Concentration invariance—the capacity to recognize a given odorant (analyte) across a range of concentrations—is an unusually difficult problem in the olfactory modality. Nevertheless, humans and other animals are able to recognize known odors across substantial concentration ranges, and this concentration invariance is a highly desirable property for artificial systems as well. Several properties of olfactory systems have been proposed to contribute to concentration invariance, but none of these alone can plausibly achieve full concentration invariance. We here propose that the mammalian olfactory system uses at least six computational mechanisms in series to reduce the concentration-dependent variance in odor representations to a level at which different concentrations of odors evoke reasonably similar representations, while preserving variance arising from differences in odor quality. We suggest that the residual variance then is treated like any other source of stimulus variance, and categorized appropriately into “odors” via perceptual learning. We further show that naïve mice respond to different concentrations of an odorant just as if they were differences in quality, suggesting that, prior to odor categorization, the learning-independent compensatory mechanisms are limited in their capacity to achieve concentration invariance.

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Many microorganisms such as bacteria and fungi possess so-called capsules made of polysaccharides which protect these microorganisms from environmental insults and host immune defenses. The polysaccharide capsule of Cryptococcus neoformans, a human pathogenic yeast, is capable of self-assembly, composed mostly of glucuronoxylomannan (GXM), a polysaccharide with a molecular weight of approximately 2,000,000, and has several layers with different densities. The objective of this study was to model pore-hindered diffusion and binding of the GXM-specific antibody within the C. neoformans capsule. Using the finite-element method (FEM), we created a model which represents the in vivo binding of a GXM-specific antibody to a C. neoformans cell taking into account the intravenous infusion time of antibody, antibody diffusion through capsular pores, and Michaelis-Menten kinetics of antibody binding to capsular GXM. The model predicted rapid diffusion of antibody to all regions of the capsule where the pore size was greater than the Stokes diameter of the antibody. Binding occurred primarily at intermediate regions of the capsule. The GXM concentration in each capsular region was the principal determinant of the steady-state antibody-GXM complex concentration, while the forward binding rate constant influenced the rate of complex formation in each region. The concentration profiles predicted by the model closely matched experimental immunofluorescence data. Inclusion of different antibody isotypes (IgG, IgA, and IgM) into the modeling algorithm resulted in similar complex formation in the outer capsular regions, but different depths of binding at the inner regions. These results have implications for the development of new antibody-based therapies.

While microfluidic technology is reaching a new level of maturity for macromolecular assays, cell-based assays are still at an infant stage 1 . This is largely due to the difficulty with which one can create a cell-compatible and steady microenvironment using conventional microfabrication techniques and materials. We address this problem via the introduction of a novel microfabrication material, agarose gel, as the base material for the microfluidic device. Agarose gel is highly malleable, and permeable to gas and nutrients necessary for cell survival, and thus an ideal material for cell-based assays. We have shown previously that agarose gel based devices have been successful in studying bacterial and neutrophil cell migration 2 . In this report, three parallel microfluidic channels are patterned in an agarose gel membrane of about 1mm thickness. Constant flows with media/buffer are maintained in the two side channels using a peristaltic pump. Cells are maintained in the center channel for observation. Since the nutrients and chemicals in the side channels are constantly diffusing from the side to center channel, the chemical environment of the center channel is easily controlled via the flow along the side channels. Using this device, we demonstrate that the movement of neural stem cells can be monitored optically with ease under various chemical conditions, and the experimental results show that the over expression of epidermal growth factor receptors (EGFR) enhances the motility of neural stem cells. Motility of neural stem cells is an important biomarker for assessing cells aggressiveness, thus tumorigenic factor 3 . Deciphering the mechanism underlying NSC motility will yield insight into both disorders of neural development and into brain cancer stem cell invasion. Protocol Procedure Coating slides with fibronectinPrior to the assembling of the microfluidic device, sterilize glass slides with fibronectin. Coat the slides in a biohood to maintain sterility. Align a sterile PDMS spacer along the edges of the slide and mark the side that is facing up with a permanent marker. Pipette 1 ml of a 5 μg/ml solution of fibronectin (Sigma) inside the PDMS spacer over the entirety of the glass slide. Leave the slides undisturbed for an hour, then dry completely using an N2 gun. The slides can be stored at 4 o C for later experiments. Assembling the deviceThe entire device assembly protocol is done in a biohood under sterile conditions, using the following procedures: Clean the silicon master with the microchannels patterned on it by wiping it down with 70% ethanol and drying with the N2 gun. Place a sterile PDMS spacer of 1 mm height using forceps around the relief features of the master. 2. Prepare the agarose gel used in the device by weighing 0.3 g of agarose powder (Fisher Scientific) and 10 ml of CO2-independent media (Invitrogen) in a 50 ml beaker. Stir the mixture with a spatula and heat in a microwave for 20 seconds on HIGH. If undissolved granules are present, heat the mixture for another 10 seconds ...

13The cell wall is a crucial structural feature in the vast majority of bacteria and 14 comprises a rigid, covalently closed, mesh-like network of peptidoglycan (PG) strands. 15While PG synthesis is important for bacterial survival under many conditions, the cell wall 16is also a dynamic structure, undergoing degradation and remodeling by so-called 17 "autolysins", enzymes that break bonds in the PG network. Cell division, for example, 18 requires extensive PG remodeling and separation of daughter cells, which depends 19 primarily upon the activity of amidases. However, in V. cholerae, we have found that 20 amidase activity alone is insufficient for daughter cell separation and that the lytic 21 transglycosylases RlpA and MltC both contribute to this process. MltC and RlpA both 22 amidase and to clear PG debris that may block the completion of outer-membrane 1 invagination. 2 3 191(13), 4186-4194. https://doi.

OBJECTIVES: Saddle pulmonary embolism is an uncommon type of venous thromboembolism that can lead to sudden hemodynamic collapse and death. Saddle pulmonary embolism can be difficult to recognize, and data on its presentation, clinical features, and associated complications are sparse. We sought to characterize patients with saddle pulmonary embolism. DESIGN: The Montage software (Nuance, Burlington, MA) was used to identify patients to create a retrospective cohort study. SETTING: Montefiore Medical Center from January 1, 2012, to December 31, 2018. PATIENTS: All subjects diagnosed with saddle pulmonary embolism in above time period. INTERVENTIONS: Charts were reviewed for demographics, diagnostics, laboratory data, presenting vital signs, inhospital mortality, 6-month survival, and prevalence of recurrent venous thromboembolism. MEASUREMENTS AND MAIN RESULTS: About 120 patients with saddle pulmonary embolism were identified. Median age was 61 years and 57.5% were women. Events were provoked by a transient risk factor in 43.3%. On presentation, median mean arterial pressures were normal (93 mm Hg). Only five of 120 of patients (4.2%) presented with vitals concerning for massive pulmonary embolism. We found a 9.2% inhospital mortality; an additional 8.6% died within 6 months of discharge. Inhospital mortality was higher in women (11.6%), compared with men (3.9%), but this was not significant ( p = 0.28). In 10 patients, both ventilation/perfusion scans and computed tomography pulmonary angiogram were performed. None of the ventilation/perfusion scans diagnosed saddle pulmonary embolism. Thrombus was visualized in the right heart in eight of 105 (7.6%), and this group had a higher inhospital mortality (37.5%). Recurrent venous thromboembolism occurred in 13 of 85 of survivors (15.3%). CONCLUSIONS: Despite presenting without the accepted clinical criteria for massive pulmonary embolism, saddle pulmonary embolism has a very high inhospital mortality. Ventilation/perfusion scan is unable to diagnose saddle pulmonary embolism. Visualized right heart thrombi portend an even higher inhospital mortality.