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Background: In recent years, legislation targeting the sexual and gender minority (SGM) community has been passed at an increasingly alarming rate, affecting access to safe and effective gender-affirming care and forcing many SGM patients, including those with inflammatory bowel disease (IBD), to withhold their identities and health concerns. Additionally, SGM patients with IBD may have unique health considerations that have not yet been well-studied Objective: This article aims to explore the intersection of IBD and sexual health in patients who identify as SGM and to identify limitations for gastroenterologists in caring for SGM patients. The article also aims to provide suggestions for improvement in SGM-competent care within gastroenterology Methods: A thorough literature review was conducted regarding sexual health and the SGM community with IBD. This included a review of surgical considerations in SGM patients, sexually transmitted infections (STIs) and prevention, and sexual dysfunction Results: Overall, little is known about the impact of IBD on patients who identify as sexual and gender minorities. Surgery, medications, and STIs continue to be a concern in the SGM community with IBD and these areas represent opportunities to improve SGM-competent IBD care. Additionally, implementation of an SGM-focused curriculum is urgently needed in medical education to improve provider knowledge and care for this unique group of patients Conclusions: Patients with IBD who identify as SGM experience challenges that are not well described in prior literature. More research is needed and is actively being pursued to guide provider awareness and improve sexual health for this patient population. [ABSTRACT FROM AUTHOR]

Purpose: Stereotactic body radiation therapy (SBRT) is increasingly used for prostate cancer, but has morbidity as both the bladder and rectum are radiated during treatment. Our goal was to document and compare lower urinary tract symptoms (LUTS) among men who underwent SBRT with and without SpaceOAR hydrogel (Augmenix, Inc., Bedford, MA). Methods: We performed a retrospective analysis of 87 men (50 SpaceOAR and 37 non-SpaceOAR) who underwent SBRT. Primary outcomes were patient reported symptoms during radiation therapy, pharmacotherapy usage, and urologic and bowel survey scores up to 6-months post-SBRT. Results: 78% of men were on α-inhibitors at the end of SBRT, an increase from 27.6% baseline usage (p < 0.001). Post-SBRT urinary frequency was more common in the non-SpaceOAR group versus the SpaceOAR group (68% versus 38%, p = 0.006), as was nocturia (35% vs. 8%, p = 0.002). Acute gastrointestinal symptoms did not differ. 58.8% of men were on α-inhibitors at 6-months of follow-up post-SBRT, an increase from 27.6% baseline usage (p < 0.001). Importantly, there was a difference of α-inhibitor use between non-SpaceOAR and SpaceOAR groups at the end of SBRT and at 1.5-, 3-, and 6-months follow up (86% vs. 53% [p = 0.002], 83% vs. 53% [p = 0.005], 72% vs. 49% [p = 0.038], respectively). Conclusion: LUTS after SBRT remains a significant problem for men undergoing treatment for prostate cancer. LUTS affects men during and up to 6-months following SBRT. Owing to these increased LUTS, preemptive minimally invasive solutions and their mechanisms of protection, including the SpaceOAR, should be further investigated. [ABSTRACT FROM AUTHOR]

Background: Knowing the true infected and symptomatic case fatality ratios (IFR and CFR) for COVID-19 is of high importance for epidemiological model projections. Early in the pandemic many locations had limited testing and reporting, so that standard methods for determining IFR and CFR required large adjustments for missed cases. We present an alternate approach, based on results from the countries at the time that had a high test to positive case ratio to estimate symptomatic CFR. Methods: We calculated age specific (0–69, 70–79, 80+ years old) time corrected crude symptomatic CFR values from 7 countries using two independent time to fatality correction methods. Data was obtained through May 7, 2020. We applied linear regression to determine whether the mean of these coefficients had converged to the true symptomatic CFR values. We then tested these coefficients against values derived in later studies as well as a large random serological study in NYC at that time. Results: The age dependent symptomatic CFR values accurately predicted the percentage of the population infected as reported by two random testing studies in NYC. They also were in good agreement with later studies that estimated age specific IFR and CFR values from serological studies and more extensive data sets available later in the pandemic. Conclusions: We found that for regions with extensive testing it is possible to get early accurate symptomatic CFR coefficients. These values, in combination with an estimate of the age dependence of infection, allows symptomatic CFR values and percentage of the population that is infected to be determined in similar regions with limited testing. [ABSTRACT FROM AUTHOR]

Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Unspecified functional bowel disorder (FBD-U) is a Rome IV diagnosis of exclusion and occurs when patients report bowel symptoms but do not meet the criteria for other functional bowel disorders (FBD; irritable bowel syndrome [IBS], functional constipation [FC], functional diarrhea [FDr], or functional bloating). Previous research suggests that FBD-U is as/more common than IBS. METHODS: One thousand five hundred one patients at a single-center tertiary care center completed an electronic survey. Study questionnaires included Rome IV Diagnostic Questionnaires, anxiety, depression, sleep, health care utilization, and bowel symptom severity measures. RESULTS: Eight hundred thirteen patients met Rome IV criteria for a FBD and 194 patients (13.1%) met criteria for FBD-U, representing the second most common FBD after IBS. Severity of abdominal pain, constipation, and diarrhea were lower in FBD-U compared with other FBD, whereas health care utilization was similar among the groups. Scores on measures of anxiety, depression, and sleep disturbances were similar in FBD-U compared with FC and FDr but were less severe than IBS. Between 25% and 50% of patients with FBD-U did not meet Rome IV criteria for other FBD due to timing of onset of the target symptom (e.g., constipation for FC, diarrhea for FDr, and abdominal pain for IBS). DISCUSSION: FBD-U, by Rome IV criteria, is highly prevalent in clinical settings. These patients are not represented in mechanistic studies or clinical trials for not having met Rome IV criteria for other FBD. Making future Rome criteria less stringent would minimize the number fulfilling criteria for FBD-U and maximize the true representation of FBD in clinical trials. [ABSTRACT FROM AUTHOR]

The differential diagnosis of parkinsonian syndromes can be challenging, particularly in early disease stages. However, prognosis and therapeutic regimes are not alike in Parkinson disease and atypical parkinsonism, and thus a correct diagnosis at the earliest possible stage is desirable. Over the past two decades,magnetic resonance imaging and radiotracer-based imaging techniques have proven to be helpful tools to enhance the accuracy of clinical diagnosis in these disorders. Here, we review recent advances in neuroimaging for the differential diagnosis of parkinsonian syndromes. [ABSTRACT FROM AUTHOR]

Over the past 2 decades, functional imaging techniques have become commonplace in the study of brain disease. Nevertheless, very few validated analytical methods have been developed specifically to identify and measure systems-level abnormalities in living patients. Network approaches are particularly relevant for translational research in the neurodegenerative disorders, which often involve stereotyped abnormalities in brain organization. In recent years, spatial covariance mapping, a multivariate analytical tool applied mainly to metabolic images acquired in the resting state, has provided a useful means of objectively assessing brain disorders at the network level. By quantifying network activity in individual subjects on a scan-by-scan basis, this technique makes it possible to objectively assess disease progression and the response to treatment on a system-wide basis. To illustrate the utility of network imaging in neurological research, we review recent applications of this approach in the study of Parkinson disease and related movement disorders. Novel uses of the technique are discussed, including the prediction of cognitive responses to dopaminergic therapy, evaluation of the effects of placebo treatment on network activity, assessment of preclinical disease progression, and the use of automated pattern-based algorithms to enhance diagnostic accuracy. ANN NEUROL 2012;72:635-647 [ABSTRACT FROM AUTHOR]

Abstract: Clinical manifestations of movement disorders, such as Parkinson''s disease (PD) and dystonia, arise from neurophysiological changes within the cortico-striato-pallidothalamocortical (CSPTC) and cerebello-thalamo-cortical (CbTC) circuits. Neuroimaging techniques that probe connectivity within these circuits can be used to understand how these disorders develop as well as identify potential targets for medical and surgical therapies. Indeed, network analysis of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has identified abnormal metabolic networks associated with the cardinal motor symptoms of PD, such as akinesia and tremor, as well as PD-related cognitive dysfunction. More recent task-based and resting state functional magnetic resonance imaging studies have reproduced several of the altered connectivity patterns identified in these abnormal PD-related networks. A similar network analysis approach in dystonia revealed abnormal disease related metabolic patterns in both manifesting and non-manifesting carriers of dystonia mutations. Other multimodal imaging approaches using magnetic resonance diffusion tensor imaging in patients with primary genetic dystonia suggest abnormal connectivity within the CbTC circuits mediate the clinical manifestations of this inherited neurodevelopmental disorder. Ongoing developments in functional imaging and future studies in early patients are likely to enhance our understanding of these movement disorders and guide novel targets for future therapies. [Copyright &y& Elsevier]

Abstract: Consistent functional brain abnormalities in Parkinson''s disease (PD) are difficult to pinpoint because differences from the normal state are often subtle. In this regard, the application of multivariate methods of analysis has been successful but not devoid of misinterpretation and controversy. The Scaled Subprofile Model (SSM), a principal components analysis (PCA)-based spatial covariance method, has yielded critical information regarding the characteristic abnormalities of functional brain organization that underlie PD and other neurodegenerative disorders. However, the relevance of disease-related spatial covariance patterns (metabolic brain networks) and the most effective methods for their derivation has been a subject of debate. We address these issues here and discuss the inherent advantages of proper application as well as the effects of the misapplication of this methodology. We show that ratio pre-normalization using the mean global metabolic rate (GMR) or regional values from a “reference” brain region (e.g. cerebellum) that may be required in univariate analytical approaches is obviated in SSM. We discuss deviations of the methodology that may yield erroneous or confounding factors. [Copyright &y& Elsevier]

Recent studies have focused on understanding the neural mechanisms underlying the emergence of clinical signs and symptoms in early stage Huntington disease (HD). Although cell-based assays have focused on cell autonomous effects of mutant huntingtin, animal HD models have revealed alterations in the function of neuronal networks, particularly those linking the cerebral cortex and striatum. These findings are complemented by metabolic imaging studies of disease progression in premanifest subjects. Quantifying metabolic progression at the systems level may identify network biomarkers to aid in the objective assessment of new disease-modifying therapies and identify new regions that merit mechanistic study in HD models. [ABSTRACT FROM AUTHOR]

Abstract: Primary torsion dystonia (PTD) is a chronic movement disorder manifested clinically by focal or generalized sustained muscle contractions, postures, and/or involuntary movements. The most common inherited form of PTD is associated with the DYT1 mutation on chromosome 9q34. A less frequent form is linked to the DYT6 locus on chromosome 8q21-22. Both forms are autosomal dominant with incomplete (∼30%) clinical penetrance. Extensive functional and microstructural imaging with positron emission tomography (PET) and diffusion tensor MRI (DTI) has been performed on manifesting and non-manifesting carriers of these mutations. The results are consistent with the view of PTD as a neurodevelopmental circuit disorder involving cortico-striatal-pallido-thalamocortical (CSPTC) and related cerebellar–thalamo-cortical pathways. Studies of resting regional metabolism have revealed consistent abnormalities in PTD involving multiple interconnected elements of these circuits. In gene carriers, changes in specific subsets of these regions have been found to relate to genotype, phenotype, or both. For instance, genotypic abnormalities in striatal metabolic activity parallel previously reported reductions in local D2 receptor availability. Likewise, we have identified a unique penetrance-related metabolic network characterized by increases in the pre–supplementary motor area (SMA) and parietal association areas, associated with relative reductions in the cerebellum, brainstem, and ventral thalamus. Interestingly, metabolic activity in the hypermetabolic areas has recently been found to be modified by the penetrance regulating D216H polymorphism. The DTI data raise the possibility that metabolic abnormalities in mutation carriers reflect adaptive responses to developmental abnormalities in the intrinsic connectivity of the motor pathways. Moreover, findings of increased motor activation responses in these subjects are compatible with the reductions in cortical inhibition that have been observed in this disorder. Future research will focus on clarifying the relationship of these changes to clinical penetrance in dystonia mutation carriers, and the reversibility of disease-related functional abnormalities by treatment. [Copyright &y& Elsevier]

Network analysis of functional brain imaging data is an innovative approach to study circuit abnormalities in neurodegenerative diseases. In Parkinson''s disease, spatial covariance analysis of resting-state metabolic images has identified specific regional patterns associated with motor and cognitive symptoms. With functional imaging, these metabolic networks have recently been used to measure system-related progression and to evaluate novel treatment strategies. Network analysis is also being used to characterize specific functional biomarkers for Huntington''s disease and Alzheimer''s disease. These networks have been particularly helpful in uncovering compensatory mechanisms in genetically at-risk individuals. Ongoing developments in network applications are likely to enhance the role of functional imaging in the investigation of neurodegenerative disorders. [Copyright &y& Elsevier]

Abstract: Functional brain networks provide a set of useful biomarkers for the assessment of movement disorders such as Parkinson''s disease (PD). Spatial covariance analysis of imaging data from PD patients has led to the identification of abnormal metabolic patterns associated with the motor and cognitive features of this disease. Measurements of pattern expression have been used for diagnosis, assessment of rates of disease progression, and objective evaluation of the efficacy of therapeutic interventions. For instance, the recent identification of new disease-specific patterns for Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) has improved diagnostic accuracy in patients with parkinsonian syndromes. Further, disease-related networks have been found to be modulated by novel treatment strategies such as gene therapy. Finally, the application of network analysis to the study of inherited movement disorders such as Huntington''s disease can aid in the assessment of disease-modifying therapies in pre-symptomatic gene mutation carriers. [Copyright &y& Elsevier]

Abstract: In recent years a number of multivariate approaches have been introduced to map neural systems in health and disease. In this review, we focus on spatial covariance methods applied to functional imaging data to identify patterns of regional activity associated with behavior. In the rest state, this form of network analysis can be used to detect abnormal topographies reflecting regional changes in distributed neural systems. In activation experiments, this approach can be used to quantify network–performance relationships in normal and disease cohorts. Functional changes in the relevant neural systems are likely to underlie the behavioral abnormalities observed in a variety of disease and treatment conditions. [Copyright &y& Elsevier]

Recent advances in gene transfer technology have led to promising new therapies for neurodegenerative disorders. This article will review methods of gene transfer therapy and applications of these techniques to both genetic and sporadic neurodegenerative illnesses. The article will focus on Parkinson's disease, Huntington's disease, and Alzheimer's disease. Several promising gene therapy approaches to these diseases are being pursued both in animal models and in early human trials. Initial safety-tolerability results from these trials appear promising. It is therefore likely that the number of human trials of gene therapy for neurodegenerative disorders will increase over the coming years. © 2007 Movement Disorder Society [ABSTRACT FROM AUTHOR]

Abstract: This study aimed to investigate cross-sectional and longitudinal changes of regional cerebral blood flow (rCBF) in preclinical dementia using single photon emission computed tomography (SPECT). SPECT and cognitive function were investigated in 39 mild cognitive impairment (MCI) subjects and 20 age-matched controls. All subjects were followed longitudinally 19 months on average, 16 MCI subjects progressed to Alzheimer''s disease (AD), who were retrospectively defined as progressive mild cognitive impairment (PMCI) at baseline and 23 MCI subjects remained stable and were defined as stable mild cognitive impairment (SMCI) at baseline. SPECT was performed both at the initial investigation and at follow-up. Image data were analyzed using multivariate analysis, SPM and volume of interest (VOI)-based analysis. Significant covariate patterns were derived, which differentiate among PMCI, SMCI and controls at baseline as well as describe the longitudinal progression of PMCI. The combined SPECT and neuropsychology increased the diagnostic accuracy of PMCI at baseline. SPECT and neuropsychological testing can be used objectively for both baseline diagnosis and to monitor changes in brain function during very early AD. [Copyright &y& Elsevier]

Abstract: Sequence learning, a cognitive task linked to cortico-striatal function, is impaired in Parkinson''s disease (PD). We chose this task as a behavioral paradigm to study the functional architecture of PD in treated and untreated conditions. In our studies, participants were scanned with H2 15O while performing a kinematically controlled motor sequence learning task and a matching motor baseline task. Experiments revealed that a specific sequence learning network predicts learning in normal subjects, and in independent cohorts of early and advanced PD patients. The analysis of the relationship of network activity to learning performance revealed diverging influences of dopaminergic therapy and deep brain stimulation (DBS). DBS of the internal GP and of STN increased network activity and task performance, while levodopa decreased both measures. In separate studies, we investigated the role of dopaminergic modulation on brain activation during sequence learning. In healthy subjects dopamine transporter (DAT) binding correlated with learning-related brain activation in prefrontal, premotor and cingulate cortices, and in the thalamus. By contrast, in PD most of these regional relationships were lost. Only ventral and dorsolateral prefrontal cortex activation correlated with caudate dopaminergic input. In a final set of studies, we found a significant decline in learning performance in early stage PD patients followed over the course of 2 years. Longitudinal declines in learning-related activation were found in parietal areas, while concomitant increases were localized to the left hippocampus. These observations support hypotheses on disease-stage and task-specific effects within the different cortico-striato-pallido-thalamocortical loops and the mesocortical system in PD. [Copyright &y& Elsevier]

Parkinsonism is a symptom of a number of neurodegenerative disorders in the elderly. Even though clinical criteria for various parkinsonian disorders have been developed recently, the differential diagnosis of parkinsonian disorders based on clinical symptoms remains unsatisfactory, particularly in early disease stages. Early differential diagnosis on the other hand is important as prognosis and treatment options differ substantially. Multiple system atrophy (MSA) is one of the major differential diagnoses of idiopathic Parkinson's disease (PD). Radio-tracer-based imaging methods such as positron emission tomography (PET) remain the established method for differential diagnosis of parkinsonian disorders. The following paper provides a review of different PET imaging methods for the differential diagnosis of PD and MSA patients. [ABSTRACT FROM AUTHOR]

Objective: Patients with Lewy body diseases have an increased risk of dementia, which is a significant predictor for survival. Posterior cortical hypometabolism on [18F]fluorodeoxyglucose positron emission tomography (PET) precedes the development of dementia by years. We therefore examined the prognostic value of cerebral glucose metabolism for survival. Methods: We enrolled patients diagnosed with Parkinson's disease (PD), Parkinson's disease with dementia, or dementia with Lewy bodies who underwent [18F]fluorodeoxyglucose PET. Regional cerebral metabolism of each patient was analyzed by determining the expression of the PD‐related cognitive pattern (Z‐score) and by visual PET rating. We analyzed the predictive value of PET for overall survival using Cox regression analyses (age‐ and sex‐corrected) and calculated prognostic indices for the best model. Results: Glucose metabolism was a significant predictor of survival in 259 included patients (n = 118 events; hazard ratio: 1.4 [1.2–1.6] per Z‐score; hazard ratio: 1.8 [1.5–2.2] per visual PET rating score; both p < 0.0001). Risk stratification with visual PET rating scores yielded a median survival of 4.8, 6.8, and 12.9 years for patients with severe, moderate, and mild posterior cortical hypometabolism (median survival not reached for normal cortical metabolism). Stratification into 5 groups based on the prognostic index revealed 10‐year survival rates of 94.1%, 78.3%, 34.7%, 0.0%, and 0.0%. Interpretation: Regional cerebral glucose metabolism is a significant predictor of survival in Lewy body diseases and may allow an earlier survival prediction than the clinical milestone "dementia." Thus, [18F]fluorodeoxyglucose PET may improve the basis for therapy decisions, especially for invasive therapeutic procedures like deep brain stimulation in Parkinson's disease. ANN NEUROL 2024;96:539–550 [ABSTRACT FROM AUTHOR]

Focuses on the declaration of independence in Israel. Goals of political Zionism; Constitutionality of the declaration of independence; Details on the United Nations resolution for the partition of Palestine.

Opinion. Attempts to define the tightening followed by the loosening of the hegemony of apartheid in South Africa between 1948 and 1986. What is cited as a key turning point in the history of apartheid of the 1948 to 1977 period; Background information on apartheid; Perception that the fear of possible mass insurrection appears to have been a key motive for the earlier segregation movement of the inter-war period; Reference to the Bantu Authorities Act of 1951.

Emphasizes the end of ideology in Western countries. Definition of ideology in the works of philosopher Karl Marx; Moral and cultural relativism resulting from marx;s doctrines; Influence of relativism inn to society at large; Lack of ideology on a modern democracy.

Explores the epistemological and societal consequences of psychological reductionism, using logical argumentation and sociological data. Presentation of a thought experiment; Thomas Hobbes's reductionism that entailed moral relativism; Brief history of modern psychology; More.

Objective: To evaluate the existing evidence on the efficacy of pessaries in improving quality of life when used for the treatment of pelvic organ prolapse (POP).Data Sources: We searched for the terms "pelvic organ prolapse" and "pessar/y/ies/ium or vaginal support device," and "safety or safe or outcome or complication or efficacy or effective or effectiveness" in PubMed, EMBASE, and CINAHL on March 16, 2020. A search was also performed on ClinicalTrials.gov , with no studies fitting our strict inclusion and exclusion criteria.Methods Of Study Selection: Studies that reported pretreatment and posttreatment mean scores and SDs after pessary treatment for standardized questionnaires were included. Studies performed in pediatric populations, pregnancy, and use of pessaries not for prolapse were excluded. Three reviewers independently screened studies.Tabulation, Integration, and Results: Data abstraction was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Data were pooled for meta-analysis when reported by at least three studies. The primary study outcome was change in mean pretreatment and posttreatment questionnaire scores, which included those for the PFDI-20 (Pelvic Floor Distress Inventory- Short Form 20), PFIQ-7 (Pelvic Floor Impact Questionnaire - Short Form 7), and subscale POPIQ (Pelvic Organ Prolapse Impact Questionnaire Long Form). A random-effects model was used to combine estimates and capture between-study heterogeneity using the I 2 -statistic. Eight studies including 627 patients were included for systematic review. The mean (SD) age was 63.0±12.2 years, and the majority of patients had stage III prolapse (48.1%) followed by stage II prolapse (43.2%) when reported. Although variable, the majority of studies conducted 3-month follow-up. A negative change in pretreatment and posttreatment scores was noted, signifying improvement after pessary use: PFDI-20 mean change -46.1 (95% CI -65.4 to -26.8); PFIQ-7 mean change -36.0 (95% CI -46.0 to -26.0); POPIQ-7 (Pelvic Organ Prolapse Impact Questionnaire-7) mean change -16.3 (95% CI -26.8 to -5.7). No significant heterogeneity was found.Conclusion: Based on improvements in standardized questionnaire scores, pessaries are effective treatment options for POP.Systematic Review Registration: PROSPERO, CRD42020172618. [ABSTRACT FROM AUTHOR]

In neurodegenerative disorders, a clearer understanding of the underlying aberrant networks facilitates the search for effective therapeutic targets and potential cures. [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging data of brain metabolism reflects the distribution of glucose consumption known to be directly related to neural activity. In FDG PET resting-state metabolic data, characteristic disease-related patterns have been identified in group analysis of various neurodegenerative conditions using principal component analysis of multivariate spatial covariance. Notably, among several parkinsonian syndromes, the identified Parkinson's disease-related pattern (PDRP) has been repeatedly validated as an imaging biomarker of PD in independent groups worldwide. Although the primary nodal associations of this network are known, its connectivity is not fully understood. Here, we describe a novel approach to elucidate functional principal component (PC) network connections by performing graph theoretical sparse network derivation directly within the disease relevant PC partition layer of the whole brain data rather than by searching for associations retrospectively in whole brain sparse representations. Using sparse inverse covariance estimation of each overlapping PC partition layer separately, a single coherent network is detected for each layer in contrast to more spatially modular segmentation in whole brain data analysis. Using this approach, the major nodal hubs of the PD disease network are identified and their characteristic functional pathways are clearly distinguished within the basal ganglia, midbrain and parietal areas. Network associations are further clarified using Laplacian spectral analysis of the adjacency matrices. In addition, the innate discriminative capacity of the eigenvector centrality of the graph derived networks in differentiating PD versus healthy external data provides evidence of their validity. [ABSTRACT FROM AUTHOR]

The article focuses on the practice of politics in Islam. It recalls the debate between then U.S. senator Stephen Douglas and Illinois lawyer Abraham Lincoln and how the issues they discussed are relevant to the confrontation between the liberal democracies of the West and the Islamic groups in the Middle East, with Israel at risk. An analogy made by Aristotle between politics and family is offered. It is also noted that the late Ayatollah Khomeini, the founder of the Iranian regime, propounded his theory of ruling in his book "Islam and Revolution." According to Khomeini, Islam is Allah's regime and that no more legislation is needed.

Between 1990 and 1998, 99 patients, 14 transfused and 85 non-transfused, with pathological stage I and II renal cell carcinoma underwent radical nephrectomy. The criterion of blood transfusion was hemoglobin level under 8 g/dl or decrease of hemoglobin level off 3 g/dl at the time of operation. The median follow-up was 57 months (range 17-105). Series I (transfused patients): mean age was 61 years (range 37-78), male female ratio 1.3:1, mean number of transfusion was 1.5 (range 1-3). Series II (nontransfused patients): mean age was 60 years (range 20-81), male female ratio 1.5:1. Five-year disease free survival in series I was 61 versus 93% in series II ( p <0.0042). The study support the hypothesis that perioperative blood transfusion may represent a negative prognostic factor in patients with renal cell carcinoma. [ABSTRACT FROM AUTHOR]

Background: To date, studies on positron emission tomography (PET) with 18F‐fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP‐RS). Objectives: To evaluate FDG‐PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice. Methods: This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non‐RS variants of PSP (vPSP), and 46 age‐matched healthy controls. Two state‐of‐the art methods for the interpretation of FDG‐PET were compared: visual analysis supported by voxel‐based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP‐related pattern. Results: Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false‐negative cases was 10% in the PSP‐RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false‐negative cases was 0% in the PSP‐RS subsample and 15% in the vPSP subsample. Conclusions: Visual interpretation of FDG‐PET supported by voxel‐based testing provides good accuracy for the detection of PSP‐RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP‐RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false‐positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel‐based testing of FDG‐PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to characterize a metabolic brain network associated with X‐linked dystonia‐parkinsonism (XDP). Methods: Thirty right‐handed Filipino men with XDP (age = 44.4 ± 8.5 years) and 30 XDP‐causing mutation negative healthy men from the same population (age = 37.4 ± 10.5 years) underwent [18F]‐fluorodeoxyglucose positron emission tomography. Scans were analyzed using spatial covariance mapping to identify a significant XDP‐related metabolic pattern (XDPRP). Patients were rated clinically at the time of imaging according to the XDP‐Movement Disorder Society of the Philippines (MDSP) scale. Results: We identified a significant XDPRP topography from 15 randomly selected subjects with XDP and 15 control subjects. This pattern was characterized by bilateral metabolic reductions in caudate/putamen, frontal operculum, and cingulate cortex, with relative increases in the bilateral somatosensory cortex and cerebellar vermis. Age‐corrected expression of XDPRP was significantly elevated (p < 0.0001) in XDP compared to controls in the derivation set and in the remaining 15 patients (testing set). We validated the XDPRP topography by identifying a similar pattern in the original testing set (r = 0.90, p < 0.0001; voxel‐wise correlation between both patterns). Significant correlations between XDPRP expression and clinical ratings for parkinsonism—but not dystonia—were observed in both XDP groups. Further network analysis revealed abnormalities of information transfer through the XDPRP space, with loss of normal connectivity and gain of abnormal functional connections linking network nodes with outside brain regions. Interpretation: XDP is associated with a characteristic metabolic network associated with abnormal functional connectivity among the basal ganglia, thalamus, motor regions, and cerebellum. Clinical signs may relate to faulty information transfer through the network to outside brain regions. ANN NEUROL 2023;94:684–695 [ABSTRACT FROM AUTHOR]

Little is known of the precise relationship between the expression of disease-related metabolic patterns and nigrostriatal dopaminergic dysfunction in parkinsonism. We studied 51 subjects with Parkinson’s disease (PD) (18 non-demented, 24 demented, and 9 dementia with Lewy bodies) and 127 with atypical parkinsonian syndromes (47 multiple system atrophy (MSA), 38 progressive supranuclear palsy (PSP), and 42 corticobasal syndrome (CBS)) with 18F-fluorodeoxyglucose PET to quantify the expression of previously validated disease-related patterns for PD, MSA, PSP, and CBS and 18F-fluoropropyl- β-CIT PET to quantify caudate and putamen dopamine transporter (DAT) binding. The patients in each group exhibited significant elevations in the expression of the corresponding disease-related pattern (p<0.001), relative to 16 healthy subjects. With the exception of cerebellar MSA (MSA-C), all groups displayed significant reductions in putamen DAT binding relative to healthy subjects (p<0.05). Correlations between the dopaminergic and metabolic measures were significant in PD and CBS but not in MSA and PSP. In all patient groups with the exception of MSA-C and CBS, pattern expression values and DAT binding correlated with disease duration and severity measures. The findings suggest that in these parkinsonian disorders, metabolic network expression and DAT binding provide complementary information regarding the underlying disease process. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer's disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP's performance need to be clarified. Methods: 240 2-[18F]fluoro-2-deoxy-d-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions. Results: ADRP's performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP's diagnostic performance only marginally in the range from 8 to 15 mm. ADRP's performance stayed optimal even when applied to validation images of resolution differing from the identification images. Conclusions: While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP's diagnostic performance. ADRP's performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones. [ABSTRACT FROM AUTHOR]

Background and purpose: Although sporadic Creutzfeldt–Jakob disease (sCJD) is a rare cause of dementia, it is critical to understand its functional networks as the prion protein spread throughout the brain may share similar mechanisms with other more common neurodegenerative disorders. In this study, the metabolic brain network associated with sCJD was investigated and its internal network organization was explored. Methods: We explored 2‐[18F]fluoro‐2‐deoxy‐d‐glucose positron emission tomography (FDG‐PET) brain scans of 29 sCJD patients, 56 normal controls (NCs) and 46 other dementia patients from two independent centers. sCJD‐related pattern (CJDRP) was identified in a cohort of 16 pathologically proven sCJD patients and 16 age‐matched NCs using scaled subprofile modeling/principal component analysis and was prospectively validated in an independent cohort of 13 sCJD patients and 20 NCs. The pattern's specificity was tested on other dementia patients and its clinical relevance by clinical correlations. The pattern's internal organization was further studied using graph theory methods. Results: The CJDRP was characterized by relative hypometabolism in the bilateral caudate, thalami, middle and superior frontal gyri, parietal lobe and posterior cingulum in association with relative hypermetabolism in the hippocampi, parahippocampal gyri and cerebellum. The pattern's expression significantly discriminated sCJD from NCs and other dementia patients (p < 0.005; receiver operating characteristic analysis CJD vs. NCs area under the curve [AUC] 0.90–0.96, sCJD vs. Alzheimer's disease AUC 0.78, sCJD vs. behavioral variant of frontotemporal dementia AUC 0.84). The pattern's expression significantly correlated with cognitive, functional decline and disease duration. The metabolic connectivity analysis revealed inefficient information transfer with specific network reorganization. Conclusions: The CJDRP is a robust metabolic biomarker of sCJD. Due to its excellent clinical correlations it has the potential to monitor disease in emerging disease‐modifying trials. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a movement disorder characterized by difficuly initiating movements (bradykinesia), muscular rigidity and tremor. This is associated with pathologically increased activity of the subthalamic nucleus (STN) and the downstream globu pallidus interna (GPi) leading reduced activity of pre-motor cortex (PMC). To normalize this pattern of activity, the STN was injected unilaterally with an adeno-associated virus vector expressing glutamic acid decarboxylase (AAV-GAD) in 12 patients with advanced PD, while the untreated side served as a control. GAD is the rate-limiting step in the synthesis of GABA, the major inhibitory neurotransmitter in the normal brain. Patients were divided into 3 groups of 4, and each group receiving 35μl of 1011(low), 3×1011(middle) or 1012(high-dose) packaged genomes/ml. All 12 patients have now been followed for 6 months. There have been no study-related adverse events. 2 patients had high neutralizing antibody titers prior to surgery, but there was no change in titers in any patient following treatment. Using the standard Unified Parkinson's disease rating scale (UPDRS), there was an overall significant reduction in total UPDRS at 6 months compared with preop (p<0.01); this was mostly due to a roughly 35% improvement in the side contralateral to the treated side (p<0.02) with no signficant change in the other side. There appeared to be a dose effect, as the low dose group had only a slight reduction while the high dose group averaged nearly 50% reduction in UPDRS. Functional brain activity, as measured by glucose PET, showed similar changes. Pathological hypermetabolism of GPi was significantly reduced on the treated side of the brain (p<0.001) while PMC activity correspondingly increased with a highly significant correlation (r-0.78,P<0.00) with improvements in clinical ratings in a dose-dependent fashion. The control side showed no significant metabolic improvement in either area. Follow-up to 12 months in all patients is currently ongoing. This is the first trial of in vivo gene therapy for an adult neurodegenerative disorder, and the safety and efficacy profile seen to date suggests that future, more definitive studies are warranted.Molecular Therapy (2006) 13, S280–S281; doi: 10.1016/j.ymthe.2006.08.807 [ABSTRACT FROM AUTHOR]

Behavioral variant of frontotemporal dementia (bvFTD) is common among young‐onset dementia patients. While bvFTD‐specific multivariate metabolic brain pattern (bFDRP) has been identified previously, little is known about its temporal evolution, internal structure, effect of atrophy, and its relationship with nonspecific resting‐state networks such as default mode network (DMN). In this multicenter study, we explored FDG‐PET brain scans of 111 bvFTD, 26 Alzheimer's disease, 16 Creutzfeldt‐Jakob's disease, 24 semantic variant primary progressive aphasia (PPA), 18 nonfluent variant PPA and 77 healthy control subjects (HC) from Slovenia, USA, and Germany. bFDRP was identified in a cohort of 20 bvFTD patients and age‐matched HC using scaled subprofile model/principle component analysis and validated in three independent cohorts. It was characterized by hypometabolism in frontal cortex, insula, anterior/middle cingulate, caudate, thalamus, and temporal poles. Its expression in bvFTD patients was significantly higher compared to HC and other dementia syndromes (p <.0004), correlated with cognitive decline (p =.0001), and increased over time in longitudinal cohort (p =.0007). Analysis of internal network organization by graph‐theory methods revealed prominent network disruption in bvFTD patients. We have further found a specific atrophy‐related pattern grossly corresponding to bFDRP; however, its contribution to the metabolic pattern was minimal. Finally, despite the overlap between bFDRP and FDG‐PET‐derived DMN, we demonstrated a predominant role of the specific bFDRP. Taken together, we validated the bFDRP network as a diagnostic/prognostic biomarker specific for bvFTD, provided a unique insight into its highly reproducible internal structure, and proved that bFDRP is unaffected by structural atrophy and independent of normal resting state networks loss. [ABSTRACT FROM AUTHOR]

Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations. Advances in neuroimaging research have enabled the development of predictive models that integrate information from multiple brain systems. Here, Perovnik, Rus and colleagues discuss the detection and validation of neurodegenerative disease-specific functional brain networks and consider their relationship to pathological processes and disease-related genotypes. Key points: Parkinson disease, Alzheimer disease and other neurodegenerative disorders are characterized by specific disease-related functional topographies (brain networks) that can be identified and validated using metabolic PET or resting-state functional MRI. Brain network activity can be quantified on an individual patient basis, and the resulting network expression levels can be used in research and clinical settings. Expression levels for multiple disease-related topographies can be entered into computational algorithms used to classify patients according to the diagnostic likelihood of these diseases. Expression levels for abnormal disease networks correlate with clinical symptom severity and can be modulated by effective treatment. Network expression levels increase over time and can be used to predict the likelihood of transition from preclinical to symptomatic disease in at-risk individuals. The characterization of treatment-induced networks opens the door to their future use as objective outcome measures in clinical trials. [ABSTRACT FROM AUTHOR]