Managing Pain with Laser Acupuncture

According to the theory of traditional Chinese medicine, Qi flows through the body along specific paths known as meridians. Any disturbance in Qi evokes a Ying−Yang imbalance in the body, and consequently leads to disease. Pain results from blood stasis and Qi stagnation. Laser acupuncture (LA), first introduced clinically in the 1970s, combines the advantages of traditional acupuncture and modern laser medicine and has been applied for the treatment of various diseases. Here, we investigated studies on the use of LA for pain management according to current evidence. Articles including English keywords related to the use of LA for pain, published between January 2006 and August 2015 were sourced from PubMed, Medline, and Cochrane Library databases. On the basis of these papers, we explored the modern applications, mechanisms, and analgesic effects of LA. LA integrates the positive effects of acupuncture and low-level laser therapy, and is therefore effective in activating blood and in moving Qi. LA relieves pain through both anti-inflammatory and analgesic effects. No adverse effects or complications resulting from LA were reported in the literature. In the hands of an experienced physician, LA can be a useful and safe method for pain management

Study on the Correlation between Objective Evaluations and Subjective Speech Quality and Intelligibility

Subjective tests are the gold standard for evaluating speech quality and intelligibility, but they are time-consuming and expensive. Thus, objective measures that align with human perceptions are crucial. This study evaluates the correlation between commonly used objective measures and subjective speech quality and intelligibility using a Chinese speech dataset. Moreover, new objective measures are proposed combining current objective measures using deep learning techniques to predict subjective quality and intelligibility. The proposed deep learning model reduces the amount of training data without significantly impacting prediction performance. We interpret the deep learning model to understand how objective measures reflect subjective quality and intelligibility. We also explore the impact of including subjective speech quality ratings on speech intelligibility prediction. Our findings offer valuable insights into the relationship between objective measures and human perceptions

Prescription characteristics of Xue-Fu-Zhu-Yu-Tang in pain management: a population-based study using the National Health Insurance Research Database in Taiwan

Objective: To explore the prevalence and distinctive features of Xue-Fu-Zhu-Yu-Tang (XFZYT) prescriptions by analyzing the National Health Insurance Research Database (NHIRD) to identify the specific medical problems for which XFZYT is prescribed.Methods: This nationwide, population-based, cross-sectional study included 109,073 XFZYT users and 532,848 XFZYT non-users among Chinese herbal product (CHP) users in NHIRD. Chi-squared tests were used to analyze disparities between the XFZYT user and XFZYT non-user cohorts, and the mean age was evaluated using the Wilcoxon rank-sum test. Logistic regression was used to compute the odds ratios (ORs) and 95% confidence intervals (95% CIs).Results: XFZYT was frequently used to treat pain. The top five conditions for which the Taiwanese traditional Chinese medicine (TCM) practitioners would prescribe XFZYT were chest pain; headache; myalgia and myositis; lumbago; and neuralgia, neuritis, and radiculitis.Conclusion: This study represents an inaugural comprehensive survey conducted on the utilization of XFZYT prescriptions among patients with diverse diseases. XFZYT is mostly used to treat pain conditions in Taiwan. Combined with the combination use of other CHPs, XFZYT is used to treat symptoms of the chest and respiratory system, soft tissue conditions, menstruation disorders, and joint and back discomfort. These results suggest that further clinical trials are warranted to verify the effects of XFZYT in pain management

Improvement of Carbon Tetrachloride-Induced Acute Hepatic Failure by Transplantation of Induced Pluripotent Stem Cells without Reprogramming Factor c-Myc

The only curative treatment for hepatic failure is liver transplantation. Unfortunately, this treatment has several major limitations, as for example donor organ shortage. A previous report demonstrated that transplantation of induced pluripotent stem cells without reprogramming factor c-Myc (3-genes iPSCs) attenuates thioacetamide-induced hepatic failure with minimal incidence of tumorigenicity. In this study, we investigated whether 3-genes iPSC transplantation is capable of rescuing carbon tetrachloride (CCl4)-induced fulminant hepatic failure and hepatic encephalopathy in mice. Firstly, we demonstrated that 3-genes iPSCs possess the capacity to differentiate into hepatocyte-like cells (iPSC-Heps) that exhibit biological functions and express various hepatic specific markers. 3-genes iPSCs also exhibited several antioxidant enzymes that prevented CCl4-induced reactive oxygen species production and cell death. Intraperitoneal transplantation of either 3-genes iPSCs or 3-genes iPSC-Heps significantly reduced hepatic necrotic areas, improved hepatic functions, and survival rate in CCl4-treated mice. CCl4-induced hepatic encephalopathy was also improved by 3-genes iPSC transplantation. Hoechst staining confirmed the successful engraftment of both 3-genes iPSCs and 3-genes iPSC-Heps, indicating the homing properties of these cells. The most pronounced hepatoprotective effect of iPSCs appeared to originate from the highest antioxidant activity of 3-gene iPSCs among all transplanted cells. In summary, our findings demonstrated that 3-genes iPSCs serve as an available cell source for the treatment of an experimental model of acute liver diseases

Disease Incidence-Severity Relationships on Leaflets, Leaves, and Fruit in the Pecan-Venturia effuse Pathosystem

The most destructive disease of pecan in the southeastern United States is scab, caused by Venturia effusa. Incidence (I)-severity (S) relationships have not previously been characterized in this pathosystem, but incidence measures can save time and should have higher accuracy compared with estimates of severity. Ten scab-susceptible cultivars and seedling trees were assessed for I and S of scab on fruit (1,972 trees) and foliage (compound leaves and leaflets, 1,129 trees) between 2010 and 2014. Samples were assessed on a tree basis, and sample size ranged from 10 to 100 specimens per tree. The range in mean I and S was different depending on the organ (fruit I = 0 to 100%, S = 0 to 100%; compound leaves and leaflets, I = 0 to 100%, S = 0-10.1%, respectively). However, mean I could be 100% at a mean S 80%. The observation that low severity persists until a high incidence of scab is achieved may limit the ability of incidence data to clearly differentiate treatment effects, even when based on the CLL transformation. But if found to be effective, and if used, it would reduce the labor requirements and result in more accurate data being obtained, as incidence estimates do not tend to suffer from the same subjective biases as do visual estimates of severity

Plant disease severity estimated visually: a century of research, best practices and opportunities for improving methods and practices to maximize accuracy

Plant disease quantification, mainly the intensity of disease symptoms on individual units (severity) is the basis for a plethora of research and applied purposes in plant pathology and related disciplines. These include evaluating treatment effect, monitoring epidemics, understanding yield loss, and phenotyping for host resistance. Although sensor technology has been available to measure disease severity using the visible spectrum or other spectral range imaging, it is visual sensing and perception that still dominates, especially in field research. Awareness of the importance of accuracy of visual estimates of severity began in 1892, when Cobb developed a set of diagrams as an aid to guide estimates of rust severity in wheat. Since that time, various approaches, some of them based on principles of psychophysics, have provided a foundation to understand sources of error during the estimation process as well as to develop different disease scales and disease-specific illustrations indicating the diseased area on specimens, similar to that developed by Cobb, and known as standard area diagrams (SADs). Several rater-related (experience, inherent ability, training) and technology-related (instruction, scales and SADs) characteristics have been shown to affect accuracy. This review provides a historical perspective of visual severity assessment, accounting for concepts, tools, changing paradigms, and methods to maximize accuracy of estimates. A list of best operating practices in plant disease quantification and future research on the topic is presented based on the current knowledge

Confidence interval procedures for proportions estimated by group testing with groups of unequal size adjusted for overdispersion

Group testing is a method of pooling a number of units together and performing a single test on the resulting group. Group testing is an appealing option when few individual units are thought to be infected and the cost of the testing is non-negligible. Overdispersion is the phenomenon of having greater variability than predicted by the random component of the model; this is common in the modeling of binomial distribution for group testing. The purpose of this paper is to provide a comparison of several established methods of constructing confidence intervals after adjusting for overdispersion. We evaluate and investigate each method in six different cases of group testing. A method based on the score statistic with correction for skewness is recommended. We illustrate the methods using two data sets, one from the detection of seed transmission and the other from serological testing for malaria

Confidence interval procedures for proportions estimated by group testing with groups of unequal size adjusted for overdispersion

Group testing is a method of pooling a number of units together and performing a single test on the resulting group. Group testing is an appealing option when few individual units are thought to be infected and the cost of the testing is non-negligible. Overdispersion is the phenomenon of having greater variability than predicted by the random component of the model; this is common in the modeling of binomial distribution for group testing. The purpose of this paper is to provide a comparison of several established methods of constructing confidence intervals after adjusting for overdispersion. We evaluate and investigate each method in six different cases of group testing. A method based on the score statistic with correction for skewness is recommended. We illustrate the methods using two data sets, one from the detection of seed transmission and the other from serological testing for malaria