CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models

We are currently in an era of fierce competition among various large language models (LLMs) continuously pushing the boundaries of benchmark performance. However, genuinely assessing the capabilities of these LLMs has become a challenging and critical issue due to potential data contamination, and it wastes dozens of time and effort for researchers and engineers to download and try those contaminated models. To save our precious time, we propose a novel and useful method, Clean-Eval, which mitigates the issue of data contamination and evaluates the LLMs in a cleaner manner. Clean-Eval employs an LLM to paraphrase and back-translate the contaminated data into a candidate set, generating expressions with the same meaning but in different surface forms. A semantic detector is then used to filter the generated low-quality samples to narrow down this candidate set. The best candidate is finally selected from this set based on the BLEURT score. According to human assessment, this best candidate is semantically similar to the original contamination data but expressed differently. All candidates can form a new benchmark to evaluate the model. Our experiments illustrate that Clean-Eval substantially restores the actual evaluation results on contaminated LLMs under both few-shot learning and fine-tuning scenarios

Utility of clinical metagenomics in diagnosing malignancies in a cohort of patients with Epstein-Barr virus positivity

BackgroundsDifferentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease.MethodsWe enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019.ResultsAmong the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately.ConclusionsThe application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach

LncRNAs GIHCG and SPINT1-AS1 Are Crucial Factors for Pan-Cancer Cells Sensitivity to Lapatinib

Lapatinib is a small molecule inhibitor of EGFR (HER1) and ERBB2 (HER2) receptors, which is used for treatment of advanced or metastatic breast cancer. To find the drug resistance mechanisms of treatment for EGFR/ERBB2 positive tumors, we analyzed the possible effects of lncRNAs. In this study, using CCLE (Cancer Cell Line Encyclopedia) database, we explored the relationship between the lncRNAs and Lapatinib sensitivity/resistance, and then validated those findings through in vitro experiments. We found that the expression of EGFR/ERBB2 and activation of ERBB pathway was significantly related to Lapatinib sensitivity. GO (Gene Oncology) analysis of top 10 pathways showed that the sensitivity of Lapatinib was positively correlated with cell keratin, epithelial differentiation, and cell-cell junction, while negatively correlated with signatures of extracellular matrix. Forty-four differentially expressed lncRNAs were found between the Lapatinib sensitive and resistant groups (fold-change > 1.5, P < 0.01). Gene set variation analysis (GSVA) was performed based on 44 lncRNAs and genes in the top 10 pathways. Five lncRNAs were identified as hub molecules. Co-expression network was constructed by more than five lncRNAs and 199 genes in the top 10 pathways, and three lncRNAs (GIHCG, SPINT1-AS1, and MAGI2-AS3) and 47 genes were identified as close-related molecules. The three lncRNAs in epithelium-derived cancers were differentially expressed between sensitive and resistant groups, but no significance was found in non-epithelium-derived cancer cells. Correlation analysis showed that SPINT1-AS1 (R = −0.715, P < 0.001) and GIHCG (R = 0.557, P = 0.013) were correlated with the IC50 of epithelium-derived cancer cells. In further experiments, GIHCG knockdown enhanced cancer cell susceptibility to Lapatinib, while high level of SPINT1-AS1 was a sensitive biomarker of NCI-N87 and MCF7 cancer cells to Lapatinib. In conclusions, lncRNAs GIHCG and SPINT1-AS1 were involved in regulating Lapatinib sensitivity. Up-regulation of GIHCG was a drug-resistant biomarker, while up-regulation of SPINT1-AS1 was a sensitive indicator

Improving the corrosion resistance of MgZn1.2GdxZr0.18 (x =0, 0.8, 1.4, 2.0) alloys via Gd additions

Funding Information: This research was financially supported by the National Key Research and Development Program of China (Grant No. 2016YFB0301101 ), the National Natural Science Foundation of China (Grant No. 51971054 ) and the Fundamental Research Funds for the Central Universities (Grant Nos. N180904006 and N2009006 ). Publisher Copyright: © 2020 Elsevier LtdEffects of Gd addition on microstructure, corrosion behavior and mechanism of cast and extruded MgZn1.2GdxZr0.18 alloys are investigated through microstructure observation, weight loss and electrochemical tests. Increasing Gd from 0 to 2.0 at.%, grains are refined, MgZn2 phase, W-phase and X-phase are formed successively, and basal texture intensity is decreased. The significantly decreased grain size by extrusion and Gd addition induces formation of protective Gd2O3 and MgO layer. The extruded MgZn1.2Gd2.0Zr0.18 alloy shows decreased corrosion rate of 3.72 ± 0.36 mm/year, owing to fine and homogeneous microstructure, dual-role (micro-anode and barrier) of X-phase, compact oxidation layer and basal crystallographic texture.Peer reviewe

A Coal Mine Underground Localization Algorithm Based on the Feature Vector

To enhance the position estimation accuracy of an underground localization system for coal mine roadways, an algorithm based on the feature vector of received signals is presented in this paper. The algorithm includes three steps: the construction process of a feature vector database and a distance database, the vector matching process and the localization process. When a signal vector is received, it only needs to calculate the distance from the received vector to the center vector of each subset and then compare it with the data in the distance database. After multiple filtering and comparing the source of the strongest signal, the coordinates closest to the received vector are found. The experiment showed that the maximum error of this algorithm was 4 m and the average error was 1.62 m. Furthermore, within a localization error of 1 m, the X-axis localization accuracy was 98% while the Y-axis localization accuracy was 86%. Also, the algorithm took much less time compared to the KNN and WKNN algorithms, so the algorithm meets the requirements of coal mine safety systems and underground personnel localization systems

Effects of Different Solvents on the Surface Acidic Oxygen-containing Functional Groups on Xanthoceras sorbifolia Shell

This study reports the preparation of a novel biomaterial from a forestry residue - Xanthoceras sorbifolia shell (XSS) - by solvent modification. The effects of acid and base (hydrochloric acerbic, acetic acid, sodium hydroxide, ammonia water) and some organic solvents (ethanol, acetone, ethyl acetate, chloroform, petroleum ether, and n-hexane) on the surface acidic functional groups (SAFGs) on XSS were investigated. The amount of SAFGs was quantified using acid and alkali chemical titration methods, and the characteristics of virgin XSS were compared with treated ones by FT-IR spectroscopy. It was found that acid solutions can increase the concentration of SAFGs, while alkaline solutions reduce it. The XSS treated in 0.5 M HCl has the largest number of total acidic functional groups and phenolic hydroxyl groups. The shell extracted with 2 M acetic acid has the highest concentration of carboxyl. The SAFG contents were remarkably increased by treatments with ethanol and acetone, due to the outstanding enhancement of phenolic hydroxyl. These changes in the SAFGs of XSS brought about by treatments with various solutions could be a theoretical foundation for modifying this residue to create a new type of highly efficient absorbent material

A Moderate Low-Carbohydrate Low-Calorie Diet Improves Lipid Profile, Insulin Sensitivity and Adiponectin Expression in Rats

Calorie restriction (CR) via manipulating dietary carbohydrates has attracted increasing interest in the prevention and treatment of metabolic syndrome. There is little consensus about the extent of carbohydrate restriction to elicit optimal results in controlling metabolic parameters. Our study will identify a better carbohydrate-restricted diet using rat models. Rats were fed with one of the following diets for 12 weeks: Control diet, 80% energy (34% carbohydrate-reduced) and 60% energy (68% carbohydrate-reduced) of the control diet. Changes in metabolic parameters and expressions of adiponectin and peroxisome proliferator activator receptor γ (PPARγ) were identified. Compared to the control diet, 68% carbohydrate-reduced diet led to a decrease in serum triglyceride and increases inlow density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C) and total cholesterol; a 34% carbohydrate-reduced diet resulted in a decrease in triglycerides and an increase in HDL-cholesterol, no changes however, were shown in LDL-cholesterol and total cholesterol; reductions in HOMA-IR were observed in both CR groups. Gene expressions of adiponectin and PPARγ in adipose tissues were found proportionally elevated with an increased degree of energy restriction. Our study for the first time ever identified that a moderate-carbohydrate restricted diet is not only effective in raising gene expressions of adiponectin and PPARγ which potentially lead to better metabolic conditions but is better at improving lipid profiles than a low-carbohydrate diet in rats

Imaging-based intelligent spectrometer on a plasmonic rainbow chip

The authors develop an imaging-based intelligent spectrometer on a plasmonic “rainbow” chip. It can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum using a single image assisted by suitably trained deep learning algorithms