Artificial intelligence in Parkinson's disease: Early detection and diagnostic advancements.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, globally affecting men and women at an exponentially growing rate, with currently no cure. Disease progression starts when dopaminergic neurons begin to die. In PD, the loss of neurotransmitter, dopamine is responsible for the overall communication of neural cells throughout the body. Clinical symptoms of PD are slowness of movement, involuntary muscular contractions, speech & writing changes, lessened automatic movement, and chronic tremors in the body. PD occurs in both familial and sporadic forms and modifiable and non-modifiable risk factors and socioeconomic conditions cause PD. Early detectable diagnostics and treatments have been developed in the last several decades. However, we still do not have precise early detectable biomarkers and therapeutic agents/drugs that prevent and/or delay the disease process. Recently, artificial intelligence (AI) science and machine learning tools have been promising in identifying early detectable markers with a greater rate of accuracy compared to past forms of treatment and diagnostic processes. Artificial intelligence refers to the intelligence exhibited by machines or software, distinct from the intelligence observed in humans that is based on neural networks in a form and can be used to diagnose the longevity and disease severity of disease. The term Machine Learning or Neural Networks is a blanket term used to identify an emerging technology that is created to work in the way of a "human brain" using many intertwined neurons to achieve the same level of raw intelligence as that of a brain. These processes have been used for neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease, to assess the severity of the patient's condition. In the current article, we discuss the prevalence and incidence of PD, and currently available diagnostic biomarkers and therapeutic strategies. We also highlighted currently available artificial intelligence science and machine learning tools and their applications to detect disease and develop therapeutic interventions.

Caring for Individuals with Alzheimer's Disease: A Spotlight on Hispanic Caregivers.

 A caregiver is a constantly evolving role that an individual most likely undertakes at some point in their lifetime. With discoveries and research in increasing life expectancy, the prevalence of neurological-related diseases, such as Alzheimer's disease (AD) and dementia, is certainly likely to require more caregivers. The demand for AD caregivers is escalating as the prevalence of the disease continues to rise. The projected rise in AD within the Hispanic population in the United States over the next few decades is expected to be the most significant among all ethnic groups. The Hispanic population faces unique dementia risks due to cultural factors like language barriers, lower education, and limited healthcare access. Higher rates of conditions such as diabetes and cardiovascular disease further elevate dementia risk. Family dynamics and caregiving responsibilities also differ, affecting dementia management within Hispanic households. Addressing these distinct challenges requires culturally sensitive approaches to diagnosis, treatment, and support for Hispanic individuals and their family's facing dementia. With AD and other dementia becoming more prevalent, this article will attempt to expand upon the status of caregivers concerning their economic, health, and cultural statuses. We will attempt to focus on the Hispanic caregivers that live in Texas and more specifically, West Texas due to the lack of current literature that applies to this area of Texas. Lastly, we discuss the ramifications of a multitude of factors that affect caregivers in Texas and attempt to provide tools that can be readily available for Hispanics and others alike.

Serotonin acts through multiple cellular targets during an olfactory critical period.

Serotonin (5-HT) is known to modulate early development during critical periods when experience drives heightened levels of plasticity in neurons. Here, we take advantage of the genetically tractable olfactory system of Drosophila to investigate how 5-HT modulates critical period plasticity in the CO2 sensing circuit of fruit flies. Our study reveals that 5HT modulation of multiple neuronal targets is necessary for experience-dependent structural changes in an odor processing circuit. The olfactory CPP is known to involve local inhibitory networks and consistent with this we found that knocking down 5-HT7 receptors in a subset of GABAergic local interneurons was sufficient to block CPP, as was knocking down GABA receptors expressed by olfactory sensory neurons (OSNs). Additionally, direct modulation of OSNs via 5-HT2B expression in the cognate OSNs sensing CO2 is also essential for CPP. Furthermore, 5-HT1B expression by serotonergic neurons in the olfactory system is also required during the critical period. Our study reveals that 5-HT modulation of multiple neuronal targets is necessary for experience-dependent structural changes in an odor processing circuit.

Treating Alzheimer's disease using nanoparticle-mediated drug delivery strategies/systems.

The administration of promising medications for the treatment of neurodegenerative disorders (NDDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) is significantly hampered by the blood-brain barrier (BBB). Nanotechnology has recently come to light as a viable strategy for overcoming this obstacle and improving drug delivery to the brain. With a focus on current developments and prospects, this review article examines the use of nanoparticles to overcome the BBB constraints to improve drug therapy for AD The potential for several nanoparticle-based approaches, such as those utilizing lipid-based, polymeric, and inorganic nanoparticles, to enhance drug transport across the BBB are highlighted. To shed insight on their involvement in aiding effective drug transport to the brain, methods of nanoparticle-mediated drug delivery, such as surface modifications, functionalization, and particular targeting ligands, are also investigated. The article also discusses the most recent findings on innovative medication formulations encapsulated within nanoparticles and the therapeutic effects they have shown in both preclinical and clinical testing. This sector has difficulties and restrictions, such as the need for increased safety, scalability, and translation to clinical applications. However, the major emphasis of this review aims to provide insight and contribute to the knowledge of how nanotechnology can potentially revolutionize the worldwide treatment of NDDs, particularly AD, to enhance clinical outcomes.

Languaging psychopathology: neurobiology and metaphor.

Explanatory models of the mind inform our working assumptions about mental illness with direct implications for clinical practice. Neurobiological models assert that the mind can be understood in terms of genetics, chemistry, and neuronal circuits. Growing evidence suggests that clinical deployment of neurobiological models of illness may have unintended adverse effects on patient attitudes, public perception, provider empathy, and the effectiveness of psychiatric treatment. New approaches are needed to find a better language for describing (let alone explaining) the experience of mental illness. To address this gap, we draw upon interdisciplinary sources and semiotic theory to characterize the role of metaphor in the conceptualization and communication of psychopathology. We examine the metaphors recruited by contemporary neurobiological models and metaphor's role in facilitating descriptive clarity or evocative creativity, depending on intention and context. These multiple roles reveal the implications of metaphorical reasoning in clinical practice, including cognitive flexibility, personalized communication, and uncertainty tolerance. With this analysis, we propose a clinical approach that embraces the meta-process of ongoing novel metaphor generation and co-elaboration, or languaging metaphors of psychopathology. Our goal is to bring attention to the value of employing ever-evolving, shapeable metaphorical depictions of psychiatric illness: metaphors that enable a capacity for change in individuals and society, reduce stigma, and nurture recovery.

An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study.

BACKGROUND: Predicting the likelihood of success of weight loss interventions using machine learning (ML) models may enhance intervention effectiveness by enabling timely and dynamic modification of intervention components for nonresponders to treatment. However, a lack of understanding and trust in these ML models impacts adoption among weight management experts. Recent advances in the field of explainable artificial intelligence enable the interpretation of ML models, yet it is unknown whether they enhance model understanding, trust, and adoption among weight management experts. OBJECTIVE: This study aimed to build and evaluate an ML model that can predict 6-month weight loss success (ie, ≥7% weight loss) from 5 engagement and diet-related features collected over the initial 2 weeks of an intervention, to assess whether providing ML-based explanations increases weight management experts' agreement with ML model predictions, and to inform factors that influence the understanding and trust of ML models to advance explainability in early prediction of weight loss among weight management experts. METHODS: We trained an ML model using the random forest (RF) algorithm and data from a 6-month weight loss intervention (N=419). We leveraged findings from existing explainability metrics to develop Prime Implicant Maintenance of Outcome (PRIMO), an interactive tool to understand predictions made by the RF model. We asked 14 weight management experts to predict hypothetical participants' weight loss success before and after using PRIMO. We compared PRIMO with 2 other explainability methods, one based on feature ranking and the other based on conditional probability. We used generalized linear mixed-effects models to evaluate participants' agreement with ML predictions and conducted likelihood ratio tests to examine the relationship between explainability methods and outcomes for nested models. We conducted guided interviews and thematic analysis to study the impact of our tool on experts' understanding and trust in the model. RESULTS: Our RF model had 81% accuracy in the early prediction of weight loss success. Weight management experts were significantly more likely to agree with the model when using PRIMO (χ2=7.9; P=.02) compared with the other 2 methods with odds ratios of 2.52 (95% CI 0.91-7.69) and 3.95 (95% CI 1.50-11.76). From our study, we inferred that our software not only influenced experts' understanding and trust but also impacted decision-making. Several themes were identified through interviews: preference for multiple explanation types, need to visualize uncertainty in explanations provided by PRIMO, and need for model performance metrics on similar participant test instances. CONCLUSIONS: Our results show the potential for weight management experts to agree with the ML-based early prediction of success in weight loss treatment programs, enabling timely and dynamic modification of intervention components to enhance intervention effectiveness. Our findings provide methods for advancing the understandability and trust of ML models among weight management experts.

Optical Coherence Tomography Angiography Characteristics of Polypoidal Lesions in Caucasians.

Purpose: The aim of the study is to analyze the swept source-optical coherence tomography angiography (SS-OCTA) characteristics of polypoidal lesions in Caucasian patients. Methods: In this retrospective observational case series, 43 polypoidal lesions in 32 eyes of 32 patients were diagnosed using indocyanine green angiography (ICGA) and compared to SS-OCTA at a tertiary medical retina center (Clinic Landstraße, Vienna Healthcare Group, Austria) between June 2017 and March 2020. Vascularity was identified by color-coded B-scan SS-OCTA while morphology was described as revealed by en face SS-OCTA after alignment with ICGA-confirmed findings. Results: In total, SS-OCTA detected all polypoidal lesions, as identified by ICGA. On B-scan SS-OCTA, circumscribed flow was detected in 33 (76.7%) polypoidal lesions and diffuse flow in 10 (23.3%) lesions. On en face SS-OCTA, polypoidal lesions appeared morphologically as 19 tangled vessel balls (44.2%), 6 tangled vessel balls next to dilated vessels (13.9%), 8 vascular dilatations (18.6%), and 8 ill-defined vascular networks (18.6%), leaving 2 lesions (4.6%) undetected. Circumscribed flow was significantly associated with tangled vessel balls (p = 0.005). Conclusion: This study highlights the importance of a multimodal imaging approach, including SS-OCTA, for the evaluation of polypoidal lesions. Our findings suggest a morphological heterogeneity of vascular patterns in Caucasian patients with polypoidal lesions, as pictured by SS-OCTA.

Toward a Bio-Organon: A model of interdependence between energy, information and knowledge in living systems.

What is an organism? In the absence of a fundamental biological definition, what constitutes a living organism, whether it is a unicellular microbe, a multicellular being or a multi-organismal society, remains an open question. New models of living systems are needed to address the scale of this question, with implications for the relationship between humanity and planetary ecology. Here we develop a generic model of an organism that can be applied across multiple scales and through major evolutionary transitions to form a toolkit, or bio-organon, for theoretical studies of planetary-wide physiology. The tool identifies the following core organismic principles that cut across spatial scale: (1) evolvability through self-knowledge, (2) entanglement between energy and information, and (3) extrasomatic "technology" to scaffold increases in spatial scale. Living systems are generally defined by their ability to self-sustain against entropic forces of degradation. Life "knows" how to survive from the inside, not from its genetic code alone, but by utilizing this code through dynamically embodied and functionally specialized flows of information and energy. That is, entangled metabolic and communication networks bring encoded knowledge to life in order to sustain life. However, knowledge is itself evolved and is evolving. The functional coupling between knowledge, energy and information has ancient origins, enabling the original, cellular "biotechnology," and cumulative evolutionary creativity in biochemical products and forms. Cellular biotechnology also enabled the nesting of specialized cells into multicellular organisms. This nested organismal hierarchy can be extended further, suggesting that an organism of organisms, or a human "superorganism," is not only possible, but in keeping with evolutionary trends.

Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI.

The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.

The Scanner as the Stimulus: Deficient Gamma-BOLD Coupling in Schizophrenia at Rest.

Functional magnetic resonance imaging (fMRI) scanners are unavoidably loud and uncomfortable experimental tools that are necessary for schizophrenia (SZ) neuroscience research. The validity of fMRI paradigms might be undermined by well-known sensory processing abnormalities in SZ that could exert distinct effects on neural activity in the presence of scanner background sound. Given the ubiquity of resting-state fMRI (rs-fMRI) paradigms in SZ research, elucidating the relationship between neural, hemodynamic, and sensory processing deficits during scanning is necessary to refine the construct validity of the MR neuroimaging environment. We recorded simultaneous electroencephalography (EEG)-fMRI at rest in people with SZ (n = 57) and healthy control participants without a psychiatric diagnosis (n = 46) and identified gamma EEG activity in the same frequency range as the background sounds emitted from our scanner during a resting-state sequence. In participants with SZ, gamma coupling to the hemodynamic signal was reduced in bilateral auditory regions of the superior temporal gyri. Impaired gamma-hemodynamic coupling was associated with sensory gating deficits and worse symptom severity. Fundamental sensory-neural processing deficits in SZ are present at rest when considering scanner background sound as a "stimulus." This finding may impact the interpretation of rs-fMRI activity in studies of people with SZ. Future neuroimaging research in SZ might consider background sound as a confounding variable, potentially related to fluctuations in neural excitability and arousal.

Early ß-hCG levels predict live birth after single embryo transfer.

PURPOSE: Specific serum beta human chorionic gonadotropin (ß-hCG) parameters that can predict live birth after an embryo transfer have yet to be defined. METHODS: We performed a retrospective cohort study of 1,028 patients with a detectable ß-hCG who underwent a single embryo transfer between 2002 and 2019 at a large academic center. Two ß-hCG parameters were examined in relation to live birth: 1) "doubling" defined as ß-hCG doubling over 48 h and 2) "reaching 100" defined as a ß-hCG ≥ 100 mIU/mL by 15 days after oocyte retrieval (AOR). RESULTS: One thousand three hundred forty cycles involving a single embryo were analyzed. Two thirds were frozen embryos and 86% were blastocyst transfers. Preimplantation genetic testing was performed in almost 30% of cycles. When ß-hCG levels "doubled," a live birth occurred in 80.7% of cycles and when ß-hCG levels "reached 100" by 15 days AOR, live birth occurred in 81.6% of cycles. When ß-hCG levels both doubled and reached 100 by 15 days, AOR 85.4% cycles resulted in live birth. A multiple logistic regression model to control for patient and cycle level factors revealed a live birth odds ratio (OR) of 8.0 (95% CI 5.7-11.1) when ß-hCG "doubled" and an OR of 21.2 (95% CI 14.3-31.5) when ß-hCG "reached 100." When both these latter parameters were met, the OR was 12.5 (95% CI 8.9-17.8). CONCLUSION: ß-hCG parameters of "doubling" and "reaching 100" by 15 days AOR are robust predictors of live birth and can aid in patient counseling regarding pregnancy outcomes soon after single embryo transfer.

Development and Implementation of a Chief Resident for Research Role in a Psychiatry Residency Training Program.

Psychiatry residency programs with robust research training can prepare physician-scientists to make contributions that advance the mental health field. Our psychiatry residency developed a chief resident for research position to help provide mentorship, community building, and advising around scholarly activities for residents. We present the process of implementing this new position in our residency to offer a model for engaging psychiatry residents in research.

Aperiodic measures of neural excitability are associated with anticorrelated hemodynamic networks at rest: A combined EEG-fMRI study.

The hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.

The Effect of Treatment Discontinuation During the COVID-19 Pandemic on Visual Acuity in Exudative Neovascular Age-Related Macular Degeneration: 1-Year Results.

INTRODUCTION: To evaluate the effect of a 9-week treatment deferral due to healthcare restrictions caused by Austria's first governmental lockdown associated with the coronavirus disease 2019 (COVID-19) pandemic on visual acuity (VA) in eyes compromised by exudative neovascular age-related macular degeneration (nAMD) after 1 year. METHODS: Retrospective data collection of 98 eyes (98 patients) with a treatment discontinuation at a tertiary eye care center (Clinic Landstraße, Vienna Healthcare Group, Austria) between March 16 and May 4, 2020. Prior to the lockdown, patients received multiple intravitreal injections (IVI) of anti-vascular endothelial growth factor with a personalized treatment interval for 3 years on average and at least three IVI after the lockdown. RESULTS: When the treatment interval doubled to 117.6 ± 31.4 days in spring 2020, patients lost 2.2 ± 4.6 ETDRS letters (p = 0.002) on average before reinitiating therapy. In total, 4.1 ± 8.1 letters (p < 0.0001) were lost despite continuous individual re-treatment over the course of the next year. In a univariate analysis, the extended interval time remained statistically significant (p < 0.0001), indicating a larger VA reduction within intervals with increasing interval time in days. CONCLUSION: The short-term treatment interruption had a persistent negative impact on the VA course of eyes under therapy after 1 year. Continuous therapy independent of the underlying treatment regimen remains of utmost importance in exudative nAMD. Our data should create awareness to regulators regarding future decisions despite the global pandemic.

Age-related macular degeneration (AMD) is the leading cause of legal blindness in developed countries. Wet AMD refers to the existence of new vessel growth in the macular, the part of the retina with the highest concentration of photoreceptors and hence the best visual acuity. The gold standard therapy of wet AMD consists of repeated injections of an antibody against new vessel formation into the eye to stabilize the disease. The sudden break of a treatment regimen for an individual person has never been investigated as it is ethically not acceptable. The coronavirus disease 2019 (COVID-19) pandemic and its associated lockdown led to an emerging situation in spring, 2020. We were forced by governmental restrictions to minimize contact with the most vulnerable patient cohort­the elderly. As an initial consequence, the Medical Retina Unit of Department of Ophthalmology (Clinic Landstraße, Vienna Healthcare Group, Austria) postponed appointments of patients with only one eye afflicted by wet AMD. This study examined the effect of a short-term treatment deferral caused by the first national COVID-19 lockdown in eyes of patients with ongoing therapy of wet AMD in Austria. The break led to a persistent visual loss despite re-treatment, which was still evident after 1 year. Our findings provide further support for an adequate and permanent therapy of wet AMD and regard intravitreal injections as urgent standard of care. It should be taken into consideration by authorities in future pandemic planning.

Therapeutic plasma exchange to mitigate flunixin meglumine overdose in a cria.

OBJECTIVE: To describe the use of therapeutic plasma exchange (TPE) in the treatment of flunixin meglumine overdose in a cria. CASE SUMMARY: A 3-day-old alpaca cria was diagnosed with ureteral obstruction and agenesis resulting in severe bilateral hydronephrosis. During hospitalization, the cria inadvertently received a flunixin meglumine overdose of >65 mg/kg. Here, we report the use of lipid emulsion and TPE to mitigate flunixin meglumine toxicosis. TPE appeared to prevent any flunixin-induced kidney or gastrointestinal injury, even in a patient with congenital defects of the urinary tract. NEW INFORMATION PROVIDED: This is the first report of the use of TPE in a cria.

The key to egress? Babesia bovis perforin-like protein 1 (PLP1) with hemolytic capacity is required for blood stage replication and is involved in the exit of the parasite from the host cell.

Bovine babesiosis is a tick-borne disease caused by apicomplexan parasites of the Babesia genus that represents a major constraint to livestock production worldwide. Currently available vaccines are based on live parasites which have archetypal limitations. Our goal is to identify candidate antigens so that new and effective vaccines against Babesia may be developed. The perforin-like protein (PLP) family has been identified as a key player in cell traversal and egress in related apicomplexans and it was also identified in Babesia, but its function in this parasite remains unknown. The aim of this work was to define the PLP family in Babesia and functionally characterize PLP1, a representative member of the family in Babesia bovis. Bioinformatic analyses demonstrate a variable number of plp genes (four to eight) in the genomes of six different Babesia spp. and conservation of the family members at the secondary and tertiary structure levels. We demonstrate here that Babesia PLPs contain the critical domains present in other apicomplexan PLPs to display the lytic capacity. We then focused on the functional characterization of PLP1 of B. bovis, both in vitro and in vivo. PLP1 is expressed and exposed to the host immune system during infection and has high hemolytic capacity under a wide range of conditions in vitro. A B. bovis plp1 knockout line displayed a decreased growth rate in vitro compared with the wild type strain and a peculiar phenotype consisting of multiple parasites within a single red blood cell, although at low frequency. This phenotype suggests that the lack of PLP1 has a negative impact on the mechanism of egression of the parasite and, therefore, on its capacity to proliferate. It is possible that PLP1 is associated with other proteins in the processes of invasion and egress, which were found to have redundant mechanisms in related apicomplexans. Future work will be focused on unravelling the network of proteins involved in these essential parasite functions.

Visual cortical plasticity and the risk for psychosis: An interim analysis of the North American Prodrome Longitudinal Study.

BACKGROUND: Adolescence/early adulthood coincides with accelerated pruning of cortical synapses and the onset of schizophrenia. Cortical gray matter reduction and dysconnectivity in schizophrenia are hypothesized to result from impaired synaptic plasticity mechanisms, including long-term potentiation (LTP), since deficient LTP may result in too many weak synapses that are then subject to over-pruning. Deficient plasticity has already been observed in schizophrenia. Here, we assessed whether such deficits are present in the psychosis risk syndrome (PRS), particularly those who subsequently convert to full psychosis. METHODS: An interim analysis was performed on a sub-sample from the NAPLS-3 study, including 46 healthy controls (HC) and 246 PRS participants. All participants performed an LTP-like visual cortical plasticity paradigm involving assessment of visual evoked potentials (VEPs) elicited by vertical and horizontal line gratings before and after high frequency ("tetanizing") visual stimulation with one of the gratings to induce "input-specific" neuroplasticity (i.e., VEP changes specific to the tetanized stimulus). Non-parametric, cluster-based permutation testing was used to identify electrodes and timepoints that demonstrated input-specific plasticity effects. RESULTS: Input-specific pre-post VEP changes (i.e., increased negative voltage) were found in a single spatio-temporal cluster covering multiple occipital electrodes in a 126-223 ms time window. This plasticity effect was deficient in PRS individuals who subsequently converted to psychosis, relative to PRS non-converters and HC. CONCLUSIONS: Input-specific LTP-like visual plasticity can be measured from VEPs in adolescents and young adults. Interim analyses suggest that deficient visual cortical plasticity is evident in those PRS individuals at greatest risk for transition to psychosis.

Painful gynecologic and obstetric complications of female genital mutilation/cutting: A systematic review and meta-analysis.

BACKGROUND: The health complications experienced by women having undergone female genital mutilation/cutting (FGM/C) are a source of growing concern to healthcare workers globally as forced displacement and migration from countries with high rates of this practice increases. In this systematic review and meta-analysis, we investigate the association between FGM/C and painful gynecologic and obstetric complications in women affected by the practice. METHODS AND FINDINGS: We performed a comprehensive literature search from inception to December 19, 2019 of Ovid MEDLINE, Ovid EMBASE, The Cochrane Library (Wiley), and POPLINE (prior to its retirement) for studies mentioning FGM/C. Two reviewers independently screened studies reporting prevalences of painful gynecologic and obstetric sequelae resulting from FGM/C. Random effects models were used to estimate pooled odds ratios (ORs) for outcomes obtained from cross-sectional, cohort, and case-control designs. Subgroup analysis was performed to assess and control for effect differences introduced by study design. Validated appraisal tools were utilized to assess quality and risk of bias. Our study was registered with PROSPERO. Two reviewers independently screened 6,666 abstracts. Of 559 full-text studies assessed for eligibility, 116 met eligibility criteria, which included studies describing the incidence or prevalence of painful sequelae associated with FGM/C. Pooled analyses after adjustment for study design found that FGM/C was associated with dyspareunia (6,283 FGM/C and 3,382 non-FGM/C participants; pooled OR: 2.47; 95% confidence interval [CI]: 1.45-4.21; I2: 79%; p-value < 0.01), perineal tears (4,898 FGM/C and 4,229 non-FGM/C participants; pooled OR: 2.63; 95% CI: 1.35-5.11; I2: 67%; p-value = 0.01), dysuria (3,686 FGM/C and 3,482 non-FGM/C participants; pooled OR: 1.43; 95% CI: 1.17-1.75; I2: 0%; p-value = 0.01), episiotomy (29,341 FGM/C and 39,260 non-FGM/C participants; pooled OR: 1.89; 95% CI: 1.26-2.82; I2: 96%; p-value < 0.01), and prolonged labor (7,516 FGM/C and 8,060 non-FGM/C participants; pooled OR: 2.04; 95% CI: 1.27-3.28; I2: 90%; p-value < 0.01). There was insufficient evidence to conclude that there was an association between FGM/C and dysmenorrhea (7,349 FGM/C and 4,411 non-FGM/C participants; pooled OR: 1.66; 95% CI: 0.97-2.84; I2: 86%; p-value = 0.06), urinary tract infection (4,493 FGM/C and 3,776 non-FGM/C participants; pooled OR: 2.11; 95% CI: 0.80-5.54; I2: 90%; p-value = 0.10), instrumental delivery (5,176 FGM/C and 31,923 non-FGM/C participants; pooled OR: 1.18; 95% CI: 0.78-1.79; I2: 63%; p-value = 0.40), or cesarean delivery (34,693 FGM/C and 46,013 non-FGM/C participants; pooled OR: 1.51; 95% CI: 0.99-2.30; I2: 96%; p-value = 0.05). Studies generally met quality assurance criteria. Limitations of this study include the largely suboptimal quality of studies. CONCLUSIONS: In this study, we observed that specific painful outcomes are significantly more common in participants with FGM/C. Women who underwent FGM/C were around twice as likely as non-FGM/C women to experience dyspareunia, perineal tears, prolonged labor, and episiotomy. These data indicate that providers must familiarize themselves with the unique health consequences of FGM/C, including accurate diagnosis, pain management, and obstetric planning. REVIEW PROTOCOL REGISTRATION: The review protocol registration in PROSPERO is CRD42018115848.