Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

Regularizing Image Reconstruction for Gradient-Domain Rendering with Feature Patches

We present a novel algorithm to reconstruct high-quality images from sampled pixels and gradients in gradient-domain rendering. Our approach extends screened Poisson reconstruction by adding additional regularization constraints. Our key idea is to exploit local patches in feature images, which contain per-pixels normals, textures, position, etc., to formulate these constraints. We describe a GPU implementation of our approach that runs on the order of seconds on megapixel images. We demonstrate a significant improvement in image quality over screened Poisson reconstruction under the L1 norm. Because we adapt the regularization constraints to the noise level in the input, our algorithm is consistent and converges to the ground truth.

Computer-based summative assessment of clinical reasoning in clerkships: A mixed-method comparison of key feature problems with case-based multiple choice questions

Background: It is yet unclear if there are differences between using electronic key feature problems (KFPs) or electronic case-based multiple choice questions (cbMCQ) for the assessment of clinical decision making. Summary of Work: Fifth year medical students were exposed to clerkships which ended with a summative exam. Assessment of knowledge per exam was done by 6-9 KFPs, 9-20 cbMCQ and 9-28 MC questions. Each KFP consisted of a case vignette and three key features (KF) using “long menu” as question format. We sought students’ perceptions of the KFPs and cbMCQs in focus groups (n of students=39). Furthermore statistical data of 11 exams (n of students=377) concerning the KFPs and (cb)MCQs were compared. Summary of Results: The analysis of the focus groups resulted in four themes reflecting students’ perceptions of KFPs and their comparison with (cb)MCQ: KFPs were perceived as (i) more realistic, (ii) more difficult, (iii) more motivating for the intense study of clinical reasoning than (cb)MCQ and (iv) showed an overall good acceptance when some preconditions are taken into account. The statistical analysis revealed that there was no difference in difficulty; however KFP showed a higher discrimination and reliability (G-coefficient) even when corrected for testing times. Correlation of the different exam parts was intermediate. Conclusions: Students perceived the KFPs as more motivating for the study of clinical reasoning. Statistically KFPs showed a higher discrimination and higher reliability than cbMCQs. Take-home messages: Including KFPs with long menu questions into summative clerkship exams seems to offer positive educational effects.

Computerbasierte Prüfung von klinischem Denken in der klinischen Ausbildung: Ein Mixed-Method Vergleich von Key Feature Problemen mit fallbasierten Multiple Choice Typ A Fragen

Fragestellung/Einleitung: Es ist unklar inwiefern Unterschiede bestehen im Einsatz von Key Feature Problemen (KFP) mit Long Menu Fragen und fallbasierten Typ A Fragen (FTA) für die Überprüfung des klinischen Denkens (Clinical Reasoning) in der klinischen Ausbildung von Medizinstudierenden. Methoden: Medizinstudierende des fünften Studienjahres nahmen an ihrer klinischen Pädiatrie-Rotation teil, die mit einer summativen Prüfung endete. Die Überprüfung des Wissen wurde pro Prüfung elektronisch mit 6-9 KFP [1], [3], 9-20 FTA und 9-28 nichtfallbasierten Multiple Choice Fragen (NFTA) durchgeführt. Jedes KFP bestand aus einer Fallvignette und drei Key Features und nutzen ein sog. Long Menu [4] als Antwortformat. Wir untersuchten die Perzeption der KFP und FTA in Focus Gruppen [2] (n of students=39). Weiterhin wurden die statistischen Kennwerte der KFP und FTA von 11 Prüfungen (n of students=377) verglichen. Ergebnisse: Die Analyse der Fokusgruppen resultierte in vier Themen, die die Perzeption der KFP und deren Vergleich mit FTA darstellten: KFP wurden als 1. realistischer, 2. schwerer, und 3. motivierender für das intensive Selbststudium des klinischen Denkens als FTA aufgenommen und zeigten 4. insgesamt eine gute Akzeptanz sofern gewisse Voraussetzungen berücksichtigt werden. Die statistische Auswertung zeigte keinen Unterschied im Schwierigkeitsgrad; jedoch zeigten die KFP eine höhere Diskrimination und Reliabilität (G-coefficient) selbst wenn für die Prüfungszeit korrigiert wurde. Die Korrelation der verschiedenen Prüfungsteile war mittel. Diskussion/Schlussfolgerung: Die Studierenden erfuhren die KFP als motivierenden für das Selbststudium des klinischen Denkens. Statistisch zeigten die KFP eine grössere Diskrimination und höhere Relibilität als die FTA. Der Einbezug von KFP mit Long Menu in Prüfungen des klinischen Studienabschnitts erscheint vielversprechend und einen „educational effect“ zu haben.

Who cares about my feature request?

Previous studies on issue tracking systems for open source software (OSS) focused mainly on requests for bug fixes. However, requests to add a new feature or an improvement to an OSS project are often also made in an issue tracking system. These inquiries are particularly important because they determine the further development of the software. This study examines if there is any difference between requests of the IBM developer community and other sources in terms of the likelihood of successful implementation. Our study consists of a case study of the issue tracking system BugZilla in the Eclipse integrated development environment (IDE). Our hypothesis, which was that feature requests from outsiders have less chances of being implemented, than feature requests from IBM developers, was confirmed.

Automatic Stabilizer Feature of Fixed Exchange Rate Regimes in Emerging Markets

This paper shows that countries characterized by a financial accelerator mechanism may reverse the usual finding of the literature -- flexible exchange rate regimes do a worse job of insulating open economies from external shocks. I obtain this result with a calibrated small open economy model that endogenizes foreign interest rates by linking them to the banking sector's foreign currency leverage. This relationship renders exchange rate policy more important compared to the usual exogeneity assumption. I find empirical support for this prediction using the Local Projections method. Finally, 2nd order approximation to the model finds larger welfare losses under flexible regimes.

Physician coding for mental illness reimbursement and the need for mental health parity

Many patients with anxiety and depression initially seek treatment from their primary care physicians. Changes in insurance coverage and current mental parity laws, make reimbursement for services a problem. This has led to a coding dilemma for physicians seeking payment for their services. This study seeks to determine first the frequency at which primary care physicians use alternative coding, and secondly, if physicians would change their coding practices, provided reimbursement was assured through changes in mental parity laws. A mail survey was sent to 260 randomly selected primary care physicians, who are family practice, internal medicine, and general practice physicians, and members of the Harris County Medical Society. The survey evaluated the physicians' demographics, the number of patients with psychiatric disorders seen by primary care physicians, the frequency with which physicians used alternative coding, and if mental parity laws changed, the rate at which physicians would use a psychiatric illness diagnosis as the primary diagnostic code. The overall response rate was 23%. Only 47 of the 59 physicians, who responded, qualified for the study and of those 45% used a psychiatric disorder to diagnose patients with a primary psychiatric disorder, 47% used a somatic/symptom disorder, and 8% used a medical diagnosis. From the physicians who would not use a psychiatric diagnosis as a primary ICD-9 code, 88% were afraid of not being reimbursed and 12% were worried about stigma or jeopardizing insurability. If payment were assured using a psychiatric diagnostic code, 81% physicians would use a psychiatric diagnosis as the primary diagnostic code. However, 19% would use an alternative diagnostic code in fear of stigmatizing and/or jeopardizing patients' insurability. Although the sample size of the study design was adequate, our survey did not have an ideal response rate, and no significant correlation was observed. However, it is evident that reimbursement for mental illness continues to be a problem for primary care physicians. The reformation of mental parity laws is necessary to ensure that patients receive mental health services and that primary care physicians are reimbursed. Despite the possibility of improved mental parity legislation, some physicians are still hesitant to assign patients with a mental illness diagnosis, due to the associated stigma, which still plays a role in today's society. ^

Dynamic population coding in primary visual cortex

More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^

Post-transcriptional Regulation of Mammalian Gene Expression in Non-coding Region of Target RNA

Tumor Suppressor Candidate 2 (TUSC2) is a novel tumor suppressor gene located in the human chromosome 3p21.3 region. TUSC2 mRNA transcripts could be detected on Northern blots in both normal lung and some lung cancer cell lines, but no endogenous TUSC2 protein could be detected in a majority of lung cancer cell lines. Mechanisms regulating TUSC2 protein expression and its inactivation in primary lung cancer cells are largely unknown. We investigated the role of the 5’- and 3’-untranslated regions (UTRs) of the TUSC2 gene in the regulation of TUSC2 protein expression. We found that two small upstream open-reading frames (uORFs) in the 5’UTR of TUSC2 could markedly inhibit the translational initiation of TUSC2 protein by interfering with the “scanning” of the ribosome initiation complexes. Site-specific stem-loop array reverse transcription-polymerase chain reaction (SLA-RT-PCR) verified several micoRNAs (miRNAs) targeted at 3’UTR and directed TUSC2 cleavage and degradation. In addition, we used the established let-7-targeted high mobility group A2 (Hmga2) mRNA as a model system to study the mechanism of regulation of target mRNA by miRNAs in mammalian cells under physiological conditions. There have been no evidence of direct link between mRNA downregulation and mRNA cleavages mediated by miRNAs. Here we showed that the endonucleolytic cleavages on mRNAs were initiated by mammalian miRNA in seed pairing style. Let-7 directed cleavage activities among the eight predicted potential target sites have varied efficiency, which are influenced by the positional and the structural contexts in the UTR. The 5’ cleaved RNA fragments were mostly oligouridylated at their 3’-termini and accumulated for delayed 5’–3’ degradation. RNA fragment oligouridylation played important roles in marking RNA fragments for delayed bulk degradation and in converting RNA degradation mode from 3’–5’ to 5’–3’ with cooperative efforts from both endonucleolytic and non-catalytic miRNA-induced silencing complex (miRISC). Our findings point to a mammalian miRNA-mediated mechanism for the regulation of mRNA that miRNA can decrease target mRNA through target mRNA cleavage and uridine addition

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

Mechanism of translationally coupled mRNA turnover mediated by c-fos protein-coding-region determinant

Proto-oncogene c-fos is a member of the class of early-response genes whose transient expression plays a crucial role in cell proliferation, differentiation, and apoptosis. Degradation of c- fos mRNA is an important mechanism for controlling c-fos expression. Rapid mRNA turnover mediated by the protein-coding-region determinant (mCRD) of the c-fos transcript illustrates a functional interplay between mRNA turnover and translation that coordinately influences the fate of cytoplasmic mRNA. It is suggested that mCRD communicates with the 3′ poly(A) tail via an mRNP complex comprising mCRD-associated proteins, which prevents deadenylation in the absence of translation. Ribosome transit as a result of translation is required to alter the conformation of the mRNP complex, thereby eliciting accelerated deadenylation and mRNA decay. To gain further insight into the mechanism of mCRD-mediated mRNA turnover, Unr was identified as an mCRD-binding protein, and its binding site within mCRD was characterized. Moreover, the functional role for Unr in mRNA decay was demonstrated. The result showed that elevation of Unr protein level in the cytoplasm led to inhibition of mRNA destabilization by mCRD. In addition, GST pull-down assay and immuno-precipitation analysis revealed that Unr interacted with PABP in an RNA-independent manner, which identified Unr as a novel PABP-interacting protein. Furthermore, the Unr interacting domain in PABP was characterized. In vivo mRNA decay experiments demonstrated a role for Unr-PABP interaction in mCRD-mediated mRNA decay. In conclusion, the findings of this study provide the first evidence that Unr plays a key role in mCRD-mediated mRNA decay. It is proposed that Unr is recruited by mCRD to initiate the formation of a dynamic mRNP complex for communicating with poly(A) tail through PABP. This unique mRNP complex may couple translation to mRNA decay, and perhaps to recruit the responsible nuclease for deadenylation. ^