Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment

Osteosarcoma is the most common malignant primary bone tumor. Standard treatment includes pre-operative chemotherapy followed by surgical resection. The response to treatment as measured by ratio of necrotic tumor area to overall tumor area is a known prognostic factor for overall survival. This assessment is currently done manually by pathologists by looking at glass slides under the microscope which may not be reproducible due to its subjective nature. Convolutional neural networks (CNNs) can be used for automated segmentation of viable and necrotic tumor on osteosarcoma whole slide images. One bottleneck for supervised learning is that large amounts of accurate annotations are required for training which is a time-consuming and expensive process. In this paper, we describe Deep Interactive Learning (DIaL) as an efficient labeling approach for training CNNs. After an initial labeling step is done, annotators only need to correct mislabeled regions from previous segmentation predictions to improve the CNN model until the satisfactory predictions are achieved. Our experiments show that our CNN model trained by only 7 hours of annotation using DIaL can successfully estimate ratios of necrosis within expected inter-observer variation rate for non-standardized manual surgical pathology task.Comment: Accepted at MICCAI 202

Gastroesophageal reflux disease in 2006: The imperfect diagnosis

There continues to be significant controversy related to diagnostic testing for gastroesophageal reflux disease (GERD). Clearly, barium contrast fluoroscopy is superior to any other test in defining the anatomy of the upper gastrointestinal (UGI) tract. Although fluoroscopy can demonstrate gastroesophageal reflux (GER), this observation does not equate to GERD. Fluoroscopy time should not be prolonged to attempt to demonstrate GER during barium contrast radiography. There are no data to justify prolonging fluoroscopy time to perform provocative maneuvers to demonstrate reflux during barium contrast UGI series. Symptoms of GERD may be associated with physiologic esophageal acid exposure measured by intraesophageal pH monitoring, and a significant percentage of patients with abnormal esophageal acid exposure have no or minimal clinical symptoms of reflux. Abnormal acid exposure defined by pH monitoring over a 24-h period does not equate to GERD. In clinical practice presumptive diagnosis of GERD is reasonably assumed by substantial reduction or elimination of suspected reflux symptoms during therapeutic trial of acid reduction therapy

Single-Cell Profiling Reveals the Origin of Phenotypic Variability in Adipogenesis

Phenotypic heterogeneity in a clonal cell population is a well-observed but poorly understood phenomenon. Here, a single-cell approach is employed to investigate non-mutative causes of phenotypic heterogeneity during the differentiation of 3T3-L1 cells into fat cells. Using coherent anti-Stokes Raman scattering microscopy and flow cytometry, adipogenic gene expression, insulin signaling, and glucose import are visualized simultaneously with lipid droplet accumulation in single cells. Expression of adipogenic genes PPARγ, C/EBPα, aP2, LP2 suggests a commitment to fat cell differentiation in all cells. However, the lack of lipid droplet in many differentiating cells suggests adipogenic gene expression is insufficient for lipid droplet formation. Instead, cell-to-cell variability in lipid droplet formation is dependent on the cascade responses of an insulin signaling pathway which includes insulin sensitivity, kinase activity, glucose import, expression of an insulin degradation enzyme, and insulin degradation rate. Increased and prolonged insulin stimulation promotes lipid droplet accumulation in all differentiating cells. Single-cell profiling reveals the kinetics of an insulin signaling cascade as the origin of phenotypic variability in drug-inducible adipogenesis

Predictors of linkage to care following community-based HIV counseling and testing in rural Kenya

Despite innovations in HIV counseling and testing (HCT), important gaps remain in understanding linkage to care. We followed a cohort diagnosed with HIV through a community-based HCT campaign that trained persons living with HIV/AIDS (PLHA) as navigators. Individual, interpersonal, and institutional predictors of linkage were assessed using survival analysis of self-reported time to enrollment. Of 483 persons consenting to follow-up, 305 (63.2%) enrolled in HIV care within 3 months. Proportions linking to care were similar across sexes, barring a sub-sample of men aged 18–25 years who were highly unlikely to enroll. Men were more likely to enroll if they had disclosed to their spouse, and women if they had disclosed to family. Women who anticipated violence or relationship breakup were less likely to link to care. Enrolment rates were significantly higher among participants receiving a PLHA visit, suggesting that a navigator approach may improve linkage from community-based HCT campaigns.Vestergaard Frandse

Inclusive V0V^0 Production Cross Sections from 920 GeV Fixed Target Proton-Nucleus Collisions

Inclusive differential cross sections $d\sigma_{pA}/dx_F$ and $d\sigma_{pA}/dp_t^2$ for the production of \kzeros, \lambdazero, and \antilambda particles are measured at HERA in proton-induced reactions on C, Al, Ti, and W targets. The incident beam energy is 920 GeV, corresponding to $\sqrt {s} = 41.6$ GeV in the proton-nucleon system. The ratios of differential cross sections \rklpa and \rllpa are measured to be $6.2\pm 0.5$ and $0.66\pm 0.07$, respectively, for \xf $\approx-0.06$. No significant dependence upon the target material is observed. Within errors, the slopes of the transverse momentum distributions $d\sigma_{pA}/dp_t^2$ also show no significant dependence upon the target material. The dependence of the extrapolated total cross sections $\sigma_{pA}$ on the atomic mass $A$ of the target material is discussed, and the deduced cross sections per nucleon $\sigma_{pN}$ are compared with results obtained at other energies.Comment: 17 pages, 7 figures, 5 table

Design of a Protective Single-Dose Intranasal Nanoparticle-Based Vaccine Platform for Respiratory Infectious Diseases

Despite the successes provided by vaccination, many challenges still exist with respect to controlling new and re-emerging infectious diseases. Innovative vaccine platforms composed of adaptable adjuvants able to appropriately modulate immune responses, induce long-lived immunity in a single dose, and deliver immunogens in a safe and stable manner via multiple routes of administration are needed. This work describes the development of a novel biodegradable polyanhydride nanoparticle-based vaccine platform administered as a single intranasal dose that induced long-lived protective immunity against respiratory disease caused by Yesinia pestis, the causative agent of pneumonic plague. Relative to the responses induced by the recombinant protein F1-V alone and MPLA-adjuvanted F1-V, the nanoparticle-based vaccination regimen induced an immune response that was characterized by high titer and high avidity IgG1 anti-F1-V antibody that persisted for at least 23 weeks post-vaccination. After challenge, no Y. pestis were recovered from the lungs, livers, or spleens of mice vaccinated with the nanoparticle-based formulation and histopathological appearance of lung, liver, and splenic tissues from these mice post-vaccination was remarkably similar to uninfected control mice