Effects of Selective Serotonin Reuptake Inhibitor Use on 3,4-Methylenedioxymethamphetamine-Assisted Therapy for Posttraumatic Stress Disorder: A Review of the Evidence, Neurobiological Plausibility, and Clinical Significance.

BACKGROUND: Among the renewed applications of psychedelic medicines in psychiatry, 3,4-methylenedioxymethamphetamine (MDMA)-assisted therapy for posttraumatic stress disorder (PTSD) has demonstrated the most promise in early small-scale studies. Recent exploratory analyses from prior clinical trials of MDMA-assisted therapy for PTSD have suggested that recent use of selective serotonin reuptake inhibitors (SSRIs)-the only medication class with United States Food and Drug Administration (FDA) approval to treat PTSD-can significantly dampen the efficacy of this novel therapy. Although psychedelic medicines are not yet FDA approved, MDMA is very likely to be the first to achieve FDA approval-perhaps within the next 2 years. Given this timeline, the field would benefit from more knowledge about potential interactions between this novel therapy and our current treatments. METHODS: This brief report reviews selected literature in the basic and clinical neurosciences relevant to the interaction of SSRIs and MDMA. FINDINGS: The possibility that SSRI use could dampen future responses to MDMA-assisted therapy for PTSD raises many important questions about the biological mechanisms as well as ethical implications around the most appropriate way to counsel patients. In this brief report, we compare the evidence for SSRIs and MDMA-assisted therapy in the treatment of PTSD and discuss what is known about the neurobiological interactions between these 2 medicines. CONCLUSIONS: There is strong neurobiological plausibility for the hypothesis that chronic SSRI use dampens response to MDMA-assisted therapy, although current knowledge in the field is limited and primarily relates to acute pharmacodynamic interactions. Our commentary highlights the urgent need for future work dedicated to addressing this important clinical topic.

Propofol-induced loss of consciousness is associated with a decrease in thalamocortical connectivity in humans.

Although the molecular effects of many anaesthetics have been well characterized, a network-level explanation for how these changes lead to loss of consciousness remains unclear. Studies using electroencephalography have characterized changes in neural oscillations in the cortex at specific frequency bands during propofol-induced anaesthesia and modelling work suggests these changes result from changes in thalamocortical functional connectivity. However, it is unclear if the neurophysiological changes seen at the cortex are due to enhanced or disrupted thalamocortical communication. Direct recordings from these sites during anaesthesia that could be used to confirm such models are rare. We recorded local field potentials from the ventral intermediate nucleus of the thalamus and electrocorticography signals from the ipsilateral sensorimotor cortex in 10 patients undergoing deep brain stimulation surgery. Signals were acquired during induction of propofol anaesthesia while subjects were resting. After confirming direct structural connectivity between the thalamus and the cortical recording site, we investigated propofol-associated changes in thalamic and cortical local power as well as thalamocortical functional connectivity, as measured with coherence, debiased weighted phase lag index, and phase amplitude coupling. Propofol anaesthesia resulted in local power increases at α frequencies (8-12 Hz) across both thalamic and cortical areas. At sensorimotor cortices, there was a broadband power increase (12-100 Hz), while the power of this same broad frequency band was suppressed within the thalamus. Despite the increase in local α power both within the thalamus and cortex, thalamocortical coherence and debiased weighted phase lag index in the α/low ß frequencies (8-16 Hz, which was present in the awake state) significantly decreased with propofol administration (P < 0.05, two group test of coherence). Likewise, propofol administration resulted in decreased phase amplitude coupling between the phase of α/low ß in the thalamus and the amplitude of broadband gamma (50-200 Hz) in the cortex (P = 0.031, Wilcoxon signed-rank test). We also report phase amplitude coupling between the phase of slow wave oscillations (0.1-1 Hz) and amplitude of broadband frequencies (8-200 Hz) within the cortex and across thalamocortical connections, during anaesthesia, both following a peak-max pattern. While confirming α-power increases with propofol administration both in thalamus and cortex, we observed decreased thalamocortical connectivity, contradicting models that suggest increasing cortical low frequency power is necessarily related to increased thalamocortical coherence but in support of the theory that propofol-induced loss of consciousness is associated with disrupted thalamocortical communication.

Prevalence and Detection of Trichomonas vaginalis in HIV-Infected Pregnant Women.

BACKGROUND: Trichomonas vaginalis is a sexually transmitted infection associated with increased transmission of HIV and significant adverse birth outcomes; culture and polymerase chain reaction (PCR) are commonly used in diagnosis. METHODS: Consenting HIV-infected pregnant women were recruited from clinics in South Africa and screened for T. vaginalis using PCR. Polymerase chain reaction-positive women provided an additional sample for culture. We compared T. vaginalis detection between PCR and culture, and investigated how PCR cycle threshold (Ct) values differ among culture results. RESULTS: A total of 359 women were enrolled and 76 (20%) tested T. vaginalis PCR positive. Cultures were obtained from 61 of the PCR-positive women, and 38 (62%) were culture positive. The median baseline Ct of the PCR-positive/culture-positive group was 22.6 versus 38.0 among those who were PCR positive/culture negative (P < 0.001). Culture-positive cases had lower Ct values (higher DNA load); a Ct value less than 30 predicted positivity with a sensitivity of 97% and a specificity of 96%. CONCLUSIONS: Culture was positive in roughly half of PCR-positive cases. The culture-negative cases had significantly higher Ct values, indicating a lower concentration of T. vaginalis DNA. A Ct value of 30 provides a reliable threshold for predicting culture positivity. The clinical significance of culture-negative infections detected by PCR is still unclear.

Propofol-induced Changes in α-ß Sensorimotor Cortical Connectivity.

BACKGROUND: Anesthetics are believed to alter functional connectivity across brain regions. However, network-level analyses of anesthesia, particularly in humans, are sparse. The authors hypothesized that propofol-induced loss of consciousness results in functional disconnection of human sensorimotor cortices underlying the loss of volitional motor responses. METHODS: The authors recorded local field potentials from sensorimotor cortices in patients with Parkinson disease (N = 12) and essential tremor (N = 7) undergoing deep brain stimulation surgery, before and after propofol-induced loss of consciousness. Local spectral power and interregional connectivity (coherence and imaginary coherence) were evaluated separately across conditions for the two populations. RESULTS: Propofol anesthesia caused power increases for frequencies between 2 and 100 Hz across the sensorimotor cortices and a shift of the dominant spectral peak in α and ß frequencies toward lower frequencies (median ± SD peak frequency: 24.5 ± 2.6 Hz to 12.8 ± 2.3 Hz in Parkinson disease; 13.8 ± 2.1 Hz to 12.1 ± 1.0 Hz in essential tremor). Despite local increases in power, sensorimotor cortical coherence was suppressed with propofol in both cohorts, specifically in ß frequencies (18 to 29 Hz) for Parkinson disease and α and ß (10 to 48 Hz) in essential tremor. CONCLUSIONS: The decrease in functional connectivity between sensory and motor cortices, despite an increase in local spectral power, suggests that propofol causes a functional disconnection of cortices with increases in autonomous activity within cortical regions. This pattern occurs across diseases evaluated, suggesting that these may be generalizable effects of propofol in patients with movement disorders and beyond. Sensorimotor network disruption may underlie anesthetic-induced loss of volitional control.

Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination.

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly important tool in mapping the functional networks of the brain. This tool has been used to examine network changes induced by cognitive and emotional states, neurological traits, and neuropsychiatric disorders. However, noise that remains in the rs-fMRI data after preprocessing has limited the reliability of individual-subject results, wherein scanner artifacts, subject movements, and other noise sources induce non-neural temporal correlations in the blood oxygen level-dependent (BOLD) timeseries. Numerous preprocessing methods have been proposed to isolate and remove these confounds; however, the field has not coalesced around a standard preprocessing pipeline. In comparisons, these preprocessing methods are often assessed with only a single metric of rs-fMRI data quality, such as reliability, without considering other aspects in tandem, such as signal-to-noise ratio and group discriminability. The present study seeks to identify the data preprocessing pipeline that optimizes rs-fMRI data across multiple outcome measures. Specifically, we aim to minimize the noise in the data and maximize result reliability, while retaining the unique features that characterize distinct groups. We examine how these metrics are influenced by bandpass filter selection and noise regression in four datasets, totaling 181 rs-fMRI scans and 38 subject-driven memory scans. Additionally, we perform two different rs-fMRI analysis methods - dual regression and region-of-interest based functional connectivity - and highlight the preprocessing parameters that optimize both approaches. Our results expand upon previous reports of individual-scan reliability, and demonstrate that preprocessing parameter selection can significantly change the noisiness, reliability, and heterogeneity of rs-fMRI data. The application of our findings to rs-fMRI data analysis should improve the validity and reliability of rs-fMRI results, both at the individual-subject level and the group level.

The need for establishing best practices and gold standards in psychedelic medicine.

Psychedelic substances are under investigation in several drug development programs. Controlled clinical trials are providing evidence for safe and effective use of psychedelic therapies for treating mental health conditions. With the anticipated FDA approval of MDMA-assisted therapy for posttraumatic stress disorder in 2023 and psilocybin therapy for depression disorders soon after, now is the time for the medical community to become informed on best practices and to actively participate in developing standards of care for these new treatments. Given the emergence of numerous drug sponsors and other companies developing therapeutic modalities for combination with psychedelic medications, it is essential that the medical professional field is at the forefront of communicating unbiased information related to safety and effectiveness. Gold standards have long been a part of medicine and serve to distinguish treatments and assessments as the highest quality by which all others can be compared to. For a treatment to be established as a gold standard, several factors are considered including the quantity and quality of the supporting data, the rigor of trials, and the safety and efficacy compared to other treatments. In this article, we review the origins of psychedelic-assisted therapy (PAT), minimum requirements for safe use of psychedelics, criteria for gold standards in mental health, and the nuances regarding how to establish gold standards in psychedelic medicine and guide clinical decision making.

Microbiome in Anxiety and Other Psychiatric Disorders.

Initial studies suggested that the fluctuations in the quantity, variety, and composition of the gut microbiota can significantly affect disease processes. This change in the gut microbiota causing negative health benefits was coined dysbiosis. Initial research focused on gastrointestinal illnesses. However, the gut microbiome was found to affect more than just gastrointestinal diseases. Numerous studies have proven that the gut microbiome can influence neuropsychiatric diseases such as Parkinson's disease, Alzheimer's disease, and multiple sclerosis.

Impulsivity Relates to Relative Preservation of Mesolimbic Connectivity in Patients with Parkinson Disease.

INTRODUCTION: The relationship between Parkinson Disease (PD) pathology, dopamine replacement therapy (DRT), and impulse control disorder (ICD) development is still incompletely understood. Given the sensorimotor-lateral substantia nigra (SN) selective degeneration associated with PD, we posit that a relative sparing of the limbic-medial SN in the context of DRT drives impulsive, reward-seeking behavior in PD patients with recent history of severe impulsivity. METHODS: Impulsive and control participants were selected from a consecutive list of PD patients receiving pre-operative deep brain stimulation (DBS) planning scans including 3T structural MRI and 64 direction diffusion tensor imaging (DTI). Using previously identified substantia nigra (SN) subsegment network connectivity profiles to develop classification targets, split-hemisphere target-based SN segmentation with probabilistic tractography was performed. The relative subsegment volumes and strength of connectivity between the SN and the limbic, associative, and motor network targets were compared. RESULTS: Our results show that there is greater probability of connectivity between the SN and limbic network targets relative to motor and associative network targets in PD patients with recent history of severe impulsivity as compared to PD patients without impulsivity (P = 0.0075). We did not observe relative volumetric subsegment differences across groups. CONCLUSION: Firstly, our results suggest that fine-grained, atlas-derived classification targets may be used in PD to parcellate and classify functionally distinct subsegments of the SN, with the apparent preservation of previously reported topographical limbic-medial SN, associative-ventral SN, and sensorimotor-lateral SN orientation. We suggest that relative, as opposed to absolute, degeneration amongst SN-associated dopaminergic networks relates to the impulsivity phenotype in PD.

Characterizing Signals Within Lesions and Mapping Brain Network Connectivity After Traumatic Axonal Injury: A 7 Tesla Resting-State FMRI Study.

Resting-state functional magnetic resonance imaging (RS-FMRI) has been widely used to map brain functional connectivity, but it is unclear how to probe connectivity within and around lesions. In this study, we characterize RS-FMRI signal time course properties and evaluate different seed placements within and around hemorrhagic traumatic axonal injury (hTAI) lesions. RS-FMRI was performed on a 7 Tesla scanner in a patient who recovered consciousness after traumatic coma and in three healthy controls. Eleven lesions in the patient were characterized in terms of (1) temporal signal-to-noise ratio (tSNR); (2) physiological noise, through comparison of noise regressors derived from the white matter (WM), cerebrospinal fluid (CSF), and gray matter (GM); and (3) seed-based functional connectivity. Temporal SNR at the center of the lesions was 38.3% and 74.1% lower compared with the same region in the contralesional hemisphere of the patient and in the ipsilesional hemispheres of the controls, respectively. Within the lesions, WM noise was more prominent than CSF and GM noise. Lesional seeds did not produce discernable networks, but seeds in the contralesional hemisphere revealed networks whose nodes appeared to be shifted or obscured due to overlapping or nearby lesions. Single-voxel seed analysis demonstrated that placing a seed within a lesion's periphery was necessary to identify networks associated with the lesion region. These findings provide evidence of resting-state network changes in the human brain after recovery from traumatic coma. Furthermore, we show that seed placement within a lesion's periphery or in the contralesional hemisphere may be necessary for network identification in patients with hTAI.

Eukaryotic G protein signaling evolved to require G protein-coupled receptors for activation.

Although bioinformatic analysis of the increasing numbers of diverse genome sequences and amount of functional data has provided insight into the evolution of signaling networks, bioinformatics approaches have limited application for understanding the evolution of highly divergent protein families. We used biochemical analyses to determine the in vitro properties of selected divergent components of the heterotrimeric guanine nucleotide-binding protein (G protein) signaling network to investigate signaling network evolution. In animals, G proteins are activated by cell-surface seven-transmembrane (7TM) receptors, which are named G protein-coupled receptors (GPCRs) and function as guanine nucleotide exchange factors (GEFs). In contrast, the plant G protein is intrinsically active, and a 7TM protein terminates G protein activity by functioning as a guanosine triphosphatase-activating protein (GAP). We showed that ancient regulation of the G protein active state is GPCR-independent and "self-activating," a property that is maintained in Bikonts, one of the two fundamental evolutionary clades containing eukaryotes, whereas G proteins of the other clade, the Unikonts, evolved from being GEF-independent to being GEF-dependent. Self-activating G proteins near the base of the Eukaryota are controlled by 7TM-GAPs, suggesting that the ancestral regulator of G protein activation was a GAP-functioning receptor, not a GEF-functioning GPCR. Our findings indicate that the GPCR paradigm describes a recently evolved network architecture found in a relatively small group of Eukaryota and suggest that the evolution of signaling network architecture is constrained by the availability of molecules that control the activation state of nexus proteins.