The giant freshwater prawn Macrobrachium rosenbergii alters background colour preference after metamorphosis from larvae to post larvae: In association with nature of photo taxis

The giant freshwater prawn Macrobrachium rosenbergii larvae have apposition eyes and are positively phototactic, whereas the postlarvae (PL) have superposition eyes and are negatively phototactic. M. rosenbergii has colour vision as early as larval stage. We discovered that M. rosenbergii alters background colour preference after metamorphosis from larvae to PL in association with nature of phototaxis. The test circular glass aquaria covered with a pair of two‐colour papers contained with a group of 100 larvae or 20 Pl, and the number of individuals in each colour background was recorded five times for each colour pair. The background colours tested were light blue, green, yellow, red, white and black. The numbers of larvae or PL in each colour background of different pairs were analysed by the Thurstone's law of comparative judgment. In the larvae, significant bias towards yellow was evident. In the PL, of the four pairings of black with other colours, all biased to black. The mean z‐scores were highest for yellow in the larvae, and for black in the PL. To determine the possible background brightness preference of the larvae and PL, six different colour backgrounds were presented in pairs. The larvae significantly preferred light blue over dark blue, white over yellow and white over black. The PL exhibited reversed preference. The relationship between z‐scores and light reflectance levels of five colour papers was significantly positive in the larvae and negative in the PL. The observed background colour preference was probably due to relative brightness rather than chromaticity difference

Impurity effect on weak anti-localization in the topological insulator Bi2Te3

We study weak anti-localization (WAL) effect in topological insulator Bi2Te3 thin films at low temperatures. Two-dimensional WAL effect associated with surface carriers is revealed in the tilted magnetic field dependence of magneto-conductance. Our data demonstrates that the observed WAL is robust against deposition of non-magnetic Au impurities on the surface of the thin films. But it is quenched by deposition of magnetic Fe impurities which destroy the pi Berry's phase of the topological surface states. The magneto-conductance data of a 5 nm Bi2Te3 film suggests that a crossover from symplectic to unitary classes is observed with the deposition of Fe impurities.Comment: 4 pages, 3 figures. Corresponding author email address: [email protected]

The CDEX-1 1 kg Point-Contact Germanium Detector for Low Mass Dark Matter Searches

The CDEX Collaboration has been established for direct detection of light dark matter particles, using ultra-low energy threshold p-type point-contact germanium detectors, in China JinPing underground Laboratory (CJPL). The first 1 kg point-contact germanium detector with a sub-keV energy threshold has been tested in a passive shielding system located in CJPL. The outputs from both the point-contact p+ electrode and the outside n+ electrode make it possible to scan the lower energy range of less than 1 keV and at the same time to detect the higher energy range up to 3 MeV. The outputs from both p+ and n+ electrode may also provide a more powerful method for signal discrimination for dark matter experiment. Some key parameters, including energy resolution, dead time, decay times of internal X-rays, and system stability, have been tested and measured. The results show that the 1 kg point-contact germanium detector, together with its shielding system and electronics, can run smoothly with good performances. This detector system will be deployed for dark matter search experiments.Comment: 6 pages, 8 figure

Will the US Economy Recover in 2010? A Minimal Spanning Tree Study

We calculated the cross correlations between the half-hourly times series of the ten Dow Jones US economic sectors over the period February 2000 to August 2008, the two-year intervals 2002--2003, 2004--2005, 2008--2009, and also over 11 segments within the present financial crisis, to construct minimal spanning trees (MSTs) of the US economy at the sector level. In all MSTs, a core-fringe structure is found, with consumer goods, consumer services, and the industrials consistently making up the core, and basic materials, oil and gas, healthcare, telecommunications, and utilities residing predominantly on the fringe. More importantly, we find that the MSTs can be classified into two distinct, statistically robust, topologies: (i) star-like, with the industrials at the center, associated with low-volatility economic growth; and (ii) chain-like, associated with high-volatility economic crisis. Finally, we present statistical evidence, based on the emergence of a star-like MST in Sep 2009, and the MST staying robustly star-like throughout the Greek Debt Crisis, that the US economy is on track to a recovery.Comment: elsarticle class, includes amsmath.sty, graphicx.sty and url.sty. 68 pages, 16 figures, 8 tables. Abridged version of the manuscript presented at the Econophysics Colloquim 2010, incorporating reviewer comment

Rapidly developed, optimized, and applied wastewater surveillance system for real-time monitoring of low-incidence, high-impact MPOX outbreak

Recent MPOX viral resurgences have mobilized public health agencies around the world. Recognizing the significant risk of MPOX outbreaks, large-scale human testing, and immunization campaigns have been initiated by local, national, and global public health authorities. Recently, traditional clinical surveillance campaigns for MPOX have been complemented with wastewater surveillance (WWS), building on the effectiveness of existing wastewater programs that were built to monitor SARS-CoV-2 and recently expanded to include influenza and respiratory syncytial virus surveillance in wastewaters. In the present study, we demonstrate and further support the finding that MPOX viral fragments agglomerate in the wastewater solids fraction. Furthermore, this study demonstrates that the current, most commonly used MPOX assays are equally effective at detecting low titers of MPOX viral signal in wastewaters. Finally, MPOX WWS is shown to be more effective at passively tracking outbreaks and/or resurgences of the disease than clinical testing alone in smaller communities with low human clinical case counts of MPOX

Definition of a new blood cell count score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of four multicenter clinical trials

Importance Blood cell count test (BCT) is a robust method that provides direct quantification of various types of immune cells to reveal the immune landscape to predict atezolizumab treatment outcomes for clinicians to decide the next phase of treatment. Objective This study aims to define a new BCTscore model to predict atezolizumab treatment benefits in non-small lung cell cancer (NSCLC) patients. Design, Setting, and Participants This study analyzed four international, multicenter clinical trials (OAK, BIRCH, POPLAR, and FIR trials) to conduct post-hoc analyses of NSCLC patients undergoing atezolizumab (anti–PD-L1) single-agent treatment (n = 1,479) or docetaxel single-agent treatment (n = 707). BCT was conducted at three time points: pre-treatment (T1), the first day of treatment cycle 3 (T2), and first day of treatment cycle 5 (T3). Univariate and multivariate Cox regression analyses were conducted to identify early BCT biomarkers to predict atezolizumab treatment outcomes in NSCLC patients. Main Outcomes and Measures Overall survival (OS) was used as the primary end point, whereas progression-free survival (PFS) according to Response Evaluation Criteria in Solid Tumors (RECIST), clinical benefit (CB), and objective response rate (ORR) were used as secondary end points. Results The BCT biomarkers of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at time point T3 and neutrophil-to-monocyte ratio (NMR) at time point T2 with absolute cutoff values of NLR_T3 = 5, PLR_T3 = 180, and NMR_T2 = 6 were identified as strong predictive biomarkers for atezolizumab (Ate)–treated NSCLC patients in comparison with docetaxel (Dtx)–treated patients regarding OS (BCTscore low risk: HR Ate vs. Dtx = 1.54 (95% CI: 1.04–2.27), P = 0.031; high risk: HR Ate vs. Dtx = 0.84 (95% CI: 0.62–1.12), P = 0.235). The identified BCTscore model showed better OS AUC in the OAK (AUC12month = 0.696), BIRCH (AUC12month = 0.672) and POPLAR+FIR studies (AUC12month = 0.727) than that of each of the three single BCT biomarkers. Conclusion and Relevance The BCTscore model is a valid predictive and prognostic biomarker for early survival prediction in atezolizumab-treated NSCLC patients

Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods

Background Development of severe immune-related adverse events (irAEs) is a major predicament to stop treatment with immune checkpoint inhibitors, even though tumor progression is suppressed. However, no effective early phase biomarker has been established to predict irAE until now. Method This study retrospectively used the data of four international, multi-center clinical trials to investigate the application of blood test biomarkers to predict irAEs in atezolizumab-treated advanced non-small cell lung cancer (NSCLC) patients. Seven machine learning methods were exploited to dissect the importance score of 21 blood test biomarkers after 1,000 simulations by the training cohort consisting of 80%, 70%, and 60% of the combined cohort with 1,320 eligible patients. Results XGBoost and LASSO exhibited the best performance in this study with relatively higher consistency between the training and test cohorts. The best area under the curve (AUC) was obtained by a 10-biomarker panel using the XGBoost method for the 8:2 training:test cohort ratio (training cohort AUC = 0.692, test cohort AUC = 0.681). This panel could be further narrowed down to a three-biomarker panel consisting of C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and thyroid-stimulating hormone (TSH) with a small median AUC difference using the XGBoost method [for the 8:2 training:test cohort ratio, training cohort AUC difference = −0.035 (p < 0.0001), and test cohort AUC difference = 0.001 (p=0.965)]. Conclusion Blood test biomarkers currently do not have sufficient predictive power to predict irAE development in atezolizumab-treated advanced NSCLC patients. Nevertheless, biomarkers related to adaptive immunity and liver or thyroid dysfunction warrant further investigation

Genetic susceptibility to hepatocellular carcinoma in chromosome 22q13.31, findings of a genome-wide association study.

Background and Aim: Chronic hepatitis C virus (HCV) infection, long-term alcohol use, cigarette smoking, and obesity are the major risk factors for hepatocellular carcinoma (HCC) in the United States, but the disease risk varies substantially among individuals with these factors, suggesting host susceptibility to and gene-environment interactions in HCC. To address genetic susceptibility to HCC, we conducted a genome-wide association study (GWAS). Methods: Two case-control studies on HCC were conducted in the United States. DNA samples were genotyped using the Illumian microarray chip with over 710 000 single nucleotide polymorphisms (SNPs). We compared these SNPs between 705 HCC cases and 1455 population controls for their associations with HCC and verified our findings in additional studies. Results: In this GWAS, we found that two SNPs were associated with HCC at Conclusions: SNPs i

Analytical protocol to identify local ancestry-associated molecular features in cancer

People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the "local" ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et&nbsp;al. (2020)