Trajectory and magnitude of response in adults with anxiety disorders: a Bayesian hierarchical modeling meta-analysis of selective serotonin reuptake inhibitors, serotonin norepinephrine reuptake inhibitors, and benzodiazepines

BACKGROUND

How the trajectory of response to medication (and placebo response) varies among selective serotonin reuptake inhibitors (SSRIs), serotonin norepinephrine reuptake inhibitors (SNRIs), benzodiazepines and across anxiety disorders is unknown.

METHODS

We performed a meta-analysis using weekly symptom severity data from randomized, parallel-group, placebo-controlled trials of SSRIs, SNRIs, and benzodiazepines in adults with anxiety disorders. Response was modeled for the standardized change in anxiety using Bayesian hierarchical models.

RESULTS

Across 122 trials (N=15,760), SSRIs, SNRIs, and benzodiazepines produced significant improvement in anxiety compared to placebo. Benzodiazepines produced faster improvement by the first week of treatment (p < 0.001). By week 8, the response for benzodiazepines and SSRIs (p = 0.103) and SNRIs (p = 0.911) did not differ nor did SSRIs and SNRIs differ (p = 0.057), although for patients with generalized anxiety disorder (GAD), the benzodiazepines produced greater improvement than SNRIs at week 8 (difference - 12.42, CrI: -25.05 to -0.78, p = 0.037). Medication response was similar across anxiety disorders except for benzodiazepines, which produced greater improvement over the first 4 weeks compared to SSRIs and SNRIs in panic disorder. For SSRIs and SNRIs, women improved more than men, and for benzodiazepines, older patients improved more compared to younger patients. Finally, placebo response plateaued by week 4 of treatment, and, at week 8, social anxiety disorder trials had lower placebo response compared to other anxiety disorders.

CONCLUSIONS

Benzodiazepines show early improvement compared to SSRIs and SNRIs. However, by week 8, all treatments yield similar results. Patient characteristics influence the improvement trajectory and magnitude, suggesting potential for personalized medication selection.

Improved graph neural network-based green anaconda optimization for segmenting and classifying the lung cancer

Normal lung cells incur genetic damage over time, which causes unchecked cell growth and ultimately leads to lung cancer. Nearly 85% of lung cancer cases are caused by smoking, but there exists factual evidence that beta-carotene supplements and arsenic in water may raise the risk of developing the illness. Asbestos, polycyclic aromatic hydrocarbons, arsenic, radon gas, nickel, chromium and hereditary factors represent various lung cancer-causing agents. Therefore, deep learning approaches are employed to quicken the crucial procedure of diagnosing lung cancer. The effectiveness of these methods has increased when used to examine cancer histopathology slides. Initially, the data is gathered from the standard benchmark dataset. Further, the pre-processing of the collected images is accomplished using the Gabor filter method. The segmentation of these pre-processed images is done through the modified expectation maximization (MEM) algorithm method. Next, using the histogram of oriented gradient (HOG) scheme, the features are extracted from these segmented images. Finally, the classification of lung cancer is performed by the improved graph neural network (IGNN), where the parameter optimization of graph neural network (GNN) is done by the green anaconda optimization (GAO) algorithm in order to derive the accuracy maximization as the major objective function. This IGNN classifies lung cancer into normal, adeno carcinoma and squamous cell carcinoma as the final output. On comparison with existing methods with respect to distinct performance measures, the simulation findings reveal the betterment of the introduced method.

What Is the Added Benefit of Combining Cognitive Behavioral Therapy and Selective Serotonin Reuptake Inhibitors in Youth with Obsessive Compulsive Disorder? A Bayesian Hierarchical Modeling Meta-Analysis

Background: Treatment of obsessive-compulsive disorder (OCD) in children and adolescents frequently involves cognitive behavioral therapy (CBT), selective serotonin reuptake inhibitors (SSRIs), or their combination. However, how adding CBT to SSRIs affects the trajectory and magnitude of improvement has not been evaluated meta-analytically. Methods: We performed a meta-analysis using weekly data from prospective randomized parallel group trials of CBT and SSRIs in pediatric patients with OCD. Response was modeled for the change in the Child Yale-Brown Obsessive-Compulsive Scale (CY-BOCS) using a Bayesian hierarchical model over 12 weeks. Results: Fourteen studies included pharmacotherapy arms, 4 studies included combined pharmacotherapy and psychotherapy, and 10 studies included a placebo or control arm. The studies included 1146 patients (mean age 12.7 ± 1.3 years, mean 42.1% female). In the logarithmic model of response, statistically significant differences in treatment effects for CBT+SSRI and SSRI monotherapy were observed compared with placebo (SSRI β = -3.59, credible interval [95% CrI]: -4.13 to -3.02, p < 0.001; SSRI+CBT β = -4.07, 95% CrI: -5.05 to -3.04, p < 0.001). Adding CBT to an SSRI produced numerically (but not statistically significantly) greater improvement over 12 weeks. Greater improvement was observed in studies with more boys (p < 0.001), younger patients (p < 0.001), and in studies with greater baseline symptom severity (p < 0.001). Conclusions: In children and adolescents with OCD, compared with placebo, both SSRIs and SSRI+CBT produced early and sustained improvement over 12 weeks, although the improvement was also related to sample characteristics. Longer term studies are needed to determine when the additive benefit of CBT emerges relative to SSRI monotherapy.

An intelligent fuzzy-particle swarm optimization supervisory-based control of robot manipulator for industrial welding applications

The propensity of manufacturers to produce goods at affordable cost, with more accuracy, and at a faster rate force them to search for novel solutions, such as deploying robots in place of people in a sector that can accommodate their needs. Welding is one of the most crucial processes in the automotive industry. This process is time-consuming, subject to error, and demands skilled professionals. The robotic application can improve this area of production and quality. Other industries, such as painting and material handling, can also profit from the use of robots. This work describes the fuzzy DC linear servo controller, which functions as a robotic arm actuator. Robots have been widely employed in most productive sectors in recent years, including assembly plates, welding, tasks at higher temperatures, etc. Controlling a robot accurately is a difficult undertaking as a robot is very nonlinear with many joints that are often organized and unstructured. To carry out the effective task, an effective PID control based on fuzzy logic has been employed together with the method of Particle Swarm Optimization (PSO) approach for the estimate of the parameter. This offline technique determines the lowest number of optimal robotic arm control parameters. To verify the controller design with computer simulation, a comparative assessment of controllers is given by means of a fuzzy surveillance controller with PSO which improves the parameter gain to provide a rapid climb, a smaller overflow, no steady condition error signal, and effective torque control of the robot arm.

The impact of age on antidepressant response: A mega-analysis of individuals with major depressive disorder

INTRODUCTION

Understanding how age affects antidepressant response in patients with major depressive disorder has been complicated by small and heterogeneous studies. Yet, understanding how age-across the lifespan-contributes to variation in response could inform treatment selection across the lifespan. This study sought to identify how age impacts antidepressant response using participant-level data from large, NIH-sponsored trials in individuals with MDD aged 12-74 years.

MATERIALS AND METHODS

Participant-level data were abstracted from three NIH-sponsored trials of pharmacotherapy (Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) Study, Treatment of Adolescent Depression Study (TADS), and the Combining Medications to Enhance Depression Outcomes Study (COMED)) in patients with MDD. Bayesian Hierarchical Models (BHMs) of individual treatment trajectories were developed using Hamiltonian Monte Carlo No U-Turn Sampling. The individual trajectory of improvement in depressive symptoms (Clinical Global Impression-Severity [CGI-S] and CGI-S equivalent from COMED) was modeled across studies and across individuals with logarithmic trend "random effects" coefficients BHMs. Age and sex (and their interaction) were examined categorically across patients.

RESULTS

Study participants (N = 907) were 29.7 ± 17 years of age, 66.3% women, and had a mean baseline CGI-S score of 4.6 ± 0.9. Patients ≤21 years and those >55 years had slower and less response to pharmacotherapy compared to those aged 21-35. Additionally, women improved more than men, and this effect did not differ across ages.

DISCUSSION

The patient's age should be considered in predicting antidepressant response, particularly in older and younger individuals who may benefit from other interventions to enhance treatment response.

Socioeconomic Predictors of Treatment Outcomes Among Adults With Major Depressive Disorder

OBJECTIVE

In this study, the authors sought to examine the impact of socioeconomic variables on outcomes of pharmacotherapy treatments for major depressive disorder in analyses that controlled for treatment access and level of care.

METHODS

The authors used data from the Combining Medications to Enhance Depression Outcomes study, a prospective clinical trial conducted from March 2008 to April 2014 with 665 adults who had major depressive disorder and were randomly assigned to three pharmacotherapeutic treatments, to develop Bayesian hierarchical models of treatment trajectories for change in Quick Inventory of Depressive Symptomatology-Self-Report ratings. Posterior tail probabilities were used to evaluate the effects of education, income, race-ethnicity, and employment on treatment outcomes.

RESULTS

After sex, age, and treatment type were controlled for in the analyses, not having a college education (<16 years of schooling), being unemployed, or being non-White were each associated with slower and less improvement. At the end of treatment (week 12), not having a college degree reduced treatment responses by 9.6% (p=0.045), being unemployed by 6.6% (p=0.007), and being non-White by 11.3% (p<0.001). Treatment response was significantly related to income; having an income at the 25th percentile of the income distribution decreased improvement by 4.8% compared with having an income at the 75th percentile (p=0.018).

CONCLUSIONS

Within a short-term, randomized controlled trial, socioeconomic factors had a critical role in the acute response of patients to pharmacotherapy for major depression.

COVID-19 vaccine sentiment analysis using public opinions on Twitter

Twitter, as is well known, is one of the most active social media platforms, with millions of tweets posted every day, in which different people express their opinions on topics such as travel, economic concerns, political decisions, and so on. As a result, it is a useful source of knowledge. We offer Sentiment Analysis using Twitter Data for the research. Initially, our technology retrieves currently accessible tweets and hashtags about various types of covid vaccinations posted on Twitter through using Twitter's API. Following that, the imported Tweets are automatically configured to generate a collection of untrained rules and random variables. To create our model, we're utilizing, Tweepy, which is a wrapper for Twitter's API. Following that, as part of the sentiment analysis of new Messages, the software produces donut graphs.

Combining selective serotonin reuptake inhibitors and cognitive behavioral therapy in youth with depression and anxiety

BACKGROUND

Treatment studies of children and adolescents with internalizing disorders suggest that the combination of a selective serotonin reuptake inhibitor (SSRI) and cognitive behavioral therapy (CBT) consistently produces greater improvement than either treatment alone. We sought to determine how response to combined treatment varies across disorders (anxiety versus depression), and by specific patient characteristics.

METHODS

Three large National Institutes of Health-funded trials of children and adolescents with major depression (n = 2) and anxiety disorders (n = 1) were evaluated, each comparing CBT + SSRI to SSRI only, Bayesian Hierarchical Models (BHMs) were used, for endpoint response, time course of response and predictors of response in participants who received SSRI or SSRI+CBT.

RESULTS

SSRI+CBT significantly decreased symptoms by week 4 (p<0.001) across disorders. This improvement continued at week 8 and 12 (p<0.001); however, the additive benefit of CBT over SSRI monotherapy was not statistically significant until week 12 (p<0.001). The fastest response to SSRI+CBT was for patients who were younger, with milder baseline anxiety/depression symptoms and depressive disorders. The slowest response for SSRI+CBT was for boys, adolescents, minoritized children, those with severe symptoms and externalizing disorders.

LIMITATIONS

Limitations included inconsistent moderators, variation in the number of observations over time and a lack of genetic or pharmacokinetic variables related to SSRI exposure across studies.

CONCLUSIONS

The superiority of SSRI+CBT for youth with depression and anxiety is further supported. For purposes of rapid and greater relief, combination treatment is the superior approach across anxiety and depression and is robust to a range of participant characteristics. However, the added value of CBT (with an SSRI) occurs late in treatment. These findings represent a step towards understanding heterogeneity of treatment response and raise the possibility that interventions could be better tailored or adapted based on patient characteristics.

Abutment conditions in faulty prosthesis among Indians

A faulty prosthesis can cause damage more than relief. Poor people who cannot afford specialty treatment prefer to go to unregistered dental practitioners who are less expensive. Therefore, it is of interest to record the presence and type of old faulty prosthesis and its effect on surrounding structures. In this study 983 case sheets were reviewed from the record management system at the Saveetha Dental College, India using keyword search. Results show that 33% of faulty prosthesis leads to periodontally compromised abutments, 26% to decay of abutment tooth, 20% to gingival inflammation, 13% to denture stomatitis, 6.6% to non-vital abutment tooth. Faulty prosthesis damages abutment tooth and the surrounding structure of oral mucosa. Thus, damage to the periodontium in fixed prosthesis is common and prevalent. Hence, faulty dental prosthesis construction should be discouraged through awareness programme.

A Comparative Study to Assess Compassion Fatigue, Burnout and Compassion Satisfaction among Casualty Nurses with Intensive Care Unit Nurses at Selected Hospitals in Vadodara

Aim: This study is focussed on comparison and assessment of compassion fatigue, burnout and compassion satisfaction among casualty nurses with intensive care unit (ICU) nurses. Study Design: Quantitative research approach and Descriptive - Comparative research design. Materials and Methods: Study targeted casualty nurses and ICU nurses working at selected hospitals in Vadodara. A total of 80 casualty nurses and ICU nurses were asked to participate in this study. Convenient sampling technique was used. First tool consists of demographic variables. Second tool consists of Compassion Fatigue/Satisfaction Self-Test (CFS), assess the existing level of compassion fatigue, burnout and compassion satisfaction. Results: Assessment of compassion fatigue among casualty nurses revealed that 18 [60%] nurses exhibited extremely high-risk level, Analysis of burnout among casualty nurses showed that 15 [50%] half of the nurses presented moderate risk level and among ICU nurses showed that 45 [90%] majority of the nurses presented high risk levels of burnout. Examining the final component of the CFS tool among casualty nurses, more than half of the respondents 16 [53.3%] were characterised as high potential level of compassion satisfaction and among ICU nurses, half of the respondents 25 [50%] were characterised as having a modest potential level of compassion satisfaction. Independent t-test shows that there was no significant difference in the level of compassion fatigue and compassion satisfaction between casualty nurses and ICU nurses. But there was a significant difference in the level of burnout between casualty nurses and ICU nurses, since the t value [18.256] was found to be greater than the table value [1.990] at .05 significant. Conclusion: Study reveals an association was found to exist between the level of compassion fatigue and demographic variables. But there was no association found in the level of burnout and compassion satisfaction among subjects with their selected demographic variables.

Cyber Bullying Awareness: - Major Cause of Mental Health Problems among Adolescent of Selected School, Chhotaudepur

Introduction: Cyberbullying is a pervasive public health issue, affecting 10% to 50% of adolescents and resulting in significant negative health outcomes. Cyberbullying is when someone, typically a teenager, bullies or harasses others on the internet and other digital spaces, particularly on social media sites. Harmful bullying behavior can include posting rumors, threats, sexual remarks, a victims' personal information, or pejorative labels. Aim: The Present research study aimed to assess the knowledge on cyber bullying & it’s effect on mental health. Materials and Methods: The data for main study was collected from 150 adolescents. Adolescents were selected using convenient sampling technique. Self-structured questionnaire was used to assess the level of knowledge about cyberbullying. Descriptive and inferential statistics such as mean, standard deviation, chi- square, t-test were applied to analyzed the data. Results: The pre-test Post-test score of Level of knowledge was compared using paired t-test (Independent t-test) revealed that (t=-29.679, df=149, p=0.05) the programme was effective to improve the level of knowledge on cyberbullying among adolescent. Chi square was use to assess the association of pre - test knowledge scores with selected demographical variable found non-significant for all the variables (p=0.05). Conclusion: Data collection done of the data collected from 150 adolescent’s students studying in 11th &12th standard adolescent’s students descriptive and inferential statistics were used for analysis of the data and interpreted by the forms of tables and graphs.

Assess the Level of Stress among Parents of Children with Autism at Selected Autism Schools of Vadodara with a View to Give Need Based Education

Introduction: Children with a Autism spectrum disorders have impairment in the area of communication and social interaction and often display repetitive and non often display. Their parents having stress a to manage their children to education and future purpose. This study has assessed the stress level in parents and manage their stress with coping mechanism. Aims and Objective: 1) To assess the level of stress among parents of children with autism.2) To find association between level of stress and selected demographic variables. Methods: The data for main study collection was 30 Parents. Description of the tools refers to the explanation of the content of the tool. The researcher lists the number of items and the scoring for each item in the tool. The tool used for the present study is Parenting stress index - Scale. Descriptive and inferential statistics were applied to analyses the data by using SPSS-20 software. We use purposive sampling technique. Results: The majority of the parents having a moderate stress (83.3%), and severe stress (10%) and mild stress (6.66%) and nonstress level (0.0%). the stress level analysis showed that stress in parents (R=0.321, p=0.00) at significance of 0.05 level present. Conclusion: The present study concluded that there is a stress level of parents among children having a moderate stress and there is a no any association between the level of stress and selected demographic variable.

The Effect of Parent Pressure and Peer Factors Affecting on the Performance of Nursing Students

Background: People cannot live alone in society. Basically people need social contacts that suit them. Sometimes they need parent’s help, love, care and guidance and some time they need friend’s intimacy, affection and love. The persons first contact is with parents and then with friends. Parent attachment is stronger during infancy and childhood whereas friend’s attachment is strong during adolescence. Attachment level varies with the ages and stages of life. This attachment influences their feelings, thinking, decisions and living styles. The persons first contact is with parents and then with friends. Aims: To assess the parental pressure and peer factors affecting the academic performance of nursing students studying in selected nursing college of Vadodara. Methods: A cross sectional research design was carried out for this study. The study was carried out on 300 students. Students were selected using stratified sampling technique. A five-point rating scale was used to assess the academic performance of students. Descriptive and inferential statistics such as mean, standard deviation, chi-square test were applied to analyze the data. Results: The effect of peer and parental pressure on the performance showed that more than half participants 61% (n=183) were having average intensity. And about 39% (n=117) of them were having high intensity. Conclusion: the present study concluded that majority of the students are having average intensity in their academics and some students are having high intensity in their academics.

ECAM: A low-cost vaping device for generating and collecting electronic cigarette condensate for in vitro studies

The use of electronic cigarettes (ECs) has become widespread despite many unknowns around their long-term health impact. ECs work by vapourising a liquid, known as an e-liquid, typically consisting of propylene glycol, glycerol, flavourings and nicotine. The chemical constituents and resultant impact on cells and tissue are dependent on several factors, including the flavourings used, the vaping topography/use pattern, and the device used. ECAM (Electronic Cigarette Aerosol Machine) is an open source, portable device for creating EC aerosol - for condensate collection and in vitro studies - using a controlled methodology. ECAM was developed as a low cost, automated, and customisable alternative to commercial devices. ECAM consists of a micro diaphragm gas pump to draw air/EC aerosol through the system. The device is automated using an Arduino and solenoid pinch valves are used to alternate between air and EC vapour. Condensate is collected in a vial within a cold-water bath. Each ECAM unit uses a temperature/humidity sensor to measure ambient air conditions and a differential pressure sensor to determine the pressure within the system. ECAM is programmed to adhere to International Standards Organisation 20768:2018. The design files, source code, and build instructions for this device can be found at https://dx.doi.org/10.17605/OSF.IO/3NGU4.

Modelling uptake and transport of therapeutic agents through the lymphatic system

The ability of the lymphatic network to absorb large molecules and bypass the first-pass liver metabolism makes it appealing as a delivery system for therapeutic substances. In most cases, the drug is injected into the subcutaneous tissue and must negotiate the tissue space, before being drained via the lymphatics. Tracking the transport of drug molecules through this route is challenging, and computational models of lymphatic drainage can play an important role in assessing the efficacy of a proposed delivery strategy. The three-dimensional computational model we present here of the peripheral lymphatic network and surrounding interstitium is informed by anatomical data, and quantifies the degree to which uptake and transit times are affected by drug particle size, physiological flow rates, and specifics of drug injection.

Sandracottus vijayakumari (Coleoptera: Dytiscidae), a new aquatic beetle species from landslide hit area of Nelliyampathy Forest Range, Western Ghats, Kerala, India

The present study deals with the description of a new species Sandracottus vijayakumari from Nelliyampathy forest range, southern Western Ghats, Kerala, India with a comparative key of closely related species S. dejeani Aube, 1838.  Only one species is known from the genus Sandracottus Sharp, 1882, from southern Western Ghats, Kerala.  The Nelliyampathy forest areas are hilly and the altitude of the hills range 40–1,530 m.  The region experiences several types of landslides especially during the monsoon (August to September 2018).  The new species was discovered in one of the worst landslide hits area in Nelliyampathy forest, Kundrachola region.  The new aquatic beetle species is moderately large in size and often very attractively marked dorsally with complex maculations.  Additionally, the new species shows a strong synapomorphy along with Eretini, Hydaticini, and Aubehydrini tribes.

What next? A Bayesian hierarchical modeling re-examination of treatments for adolescents with selective serotonin reuptake inhibitor-resistant depression

BACKGROUND

Psychiatrists frequently struggle with how to sequence treatment for depressed adolescents who do not respond to an adequate trial of a selective serotonin reuptake inhibitor (SSRI). This study leveraged recent statistical and computational advances to create Bayesian hierarchal models (BHMs) of response in the treatment of SSRI-resistant depression in adolescents study to inform treatment planning.

METHODS

BHMs of individual treatment trajectories were developed and estimated using Hamiltonian Monte Carlo no u-turn sampling. From the Monte Carlo pseudorandom sample, 95% credible intervals, means, posterior tail probabilities, and so forth, were determined. Then, for the random effects model, posterior tail probabilities were used to create Bayesian two-tailed p values to evaluate the null hypotheses: no difference in efficacy between SSRIs and venlafaxine. The robustness of the results was examined using the fixed effects model of treatment comparisons.

RESULTS

In patients not receiving cognitive behavioral therapy (CBT; n = 168), SSRIs produced greater and faster improvement in depressive symptoms compared to venlafaxine (p = .015). No differences in response or trajectory of response for symptoms of anxiety were detected between SSRIs and venlafaxine (p = .168). For patients receiving CBT (n = 162), SSRIs and venlafaxine produced similar improvements in symptoms of anxiety and depression.

CONCLUSIONS

Findings from this novel computational approach suggest that a second trial of an SSRI is warranted for depressed adolescents who fail to respond to initial SSRI treatment.

3D Culture Facilitates VEGF-Stimulated Endothelial Differentiation of Adipose-Derived Stem Cells

De novo vascularization of implantable tissue and whole organ constructs has been a significant challenge in the field of tissue engineering; the use of endothelial cell populations for this task is constrained by the cell population's limited regeneration capacity and potential for loss of function. Thus, there is a need for a stem-cell population that may be induced into an endothelial cell phenotype reliably. Adipose derived stem cells (ADSCs) are multipotent cells that can be readily isolated from donor fat and may have the potential to be readily induced into endothelial cells. The ability to stimulate endothelial differentiation of these cells has been limited in standard 2D culture. We hypothesized that 3D culture would yield better differentiation. To study the influence of cell density and culture conditions on the potential of ADSCs to differentiate into an endothelial-like state, we seeded these cells types within a 3D cell-adhesive, proteolytically degradable, peptide-modified poly(ethylene-glycol) (PEG) hydrogel. ADSCs were either cultured in basal media or pro-angiogenic media supplemented with 20 ng/mL of VEGF in 2D and then encapsulated at low or high densities within the PEG-based hydrogel. These encapsulated cells were maintained in either basal media or pro-angiogenic media. Cells were then isolated from the hydrogels and cultured in Matrigel to assess the potential for tubule formation. Our work shows that maintenance of ADSCs in a pro-angiogenic medium in 2D monoculture alone does not result in any CD31 expression. Furthermore, the level of CD31 expression was affected by the density of the cells encapsulated within the PEG-based hydrogel. Upon isolation of these cells, we found that these induced ADSCs were able to form tubules within Matrigel, indicative of endothelial function, while ADSCs cultured in basal medium could not. This finding points to the potential for this stem-cell population to serve as a safe and reliable source of endothelial cells for tissue engineering and regenerative medicine purposes.

Surface topography and hydrophilicity regulate macrophage phenotype in milled microfluidic systems

Micromilling is an underutilized technique for fabricating microfluidic platforms that is well-suited for the diverse needs of the biologic community. This technique, however, produces culture surfaces that are considerably rougher than in commercially available culture platforms and the hydrophilicity of these surfaces can vary considerably depending on the choice of material. In this study, we evaluated the impact of surface topography and hydrophilicity in milled microfluidic devices on the cellular phenotype and function of primary human macrophages. We found that the rough culture surface within micromilled systems affected the phenotype of macrophages cultured in these devices. However, the presence, type, and magnitude of this effect was dependent on the surface hydrophilicity as well as exposure to chemical polarization signals. These findings confirm that while milled microfluidic systems are an effective platform for culture and analysis of primary macrophages, the topography and hydrophilicity of the culture surface within these systems should be considered in the planning and analysis of any macrophage experiments in which phenotype is relevant.

Evaluation of activity of hypothalamo-pituitary-gonadal axis in postmenopausal women suffering from severe acute illness

Background & objectives:

Postmenopausal women constitute an ideal model for studying the extent of hypothalamo-pituitary gonadal (HPG) axis suppression in critical illness as the gonadotropins are normally high and non-cyclical in them. The objective was to assess the impact of acute severe illness in postmenopausal women on the HPG axis and the activities of the hypothalamo-pituitary-adrenal (HPA), the hypothalamo- pituitary-thyroid (HPT) axes; and levels of serum prolactin, by comparison between critically ill postmenopausal women and otherwise healthy postmenopausal women.

Methods:

Thirty five consecutive postmenopausal women older than 60 yr admitted to medical intensive care with a Simplified Acute Physiology Score II (SAPS II) more than 30 were included. On day five of their in-hospital stay, blood samples were collected for oestradiol, luteinizing hormone (LH), follicle stimulating hormone (FSH), cortisol, androstenedione, prolactin and thyroid profile. Thirty five apparently healthy postmenopausal women were selected as controls.

Results:

Levels of LH, FSH, thyrotropin, free thyroxin (fT₄) and free tri-iodothyronine (fT₃) were lower while oestradiol, cortisol and dehydroepiandrosterone were higher among patients in comparison to healthy controls. Prolactin levels were similar in patients and controls. Among sick patients both FSH and fT₄ showed a negative correlation (P<0.05) with the SAPS II score.

Interpretation & conclusions:

In critically ill postmenopausal women, paradoxically elevated oestrogen levels despite gonadotropin suppression suggests a non-ovarian origin. Prolactin remained unaltered in patients despite their illness, possibly reflecting atrophy of lactotrophs in menopause.

In vitro anti-HIV-1 activity of fucoidan from Sargassum swartzii

Sargassum swartzii, a marine brown algae with wide range of biological properties belongs to the family Sargassaceae. Bioactive fucoidan fractions (CFF, FF1 and FF2) were isolated from S. swartzii and characterized by linear gradient anion-exchange chromatography and FT-IR. The characterized fucoidan fractions contained mainly sugars, sulfate and uronic acid. In the present study, anti-HIV-1 property of the fucoidan fractions was investigated. Fraction FF2 was found to exhibit significant anti-HIV-1 activity at concentrations of 1.56 and 6.25 μg/ml as observed by >50% reduction in HIV-1 p24 antigen levels and reverse transcriptase activity. Fucoidan fractions have no cytotoxic effects on PBMCs at the concentration range of 1.56-1000 μg/ml. These results suggest that fucoidan fractions could have inhibitory activity against HIV and has potential as an anti-HIV-1 agent.

Engineering 3D Nanoplasmonic Assemblies for High Performance Spectroscopic Sensing

We demonstrate the fabrication of plasmonic sensors that comprise gold nanopillar arrays exhibiting high surface areas, and narrow gaps, through self-assembly of amphiphilic diblock copolymer micelles on silicon substrates. Silicon nanopillars with high integrity over arbitrary large areas are obtained using copolymer micelles as lithographic templates. The gaps between metal features are controlled by varying the thickness of the evaporated gold. The resulting gold metal nanopillar arrays exhibit an engineered surface topography, together with uniform and controlled separations down to sub-10 nm suitable for highly sensitive detection of molecular analytes by Surface Enhanced Raman Spectroscopy (SERS). The significance of the approach is demonstrated through the control exercised at each step, including template preparation and pattern-transfer steps. The approach is a promising means to address trade-offs between resolutions, throughput, and performance in the fabrication of nanoplasmonic assemblies for sensing applications.

Ischemia-modified albumin levels in overt and subclinical hypothyroidism

BACKGROUND

Free radical-mediated oxidative stress (OS) has been implicated in the pathogenesis of thyroid disorders. The ischemia-modified albumin (IMA) has been proposed as a marker of protein oxidative damage, which has been found to reflect hypoxic stress.

AIM

Our aim was to evaluate IMA, malondialdehyde (MDA), and reduced glutathione (GSH) levels in patients with overt hypothyroidism (OHT) and subclinical hypothyroidism (SHT) in comparison to euthyroid controls.

SUBJECTS AND METHODS

Albumin, IMA, IMA/albumin ratio, MDA, GSH, total cholesterol (TC), triglycerides (TG), HDL-Cholesterol were assessed in 105 subjects grouped into OHT, SHT patients, and euthyroid controls with 35 subjects in each group.

RESULTS

MDA and IMA levels were significantly elevated while the GSH concentrations were significantly lower in OHT and SHT patients compared to controls (p < 0.01). When IMA values were normalized for albumin concentrations, the IMA/albumin ratio was also significantly elevated in both patient groups compared to controls (p < 0.01). These changes were more pronounced in the OHT group when compared to SHT group. In OHT group, thyroid-stimulating hormone (TSH) levels showed significant positive correlation with MDA (r = 0.470, p = 0.004), IMA (r = 0.530, p = 0.001), and IMA/albumin ratio (r = 0.525, p = 0.001). Both IMA (r = -0.342, p = 0.041), IMA/albumin ratio (r = -0.378, p = 0.023) showed significant negative correlation with GSH in OHT patients. No significant correlation between variables was, however, observed in SHT group.

CONCLUSIONS

Increase of MDA and IMA levels with decreased antioxidant status indicate the presence of OS in hypothyroid patients, which was more pronounced in OHT patients. Elevated levels of IMA can be a clinically useful marker of protein oxidative damage and OS in hypothyroidism.

Malignancy in solitary thyroid nodule: A clinicoradiopathological evaluation

BACKGROUND

Thyroid nodules are common. They can be either benign or malignant. Solitary thyroid nodules (STN) have a high likelihood of being malignant. They should be characterized properly for optimum management.

MATERIALS AND METHODS

In this study, we have analyzed our departmental data over a period of 5 years. All the patients who presented to the outpatient department with a clinically detected STN were included in the study group. Our approach was individualized. Preoperative ultrasonography (USG) and fine-needle aspiration cytology were planned in all these patients. Hemi thyroidectomy and total thyroidectomy with and without neck dissection were performed wherever appropriate.

RESULTS

There were 162 cases of clinically detected STN. USG findings were available in 146 cases. Postoperative histopathology was reported as malignant in 58 cases. Malignant STN was more likely in males. Ultrasonographically detected solid STN were more prone for malignancy as compared to multinodular goiter (P = 0.000) Presence of micro calcification and cervical lymphadenopathy were more commonly noted in malignant thyroid swellings.

CONCLUSION

Solitary thyroid nodules do have a high likelihood of harboring a malignancy. Solid echogenicity, micro calcification and cervical lymphadenopathy on USG were seen more frequently in malignant nodules.

SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures

We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information

RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with ∼94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ∼83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA-protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred.

Anti-HBV activity of the different extracts from Phyllanthus rheedei Wight in cell culture based assay systems

ETHNOPHARMACOLOGICAL RELEVANCE

Phyllanthusrheedei Wight is a plant used by Muthuvan tribes of Kerala for treating liver related diseases.

MATERIALS AND METHODS

The different extracts of Phyllanthus rheedei were analysed on cell lines were viz, PLC/PRF, Hep3B, FLCII10 and HepG2215 for its anti-HBV property. The analysis was done through ELISA, SQRT-PCR and immuno blotting. The most active extract was then divided in to fractions using HPTLC and the most active fraction was further identified.

RESULTS

From the screening experiments it was shown that the ethanol extract of this plant has the maximum activity in lowering the viral markers like HBsAg, HBV Core and HBV X protein and whole virions with comparatively lesser cytotoxicity. The dose responses of this particular extract were further established.

CONCLUSIONS

This study concluded that the ethanol extract of Phyllanthusrheedei is very much effective in preventing the multiplication of HBV at the cellular level. This study scientifically validated the tribal claim of the use of this plant for severe liver disorders.

Palmar arch reconstruction using dorsal venous arch of foot for revascularisation of multiple digits

A case of trauma causing total loss of superficial and deep palmar arches of hand with ischemia of all the digits was managed using dorsal venous arch of the foot to reconstruct the palmar arch. The ends of the venous arch were anastomosed to radial and ulnar arteries and the tributaries to the arch were coapted to the cut ends of the common digital vessels and princeps pollicis. The surgery yielded gratifying results, successfully revascularising all the digits.

A protein block based fold recognition method for the annotation of twilight zone sequences

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

Antioxidant defense in overt and subclinical hypothyroidism

Oxidative stress as a result of disequilibrium between free radical generation and antioxidant status has been implicated in several pathologies including thyroid diseases. Studies on antioxidant status in overt (OHT) and subclinical hypothyroidism (SHT) are controversial and limited. The aim of this study was to determine the effect of OHT and SHT on antioxidant status. Thirty-six patients with OHT, 36 patients with SHT, and 39 healthy euthyroid subjects as the control group were included in the study. Plasma levels of malondialdehyde (MDA), reduced glutathione (GSH) and total antioxidant capacity (TAC) as ferric reducing ability of plasma (FRAP), and erythrocyte antioxidant enzymes superoxide dismutase (SOD), glutathione peroxidase (GPx), SOD/GPx ratios, catalase (CAT), and glutathione reductase (GR) were analyzed in all groups. MDA and GPx values were elevated, while GSH, FRAP, SOD, and SOD/GPx ratio were decreased in both patient groups compared with controls. No change in activities of CAT and GR were observed in both the patient groups. Significant differences were observed between OHT and SHT groups with high MDA, GPX and low GSH, FRAP, SOD, and SOD/GPx ratio in OHT group. Thus, hypothyroid patients have a deficient antioxidant defense in the form of decreased activity of SOD, decreased levels of FRAP and GSH along with an increase in GPx activity. The severity of the disease appears to decide the degree of deficiency and our findings also point to this, in the form of decrease in SOD, FRAP, and GSH observed being more in OHT than in SHT patients. Hormonal changes and increased lipid peroxidation, which also vary with severity of disease, appear to contribute to the antioxidant deficiency.

Evaluation of protein oxidation and its association with lipid peroxidation and thyrotropin levels in overt and subclinical hypothyroidism

Both overt (OHT) and subclinical hypothyroid (SHT) disorders have been found to be associated with increased oxidative stress (OXS). Excess thyrotropin [thyroid stimulating hormone (TSH)] is known to directly produce OXS. Increased lipid peroxidation is known to facilitate protein carbonylation. However, the associations between lipid and protein oxidation and elevated TSH levels have not been studied. Thyroid profile, lipid peroxidation as malondialdehyde (MDA) levels and protein carbonylation as protein carbonyls (PCO) were estimated in OHT and SHT groups consisting of 36 patients each, in comparison to 39 euthyroid controls. We also determined the associations between TSH, MDA, and PCO levels in OHT and SHT groups. Increased oxidative damage was evidenced through significant elevations in the concentrations of MDA and PCO in OHT and SHT groups compared to controls (p < 0.01). Both TSH and MDA levels were positively associated with PCO in OHT group. Partial correlation analysis revealed that both excess TSH and increased MDA levels are mutually influencing elevated PCO. The results indicate that there is a simultaneous oxidative damage to lipids and proteins leading to increased MDA and PCO levels in both patient groups. Either of the excess TSH and increased MDA levels are combinably involved in the elevation of PCO in hypothyroidism.

Association of lipid peroxidation with endothelial dysfunction in patients with overt hypothyroidism

Hypothyroidism is associated with increased oxidative stress. The mechanism underlying the endothelial dysfunction in thyroid disease is not yet clear. This study aims to investigate lipid peroxidation and its association with endothelial dysfunction in overt hypothyroidism (OHT).Plasma malondialdehyde (MDA) as a marker of oxidative stress and plasma nitrates and asymmetric dimethyl arginine levels (ADMA) as markers of endothelial dysfunction were estimated in 25 OHT patients in comparison to 25 euthyroid controls. Plasma MDA, ADMA levels were significantly increased, whereas plasma nitrates were significantly decreased in the patient group compared to control group (p<0.01). Moreover, a significant positive association between plasma MDA and ADMA was found in the patient group (ρ=0.472, p=0.036). Our results reveal the presence of endothelial dysfunction in OHT patients as evidenced by decreased plasma nitrates and increased ADMA levels. Increased levels of MDA represent an increased generation of reactive oxygen species in these patients. A finding of significant direct relation of plasma MDA with ADMA indicates that oxidative stress has a strong impact on endothelial dysfunction in overt hypothyroidism. Further studies focusing on the role of oxidative stress in endothelial dysfunction and the effects of antioxidant supplementation on endothelial function in OHT patients are required.

High-density lipoprotein cholesterol: How High

The high-density lipoprotein cholesterol (HDL-C) is considered anti-atherogenic good cholesterol. It is involved in reverse transport of lipids. Epidemiological studies have found inverse relationship of HDL-C and coronary heart disease (CHD) risk. When grouped according to HDL-C, subjects having HDL-C more than 60 mg/dL had lesser risk of CHD than those having HDL-C of 40-60 mg/dL, who in turn had lesser risk than those who had HDL-C less than 40 mg/dL. No upper limit for beneficial effect of HDL-C on CHD risk has been identified. The goals of treating patients with low HDL-C have not been firmly established. Though many drugs are known to improve HDL-C concentration, statins are proven to improve CHD risk and mortality. Cholesteryl ester transfer protein (CETP) is involved in metabolism of HDL-C and its inhibitors are actively being screened for clinical utility. However, final answer is still awaited on CETP-inhibitors.

Swyer Syndrome : A Case Report with Literature Review

Gonadoblastomas are known to develop in dysgenetic gonads, especially so, if Y chromosome material is present. A 20-years- old girl who noticed breast development since the age of 12 years presented with primary amenorhoea, distension of lower abdomen and intermittent pain for two months. She had breakthrough bleeding with six months of estrogen replacement. Tanner breast stage was fi ve and pubic hair stage was also fi ve. Examination revealed a mass in the lower abdomen extending into hypogastrium, umbilical and lumbar regions. Her gonadotropin levels were grossly elevated. Karyotyping showed 46XY. CT scan of abdomen showed a 17X11 cm mass in the pelvis without visible gonads. Surgical excision of the mass along with bilateral salpingophorectomy was performed. Histopathology revealed the mass to be a dysgerminoma, while the right gonad lodged gonadoblastoma. She was diagnosed as a rare case of Swyer syndrome. Keywords: Dysgerminoma, gonadoblastoma, Swyer syndrome, XY gonadal dysgenesis.

Swyer syndrome: a case report with literature review

Gonadoblastomas are known to develop in dysgenetic gonads, especially so, if Y chromosome material is present. A 20-years-old girl who noticed breast development since the age of 12 years presented with primary amenorhoea, distension of lower abdomen and intermittent pain for two months. She had breakthrough bleeding with six months of estrogen replacement. Tanner breast stage was five and pubic hair stage was also five. Examination revealed a mass in the lower abdomen extending into hypogastrium, umbilical and lumbar regions. Her gonadotropin levels were grossly elevated. Karyotyping showed 46XY. CT scan of abdomen showed a 17X11 cm mass in the pelvis without visible gonads. Surgical excision of the mass along with bilateral salpingophorectomy was performed. Histopathology revealed the mass to be a dysgerminoma, while the right gonad lodged gonadoblastoma. She was diagnosed as a rare case of Swyer syndrome.