Rationale: Despite its widespread use in oncology, the PET radiotracer ¹⁸F-FDG is ineffective for improving early detection of pancreatic ductal adenocarcinoma (PDAC). An alternative strategy for early detection of pancreatic cancer involves visualisation of high-grade pancreatic intraepithelial neoplasias (PanIN-3), generally regarded as the non-invasive precursors of PDAC. The DNA damage response is known to be hyper-activated in late-stage PanINs. Therefore, we investigated whether the SPECT imaging agent, ¹¹¹In-anti-H2AX-TAT, allows visualisation of the DNA damage repair marker H2AX in PanIN-3s in an engineered mouse model of PDAC, to facilitate early detection of PDAC. Methods: Genetically engineered KPC mice (KRasLSL.G12D/+; p53LSL.R172H/+; PdxCre) were imaged with ¹⁸F-FDG and ¹¹¹In-anti-H2AX-TAT. PanIN/PDAC presence visualised by histology was compared with autoradiography and immunofluorescence. Separately, the survival of KPC mice imaged with ¹¹¹In-anti-H2AX-TAT was evaluated. Results: In KPC mouse pancreata, H2AX expression was increased in high-grade PanINs, but not in PDAC, corroborating earlier results obtained from human pancreas sections. Uptake of ¹¹¹In-anti-H2AX-TAT, but not ¹¹¹In-IgG-TAT or ¹⁸F-FDG, within the pancreas was positively correlated with the age of KPC mice, which was correlated with the number of high-grade PanINs. ¹¹¹In-anti-H2AX-TAT localises preferentially in high-grade PanIN lesions, but not in established PDAC. Younger, non-tumour-bearing KPC mice that show uptake of ¹¹¹In-anti-H2AX-TAT in the pancreas survive significantly shorter than mice with physiological ¹¹¹In-anti-H2AX-TAT uptake. Conclusion: ¹¹¹In-anti-H2AX-TAT imaging allows non-invasive detection of DNA damage repair signalling upregulation in pre-invasive PanIN lesions and is a promising new tool to aid in the early detection and staging of pancreatic cancer.

Head motion degrades image quality and causes erroneous parameter estimates in tracer kinetic modeling in brain PET studies. Existing motion correction methods include frame-based image-registration (FIR) and correction using real-time hardware-based motion tracking (HMT) information. However, FIR cannot correct for motion within one predefined scan period while HMT is not readily available in the clinic since it typically requires attaching a tracking device to the patient. In this study, we propose a motion correction framework with a data-driven algorithm, i.e., using the PET raw data itself, to address these limitations. Methods: We propose a data-driven algorithm, Centroid of Distribution (COD), to detect head motion. In COD, the central coordinates of the line of response (LOR) of all events are averaged over 1-sec intervals to generate a COD trace. A point-to-point change in the COD trace in one direction that exceeded a user-defined threshold was defined as a time point of head motion, which was followed by manually adding additional motion time points. All the frames defined by such time points were reconstructed without attenuation correction and rigidly registered to a reference frame. The resulting transformation matrices were then used to perform the final motion compensated reconstruction. We applied the new COD framework to 23 human dynamic datasets, all containing large head motions, with ¹⁸F-FDG (N = 13) and ¹¹C-UCB-J (N = 10), and compared its performance with FIR and with HMT using the Vicra, which can be considered as the "gold standard". Results: The COD method yielded 1.0±3.2% (mean ± standard deviation across all subjects and 12 grey matter regions) SUV difference for ¹⁸F-FDG (3.7±5.4% for ¹¹C-UCB-J) compared to HMT while no motion correction (NMC) and FIR yielded -15.7±12.2% (-20.5±15.8%) and -4.7±6.9% (-6.2±11.0%), respectively. For ¹⁸F-FDG dynamic studies, COD yielded differences of 3.6±10.9% in Ki value as compared to HMT, while NMC and FIR yielded -18.0±39.2% and -2.6±19.8%, respectively. For ¹¹C-UCB-J, COD yielded 3.7±5.2% differences in VT compared to HMT, while NMC and FIR yielded -20.0±12.5% and -5.3±9.4%, respectively. Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR and achieved comparable or even better performance as compared to the Vicra HMT method in both static and dynamic studies.

Purpose: The main objective of this prospective study was to determine the impact of multi-phasic acquisition of ⁶⁸Ga-PSMA PET/CT in the detection of recurrent prostate cancer (PCa) in the early stage of biochemical recurrence (BR) with prostate-serum-antigen (PSA) level <1ng/ml. Also, ⁶⁸Ga-PSMA PET/CT positivity was correlated with clinical parameters for the assessment of predictive markers. Methods: A prospective monocentric study was conducted on 135 PCa patients with BR and PSA<1ng/ml. All patients have undergone initial prostatectomy with additional radiation therapy in 19.3% and androgen-deprivation therapy (ADT) in 7.4% of patients. Dynamic acquisition [1–8min. post-injection (p.i.)] from the prostate bed, standard whole-body (60min. p.i.) and limited bed positions of delayed studies (120-150min. p.i.), were performed. Studies were reviewed by two board-certified nuclear medicine specialists, independently. A combination of visual and semi-quantitative analyses and correlation with morphological (e.g. MRI) and/or clinical follow-up findings was used for the final interpretation of abnormal lesions as benign or malignant. ⁶⁸Ga-PSMA PET/CT positivity was also correlated with primary clinical findings. Results: Incorporating the information of all phases, 116 lesions were detected in 49.6% of patients (22 local recurrences, 63 lymph nodes, and 31 distant metastases). The detection rates were 31.8%, 44.9%, and 71.4% for PSA<0.2ng/ml, 0.2≤PSA<0.5, and 0.5≤PSA<1, respectively. Additional dynamic and/or delayed phases resulted in better determination of equivocal lesions and a higher diagnostic performance in 25.9% of patients. Stand-alone dynamic and delayed images led to better interpretation of equivocal findings in the prostate bed (31.4%) and other (lymph node/bone) lesions (20%), respectively. Conclusion: ⁶⁸Ga-PSMA PET/CT revealed promising results for the early detection of recurrent disease in patients with PSA level of 0.5-1.0ng/ml. However, it showed limited value in cases with PSA<0.5ng/ml. Multi-phasic ⁶⁸Ga-PSMA PET/CT led to better determination of equivocal findings. Although, dynamic images may provide helpful information in assessment of the prostate bed; however, delayed acquisitions seem to have higher impact in clarifying of the equivocal findings.

Rationale: Fluorescence molecular endoscopy (FME) is an emerging technique that has the potential to improve the 22% colorectal polyp detection miss-rate. We determined the optimal dose-to-imaging interval and safety of FME using EMI-137, a c-Met targeted fluorescent peptide, in a population at high-risk for colorectal cancer. Methods: We performed in vivo FME and quantification of fluorescence by multi-diameter single-fiber reflectance, single-fiber fluorescence spectroscopy in 15 patients with a dysplastic colorectal adenoma. EMI-137 was intravenously administered (0.13mg/kg) at a one-, two- or three-hour dose-to-imaging interval (N = 3 patients per cohort). Two cohorts were expanded to six patients based on target-to-background ratios (TBR). Fluorescence was correlated to histopathology and c-Met expression. EMI-137 binding specificity was assessed by fluorescence microscopy and in vitro experiments. Results: FME using EMI-137 appeared to be safe and well tolerated. All dose-to-imaging intervals showed significantly increased fluorescence in the colorectal lesions compared to surrounding tissue, with a TBR of 1.53, 1.66 and 1.74 respectively (mean intrinsic fluorescence (Q·μ^f_a,x) = 0.035 vs. 0.023mm^-1, P<0.0003; 0.034 vs. 0.021mm^-1, P<0.0001; 0.033 vs. 0.019mm^-1, P<0.0001). Fluorescence correlated to histopathology on a macroscopic and microscopic level, with significant c-Met overexpression in dysplastic mucosa. In vitro, a dose-dependent specific binding was confirmed. Conclusion: FME using EMI-137 appeared to be safe and feasible within a one-to-three hour dose-to-imaging interval. No clinically significant differences were observed between the cohorts, although a one-hour dose-to-imaging interval was preferred from a clinical perspective. Future studies will investigate EMI-137 for improved colorectal polyp detection during screening colonoscopies.

Latest digital whole-body PET scanners provide a combination of higher sensitivity and improved spatial and timing resolution. We performed a lesion detectability study on two generations of Siemens Biograph PET/CT scanners, the mCT and Vision, to study the impact of improved physical performance on clinical performance. Our hypothesis is that the improved performance of the Vision will result in improved lesion detectability, allowing shorter imaging times or equivalently, lower injected dose. Methods: Data were acquired with the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network torso phantom combined with a 20-cm diameter cylindrical phantom. Spherical lesions were emulated by acquiring spheres-in-air data, and combining it with the phantom data to generate combined datasets with embedded lesions of known contrast. Two sphere sizes and uptakes were used: 9.89 mm diameter spheres with 6:1 (lung) and 3:1 (cylinder) and 4.95 mm diameter spheres with 9.6:1 (lung) and 4.5:1 (cylinder) local activity concentration uptakes. Standard image reconstruction was performed: ordinary Poisson ordered subsets expectation maximization algorithm with point spread function and time-of-flight modeling and post-reconstruction smoothing with a 5 mm Gaussian filter. The Vision images were also generated without any post-reconstruction smoothing. Generalized scan statistics methodology was used to estimate the area under the localization receiver operating characteristic curve (ALROC). Results: Higher sensitivity and improved TOF performance of Vision leads to reduced contrast in the background noise nodule distribution. Measured lesion contrast is also higher on the Vision due to its improved spatial resolution. Hence, the ALROC values are noticeably higher for the Vision relative to the mCT. Conclusion: Improved overall performance of the Vision provides a factor of 4-6 reduction in imaging time (or injected dose) over the mCT when using the ALROC metric for lesions >9.89 mm in diameter. Smaller lesions are barely detected in the mCT, leading to even higher ALROC gains with the Vision. Improved spatial resolution of the Vision also leads to a higher measured contrast that is closer to the real uptake, implying improved quantification. Post-reconstruction smoothing, however, reduces this improvement in measured contrast, thereby reducing the ALROC values for small, high uptake lesions.

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.

We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.

Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Ankylosing Spondylitis (AS) is a common, inflammatory rheumatic disease, which primarily affects the axial skeleton and is associated with sacroiliitis, uveitis and enthesitis. Unlike other autoimmune rheumatic diseases, such as rheumatoid arthritis or systemic lupus erythematosus, autoantibodies have not yet been reported to be a feature of AS. We therefore wished to determine if plasma from patients with AS contained autoantibodies and if so, characterize and quantify this response in comparison to patients with Rheumatoid Arthritis (RA) and healthy controls. Two high-density nucleic acid programmable protein arrays expressing a total of 3498 proteins were screened with plasma from 25 patients with AS, 17 with RA and 25 healthy controls. Autoantigens identified were subjected to Ingenuity Pathway Analysis in order to determine patterns of signalling cascades or tissue origin. 44% of patients with Ankylosing Spondylitis demonstrated a broad autoantibody response, as compared to 33% of patients with RA and only 8% of healthy controls. Individuals with AS demonstrated autoantibody responses to shared autoantigens, and 60% of autoantigens identified in the AS cohort were restricted to that group. The AS patients autoantibody responses were targeted towards connective, skeletal and muscular tissue, unlike those of RA patients or healthy controls. Thus, patients with AS show evidence of systemic humoral autoimmunity and multispecific autoantibody production. Nucleic Acid Programmable Protein Arrays constitute a powerful tool to study autoimmune diseases.

Diabetic retinopathy (DR) is diagnosed clinically by directly viewing retinal vascular changes during ophthalmoscopy or through fundus photographs. However, electroretinography (ERG) studies in humans and rodents have revealed that retinal dysfunction is demonstrable prior to the development of visible vascular defects. Specifically, delays in dark-adapted ERG oscillatory potential (OP) implicit times in response to dim flash stimuli (<-1.8 log cd·s/m²) occur prior to clinically-recognized diabetic retinopathy. Animal studies suggest that retinal dopamine deficiency underlies these early functional deficits. Here, we randomized persons with diabetes, without clinically detectable retinopathy, to treatment with either low or high dose Sinemet (levodopa plus carbidopa) for 2 weeks and compared their ERG findings with those of control (no DM) subjects. We assessed dim flash stimulated OP delays using a novel hand-held ERG system (RETeval) at baseline, 2 and 4 weeks. RETeval recordings identified significant OP implicit-time delays in persons with diabetes without retinopathy compared to age-matched controls (p<0.001). After two weeks of Sinemet treatment, OP implicit times were restored to control values, and these improvements persisted even after a two-week washout. We conclude that detection of dim flash OP delays could provide early detection of DR, and that Sinemet treatment may reverse retinal dysfunction.

Assessing young people with possible eating disorders can be complex for a variety of reasons. Building a therapeutic relationship with a young person with a possible eating disorder and their family is key to enabling a thorough assessment and ongoing management, but it introduces difficult issues regarding confidentiality and risk. In this...

London : D. Bogue, 1881.

Daren Wang, Yi Yu, Alessandro Rinaldo.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1917--1961.

Abstract:
The problem of univariate mean change point detection and localization based on a sequence of $n$ independent observations with piecewise constant means has been intensively studied for more than half century, and serves as a blueprint for change point problems in more complex settings. We provide a complete characterization of this classical problem in a general framework in which the upper bound $sigma ^{2}$ on the noise variance, the minimal spacing $Delta $ between two consecutive change points and the minimal magnitude $kappa $ of the changes, are allowed to vary with $n$. We first show that consistent localization of the change points is impossible in the low signal-to-noise ratio regime $frac{kappa sqrt{Delta }}{sigma }preceq sqrt{log (n)}$. In contrast, when $frac{kappa sqrt{Delta }}{sigma }$ diverges with $n$ at the rate of at least $sqrt{log (n)}$, we demonstrate that two computationally-efficient change point estimators, one based on the solution to an $ell _{0}$-penalized least squares problem and the other on the popular wild binary segmentation algorithm, are both consistent and achieve a localization rate of the order $frac{sigma ^{2}}{kappa ^{2}}log (n)$. We further show that such rate is minimax optimal, up to a $log (n)$ term.

Zhixin Zhou, Ping Li.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1302--1347.

Abstract:
The Chernoff coefficient is known to be an upper bound of Bayes error probability in classification problem. In this paper, we will develop a rate optimal Chernoff bound on the Bayes error probability. The new bound is not only an upper bound but also a lower bound of Bayes error probability up to a constant factor. Moreover, we will apply this result to community detection in the stochastic block models. As a clustering problem, the optimal misclassification rate of community detection problem can be characterized by our rate optimal Chernoff bound. This can be formalized by deriving a minimax error rate over certain parameter space of stochastic block models, then achieving such an error rate by a feasible algorithm employing multiple steps of EM type updates.

Ery Arias-Castro, Rong Huang, Nicolas Verzelen.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 702--730.

Abstract:
In a bivariate setting, we consider the problem of detecting a sparse contamination or mixture component, where the effect manifests itself as a positive dependence between the variables, which are otherwise independent in the main component. We first look at this problem in the context of a normal mixture model. In essence, the situation reduces to a univariate setting where the effect is a decrease in variance. In particular, a higher criticism test based on the pairwise differences is shown to achieve the detection boundary defined by the (oracle) likelihood ratio test. We then turn to a Gaussian copula model where the marginal distributions are unknown. Standard invariance considerations lead us to consider rank tests. In fact, a higher criticism test based on the pairwise rank differences achieves the detection boundary in the normal mixture model, although not in the very sparse regime. We do not know of any rank test that has any power in that regime.

In statistical learning framework with regressions, interactions are the contributions to the response variable from the products of the explanatory variables. In high-dimensional problems, detecting interactions is challenging due to combinatorial complexity and limited data information. We consider detecting interactions by exploring their connections with the principal Hessian matrix. Specifically, we propose a one-step synthetic approach for estimating the principal Hessian matrix by a penalized M-estimator. An alternating direction method of multipliers (ADMM) is proposed to efficiently solve the encountered regularized optimization problem. Based on the sparse estimator, we detect the interactions by identifying its nonzero components. Our method directly targets at the interactions, and it requires no structural assumption on the hierarchy of the interactions effects. We show that our estimator is theoretically valid, computationally efficient, and practically useful for detecting the interactions in a broad spectrum of scenarios.

Anomaly detection is not an easy problem since distribution of anomalous samples is unknown a priori. We explore a novel method that gives a trade-off possibility between one-class and two-class approaches, and leads to a better performance on anomaly detection problems with small or non-representative anomalous samples. The method is evaluated using several data sets and compared to a set of conventional one-class and two-class approaches.

Clément Marteau, Theofanis Sapatinas.

Source: Statistics Surveys, Volume 9, 253--297.

Abstract:
We are concerned with minimax signal detection. In this setting, we discuss non-asymptotic and asymptotic approaches through a unified treatment. In particular, we consider a Gaussian sequence model that contains classical models as special cases, such as, direct, well-posed inverse and ill-posed inverse problems. Working with certain ellipsoids in the space of squared-summable sequences of real numbers, with a ball of positive radius removed, we compare the construction of lower and upper bounds for the minimax separation radius (non-asymptotic approach) and the minimax separation rate (asymptotic approach) that have been proposed in the literature. Some additional contributions, bringing to light links between non-asymptotic and asymptotic approaches to minimax signal, are also presented. An example of a mildly ill-posed inverse problem is used for illustrative purposes. In particular, it is shown that tools used to derive ‘asymptotic’ results can be exploited to draw ‘non-asymptotic’ conclusions, and vice-versa. In order to enhance our understanding of these two minimax signal detection paradigms, we bring into light hitherto unknown similarities and links between non-asymptotic and asymptotic approaches.

Building a scalable machine learning system for unsupervised anomaly detection via representation learning is highly desirable. One of the prevalent methods is using a reconstruction error from variational autoencoder (VAE) via maximizing the evidence lower bound. We revisit VAE from the perspective of information theory to provide some theoretical foundations on using the reconstruction error, and finally arrive at a simpler and more effective model for anomaly detection. In addition, to enhance the effectiveness of detecting anomalies, we incorporate a practical model uncertainty measure into the metric. We show empirically the competitive performance of our approach on benchmark datasets.

Datasets in sleep science present challenges for machine learning algorithms due to differences in recording setups across clinics. We investigate two deep transfer learning strategies for overcoming the channel mismatch problem for cases where two datasets do not contain exactly the same setup leading to degraded performance in single-EEG models. Specifically, we train a baseline model on multivariate polysomnography data and subsequently replace the first two layers to prepare the architecture for single-channel electroencephalography data. Using a fine-tuning strategy, our model yields similar performance to the baseline model (F1=0.682 and F1=0.694, respectively), and was significantly better than a comparable single-channel model. Our results are promising for researchers working with small databases who wish to use deep learning models pre-trained on larger databases.

The paper focuses on a novel approach for false-positive reduction (FPR) of nodule candidates in Computer-aided detection (CADe) system after suspicious lesions proposing stage. Unlike common decisions in medical image analysis, the proposed approach considers input data not as 2d or 3d image, but as a point cloud and uses deep learning models for point clouds. We found out that models for point clouds require less memory and are faster on both training and inference than traditional CNN 3D, achieves better performance and does not impose restrictions on the size of the input image, thereby the size of the nodule candidate. We propose an algorithm for transforming 3d CT scan data to point cloud. In some cases, the volume of the nodule candidate can be much smaller than the surrounding context, for example, in the case of subpleural localization of the nodule. Therefore, we developed an algorithm for sampling points from a point cloud constructed from a 3D image of the candidate region. The algorithm guarantees to capture both context and candidate information as part of the point cloud of the nodule candidate. An experiment with creating a dataset from an open LIDC-IDRI database for a feature of the FPR task was accurately designed, set up and described in detail. The data augmentation technique was applied to avoid overfitting and as an upsampling method. Experiments are conducted with PointNet, PointNet++ and DGCNN. We show that the proposed approach outperforms baseline CNN 3D models and demonstrates 85.98 FROC versus 77.26 FROC for baseline models.

Subhadeep Paul, Yuguo Chen.

Source: The Annals of Statistics, Volume 48, Number 1, 230--250.

Abstract:
We consider the problem of estimating a consensus community structure by combining information from multiple layers of a multi-layer network using methods based on the spectral clustering or a low-rank matrix factorization. As a general theme, these “intermediate fusion” methods involve obtaining a low column rank matrix by optimizing an objective function and then using the columns of the matrix for clustering. However, the theoretical properties of these methods remain largely unexplored. In the absence of statistical guarantees on the objective functions, it is difficult to determine if the algorithms optimizing the objectives will return good community structures. We investigate the consistency properties of the global optimizer of some of these objective functions under the multi-layer stochastic blockmodel. For this purpose, we derive several new asymptotic results showing consistency of the intermediate fusion techniques along with the spectral clustering of mean adjacency matrix under a high dimensional setup, where the number of nodes, the number of layers and the number of communities of the multi-layer graph grow. Our numerical study shows that the intermediate fusion techniques outperform late fusion methods, namely spectral clustering on aggregate spectral kernel and module allegiance matrix in sparse networks, while they outperform the spectral clustering of mean adjacency matrix in multi-layer networks that contain layers with both homophilic and heterophilic communities.

Silvia Metelli, Nicholas Heard.

Source: The Annals of Applied Statistics, Volume 13, Number 4, 2586--2610.

Abstract:
Monitoring computer network traffic for anomalous behaviour presents an important security challenge. Arrivals of new edges in a network graph represent connections between a client and server pair not previously observed, and in rare cases these might suggest the presence of intruders or malicious implants. We propose a Bayesian model and anomaly detection method for simultaneously characterising existing network structure and modelling likely new edge formation. The method is demonstrated on real computer network authentication data and successfully identifies some machines which are known to be compromised.

Gregor Thut
Sep 13, 2006; 26:9494-9502
BehavioralSystemsCognitive

We consider the question of how sensory networks enable the detection of sensory stimuli in a combinatorial coding space. We are specifically interested in the olfactory system, wherein recent experimental studies have reported the existence of rich, enigmatic response patterns associated with stimulus onset and offset. This study aims to identify the functional relevance of such response patterns (i.e., what benefits does such neural activity provide in the context of detecting stimuli in a natural environment). We study this problem through the lens of normative, optimization-based modeling. Here, we define the notion of a low-dimensional latent representation of stimulus identity, which is generated through action of the sensory network. The objective of our optimization framework is to ensure high-fidelity tracking of a nominal representation in this latent space in an energy-efficient manner. It turns out that the optimal motifs emerging from this framework possess morphologic similarity with prototypical onset and offset responses observed in vivo in locusts (Schistocerca americana) of either sex. Furthermore, this objective can be exactly achieved by a network with reciprocal excitatory–inhibitory competitive dynamics, similar to interactions between projection neurons and local neurons in the early olfactory system of insects. The derived model also makes several predictions regarding maintenance of robust latent representations in the presence of confounding background information and trade-offs between the energy of sensory activity and resultant behavioral measures such as speed and accuracy of stimulus detection.

SIGNIFICANCE STATEMENT A key area of study in olfactory coding involves understanding the transformation from high-dimensional sensory stimulus to low-dimensional decoded representation. Here, we examine not only the dimensionality reduction of this mapping but also its temporal dynamics, with specific focus on stimuli that are temporally continuous. Through optimization-based synthesis, we examine how sensory networks can track representations without prior assumption of discrete trial structure. We show that such tracking can be achieved by canonical network architectures and dynamics, and that the resulting responses resemble observations from neurons in the insect olfactory system. Thus, our results provide hypotheses regarding the functional role of olfactory circuit activity at both single neuronal and population scales.

Systematic screening for child abuse of all children presenting at emergency departments might increase the detection rate of child abuse but studies to support this proposal are scarce.

Systematic screening for child abuse in emergency departments is effective in increasing the detection of suspected child abuse. Training emergency department staff and requiring screening legally at emergency departments increase the extent of screening. (Read the full article)

Fever without an apparent source is common in children. Currently in the United States, serious bacterial infection is uncommonly the cause. Most cases are assumed to be viral, but the specific viral causes have not been delineated. Antibiotics are frequently prescribed.

By using polymerase chain reaction, we detected pathogenic viruses frequently in children with fever without an apparent source. Adenovirus, human herpesvirus-6, enterovirus, and parechovirus were predominant. Testing of blood had high yield. Better recognition of viral etiologies may help reduce unnecessary antibiotic use. (Read the full article)

There is evidence that Kingella kingae, the major bacterial cause of osteoarticular infection in children <4 years of age, first colonizes the oropharynx before penetrating the bloodstream and invading distant organs. Diagnosis remains challenging because clinical findings at admission may be normal.

Our study demonstrated for the first time that a simple technique of detecting of K kingae DNA in the oropharynx can provide strong evidence that this microorganism is responsible for the OAI, or even stronger evidence that it is not. (Read the full article)

Newborns with critical congenital heart disease (CCHD) are at risk for cardiovascular collapse or death if discharged from the birth hospital without a diagnosis. Newborn screening aims to identify CCHD missed in prenatal and postnatal examinations.

Birth hospital nursery level and CCHD type were found to be associated with late CCHD detection. Routine newborn screening could conceivably reduce differences in the frequency of late diagnosis between birth hospital facilities. (Read the full article)

Early diagnosis of LOS in preterm infants may be challenging because of the questionable accuracy of blood culture and the common markers of infections, such as C-reactive protein and procalcitonin.

Our study demonstrated for the first time that P-SEP is an accurate biomarker for the diagnosis of LOS in preterm infants and might contribute to the monitoring of infant response to therapeutic interventions. (Read the full article)

Handheld echocardiography is a more portable and lower-cost alternative to standard echocardiography for rheumatic heart disease screening. Direct comparison of handheld echocardiography and auscultation for the detection of rheumatic heart disease has not been done previously.

Handheld echocardiography significantly improves detection of rheumatic heart disease compared with auscultation alone and may be a cost-effective screening strategy in developing countries. (Read the full article)

Parents generally adapt well to newborn screening results, but reactions to carrier status for X-linked conditions are unknown.

Results suggest that detection and disclosure of FMR1 newborn carrier status may not result in significant adverse events for mothers. (Read the full article)

The rapid evolution of resistance in the malaria parasite to every single drug developed against it calls for the urgent identification of new molecular targets. Using a stain specific for the detection of intracellular amyloid deposits in live cells we have detected the presence of abundant protein aggregates in Plasmodium falciparum blood stages and female gametes cultured in vitro, in the blood stages of mice infected by Plasmodium yoelii, and in the mosquito stages of the murine malaria species Plasmodium berghei. Aggregated proteins could not be detected in early rings, the parasite form that starts the intraerythrocytic cycle. A proteomics approach was followed to pinpoint actual aggregating polypeptides in functional P. falciparum blood stages, which resulted in the identification of 369 proteins, with roles particularly enriched in nuclear import-related processes. Five aggregation-prone short peptides selected from this protein pool exhibited different aggregation propensity according to Thioflavin-T fluorescence measurements, and were observed to form amorphous aggregates and amyloid fibrils in transmission electron microscope images. The results presented suggest that generalized protein aggregation might have a functional role in malaria parasites. Future antimalarial strategies based on the upsetting of the pathogen's proteostasis and therefore affecting multiple gene products could represent the entry to new therapeutic approaches.

Agency: GSS Closing Date: 5/28/2020

Seismic noise is a relatively persistent vibration of the ground that is usually an unwanted component of signals recorded by seismometers, according to the scientists.

Malmon is a real-time exploit/backdoor detection tool for Linux that audits the integrity of files in a given directory.

Malmon is a real-time exploit/backdoor detection tool for Linux that audits the integrity of files in a given directory.

Whitepaper called Bypassing Root Detection Mechanism. Written in Persian.

The Health Sector Development Program, supported by the ADF facility and additional ADF grant funding for a total of $20 million, is improving primary health care delivery and information systems in Bhutan.

Title: Implants May Delay Breast Cancer Detection, Raise Death Risk
Category: Health News
Created: 4/30/2013 8:35:00 PM
Last Editorial Review: 5/1/2013 12:00:00 AM

BACKGROUND AND OBJECTIVES:

Early diagnosis of cerebral palsy (CP) is critical in obtaining evidence-based interventions when plasticity is greatest. In 2017, international guidelines for early detection of CP were published on the basis of a systematic review of evidence. Our study aim was to reduce the age at CP diagnosis throughout a network of 5 diverse US high-risk infant follow-up programs through consistent implementation of these guidelines.

Current pneumococcal vaccines cover the 10 to 23 most common serotypes of the 92 presently described. However, with the increased usage of pneumococcal-serotype-based vaccines, the risk of serotype replacement and an increase in disease caused by nonvaccine serotypes remains. Serotype surveillance of pneumococcal infections relies heavily on culture techniques, which are known to be insensitive, particularly in cases of noninvasive disease. Pneumococcal-serotype-specific urine assays offer an alternative method of serotyping for both invasive and noninvasive disease. However, the assays described previously cover mainly conjugate vaccine serotypes, give little information about circulating nonvaccine serotypes, and are currently available only in one or two specialist laboratories. Our laboratory has developed a Luminex-based extended-range antigen capture assay to detect pneumococcal-serotype-specific antigens in urine samples. The assay targets 24 distinct serotypes/serogroups plus the cell wall polysaccharide (CWP) and some cross-reactive serotypes. We report that the assay is capable of detecting all the targeted serotypes and the CWP at 0.1 ng/ml, while some serotypes are detected at concentrations as low as 0.3 pg/ml. The analytical serotype specificity was determined to be 98.4% using a panel of polysaccharide-negative urine specimens spiked with nonpneumococcal bacterial antigens. We also report clinical sensitivities of 96.2% and specificities of 89.9% established using a panel of urine specimens from patients diagnosed with community-acquired pneumonia or pneumococcal disease. This assay can be extended for testing other clinical samples and has the potential to greatly improve serotype-specific surveillance in the many cases of pneumococcal disease in which a culture is never obtained.

Accurate detection of influenza A virus (IAV) is crucial for patient management, infection control, and epidemiological surveillance. The World Health Organization and the Centers for Disease Control and Prevention have recommended using the M gene as the diagnostic gene target for reverse-transcription-PCR (RT-PCR). However, M gene RT-PCR has reduced sensitivity for recent IAV due to novel gene mutations. Here, we sought to identify novel diagnostic targets for the molecular detection of IAV using long-read third-generation sequencing. Direct nanopore sequencing from 18 nasopharyngeal specimens and one saliva specimen showed that the 5' and 3' ends of the PB2 gene and the entire NS gene were highly abundant. Primers selected for PB2 and NS genes were well matched with seasonal or avian IAV gene sequences. Our novel PB2 and NS gene real-time RT-PCR assays showed limits of detection similar to or lower than that of M gene RT-PCR and achieved 100% sensitivity and specificity in the detection of A(H1N1), A(H3N2), and A(H7N9) in nasopharyngeal and saliva specimens. For 10 patients with IAV detected by M gene RT-PCR conversion in sequentially collected specimens, NS and/or PB2 gene RT-PCR was positive in 2 (20%) of the initial specimens that were missed by M gene RT-PCR. In conclusion, we have shown that PB2 or NS gene RT-PCRs are suitable alternatives to the recommended M gene RT-PCR for diagnosis of IAV. Long-read nanopore sequencing facilitates the identification of novel diagnostic targets.

Routine identification of fungal pathogens from positive blood cultures by culture-based methods can be time-consuming, delaying treatment with appropriate antifungal agents. The GenMark Dx ePlex investigational use only blood culture identification fungal pathogen panel (BCID-FP) rapidly detects 15 fungal targets simultaneously in blood culture samples positive for fungi by Gram staining. We aimed to determine the performance of the BCID-FP in a multicenter clinical study. Blood culture samples collected at 10 United States sites and tested with BCID-FP at 4 sites were compared to the standard-of-care microbiological and biochemical techniques, fluorescence in situ hybridization using peptide nucleic acid probes (PNA-FISH) and matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS). Discrepant results were analyzed by bi-directional PCR/sequencing of residual blood culture samples. A total of 866 clinical samples, 120 retrospectively and 21 prospectively collected, along with 725 contrived samples were evaluated. Sensitivity and specificity of detection of Candida species (C. albicans, C. auris, C. dubliniensis, C. famata, C. glabrata, C. guilliermondii, C. kefyr, C. krusei, C. lusitaniae, C. parapsilosis, and C. tropicalis) ranged from 97.1 to 100% and 99.8 to 100%, respectively. For the other organism targets, sensitivity and specificity were as follows: 100% each for Cryptococcus neoformans and C. gattii, 98.6% and 100% for Fusarium spp., and 96.2% and 99.9% for Rhodotorula spp., respectively. In 4 of the 141 clinical samples, the BCID-FP panel correctly identified an additional Candida species, undetected by standard-of-care methods. The BCID-FP panel offers a faster turnaround time for identification of fungal pathogens in positive blood cultures that may allow for earlier antifungal interventions and includes C. auris, a highly multidrug-resistant fungus.

Microscopy and rapid diagnostic tests (RDTs) are the main diagnostic tools for malaria but fail to detect low-density parasitemias that are important for maintaining malaria transmission. To complement existing diagnostic methods, an isothermal reverse transcription-recombinase polymerase amplification and lateral flow assay (RT-RPA) was developed. We compared the performance with that of ultrasensitive reverse transcription-quantitative PCR (uRT-qPCR) using nucleic acid extracts from blood samples (n = 114) obtained after standardized controlled human malaria infection (CHMI) with Plasmodium falciparum sporozoites. As a preliminary investigation, we also sampled asymptomatic individuals (n = 28) in an area of malaria endemicity (Lambaréné, Gabon) to validate RT-RPA and assess its performance with unprocessed blood samples (dbRT-RPA). In 114 samples analyzed from CHMI trials, the positive percent agreement to uRT-qPCR was 90% (95% confidence interval [CI], 80 to 96). The negative percent agreement was 100% (95% CI, 92 to 100). The lower limit of detection was 64 parasites/ml. In Gabon, RT-RPA was 100% accurate with asymptomatic volunteers (n = 28), while simplified dbRT-RPA showed 89% accuracy. In a subgroup analysis, RT-RPA detected 9/10 RT-qPCR-positive samples, while loop-mediated isothermal amplification (LAMP) detected 2/10. RT-RPA is a reliable diagnostic test for asymptomatic low-density infections. It is particularly useful in settings where uRT-qPCR is difficult to implement.

Human granulocytic anaplasmosis (HGA) is a tick-borne disease caused by the obligate intracellular Gram-negative bacterium Anaplasma phagocytophilum. The disease often presents with nonspecific symptoms with negative serology during the acute phase. Direct pathogen detection is the best approach for early confirmatory diagnosis. Over the years, PCR-based molecular detection methods have been developed, but optimal sensitivity is not achieved by conventional PCR while real-time PCR requires expensive and sophisticated instruments. To improve the sensitivity and also develop an assay that can be used in resource-limited areas, an isothermal DNA amplification assay based on recombinase polymerase amplification (RPA) was developed. To do this, we identified a 171-bp DNA sequence within multiple paralogous copies of msp2 within the genome of A. phagocytophilum. Our novel RPA assay targeting this sequence has an analytical limit of detection of one genome equivalent copy of A. phagocytophilum and can reliably detect 125 bacteria/ml in human blood. A high level of specificity was demonstrated by the absence of nonspecific amplification using genomic DNA from human or DNA from other closely-related pathogenic bacteria, such as Anaplasma platys, Ehrlichia chaffeensis, Orientia tsutsugamushi, and Rickettsia rickettsii, etc. When applied to patient DNA extracted from whole blood, this new RPA assay was able to detect 100% of previously diagnosed A. phagocytophilum cases. The sensitivity and rapidness of this assay represents a major improvement for early diagnosis of A. phagocytophilum in human patients and suggest a role for better surveillance in its reservoirs or vectors, especially in remote regions where resources are limited.

Limited treatment options contribute to high morbidity/mortality rates with carbapenem-resistant, Gram-negative bacterial infections. New approaches for carbapenemase-producing organism (CPO) detection may help inform clinician decision-making on patient treatment and infection control. BD Phoenix CPO detect (CPO detect) detects and classifies carbapenemases in Enterobacterales, Acinetobacter baumannii, and Pseudomonas aeruginosa during susceptibility testing. The clinical performance of CPO detect is reported here. Enterobacterales, Acinetobacter baumannii, and Pseudomonas aeruginosa isolates were evaluated across three sites using CPO detect and a composite reference method (RM); the latter was comprised of the modified carbapenem inactivation method and a MIC screen for ertapenem, imipenem, and meropenem. Multiplex PCR testing was also utilized for Ambler class determination. Positive and negative percentages of agreement (PPA and NPA, respectively) between CPO detect and the RM were determined. The PPA and NPA for Enterobacterales were 98.5% (confidence intervals, 96.6%, 99.4%) and 97.2% (95.8%, 98.2%), respectively. The A. baumannii PPA and NPA, respectively, were 97.1% (90.2%, 99.2%) and 97.1% (89.9%, 99.2%). The P. aeruginosa PPA and NPA, respectively, were 95.9% (88.6%, 98.6%) and 92.3% (86.7%, 95.6%). The PPA values for carbapenemase class designations for all organisms combined and Enterobacterales alone, respectively, were 95.3% (90.2%, 97.8%) and 94.6% (88.8%, 97.5%) for class A, 94.0% (88.7%, 96.6%) and 96.4% (90.0%, 98.8%) for class B, and 95.0% (90.1%, 97.6%) and 99.0% (94.4%, 99.8%) for class D carbapenemases. NPA values for all organisms and Enterobacterales alone ranged from 98.5% to 100%. CPO detect provided accurate detection and classification of CPOs for the majority of isolates of Enterobacterales, Acinetobacter baumannii, and Pseudomonas aeruginosa tested.