Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy.

Methane (CH4) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH4. To address this limitation, we developed novel CH4 prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH4 production (g CH4/animal·d, ANIM-B models) and CH4 yield (g CH4/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin's concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH4 prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH4 emissions from sheep, providing valuable insights for future research and mitigation strategies.

Insomnia severity and its correlates among English as a second language (ESL) college students.

OBJECTIVE: Little is known about insomnia characteristics among the English as a second language (ESL) student population. This study compared insomnia severity between ESL students and English native-speaking students and identified correlates of insomnia in the ESL population. PARTICIPANTS: College students (N = 352) from a private university in the Northeastern United States, including 22.4% (N = 79) ESL students. METHODS: For this cross-sectional study, participants completed the Insomnia Severity Index and indices of common risk factors of insomnia along with acculturation and language anxiety. RESULTS: ESL students reported higher insomnia severity than their US counterparts after controlling for depression, anxiety, and demographics. General anxiety, language anxiety, and cognitive pre-sleep arousal were selected as the strongest predictors of insomnia among the ESL population. CONCLUSIONS: Findings suggest that ESL college group is vulnerable to greater insomnia, and language anxiety is unique and important correlate of insomnia in this population.

Randomized controlled trial of cognitive refocusing versus stimulus control treatment for college insomnia: feasibility of a brief, electronic-based, and peer-led approach.

OBJECTIVE: Performance of Cognitive Refocusing Treatment for Insomnia (CRT-I) relative to stimulus control treatment (SCT) remains unknown among college students. This pilot trial compared single-session, electronic-based, peer-led CRT-I to SCT, and as well as awareness-based (AC) and no-treatment (NTC) controls. PARTICIPANTS: College students (N = 82; Mage=18.59 [SD = 0.78]; 58% female; 61% White; 16% Hispanic) with insomnia symptoms were randomly assigned to CRT-I (n = 12), SCT (n = 14), and AC (n = 14) conditions, or non-randomly recruited to NTC (n = 42). METHODS: All participants completed baseline and one-month follow-up surveys, and reported daily task enactment (except NTC). RESULTS: Feasibility ratings were comparable across conditions. Within-group treatment effects revealed greater improvements in (a) insomnia symptom severity among CRT-I (d = 1.13) and SCT (d = 1.66) groups relative to AC (d = 0.90) and (b) pre-sleep cognitive arousal among CRT-I (d = 0.94) and SCT (d = 1.42) groups relative to AC (d = 0.75). CONCLUSIONS: Brief, electronic-based, peer-led CRT-I and SCT interventions appear feasible and potentially efficacious for college insomnia.

Cannabis use for sleep aid among high school students: Concurrent and prospective associations with substance use and sleep problems.

INTRODUCTION: Adolescents are at risk for both sleep problems and cannabis use. Despite emerging evidence for college students' self-medication with cannabis to help sleep, generalizability to earlier developmental stages remains unknown. This study remedied this literature gap by characterizing high school students' cannabis sleep aid use in terms of psychosocial correlates and prospective associations with substance use and sleep. METHODS: Data were drawn froma longitudinal urban adolescent health behavior study, Project Teen, including 4079th-11thgraders(Year 1 Mage = 16.00 [SD = 1.08, range = 13-19]; 58% female; 41% Black, 22% White, 18% Asian, 17% multiracial,2% Native Hawaiian or other Pacific Islander, 1% American Indian or Alaska Native; 12% Hispanic/Latinx). Students completed two web-based surveys (Minterval = 388.89 days [SD = 27.34]) assessingsubstance use and sleep at Year 1 (Y1) and Year 2 (Y2). RESULTS: Students reporting lifetime cannabis sleep aid use (8%) endorsed greater depression and anxiety symptoms at Y1, as well as greater cannabis, alcohol, and cigarette use (but not insomnia symptoms or sleep durations) at Y1 and Y2, compared to non-using peers. Over one year, cannabis sleep aid use was associated with increased cannabis dependence symptoms among students using cannabis, past-2-week binge drinking among students using alcohol, and lifetime cigarette use. However, cannabis sleep aid use was not prospectively associated with changes in insomnia symptoms or sleep durations. CONCLUSIONS: Although replication is needed, cannabis sleep aid use among high school students may be associated with exacerbated cannabis dependence symptoms and increased binge drinking and cigarette use over time, without the intended sleep benefit.

Full adoption of the most effective strategies to mitigate methane emissions by ruminants can help meet the 1.5 °C target by 2030 but not 2050.

To meet the 1.5 °C target, methane (CH4) from ruminants must be reduced by 11 to 30% by 2030 and 24 to 47% by 2050 compared to 2010 levels. A meta-analysis identified strategies to decrease product-based (PB; CH4 per unit meat or milk) and absolute (ABS) enteric CH4 emissions while maintaining or increasing animal productivity (AP; weight gain or milk yield). Next, the potential of different adoption rates of one PB or one ABS strategy to contribute to the 1.5 °C target was estimated. The database included findings from 430 peer-reviewed studies, which reported 98 mitigation strategies that can be classified into three categories: animal and feed management, diet formulation, and rumen manipulation. A random-effects meta-analysis weighted by inverse variance was carried out. Three PB strategies­namely, increasing feeding level, decreasing grass maturity, and decreasing dietary forage-to-concentrate ratio­decreased CH4 per unit meat or milk by on average 12% and increased AP by a median of 17%. Five ABS strategies­namely CH4 inhibitors, tanniferous forages, electron sinks, oils and fats, and oilseeds­decreased daily methane by on average 21%. Globally, only 100% adoption of the most effective PB and ABS strategies can meet the 1.5 °C target by 2030 but not 2050, because mitigation effects are offset by projected increases in CH4 due to increasing milk and meat demand. Notably, by 2030 and 2050, low- and middle-income countries may not meet their contribution to the 1.5 °C target for this same reason, whereas high-income countries could meet their contributions due to only a minor projected increase in enteric CH4 emissions.

Tobacco cigarette smokers who endorse greater intolerance for nicotine withdrawal also report more severe insomnia symptoms.

It has been suggested that nighttime nicotine withdrawal may help to explain why tobacco cigarette smokers are more likely than nonsmokers to experience clinically significant insomnia. There is also reason to believe that intolerance for withdrawal symptoms could play a role in withdrawal-related sleep disturbance. However, we are not aware of any previous research that examined whether smokers who endorse greater intolerance for smoking abstinence also report greater difficulty initiating and/or maintaining sleep. To address this question, 224 adult cigarette smokers (42.9% female, Mcigarettes per day = 21.3) completed the baseline portion of an experimental study that included assessment of current/historical smoking behavior, perceived intolerance for smoking abstinence, and insomnia severity and impact on functioning. The results indicated that, after accounting for general distress intolerance and sociodemographic factors, smokers who endorsed greater intolerance for nicotine withdrawal also reported greater insomnia severity and impact. Logistic regression further revealed that, for every 1-point increase in nicotine withdrawal intolerance scores, smokers were nearly twice as likely to score above threshold for clinically significant insomnia (p = .001). Collectively, these initial findings suggest that intolerance for nicotine withdrawal may warrant consideration as a potentially modifiable mechanistic factor in comorbid insomnia and nicotine/tobacco dependence. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Sleep Problems and Drinking Frequency among Urban Multiracial and Monoracial Adolescents: Role of Discrimination Experiences and Negative Mood.

Mounting evidence suggests that multiracial adolescents may be at greater risk than their monoracial peers for both sleep problems and alcohol use. However, mechanisms underlying these uniquely-heightened risky health behaviors among multiracial adolescents remain a gap in the literature. This cross-sectional study examined a risk pathway involving discrimination experiences and negative mood underlying racial disparities in concurrent sleep problems and drinking frequency. Students at an urban, socioeconomically-disadvantaged high school (N = 414; grades 9-11, Mage = 16.00 [SD = 1.08]; 57% female; 17% multiracial, 41% Black, 22% White, 18% Asian, 2% Other; 12% Hispanic/Latinx) completed a survey. Path analysis demonstrated that associations of multiracial status with sleep problems (insomnia symptom severity and insufficient weekday sleep duration), but not drinking frequencies (past-year drinking or past-2-week binge-drinking frequencies), were explained by discrimination experiences and, in turn, negative mood. In ancillary analysis excluding White students, the serial indirect risk pathway was significant for both insomnia symptom severity and past-year drinking frequency outcomes. Discrimination experiences and negative mood may function as intermediate factors contributing to racial disparities in adolescent sleep problems, although longitudinal replication is needed.

Sleep-Related Cannabis Expectancy Questionnaire (SR-CEQ): Initial Development among College Students.

A growing body of literature demonstrates that cannabis is commonly used to aid sleep. Consistent with social cognitive theory, there is a vast literature documenting the role of outcome expectancies in the initiation, progression, and maintenance of cannabis use. Despite the readily endorsed belief that cannabis will help improve sleep, sleep-related expectancies have not been included in widely used cannabis expectancy measures. This study aimed to develop and provide preliminary psychometric evaluation of the Sleep-Related Cannabis Expectancy Questionnaire (SR-CEQ). Cross-sectional data were drawn from N= 166 college students (Mage = 18.83 [SD = 1.06; range: 18-24], 34% male, 71% White). Students completed an online survey including demographics and the 12-item SR-CEQ. Exploratory Factor Analysis identified two factors representing Negative Sleep-Related Cannabis Expectancies and Positive Sleep-Related Cannabis Expectancies. Confirmatory Factor Analysis demonstrated adequate fit of the two-factor measurement model to observed data (SRMR = 0.08). Students endorsed greater positive (versus negative) sleep-related cannabis expectancies on average, and male students reported significantly greater negative expectancies (but not positive expectancies) compared to female students. The SR-CEQ is the first cannabis expectancy assessment tool specific to sleep-related cannabis outcomes. Ongoing psychometric validation of the SR-CEQ is needed to assess convergent/predictive validity and replicate findings among relevant clinical samples.

Using water quality and isotope studies to inform research in chronic kidney disease of unknown aetiology endemic areas in Sri Lanka.

Chronic Kidney Disease of unknown aetiology (CKDu) is a major public health concern in dry climatic, agricultural regions of Sri Lanka. The chemistry of groundwater (the main source of drinking water) in the area has been studied extensively, in relation to the occurrence of CKDu. This paper investigates water quality studies published in CKDu affected areas of Sri Lanka and also presents a new data set of 27 hydrochemical and isotopic samples collected from groundwater wells in selected CKDu endemic areas in Sri Lanka. The study outcomes do not provide evidence of pollutants such as heavy metals in groundwater. However, the study identifies elevated concentrations of silica which requires further investigation. Two groups of groundwater have been identified based on the isotopic results suggesting different sources or origins. The available water quality data, including the data from this study, is not sufficient to answer questions on whether the chemistry of groundwater is related to the CKDu occurrence. However, this study identifies the importance of detailed investigation into degradation products of agrochemicals, the organic matter content and the influence of elevate silica concentration in groundwater. The study also provides research directions in the form of isotopic tracers and the frequency of sampling that is needed to capture potential pollutants in future groundwater quality studies in CKDu endemic areas in Sri Lanka.

Cannabis and alcohol use for sleep aid: A daily diary investigation.

OBJECTIVE: One in 5 college students use substances such as cannabis and/or alcohol to help sleep. Despite this high prevalence of sleep aid use, there remains a lack of research on the potential day-to-day sleep- and substance-related consequences. The current study examined associations of cannabis and alcohol sleep aid use with subsequent sleep and substance use consequences among college students. METHOD: Of a baseline sample of 217 college students endorsing past-month cannabis and/or alcohol use (1% cannabis only, 42% alcohol only, 58% both), 83 students endorsing past-month cannabis and/or alcohol use for sleep aid (Mage = 19.33 [SD = 1.11], 30% male, 72% White) completed online questionnaires for 14 consecutive days to report daily sleep, substance use, and negative substance consequences. RESULTS: Multilevel models demonstrated that nights of cannabis sleep aid use predicted longer same-night sleep duration, shorter same-night wake time after sleep onset, and greater next-day daytime fatigue within person, after controlling for daily cannabis frequency. Alcohol sleep aid use was not associated with sleep-related outcomes or negative drinking consequences after controlling for daily alcohol quantity; these null results may be due to a low frequency of alcohol sleep aid use (1% of observations) over 14 days of assessment. CONCLUSIONS: Results highlight daytime fatigue as a potential adverse short-term outcome of cannabis sleep aid use, despite its proximal sleep-related benefits. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Greywater irrigation as a source of organic micro-pollutants to shallow groundwater and nearby surface water.

Increased water demands due to population growth and increased urbanisation have driven adoption of various water reuse practices. The irrigation of greywater (water from all household uses, except toilets) has been proposed as one potential sustainable practice. Research has clearly identified environmental harm from the presence of micro-pollutants in soils, groundwater and surface water. Greywater contains a range of micro pollutants yet very little is known about their potential environmental fate when greywater is irrigated to soil. Therefore, this study assessed whether organic micro-pollutants in irrigated greywater were transferred to shallow groundwater and an adjacent surface waterway. A total of 22 organic micro-pollutants were detected in greywater. Six of these (acesulfame, caffeine, DEET, paracetamol, salicylic acid and triclosan) were selected as potential tracers of greywater contamination. Three of these chemicals (acesulfame, caffeine, DEET) were detected in the groundwater, while salicylic acid was also detected in adjacent surface water. Caffeine and DEET in surface water were directly attributable to greywater irrigation. Thus the practice of greywater irrigation can act as a source of organic micro-pollutants to shallow groundwater and nearby surface water. The full list of micro-pollutants that could be introduced via greywater and the risk they pose to aquatic ecosystems is not yet known.

Sleep-related functional impairment as a moderator of risky drinking and subsequent negative drinking consequences in college students.

OBJECTIVE: Poor sleep quality and insufficient total sleep time have been shown to modify the relationship between college drinking and negative drinking consequences. This study aimed to examine whether prospective associations between risky drinking and negative drinking consequences similarly differ by sleep-related functional impairment, which is novel to the literature. METHOD: Data were obtained from a 2-month prospective study of 157 college drinkers (mean age = 19 years [SD = 1.11], 30% male, 76% White). Online questionnaires were administered at both Time 1 (T1) and Time 2 (T2) to measure sleep-related functional impairment (assessed by Insomnia Diurnal Impact Scale; Ruiz, Guilera, & Gomez-Benito, 2011) and drinking behaviors and negative drinking consequences (assessed retrospectively over the past 2 months). RESULTS: Prospective negative binomial regression analyses demonstrated that associations of both maximum drinks and binge drinking frequency at T1 with negative drinking consequences at T2 differed by T1 sleep-related functional impairment after controlling for covariates (sex, negative mood, total sleep time, insomnia symptoms, morning preference, and negative drinking consequences at T1). Students reporting lower sleep-related functional impairment experienced high levels of negative drinking consequences only at high levels of risky drinking, whereas students reporting higher sleep-related functional impairment experienced consistently high levels of negative drinking consequences regardless of their risky drinking levels. CONCLUSION: Findings indicate that sleep-related functional impairment may exacerbate negative drinking consequences of risky drinking. Thus, sleep-related functional impairment helps to explain individual differences in the association between risky drinking and negative drinking consequences in college students.

Self-Medication for Sleep in College Students: Concurrent and Prospective Associations With Sleep and Alcohol Behavior.

OBJECTIVE/BACKGROUND: College students are at an increased risk for poor sleep and associated sleep problems. Emerging evidence suggests that a substantial subset of college students self-medicate with alcohol, marijuana, or over-the-counter medications to help sleep. The current study identified demographic, psychosocial, and sleep- and alcohol-related correlates of self-medication for sleep, and assessed its concurrent and prospective associations with insomnia symptoms, alcohol drinking, and negative drinking consequences. PARTICIPANTS: Undergraduate students (N = 171; mean age = 19 years [SD = 1.35], 32% male, 74% White) enrolled in a four-year university in the northeastern United States. METHODS: Data were drawn from a short-term two-wave longitudinal study. Participants completed two online surveys, separated by an average interval of 68 days (SD = 10.22). RESULTS: At Time 1, 25% of students reported using at least one substance (alcohol, marijuana, or over-the-counter medications) for sleep aid in the past two weeks. Male and older students were more likely to report using substances for sleep. Sleep aid use at Time 1 was concurrently associated with greater levels of alcohol frequency, negative drinking consequences, and insomnia symptoms. Further, sleep aid use at Time 1 was associated with an increase in negative drinking consequences from Time 1 to Time 2, but not with changes in alcohol frequency or insomnia symptoms. CONCLUSIONS: These findings indicate that substances are widely used among college students for sleep aid. Sleep aid use is associated with greater concurrent drinking and insomnia symptoms, and increases in negative drinking consequences over a short time period.

Discovery of 2,6-disubstituted pyrazine derivatives as inhibitors of CK2 and PIM kinases.

The design and synthesis of a novel series of 2,6-disubstituted pyrazine derivatives as CK2 kinase inhibitors is described. Structure-guided optimization of a 5-substituted-3-thiophene carboxylic acid screening hit (3a) led to the development of a lead compound (12b), which shows inhibition in both enzymatic and cellular assays. Subsequent design and hybridization efforts also led to the unexpected identification of analogs with potent PIM kinase activity (14f).

Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database.

Enteric methane (CH4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH4 emission conversion factors for specific regions are required to improve CH4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

Does the endometrial gene expression of fertile women vary within and between cycles?

STUDY QUESTION: Does gene expression of putative endometrial implantation markers vary in expression between menstrual cycles? SUMMARY ANSWER: In fertile women the expression of certain genes exhibits a pattern of stable regulation.which is not affected even when sampled twice in one cycle. WHAT IS KNOWN ALREADY: Successful implantation occurs in a minority of IVF embryo transfers. In contrast to knowledge regarding the ovulatory process, there is a sparse understanding of endometrial genes critical to implantation. This lack of knowledge hinders progress in this field. STUDY DESIGN, SIZE, DURATION: Endometrial pipelle samples were collected based on blood endocrinological markers at 2 and 7 days post initial LH surge. Five samples were collected over four cycles where the interval between collections ranged from sequential months to three years. PARTICIPANTS/MATERIALS, SETTING, METHODS: Six fertile women attending an IVF clinic for male factor infertility, had samples collected. Global gene expression profiles were obtained from laser-microdissected, endometrial glands and stroma. Nineteen potential proliferation, cytokine and adhesion markers based on previous validated reports were studied. MAIN RESULTS AND THE ROLE OF CHANCE: There was a significant modification between LH+2 and LH+7 of expression for 23 genes-11 in 8 in glands and stroma, 4 in stroma only and 3 in glands only suggesting stable, controlled regulation. Nevertheless, genes exhibited individual characteristics, e.g MKI67 exhibited lower expression at LH+7 than LH+2 and CCL4 higher, whereas TRO expressed limited difference in both cell types. Stability between cycles was demonstrated for gene expression at both LH+2-more than 60% of genes had <25% variation and at LH+7-60% had <30% variation. Further, effects of prior collection of an LH+2 sample on gene expression at LH+7 were not detected. The range of mRNA expression suggested that a clinical/diagnostic sample at LH+2 and LH+7 is likely to be a better index of endometrial function than a single sample. The possibility of redundancy suggests a panel would be more informative than a single marker. LARGE SCALE DATA: Raw and normalized microarray data have been deposited with the EMBL's European Genome-Phenome Archive for collaborative analysis, reference ega-box-815 (Lappalainen I, Almeida-King J, Kumanduri V, Senf A, Spalding JD, Ur-Rehman S, Saunders G, Kandasamy J, Caccamo M, Leinonen R et al. The European Genome-phenome Archive of human data consented for biomedical research. Nat Genet 2015;47:692-695.) [https://www.ebi.ac.uk/ega/home]. LIMITATIONS, REASONS FOR CAUTION: This type of research has difficulties of recruitment of fertile women for multiple blood testing and repeat endometrial biopsies. Therefore, these data had decreased statistical power due to the overall participant numbers. However, the inclusion of four cycles for each participant permitted the aim of obtaining information on intercycle and intracycle variability to be achieved. WIDER IMPLICATIONS OF THE FINDINGS: Our results support the feasibility of a clinical means of identification of a functional receptive endometrium. The robustness of data from individual women suggests that samples from one cycle can generally be applied to subsequent cycles. STUDY FUNDING/COMPETING INTEREST(S): Funding was granted from the Tertiary Education Commission of New Zealand, Contract I.D.:UOOX06007. There are no competing interests.

Cerebrospinal Fluid Clearance in Alzheimer Disease Measured with Dynamic PET.

Evidence supporting the hypothesis that reduced cerebrospinal fluid (CSF) clearance is involved in the pathophysiology of Alzheimer disease (AD) comes primarily from rodent models. However, unlike rodents, in which predominant extracranial CSF egress is via olfactory nerves traversing the cribriform plate, human CSF clearance pathways are not well characterized. Dynamic PET with 18F-THK5117, a tracer for tau pathology, was used to estimate the ventricular CSF time-activity as a biomarker for CSF clearance. We tested 3 hypotheses: extracranial CSF is detected at the superior turbinates; CSF clearance is reduced in AD; and CSF clearance is inversely associated with amyloid deposition. Methods: Fifteen subjects, 8 with AD and 7 normal control volunteers, were examined with 18F-THK5117. Ten subjects additionally underwent 11C-Pittsburgh compound B (11C-PiB) PET scanning, and 8 were 11C-PiB-positive. Ventricular time-activity curves of 18F-THK5117 were used to identify highly correlated time-activity curves from extracranial voxels. Results: For all subjects, the greatest density of CSF-positive extracranial voxels was in the nasal turbinates. Tracer concentration analyses validated the superior nasal turbinate CSF signal intensity. AD patients showed ventricular tracer clearance reduced by 23% and 66% fewer superior turbinate CSF egress sites. Ventricular CSF clearance was inversely associated with amyloid deposition. Conclusion: The human nasal turbinate is part of the CSF clearance system. Lateral ventricle and superior nasal turbinate CSF clearance abnormalities are found in AD. Ventricular CSF clearance reductions are associated with increased brain amyloid depositions. These data suggest that PET-measured CSF clearance is a biomarker of potential interest in AD and other neurodegenerative diseases.

A web-based knowledge management system integrating Western and Traditional Chinese Medicine for relational medical diagnosis.

This article presents the design of a web-based knowledge management system as a training and research tool for the exploration of key relationships between Western and Traditional Chinese Medicine, in order to facilitate relational medical diagnosis integrating these mainstream healing modalities. The main goal of this system is to facilitate decision-making processes, while developing skills and creating new medical knowledge. Traditional Chinese Medicine can be considered as an ancient relational knowledge-based approach, focusing on balancing interrelated human functions to reach a healthy state. Western Medicine focuses on specialties and body systems and has achieved advanced methods to evaluate the impact of a health disorder on the body functions. Identifying key relationships between Traditional Chinese and Western Medicine opens new approaches for health care practices and can increase the understanding of human medical conditions. Our knowledge management system was designed from initial datasets of symptoms, known diagnosis and treatments, collected from both medicines. The datasets were subjected to process-oriented analysis, hierarchical knowledge representation and relational database interconnection. Web technology was implemented to develop a user-friendly interface, for easy navigation, training and research. Our system was prototyped with a case study on chronic prostatitis. This trial presented the system's capability for users to learn the correlation approach, connecting knowledge in Western and Traditional Chinese Medicine by querying the database, mapping validated medical information, accessing complementary information from official sites, and creating new knowledge as part of the learning process. By addressing the challenging tasks of data acquisition and modeling, organization, storage and transfer, the proposed web-based knowledge management system is presented as a tool for users in medical training and research to explore, learn and update relational information for the practice of integrated medical diagnosis. This proposal in education has the potential to enable further creation of medical knowledge from both Traditional Chinese and Western Medicine for improved care providing. The presented system positively improves the information visualization, learning process and knowledge sharing, for training and development of new skills for diagnosis and treatment, and a better understanding of medical diseases.

Identification of (R)-N-((4-Methoxy-6-methyl-2-oxo-1,2-dihydropyridin-3-yl)methyl)-2-methyl-1-(1-(1-(2,2,2-trifluoroethyl)piperidin-4-yl)ethyl)-1H-indole-3-carboxamide (CPI-1205), a Potent and Selective Inhibitor of Histone Methyltransferase EZH2, Suitable for Phase I Clinical Trials for B-Cell Lymphomas.

Polycomb repressive complex 2 (PRC2) has been shown to play a major role in transcriptional silencing in part by installing methylation marks on lysine 27 of histone 3. Dysregulation of PRC2 function correlates with certain malignancies and poor prognosis. EZH2 is the catalytic engine of the PRC2 complex and thus represents a key candidate oncology target for pharmacological intervention. Here we report the optimization of our indole-based EZH2 inhibitor series that led to the identification of CPI-1205, a highly potent (biochemical IC50 = 0.002 µM, cellular EC50 = 0.032 µM) and selective inhibitor of EZH2. This compound demonstrates robust antitumor effects in a Karpas-422 xenograft model when dosed at 160 mg/kg BID and is currently in Phase I clinical trials. Additionally, we disclose the co-crystal structure of our inhibitor series bound to the human PRC2 complex.