Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and characterization of a novel molecular classification based on disulfidptosis-related genes to predict prognosis and immunotherapy efficacy in hepatocellular carcinoma

Background: Disulfidptosis has been discovered as a mechanism of cell death mediating by SLC7A11. Nonetheless, little is known about the relationship between disulfidptosis-related genes (DRG) and hepatocellular carcinoma (HCC). Methods: 7 datasets including 1,302 HCC patients and 62,530 cells were downloaded. We adopted consensus clustering algorithm to construct the consensus matrix and cluster the samples’ DRG related expression profile data. Then, weighted gene co-expression network analysis (WGCNA) was conducted to identify hub gene modules associated with the identified clusters and determine the correlation between modules. A DRG.score was constructed based on genes through differential analysis and WGCNA of the 2 clusters. Results: Univariate and multivariate Cox regression analysis show that SLC7A11 and LRPPRC can be used as an independent factor in HCC. Then, two molecular subgroups with significantly different survival were identified based on 10 DRG. The cluster.A showed a worse prognosis, higher immune infiltration, and higher immune checkpoint expression. Then, by differential analysis and WGCNA of the 2 clusters, we identified 5 hub genes, and constructed a DRG.score. Univariate and multivariate Cox regression analysis show that DRG.score can be used as an independent factor to predict the prognosis in HCC. Furthermore, high DRG.score group had a worse prognosis, and was validated in TCGA-LIHC, LIRI-JP, GSE14520, GSE36376, and GSE76427. Preclinically, patients with higher DRG.score demonstrated significant immunotherapy therapeutic advantages and transcatheter arterial chemoembolization clinical benefits. Conclusions: SLC7A11 and LRPPRC play an essential role in HCC prognosis prediction. The DRG.score might become useful biomarkers for novel therapeutic targets.
Geometric Deep Neural Network Using Rigid and Non-Rigid Transformations for Landmark-Based Human Behavior Analysis

Deep learning architectures, albeit successful in most computer vision tasks, were designed for data with an underlying Euclidean structure, which is not usually fulfilled since pre-processed data may lie on a non-linear space. In this article, we propose a geometric deep learning approach using rigid and non-rigid transformations, named KShapenet, for 2D and 3D landmark-based human motion analysis. Landmark configuration sequences are first modeled as trajectories on Kendall's shape space and then mapped to a linear tangent space. The resulting structured data are then input to a deep learning architecture, which includes a layer that optimizes over rigid and non-rigid transformations of landmark configurations, followed by a CNN-LSTM network. We apply KShapenet to 3D human landmark sequences for action and gait recognition, and 2D facial landmark sequences for expression recognition, and demonstrate the competitiveness of the proposed approach with respect to state-of-the-art.
Effect of l-Dopa in acute temozolomide-induced cognitive impairment in male mice: a possible antineuroinflammatory role

Temozolomide is used commonly in the treatment of some types of cancers, but it may also result in cognitive impairments such as memory deficits. l-Dopa, a well known medicine for the central nervous system, has been shown to have positive effects on some cognitive disorders. Here we sought to investigate the effect of l-Dopa on temozolomide-induced cognitive impairments. BALB/c mice were subjected to 3-days temozolomide and 6-days concomitant l-Dopa/benserazide administration in six groups (control, l-Dopa 25 mg/kg, l-Dopa 75 mg/kg, temozolomide, temozolomide + l-Dopa 25 mg/kg, and temozolomide + l-Dopa 75 mg/kg). Open field test, object location recognition, novel object recognition test, and shuttle-box test were carried out to determine the locomotor, anxiety-like behavior, and memory function of subjects. TNF-α and brain-derived neurotrophic factor (BDNF) gene expression in the hippocampus was measured by real-time PCR. Mice treated with temozolomide showed recognition memory impairment, along with hippocampal TNF-α and BDNF mRNA expression level raise, and detection of histological insults in hematoxylin and eosin hippocampal slides. Mice that received temozolomide + l-Dopa showed normal behavioral function and lower TNF-α and BDNF hippocampal mRNA expression levels, and histologically normal hippocampal CA1 region in comparison with mice in the temozolomide group. Our results provide evidence that l-Dopa prevents temozolomide-induced recognition memory deficit in mice at the acute phase probably via l-Dopa antineuroinflammatory effects.
Exploring switch II pocket conformation of KRAS(G12D) with mutant-selective monobody inhibitors

Significance KRAS(G12D) is a prevalent activating mutation associated with devastating cancers. Although recent breakthroughs have demonstrated that KRAS(G12D) is no longer undruggable, there are still few direct inhibitors selective to KRAS(G12D). We describe a series of synthetic binding proteins, monobodies, that were exquisitely selective to KRAS(G12D). When used as genetically encoded intracellular biologics, they inhibited signaling and tumorigenesis mediated by KRAS(G12D). Structural and systematic mutational analyses revealed a conformation of KRAS(G12D) distinct from those reported previously and key features for the high selectivity of the monobodies, which will guide the development of next-generation inhibitors against KRAS(G12D). The relative ease of generating these monobody inhibitors and gaining mechanistic insights suggests their utility as tool reagents for interrogating challenging therapeutic targets.
Transcription factors TgbHLH95 and TgbZIP44 cotarget terpene biosynthesis gene TgGPPS in Torreya grandis nuts

Abstract Terpenes are volatile compounds responsible for aroma and the postharvest quality of commercially important xiangfei (Torreya grandis) nuts, and there is interest in understanding the regulation of their biosynthesis. Here, a transcriptomics analysis of xiangfei nuts after harvest identified 156 genes associated with the terpenoid metabolic pathway. A geranyl diphosphate (GPP) synthase (TgGPPS) involved in production of the monoterpene precursor GPP was targeted for functional characterization, and its transcript levels positively correlated with terpene levels. Furthermore, transient overexpression of TgGPPS in tobacco (Nicotiana tabacum) leaves or tomato (Solanum lycopersicum) fruit led to monoterpene accumulation. Analysis of differentially expressed transcription factors identified one basic helix-loop-helix protein (TgbHLH95) and one basic leucine zipper protein (TgbZIP44) as potential TgGPPS regulators. TgbHLH95 showed significant transactivation of the TgGPPS promoter, and its transient overexpression in tobacco leaves led to monoterpene accumulation, whereas TgbZIP44 directly bound to an ACGT-containing element in the TgGPPS promoter, as determined by yeast 1-hybrid test and electrophoretic mobility shift assay. Bimolecular fluorescence complementation, firefly luciferase complementation imaging, co-immunoprecipitation, and GST pull-down assays confirmed a direct protein–protein interaction between TgbHLH95 and TgbZIP44 in vivo and in vitro, and in combination these proteins induced the TgGPPS promoter up to 4.7-fold in transactivation assays. These results indicate that a TgbHLH95/TgbZIP44 complex activates the TgGPPS promoter and upregulates terpene biosynthesis in xiangfei nuts after harvest, thereby contributing to its aroma.
Simultaneous Two Beam Acceleration Lattice Design Study for the Post Linear Accelerator of RISP

The Rare Isotope Science Project, RISP, is the research complex by using heavy ion accelerator, in which RISP research complex consists of front-end system, super conducting linear accelerator(SCL), ISOL system, In-flight system. The original purpose of post linear accelerator was for the alternative acceleration of stable driver beam from ECR ion source and unstable rare isotope beam from ISOL system. However, the post accelerator lattice was re-designed with new concept of acceleration method to get more benefits. The idea was the simultaneous acceleration of stable driver beam and RI beam by using the post accelerator lattice of average A/q value. In this proceeding, we will describe the results of beam dynamics study of simultaneous two beam acceleration at SCL3.
Direct synthesis of nanopatterned epitaxial graphene on silicon carbide

This article introduces a straightforward approach for the direct synthesis of transfer-free, nanopatterned epitaxial graphene on silicon carbide on silicon substrates. A catalytic alloy tailored to optimal SiC graphitization is pre-patterned with common lithography and lift-off techniques to form planar graphene structures on top of an unpatterned SiC layer. This method is compatible with both electron-beam lithography and UV-lithography, and graphene gratings down to at least ∼100 nm width/space can be realized at the wafer scale. The minimum pitch is limited by the flow of the metal catalyst during the liquid-phase graphitization process. We expect that the current pitch resolution could be further improved by optimizing the metal deposition method and lift-off process.
Biomolecular phase separation in stress granule assembly and virus infection

Liquid-liquid phase separation (LLPS) has emerged as a crucial mechanism for cellular compartmentalization. One prominent example of this is the stress granule. Found in various types of cells, stress granule is a biomolecular condensate formed through phase separation. It comprises numerous RNA and RNA-binding proteins. Over the past decades, substantial knowledge has been gained about the composition and dynamics of stress granules. SGs can regulate various signaling pathways and have been associated with numerous human diseases, such as neurodegenerative diseases, cancer, and infectious diseases. The threat of viral infections continues to loom over society. Both DNA and RNA viruses depend on host cells for replication. Intriguingly, many stages of the viral life cycle are closely tied to RNA metabolism in human cells. The field of biomolecular condensates has rapidly advanced in recent times. In this context, we aim to summarize research on stress granules and their link to viral infections. Notably, stress granules triggered by viral infections behave differently from the canonical stress granules triggered by sodium arsenite (SA) and heat shock. Studying stress granules in the context of viral infections could offer a valuable platform to link viral replication processes and host anti-viral responses. A deeper understanding of these biological processes could pave the way for innovative interventions and treatments for viral infectious diseases. They could potentially bridge the gap between basic biological processes and interactions between viruses and their hosts.
Autoimmune Atrial Fibrillation

BACKGROUND: Atrial fibrillation (AF) is by far the most common cardiac arrhythmia. In about 3% of individuals, AF develops as a primary disorder without any identifiable trigger (idiopathic or historically termed lone AF). In line with the emerging field of autoantibody-related cardiac arrhythmias, the objective of this study was to explore whether autoantibodies targeting cardiac ion channels can underlie unexplained AF. METHODS: Peptide microarray was used to screen patient samples for autoantibodies. We compared patients with unexplained AF (n=37 pre-existent AF; n=14 incident AF on follow-up) to age- and sex-matched controls (n=37). Electrophysiological properties of the identified autoantibody were then tested in vitro with the patch clamp technique and in vivo with an experimental mouse model of immunization. RESULTS: A common autoantibody response against Kir3.4 protein was detected in patients with AF and even before the development of clinically apparent AF. Kir3.4 protein forms a heterotetramer that underlies the cardiac acetylcholine-activated inwardly rectifying K+ current, IKACh. Functional studies on human induced pluripotent stem cell–derived atrial cardiomyocytes showed that anti-Kir3.4 IgG purified from patients with AF shortened action potentials and enhanced the constitutive form of IKACh, both key mediators of AF. To establish a causal relationship, we developed a mouse model of Kir3.4 autoimmunity. Electrophysiological study in Kir3.4-immunized mice showed that Kir3.4 autoantibodies significantly reduced atrial effective refractory period and predisposed animals to a 2.8-fold increased susceptibility to AF. CONCLUSIONS: To our knowledge, this is the first report of an autoimmune pathogenesis of AF with direct evidence of Kir3.4 autoantibody-mediated AF.
Acute Glycemic Variability and Early Outcomes After Cardiac Surgery: A Meta-Analysis

Abstract The influence of acute glycemic variability (GV) on early outcomes of patients after cardiac surgery remains not fully determined. We performed a systematic review and meta-analysis to evaluate the association between acute GV and in-hospital outcomes of patients after cardiac surgery. Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library, and Web of Science. A randomized-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Nine cohort studies involving 16 411 patients after cardiac surgery were included in this meta-analysis. Pooled results showed that a high acute GV was associated with an increased risk of major adverse events (MAE) during hospitalization for patients after cardiac surgery [odds ratio [OR]: 1.29, 95% CI: 1.15 to 1.45, p<0.001, I22=38%]. Sensitivity analysis limited to studies of on-pump surgery and GV evaluated by coefficient of variation of blood glucose showed similar results. Subgroup analysis suggested that a high acute GV was related to an increased incidence of MAE in patients after coronary artery bypass graft, but not for those after isolated valvular surgery (p=0.04), and the association was weakened after adjustment of glycosylated hemoglobin (p=0.01). Moreover, a high acute GV was also related to an increased risk of in-hospital mortality (OR: 1.55, 95% CI: 1.15 to 2.09, p=0.004; I22=0%). A high acute GV may be associated with poor in-hospital outcomes in patients after cardiac surgery.
Fracture in Irradiated Rat Femur: A Description of an Experimental Model and Evaluation of its Effectiveness

Resumo Objetivo Nosso objetivo é descrever um modelo experimental para estudo de fraturas de fêmur em ratos após exposição a radiação ionizante, demonstrando uma forma de aplicação de uma substância para análise, o método de padronização de fratura e irradiação e a forma de avaliação de sua eficácia com base em estudos radiográficos. Métodos Utilizamos 24 ratos divididos em dois grupos de 12 animais cada. O grupo ESTUDO foi exposto à radiação ionizante e tratado com soro fisiológico, enquanto o grupo CONTROLE não foi exposto à radiação e foi tratado com soro fisiológico. Todos os animais foram submetidos à fratura padronizada do fêmur direito e sua fixação com fio intramedular. A eficácia da consolidação óssea foi determinada por exame radiográfico. Resultados A cicatrização de fraturas foi mais eficiente em ossos não expostos à radiação ionizante ( p = 0,012). Todas as fraturas atenderam aos critérios de serem simples, diafisárias, transversas ou oblíquas curtas. Conclusão O modelo experimental apresentado é uma boa alternativa para o estudo de fraturas em ossos irradiados em ratos. Abstract Objective We aim to describe an experimental model for studying femoral fractures in rats after exposure to ionizing radiation, demonstrating a way to apply a substance for analysis, the method for patterning fracture and irradiation, and how to evaluate its effectiveness based on radiographic studies. Methods We used 24 rats divided into 2 groups of 12 animals each. The STUDY group was exposed to ionizing radiation and treated with saline solution, and the CONTROL group was not exposed to radiation and was treated with saline solution. All animals were subjected to standardized fracture of the right femur that was fixed with intramedullary wire. The efficiency of the bone union was assessed by radiographic exam. Results Fracture healing was more efficient in bones not exposed to ionizing radiation ( p = 0.012). All fractures met the criteria of being simple, diaphyseal, transverse or short oblique. Conclusion The experimental model presented is an efficient alternative for the study of fractures in irradiated bones in rats.
The effectiveness of universal design for learning: A systematic review of the literature and meta-analysis

Abstract Universal Design for Learning (UDL) framework supports students’ diversity principles in inclusive education settings. This systematic review and meta-analysis examined the effectiveness of UDL principles in educational settings. The inclusion criteria of the systematic search include empirical peer-reviewed research (pre-and post-design) published between 2015 to 2021 in English and Arabic (N = 13). Findings of the systematic review revealed that the identified studies were conducted in six countries, either specific or generic domain-related; targeting K-12 or higher education levels, generally implemented all UDL principles, directed to teachers or students using professional development programmes or school interventions, and mainly used one group quantitative research design. The meta-analysis findings showed that the total effect sizes for the identified studies were 3.56; however, considerable heterogeneity was evident. The meta-analysis results specifically showed statistically significant effect sizes for one group studies, student participants, specific domain, and quantitative research design. Discussion and future directions are presented.
MUXProofs: Succinct Arguments for Machine Computation from Tuple Lookups

Proofs for machine computation allow for proving the correct execution of arbitrary programs that operate over fixed instruction sets (e.g., RISC-V, EVM, Wasm). A standard approach for proving machine computation is to prove a universal set of constraints that encode the full instruction set at each step of program execution. This approach incurs prover cost per execution step on the order of the sum of instruction constraints for instructions in the set despite only a single instruction being executed. Existing approaches that avoid the universal cost per step (and incur only the cost of a single instruction’s constraints per step) either fail to provide zero-knowledge of program execution or rely on recursive proof composition techniques where security derives from heuristic non-black-box random oracle instantiation. Wepresent a new protocol for proving machine execution that resolves the above limitations, allowing for prover efficiency on the order of executed instructions while achieving zero-knowledge and avoiding the use of proof recursion. Our core technical contribution is a new primitive that we call a tuple lookup argument which is used to allow a prover to build up a machine execution “on-the-fly”. Our tuple lookup argument relies on univariate polynomial commitments in which tuples are encoded as evaluations on cosets of a multiplicative subgroup. We instantiate our protocol by combining our tuple lookup with the popular Marlin succinct non-interactive proof system.
Concrete NTRU Security and Advances in Practical Lattice-Based Electronic Voting

In recent years there has been much focus on the development of core cryptographic primitives based on lattice assumptions. This has been driven by the NIST call for post-quantum key encapsulation and digital signature specifications. However, there has been much less work on efficient privacy-preserving protocols with post-quantum security. In this work we present an efficient electronic voting scheme from lattice assumptions, ensuring the long-term security of encrypted ballots and voters’ privacy. The scheme relies on the NTRU and RLWE assumptions. We begin by conducting an extensive analysis of the concrete hardness of the NTRU problem. Extending the ternary-NTRU analysis of Ducas and van Woerden (ASIACRYPT 2021), we determine the concrete fatigue point of NTRU to be q = 0 . 0058 · σ 2 · d 2 . 484 (above which parameters become overstretched ) for modulus q , ring dimension d , and secrets drawn from a Gaussian of parameter σ . Moreover, we demonstrate that the nature of this relation enables a more fine-grained choice of secret key sizes, leading to more efficient parameters in practice. Using the above analysis, our second and main contribution is to significantly improve the efficiency of the state-of-the-art lattice-based voting scheme by Aranha et al. (ACM CCS 2023). Replacing the BGV encryption scheme with NTRU we obtain a factor × 5 . 3 reduction in ciphertext size and × 2 . 6 more efficient system overall, making the scheme suitable for use in real-world elections. As an additional contribution, we analyse the (partially) blind signature scheme by del Pino and Katsumata (CRYPTO 2022). We note that the NTRU security is much lower than claimed and propose new parameters.
The tweakable block cipher family QARMAv2

We introduce the tweakable block cipher QARMAv2 . It is a redesign of QARMA to improve its security bounds and allow for longer tweaks, while keeping very similar latency and area values. The wider tweak input caters to both speciﬁc use cases and the design of modes of operation with higher security bounds. This is achieved through new key and tweak schedules, revised S-Box and linear layer choices, adjustments to the 128-bit version, and a more comprehensive security analysis. The new cipher oﬀers competitive latency and area in fully unrolled HW implementations. Some of our results may be of independent interest. This includes new MILP models of certain classes of diﬀusion matrices, the comparative analysis of a full reﬂection cipher against an iterative half-cipher, and our boomerang attack framework.
Privacy Preserving Records Sharing using Blockchain and Format Preserving Encryption

Healthcare providers cannot share their patients’ encrypted data among themselves because of interoperability issues. Many blockchain-based solutions have been proposed to allow for sharing medical data in a privacy-preserving manner, but interoperability problems persist. In this paper, we present a protocol called Blockchain-Format Preserving Encryption (B-FPE) to preserve patients’ data privacy. Each patient is provided with an FPE key at the time of registration. All medical records are encrypted with the FPE key and stored in the blockchain. All the blockchain transactions are signed using group signatures. We use group signatures for signing the transactions to maintain the anonymity of healthcare providers. The new encrypted data block is concatenated to the blockchain. We present two cases: The regular phase, in which a patient is in a conscious state to share their FPE key with the healthcare provider, and the Emergency phase, in which a patient is not in a conscious state to share their key with the healthcare provider. In the latter case, the healthcare provider reconstructs the FPE key and decrypts the ciphertext. We assume this decryption happens in an oblivious manner.