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"Mehta, D"
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Analysis of bacterial vaginosis, the vaginal microbiome, and sexually transmitted infections following the provision of menstrual cups in Kenyan schools: Results of a nested study within a cluster randomized controlled trial
Nonhygienic products for managing menstruation are reported to cause reproductive tract infections. Menstrual cups are a potential solution. We assessed whether menstrual cups would reduce bacterial vaginosis (BV), vaginal microbiome (VMB), and sexually transmitted infections (STIs) as studies have not evaluated this.
A cluster randomized controlled trial was performed in 96 Kenyan secondary schools, randomized (1:1:1:1) to control, menstrual cup, cash transfer, or menstrual cup plus cash transfer. This substudy assessing the impact of menstrual cups on BV, VMB, and STIs, included 6 schools from the control (3) and menstrual cup only (3) groups, both receiving BV and STI testing and treatment at each visit. Self-collected vaginal swabs were used to measure VMB (16S rRNA gene amplicon sequencing), BV (Nugent score), and STIs. STIs were a composite of Chlamydia trachomatis and Neisseria gonorrhoeae (nucleic acid amplification test) and Trichomonas vaginalis (rapid immunochromatographic assay). Participants were not masked and were followed for 30 months. The primary outcome was diagnosis of BV; secondary outcomes were VMB and STIs. Intention-to-treat blinded analyses used mixed effects generalized linear regressions, with random effects term for school. The study was conducted between May 2, 2018, and February 7, 2021. A total of 436 participants were included: 213 cup, 223 control. There were 289 BV diagnoses: 162 among control participants and 127 among intervention participants (odds ratio 0.76 [95% CI 0.59 to 0.98]; p = 0.038). The occurrence of Lactobacillus crispatus-dominated VMB was higher among cup group participants (odds ratio 1.37 [95% CI 1.06 to 1.75]), as was the mean relative abundance of L. crispatus (3.95% [95% CI 1.92 to 5.99]). There was no effect of intervention on STIs (relative risk 0.82 [95% CI 0.50 to 1.35]). The primary limitations of this study were insufficient power for subgroup analyses, and generalizability of findings to nonschool and other global settings.
Menstrual cups with BV and STI testing and treatment benefitted adolescent schoolgirls through lower occurrence of BV and higher L. crispatus compared with only BV and STI testing and treatment during the 30 months of a cluster randomized menstrual cup intervention.
ClinicalTrials.gov NCT03051789.
Journal Article
Routledge handbook of sports technology and engineering
This text offers a comprehensive survey of contemporary sports technology and engineering, providing a complete overview of academic, professional and industrial knowledge and technique. The book is divided into four main sections.
Book
Hippocampal sharp-wave ripples linked to visual episodic recollection in humans
What are the brain mechanisms responsible for episodic memory retrieval? Norman et al. investigated epilepsy patients who had electrodes implanted in the hippocampus and a variety of cortical areas. Using a visual learning paradigm, they examined the temporal relationship between the incidence of hippocampal sharp-wave ripples and recall. Effective encoding of visual information was associated with higher incidence of ripples. Successful recall was preceded by an increased probability of ripples, which were also associated with transient reemergence of activation patterns in higher visual cortical areas. Hippocampal ripples may thus boost recollections during episodic memory retrieval. Science , this issue p. eaax1030 Ripples reinstate human memory during free recall. Hippocampal sharp-wave ripples (SWRs) constitute one of the most synchronized activation events in the brain and play a critical role in offline memory consolidation. Yet their cognitive content and function during awake, conscious behavior remains unclear. We directly examined this question using intracranial recordings in human patients engaged in episodic free recall of previously viewed photographs. Our results reveal a content-selective increase in hippocampal ripple rate emerging 1 to 2 seconds prior to recall events. During recollection, high-order visual areas showed pronounced SWR-coupled reemergence of activation patterns associated with recalled content. Finally, the SWR rate during encoding predicted subsequent free-recall performance. These results point to a role for hippocampal SWRs in triggering spontaneous recollections and orchestrating the reinstatement of cortical representations during free episodic memory retrieval.
Journal Article
Towards reconstructing intelligible speech from the human auditory cortex
Auditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combined the recent advances in deep learning with the latest innovations in speech synthesis technologies to reconstruct closed-set intelligible speech from the human auditory cortex. We investigated the dependence of reconstruction accuracy on linear and nonlinear (deep neural network) regression methods and the acoustic representation that is used as the target of reconstruction, including auditory spectrogram and speech synthesis parameters. In addition, we compared the reconstruction accuracy from low and high neural frequency ranges. Our results show that a deep neural network model that directly estimates the parameters of a speech synthesizer from all neural frequencies achieves the highest subjective and objective scores on a digit recognition task, improving the intelligibility by 65% over the baseline method which used linear regression to reconstruct the auditory spectrogram. These results demonstrate the efficacy of deep learning and speech synthesis algorithms for designing the next generation of speech BCI systems, which not only can restore communications for paralyzed patients but also have the potential to transform human-computer interaction technologies.
Journal Article
Vagus nerve stimulation inhibits cytokine production and attenuates disease severity in rheumatoid arthritis
Rheumatoid arthritis (RA) is a heterogeneous, prevalent, chronic autoimmune disease characterized by painful swollen joints and significant disabilities. Symptomatic relief can be achieved in up to 50% of patients using biological agents that inhibit tumor necrosis factor (TNF) or other mechanisms of action, but there are no universally effective therapies. Recent advances in basic and preclinical science reveal that reflex neural circuits inhibit the production of cytokines and inflammation in animal models. One well-characterized cytokine-inhibiting mechanism, termed the “inflammatory reflex,” is dependent upon vagus nerve signals that inhibit cytokine production and attenuate experimental arthritis severity in mice and rats. It previously was unknown whether directly stimulating the inflammatory reflex in humans inhibits TNF production. Here we show that an implantable vagus nerve-stimulating device in epilepsy patients inhibits peripheral blood production of TNF, IL-1β, and IL-6. Vagus nerve stimulation (up to four times daily) in RA patients significantly inhibited TNF production for up to 84 d. Moreover, RA disease severity, as measured by standardized clinical composite scores, improved significantly. Together, these results establish that vagus nerve stimulation targeting the inflammatory reflex modulates TNF production and reduces inflammation in humans. These findings suggest that it is possible to use mechanism-based neuromodulating devices in the experimental therapy of RA and possibly other autoimmune and autoinflammatory diseases.
Journal Article
A systematic review and meta-analysis of neuromodulation therapies for substance use disorders
While pharmacological, behavioral and psychosocial treatments are available for substance use disorders (SUDs), they are not always effective or well-tolerated. Neuromodulation (NM) methods, including repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) may address SUDs by targeting addiction neurocircuitry. We evaluated the efficacy of NM to improve behavioral outcomes in SUDs. A systematic literature search was performed on MEDLINE, PsychINFO, and PubMed databases and a list of search terms for four key concepts (SUD, rTMS, tDCS, DBS) was applied. Ninety-four studies were identified that examined the effects of rTMS, tDCS, and DBS on substance use outcomes (e.g., craving, consumption, and relapse) amongst individuals with SUDs including alcohol, tobacco, cannabis, stimulants, and opioids. Meta-analyses were performed for alcohol and tobacco studies using rTMS and tDCS. We found that rTMS reduced substance use and craving, as indicated by medium to large effect sizes (Hedge’s g > 0.5). Results were most encouraging when multiple stimulation sessions were applied, and the left dorsolateral prefrontal cortex (DLPFC) was targeted. tDCS also produced medium effect sizes for drug use and craving, though they were highly variable and less robust than rTMS; right anodal DLPFC stimulation appeared to be most efficacious. DBS studies were typically small, uncontrolled studies, but showed promise in reducing misuse of multiple substances. NM may be promising for the treatment of SUDs. Future studies should determine underlying neural mechanisms of NM, and further evaluate extended treatment durations, accelerated administration protocols and long-term outcomes with biochemical verification of substance use.
Journal Article
N-cadherin adhesive interactions modulate matrix mechanosensing and fate commitment of mesenchymal stem cells
During mesenchymal development, the microenvironment gradually transitions from one that is rich in cell–cell interactions to one that is dominated by cell–ECM (extracellular matrix) interactions. Because these cues cannot readily be decoupled
in vitro
or
in vivo
, how they converge to regulate mesenchymal stem cell (MSC) mechanosensing is not fully understood. Here, we show that a hyaluronic acid hydrogel system enables, across a physiological range of ECM stiffness, the independent co-presentation of the HAVDI adhesive motif from the EC1 domain of N-cadherin and the RGD adhesive motif from fibronectin. Decoupled presentation of these cues revealed that HAVDI ligation (at constant RGD ligation) reduced the contractile state and thereby nuclear YAP/TAZ localization in MSCs, resulting in altered interpretation of ECM stiffness and subsequent changes in downstream cell proliferation and differentiation. Our findings reveal that, in an evolving developmental context, HAVDI/N-cadherin interactions can alter stem cell perception of the stiffening extracellular microenvironment.
N-cadherin can alter how the stiffening extracellular microenvironment is interpreted by mesenchymal stem cells, leading to subsequent changes in downstream cell proliferation and differentiation.
Journal Article
Brain-informed speech separation (BISS) for enhancement of target speaker in multitalker speech perception
•Multi-talker speech perception is challenging for people with hearing loss.•Automatic speech separation cannot help without first identifying the target speaker.•We used the brain signal of listeners to jointly identify and extract target speech.•This method eliminates the need for separating sound sources or knowing their number.•We show the efficacy of this method in both normal and hearing impaired subjects.
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Hearing-impaired people often struggle to follow the speech stream of an individual talker in noisy environments. Recent studies show that the brain tracks attended speech and that the attended talker can be decoded from neural data on a single-trial level. This raises the possibility of “neuro-steered” hearing devices in which the brain-decoded intention of a hearing-impaired listener is used to enhance the voice of the attended speaker from a speech separation front-end. So far, methods that use this paradigm have focused on optimizing the brain decoding and the acoustic speech separation independently. In this work, we propose a novel framework called brain-informed speech separation (BISS)11BISS: brain-informed speech separation. in which the information about the attended speech, as decoded from the subject’s brain, is directly used to perform speech separation in the front-end. We present a deep learning model that uses neural data to extract the clean audio signal that a listener is attending to from a multi-talker speech mixture. We show that the framework can be applied successfully to the decoded output from either invasive intracranial electroencephalography (iEEG) or non-invasive electroencephalography (EEG) recordings from hearing-impaired subjects. It also results in improved speech separation, even in scenes with background noise. The generalization capability of the system renders it a perfect candidate for neuro-steered hearing-assistive devices.
Journal Article
On the importance of precise electrode placement for targeted transcranial electric stimulation
Transcranial electric stimulation (TES) is an increasingly popular method for non-invasive modulation of brain activity and a potential treatment for neuropsychiatric disorders. However, there are concerns about the reliability of its application because of variability in TES-induced intracranial electric fields across individuals. While realistic computational models offer can help to alleviate these concerns, their direct empirical validation is sparse, and their practical implications are not always clear. In this study, we combine direct intracranial measurements of electric fields generated by TES in surgical epilepsy patients with computational modeling. First, we directly validate the computational models and identify key parameters needed for accurate model predictions. Second, we derive practical guidelines for a reliable application of TES in terms of the precision of electrode placement needed to achieve a desired electric field distribution. Based on our results, we recommend electrode placement accuracy to be < 1 cm for a reliable application of TES across sessions.
•Validation of computational models for TES•Investigation of electrode placement accuracy in 25 head models•Recommendation for electrode placements guidelines for TES
Journal Article