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In the last decade, there has been an increased appreciation for mitochondria as central hubs in diverse processes, such as cellular energy, immunity, and signal transduction. As such, we have become aware that mitochondrial dysfunction underlies many diseases, including primary (mutations in genes encoding mitochondrial proteins) and secondary mitochondrial diseases (mutations in non-mitochondrial genes critical for mitochondrial biology), as well as complex diseases with mitochondrial dysfunction (chronic or degenerative diseases). Evidence suggests that mitochondrial dysfunction may often precede other pathological signs in these disorders, further modulated by genetics, environment, and lifestyle.

Small angle x-ray scattering (SAXS) is a widely recognized solution for measuring complex nanostructures. With the increasing demand for accurately assessing structural characteristics and optimizing manufacturing processes, uncertainty quantification in SAXS inverse problems has become a critical issue. However, traditional methods face challenges such as slow computation speed and inaccurate estimation of multidimensional parameters. To overcome these issues, we propose an uncertainty quantification approach suitable for SAXS measurement that approximates the posterior using Bayesian deep learning. The effectiveness and reliability of our method are illustrated by assessing structural parameters of synthetic 2D Si grating samples. The uncertainty quantification takes only about 2.3 s, thousands of times faster than the conventional Markov Chain Monte Carlo (MCMC) methods. Also, our method has superior repeatability for parameter measurement compared to the MCMC approaches. It provides the potential of efficient and reliable SAXS measurement in increasingly intricate semiconductor manufacturing. [ABSTRACT FROM AUTHOR]

Abstract Background Amplification of the 8p11-12 region has been found in approximately 15% of human breast cancer and is associated with poor prognosis. Previous genomic analysis has led us to identify the endoplasmic reticulum (ER) lipid raft-associated 2 (ERLIN2) gene as one of the candidate oncogenes within the 8p11-12 amplicon in human breast cancer, particularly in the luminal subtype. ERLIN2, an ER membrane protein, has recently been identified as a novel mediator of ER-associated degradation. Yet, the biological roles of ERLIN2 and molecular mechanisms by which ERLIN2 coordinates ER pathways in breast carcinogenesis remain unclear. Methods We established the MCF10A-ERLIN2 cell line, which stably over expresses ERLIN2 in human nontransformed mammary epithelial cells (MCF10A) using the pLenti6/V5-ERLIN2 construct. ERLIN2 over expressing cells and their respective parental cell lines were assayed for in vitro transforming phenotypes. Next, we knocked down the ERLIN2 as well as the ER stress sensor IRE1α activity in the breast cancer cell lines to characterize the biological roles and molecular basis of the ERLIN2 in carcinogenesis. Finally, immunohistochemical staining was performed to detect ERLIN2 expression in normal and cancerous human breast tissues Results We found that amplification of the ERLIN2 gene and over expression of the ERLIN2 protein occurs in both luminal and Her2 subtypes of breast cancer. Gain- and loss-of-function approaches demonstrated that ERLIN2 is a novel oncogenic factor associated with the ER stress response pathway. The IRE1α/XBP1 axis in the ER stress pathway modulated expression of ERLIN2 protein levels in breast cancer cells. We also showed that over expression of ERLIN2 facilitated the adaptation of breast epithelial cells to ER stress by supporting cell growth and protecting the cells from ER stress-induced cell death. Conclusions ERLIN2 may confer a selective growth advantage for breast cancer cells by facilitating a cytoprotective response to various cellular stresses associated with oncogenesis. The information provided here sheds new light on the mechanism of breast cancer malignancy

Abstract The unfolded protein response (UPR) is a cascade of intracellular stress signaling events in response to an accumulation of unfolded or misfolded proteins in the lumen of the endoplasmic reticulum (ER). Cancer cells are often exposed to hypoxia, nutrient starvation, oxidative stress and other metabolic dysregulation that cause ER stress and activation of the UPR. Depending on the duration and degree of ER stress, the UPR can provide either survival signals by activating adaptive and antiapoptotic pathways, or death signals by inducing cell death programs. Sustained induction or repression of UPR pharmacologically may thus have beneficial and therapeutic effects against cancer. In this review, we discuss the basic mechanisms of UPR and highlight the importance of UPR in cancer biology. We also update the UPR-targeted cancer therapeutics currently in clinical trials.

Lilium is one of the most widely cultivated ornamental bulbous plants in the world. Although research has shown that variable temperature treatments can accelerate the development process from vegetative to reproductive growth in Lilium, the molecular regulation mechanisms of this development are not clear. In this study, Lbr-miR171b and its target gene, LbrSCL6, were selected and validated using transgenic functional verification, subcellular localization, and transcriptional activation. This study also investigated the differential expression of Lbr-miR171b and LbrSCL6 in two temperature treatment groups (25 °C and 15 °C). Lbr-miR171b expression significantly increased after the temperature change, whereas that of LbrSCL6 exhibited the opposite trend. Through in situ hybridization experiments facilitated by the design of hybridization probes targeting LbrSCL6, a reduction in LbrSCL6 expression was detected following variable temperature treatment at 15 °C. The transgenic overexpression of Lbr-miR171b in plants promoted the phase transition, while LbrSCL6 overexpression induced a delay in the phase transition. In addition, LbrWOX4 interacted with LbrSCL6 in yeast two-hybrid and bimolecular fluorescence complementation assays. In conclusion, these results explain the molecular regulatory mechanisms governing the phase transition in Lilium. [ABSTRACT FROM AUTHOR]