Prevalence of Obstructive Sleep Apnoea in patients with primary nasal and nasopharyngeal pathologies

The aim of this study was to study the prevalence of obstructive sleep apnea syndrome in patients with nasal and nasopharyngeal pathologies. A total of 60 consenting patients between the age of 14 to 60 years with primary nasal and nasopharyngeal pathologies were taken up for the study. These patients underwent history taking, detailed clinical examination including BMI, diagnostic nasal endoscopy and overnight polysomnography. The polysomnography results of people with different pathologies were compared and analysed. Based on the analysis it was arrived that isolated pathologies like septal deviation, nasal polypi and adenoid hypertrophy provided a statistically significant association with occurrence and severity of OSA. Also, that patients with combined pathologies were more proportionately affected by OSA than those with isolated pathologies. Nasal and nasopharyngeal pathologies have significant association with obstructive sleep apnea syndrome and all patients with these pathologies need to undergo polysomnography along with other routine investigations.

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.