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The FDA published a final rule for Medical Devices; Laboratory Developed Tests in the Federal Register on May 6, 2024, which aims to ensure the safety and effectiveness of laboratory developed tests (LDTs) by amending current regulations. The rule also includes a policy to phase out the FDA's general enforcement discretion approach for LDTs, aligning them with other In Vitro Diagnostic Devices. Notably, direct-to-consumer (DTC) testing is exempt from this policy shift, as the FDA believes this category of tests has already met applicable requirements. This rule was first proposed in the Federal Register on October 3, 2023. The publication of this proposed rule sparked a considerable volume of public reactions during the comment period of the rule-making process, comprising general sentiment, key concerns, and suggestions. This commentary analyzes these concerns, particularly focusing on DTC tests, and offers recommendations, including reassessing the FDA's enforcement discretion for hybrid DTC tests, advocating for clear guidance on clinical oversight, and prioritizing a risk-based enforcement approach. Additionally, enhancing public education about the risks of DTC testing is crucial for safeguarding public health. [ABSTRACT FROM AUTHOR]

Diffusion MRI is a modern neuroimaging modality with a unique ability to acquire microstructural information by measuring water self-diffusion at the voxel level. However, it generates huge amounts of data, resulting from a large number of repeated 3D scans. Each volume samples a location in q-space, indicating the direction and strength of a diffusion sensitizing gradient during the measurement. This captures detailed information about the self-diffusion and the tissue microstructure that restricts it. Lossless compression with GZIP is widely used to reduce the memory requirements. We introduce a novel lossless codec for diffusion MRI data. It reduces file sizes by more than 30% compared to GZIP and also beats lossless codecs from the JPEG family. Our codec builds on recent work on lossless PDE-based compression of 3D medical images, but additionally exploits smoothness in q-space. We demonstrate that, compared to using only image space PDEs, q-space PDEs further improve compression rates. Moreover, implementing them with finite element methods and a custom acceleration significantly reduces computational expense. Finally, we show that our codec clearly benefits from integrating subject motion correction and slightly from optimizing the order in which the 3D volumes are coded. [ABSTRACT FROM AUTHOR]

Purpose: Sparse inverse covariance estimation (SICE) is increasingly utilized to estimate inter-subject covariance of FDG uptake (FDGcov) as proxy of metabolic brain connectivity. However, this statistical method suffers from the lack of robustness in the connectivity estimation. Patterns of FDGcov were observed to be spatially similar with patterns of structural connectivity as obtained from DTI imaging. Based on this similarity, we propose to regularize the sparse estimation of FDGcov using the structural connectivity. Methods: We retrospectively analyzed the FDG-PET and DTI data of 26 healthy controls, 41 patients with Alzheimer's disease (AD), and 30 patients with frontotemporal lobar degeneration (FTLD). Structural connectivity matrix derived from DTI data was introduced as a regularization parameter to assign individual penalties to each potential metabolic connectivity. Leave-one-out cross validation experiments were performed to assess the differential diagnosis ability of structure weighted SICE approach. A few approaches of structure weighted were compared with the standard SICE. Results: Compared to the standard SICE, structural weighting has shown more stable performance in the supervised classification, especially in the differentiation AD vs. FTLD (accuracy of 89–90%, while unweighted SICE only 85%). There was a significant positive relationship between the minimum number of metabolic connection and the robustness of the classification accuracy (r = 0.57, P < 0.001). Shuffling experiments showed significant differences between classification score derived with true structural weighting and those obtained by randomized structure (P < 0.05). Conclusion: The structure-weighted sparse estimation can enhance the robustness of metabolic connectivity, which may consequently improve the differentiation of pathological phenotypes. [ABSTRACT FROM AUTHOR]

Background: Stakeholder engagement helps ensure that research is relevant, clinical innovations are responsive, and healthcare services are patient-centered. Objective: Establish and sustain a Veteran engagement board involving older Veterans and caregivers to provide input on aging-related research and clinical demonstration projects. Design and Participants: The Older Veteran Engagement Team (OVET)—a group of eight Veterans and one caregiver who range in age from 62 to 92—was formed in November 2017 and has met monthly since January 2018. The OVET provides feedback on topics that reflect the foci of the VA Eastern Colorado Geriatric Research Education and Clinical Center (GRECC) (e.g., physical functioning, hearing health, and emotional wellness/mental health). Ongoing evaluation documents the return on investment of Veteran engagement. Main Measures: The OVET member and provider/investigator meeting evaluations with longitudinal follow-up at 6 and 12 months. Results: Return on investment of Veteran engagement is multi-faceted. For OVET, ROI ranges from grant support to improved healthcare quality/efficiency to social-emotional benefits. To date, funding awards total over $2.3 M for NIH and VA-funded projects to which OVET provided substantive feedback. Documented impacts on healthcare services include reductions in patient wait times, more appropriate utilization of services and increased patient satisfaction. Social-emotional benefits include generativity, as OVET members contribute to improving clinical and community-based supports for other Veterans. The OVET provides an opportunity for older Veterans to share their lived experience with trainees and early career investigators who are preparing for careers serving Veterans. Conclusion: The OVET is similar to other established stakeholder engagement groups; team members offer their individual viewpoints at any stage of research, clinical demonstration, or quality improvement projects. The OVET provides a mechanism for the voice of older Veterans and caregivers to shape aspects of individual projects. Importantly, these projects support patient-centered care and promote the characteristics of an age-friendly healthcare system. [ABSTRACT FROM AUTHOR]

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Copyright of Der Ophthalmologe is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Peripheral arterial disease (PAD) is caused by atherosclerosis and is a common disease of the elderly leading to excess morbidity and mortality. Early PAD diagnosis is important, as the only available causal therapy is addressing risk factors like smoking, hypercholesterolemia or hypertension. However, current diagnostic techniques often do not detect early stages of PAD. We theorize that PAD's underlying cause atherosclerosis can be detected on color fundus photography (CFP) images with a convolutional neural network architecture, which might aid earlier PAD diagnosis and improve disease monitoring. In this explorative study a deep attention-based Multiple Instance Learning (MIL) architecture is used to capture retinal imaging biomarkers on CFP images of 135 examinations. To capture subtle variations in vascular structures, higher image resolution can be utilized by partitioning the CFP into patches. Our architecture converts each patch into a feature vector, and determines its relative importance via an automatically computed attention weight. Our best model achieves an ROC AUC score of 0.890. Visualizing these attention weights provides insights about the network's decision and suggests ocular involvement in PAD. Statistical analysis confirms that the optic disc and the temporal arcades are weighted significantly higher (p < 0.001) than retinal background. Our results support the feasibility of detecting the presence of PAD with a modern deep learning approach. [ABSTRACT FROM AUTHOR]

Purpose: T2-weighted signal hyperintensities in white matter (WM) are a diagnostic finding in brain magnetic resonance imaging (MRI) of patients with metachromatic leukodystrophy (MLD). In our systematic investigation of the evolution of T2-hyperintensities in patients with the late-infantile form, we describe and characterize T2-pseudonormalization in the advanced stage of the natural disease course. Methods: The volume of T2-hyperintensities was quantified in 34 MRIs of 27 children with late-infantile MLD (median age 2.25 years, range 0.5–5.2 years). In three children with the most advanced clinical course (age >4 years) and for whom the T2-pseudonormalization was the most pronounced, WM microstructure was investigated using a multimodal MRI protocol, including diffusion-weighted imaging, MR spectroscopy (MRS), myelin water fraction (MWF), magnetization transfer ratio (MTR), T1-mapping and quantitative susceptibility mapping. Results: T2-hyperintensities in cerebral WM returned to normal in large areas of 3 patients in the advanced disease stage. Multimodal assessment of WM microstructure in areas with T2-pseudonormalization revealed highly decreased values for NAA, neurite density, isotropic water, mean and radial kurtosis, MWF and MTR, as well as increased radial diffusivity. Conclusion: In late-infantile MLD patients, we found T2-pseudonormalization in WM tissue with highly abnormal microstructure characterizing the most advanced disease stage. Pathological hallmarks might be a loss of myelin, but also neuronal loss as well as increased tissue density due to gliosis and accumulated storage material. These results suggest that a multimodal MRI protocol using more specific microstructural parameters than T2-weighted sequences should be used when evaluating the effect of treatment trials in MLD. [ABSTRACT FROM AUTHOR]

Here, we investigate the extent to which re-implementing a previously published algorithm for OCT-based drusen quantification permits replicating the reported accuracy on an independent dataset. We refined that algorithm so that its accuracy is increased. Following a systematic literature search, an algorithm was selected based on its reported excellent results. Several steps were added to improve its accuracy. The replicated and refined algorithms were evaluated on an independent dataset with the same metrics as in the original publication. Accuracy of the refined algorithm (overlap ratio 36–52%) was significantly greater than the replicated one (overlap ratio 25–39%). In particular, separation of the retinal pigment epithelium and the ellipsoid zone could be improved by the refinement. However, accuracy was still lower than reported previously on different data (overlap ratio 67–76%). This is the first replication study of an algorithm for OCT image analysis. Its results indicate that current standards for algorithm validation do not provide a reliable estimate of algorithm performance on images that differ with respect to patient selection and image quality. In order to contribute to an improved reproducibility in this field, we publish both our replication and the refinement, as well as an exemplary dataset. [ABSTRACT FROM AUTHOR]

The purpose of this study was to assess if clinical indications, patient location, and imaging sites predict the viewing pattern of referring physicians for CT and MR of the head, chest, and abdomen. Our study included 166,953 CT/MR images of head/chest/abdomen in 2016–2017 in the outpatient (OP, n = 83,981 CT/MR), inpatient (IP, n = 51,052), and emergency (ED, n = 31,920) settings. There were 125,329 CT/MR performed in the hospital setting and 41,624 in one of the nine off-campus locations. We extracted information regarding body region (head/chest/abdomen), patient location, and imaging site from the electronic medical records (EPIC). We recorded clinical indications and the number of times referring physicians viewed CT/MR (defined as the number of separate views of imaging in the EPIC). Data were analyzed with the Microsoft SQL and SPSS statistical software. About 33% of IP CT and MR studies are viewed > 6 times compared to 7% for OP and 19% of ED studies (p < 0.001). Conversely, most OP studies (55%) were viewed 1–2 times only, compared to 21% for IP and 38% for ED studies (p < 0.001). In-hospital exams are viewed (≥ 6 views; 39% studies) more frequently than off-campus imaging (≥ 6 views; 17% studies) (p < 0.001). For head CT/MR, certain clinical indications (i.e., stroke) had higher viewing rates compared to other clinical indications such as malignancy, headache, and dizziness. Conversely, for chest CT, dyspnea-hypoxia had much higher viewing rates (> 6 times) in IP (55%) and ED (46%) than in OP settings (22%). Patient location and imaging site regardless of clinical indications have a profound effect on viewing patterns of referring physicians. Understanding viewing patterns of the referring physicians can help guide interpretation priorities and finding communication for imaging exams based on patient location, imaging site, and clinical indications. The information can help in the efficient delivery of patient care. [ABSTRACT FROM AUTHOR]

Ridge and valley enhancing filters are widely used in applications such as vessel detection in medical image computing. When images are degraded by noise or include vessels at different scales, such filters are an essential step for meaningful and stable vessel localization. In this work, we propose a novel multi-scale anisotropic fourth-order diffusion equation that allows us to smooth along vessels, while sharpening them in the orthogonal direction. The proposed filter uses a fourth-order diffusion tensor whose eigentensors and eigenvalues are determined from the local Hessian matrix, at a scale that is automatically selected for each pixel. We discuss efficient implementation using a fast explicit diffusion scheme and demonstrate results on synthetic images and vessels in fundus images. Compared to previous isotropic and anisotropic fourth-order filters, as well as established second-order vessel enhancing filters, our newly proposed one better restores the centerlines in all cases. [ABSTRACT FROM AUTHOR]

Purpose: Develop a multi-fiber tractography method that produces fast and robust results based on input data from a wide range of diffusion MRI protocols, including high angular resolution diffusion imaging, multi-shell imaging, and clinical diffusion spectrum imaging (DSI) Methods: In a unified deconvolution framework for different types of diffusion MRI protocols, we represent fiber orientation distribution functions as higher-order tensors, which permits use of a novel positive definiteness constraint (H-psd) that makes estimation from noisy input more robust. The resulting directions are used for deterministic fiber tracking with branching. Results: We quantify accuracy on simulated data, as well as condition numbers and computation times on clinical data. We qualitatively investigate the benefits when processing suboptimal data, and show direct comparisons to several state-of-the-art techniques. Conclusion: The proposed method works faster than state-of-the-art approaches, achieves higher angular resolution on simulated data with known ground truth, and plausible results on clinical data. In addition to working with the same data as previous methods for multi-tissue deconvolution, it also supports DSI data. [ABSTRACT FROM AUTHOR]

Compound optimization generally requires considering multiple properties in concert and reaching a balance between them. Computationally, this process can be supported by multi-objective optimization methods that produce numerical solutions to an optimization task. Since a variety of comparable multi-property solutions are usually obtained further prioritization is required. However, the underlying multi-dimensional property spaces are typically complex and difficult to rationalize. Herein, an approach is introduced to visualize multi-property landscapes by adapting the concepts of star and parallel coordinates from computer graphics. The visualization method is designed to complement multi-objective compound optimization. We show that visualization makes it possible to further distinguish between numerically equivalent optimization solutions and helps to select drug-like compounds from multi-dimensional property spaces. The methodology is intuitive, applicable to a wide range of chemical optimization problems, and made freely available to the scientific community. [ABSTRACT FROM AUTHOR]

The first record of a lionfish larva Pterois volitans (Linnaeus 1758) collected from the ichthyoplankton in the Atlantic was found within the Yucatan current off the Western Caribbean, near Cancun, Mexico. The postflexion larva measured 8 mm standard length and was collected using a neuston net aboard the NOAA Ship Gordon Gunter on April 10, 2010. Published morphological and meristic characters were initially used for identification; genetic verification using mtDNA followed. The larva showed 3 distinct pigments beneath the parietal spines that were not included in the original larval description of the species. Ageing of sagittal otoliths exhibited 15-16 daily increments indicating a possible spawn in late March. Given that adult lionfish are established along the Mesoamerican barrier reef, oceanographic patterns suggest that the likely origin of this larva may have been from the southern coast of the Mexican Caribbean to Belize or even Honduras. The Yucatan Current is a rapid means for the potential dispersal of lionfish larvae into the Gulf of Mexico and southern Florida. [ABSTRACT FROM AUTHOR]

The circadian clock is required for adaptive responses to daily and seasonal changes in environmental conditions. Light and the circadian clock interact to consolidate the phase of hypocotyl cell elongation to peak at dawn under diurnal cycles in Arabidopsis thaliana. Here we identify a protein complex (called the evening complex)-composed of the proteins encoded by EARLY FLOWERING 3 (ELF3), ELF4 and the transcription-factor-encoding gene LUX ARRHYTHMO (LUX; also known as PHYTOCLOCK 1)-that directly regulates plant growth. ELF3 is both necessary and sufficient to form a complex between ELF4 and LUX, and the complex is diurnally regulated, peaking at dusk. ELF3, ELF4 and LUX are required for the proper expression of the growth-promoting transcription factors encoded by PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and PIF5 (also known as PHYTOCHROME INTERACTING FACTOR 3-LIKE 6) under diurnal conditions. LUX targets the complex to the promoters of PIF4 and PIF5 in vivo. Mutations in PIF4 and/or PIF5 are epistatic to the loss of the ELF4-ELF3-LUX complex, suggesting that regulation of PIF4 and PIF5 is a crucial function of the complex. Therefore, the evening complex underlies the molecular basis for circadian gating of hypocotyl growth in the early evening. [ABSTRACT FROM AUTHOR]

The purpose of our study was to demonstrate the use of Natural Language Processing (Leximer), along with Online Analytic Processing, (NLP-OLAP), for extraction of finding trends in a large radiology practice. Prior studies have validated the Natural Language Processing (NLP) program, Leximer for classifying unstructured radiology reports based on the presence of positive radiology findings ( FPOS) and negative radiology findings ( FNEG). The FPOS included new relevant radiology findings and any change in status from prior imaging. Electronic radiology reports from 1995–2002 and data from analysis of these reports with NLP-Leximer were saved in a data warehouse and exported to a multidimensional structure called the Radcube. Various relational queries on the data in the Radcube were performed using OLAP technique. Thus, NLP-OLAP was applied to determine trends of FPOS in different radiology exams for different patient and examination attributes. Pivot tables were exported from NLP-OLAP interface to Microsoft Excel for statistical analysis. Radcube allowed rapid and comprehensive analysis of FPOS and FNEG trends in a large radiology report database. Trends of FPOS were extracted for different patient attributes such as age groups, gender, clinical indications, diseases with ICD codes, patient types (inpatient, ambulatory), imaging characteristics such as imaging modalities, referring physicians, radiology subspecialties, and body regions. Data analysis showed substantial differences between FPOS rates for different imaging modalities ranging from 23.1% (mammography, 49,163/212,906) to 85.8% (nuclear medicine, 93,852/109,374; p < 0.0001). In conclusion, NLP-OLAP can help in analysis of yield of different radiology exams from a large radiology report database. [ABSTRACT FROM AUTHOR]

Objective: Develop methods for automated transfer of images and associated text from a teaching-file repository into presentation material for speaker-led conferences. erials/Methods:Our institution uses a Microsoft Windows (Microsoft Corp, Redmond, WA) software application to maintain a digital teaching-file database that can store and retrieve content in a case-centric fashion. Virtually any number of images can be stored with any given case. Cases and their associated images can be retrieved via a module that supports searches by American College of Radiology (ACR) code and by free-text Boolean queries on the history, findings, diagnosis, and discussion components of a case. In addition to the software system serving directly as an interactive teaching tool, the digital teaching file itself serves as an image repository and resource for attending radiologists who create their own presentations and lectures. To better support this use, software modules were developed for interprocess communication and automated creation of Powerpoint slides. These modules are fully integrated with the teaching-file software application. A single image or a set of selected images can be automatically made into individual slides with two mouse clicks. Images are automatically centered and optimally sized. A slide title is automatically rendered from the user’s preference of the case history or diagnosis (stored with the case), or via the entry of freeform text. We describe the programming techniques that are used, as well as how several features of the operating system and Powerpoint itself can be integrated with a customized software application to facilitate this objective. Results: The creation of presentation-ready Powerpoint slides is fully automated from within our teaching-file application, and the time required to create a presentation compared to the conventional method of manually seeking and inserting files from within Powerpoint itself, on a per-slide basis, is drastically reduced. The benefits are magnified by having all imagery stored within an organized and searchable database system so that desired images can be easily located. Conclusion: A digital teaching-file system can serve as a useful image repository for purposes ancillary to direct computerized instruction. Software that supports these uses, such as the automated creation of presentation material for speaker-led conferences, facilitates the radiologist’s role as an educator. [ABSTRACT FROM AUTHOR]

Objective: To provide a standardized and scaleable mechanism for exchanging digital radiologic educational content between software systems that use disparate authoring, storage, and presentation technologies. Materials/Methods: Our institution uses two distinct software systems for creating educational content for radiology. Each system is used to create in-house educational content as well as commercial educational products. One system is an authoring and viewing application that facilitates the input and storage of hierarchical knowledge and associated imagery, and is capable of supporting a variety of entity relationships. This system is primarily used for the production and subsequent viewing of educational CD-ROMS. Another software system is primarily used for radiologic education on the world wide web. This system facilitates input and storage of interactive knowledge and associated imagery, delivering this content over the internet in a Socratic manner simulating in-person interaction with an expert. A subset of knowledge entities common to both systems was derived. An additional subset of knowledge entities that could be bidirectionally mapped via algorithmic transforms was also derived. An extensible markup language (XML) object model and associated lexicon were then created to represent these knowledge entities and their interactive behaviors. Forward-looking attention was exercised in the creation of the object model in order to facilitate straightforward future integration of other sources of educational content. XML generators and interpreters were written for both systems. Results: Deriving the XML object model and lexicon was the most critical and time-consuming aspect of the project. The coding of the XML generators and interpreters required only a few hours for each environment. Subsequently, the transfer of hundreds of educational cases and thematic presentations between the systems can now be accomplished in a matter of minutes. The use of of context as well as content, thus providing “presentationready” outcomes. Conclusion: The automation of knowledge exchange between dissimilar digital teaching environments magnifies the efforts of educators and enriches the learning experience for participants. XML is a powerful and useful mechanism for transfering educational content, as well as the context and interactive behaviors of such content, between disparate systems. [ABSTRACT FROM AUTHOR]

In order to identify proteins that interact with plant transcriptional complexes, we performed a two-hybrid screen in yeast using a cDNA library from embryogenic rice suspension cultures and the plant transcriptional activator viviparous-1 (vp1) as ‘bait’. In this screen, we detected an interaction between VP1 and a rice homologue of the Saccharomyces cerevisiae RAD23 gene (osRAD23). The RAD23 protein is associated with the general transcriptional machinery in yeast, and is believed to play a role in the processes of nucleotide excision repair in yeast and mammalian cells. This report is the first identification of a RAD23 homolog in plants. The osRAD23 amino acid sequence shares 50–60% similarity throughout its length with RAD23 sequences from yeast, mice, and man. osRAD23 contains a characteristic ubiquitin-like domain at its N-terminus, which is similar to other RAD23 genes. Analysis of the expressed sequence tag database identifies two different classes of RAD23 genes in both Arabidopsis and rice. Southern analysis of rice genomic DNA indicated the presence of at least two RAD23-like genes. A single transcript (1.5 kb) of osRAD23 was detected in total RNA from rice embryonic tissue, while three transcripts (1.8, 1.5 and 1.0 kb) were observed in total RNA from vegetative tissues of rice. [ABSTRACT FROM AUTHOR]

Lionfish ( Pterois volitans and Pterois miles) are the first non-native marine reef fish to become established in the Western North Atlantic and Caribbean Sea. Next-generation sequencing techniques were employed to identify 18 polymorphic microsatellite loci for P. volitans and P. miles from waters off North Carolina, USA. Allele frequencies for all 18 loci conformed to Hardy-Weinberg expectations after correction for multiple comparisons, the number of alleles ranged from 2 to 20 (mean = 7.1), and observed heterozygosities ranged from 0.200 to 0.938 (mean H = 0.636). All 18 loci cross-amplified DNAs from representative haplotypes of both P. volitans and P. miles, and the vast majority of alleles were shared. These are the first highly polymorphic nuclear markers described for invasive lionfish and will be useful for characterizing population connectivity and monitoring the progress of the invasion on reef habitats of the Western Atlantic. [ABSTRACT FROM AUTHOR]

Species in the genus Bathymodiolus are mytilid mussels found at deep-sea hydrothermal vents and cold seeps. Next-generation sequencing techniques were employed to identify eighteen unlinked polymorphic microsatellite loci for Bathymodiolus manusensis from Manus Basin in the western Pacific. Allele frequencies for eight loci conform to Hardy-Weinberg expectations and observed heterozygosities ranged from 0.04 to 0.90 (mean H = 0.45, SD = 0.25). Ten of eighteen loci cross-amplified in Bathymodiolus heckerae from Atlantic seeps. Microsatellites developed for Bathymodiolus manusensis are being deployed to study connectivity among populations of this species colonizing geographically discrete back-arc basin vent systems. [ABSTRACT FROM AUTHOR]

Ifremeria nautilei is deep-sea provannid gastropod endemic to hydrothermal vents at southwest Pacific back-arc spreading centers. Twelve, selectively neutral and unlinked polymorphic microsatellite loci were developed for this species. Three loci deviated significantly from Hardy-Weinberg expectations. Average observed heterozygosity ranged from 0.719 to 0.906 (mean H = 0.547, SD = 0.206). Three of the 12 loci cross-amplified in two species of Alviniconcha (Provannidae) that co-occur with I. nautilei at Pacific vent habitats. Microsatellites developed for I. nautilei are being deployed to study connectivity among populations of this species colonizing geographically discrete back-arc basin vent systems. [ABSTRACT FROM AUTHOR]

Reports on Y. Chang et al.'s identification of a human herpes virus in Kaposi's sarcoma (KS). Epidemiologal indicators; Transmission; Prevalence; Role of the herpes virus in the development of KS.