A novel regulatory pathway of Desmoglein-3 in keratinocyte stress response

The desmosomal cadherin Desmoglein-3 (Dsg3) is a core adhesion component in desmosome junctions that occur with high frequency in the stratified squamous epithelial membrane lining the skin and mucous membrane. Dsg3 is identified as a major target of the circulating autoantibodies in Pemphigus Vulgaris (PV), an autoimmune blistering skin disease, and many signaling pathways have been demonstrated to be activated by PV-IgG targeting Dsg3, highlighting its role as a surface regulator in cell signaling. A recent study has revealed an unprecedented role of Dsg3 in the suppression of p53 and shows dysfunction of this pathway in PV. Furthermore, reciprocal crosstalk between p53 and yes-associated protein (YAP) downstream of Dsg3 has been observed in keratinocytes in which increased YAP expression causes suppression of p53 or vice versa. Both p53 and YAP are the crucial nuclear transcription factors involved in regulating cell fate decision, adaptation and tissue integrity in response to environmental and biological cues and are mutually exclusive in human cancer. In this review, we discuss Dsg3 signaling role in keratinocyte response to stress signals, with the highlight on our recent findings of the Dsg3/p53 pathway in the control of cell proliferation and tissue homeostasis, including the DNA integrity, beyond its function in cell-cell adhesion

Factors influencing intention to create new venture among young graduates

The purpose of this paper is to investigate the factors that are influencing the young graduates for intention to create new venture. The study further highlights how the attraction, networking support, entrepreneurial capabilities, self-independence and self-reliance influence the young students to initiate their new businesses. The sample size of this study was 255 final semester students of various disciplines in different universities from Islamabad and Rawalpindi. The survey based questionnaire was used for data collection. Based on findings this study concludes that all variables, included in the study, play a vital role in new venture creation. Therefore, on the basis of findings this study concludes that young students are more motivated towards new venture creation and start their own businesses.Influencing factors, new venture creation, different disciplines, young graduates, motivation

A simple method to reduce infection of ventriculoperitoneal shunts Clinical article

Object: Postoperative shunt infection is the most common and feared complication of ventriculoperitoneal (VP) shunt placement for treatment of hydrocephalus. The rate of shunt infection is highest in the 1st postoperative month. The most common organisms responsible for shunt infection include coagulase-negative Staphylococcus and Staphylococcus aureus. This suggests a transfer of Patient\u27s skin flora via the surgeons\u27 glove as a possible means of infection. The authors conducted a study to determine if the rate of postoperative shunt infections could be reduced simply by changing gloves before handling the shunt catheter. Methods: A total of 111 neonates born with congenital hydrocephalus requiring a VP shunt were enrolled retrospectively and divided into 2 groups: a control group of 54 neonates treated with standard protocol VP shunt placement (Group A) and a treatment group of 57 neonates in whom, after initially double gloving, the outer pair of gloves was removed before handling the shunt catheter (Group B). Shunt infection rates were compared up to 6 months postoperatively. Results: There was a statistically significant reduction of infection rate from 16.33% in Group A (control) to 3.77% in Group B (p = 0.0458). Conclusions: The study shows that a changing of gloves before handling the shunt catheter may be a simple and cost-effective way to reduce the burden of postoperative shunt infections

Physics-constrained neural differential equations for learning multi-ionic transport

Continuum models for ion transport through polyamide nanopores require solving partial differential equations (PDEs) through complex pore geometries. Resolving spatiotemporal features at this length and time-scale can make solving these equations computationally intractable. In addition, mechanistic models frequently require functional relationships between ion interaction parameters under nano-confinement, which are often too challenging to measure experimentally or know a priori. In this work, we develop the first physics-informed deep learning model to learn ion transport behaviour across polyamide nanopores. The proposed architecture leverages neural differential equations in conjunction with classical closure models as inductive biases directly encoded into the neural framework. The neural differential equations are pre-trained on simulated data from continuum models and fine-tuned on independent experimental data to learn ion rejection behaviour. Gaussian noise augmentations from experimental uncertainty estimates are also introduced into the measured data to improve model generalization. Our approach is compared to other physics-informed deep learning models and shows strong agreement with experimental measurements across all studied datasets.Comment: 11 page

Attention-enhanced neural differential equations for physics-informed deep learning of ion transport

Species transport models typically combine partial differential equations (PDEs) with relations from hindered transport theory to quantify electromigrative, convective, and diffusive transport through complex nanoporous systems; however, these formulations are frequently substantial simplifications of the governing dynamics, leading to the poor generalization performance of PDE-based models. Given the growing interest in deep learning methods for the physical sciences, we develop a machine learning-based approach to characterize ion transport across nanoporous membranes. Our proposed framework centers around attention-enhanced neural differential equations that incorporate electroneutrality-based inductive biases to improve generalization performance relative to conventional PDE-based methods. In addition, we study the role of the attention mechanism in illuminating physically-meaningful ion-pairing relationships across diverse mixture compositions. Further, we investigate the importance of pre-training on simulated data from PDE-based models, as well as the performance benefits from hard vs. soft inductive biases. Our results indicate that physics-informed deep learning solutions can outperform their classical PDE-based counterparts and provide promising avenues for modelling complex transport phenomena across diverse applications.Comment: 8 pages, 2 figures. Accepted in the NeurIPS Machine Learning and the Physical Sciences Worksho

Corporate Social Responsibility, Sustainability Governance and Sustainable Performance: A Preliminary Insight

This conceptual paper aims to investigate corporate social responsibility (CSR) practises in the tourism sector. Drawing on the existing literature, this study conceptualises the linkage between CSR, sustainability governance, and sustainable performance. Moreover, this study conceptualises three sub-dimensions of CSR. The integration of CSR in the tourism sector is significant and novel. An analytical review is conducted to present conceptual linkage and research implications. The finding implies that CSR positively influences the sustainable performance of organisations and sustainable governance plays a mediating role between relationships. This study provides important implications that help tourism industry practitioners to realise the significance of reducing environmental and social problems, which cause by tourism activities. Further, this study obtains support from institutional theory to explain the relationships of governance mechanism and CSR that leads to economic performance as well as create value for nature and the local community. Additionally, the future direction of research is provided that highlights some important avenues in the sustainability fiel

RF MEMS Based Tunable Bowtie Shaped Substrate Integrated Waveguide Filter

A tunable bandpass filter based on a technique that utilizes substrate integrated waveguide (SIW) and double coupling is presented. The SIW based bandpass filter is implemented using a bowtie shaped resonator structure. The bowtie shaped filter exhibits similar performance as found in rectangular and circular shaped SIW based bandpass filters. This concept reduces the circuit foot print of SIW; along with miniaturization high quality factor is maintained by the structure. The design methodology for single-pole triangular resonator structure is presented. Two different inter-resonator couplings of the resonators are incorporated in the design of the two-pole bowtie shaped SIW bandpass filter, and switching between the two couplings using a packaged RF MEMS switch delivers the tunable filter. A tunning of 1 GHz is achieved for two frequency states of 6.3 and 7.3 GHz. The total size of the circuit is 70mm x 36mm x 0.787 mm (LxWxH)