A Literature Review of Studies Evaluating Rotator Cuff Activation during Early Rehabilitation Exercises for Post-Op Rotator Cuff Repair

Despite the modern advancement of surgical repair equipment and techniques, many rotator cuff repairs do not clinically heal. Prescribed rehabilitative exercises must appropriately load the repaired muscle-tendon complex to promote healing and prevent capsular adhesions without damaging the repair. The clinician must possess an understanding of the anatomy and physiology of the healing rotator cuff, and understand the importance of the plane of movement, speed of the movement, position of the extremity, level of assistance, and type of resistance used. Electromyography (EMG) provides a useful means to determine muscle activation levels during specific exercises. Descriptions of specific exercises and EMG activation as they relate to the rotator cuff muscles are described. The specific performance of the exercises, the reliability of such EMG measures, and the descriptive figures are described. Practicing clinicians will benefit from the correct interpretation of the EMG data, and how it can be used in the exercise prescription when formulating a treatment plan

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states

Isolation of YAC Clones From the Pericentromeric Region of Chromosome 10 and Development of New Genetic Markers Linked to the Multiple Endocrine Neoplasia Type 2A Gene

Genetic linkage mapping and contig assembly using yeast artificial chromosome (YAC) technology form the basis of our strategy to clone and define the genomic structure of the pericentromeric region of chromosome 10 containing the multiple endocrine neoplasia type 2A gene. Thus far YAC walks have been initiated from five chromosome 10 pericentromeric loci including RBP3, D10S94, RET, D10Z1, and FNRB. Long range pulsed-field gel electrophoresis maps are constructed from the YACs isolated to define clone overlaps and to identify putative CpG islands. Bidirectional YAC walks are continued by rescreening the YAC library with sequence-tagged site assays developed from endclones. Several new restriction fragment length polymorphisms and simple sequence repeat polymorphism markers have been identified from the YAC clones. In particular, two highly informative (CA)n dinucleotide repeat markers, sTCL-1 from proximal chromosome 10p (16 alleles, PIC = 0.68) and sJRH-1 from the RBP3 locus (18 alleles. PIC = 0.88), provide useful reagents for a polymerase chain reaction-based predictive genetic test that can be performed rapidly from small amounts of DNA

Reading, Trauma and Literary Caregiving 1914-1918: Helen Mary Gaskell and the War Library

This article is about the relationship between reading, trauma and responsive literary caregiving in Britain during the First World War. Its analysis of two little-known documents describing the history of the War Library, begun by Helen Mary Gaskell in 1914, exposes a gap in the scholarship of war-time reading; generates a new narrative of "how," "when," and "why" books went to war; and foregrounds gender in its analysis of the historiography. The Library of Congress's T. W. Koch discovered Gaskell's ground-breaking work in 1917 and reported its successes to the American Library Association. The British Times also covered Gaskell's library, yet researchers working on reading during the war have routinely neglected her distinct model and method, skewing the research base on war-time reading and its association with trauma and caregiving. In the article's second half, a literary case study of a popular war novel demonstrates the extent of the "bitter cry for books." The success of Gaskell's intervention is examined alongside H. G. Wells's representation of textual healing. Reading is shown to offer sick, traumatized and recovering combatants emotional and psychological caregiving in ways that she could not always have predicted and that are not visible in the literary/historical record

Post-thyroid FNA testing and treatment options: A synopsis of the National Cancer Institute Thyroid Fine Needle Aspiration State of the Science Conference

The National Cancer Institute (NCI) sponsored the NCI Thyroid Fine Needle Aspiration (FNA) State of the Science Conference on October 22–23, 2007 in Bethesda, MD. The 2-day meeting was accompanied by a permanent informational Web site and several on-line discussion periods between May 1 and December 15, 2007 ( http://thyroidfna.cancer.gov ). This document addresses follow-up procedures and therapeutic options for suggested diagnostic categories. Follow-up options for “nondiagnostic” and “benign” thyroid aspirates are given. The value of ultrasound examination in the follow-up of “nondiagnostic” and “benign” thyroid aspirates is discussed. Ultrasound findings requiring reaspiration or surgical resection are described as are the timing and length of clinical and ultrasonographic surveillance for cytologically “benign” nodules. Options for surgical intervention are given for the diagnostic categories of “atypical/borderline,” “follicular neoplasm,” “suspicious for malignancy” and “malignant” ( http://thyroidfna.cancer.gov/pages/info/agenda/ ). Diagn. Cytopathol. 2008;36:442–448. © 2008 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58659/1/20832_ftp.pd

Short-Haul Revitalization Study Final Report

A feasibility study was performed for an advanced commercial short-haul aircraft to evaluate the potential for increased service for short-haul flights that operate out of regional and community airports. An analysis of potential origin-destination markets and trip distances resulted in a seat capacity selection of 48 passengers and a design range of 600 NM. A down-select of advanced technologies resulted in a hybrid-electric propulsion system being chosen as the primary enabling technology. A conceptual design of the advanced aircraft was developed, and a mission and sizing analysis was performed, comparing variants of the advanced aircraft with different levels of electrification. Fairly aggressive levels of electrification and battery specific energy are needed for the hybridelectric architecture to realize any benefit in terms of total energy cost for the 600 NM design mission. The development and operational costs were estimated for the advanced aircraft and compared to the baseline. This analysis demonstrated the negative effect of the cost to develop the hybrid-electric technology on the eventual operating cost. A market analysis was performed to determine possible passenger demand for the advanced shorthaul aircraft. According to the market analysis, there is potential demand for such an aircraft, but not necessarily in many of the smaller regional and community airports that were the intended beneficiaries of this new aircraft concept

Modeling and synthesis of breast cancer optical property signatures with generative models

Is it possible to find deterministic relationships between optical measurements and pathophysiology in an unsupervised manner and based on data alone? Optical property quantification is a rapidly growing biomedical imaging technique for characterizing biological tissues that shows promise in a range of clinical applications, such as intraoperative breast-conserving surgery margin assessment. However, translating tissue optical properties to clinical pathology information is still a cumbersome problem due to, amongst other things, inter- and intrapatient variability, calibration, and ultimately the nonlinear behavior of light in turbid media. These challenges limit the ability of standard statistical methods to generate a simple model of pathology, requiring more advanced algorithms. We present a data-driven, nonlinear model of breast cancer pathology for real-time margin assessment of resected samples using optical properties derived from spatial frequency domain imaging data. A series of deep neural network models are employed to obtain sets of latent embeddings that relate optical data signatures to the underlying tissue pathology in a tractable manner. These self-explanatory models can translate absorption and scattering properties measured from pathology, while also being able to synthesize new data. The method was tested on a total of 70 resected breast tissue samples containing 137 regions of interest, achieving rapid optical property modeling with errors only limited by current semi-empirical models, allowing for mass sample synthesis and providing a systematic understanding of dataset properties, paving the way for deep automated margin assessment algorithms using structured light imaging or, in principle, any other optical imaging technique seeking modeling. Code is available.This work was supported in part by the National Cancer Institute, US National Institutes of Health, under grants R01 CA192803 and F31 CA196308, by the Spanish Ministry of Science and Innovation under grant FIS2010-19860, by the Spanish Ministry of Science, Innovation and Universities under grants TEC2016-76021-C2-2-R and PID2019-107270RB-C21, by the Spanish Minstry of Economy, Industry and Competitiveness and Instituto de Salud Carlos III via DTS17-00055, by IDIVAL under grants INNVAL 16/02, and INNVAL 18/23, and by the Spanish Ministry of Education, Culture, and Sports with PhD grant FPU16/05705, as well as FEDER funds

Integration and validation of host transcript signatures, including a novel 3-transcript tuberculosis signature, to enable one-step multiclass diagnosis of childhood febrile disease

Background: Whole blood host transcript signatures show great potential for diagnosis of infectious and inflammatory illness, with most published signatures performing binary classification tasks. Barriers to clinical implementation include validation studies, and development of strategies that enable simultaneous, multiclass diagnosis of febrile illness based on gene expression. Methods: We validated five distinct diagnostic signatures for paediatric infectious diseases in parallel using a single NanoString nCounter® experiment. We included a novel 3-transcript signature for childhood tuberculosis, and four published signatures which differentiate bacterial infection, viral infection, or Kawasaki disease from other febrile illnesses. Signature performance was assessed using receiver operating characteristic curve statistics. We also explored conceptual frameworks for multiclass diagnostic signatures, including additional transcripts found to be significantly differentially expressed in previous studies. Relaxed, regularised logistic regression models were used to derive two novel multiclass signatures: a mixed One-vs-All model (MOVA), running multiple binomial models in parallel, and a full-multiclass model. In-sample performance of these models was compared using radar-plots and confusion matrix statistics. Results: Samples from 91 children were included in the study: 23 bacterial infections (DB), 20 viral infections (DV), 14 Kawasaki disease (KD), 18 tuberculosis disease (TB), and 16 healthy controls. The five signatures tested demonstrated cross-platform performance similar to their primary discovery-validation cohorts. The signatures could differentiate: KD from other diseases with area under ROC curve (AUC) of 0.897 [95% confidence interval: 0.822–0.972]; DB from DV with AUC of 0.825 [0.691–0.959] (signature-1) and 0.867 [0.753–0.982] (signature-2); TB from other diseases with AUC of 0.882 [0.787–0.977] (novel signature); TB from healthy children with AUC of 0.910 [0.808–1.000]. Application of signatures outside of their designed context reduced performance. In-sample error rates for the multiclass models were 13.3% for the MOVA model and 0.0% for the full-multiclass model. The MOVA model misclassified DB cases most frequently (18.7%) and TB cases least (2.7%). Conclusions: Our study demonstrates the feasibility of NanoString technology for cross-platform validation of multiple transcriptomic signatures in parallel. This external cohort validated performance of all five signatures, including a novel sparse TB signature. Two exploratory multi-class models showed high potential accuracy across four distinct diagnostic groups

Rates of Anti-Tuberculosis Drug Resistance in Kampala-Uganda Are Low and Not Associated with HIV Infection

Background: Drug resistance among tuberculosis patients in sub-Saharan Africa is increasing, possibly due to association with HIV infection. We studied drug resistance and HIV infection in a representative sample of 533 smear-positive tuberculosis patients diagnosed in Kampala, Uganda. Methods/Principal Findings: Among 473 new patients, multidrug resistance was found in 5 (1.1%, 95% CI 0.3-2.5) and resistance to any drug in 57 (12.1%, 9.3-15.3). Among 60 previously treated patients this was 7 (11.7%, 4.8-22.6) and 17 (28.3%; 17.5-41.4), respectively. Of 517 patients with HIV results, 165 (31.9%, 27.9-36.1) tested positive. Neither multidrug (adjusted odds ratio (ORadj) 0.7; 95% CI 0.19-2.6) nor any resistance (ORadj 0.7; 0.43-1.3) was associated with HIV status. Primary resistance to any drug was more common among patients who had worked in health care (ORadj 3.5; 1.0-12.0). Conclusion/Significance: Anti-tuberculosis drug resistance rates in Kampala are low and not associated with HIV infection, but may be associated with exposure during health car