Ginseng, an oriental gift to the world of healthcare and preventive medicine, is among the top ten medicinal herbs globally. The constitutive triterpene saponins, ginsenosides, or panaxosides are ...attributed to ginseng’s miraculous efficacy towards anti-aging, rejuvenating, and immune-potentiating benefits. The major ginsenosides such as Rb1, Rb2, Rc, Rd., Re, and Rg1, formed after extensive glycosylations of the aglycone “dammaranediol,” dominate the chemical profile of this genus in vivo and in vitro. Elicitations have successfully led to appreciable enhancements in the production of these major ginsenosides. However, current research on ginseng biotechnology has been focusing on the enrichment or production of the minor ginsenosides (the less glycosylated precursors of the major ginsenosides) in ginseng preparations, which are either absent or are produced in very low amounts in nature or via cell cultures. The minor ginsenosides under current scientific scrutiny include diol ginsenosides such as Rg3, Rh2, compound K, and triol ginsenosides Rg2 and Rh1, which are being touted as the next “anti-neoplastic pharmacophores,” with better bioavailability and potency as compared to the major ginsenosides. This review aims at describing the strategies for ginsenoside production with special attention towards production of the minor ginsenosides from the major ginsenosides via microbial biotransformation, elicitations, and from heterologous expression systems.
We assess American cultural beliefs about labor pain and labor pain management, including stereotypical and disparate beliefs about labor pain of women from different racial groups.
Understanding ...cultural beliefs about labor pain is critical as these beliefs influence experience, interpretation, and treatment of labor pain.
We used an online survey with quantitative and qualitative questions about American labor pain beliefs. Participants were recruited and compensated using TurkPrime's Panels during the first week in August 2017 and the last week in May 2018. The completion rate was 76.86 percent (n = 214). After screening using quality control items, the final sample included 200 respondents.
Qualitative results indicate that 56.5 percent (n = 113) of respondents have an accurate understanding of nociceptive/sensory drivers of labor pain, and 55.8 percent (n = 63) of those respondents focused on the second stage of labor. However, only two respondents (1%) mentioned non-sensory (i.e., psychological) causes of labor pain - reflecting a lack of cultural knowledge of the biopsychosocial nature of pain. Categorical responses indicate almost all respondents (95%; n = 190) believe women have a right to labor pain relief, and the majority believe labor pain has value (68%; n = 136) and should be treated medically (87%; n = 174). Quantitative results document stereotypical beliefs that women of color experience less labor pain than white women. Belief that there is value in experiencing labor pain and that pain should not be treated medically were both associated with greater racial disparities in beliefs about labor pain severity. Beliefs were not related to respondent sociodemographic identity, suggesting they are American cultural constructs.
Future consideration of the influence of dominant American cultural beliefs about labor pain – including misunderstanding of the nature of labor pain and racial bias in expectations of labor pain – on individuals, norms, and structures is expected to improve quality of patient care.
•American beliefs about causes of labor pain are often inaccurate.•Beliefs focus on sensory/physical sources and ignore social/psychological factors.•Explicit belief that women of color experience less labor pain than white women.•General cultural beliefs about labor pain are associated with racial biases.
A central evolutionary challenge for social groups is uniting a heterogeneous set of individuals towards common goals. One means by which social groups form and endure is by endowing group members ...with extraordinary prosocial proclivities, such as ingroup love, towards other group members. Here we examined the neural basis of extraordinary empathy and altruistic motivation in African-American and Caucasian-American individuals using functional magnetic resonance imaging. Our results indicate that empathy for ingroup members is neurally distinct from empathy for humankind, more generally. People showed greater response within anterior cingulate cortex and bilateral insula when observing the suffering of others, but African-American individuals additionally recruit medial prefrontal cortex when observing the suffering of members of their own social group. Moreover, neural activity within medial prefrontal cortex in response to pain expressed by ingroup relative to outgroup members predicted greater empathy and altruistic motivation for one's ingroup, suggesting that neurocognitive processes associated with self identity underlie extraordinary empathy and altruistic motivation for members of one's own social group. Taken together, our findings reveal distinct neural mechanisms of empathy and altruistic motivation in an intergroup context and may serve as a foundation for future research investigating the neural bases of intergroup prosociality, more broadly construed.
Support vector machines (SVMs) have considerable potential as classifiers of remotely sensed data. A constraint on their application in remote sensing has been their binary nature, requiring ...multiclass classifications to be based upon a large number of binary analyses. Here, an approach for multiclass classification of airborne sensor data by a single SVM analysis is evaluated against a series of classifiers that are widely used in remote sensing, with particular regard to the effect of training set size on classification accuracy. In addition to the SVM, the same datasets were classified using a discriminant analysis, decision tree, and multilayer perceptron neural network. The accuracy statements of the classifications derived from the different classifiers were compared in a statistically rigorous fashion that accommodated for the related nature of the samples used in the analyses. For each classification technique, accuracy was positively related with the size of the training set. In general, the most accurate classifications were derived from the SVM approach, and with the largest training set the SVM classification was significantly (p < 0.05)more accurate (93.75%) than that derived from the discriminant analysis (90.00%) and decision tree algorithms (90.31%). Although each classifier could yield a very accurate classification, > 90% correct, the classifiers differed in the ability to correctly label individual cases and so may be suitable candidates for an ensemble-based approach to classification.
•Presents a novel design of latent thermal energy storage for concentrating solar power.•Presents a rigorous computational modeling of the system to elucidate its performance.•Presents optimum design ...of the thermal energy storage system.
Storing sun’s energy in the form of latent thermal energy of a phase change material (PCM) offers high volumetric energy storage density resulting in low capital cost. The objective of this paper is to analyze the dynamic behavior of a packed bed thermal energy storage system with encapsulated PCMs, subjected to partial charging and discharging cycles, and constraints on charge and discharge temperatures as encountered in a concentrating solar power (CSP) plant operation. A transient, numerical analysis of a molten salt, single tank latent thermocline energy storage system (LTES) is performed for repeated charging and discharging cycles to investigate its dynamic response. The influence of the design configuration and operating parameters on the dynamic storage and delivery performance of the system is studied to identify configurations that maximize utilization of the storage system. Based on the parametric studies, guidelines are derived for designing a packed bed PCM based storage system for CSP plant operating conditions.
Instead small-scale trials with differing methodologies continue to be performed, adding to the confusion. ...there remains a need to ensure that clinical trials are performed with rigour and ...attention to detail. Previously the European Society of Cardiology Task Force for Stem Cells in Cardiac Disease published recommendations 2 regarding the need to rationalise clinical trials in this field to avoid the accumulation of trial data with varying methodologies and hence the danger of creating a large pool of unrelated knowledge in which a clear signal would be difficult to detect. Several explanations have been put forward to explain this discrepancy, including the use of automated instead of manual cell processing in the US study with a potential loss of ‘active cellular’ component. ...the rationale for intramyocardial delivery of autologous cell therapy for the treatment of heart failure is scientifically justified but not clinically proven. ...this line of clinical translation will disappear not through lack of scientific endeavour but through lack of commercial opportunity to deliver into the existing healthcare systems.
The objective of this work was to determine the impact of therapeutic hypothermia (TH) on the magnitude and time course of mean diffusivity (MD) changes following hypoxic-ischemic encephalopathy ...(HIE) in newborns.
Cerebral MRI scans of infants undergoing whole body TH for HIE from 2007 to 2010 were retrospectively reviewed. The data were analyzed identically to a control group of newborns with HIE previously published, prior to the development of TH. Anatomic injury was defined on T1- and T2-weighted ("late") MRI obtained after the fifth day of life. Since MD values vary regionally, the ratios of MD values for injured and normal tissue were calculated for areas of injury. Normal values were obtained from corresponding brain regions of 12 infants undergoing TH who had no injury on MRI studies.
Twenty-three of 59 infants who underwent TH and MRI displayed cerebral injury on late MRI and were included in the study. MD ratios were decreased in all injured infants within the first 7 days of life. The return of MD to normal (pseudonormalization) occurred after the tenth day as compared to 6-8 days in the control group. Infants with severest injury demonstrated greater reduction in MD, but no difference in time to pseudonormalization.
TH slows the evolution of diffusion abnormalities on MRI following HIE in term infants.
We aimed to identify recipient, donor and transplant risk factors associated with graft failure and patient mortality following donation after cardiac death (DCD) liver transplantation. These ...estimates were derived from Scientific Registry of Transplant Recipients data from all US liver‐only DCD recipients between September 1, 2001 and April 30, 2009 (n = 1567) and Cox regression techniques. Three years post‐DCD liver transplant, 64.9% of recipients were alive with functioning grafts, 13.6% required retransplant and 21.6% died. Significant recipient factors predictive of graft failure included: age ≥ 55 years, male sex, African–American race, HCV positivity, metabolic liver disorder, transplant MELD ≥ 35, hospitalization at transplant and the need for life support at transplant (all, p ≤ 0.05). Donor characteristics included age ≥ 50 years and weight >100 kg (all, p ≤ 0.005). Each hour increase in cold ischemia time (CIT) was associated with 6% higher graft failure rate (HR 1.06, p < 0.001). Donor warm ischemia time ≥ 35 min significantly increased graft failure rates (HR 1.84, p = 0.002). Recipient predictors of mortality were age ≥ 55 years, hospitalization at transplant and retransplantation (all, p ≤ 0.006). Donor weight >100 kg and CIT also increased patient mortality (all, p ≤ 0.035). These findings are useful for transplant surgeons creating DCD liver acceptance protocols.
Several recipient, donor, and transplant‐related factors are associated with increased graft failure and mortality risk following DCD liver transplant, but this study found that donor warm ischemia time greater than 35 minutes was particularly noteworthy.
Support vector machines (SVMs) have considerable potential for supervised classification analyses, but their binary nature has been a constraint on their use in remote sensing. This typically ...requires a multiclass analysis be broken down into a series of binary classifications, following either the one-against-one or one-against-all strategies. However, the binary SVM can be extended for a one-shot multiclass classification needing a single optimization operation. Here, an approach for one-shot multi- class classification of multispectral data was evaluated against approaches based on binary SVM for a set of five-class classifications. The one-shot multiclass classification was more accurate (92.00%) than the approaches based on a series of binary classifications (89.22% and 91.33%). Additionally, the one-shot multi- class SVM had other advantages relative to the binary SVM-based approaches, notably the need to be optimized only once for the parameters C and 7 as opposed to five times for one-against-all and ten times for the one-against-one approach, respectively, and used fewer support vectors, 215 as compared to 243 and 246 for the binary based approaches. Similar trends were also apparent in results of analyses of a data set of larger dimensionality. It was also apparent that the conventional one-against-all strategy could not be guaranteed to yield a complete confusion matrix that can greatly limit the assessment and later use of a classification derived by that method.
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