Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning

Recently, various parameter-efficient fine-tuning (PEFT) strategies for application to language models have been proposed and successfully implemented. However, this raises the question of whether PEFT, which only updates a limited set of model parameters, constitutes security vulnerabilities when confronted with weight-poisoning backdoor attacks. In this study, we show that PEFT is more susceptible to weight-poisoning backdoor attacks compared to the full-parameter fine-tuning method, with pre-defined triggers remaining exploitable and pre-defined targets maintaining high confidence, even after fine-tuning. Motivated by this insight, we developed a Poisoned Sample Identification Module (PSIM) leveraging PEFT, which identifies poisoned samples through confidence, providing robust defense against weight-poisoning backdoor attacks. Specifically, we leverage PEFT to train the PSIM with randomly reset sample labels. During the inference process, extreme confidence serves as an indicator for poisoned samples, while others are clean. We conduct experiments on text classification tasks, five fine-tuning strategies, and three weight-poisoning backdoor attack methods. Experiments show near 100% success rates for weight-poisoning backdoor attacks when utilizing PEFT. Furthermore, our defensive approach exhibits overall competitive performance in mitigating weight-poisoning backdoor attacks.Comment: NAACL Findings 202

Privacy-preserving design of graph neural networks with applications to vertical federated learning

The paradigm of vertical federated learning (VFL), where institutions collaboratively train machine learning models via combining each other's local feature or label information, has achieved great success in applications to financial risk management (FRM). The surging developments of graph representation learning (GRL) have opened up new opportunities for FRM applications under FL via efficiently utilizing the graph-structured data generated from underlying transaction networks. Meanwhile, transaction information is often considered highly sensitive. To prevent data leakage during training, it is critical to develop FL protocols with formal privacy guarantees. In this paper, we present an end-to-end GRL framework in the VFL setting called VESPER, which is built upon a general privatization scheme termed perturbed message passing (PMP) that allows the privatization of many popular graph neural architectures.Based on PMP, we discuss the strengths and weaknesses of specific design choices of concrete graph neural architectures and provide solutions and improvements for both dense and sparse graphs. Extensive empirical evaluations over both public datasets and an industry dataset demonstrate that VESPER is capable of training high-performance GNN models over both sparse and dense graphs under reasonable privacy budgets

May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension

Aims Raised blood pressure (BP) is the biggest contributor to mortality and disease burden worldwide and fewer than half of those with hypertension are aware of it. May Measurement Month (MMM) is a global campaign set up in 2017, to raise awareness of high BP and as a pragmatic solution to a lack of formal screening worldwide. The 2018 campaign was expanded, aiming to include more participants and countries. Methods and results Eighty-nine countries participated in MMM 2018. Volunteers (≥18 years) were recruited through opportunistic sampling at a variety of screening sites. Each participant had three BP measurements and completed a questionnaire on demographic, lifestyle, and environmental factors. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or taking antihypertensive medication. In total, 74.9% of screenees provided three BP readings. Multiple imputation using chained equations was used to impute missing readings. 1 504 963 individuals (mean age 45.3 years; 52.4% female) were screened. After multiple imputation, 502 079 (33.4%) individuals had hypertension, of whom 59.5% were aware of their diagnosis and 55.3% were taking antihypertensive medication. Of those on medication, 60.0% were controlled and of all hypertensives, 33.2% were controlled. We detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) hypertension. Conclusion May Measurement Month expanded significantly compared with 2017, including more participants in more countries. The campaign identified over 335 000 adults with untreated or inadequately treated hypertension. In the absence of systematic screening programmes, MMM was effective at raising awareness at least among these individuals at risk

ACNPD: The Database for Elucidating the Relationships Between Natural Products, Compounds, Molecular Mechanisms, and Cancer Types

Objectives: Cancer is well-known as a collection of diseases of uncontrolled proliferation of cells caused by mutated genes which are generated by external or internal factors. As the mechanisms of cancer have been constantly revealed, including cell cycle, proliferation, apoptosis and so on, a series of new emerging anti-cancer drugs acting on each stage have also been developed. It is worth noting that natural products are one of the important sources for the development of anti-cancer drugs. To the best of our knowledge, there is not any database summarizing the relationships between natural products, compounds, molecular mechanisms, and cancer types.Materials and methods: Based upon published literatures and other sources, we have constructed an anti-cancer natural product database (ACNPD) (http://www.acnpd-fu.com/). The database currently contains 521 compounds, which specifically refer to natural compounds derived from traditional Chinese medicine plants (derivatives are not considered herein). And, it includes 1,593 molecular mechanisms/signaling pathways, covering 10 common cancer types, such as breast cancer, lung cancer and cervical cancer.Results: Integrating existing data sources, we have obtained a large amount of information on natural anti-cancer products, including herbal sources, regulatory targets and signaling pathways. ACNPD is a valuable online resource that illustrates the complex pharmacological relationship between natural products and human cancers.Conclusion: In summary, ACNPD is crucial for better understanding of the relationships between traditional Chinese medicine (TCM) and cancer, which is not only conducive to expand the influence of TCM, but help to find more new anti-cancer drugs in the future.</jats:p

Complete plastid genome of Rhododendron griersonianum, a critically endangered plant with extremely small populations (PSESP) from southwest China

The complete plastid genome of Rhododendron griersonianum, a critically endangered plant species with extremely small populations, was obtained using Illumina HiSeq X Ten and ONT PromethION sequencing. The full length of the plastid genome is 206,467 bp with an overall GC content of 35.8%, which encodes 118 unique genes, including 78 protein-coding genes, 36 tRNA and 4 rRNA genes. Phylogenetic analysis revealed that all Rhododendron species formed a monophyletic clade. This study provides a valuable reference and will facilitate future studies related to the general characteristics and evolution of plastid genomes in the genus Rhododendron

Screening of Genes Related to Growth, Development and Meat Quality of Sahan Crossbred F1 Sheep Based on RNA-Seq Technology

This study aimed to identify genes related to sheep growth, development and meat quality. Small-tailed Han sheep (STH), and small-tailed Han sheep and Suffolk crossbred F1 (STH×SFK), were selected to determine the growth performance, slaughter performance, and meat quality. The longissimus dorsi muscle was selected for transcriptome sequencing, and the target gene was screened based on bioinformatics analysis; real-time fluorescent quantitative PCR (RT-PCR) and western blotting (WB) were conducted to verify the target gene. Locations of genes in tissues were confirmed via immunofluorescence. The results showed that the pre-slaughter live weight, bust circumference, slaughter performance, and marbling score of the STH×SFK population were significantly higher than those of the STH population (P &amp;lt; 0.01). Sequencing results showed that 560 differentially expressed genes (DEGs) were identified in the STH×SFK population, of which 377 exhibited up-regulated and 183 exhibited down-regulated expression levels. GO annotation revealed that DEGs could be classified into 13 cell components, 10 molecular functions, and 22 biological processes. The KEGG enrichment analysis showed that DEGs were mainly enriched in the Rap1 signaling pathway, Ras signaling pathway, and other pathways related to growth and meat quality. Based on the GO and KEGG analyses, four candidate genes related to sheep growth and meat quality, namely myostain (MSTN), interferon-related developmental regulator 1 (IFRD1), peroxisome proliferator activator receptor delta (PPARD), and myosin light chain 2 (MLC2 or MYL2), were screened. The expression levels of genes and proteins were verified via RT-PCR and WB, and the results were consistent with the trend of transcriptome sequencing. Immunofluorescence results showed that IFRD1 was expressed in the cytoplasm and nucleus, and MYL2 was expressed in the cytoplasm. This study revealed the mechanism of gene regulation of sheep growth and development at the molecular level and provided a theoretical basis for studying sheep genetics and breeding.</jats:p

Designing strategies of small-molecule compounds for modulating non-coding RNAs in cancer therapy

AbstractNon-coding RNAs (ncRNAs) have been defined as a class of RNA molecules transcribed from the genome but not encoding proteins, such as microRNAs, long non-coding RNAs, Circular RNAs, and Piwi-interacting RNAs. Accumulating evidence has recently been revealing that ncRNAs become potential druggable targets for regulation of several small-molecule compounds, based on their complex spatial structures and biological functions in cancer therapy. Thus, in this review, we focus on summarizing some new emerging designing strategies, such as high-throughput screening approach, small-molecule microarray approach, structure-based designing approach, phenotypic screening approach, fragment-based designing approach, and pharmacological validation approach. Based on the above-mentioned approaches, a series of representative small-molecule compounds, including Bisphenol-A, Mitoxantrone and Enoxacin have been demonstrated to modulate or selectively target ncRNAs in different types of human cancers. Collectively, these inspiring findings would provide a clue on developing more novel avenues for pharmacological modulations of ncRNAs with small-molecule drugs for future cancer therapeutics.</jats:p

Table1_ACNPD: The Database for Elucidating the Relationships Between Natural Products, Compounds, Molecular Mechanisms, and Cancer Types.docx

Objectives: Cancer is well-known as a collection of diseases of uncontrolled proliferation of cells caused by mutated genes which are generated by external or internal factors. As the mechanisms of cancer have been constantly revealed, including cell cycle, proliferation, apoptosis and so on, a series of new emerging anti-cancer drugs acting on each stage have also been developed. It is worth noting that natural products are one of the important sources for the development of anti-cancer drugs. To the best of our knowledge, there is not any database summarizing the relationships between natural products, compounds, molecular mechanisms, and cancer types.Materials and methods: Based upon published literatures and other sources, we have constructed an anti-cancer natural product database (ACNPD) (http://www.acnpd-fu.com/). The database currently contains 521 compounds, which specifically refer to natural compounds derived from traditional Chinese medicine plants (derivatives are not considered herein). And, it includes 1,593 molecular mechanisms/signaling pathways, covering 10 common cancer types, such as breast cancer, lung cancer and cervical cancer.Results: Integrating existing data sources, we have obtained a large amount of information on natural anti-cancer products, including herbal sources, regulatory targets and signaling pathways. ACNPD is a valuable online resource that illustrates the complex pharmacological relationship between natural products and human cancers.Conclusion: In summary, ACNPD is crucial for better understanding of the relationships between traditional Chinese medicine (TCM) and cancer, which is not only conducive to expand the influence of TCM, but help to find more new anti-cancer drugs in the future.</p