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Background and Purpose: Chronic active multiple sclerosis (MS) lesions are characterized by a paramagnetic rim at the edge of the lesion and are associated with increased disability in patients. Quantitative susceptibility mapping (QSM) is an MRI technique that is sensitive to chronic active lesions, termed rim + lesions on the QSM. We present QSMRim-Net, a data imbalance-aware deep neural network that fuses lesion-level radiomic and convolutional image features for automated identification of rim + lesions on QSM., Methods: QSM and T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI of the brain were collected at 3 T for 172 MS patients. Rim + lesions were manually annotated by two human experts, followed by consensus from a third expert, for a total of 177 rim + and 3986 rim negative (rim-) lesions. Our automated rim + detection algorithm, QSMRim-Net, consists of a two-branch feature extraction network and a synthetic minority oversampling network to classify rim + lesions. The first network branch is for image feature extraction from the QSM and T2-FLAIR, and the second network branch is a fully connected network for QSM lesion-level radiomic feature extraction. The oversampling network is designed to increase classification performance with imbalanced data., Results: On a lesion-level, in a five-fold cross validation framework, the proposed QSMRim-Net detected rim + lesions with a partial area under the receiver operating characteristic curve (pROC AUC) of 0.760, where clinically relevant false positive rates of less than 0.1 were considered. The method attained an area under the precision recall curve (PR AUC) of 0.704. QSMRim-Net out-performed other state-of-the-art methods applied to the QSM on both pROC AUC and PR AUC. On a subject-level, comparing the predicted rim + lesion count and the human expert annotated count, QSMRim-Net achieved the lowest mean square error of 0.98 and the highest correlation of 0.89 (95% CI: 0.86, 0.92)., Conclusion: This study develops a novel automated deep neural network for rim + MS lesion identification using T2-FLAIR and QSM images., (Copyright © 2022. Published by Elsevier Inc.)

Purpose: To evaluate the diagnostic accuracy of computed tomography angiography (CTA) acquired with shuttle technique (CTAs) and helical CTA (CTAh) for vasospasm, using digital subtraction angiography (DSA) obtained within 24 h as reference standard., Methods: Thirty-six patients with suspected vasospasm in the setting of aneurysmal subarachnoid hemorrhage (ASAH, 30/36) or acute inflammatory/infectious conditions (6/36) who underwent CTAs (17/36) or CTAh (19/36) followed by DSA within 24 h were identified retrospectively. Presence of vasospasm in the proximal cerebral arterial segments was assessed qualitatively and semi-quantitatively on CTA and subsequent DSA. Sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated. Inter-rater variability was assessed using Cohen's kappa., Results: On CTAs, 35% of patients had low and 65% had high vasospasm burden. On CTAh, 37% had low and 63% had high vasospasm burden. ROC analysis demonstrated an AUC of 0.87 for CTAs (95%CI 0.67-1.00, p = 0.015) and 0.88 for CTAh (0.72-1.00, p = 0.028). Cohen's kappa was 0.843 (95%CI 0.548-1.000). Thresholding with Youden's J index, CTAs had a sensitivity of 85.71% (95%CI 48.69 to 99.27) and specificity of 66.67% (35.42 to 87.94). CTAh had sensitivity of 100% (56.55 to 100.00) and specificity of 78.57% (52.41 to 92.43)., Conclusion: CTAs and CTAh yielded similar sensitivity, specificity, and AUC values on ROC analysis for the detection of vasospasm using DSA as reference standard. Our findings suggest that CTAs is a promising alternative to CTAh especially in patients requiring serial imaging, given its potential advantages of decreased radiation exposure, contrast dose, and cost-effectiveness., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Distinguishing frontotemporal lobar degeneration (FTLD) and Alzheimer Disease (AD) on FDG-PET based on qualitative review alone can pose a diagnostic challenge. SPM has been shown to improve diagnostic performance in research settings, but translation to clinical practice has been lacking. Our purpose was to create a heuristic scoring method based on statistical parametric mapping z-scores. We aimed to compare the performance of the scoring method to the initial qualitative read and a machine learning (ML)-based method as benchmarks. FDG-PET/CT or PET/MRI of 65 patients with suspected dementia were processed using SPM software, yielding z-scores from either whole brain (W) or cerebellar (C) normalization relative to a healthy cohort. A non-ML, heuristic scoring system was applied using region counts below a preset z-score cutoff. W z-scores, C z-scores, or WC z-scores (z-scores from both W and C normalization) served as features to build random forest models. The neurological diagnosis was used as the gold standard. The sensitivity of the non-ML scoring system and the random forest models to detect AD was higher than the initial qualitative read of the standard FDG-PET [0.89-1.00 vs. 0.22 (95% CI, 0-0.33)]. A categorical random forest model to distinguish AD, FTLD, and normal cases had similar accuracy than the non-ML scoring model (0.63 vs. 0.61). Our non-ML-based scoring system of SPM z-scores approximated the diagnostic performance of a ML-based method and demonstrated higher sensitivity in the detection of AD compared to qualitative reads. This approach may improve the diagnostic performance., Competing Interests: None., (AJNMMI Copyright © 2021.)

A combination therapy using Prussian blue nanoparticles (PBNP) as photothermal therapy (PTT) agents coated with CpG oligodeoxynucleotides, an immunologic adjuvant, as a nanoimmunotherapy (CpG-PBNP-PTT) for neuroblastoma (NB) is described. NB driven by MYCN amplification confers high risk and correlates with a dismal prognosis, accounting for the majority of NB-related mortality. The efficacy of the CpG-PBNP-PTT nanoimmunotherapy in a clinically relevant, TH-MYCN murine NB model (9464D) overexpressing MYCN is tested. When administered to 9464D NB cells in vitro, CpG-PBNP-PTT triggers thermal dose-dependent immunogenic cell death and tumor cell priming for immune recognition in vitro, measured by the expression of specific costimulatory and antigen-presenting molecules. In vivo, intratumorally administered CpG-PBNP-PTT generates complete tumor regression and significantly higher long-term survival compared to controls. Furthermore, CpG-PBNP-PTT-treated mice reject tumor rechallenge. Ex vivo studies confirm these therapeutic responses result from the generation of robust T cell-mediated immunological memory. Consequently, in a synchronous 9464D tumor model, CpG-PBNP-PTT induces complete tumor regression on the treated flank and significantly slows tumor progression on the untreated flank, improving animal survival. These findings demonstrate that localized administration of the CpG-PBNP-PTT nanoimmunotherapy drives potent systemic T cell responses in solid tumors such as NB and therefore has therapeutic implications for NB., Competing Interests: 6.Conflict of Interest The authors declare no conflict of interest.

Adoptive T cell therapy has emerged as a revolutionary immunotherapy for treating cancer. Despite immense promise and clinical success in some hematologic malignancies, limitations remain that thwart its efficacy in solid tumors. Particularly in tumors of the central nervous system (CNS), T cell therapy is often restricted by the difficulty in intratumoral delivery across anatomical niches, suboptimal T cell specificity or activation, and intratumoral T cell dysfunction due to immunosuppressive tumor microenvironments (TMEs). Nanoparticles may offer several advantages to overcome these limitations of T cell therapy, as they can be designed to robustly and specifically activate T cells ex vivo prior to adoptive transfer, to encapsulate T cell stimulating agents for co-localized stimulation, and to be conjugated onto T cells for added functionality. This perspective highlights recent preclinical advances in using nanoparticles to enhance T cell therapy, and discusses the potential applicability and constraints of nanoparticle-enhanced T cells as a new platform for treating CNS tumors., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Balakrishnan and Sweeney.)

Background and Purpose: The presence of a paramagnetic rim around a white matter lesion has recently been shown to be a hallmark of a particular pathological type of multiple sclerosis lesion. Increased prevalence of these paramagnetic rim lesions is associated with a more severe disease course in MS, but manual identification is time-consuming. We present APRL, a method to automatically detect paramagnetic rim lesions on 3T T2*-phase images., Methods: T1-weighted, T2-FLAIR, and T2*-phase MRI of the brain were collected at 3T for 20 subjects with MS. The images were then processed with automated lesion segmentation, lesion center detection, lesion labelling, and lesion-level radiomic feature extraction. A total of 951 lesions were identified, 113 (12%) of which contained a paramagnetic rim. We divided our data into a training set (16 patients, 753 lesions) and a testing set (4 patients, 198 lesions), fit a random forest classification model on the training set, and assessed our ability to classify paramagnetic rim lesions on the test set., Results: The number of paramagnetic rim lesions per subject identified via our automated lesion labelling method was highly correlated with the gold standard count per subject, r = 0.86 (95% CI [0.68, 0.94]). The classification algorithm using radiomic features classified lesions with an area under the curve of 0.82 (95% CI [0.74, 0.92])., Conclusion: This study develops a fully automated technique, APRL, for the detection of paramagnetic rim lesions using standard T1 and FLAIR sequences and a T2*phase sequence obtained on 3T MR images., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Accurate detection and segmentation of multiple sclerosis (MS) brain lesions on magnetic resonance images are important for disease diagnosis and treatment. This is a challenging task as lesions vary greatly in size, shape, location, and image contrast. The objective of our study was to develop an algorithm based on deep convolutional neural network integrated with anatomic information and lesion-wise loss function (ALL-Net) for fast and accurate automated segmentation of MS lesions. Distance transformation mapping was used to construct a convolutional module that encoded lesion-specific anatomical information. To overcome the lesion size imbalance during network training and improve the detection of small lesions, a lesion-wise loss function was developed in which individual lesions were modeled as spheres of equal size. On the ISBI-2015 longitudinal MS lesion segmentation challenge dataset (19 subjects in total), ALL-Net achieved an overall score of 93.32 and was amongst the top performing methods. On the larger Cornell MS dataset (176 subjects in total), ALL-Net significantly improved both voxel-wise metrics (Dice improvement of 3.9% to 35.3% with p-values ranging from p < 0.01 to p < 0.0001, and AUC of voxel-wise precision-recall curve improvement of 2.1% to 29.8%) and lesion-wise metrics (lesion-wise F1 score improvement of 12.6% to 29.8% with all p-values p < 0.0001, and AUC of lesion-wise ROC curve improvement of 1.4% to 20.0%) compared to leading publicly available MS lesion segmentation tools., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Immune checkpoint blockade (ICB) comprising monoclonal antibodies (mAbs) against immune 'checkpoints', such as CTLA-4 and the PD1/PDL1 axis have dramatically improved clinical outcomes for patients with cancer. However, ICB by itself has failed to provide benefit in a wide range of solid tumors, where recurrence still occurs with high incidence. These poor response rates may be due to the therapeutic shortcomings of ICB; namely, a lack of cancer-specific cytotoxicity and ability to debulk tumors. To overcome these limitations, effective ICB therapy may require the combination with other complementary therapeutic platforms. Here, we propose that photothermal therapy (PTT) is an ideal therapeutic modality for combination with ICB because it can generate both tumor-specific cytotoxicity and immunogenicity. PTT elicits these specific effects because it is a localized thermal ablation technique that utilizes light-responsive nanoparticles activated by a wavelength-matched laser. While ICB immunotherapy alone improves cancer immunogenicity but does not generate robust antitumor cytotoxicity, nanoparticle-based PTT elicits targeted and controlled cytotoxicity but sub-optimal long-term immunogenicity. Thus, the two platforms offer complementary and potentially synergistic antitumor effects, which will be detailed in this review. We highlight three classes of nanoparticles used as agents of PTT (i.e., metallic inorganic nanoparticles, carbon-based nanoparticles and organic dyes), and illustrate the potential for nanoparticle-based PTT to potentiate the effects of ICB in preclinical models. Through this discussion, we aim to present PTT combined with ICB as a potent synergistic combination treatment for diverse cancer types currently refractory to ICB as well as PTT monotherapies.

Even though there is a clear link between Alzheimer's Disease (AD) related neuropathology and cognitive decline, numerous studies have observed that healthy cognition can exist in the presence of extensive AD pathology, a phenomenon sometimes called Cognitive Resilience (CR). To better understand and study CR, we develop the Alzheimer's Disease Cognitive Resilience Score (AD-CR Score), which we define as the difference between the observed and expected cognition given the observed level of AD pathology. Unlike other definitions of CR, our AD-CR Score is a fully non-parametric, stand-alone, individual-level quantification of CR that is derived independently of other factors or proxy variables. Using data from two ongoing, longitudinal cohort studies of aging, the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP), we validate our AD-CR Score by showing strong associations with known factors related to CR such as baseline and longitudinal cognition, non AD-related pathology, education, personality, APOE, parkinsonism, depression, and life activities. Even though the proposed AD-CR Score cannot be directly calculated during an individual's lifetime because it uses postmortem pathology, we also develop a machine learning framework that achieves promising results in terms of predicting whether an individual will have an extremely high or low AD-CR Score using only measures available during the lifetime. Given this, our AD-CR Score can be used for further investigations into mechanisms of CR, and potentially for subject stratification prior to clinical trials of personalized therapies., Competing Interests: The authors have declared that no competing interests exist.

Natural killer (NK) cells are attractive effector cells of the innate immune system against human immunodeficiency virus (HIV) and cancer. However, NK cell therapies are limited by the fact that target cells evade NK cells, for example, in latent reservoirs (in HIV) or through upregulation of inhibitory signals (in cancer). To address this limitation, we describe a biodegradable nanoparticle-based "priming" approach to enhance the cytotoxic efficacy of peripheral blood mononuclear cell-derived NK cells. We present poly(lactic-co-glycolic acid) (PLGA) nanodepots (NDs) that co-encapsulate prostratin, a latency-reversing agent, and anti-CD25 (aCD25), a cell surface binding antibody, to enhance primary NK cell function against HIV and cancer. We utilize a nanoemulsion synthesis scheme to encapsulate both prostratin and aCD25 within the PLGA NDs (termed Pro-aCD25-NDs). Physicochemical characterization studies of the NDs demonstrated that our synthesis scheme resulted in stable and monodisperse Pro-aCD25-NDs. The NDs successfully released both active prostratin and anti-CD25, and with controllable release kinetics. When Pro-aCD25-NDs were administered in an in vitro model of latent HIV and acute T cell leukemia using J-Lat 10.6 cells, the NDs were observed to prime J-Lat cells resulting in significantly increased NK cell-mediated cytotoxicity compared to free prostratin plus anti-CD25, and other controls. These findings demonstrate the feasibility of using our Pro-aCD25-NDs to prime target cells for enhancing the cytotoxicity of NK cells as antiviral or antitumor agents.

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.

Theranostic nanoparticles offer the potential for mixing and matching disparate diagnostic and therapeutic functionalities within a single nanoparticle for the personalized treatment of diseases. In this article, we present composite iron oxide-gadolinium-containing Prussian blue nanoparticles (Fe 3 O 4 @GdPB) as a novel theranostic agent for T 1 -weighted magnetic resonance imaging (MRI) and photothermal therapy (PTT) of tumors. These particles combine the well-described properties and safety profiles of the constituent Fe 3 O 4 nanoparticles and gadolinium-containing Prussian blue nanoparticles. The Fe 3 O 4 @GdPB nanoparticles function both as effective MRI contrast agents and PTT agents as determined by characterizing studies performed in vitro and retain their properties in the presence of cells. Importantly, the Fe 3 O 4 @GdPB nanoparticles function as effective MRI contrast agents in vivo by increasing signal:noise ratios in T 1 -weighted scans of tumors and as effective PTT agents in vivo by decreasing tumor growth rates and increasing survival in an animal model of neuroblastoma. These findings demonstrate the potential of the Fe 3 O 4 @GdPB nanoparticles to function as effective theranostic agents., Competing Interests: Disclosure The authors report no conflicts of interest in this work.

We describe "photothermal immunotherapy," which combines Prussian blue nanoparticle (PBNP)-based photothermal therapy (PTT) with anti-CTLA-4 checkpoint inhibition for treating neuroblastoma, a common, hard-to-treat pediatric cancer. PBNPs exhibit pH-dependent stability, which makes them suitable for intratumorally-administered PTT. PBNP-based PTT is able to lower tumor burden and prime an immune response, specifically an increased infiltration of lymphocytes and T cells to the tumor area, which is complemented by the antitumor effects of anti-CTLA-4 immunotherapy, providing a more durable treatment against neuroblastoma in an animal model. We observe 55.5% survival in photothermal immunotherapy-treated mice at 100days compared to 12.5%, 0%, 0%, and 0% survival in mice receiving: anti-CTLA-4 alone, PBNPs alone, PTT alone, and no treatment, respectively. Additionally, long-term surviving, photothermal immunotherapy-treated mice exhibit protection against neuroblastoma rechallenge, suggesting the development of immunity against these tumors. Our findings suggest the potential of photothermal immunotherapy in improving treatments for neuroblastoma., (Copyright © 2016 Elsevier Inc. All rights reserved.)

We propose a lag functional linear model to predict a response using multiple functional predictors observed at discrete grids with noise. Two procedures are proposed to estimate the regression parameter functions: (1) an approach that ensures smoothness for each value of time using generalized cross-validation; and (2) a global smoothing approach using a restricted maximum likelihood framework. Numerical studies are presented to analyze predictive accuracy in many realistic scenarios. The methods are employed to estimate a magnetic resonance imaging (MRI)-based measure of tissue damage (the magnetization transfer ratio, or MTR) in multiple sclerosis (MS) lesions, a disease that causes damage to the myelin sheaths around axons in the central nervous system. Our method of estimation of MTR within lesions is useful retrospectively in research applications where MTR was not acquired, as well as in clinical practice settings where acquiring MTR is not currently part of the standard of care. The model facilitates the use of commonly acquired imaging modalities to estimate MTR within lesions, and outperforms cross-sectional models that do not account for temporal patterns of lesion development and repair.

Quantitative T1 maps estimate T1 relaxation times and can be used to assess diffuse tissue abnormalities within normal-appearing tissue. T1 maps are popular for studying the progression and treatment of multiple sclerosis (MS). However, their inclusion in standard imaging protocols remains limited due to the additional scanning time and expert calibration required and susceptibility to bias and noise. Here, we propose a new method of estimating T1 maps using four conventional MR images, which are intensity-normalized using cerebellar gray matter as a reference tissue and related to T1 using a smooth regression model. Using cross-validation, we generate statistical T1 maps for 61 subjects with MS. The statistical maps are less noisy than the acquired maps and show similar reproducibility. Tests of group differences in normal-appearing white matter across MS subtypes give similar results using both methods., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect, and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, 2008, Gagnon-Bartsch and Speed, 2012], two batch effect correction tools largely used in genomics, we decompose the voxel intensities of images registered to a template into a biological component and an unwanted variation component. The unwanted variation component is estimated from a control region obtained from the cerebrospinal fluid (CSF), where intensities are known to be unassociated with disease status and other clinical covariates. We perform a singular value decomposition (SVD) of the control voxels to estimate factors of unwanted variation. We then estimate the unwanted factors using linear regression for every voxel of the brain and take the residuals as the RAVEL-corrected intensities. We assess the performance of RAVEL using T1-weighted (T1-w) images from more than 900 subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI), as well as healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compare RAVEL to two intensity-normalization-only methods: histogram matching and White Stripe. We show that RAVEL performs best at improving the replicability of the brain regions that are empirically found to be most associated with AD, and that these regions are significantly more present in structures impacted by AD (hippocampus, amygdala, parahippocampal gyrus, enthorinal area, and fornix stria terminals). In addition, we show that the RAVEL-corrected intensities have the best performance in distinguishing between MCI subjects and healthy subjects using the mean hippocampal intensity (AUC=67%), a marked improvement compared to results from intensity normalization alone (AUC=63% and 59% for histogram matching and White Stripe, respectively). RAVEL is promising for many other imaging modalities., (Published by Elsevier Inc.)

The formation of multiple sclerosis (MS) lesions is a complex process involving inflammation, tissue damage, and tissue repair - all of which are visible on structural magnetic resonance imaging (MRI) and potentially modifiable by pharmacological therapy. In this paper, we introduce two statistical models for relating voxel-level, longitudinal, multi-sequence structural MRI intensities within MS lesions to clinical information and therapeutic interventions: (1) a principal component analysis (PCA) and regression model and (2) function-on-scalar regression models. To do so, we first characterize the post-lesion incidence repair process on longitudinal, multi-sequence structural MRI from 34 MS patients as voxel-level intensity profiles. For the PCA regression model, we perform PCA on the intensity profiles to develop a voxel-level biomarker for identifying slow and persistent, long-term intensity changes within lesion tissue voxels. The proposed biomarker's ability to identify such effects is validated by two experienced clinicians (a neuroradiologist and a neurologist). On a scale of 1 to 4, with 4 being the highest quality, the neuroradiologist gave the score on the first PC a median quality rating of 4 (95% CI: [4,4]), and the neurologist gave the score a median rating of 3 (95% CI: [3,3]). We then relate the biomarker to the clinical information in a mixed model framework. Treatment with disease-modifying therapies (p < 0.01), steroids (p < 0.01), and being closer to the boundary of abnormal signal intensity (p < 0.01) are all associated with return of a voxel to an intensity value closer to that of normal-appearing tissue. The function-on-scalar regression model allows for assessment of the post-incidence time points at which the covariates are associated with the profiles. In the function-on-scalar regression, both age and distance to the boundary were found to have a statistically significant association with the lesion intensities at some time point. The two models presented in this article show promise for understanding the mechanisms of tissue damage in MS and for evaluating the impact of treatments for the disease in clinical trials.

Activating mutations in genes encoding phosphatidylinositol 3-kinase (PI3K)-AKT pathway components cause megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome (MPPH, OMIM 603387). Here we report that individuals with MPPH lacking upstream PI3K-AKT pathway mutations carry de novo mutations in CCND2 (encoding cyclin D2) that are clustered around a residue that can be phosphorylated by glycogen synthase kinase 3β (GSK-3β). Mutant CCND2 was resistant to proteasomal degradation in vitro compared to wild-type CCND2. The PI3K-AKT pathway modulates GSK-3β activity, and cells from individuals with PIK3CA, PIK3R2 or AKT3 mutations showed similar CCND2 accumulation. CCND2 was expressed at higher levels in brains of mouse embryos expressing activated AKT3. In utero electroporation of mutant CCND2 into embryonic mouse brains produced more proliferating transfected progenitors and a smaller fraction of progenitors exiting the cell cycle compared to cells electroporated with wild-type CCND2. These observations suggest that cyclin D2 stabilization, caused by CCND2 mutation or PI3K-AKT activation, is a unifying mechanism in PI3K-AKT-related megalencephaly syndromes.

Context: P450 oxidoreductase deficiency (PORD) is a unique congenital adrenal hyperplasia variant that manifests with glucocorticoid deficiency, disordered sex development (DSD), and skeletal malformations. No comprehensive data on genotype-phenotype correlations in Caucasian patients are available., Objective: The objective of the study was to establish genotype-phenotype correlations in a large PORD cohort., Design: The design of the study was the clinical, biochemical, and genetic assessment including multiplex ligation-dependent probe amplification (MLPA) in 30 PORD patients from 11 countries., Results: We identified 23 P450 oxidoreductase (POR) mutations (14 novel) including an exonic deletion and a partial duplication detected by MLPA. Only 22% of unrelated patients carried homozygous POR mutations. p.A287P was the most common mutation (43% of unrelated alleles); no other hot spot was identified. Urinary steroid profiling showed characteristic PORD metabolomes with variable impairment of 17α-hydroxylase and 21-hydroxylase. Short cosyntropin testing revealed adrenal insufficiency in 89%. DSD was present in 15 of 18 46,XX and seven of 12 46,XY individuals. Homozygosity for p.A287P was invariably associated with 46,XX DSD but normal genitalia in 46,XY individuals. The majority of patients with mild to moderate skeletal malformations, assessed by a novel scoring system, were compound heterozygous for missense mutations, whereas nearly all patients with severe malformations carried a major loss-of-function defect on one of the affected alleles., Conclusions: We report clinical, biochemical, and genetic findings in a large PORD cohort and show that MLPA is a useful addition to POR mutation analysis. Homozygosity for the most frequent mutation in Caucasians, p.A287P, allows for prediction of genital phenotype and moderate malformations. Adrenal insufficiency is frequent, easily overlooked, but readily detected by cosyntropin testing.

Background: Sexually transmitted infections (STIs) are associated with an increased risk of HIV infection. To model the interaction between STIs and HIV infection, we evaluated the capacity of the pigtail macaque model to sustain triple infection with Trichomonas vaginalis, Chlamydia trachomatis, and SHIV(SF162P3)., Methods: Seven SHIV(SF162P3) -infected pigtail macaques were inoculated with T. vaginalis only (n = 2), C. trachomatis only (n = 1), both T. vaginalis and C. trachomatis (n = 2), or control media (no STI; n = 2). Infections were confirmed by culture and/or nucleic acid testing. Genital mucosa was visualized by colposcopy., Results: Characteristic gynecologic signs were observed for both STIs, but not in control animals. Manifestations were most prominent at days 7-10 post-infection. STIs persisted between 4 and 6 weeks and were cleared with antibiotics., Conclusions: These pilot studies demonstrate the first successful STI-SHIV triple infection of pigtail macaques, with clinical presentation of genital STI symptoms similar to those observed in humans., (Published 2011. This article is a U.S. Government work and is in the public domain in the USA.)

Daily preexposure prophylaxis (PrEP) with Truvada (emtricitabine [FTC] and tenofovir disoproxil fumarate [TDF]) is a novel HIV prevention strategy recently found to reduce HIV incidence among men who have sex with men. We used a macaque model of HIV transmission to investigate if Truvada maintains prophylactic efficacy against an FTC-resistant isolate containing the M184V mutation. Five macaques received a dose of Truvada 3 days before exposing them rectally to the simian/human immunodeficiency virus mutant SHIV162p3(M184V), followed by a second dose 2 h after exposure. Five untreated animals were used as controls. Virus exposures were done weekly for up to 14 weeks. Despite the high (>100-fold) level of FTC resistance conferred by M184V, all five treated animals were protected from infection, while the five untreated macaques were infected (P = 0.0008). Our results show that Truvada maintains high prophylactic efficacy against an FTC-resistant isolate. Increased susceptibility to tenofovir due to M184V and other factors, including residual antiviral activity by FTC and/or reduced virus fitness due to M184V, may all have contributed to the observed protection.

Background: Absenteeism from outpatient appointments is common. Telephone appointment-reminder calls reduce outpatient-appointment absenteeism in many clinic settings., Objective: To determine if telephone appointment-reminder calls reduce outpatient absenteeism at a hospital-based pulmonary function laboratory., Methods: We conducted a retrospective review of our pulmonary function laboratory's outpatient appointment records from April to November 2004. Data were collected from consecutive outpatient appointments, including patient age, sex, whether a telephone appointment-reminder call was successfully made, and whether the patient showed up for the scheduled test. We performed 3 analyses. Differences in absenteeism between the groups was the primary outcome measure. First, appointments were separated into 2 groups: (1) appointments for which a reminder call was attempted ("called" group) and (2) appointments for which a reminder call was not attempted ("not-called" group). The appointments were then separated into 2 further groups: (1) the reminder call was successfully achieved ("contacted" group) and (2) the patient either was not called or was called but could not be reached ("not-contacted" group). Finally, the contacted group was separated into 2 further groups: (1) reminder calls that resulted in direct conversation with an appropriate person at the patient's listed telephone number, and (2) reminder message left on an answering machine., Results: Data were collected from 515 consecutive outpatient appointments; 45 (8.7%) of these patients did not show up for testing. The absentee rate was 4.7% (n = 10) in the called group and 11.6% (n = 35) in the not-called group (p = 0.0066). In the called group, 6.5% (n = 14) could not be reached. The absentee rate was 4% (n = 8) in the contacted group and 11.7% (n = 37) in the not-contacted group (p = 0.0021). We found no difference in absenteeism between patients who received reminders via direct conversation (4.2%) and those who had a reminder message left on an answering machine (3.7%) (p > 0.05)., Conclusions: A policy of reminding outpatients of their appointments via telephone reduces absenteeism at a hospital-based pulmonary function laboratory. We found no difference in absenteeism between communicating the reminder via direct conversation versus via leaving a message on an answering machine.