Reciprocal polarization imaging of complex media

The vectorial evolution of polarized light interaction with a medium can reveal its microstructure and anisotropy beyond what can be obtained from scalar light interaction. Anisotropic properties (diattenuation, retardance, and depolarization) of a complex medium can be quantified by polarization imaging by measuring the Mueller matrix. However, polarization imaging in the reflection geometry, ubiquitous and often preferred in diverse applications, has suffered a poor recovery of the medium's anisotropic properties due to the lack of suitable decomposition of the Mueller matrices measured inside a backward geometry. Here, we present reciprocal polarization imaging of complex media after introducing reciprocal polar decomposition for backscattering Mueller matrices. Based on the reciprocity of the optical wave in its forward and backward scattering paths, the anisotropic diattenuation, retardance, and depolarization of a complex medium are determined by measuring the backscattering Mueller matrix. We demonstrate reciprocal polarization imaging in various applications for quantifying complex non-chiral and chiral media (birefringence resolution target, tissue sections, and glucose suspension), uncovering their anisotropic microstructures with remarkable clarity and accuracy. We also highlight types of complex media that Lu-Chipman and differential decompositions of backscattering Mueller matrices lead to erroneous medium polarization properties, whereas reciprocal polar decomposition recovers properly. Reciprocal polarization imaging will be instrumental in imaging complex media from remote sensing to biomedicine and will open new applications of polarization optics in reflection geometry

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Deubiquitinase USP19 modulates apoptotic calcium release and endoplasmic reticulum stress by deubiquitinating BAG6 in triple negative breast cancer

Abstract Background Triple‐negative breast cancer (TNBC), a heterogeneous subtype of breast cancer (BC), had poor prognosis. Endoplasmic reticulum (ER) stress was responsible for cellular processes and played a crucial role in the cell function. ER stress is a complex and dynamic process that can induce abnormal apoptosis and death. However, the underlying mechanism of ER stress involved in TNBC is not well defined. Methods We identified ubiquitin‐specific protease 19 (USP19) as a TNBC negative regulator for further investigation. The effects of USP19 on BC proliferation were assessed in vitro using proliferation test and cell‐cycle assays, while the effects in vivo were examined using a mouse tumorigenicity model. Through in vitro flow cytometric analyses and in vivo TUNEL assays, cell apoptosis was assessed. Proteomics was used to examine the proteins that interact with USP19. Results Multiple in vitro and in vivo tests showed that USP19 decreases TNBC cell growth while increasing apoptosis. Then, we demonstrated that USP19 interacts with deubiquitinates and subsequently stabilises family molecular chaperone regulator 6 (BAG6). BAG6 can boost B‐cell lymphoma 2 (BCL2) ubiquitination and degradation, thereby raising ER calcium (Ca2+) levels and causing ER stress. We also found that the N6‐methyladenosine (m6A) “writer” methyltransferase‐like 14 (METTL14) increased global m6A modification. Conclusions Our study reveals that USP19 elevates the intracellular Ca2+ concentration to alter ER stress via regulation of BAG6 and BCL2 stability and may be a viable therapeutic target for TNBC therapy

Targeted next-generation sequencing as a comprehensive test for patients with and female carriers of DMD/BMD:a multi-population diagnostic study

Duchenne and Becker muscular dystrophies (DMD/BMD) are the most commonly inherited neuromuscular disease. However, accurate and convenient molecular diagnosis cannot be achieved easily because of the enormous size of the dystrophin gene and complex causative mutation spectrum. Such traditional methods as multiplex ligation-dependent probe amplification plus Sanger sequencing require multiple steps to fulfill the diagnosis of DMD/BMD. Here, we introduce a new single-step method for the genetic analysis of DMD patients and female carriers in real clinical settings and demonstrate the validation of its accuracy. A total of 89 patients, 18 female carriers and 245 non-DMD patients were evaluated using our targeted NGS approaches. Compared with traditional methods, our new method yielded 99.99% specificity and 98.96% sensitivity for copy number variations detection and 100% accuracy for the identification of single-nucleotide variation mutations. Additionally, this method is able to detect partial deletions/duplications, thus offering precise personal DMD gene information for gene therapy. We detected novel partial deletions of exons in nine samples for which the breakpoints were located within exonic regions. The results proved that our new method is suitable for routine clinical practice, with shorter turnaround time, higher accuracy, and better insight into comprehensive genetic information (detailed breakpoints) for ensuing gene therapy

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences