Growth factors in lung development and disease: friends or foe?

Growth factors mediate tissue interactions and regulate a variety of cellular functions that are critical for normal lung development and homeostasis. Besides their involvement in lung pattern formation, growth and cell differentiation during organogenesis, these factors have been also implicated in modulating injury-repair responses of the adult lung. Altered expression of growth factors, such as transforming growth factor β1, vascular endothelial growth factor and epidermal growth factor, and/or their receptors, has been found in a number of pathological lung conditions. In this paper, we discuss the dual role of these molecules in mediating beneficial feedback responses or responses that can further damage lung integrity; we shall also discuss the basis for their prospective use as therapeutic agents

A controlled diaphyseal expansion osteotomy for the implantation of a wagner cone prosthesis in a stenotic femoral canal encountered in a polio limb: a case report of the technique

Dysplastic hips pose a significant technical challenge to arthroplasty surgeons. Such deformed hips might be encountered either in congenital and developmental conditions or as sequel of neuromuscular disorders (like poliomyelitis), following infections, or after childhood surgical procedures of the hip. The scientific literature, focussing on total hip arthroplasty (THA), for coxarthrosis in patients with residual poliomyelitis, is relatively rare. Several anatomical distortions seen in dysplastic femurs are described, one of which includes an undersized diaphysis with a stenotic medullary canal. We present a case of a 28 years old male with residual poliomyelitis who underwent a cementless THA for a non united transcervical neck of femur fracture. The patient had an extremely narrow medullary canal which posed a formidable difficulty in the procedure. This was overcome by a novel diaphyseal expansion osteotomy, which enabled the implantation of Wagner Cone prosthesis. This technique, which has hitherto not been described in the literature, can significantly facilitate the implantation of an appropriately sized stem in an undersized femur while at the same time ensuring a good long-term result

Separating multiscale Battery dynamics and predicting multi-step ahead voltage simultaneously through a data-driven approach

Accurate prediction of battery performance under various ageing conditions is necessary for reliable and stable battery operations. Due to complex battery degradation mechanisms, estimating the accurate ageing level and ageing-dependent battery dynamics is difficult. This work presents a health-aware battery model that is capable of separating fast dynamics from slowly varying states of degradation and state of charge (SOC). The method is based on a sequence-to-sequence learning-based encoder-decoder model, where the encoder infers the slowly varying states as the latent space variables in an unsupervised way, and the decoder provides health-aware multi-step ahead prediction conditioned on slowly varying states from the encoder. The proposed approach is verified on a Lithium-ion battery ageing dataset based on real driving profiles of electric vehicles.Comment: 6 pages, 10 figures, IEEE Vehicle Power and Propulsion confernce(IEEE VPPC 2023

Quantitative modeling of \textit{in situ} x-ray reflectivity during organic molecule thin film growth

Synchrotron-based x-ray reflectivity is increasingly employed as an \textit{in situ} probe of surface morphology during thin film growth, but complete interpretation of the results requires modeling the growth process. Many models have been developed and employed for this purpose, yet no detailed, comparative studies of their scope and accuracy exists in the literature. Using experimental data obtained from hyperthermal deposition of pentane and diindenoperylene (DIP) on SiO$_2$, we compare and contrast three such models, both with each other and with detailed characterization of the surface morphology using ex-situ atomic force microscopy (AFM). These two systems each exhibit particular phenomena of broader interest: pentacene/SiO$_2$ exhibits a rapid transition from rough to smooth growth. DIP/SiO$_2$, under the conditions employed here, exhibits growth rate acceleration due to a different sticking probability between the substrate and film. In general, \textit{independent of which model is used}, we find good agreement between the surface morphology obtained from fits to the \insitu x-ray data with the actual morphology at early times. This agreement deteriorates at later time, once the root-mean squared (rms) film roughness exceeds about 1 ML. A second observation is that, because layer coverages are under-determined by the evolution of a single point on the reflectivity curve, we find that the best fits to reflectivity data --- corresponding to the lowest values of $\chi_\nu^2$ --- do not necessarily yield the best agreement between simulated and measured surface morphologies. Instead, it appears critical that the model reproduce all local extrema in the data. In addition to showing that layer morphologies can be extracted from a minimal set of data, the methodology established here provides a basis for improving models of multilayer growth by comparison to real systems.Comment: 34 pages (double-spaced, including figures and references), 10 figures, 3 appendice

EgoEnv: Human-centric environment representations from egocentric video

First-person video highlights a camera-wearer's activities in the context of their persistent environment. However, current video understanding approaches reason over visual features from short video clips that are detached from the underlying physical space and capture only what is immediately visible. To facilitate human-centric environment understanding, we present an approach that links egocentric video and the environment by learning representations that are predictive of the camera-wearer's (potentially unseen) local surroundings. We train such models using videos from agents in simulated 3D environments where the environment is fully observable, and test them on human-captured real-world videos from unseen environments. On two human-centric video tasks, we show that models equipped with our environment-aware features consistently outperform their counterparts with traditional clip features. Moreover, despite being trained exclusively on simulated videos, our approach successfully handles real-world videos from HouseTours and Ego4D, and achieves state-of-the-art results on the Ego4D NLQ challenge. Project page: https://vision.cs.utexas.edu/projects/ego-env/Comment: Published in NeurIPS 2023 (Oral

After the Dividend:Caring for a Greying India

As in any other society, in India too, the economic security of the aged is based on three main sources: their own income and savings, support from the extended family, particularly children, and support from the state. As India moves rapidly towards a demographic future in which the elderly form a large part of the population, this article examines trends in each of the three supports. While doing so it identifies the policy challenges and lists suggestions to deal with them

Quantifying Outlierness of Funds from their Categories using Supervised Similarity

Mutual fund categorization has become a standard tool for the investment management industry and is extensively used by allocators for portfolio construction and manager selection, as well as by fund managers for peer analysis and competitive positioning. As a result, a (unintended) miscategorization or lack of precision can significantly impact allocation decisions and investment fund managers. Here, we aim to quantify the effect of miscategorization of funds utilizing a machine learning based approach. We formulate the problem of miscategorization of funds as a distance-based outlier detection problem, where the outliers are the data-points that are far from the rest of the data-points in the given feature space. We implement and employ a Random Forest (RF) based method of distance metric learning, and compute the so-called class-wise outlier measures for each data-point to identify outliers in the data. We test our implementation on various publicly available data sets, and then apply it to mutual fund data. We show that there is a strong relationship between the outlier measures of the funds and their future returns and discuss the implications of our findings.Comment: 8 pages, 5 tables, 8 figure

A case of pulmonary hemorrhage and renal failure

Background: Alveolar hemorrhage can be seen in many vasculitic disorders. However, granulomatosis polyangiitis (formerly Wegener’s granulomatosis) uncommonly presents with life threatening alveolar hemorrhage and has only been discussed in a few case reports [1]. Case Presentation: A 53 year old Caucasian male presented with hemoptysis and profound anemia. Two weeks prior, he had presented with abdominal pain with normal renal function and numerous pulmonary nodules. During the current admission, the patient was hypoxic with acute renal failure requiring hemodialysis. Urine sediment demonstrated dysmorphic red blood cells. A bronchoscopy revealed diffuse alveolar hemorrhage. The diagnosis of pulmonary-renal syndrome was made and therapeutic plasma exchange was initiated. Laboratory studies were significant for a c-ANCA titer positive at 1:640 FIU and anti-proteinase (PR)-3 antibody titer positive with 78.3 U/ml. Renal biopsy demonstrated necrotizing crescentic glomerulonephritis. A diagnosis of granulomatosis vasculitis was determined. Conclusion: Alveolar hemorrhage is rare to be the presenting symptom of granulomatosis vasculitis where the common presenting features are recurrent sinusitis, epistaxis, chronic otitis media or rhinitis. Physicians should consider granulomatosis vasculitis in the differential diagnosis of pulmonary-renal syndrome presenting with hemoptysis

Synthesis, characterization, molecular docking studies and biological activity ofcoumarin linked 2-pyridone heterocycles

In the present paper, the synthesis, characterization, antimicrobial activity and in silico molecular docking study of6-((arylidene)amino)-4-(4-chlorophenyl)-2-oxo-1-((1-(2-oxo-2H-chromen-3-yl)ethylidene)amino)-1,2-dihydropyridine-3,5-dicarbonitriles 4a-o have been reported. Compounds 4d, 4g, 4j, 4k, 4m and 4o show significant activity. Structuredetermination of the synthesized compounds has been done by the standard spectroscopic techniques. It is observed thatbiological activity is influenced by electronic environment of the molecules. Electron withdrawing group at para positionplays a major role for enhancing the biological activity for antibacterial activity and the electron donating group at paraposition for antifungal activity. Compounds 4a-o have been further evaluated for cytotoxicity on HeLa cells. From thecytotoxicity results, compounds have been found to possess low cytotoxicity with potent antimicrobial activity

Synthesis, characterization, molecular docking studies and biological activity of coumarin linked 2-pyridone heterocycles

231-237In the present paper, the synthesis, characterization, antimicrobial activity and in silico molecular docking study of 6-((arylidene)amino)-4-(4-chlorophenyl)-2-oxo-1-((1-(2-oxo-2H-chromen-3-yl)ethylidene)amino)-1,2-dihydropyridine-3,5-dicarbonitriles 4a-o have been reported. Compounds 4d, 4g, 4j, 4k, 4m and 4o show significant activity. Structure determination of the synthesized compounds has been done by the standard spectroscopic techniques. It is observed that biological activity is influenced by electronic environment of the molecules. Electron withdrawing group at para position plays a major role for enhancing the biological activity for antibacterial activity and the electron donating group at para position for antifungal activity. Compounds 4a-o have been further evaluated for cytotoxicity on HeLa cells. From the cytotoxicity results, compounds have been found to possess low cytotoxicity with potent antimicrobial activity