ROMO: Retrieval-enhanced Offline Model-based Optimization

Data-driven black-box model-based optimization (MBO) problems arise in a great number of practical application scenarios, where the goal is to find a design over the whole space maximizing a black-box target function based on a static offline dataset. In this work, we consider a more general but challenging MBO setting, named constrained MBO (CoMBO), where only part of the design space can be optimized while the rest is constrained by the environment. A new challenge arising from CoMBO is that most observed designs that satisfy the constraints are mediocre in evaluation. Therefore, we focus on optimizing these mediocre designs in the offline dataset while maintaining the given constraints rather than further boosting the best observed design in the traditional MBO setting. We propose retrieval-enhanced offline model-based optimization (ROMO), a new derivable forward approach that retrieves the offline dataset and aggregates relevant samples to provide a trusted prediction, and use it for gradient-based optimization. ROMO is simple to implement and outperforms state-of-the-art approaches in the CoMBO setting. Empirically, we conduct experiments on a synthetic Hartmann (3D) function dataset, an industrial CIO dataset, and a suite of modified tasks in the Design-Bench benchmark. Results show that ROMO performs well in a wide range of constrained optimization tasks.Comment: 15 pages, 9 figure

Bibliometric analysis of global research trends between gut microbiota and breast cancer: from 2013 to 2023

BackgroundBreast cancer is the most prevalent cancer globally and is associated with significant mortality. Recent research has provided crucial insights into the role of gut microbiota in the onset and progression of breast cancer, confirming its impact on the disease’s management. Despite numerous studies exploring this relationship, there is a lack of comprehensive bibliometric analyses to outline the field’s current state and emerging trends. This study aims to fill that gap by analyzing key research directions and identifying emerging hotspots.MethodPublications from 2013 to 2023 were retrieved from the Web of Science Core Collection database. The VOSviewer, R language and SCImago Graphica software were utilized to analyze and visualize the volume of publications, countries/regions, institutions, authors, and keywords in this field.ResultsA total of 515 publications were included in this study. The journal Cancers was identified as the most prolific, contributing 21 papers. The United States and China were the leading contributors to this field. The University of Alabama at Birmingham was the most productive institution. Peter Bai published the most papers, while James J. Goedert was the most cited author. Analysis of highly cited literature and keyword clustering confirmed a close relationship between gut microbiota and breast cancer. Keywords such as “metabolomics” and “probiotics” have been prominently highlighted in the keyword analysis, indicating future research hotspots in exploring the interaction between metabolites in the breast cancer microenvironment and gut microbiota. Additionally, these keywords suggest significant interest in the therapeutic potential of probiotics for breast cancer treatment.ConclusionResearch on the relationship between gut microbiota and breast cancer is expanding. Attention should be focused on understanding the mechanisms of their interaction, particularly the metabolite-microbiota-breast cancer crosstalk. These insights have the potential to advance prevention, diagnosis, and treatment strategies for breast cancer. This bibliometric study provides a comprehensive assessment of the current state and future trends of research in this field, offering valuable perspectives for future studies on gut microbiota and breast cancer

Updating the therapeutic role of ginsenosides in breast cancer: a bibliometrics study to an in-depth review

Breast cancer is currently the most common malignancy and has a high mortality rate. Ginsenosides, the primary bioactive constituents of ginseng, have been shown to be highly effective against breast cancer both in vitro and in vivo. This study aims to comprehensively understand the mechanisms underlying the antineoplastic effects of ginsenosides on breast cancer. Through meticulous bibliometric analysis and an exhaustive review of pertinent research, we explore and summarize the mechanism of action of ginsenosides in treating breast cancer, including inducing apoptosis, autophagy, inhibiting epithelial-mesenchymal transition and metastasis, and regulating miRNA and lncRNA. This scholarly endeavor not only provides novel prospects for the application of ginsenosides in the treatment of breast cancer but also suggests future research directions for researchers

Recombinant proteins A29L, M1R, A35R, and B6R vaccination protects mice from mpox virus challenge

Since May 2022, mutant strains of mpox (formerly monkeypox) virus (MPXV) have been rapidly spreading among individuals who have not traveled to endemic areas in multiple locations, including Europe and the United States. Both intracellular and extracellular forms of mpox virus have multiple outer membrane proteins that can stimulate immune response. Here, we investigated the immunogenicity of MPXV structural proteins such as A29L, M1R, A35R, and B6R as a combination vaccine, and the protective effect against the 2022 mpox mutant strain was also evaluated in BALB/c mice. After mixed 15 μg QS-21 adjuvant, all four virus structural proteins were administered subcutaneously to mice. Antibody titers in mouse sera rose sharply after the initial boost, along with an increased capacity of immune cells to produce IFN-γ alongside an elevated level of cellular immunity mediated by Th1 cells. The vaccine-induced neutralizing antibodies significantly inhibited the replication of MPXV in mice and reduced the pathological damage of organs. This study demonstrates the feasibility of a multiple recombinant vaccine for MPXV variant strains

The Use of SVM for Chinese New Word Identification

We present a study of new word identification (NWI) to improve the performance of a Chinese word segmenter. In this paper the distribution and types of new words are discussed empirically. In particular, we focus on the new words of two surface patterns, which account for more than 80 % of new words in our data sets: NW11 (two-character new word) and NW21 (a bi-character word followed with a single character). NWI is defined as a problem of binary classification. A statistical learning approach based on a SVM classifier is used. Different features for NWI are explored, including in-word probability of a character (IWP), the analogy between new words and lexicon words, anti-word list, and frequency in documents. The experiments show that these features are useful for NWI. The Fscores of NWI we achieved are 64.4% and 54.7 % for NW11 and NW21, respectively. The overall performance of the Chinese word segmenter could be improved by Roov 24.5 % and F-score 6.5% in PK-close test of the 1st SIGHAN bakeoff. This achieves the performance of state-of-the-art word segmenters.

DataSheet1_Updating the therapeutic role of ginsenosides in breast cancer: a bibliometrics study to an in-depth review.DOCX

Breast cancer is currently the most common malignancy and has a high mortality rate. Ginsenosides, the primary bioactive constituents of ginseng, have been shown to be highly effective against breast cancer both in vitro and in vivo. This study aims to comprehensively understand the mechanisms underlying the antineoplastic effects of ginsenosides on breast cancer. Through meticulous bibliometric analysis and an exhaustive review of pertinent research, we explore and summarize the mechanism of action of ginsenosides in treating breast cancer, including inducing apoptosis, autophagy, inhibiting epithelial-mesenchymal transition and metastasis, and regulating miRNA and lncRNA. This scholarly endeavor not only provides novel prospects for the application of ginsenosides in the treatment of breast cancer but also suggests future research directions for researchers.</p

Table2_Updating the therapeutic role of ginsenosides in breast cancer: a bibliometrics study to an in-depth review.DOCX

Breast cancer is currently the most common malignancy and has a high mortality rate. Ginsenosides, the primary bioactive constituents of ginseng, have been shown to be highly effective against breast cancer both in vitro and in vivo. This study aims to comprehensively understand the mechanisms underlying the antineoplastic effects of ginsenosides on breast cancer. Through meticulous bibliometric analysis and an exhaustive review of pertinent research, we explore and summarize the mechanism of action of ginsenosides in treating breast cancer, including inducing apoptosis, autophagy, inhibiting epithelial-mesenchymal transition and metastasis, and regulating miRNA and lncRNA. This scholarly endeavor not only provides novel prospects for the application of ginsenosides in the treatment of breast cancer but also suggests future research directions for researchers.</p

Table1_Updating the therapeutic role of ginsenosides in breast cancer: a bibliometrics study to an in-depth review.DOCX

Breast cancer is currently the most common malignancy and has a high mortality rate. Ginsenosides, the primary bioactive constituents of ginseng, have been shown to be highly effective against breast cancer both in vitro and in vivo. This study aims to comprehensively understand the mechanisms underlying the antineoplastic effects of ginsenosides on breast cancer. Through meticulous bibliometric analysis and an exhaustive review of pertinent research, we explore and summarize the mechanism of action of ginsenosides in treating breast cancer, including inducing apoptosis, autophagy, inhibiting epithelial-mesenchymal transition and metastasis, and regulating miRNA and lncRNA. This scholarly endeavor not only provides novel prospects for the application of ginsenosides in the treatment of breast cancer but also suggests future research directions for researchers.</p

Ultra-low-gold loading Au/CeO2 catalysts for ambient temperature CO oxidation: Effect of preparation conditions on surface composition and activity

A series of 0.06-0.09 wt% Au/CeO2 catalysts for CO oxidation at ambient temperature were prepared under different preparation conditions and characterized by BET, XRD, XPS, HRTEM and FT-IR techniques. Experiment results showed that with acid material as support, the catalyst prepared by raising the pH of the acid support suspension before introduction of the HAuCl4 solution exhibits the highest activity because of the higher Au-o/Au delta+ ratio existing on the surface. The optimum calcination temperature of the support CeO2 and the drying temperature of the catalyst, which affect strongly the amount of water-derived species and the activity, were found to be 873 and 333 K, respectively. Base pretreatment for acid CeO2 support leads to the decrease in Au delta+ and favors the preparation of an excellent catalyst with the specific rate raised from 2.92 to 10.06 mol g(Au)(-1) h(-1). Possible active center model and its formation process were proposed. (C) 2010 Elsevier Inc. All rights reserved.China Tobacco Fujian Industrial Corporatio