year after the Sanfujiu treatment, and examine variations in the perceived efficacy of Sanfujiu among different subgroups, based on the patients' ages, diagnoses and number of reactive symptoms immediately after the treatment. We enrolled 105 patients who completed Sanfujiu treatment at a medical university hospital in Taipei as the subjects. One year after treatment, trained interviewers conducted telephone interviews with the patients. Approximately 60% of them perceived the treatment as being effective at 1 year later, which was higher than that at 1 week after treatment (45.7%). Younger subjects (<19 years of age) and patients with asthma were more likely to report the treatment as being effective. Patients who had more reactive symptoms after the third Sanfujiu treatment were more likely to report the treatment as being effective. The results demonstrated that Sanfujiu was moderately effective, as perceived by patients in Taiwan, in treating their allergic symptoms

Deep Learning-based Fall Detection Algorithm Using Ensemble Model of Coarse-fine CNN and GRU Networks

Falls are the public health issue for the elderly all over the world since the fall-induced injuries are associated with a large amount of healthcare cost. Falls can cause serious injuries, even leading to death if the elderly suffers a "long-lie". Hence, a reliable fall detection (FD) system is required to provide an emergency alarm for first aid. Due to the advances in wearable device technology and artificial intelligence, some fall detection systems have been developed using machine learning and deep learning methods to analyze the signal collected from accelerometer and gyroscopes. In order to achieve better fall detection performance, an ensemble model that combines a coarse-fine convolutional neural network and gated recurrent unit is proposed in this study. The parallel structure design used in this model restores the different grains of spatial characteristics and capture temporal dependencies for feature representation. This study applies the FallAllD public dataset to validate the reliability of the proposed model, which achieves a recall, precision, and F-score of 92.54%, 96.13%, and 94.26%, respectively. The results demonstrate the reliability of the proposed ensemble model in discriminating falls from daily living activities and its superior performance compared to the state-of-the-art convolutional neural network long short-term memory (CNN-LSTM) for FD

Outcome and prognostic factors in critically ill patients with systemic lupus erythematosus: a retrospective study

INTRODUCTION: Systemic lupus erythematosus (SLE) is an archetypal autoimmune disease, involving multiple organ systems with varying course and prognosis. However, there is a paucity of clinical data regarding prognostic factors in SLE patients admitted to the intensive care unit (ICU). METHODS: From January 1992 to December 2000, all patients admitted to the ICU with a diagnosis of SLE were included. Patients were excluded if the diagnosis of SLE was established at or after ICU admission. A multivariate logistic regression model was applied using Acute Physiology and Chronic Health Evaluation II scores and variables that were at least moderately associated (P < 0.2) with survival in the univariate analysis. RESULTS: A total of 51 patients meeting the criteria were included. The mortality rate was 47%. The most common cause of admission was pneumonia with acute respiratory distress syndrome. Multivariate logistic regression analysis showed that intracranial haemorrhage occurring while the patient was in the ICU (relative risk = 18.68), complicating gastrointestinal bleeding (relative risk = 6.97) and concurrent septic shock (relative risk = 77.06) were associated with greater risk of dying, whereas causes of ICU admission and Acute Physiology and Chronic Health Evaluation II score were not significantly associated with death. CONCLUSION: The mortality rate in critically ill SLE patients was high. Gastrointestinal bleeding, intracranial haemorrhage and septic shock were significant prognostic factors in SLE patients admitted to the ICU

Carbon nanotube composites for glucose biosensor incorporated with reverse iontophoresis function for noninvasive glucose monitoring

This study aims to develop an amperometric glucose biosensor, based on carbon nanotubes material for reverse iontophoresis, fabricated by immobilizing a mixture of glucose oxidase (GOD) and multiwalled carbon nanotubes (MWCNT) epoxy-composite, on a planar screen-printed carbon electrode. MWCNT was employed to ensure proper incorporation into the epoxy mixture and faster electron transfer between the GOD and the transducer. Results showed this biosensor possesses a low detection potential (+500 mV), good sensitivity (4 μA/mM) and an excellent linear response range (r2 = 0.999; 0–4 mM) of glucose detection at +500 mV (versus Ag/AgCl). The response time of the biosensor was about 25 s. In addition, the biosensor could be used in conjunction with reverse iontophoresis technique. In an actual evaluation model, an excellent linear relationship (r2 = 0.986) was found between the glucose concentration of the actual model and the biosensor’s current response. Thus, a glucose biosensor based on carbon nanotube composites and incorporated with reverse iontophoresis function was developed

Overexpression of Nuclear Protein Kinase CK2 α Catalytic Subunit (CK2α) as a Poor Prognosticator in Human Colorectal Cancer

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignancies but the current therapeutic approaches for advanced CRC are less efficient. Thus, novel therapeutic approaches are badly needed. The purpose of this study is to investigate the involvement of nuclear protein kinase CK2 α subunit (CK2α) in tumor progression, and in the prognosis of human CRC. METHODOLOGY/PRINCIPAL FINDINGS: Expression levels of nuclear CK2α were analyzed in 245 colorectal tissues from patients with CRC by immunohistochemistry, quantitative real-time PCR and Western blot. We correlated the expression levels with clinicopathologic parameters and prognosis in human CRC patients. Overexpression of nuclear CK2α was significantly correlated with depth of invasion, nodal status, American Joint Committee on Cancer (AJCC) staging, degree of differentiation, and perineural invasion. Patients with high expression levels of nuclear CK2α had a significantly poorer overall survival rate compared with patients with low expression levels of nuclear CK2α. In multi-variate Cox regression analysis, overexpression of nuclear CK2α was proven to be an independent prognostic marker for CRC. In addition, DLD-1 human colon cancer cells were employed as a cellular model to study the role of CK2α on cell growth, and the expression of CK2α in DLD-1 cells was inhibited by using siRNA technology. The data indicated that CK2α-specific siRNA treatment resulted in growth inhibition. CONCLUSIONS/SIGNIFICANCE: Taken together, overexpression of nuclear CK2α can be a useful marker for predicting the outcome of patients with CRC