Chemical Stability of Hydrocortisone in Topical Preparation in Proprietary VersaPro™ Cream Base

The United States Pharmacopeia-National Formulary (USP-NF) suggests beyond use dating ((BUD) for compounded topical preparations containing active pharmaceutical ingredients (API) [1]. The beyond the use dates of the preparations are based on the conservative and empirical guidelines of USP 795. Hydrocortisone (HC) content compounded in the VersaPro™ base cream was quantified using a HPLC method at time zero and after 30 and 60 days of storage at both room temperature and 4°C. The analysis suggests that the compounded preparations retain > 95% of the stated initial potency of HC regardless of storage conditions. Thus HC creams prepared in VersaPro™ cream base can be safely assigned a beyond the use date of two months when stored at room temperature.   Type: Original Researc

Emotion Processing Deficit in Euthymic Bipolar Disorder: A Potential Endophenotype

Background: Emotion processing deficits have been described in patients with bipolar disorder (BD) and are considered one of the core cognitive abnormalities in BD with endophenotype potential. However, the literature on specific impairments in emotion processing cognitive strategies (directive/cortical/higher versus intuitive/limbic/lower) in euthymic adult BD patients and healthy first-degree relatives/high-risk (HR) subjects in comparison with healthy controls (HCs) is sparse. Methods: We examined facial emotion recognition deficits (FERD) in BD (N = 30), HR (N = 21), and HC (N = 30) matched for age (years), years of education, and sex using computer-administered face emotions–Matching And Labeling Task (eMALT). Results: The three groups were significantly different based on labeling accuracy scores for fear and anger (FA) (P \u3c 0.001) and sad and disgust (SD) (P \u3c 0.001). On post-hoc analysis, HR subjects exhibited a significant deficit in the labeling accuracy of FA facial emotions (P \u3c 0.001) compared to HC. The BD group was found to have significant differences in all FA (P = 0.004) and SD (P = 0.003) emotion matching as well as FA (P = 0.001) and SD (P \u3c 0.001) emotion labeling accuracy scores. Conclusions: BD in remission exhibits FERD in general, whereas specific labeling deficits of fear and anger emotions, indicating impaired directive higher order aspect of emotion processing, were demonstrated in HR subjects. This appears to be a potential endophenotype. These deficits could underlie the pathogenesis in BD, with possible frontolimbic circuitry impairment. They may have potential implications in functional recovery and prognosis of BD

Translational bioinformatics in mental health: open access data sources and computational biomarker discovery

Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.National Institutes of Health [UL1TR001117, R01LM012095, R01LM012806]Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder:Results from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LME INT), (2) LME that models both site-specific random intercepts and age-related random slopes (LME INT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ 2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ 2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ 2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects

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Not AvailableQuantification of plants biophysical variable, economic yield and oil content of oilseed Brassica is important to know the potential impact of in-season weather variability. Agroclimatic models may be used to predict the plants' response and adaptability in the soil-plants-atmospheric systems and thereby screening various mitigation options to combat impinging climate change. In this study, some important biophysical indicators viz., leaf area index (LAI), dry biomass, economic seed yield and oil content of Indian mustard have been predicted using thermal unit based regression models following field experimentations carried out in two consecutive winter seasons of 2005-06 and 2006-07 on a sandy clay loam soil of IARI research farm, New Delhi. Linear and non-linear regression models were developed in which thermal indices viz., Growing Degree Days (GDD), Heliothermal Unit (HTU) and Photothermal Unit (PTU) have been used as independent variables. These thermal units were cumulated up to maximum leaf area index and dry biomass and 50% physiological maturity. Models developed from pooled data showed statistically significant and positive correlations existed between biophysical variables with thermal units.GDDand PTU based regression models may be recommended for predicting leaf area index (LAI = 0.008 ×GDD- 3.54; R = 0.78 * * and LAI = 0.0007 × PTU - 3.31; R = 0.75 * *) and dry biomass production (Dry biomass = 1.89 × GDD - 1060.3; R = 0.87 * * and Dry biomass = 0.15 ×PTU- 794.02;R = 0.85 * *).HTUbased regression models were found to be better predictor only when accumulated values of the index exceeded 1000 Cd hours (LAI = 0.0005 × HTU + 0.69; R = 0.31 and Dry biomass = 0.11 × HTU + 202.81; R = 0.51). The generated agroclimatic models may be complementary to decision support systems for predicting biophysical parameters under semi-arid subtropical environment using daily information on critical weather parameters.Not Availabl

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Not AvailableA statistical assessment of curve fitting to soil water retention curve has been carried out for two different types of soils viz., Kharagpur sandy loam soil (four layers) and Black clay soil of Akola. The closed form equation describing soil water retention function of van Genuchten [VG (m, n) and VG (n)] and Brooks- Corey (BC) was fitted using RETC software and detailed statistical analysis was carried out to compare their performance. Results revealed that all the three models were found to perform reasonably well. The statistical analysis performed to discriminate the models such as R , AIC, t-value and RSS had showed a little difference among the models used for comparison. However, considering the relative ease at which the computation of hydraulic properties can be performed and the practical situation that can be accommodated, VG(n) is the best model among all the three models. This represents a simple closed form equation that can be derived to express the hydraulic conductivity function as compared toVG(m, n).Not Availabl

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Not AvailableTrenching is the most efficient practice for restoration of degraded non-arable lands. Government and various agencies put tremendous efforts and spend lot of money in the rehabilitation of degraded lands by carrying out trenching. Design and layout of trenches under different rainfall conditions involve lot of computation based on watershed information to derive maximum benefit of the technology. However, in the absence of clear guidelines for computation of trench specifications (spacing, cross section and density), desirable results are not achieved from this intervention. Under field conditions wide fluctuations in trench specifications are observed in different regions of the country, due to highly diverse land forms and climatic conditions. A Decision Support System is designed to bridge the knowledge gap between experts and actual field level implementers by helping the user to make decisions for the design and layout of Continuous Contour Trenches (CCT) and Staggered Contour Trenches (SCT) under varied land forms and climatic conditions. The DSS will be of immense importance and of practical use for persons working in State government agencies, NGOs and Forest Departments implementing watershed development programmes.Not Availabl

Anubhoothi: a psychopathology of unusual sexual experience

The case history and management of a 26 years old adult is reported who presented with an unusual symptom of sexual experience, in the background of symptoms of depression and anxiety; had been given multiple diagnoses at multiple points of time and treated with multiple medications. On establishment of rapport, he revealed details of his unusual experiences, which had been unexplored. When he was about 11 years and ten months, he sat next to a lady; he could perceive a particular experience for the first time in his life. And next time with another lady too he perceived a particular type of smell (“madaka gandha” meaning an intoxicating smell) along with the other feelings. He began to have these feelings whenever he was in the vicinity of a female except his mother and sister. The smell reminded him of roses vaguely and was at least ten to 20 times more pleasurable than an orgasm that he got with masturbation. These feelings were more pleasurable than he could ever imagine and happened always with the presence of a female in the vicinity. This was never associated with periods of unresponsiveness or any other history suggestive of seizures. He titled the experience as “anubhoothi”. These experiences occurred on a regular basis for a period of ten months following which there was abrupt cessation of the same, without any intervention. Later he developed all symptoms. A coordinated management plan spearheaded by the multi-disciplinary treatment team could bring down his symptoms as well as make him functional. This case indicates that it is essential to explore abnormalities of experiences to understand the psychopathology and plan management