IS MULLIGAN'S SUSTAINED NATURAL APOPHYSEAL GLIDES (SNAGS) OR MUSCLE ENERGY TECHNIQUE IS EFFECTIVE IN THE NON-SURGICAL MANAGEMENT OF CERVICOGENIC HEADACHE? A TWO-GROUP PRETEST-POSTTEST RANDOMIZED CONTROLLED TRIAL

Objective: The purpose of this study is to compare the efficacy of Mulligan's Glides like sustained natural apophyseal glides and muscle energy technique (MET) in the management of individual with cervicogenic headache (ICH).Methods: A total of 30 ICH were recruited by the simple random sampling to participate in this two-group pretest-posttest, single-blinded randomized clinical study. Recruited ICH was randomly allocated into two groups, Group A and Group B. ICH in Group A was provided with Mulligan's SNAGs of 3 glides/session/day×5 days/week×4-week duration, while in Group B, ICH received MET for suboccipital muscles for 6 times/session/day×5 days/ week×4 weeks. Both the groups received the common intervention of stretching and strengthening for cervical muscles for 4 weeks. Pain scores (visual analog score [VAS]), disability (headache disability index [HD]), and cervical extension range of motion (ROM) were documented at baseline and 4th week after intervention and analyzed.Results: Group B demonstrated significance difference (p<0.05) in HDI, VAS, and cervical extension ROM when compared to Group A.Conclusion: 4 week MET has the sufficient potential to decrease neck pain, disability, and increase cervical mobility among ICH as a non-surgical management

Digital Technology Needs in Maternal Mental Health: A Qualitative Inquiry.

Digital technologies offer many opportunities to improve mental healthcare management for women seeking pre- and-postnatal care. They provide a discrete, practical medium that is well-suited for the sensitive nature of mental health. Women who are more prone to experiencing peripartum depression (PPD), such as those of low-socioeconomic background or in high-risk pregnancies, can benefit the most from such technologies. However, current digital interventions directed towards this population provide suboptimal support, and their responsiveness to end user needs is quite limited. Our objective is to understand the digital terrain of information needs for low-socioeconomic status women with high-risk pregnancies, specifically within the management of their mental health. This qualitative study consists of semi-structured focus groups and interviews with a sample of nineteen patients. A total of eleven core themes emerged from participant comments. Resulting themes highlighted the need for digital technologies that promote personalized care, a sense of community, and improved provider communication

Digital Health Technologies for Peripartum Depression Management Among Low-Socioeconomic Populations: Perspectives From Patients, Providers, and Social Media Channels

BACKGROUND: Peripartum Depression (PPD) affects approximately 10-15% of perinatal women in the U.S., with those of low socioeconomic status (low-SES) more likely to develop symptoms. Multilevel treatment barriers including social stigma and not having appropriate access to mental health resources have played a major role in PPD-related disparities. Emerging advances in digital technologies and analytics provide opportunities to identify and address access barriers, knowledge gaps, and engagement issues. However, most market solutions for PPD prevention and management are produced generically without considering the specialized needs of low-SES populations. In this study, we examine and portray the information and technology needs of low-SES women by considering their unique perspectives and providers\u27 current experiences. We supplement our understanding of women\u27s needs by harvesting online social discourse in PPD-related forums, which we identify as valuable information resources among these populations. METHODS: We conducted (a) 2 focus groups (n = 9), (b) semi-structured interviews with care providers (n = 9) and low SES women (n = 10), and (c) secondary analysis of online messages (n = 1,424). Qualitative data were inductively analyzed using a grounded theory approach. RESULTS: A total of 134 open concepts resulted from patient interviews, 185 from provider interviews, and 106 from focus groups. These revealed six core themes for PPD management, including Use of Technology/Features , Access to Care , and Pregnancy Education . Our social media analysis revealed six PPD topics of importance in online messages, including Physical and Mental Health (n = 725 messages), and Social Support (n = 674). CONCLUSION: Our data triangulation allowed us to analyze PPD information and technology needs at different levels of granularity. Differences between patients and providers included a focus from providers on needing better support from administrative staff, as well as better PPD clinical decision support. Our results can inform future research and development efforts to address PPD health disparities

Temporal Multi-Step Predictive Modeling of Remission in Major Depressive Disorder Using Early Stage Treatment Data; Star*D Based Machine Learning Approach

BACKGROUND: Artificial intelligence is currently being used to facilitate early disease detection, better understand disease progression, optimize medication/treatment dosages, and uncover promising novel treatments and potential outcomes. METHODS: Utilizing the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, we built a machine learning model to predict depression remission rates using same clinical data as features for each of the first three antidepressant treatment steps in STAR*D. We only used early treatment data (baseline and first follow up) in each STAR*D step to temporally analyze predictive features of remission at the end of the step. RESULTS: Our model showed significant prediction performance across the three treatment steps, At step 1, Model accuracy was 66 %; sensitivity-65 %, specificity-67 %, positive predictive value (PPV)-65.5 %, and negative predictive value (NPV)-66.6 %. At step 2, model accuracy was 71.3 %, sensitivity-74.3 %, specificity-69 %, PPV-64.5 %, and NPV-77.9 %. At step 3, accuracy reached 84.6 %; sensitivity-69 %, specificity-88.8 %, PPV-67 %, and NPV-91.1 %. Across all three steps, the early Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) scores were key elements in predicting the final treatment outcome. The model also identified key sociodemographic factors that predicted treatment remission at different steps. LIMITATIONS: The retrospective design, lack of replication in an independent dataset, and the use of a complete case analysis model in our analysis. CONCLUSIONS: This proof-of-concept study showed that using early treatment data, multi-step temporal prediction of depressive symptom remission results in clinically useful accuracy rates. Whether these predictive models are generalizable deserves further study

Within Subject Cross-Tissue Analyzes of Epigenetic Clocks in Substance Use Disorder Postmortem Brain and Blood

There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n = 42), including alcohol (n = 10), opioid (n = 19), and stimulant use disorder (n = 13), and controls (n = 10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (β = 0.191, p-value = 0.0104) and a nominally lower DNAmTL (β = -0.149, p-value = 0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (β = 0.0150, p-value = 0.087). Cross-tissue analyzes indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used

Within Subject Cross-Tissue Analyzes of Epigenetic Clocks in Substance Use Disorder Postmortem Brain and Blood.

There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n=42), including alcohol (n=10), opioid (n=19), and stimulant use disorder (n=13), and controls (n=10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (beta=0.191, p-value=0.0104) and a nominally lower DNAmTL (beta=−0.149, p-value=0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (beta=0.0150, p-value=0.087). Cross-tissue analyses indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used

Early screening for post-stroke depression, and the effect on functional outcomes, quality of life and mortality: a protocol for a systematic review and meta-analysis

INTRODUCTION: Post-stroke depression (PSD) is a severe complication of cerebrovascular stroke affecting about one-third of stroke survivors. Moreover, PSD is associated with functional recovery and quality of life (QOL) in stroke survivors. Screening for PSD is recommended. There are, however, differences in the literature on the impact of early screening on functional outcomes. In this systematic review, we synthesise the currently available literature regarding the associations between timing and setting of PSD screening and mortality, QOL and functional outcomes in stroke survivors. METHODS AND ANALYSIS: We will systematically search electronic databases including PubMed, Embase, APA PsycINFO, Web of Science, Scopus and CINAHL from inception to August 2021. Four reviewers will screen the title and abstract and full-text level records identified in the search in a blinded fashion to determine the study eligibility. Any selection disagreements between the reviewers will be resolved by the study investigator. Data extraction of eligible studies will be conducted by two reviewers using a predefined template. We will complete the quality assessment of included articles independently by two reviewers using the Newcastle Ottawa Scale. Eventual discrepancies will be resolved by the principal investigator. ETHICS AND DISSEMINATION: Due to the nature of the study design, ethical approval is not required. The systematic review and meta-analysis findings will be published and disseminated in a peer-reviewed journal. Our results will also be disseminated through posters and presentations at appropriate scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42021235993

Microrna-Mrna Networks Are Dysregulated in Opioid Use Disorder Postmortem Brain: Further Evidence for Opioid-Induced Neurovascular Alterations

INTRODUCTION: To understand mechanisms and identify potential targets for intervention in the current crisis of opioid use disorder (OUD), postmortem brains represent an under-utilized resource. To refine previously reported gene signatures of neurobiological alterations in OUD from the dorsolateral prefrontal cortex (Brodmann Area 9, BA9), we explored the role of microRNAs (miRNA) as powerful epigenetic regulators of gene function. METHODS: Building on the growing appreciation that miRNAs can cross the blood-brain barrier, we carried out miRNA profiling in same-subject postmortem samples from BA9 and blood tissues. RESULTS: miRNA-mRNA network analysis showed that even though miRNAs identified in BA9 and blood were fairly distinct, their target genes and corresponding enriched pathways overlapped strongly. Among the dominant enriched biological processes were tissue development and morphogenesis, and MAPK signaling pathways. These findings point to robust, redundant, and systemic opioid-induced miRNA dysregulation with a potential functional impact on transcriptomic changes. Further, using correlation network analysis, we identified cell-type specific miRNA targets, specifically in astrocytes, neurons, and endothelial cells, associated with OUD transcriptomic dysregulation. Finally, leveraging a collection of control brain transcriptomes from the Genotype-Tissue Expression (GTEx) project, we identified a correlation of OUD miRNA targets with TGF beta, hypoxia, angiogenesis, coagulation, immune system, and inflammatory pathways. DISCUSSION: These findings support previous reports of neurovascular and immune system alterations as a consequence of opioid abuse and shed new light on miRNA network regulators of cellular response to opioid drugs

Effect of Citalopram on Emotion Processing in Humans:A Combined 5-HT [C]CUMI-101 PET and Functional MRI Study

A subset of patients started on a selective serotonin reuptake inhibitor (SSRI) initially experience increased anxiety, which can lead to early discontinuation before therapeutic effects are manifest. The neural basis of this early SSRI effect is not known. Presynaptic dorsal raphe neuron (DRN) 5-HT1A receptors are known to play a critical role in affect processing. Thus we investigated the effect of acute citalopram on emotional processing and the relationship between DRN 5-HT1A receptor availability and amygdala reactivity. Thirteen (mean age 48±9 years) healthy male subjects received either a saline or citalopram infusion intravenously (10 mg over 30 min) on separate occasions in a single-blind, random order, cross-over design. On each occasion, participants underwent a block design face-emotion processing task during fMRI known to activate the amygdala. Ten subjects also completed a positron emission tomography (PET) scan to quantify DRN 5-HT1A availability using [(11)C]CUMI-101.Citalopram infusion when compared to saline resulted in a significantly increased bilateral amygdala responses to fearful vs. neutral faces (Left p=0.025; Right p=0.038 FWE-corrected). DRN [(11)C]CUMI-101availability significantly positively correlated with the effect of citalopram on the left amygdala response to fearful faces (Z=2.51, p=0.027) and right amygdala response to happy faces (Z=2.33, p=0.032). Our findings indicate that the initial effect of SSRI treatment is to alter processing of aversive stimuli, and that this is linked to DRN 5-HT1A receptors in line with evidence that 5-HT1A receptors have a role in mediating emotional processing

A leaky umbrella has little value: evidence clearly indicates the serotonin system is implicated in depression.

A recent “umbrella” review examined various biomarkers relating to the serotonin system, and concluded there was no consistent evidence implicating serotonin in the pathophysiology of depression. We present reasons for why this conclusion is overstated, including methodological weaknesses in the review process, selective reporting of data, over-simplification, and errors in the interpretation of neuropsychopharmacological findings. We use the examples of tryptophan depletion and serotonergic molecular imaging, the two research areas most relevant to the investigation of serotonin, to illustrate this