The internet-of-things (also known as IoT) connects a large number of information-sensing devices to the Internet to collect all kinds of information needed in real time. The reliability of the source of a large number of accessed information tests the processing speed of signatures. Batch signature allows a signer to sign a group of messages at one time, and signatures' verification can be completed individually and independently. Therefore, batch signature is suitable for data integration authentication in IoT. An outstanding advantage of batch signature is that a signer is able to sign as many messages as possible at one time without worrying about the size of signed messages. To reduce complexity yielded by multiple message signing, a binary tree is usually leveraged in the construction of batch signature. However, this structure requires a batch residue, making the size of a batch signature (for a group of messages) even longer than the sum of single signatures. In this paper, we make use of the intersection method from lattice to propose a novel generic method for batch signature. We further combine our method with hash-and-sign paradigm and Fiat⁻Shamir transformation to propose new batch signature schemes. In our constructions, a batch signature does not need a batch residue, so that the size of the signature is relatively smaller. Our schemes are securely proved to be existential unforgeability against adaptive chosen message attacks under the small integer solution problem, which shows great potential resisting quantum computer attacks.
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http://dx.doi.org/10.3390/s18114056 | DOI Listing |
mSystems
January 2025
State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, Jiangxi, China.
Unlabelled: Oral squamous cell carcinoma (OSCC) is a prevalent malignancy in the oral-maxillofacial region with a poor prognosis. Oral microbiomes play a potential role in the pathogenesis of this disease. However, findings from individual studies have been inconsistent, and a comprehensive understanding of OSCC-associated microbiome dysbiosis remains elusive.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Background: The tumor microenvironment (TME) is integral to tumor progression. However, its prognostic implications and underlying mechanisms in clear cell renal cell carcinoma (ccRCC) are not yet fully elucidated. This study aims to examine the prognostic significance of genes associated with immune-stromal scores and to explore their underlying mechanisms in ccRCC.
View Article and Find Full Text PDFToxicology
January 2025
Deparment of clinical pharmacy, Jieyang People's Hospital, 522000, China. Electronic address:
Drug-induced autoimmunity (DIA) is a non-IgE immune-related adverse drug reaction that poses substantial challenges in predictive toxicology due to its idiosyncratic nature, complex pathogenesis, and diverse clinical manifestations. To address these challenges, we developed InterDIA, an interpretable machine learning framework for predicting DIA toxicity based on molecular physicochemical properties. Multi-strategy feature selection and advanced ensemble resampling approaches were integrated to enhance prediction accuracy and overcome data imbalance.
View Article and Find Full Text PDFThis 30-color panel was developed to enable the enumeration and purification of distinct circulating immune cell subsets implicated in the pathogenesis of systemic autoimmune diseases including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc; scleroderma), Sjögren's disease (SjD), idiopathic inflammatory myopathy (IIM), and others. While designed for application to peripheral blood mononuclear cells, the inclusion of CD45 coupled with the ability to extract cellular autofluorescence spectral signatures enables the application of this panel to other tissue types. Of the 30 total markers, this panel employs 18 markers to profile T cell subsets consisting of different memory subsets and T helper polarities, > 10 markers to profile B cell subsets including double-negative B cells, and a total of 8 lineage markers to identify immune lineages including monocyte and natural killer cell subsets, conventional dendritic cells, plasmacytoid dendritic cells, and basophils.
View Article and Find Full Text PDFJ Nanobiotechnology
January 2025
Laboratorio de Medicina Nano-Regenerativa, Centro de Investigación e Innovación Biomédica (CiiB), Universidad de los Andes, Santiago, Chile.
Osteoarthritis (OA) is a joint disease characterized by articular cartilage degradation. Persistent low-grade inflammation defines OA pathogenesis, with crucial involvement of pro-inflammatory M1-like macrophages. While mesenchymal stromal cells (MSC) and their small extracellular vesicles (sEV) hold promise for OA treatment, achieving consistent clinical-grade sEV products remains a significant challenge.
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