Osteopathic Manipulative Treatment as an Intervention to Reduce Stress, Anxiety, and Depression in First Responders: A Pilot Study.

In this pilot study, we examined the efficacy of Osteopathic Manipulative Treatment (OMT) for improving symptoms of stress, anxiety, and depression (SAD) to determine a correlation between overall improvement in health and quality of life for first responders. Participants received weekly OMT or sham OMT targeting autonomic imbalance. Indicators of SAD were examined pre- and post-study. Overall, this pilot study suggests improvement in both the social-psychological (mental) self-assessments, and alterations in SAD-associated biomarkers from OMT.

Fully automated patellofemoral MRI segmentation using holistically nested networks: Implications for evaluating patellofemoral osteoarthritis, pain, injury, pathology, and adolescent development.

PURPOSE: Our clinical understanding of the relationship between 3D bone morphology and knee osteoarthritis, as well as our ability to investigate potential causative factors of osteoarthritis, has been hampered by the time-intensive nature of manually segmenting bone from MR images. Thus, we aim to develop and validate a fully automated deep learning framework for segmenting the patella and distal femur cortex, in both adults and actively growing adolescents. METHODS: Data from 93 subjects, obtained from on institutional review board-approved protocol, formed the study database. 3D sagittal gradient recalled echo and gradient recalled echo with fat saturation images and manual models of the outer cortex were available for 86 femurs and 90 patellae. A deep-learning-based 2D holistically nested network (HNN) architecture was developed to automatically segment the patella and distal femur using both single (sagittal, uniplanar) and 3 cardinal plane (triplanar) methodologies. Errors in the surface-to-surface distances and the Dice coefficient were the primary measures used to quantitatively evaluate segmentation accuracy using a 9-fold cross-validation. RESULTS: Average absolute errors for segmenting both the patella and femur were 0.33 mm. The Dice coefficients were 97% and 94% for the femur and patella. The uniplanar, relative to the triplanar, methodology produced slightly superior segmentation. Neither the presence of active growth plates nor pathology influenced segmentation accuracy. CONCLUSION: The proposed HNN with multi-feature architecture provides a fully automatic technique capable of delineating the often indistinct interfaces between the bone and other joint structures with an accuracy better than nearly all other techniques presented previously, even when active growth plates are present.

Axial superresolution via multiangle TIRF microscopy with sequential imaging and photobleaching.

We report superresolution optical sectioning using a multiangle total internal reflection fluorescence (TIRF) microscope. TIRF images were constructed from several layers within a normal TIRF excitation zone by sequentially imaging and photobleaching the fluorescent molecules. The depth of the evanescent wave at different layers was altered by tuning the excitation light incident angle. The angle was tuned from the highest (the smallest TIRF depth) toward the critical angle (the largest TIRF depth) to preferentially photobleach fluorescence from the lower layers and allow straightforward observation of deeper structures without masking by the brighter signals closer to the coverglass. Reconstruction of the TIRF images enabled 3D imaging of biological samples with 20-nm axial resolution. Two-color imaging of epidermal growth factor (EGF) ligand and clathrin revealed the dynamics of EGF-activated clathrin-mediated endocytosis during internalization. Furthermore, Bayesian analysis of images collected during the photobleaching step of each plane enabled lateral superresolution (<100 nm) within each of the sections.

The NINDS Parkinson's disease biomarkers program.

BACKGROUND: Neuroprotection for Parkinson's disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke has therefore established the Parkinson's Disease Biomarkers Program to promote discovery of PD biomarkers for use in phase II and III clinical trials. METHODS: Using a novel consortium design, the Parkinson's Disease Biomarker Program is focused on the development of clinical and laboratory-based biomarkers for PD diagnosis, progression, and prognosis. Standardized operating procedures and pooled reference samples were created to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the research community for additional biomarker projects. RESULTS: Eleven consortium projects are ongoing, seven of which recruit participants and obtain biosamples. As of October 2014, 1,082 participants have enrolled (620 PD, 101 with other causes of parkinsonism, 23 essential tremor, and 338 controls), 1,040 of whom have at least one biosample. Six thousand eight hundred ninety-eight total biosamples are available from baseline, 6-, 12-, and 18-month visits: 1,006 DNA, 1,661 RNA, 1,419 whole blood, 1,382 plasma, 1,200 serum, and 230 cerebrospinal fluid (CSF). Quality control analysis of plasma, serum, and CSF samples indicates that almost all samples are high quality (24 of 2,812 samples exceed acceptable hemoglobin levels). CONCLUSIONS: By making samples and data widely available, using stringent operating procedures based on existing standards, hypothesis testing for biomarker discovery, and providing a resource that complements existing programs, the Parkinson's Disease Biomarker Program will accelerate the pace of PD biomarker research. © 2015 International Parkinson and Movement Disorder Society.

Location of Radicular Spinal Arteries in the Lumbar Spine from Analysis of CT Angiograms of the Abdomen and Pelvis.

OBJECTIVE: Reports of catastrophic neurologic injuries following lumbar transforaminal epidural steroid injections are rare but serious potential complications. The traditional method of performing lumbar transforaminal epidural steroid injections is in the "safe triangle" to avoid contact to the spinal nerve. Some authors advocate an alternative approach by placing the needle inferiorly in a region referred to as "Kambin's triangle" to avoid incurring arteries. This study aimed to determine the location of arteries within the L1-L4 intervertebral foramen in vivo, specifically if they lie within or in close proximity to the "safe triangle" or Kambin's triangle using CT angiograms of the abdomen and pelvis. STUDY DESIGN: The authors retrospectively evaluated the location in vivo of arterial vessels in the intervertebral foramen from L1 to L4 in patients who underwent abdominopelvic CT angiograms for aortic vascular disease. The data were reanalyzed to confirm inter-rater reliability. RESULTS: Arteries were found in both the safe triangle and Kambin's triangle at a statistically significant rate (P < 0.05). CONCLUSIONS: In this group of patients, an artery was found in either the safe triangle or in Kambin's triangle frequently, suggesting the location of these arteries can be quite variable. Physicians performing these procedures should use universal precautions to avoid inadvertent injection into the lumbar spinal arteries and minimize potential complications regardless of the approach.

Do Decision Support Tools Decrease the Prevalence of Hospital-Acquired Venous Thromboembolisms When Compared to Clinical Judgement? A Single-Center Pre-Post Study.

Introduction: Hospital-acquired venous thromboembolisms (HA-VTEs) carry a significant health burden on patients and a financial burden on hospitals due to reimbursement penalties. VTE prophylaxis at our institute was performed through utilizing an order set based on healthcare professionals' perceived level of risk. However, the use of standardized risk assessment models is recommended by multiple professional societies. Furthermore, integrating decision support tools (DST) based on the standardized risk assessment models has been shown to increase the administration of appropriate deep vein thrombosis (DVT) prophylaxis. Nonetheless, such scoring systems are not inherently flawless and their integration into EMR as a mandatory step can come at the risk of healthcare professional fatigue and burnout. We conducted a study to evaluate the incidence of HA-VTE and length of stay pre- and post implementation of a DST. Methods: We conducted a retrospective, pre-post-implementation observational study at a tertiary medical center after implementing a mandatory DST. The DST used Padua scores for medical patients and Caprini scores for surgical patients. Patients were identified through ICD-10 codes and outcomes were collected from electronic charts. Healthcare professionals were surveyed through an anonymous survey and stored securely. Statistical analysis was conducted by using R (version 3.4.3). Results: A total of 343 patients developed HA-VTE during the study period. Of these, 170 patients developed HA-VTE in the 9 months following the implementation of the DST, while 173 patients were identified in the 9 months preceding the implementation. There was no statistically significant difference in mean HA-VTE/1000 discharge/month pre- and post implementation (4.4 (SD 1.6) compared to 4.6 (SD 1.2), confidence interval [CI] -1.6 to 1.2, p = 0.8). The DST was used in 73% of all HA-VTE cases over the first 6 months of implementation. The hospital length of stay (LOS) was 14.2 (SD 1.9) days prior to implementation and 14.1 (SD 1.6) days afterwards. No statistically significant change in readmission rates was noted (8.8% (SD 2.6) prior to implementation and 15.53% (SD 9.6) afterwards, CI -14.27 to 0.74, p = 0.07). Of the 56 healthcare professionals who answered the survey, 84% (n = 47) reported to be dissatisfied or extremely dissatisfied with the DST, while 91% (n = 51) reported that it slowed them down. Conclusions: There were no apparent changes in the prevalence of HA-VTE, length of stay, or readmission rates when VTE prophylaxis was mandated through DST compared to a prior model which used order sets based on perceived risk. Further studies are needed to further evaluate the current risk assessment models and improve healthcare professionals' satisfaction with DST.

Biomedical Data Repository Concepts and Management Principles.

The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in research findings, and developments such as the Final Data Management and Sharing Policy from the U.S. National Institutes of Health and a memorandum on increasing public access to federally funded research, issued by the U.S. Office of Science and Technology Policy. This paper explores the pivotal role of data repositories in biomedical research and open science, emphasizing their importance in managing, preserving, and sharing research data. Our objective is to familiarize readers with the functions of data repositories, set expectations for their services, and provide an overview of methods to evaluate their capabilities. The paper serves to introduce fundamental concepts and community-based guiding principles and aims to equip researchers, repository operators, funders, and policymakers with the knowledge to select appropriate repositories for their data management and sharing needs and foster a foundation for the open sharing and preservation of research data.

Defective motion processing in children with cerebral visual impairment due to periventricular white matter damage.

AIM: We sought to characterize visual motion processing in children with cerebral visual impairment (CVI) due to periventricular white matter damage caused by either hydrocephalus (eight individuals) or periventricular leukomalacia (PVL) associated with prematurity (11 individuals). METHOD: Using steady-state visually evoked potentials (ssVEP), we measured cortical activity related to motion processing for two distinct types of visual stimuli: 'local' motion patterns thought to activate mainly primary visual cortex (V1), and 'global' or coherent patterns thought to activate higher cortical visual association areas (V3, V5, etc.). We studied three groups of children: (1) 19 children with CVI (mean age 9y 6mo [SD 3y 8mo]; 9 male; 10 female); (2) 40 neurologically and visually normal comparison children (mean age 9y 6mo [SD 3y 1mo]; 18 male; 22 female); and (3) because strabismus and amblyopia are common in children with CVI, a group of 41 children without neurological problems who had visual deficits due to amblyopia and/or strabismus (mean age 7y 8mo [SD 2y 8mo]; 28 male; 13 female). RESULTS: We found that the processing of global as opposed to local motion was preferentially impaired in individuals with CVI, especially for slower target velocities (p=0.028). INTERPRETATION: Motion processing is impaired in children with CVI. ssVEP may provide useful and objective information about the development of higher visual function in children at risk for CVI.

Automatic quadriceps and patellae segmentation of MRI with cascaded U2 -Net and SASSNet deep learning model.

PURPOSE: Automatic muscle segmentation is critical for advancing our understanding of human physiology, biomechanics, and musculoskeletal pathologies, as it allows for timely exploration of large multi-dimensional image sets. Segmentation models are rarely developed/validated for the pediatric model. As such, autosegmentation is not available to explore how muscle architectural changes during development and how disease/pathology affects the developing musculoskeletal system. Thus, we aimed to develop and validate an end-to-end, fully automated, deep learning model for accurate segmentation of the rectus femoris and vastus lateral, medialis, and intermedialis using a pediatric database. METHODS: We developed a two-stage cascaded deep learning model in a coarse-to-fine manner. In the first stage, the U2 -Net roughly detects the muscle subcompartment region. Then, in the second stage, the shape-aware 3D semantic segmentation method SASSNet refines the cropped target regions to generate the more finer and accurate segmentation masks. We utilized multifeature image maps in both stages to stabilize performance and validated their use with an ablation study. The second-stage SASSNet was independently run and evaluated with three different cropped region resolutions: the original image resolution, and images downsampled 2× and 4× (high, mid, and low). The relationship between image resolution and segmentation accuracy was explored. In addition, the patella was included as a comparator to past work. We evaluated segmentation accuracy using leave-one-out testing on a database of 3D MR images (0.43 × 0.43 × 2 mm) from 40 pediatric participants (age 15.3 ± 1.9 years, 55.8 ± 11.8 kg, 164.2 ± 7.9 cm, 38F/2 M). RESULTS: The mid-resolution second stage produced the best results for the vastus medialis, rectus femoris, and patella (Dice similarity coefficient = 95.0%, 95.1%, 93.7%), whereas the low-resolution second stage produced the best results for the vastus lateralis and vastus intermedialis (DSC = 94.5% and 93.7%). In comparing the low- to mid-resolution cases, the vasti intermedialis, vastus medialis, rectus femoris, and patella produced significant differences (p = 0.0015, p = 0.0101, p < 0.0001, p = 0.0003) and the vasti lateralis did not (p = 0.2177). The high-resolution stage 2 had significantly lower accuracy (1.0 to 4.4 dice percentage points) compared to both the mid- and low-resolution routines (p value ranged from < 0.001 to 0.04). The one exception was the rectus femoris, where there was no difference between the low- and high-resolution cases. The ablation study demonstrated that the multifeature is more reliable than the single feature. CONCLUSIONS: Our successful implementation of this two-stage segmentation pipeline provides a critical tool for expanding pediatric muscle physiology and clinical research. With a relatively small and variable dataset, our fully automatic segmentation technique produces accuracies that matched or exceeded the current state of the art. The two-stage segmentation avoids memory issues and excessive run times by using a first stage focused on cropping out unnecessary data. The excellent Dice similarity coefficients improve upon previous template-based automatic and semiautomatic methodologies targeting the leg musculature. More importantly, with a naturally variable dataset (size, shape, etc.), the proposed model demonstrates slightly improved accuracies, compared to previous neural networks methods.

Novel lymphotoxin alpha (LTalpha) knockout mice with unperturbed tumor necrosis factor expression: reassessing LTalpha biological functions.

Lymphotoxin alpha (LTalpha) can exist in soluble form and exert tumor necrosis factor (TNF)-like activity through TNF receptors. Based on the phenotypes of knockout (KO) mice, the physiological functions of LTalpha and TNF are considered partly redundant, in particular, in supporting the microarchitecture of the spleen and in host defense. We exploited Cre-LoxP technology to generate a novel neomycin resistance gene (neo) cassette-free LTalpha-deficient mouse strain (neo-free LTalpha KO [LTalphaDelta/Delta]). Unlike the "conventional" LTalpha-/- mice, new LTalphaDelta/Delta animals were capable of producing normal levels of systemic TNF upon lipopolysaccharide (LPS) challenge and were susceptible to LPS/D-galactosamine (D-GalN) toxicity. Activated neutrophils, monocytes, and macrophages from LTalphaDelta/Delta mice expressed TNF normally at both the mRNA and protein levels as opposed to conventional LTalpha KO mice, which showed substantial decreases in TNF. Additionally, the spleens of the neo-free LTalpha KO mice displayed several features resembling those of LTbeta KO mice rather than conventional LTalpha KO animals. The phenotype of the new LTalphaDelta/Delta mice indicates that LTalpha plays a smaller role in lymphoid organ maintenance than previously thought and has no direct role in the regulation of TNF expression.

Development of an informatics system for accelerating biomedical research.

Biomedical translational research can benefit from informatics system that support the confidentiality, integrity and accessibility of data.  Such systems require functional capabilities for researchers to securely submit data to designated biomedical repositories. Reusability of data is enhanced by the availability functional capabilities that ensure confidentiality, integrity and access of data. A biomedical research system was developed by combining common data element methodology with a service-oriented architecture to support multiple disease focused research programs. Seven service modules are integrated together to provide a collaborative and extensible web-based environment. The modules - Data Dictionary, Account Management, Query Tool, Protocol and Form Research Management System, Meta Study, Repository Manager and globally unique identifier (GUID) facilitate the management of research protocols, submitting and curating data (clinical, imaging, and derived genomics) within the associated data repositories. No personally identifiable information is stored within the repositories. Data is made findable by use of digital object identifiers that are associated with the research studies. Reuse of data is possible by searching through volumes of aggregated research data across multiple studies. The application of common data element(s) methodology for development of content-based repositories leads to increase in data interoperability that can further hypothesis-based biomedical research.

Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections.

Accurate and automated prostate whole gland and central gland segmentations on MR images are essential for aiding any prostate cancer diagnosis system. Our work presents a 2-D orthogonal deep learning method to automatically segment the whole prostate and central gland from T2-weighted axial-only MR images. The proposed method can generate high-density 3-D surfaces from low-resolution ( z axis) MR images. In the past, most methods have focused on axial images alone, e.g., 2-D based segmentation of the prostate from each 2-D slice. Those methods suffer the problems of over-segmenting or under-segmenting the prostate at apex and base, which adds a major contribution for errors. The proposed method leverages the orthogonal context to effectively reduce the apex and base segmentation ambiguities. It also overcomes jittering or stair-step surface artifacts when constructing a 3-D surface from 2-D segmentation or direct 3-D segmentation approaches, such as 3-D U-Net. The experimental results demonstrate that the proposed method achieves 92.4 % ± 3 % Dice similarity coefficient (DSC) for prostate and DSC of 90.1 % ± 4.6 % for central gland without trimming any ending contours at apex and base. The experiments illustrate the feasibility and robustness of the 2-D-based holistically nested networks with short connections method for MR prostate and central gland segmentation. The proposed method achieves segmentation results on par with the current literature.

Extensive cortical inflammation is associated with epilepsy in multiple sclerosis.

INTRODUCTION: Epilepsy is three to six times more frequent in MS than in the general population. Previous studies based on conventional magnetic resonance (MR) imaging have suggested a possible correlation between cortical inflammatory pathology and epileptic seizures. However, pure intracortical lesions (ICLs) are unlikely to be demonstrated with conventional MR. We applied the double inversion recovery (DIR) sequence in relapsing remitting MS (RRMS) patients with or without epileptic seizures in order to clarify the relationship between ICLs and epilepsy in MS in vivo. METHODS: Twenty RRMS patients who had epileptic seizures (RRMS/E) during the course of the disease were studied for the presence of ICLs. A group of 80 RRMS patients with no history of seizures and matched for gender, age, disease duration, Expanded Disability Status Scale (EDSS) grading, and T2 lesion volume (T2-WMLV) was selected as reference population. ICLs were detected by applying the DIR sequence. RESULTS: ICLs were observed in 18/20 (90%) RRMS/E and in 39/80 (48%) RRMS (p = 0.001). RRMS/E showed five times more ICLs (7.2 +/- 8.4) than RRMS (1.5 +/- 2.4; p = 0.015). The total ICLs volume was 6 times larger in RRMS/E than in RRMS (1.2 +/- 1.7 cm3 versus 0.2 +/- 0.2 cm3, p = 0.016). No significant difference was observed between RRMS and RRMS/E with regard to the number and volume of juxtacortical lesions and T2-WMLV. DISCUSSION: Our findings indicate that RRMS/E have more extensive cortical inflammation than RRMS patients with no history of epilepsy. Inflammatory ICLs may be responsible for epilepsy in MS.

Long-term preservation of biomedical research data.

Genomics and molecular imaging, along with clinical and translational research have transformed biomedical science into a data-intensive scientific endeavor. For researchers to benefit from Big Data sets, developing long-term biomedical digital data preservation strategy is very important. In this opinion article, we discuss specific actions that researchers and institutions can take to make research data a continued resource even after research projects have reached the end of their lifecycle. The actions involve utilizing an Open Archival Information System model comprised of six functional entities: Ingest, Access, Data Management, Archival Storage, Administration and Preservation Planning. We believe that involvement of data stewards early in the digital data life-cycle management process can significantly contribute towards long term preservation of biomedical data. Developing data collection strategies consistent with institutional policies, and encouraging the use of common data elements in clinical research, patient registries and other human subject research can be advantageous for data sharing and integration purposes. Specifically, data stewards at the onset of research program should engage with established repositories and curators to develop data sustainability plans for research data. Placing equal importance on the requirements for initial activities (e.g., collection, processing, storage) with subsequent activities (data analysis, sharing) can improve data quality, provide traceability and support reproducibility. Preparing and tracking data provenance, using common data elements and biomedical ontologies are important for standardizing the data description, making the interpretation and reuse of data easier. The Big Data biomedical community requires scalable platform that can support the diversity and complexity of data ingest modes (e.g. machine, software or human entry modes). Secure virtual workspaces to integrate and manipulate data, with shared software programs (e.g., bioinformatics tools), can facilitate the FAIR (Findable, Accessible, Interoperable and Reusable) use of data for near- and long-term research needs.

Volumetric neuroimage analysis extensions for the MIPAV software package.

We describe a new collection of publicly available software tools for performing quantitative neuroimage analysis. The tools perform semi-automatic brain extraction, tissue classification, Talairach alignment, and atlas-based measurements within a user-friendly graphical environment. They are implemented as plug-ins for MIPAV, a freely available medical image processing software package from the National Institutes of Health. Because the plug-ins and MIPAV are implemented in Java, both can be utilized on nearly any operating system platform. In addition to the software plug-ins, we have also released a digital version of the Talairach atlas that can be used to perform regional volumetric analyses. Several studies are conducted applying the new tools to simulated and real neuroimaging data sets.

Cortical atrophy is relevant in multiple sclerosis at clinical onset.

INTRODUCTION: Increasing evidence suggests relevant cortical gray matter pathology in patients with Multiple Sclerosis (MS), but how early this pathology begins; its impact on clinical disability and which cortical areas are primarily affected needs to be further elucidated. METHODS: 115 consecutive patients (10 Clinically Isolated Syndrome (CIS), 32 possible MS (p-MS), 42 Relapsing Remitting MS (RR-MS), 31 Secondary Progressive MS (SP-MS)), and 40 age/gender-matched healthy volunteers (HV) underwent a neurological examination and a 1.5 T MRI. Global and regional Cortical Thickness (CTh) measurements, brain parenchyma fraction and T2 lesion load were analyzed. RESULTS: We found a significant global cortical thinning in p-MS (2.22 +/- 0.09 mm), RR-MS (2.16 +/- 0.10 mm) and SP-MS (1.98 +/- 0.11 mm) compared to CIS (2.51 +/- 0.11 mm) and HV (2.48 +/- 0.08 mm). The correlations between mean CTh and white matter (WM) lesion load was only moderate in MS (r = -0.393, p = 0.03) and absent in p-MS (r = -0.147, p = 0.422). Analysis of regional CTh revealed that the majority of cortical areas were involved not only in MS, but also in p-MS. The type of clinical picture at onset (in particular, pyramidal signs/symptoms and optic neuritis) correlated with atrophy in the corresponding cortical areas. DISCUSSION: Cortical thinning is a diffuse and early phenomenon in MS already detectable at clinical onset. It correlates with clinical disability and is partially independent from WM inflammatory pathology.

Checking Questionable Entry of Personally Identifiable Information Encrypted by One-Way Hash Transformation.

BACKGROUND: As one of the several effective solutions for personal privacy protection, a global unique identifier (GUID) is linked with hash codes that are generated from combinations of personally identifiable information (PII) by a one-way hash algorithm. On the GUID server, no PII is permitted to be stored, and only GUID and hash codes are allowed. The quality of PII entry is critical to the GUID system. OBJECTIVE: The goal of our study was to explore a method of checking questionable entry of PII in this context without using or sending any portion of PII while registering a subject. METHODS: According to the principle of GUID system, all possible combination patterns of PII fields were analyzed and used to generate hash codes, which were stored on the GUID server. Based on the matching rules of the GUID system, an error-checking algorithm was developed using set theory to check PII entry errors. We selected 200,000 simulated individuals with randomly-planted errors to evaluate the proposed algorithm. These errors were placed in the required PII fields or optional PII fields. The performance of the proposed algorithm was also tested in the registering system of study subjects. RESULTS: There are 127,700 error-planted subjects, of which 114,464 (89.64%) can still be identified as the previous one and remaining 13,236 (10.36%, 13,236/127,700) are discriminated as new subjects. As expected, 100% of nonidentified subjects had errors within the required PII fields. The possibility that a subject is identified is related to the count and the type of incorrect PII field. For all identified subjects, their errors can be found by the proposed algorithm. The scope of questionable PII fields is also associated with the count and the type of the incorrect PII field. The best situation is to precisely find the exact incorrect PII fields, and the worst situation is to shrink the questionable scope only to a set of 13 PII fields. In the application, the proposed algorithm can give a hint of questionable PII entry and perform as an effective tool. CONCLUSIONS: The GUID system has high error tolerance and may correctly identify and associate a subject even with few PII field errors. Correct data entry, especially required PII fields, is critical to avoiding false splits. In the context of one-way hash transformation, the questionable input of PII may be identified by applying set theory operators based on the hash codes. The count and the type of incorrect PII fields play an important role in identifying a subject and locating questionable PII fields.

Analyzing Dendritic Morphology in Columns and Layers.

In many regions of the central nervous systems, such as the fly optic lobes and the vertebrate cortex, synaptic circuits are organized in layers and columns to facilitate brain wiring during development and information processing in developed animals. Postsynaptic neurons elaborate dendrites in type-specific patterns in specific layers to synapse with appropriate presynaptic terminals. The fly medulla neuropil is composed of 10 layers and about 750 columns; each column is innervated by dendrites of over 38 types of medulla neurons, which match with the axonal terminals of some 7 types of afferents in a type-specific fashion. This report details the procedures to image and analyze dendrites of medulla neurons. The workflow includes three sections: (i) the dual-view imaging section combines two confocal image stacks collected at orthogonal orientations into a high-resolution 3D image of dendrites; (ii) the dendrite tracing and registration section traces dendritic arbors in 3D and registers dendritic traces to the reference column array; (iii) the dendritic analysis section analyzes dendritic patterns with respect to columns and layers, including layer-specific termination and planar projection direction of dendritic arbors, and derives estimates of dendritic branching and termination frequencies. The protocols utilize custom plugins built on the open-source MIPAV (Medical Imaging Processing, Analysis, and Visualization) platform and custom toolboxes in the matrix laboratory language. Together, these protocols provide a complete workflow to analyze the dendritic routing of Drosophila medulla neurons in layers and columns, to identify cell types, and to determine defects in mutants.