Surface Defect incorporated Diamond Machining of Silicon

This paper reports the performance enhancement benefits in diamond turning of the silicon wafer by incorporation of the Surface Defect Machining (SDM) method. The hybrid micromachining methods usually require additional hardware to leverage the added advantage of hybrid technologies such as laser heating, cryogenic cooling, electric pulse or ultrasonic elliptical vibration. The SDM method tested in this paper does not require any such additional baggage and is easy to implement in a sequential micro-machining mode. This paper made use of Raman spectroscopy data, average surface roughness data and imaging data of the cutting chips of silicon for drawing a comparison between conventional Single Point Diamond Turning (SPDT) and SDM while incorporating surface defects in the (i) circumferential and (ii) radial directions. Complimentary 3D Finite Element Analysis (FEA) was performed to analyse the cutting forces and the evolution of residual stress on the machined wafer. It was found that the surface defects generated in the circumferential direction with an interspacing of 1 mm revealed the lowest average surface roughness (Ra) of 3.2 nm as opposed to 8 nm Ra obtained through conventional SPDT using the same cutting parameters. The observation of the Raman spectroscopy performed on the cutting chips showed remnants of phase transformation during the micromachining process in all cases. FEA was used to extract quantifiable information about the residual stress as well as the sub-surface integrity and it was discovered that the grooves made in the circumferential direction gave the best machining performance. The information being reported here is expected to provide an avalanche of opportunities in the SPDT area for low-cost machining solution for a range of other nominal hard, brittle materials such as SiC, ZnSe and GaAs as well as hard steels

Immunomodulation by Mesenchymal Stem Cells A Potential Therapeutic Strategy for Type 1 Diabetes

Mesenchymal stem cells (MSCs) are pluripotent stromal cells that have the potential to give rise to cells of diverse lineages. Interestingly, MSCs can be found in virtually all postnatal tissues. The main criteria currently used to characterize and identify these cells are the capacity for self-renewal and differentiation into tissues of mesodermal origin, combined with a lack in expression of certain hematopoietic molecules. Because of their developmental plasticity, the notion of MSC-based therapeutic intervention has become an emerging strategy for the replacement of injured tissues. MSCs have also been noted to possess the ability to impart profound immunomodulatory effects in vivo. Indeed, some of the initial observations regarding MSC protection from tissue injury once thought mediated by tissue regeneration may, in reality, result from immunomodulation. Whereas the exact mechanisms underlying the immunomodulatory functions of MSC remain largely unknown, these cells have been exploited in a variety of clinical trials aimed at reducing the burden of immune-mediated disease. This article focuses on recent advances that have broadened our understanding of the immunomodulatory properties of MSC and provides insight as to their potential for clinical use as a cell-based therapy for immune-mediated disorders and, in particular, type 1 diabetes

Three-dimensional numerical model of heat losses from district heating network pre-insulated pipes buried in the ground

The purpose of the paper is to investigate the challenges in modelling the energy losses of heating networks and to analyse the factors that influence them. The verification of the simulation was conducted on a test stand in-situ and based on the measurements of the testing station, a database for the final version of the numerical model was developed and a series of simulations were performed. Examples of the calculated results are shown in the graphs. The paper presents an innovative method of identify the energy losses of underground heating network pipelines and quantify the temperature distribution around them, in transient working conditions. The presented method makes use of numerical models and measured data of actual objects.The dimensions of the pipelines used were 6m wide, 8m high and 1m in depth, while they were simulated under conditions of zero heat flow in the ground, in the perpendicular to the sides direction of the calculated area and considering the effects of ground's thermal conductivity. The mesh was developed using advanced functions, which resulted its high quality with the average orthogonal quality of 0.99 (close to 1.00) and Skewness of 0.05 (between 0.00 and 0.25). To achieve better accuracy of the simulation model, the initial conditions were determined based on the numerical results of a three-dimensional analysis of heat losses, in steady state conditions in a single moment. The validation process confirmed the high quality of the model, as the differences between the ground temperatures were approximately 0.1°C

Insulin-induced remission in new-onset NOD mice is maintained by the PD-1–PD-L1 pathway

The past decade has seen a significant increase in the number of potentially tolerogenic therapies for treatment of new-onset diabetes. However, most treatments are antigen nonspecific, and the mechanism for the maintenance of long-term tolerance remains unclear. In this study, we developed an antigen-specific therapy, insulin-coupled antigen-presenting cells, to treat diabetes in nonobese diabetic mice after disease onset. Using this approach, we demonstrate disease remission, inhibition of pathogenic T cell proliferation, decreased cytokine production, and induction of anergy. Moreover, we show that robust long-term tolerance depends on the programmed death 1 (PD-1)–programmed death ligand (PD-L)1 pathway, not the distinct cytotoxic T lymphocyte–associated antigen 4 pathway. Anti–PD-1 and anti–PD-L1, but not anti–PD-L2, reversed tolerance weeks after tolerogenic therapy by promoting antigen-specific T cell proliferation and inflammatory cytokine production directly in infiltrated tissues. PD-1–PD-L1 blockade did not limit T regulatory cell activity, suggesting direct effects on pathogenic T cells. Finally, we describe a critical role for PD-1–PD-L1 in another powerful immunotherapy model using anti-CD3, suggesting that PD-1–PD-L1 interactions form part of a common pathway to selectively maintain tolerance within the target tissues

UNE TUMEUR VESICALE RARE : L’ADENOCARCINOME COLLOÏDE PRIMITIF. A PROPOS D’UNE OBSERVATION ET REVUE DE LA LITTERATURE

Primary mucinous adenocarcinoma is a rare bladder’s tumor, accounting for 14,6% of all primary bladder’s adenocarcinomas. Immunohistochemical analysis is important to define the primitive origin of the tumor and to eliminate a dissemination of other adenocarcinomas such as colorectal, prostate and gynecological tract or an urachous degenerescence. The treatment is meanly surgical by radical cystectomy. The prognosis becomes poor. In this observation, we report the case of a 52 year’s old man treated for a bladder’s primary mucinous adenocarcinoma by a radical cystectomiy and enterocystoplasty. He’s still alive after four years.L’adénocarcinome colloïde primitif est une tumeur vésicale rare, représentant 14,6 % de l’ensemble des adénocarcinomes primitifs de vessie. Il siège fréquemment au niveau du dôme de la vessie. L’étude immunohistochimique est capitale pour retenir la nature primitive de la tumeur et éliminer une origine ouraquienne ou une extension prostatique, colorectale ou gynécologique. Le traitement est essentiellement chirurgical dominé par la cystectomie totale. Le pronostic de cette tumeur demeure réservé. Dans cette observation, nous rapportons le cas d’un patient de 51 ans pris en charge pour adénocarcinome colloïde primitif de vessie, traité par cystectomie totale et entérocystoplastie de remplacement. Le recul est de 04 ans

The effects of breastfeeding on retinoblastoma development: Results from an international multicenter retinoblastoma survey

The protective effects of breastfeeding on various childhood malignancies have been established but an association has not yet been determined for retinoblastoma (RB). We aimed to further investigate the role of breastfeeding in the severity of nonhereditary RB development, assessing relationship to (1) age at diagnosis, (2) ocular prognosis, measured by International Intraocular RB Classification (IIRC) or Intraocular Classification of RB (ICRB) group and success of eye salvage, and (3) extraocular involvement. Analyses were performed on a global dataset subgroup of 344 RB patients whose legal guardian(s) consented to answer a neonatal questionnaire. Patients with undetermined or mixed feeding history, family history of RB, or sporadic bilateral RB were excluded. There was no statistically significant difference between breastfed and formula-fed groups in (1) age at diagnosis (p = 0.20), (2) ocular prognosis measures of IIRC/ICRB group (p = 0.62) and success of eye salvage (p = 0.16), or (3) extraocular involvement shown by International Retinoblastoma Staging System (IRSS) at presentation (p = 0.74), lymph node involvement (p = 0.20), and distant metastases (p = 0.37). This study suggests that breastfeeding neither impacts the sporadic development nor is associated with a decrease in the severity of nonhereditary RB as measured by age at diagnosis, stage of disease, ocular prognosis, and extraocular spread. A further exploration into the impact of diet on children who develop RB is warranted

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Immunomodulation by Mesenchymal Stem Cells : A Potential Therapeutic Strategy for Type 1 Diabetes

Mesenchymal stem cells (MSCs) are pluripotent stromal cells that have the potential to give rise to cells of diverse lineages. Interestingly, MSCs can be found in virtually all postnatal tissues. The main criteria currently used to characterize and identify these cells are the capacity for self-renewal and differentiation into tissues of mesodermal origin, combined with a lack in expression of certain hematopoietic molecules. Because of their developmental plasticity, the notion of MSC-based therapeutic intervention has become an emerging strategy for the replacement of injured tissues. MSCs have also been noted to possess the ability to impart profound immunomodulatory effects in vivo. Indeed, some of the initial observations regarding MSC protection from tissue injury once thought mediated by tissue regeneration may, in reality, result from immunomodulation. Whereas the exact mechanisms underlying the immunomodulatory functions of MSC remain largely unknown, these cells have been exploited in a variety of clinical trials aimed at reducing the burden of immune-mediated disease. This article focuses on recent advances that have broadened our understanding of the immunomodulatory properties of MSC and provides insight as to their potential for clinical use as a cell-based therapy for immune-mediated disorders and, in particular, type 1 diabetes

Air quality and urban sustainable development: the application of machine learning tools

[EN] Air quality has an efect on a population¿s quality of life. As a dimension of sustainable urban development, governments have been concerned about this indicator. This is refected in the references consulted that have demonstrated progress in forecasting pollution events to issue early warnings using conventional tools which, as a result of the new era of big data, are becoming obsolete. There are a limited number of studies with applications of machine learning tools to characterize and forecast behavior of the environmental, social and economic dimensions of sustainable development as they pertain to air quality. This article presents an analysis of studies that developed machine learning models to forecast sustainable development and air quality. Additionally, this paper sets out to present research that studied the relationship between air quality and urban sustainable development to identify the reliability and possible applications in diferent urban contexts of these machine learning tools. To that end, a systematic review was carried out, revealing that machine learning tools have been primarily used for clustering and classifying variables and indicators according to the problem analyzed, while tools such as artifcial neural networks and support vector machines are the most widely used to predict diferent types of events. The nonlinear nature and synergy of the dimensions of sustainable development are of great interest for the application of machine learning tools.Molina-Gómez, NI.; Díaz-Arévalo, JL.; López Jiménez, PA. (2021). Air quality and urban sustainable development: the application of machine learning tools. 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