Natural sd-RCCA secure public-key encryptions from hybrid paradigms

The existence of natural public-key encryption (PKE) schemes satisfying secretly detectable replayable CCA (sd-RCCA) security is left as open. By introducing probabilistic message authentication codes (MACs) into popular KEM plus DEM paradigms, several instances of such schemes are presented in this paper. It is known that the encrypt-then-authenticate paradigm gives an RCCA secure DEM when the underlying MAC is regular (but not strong) secure, where forgeries for old messages might be possible. By further requiring that the validity of such forgeries can be verified only secretly, sd-RCCA secure DEMs is obtained. Combining such DEMs with CCA secure KEMs gives sd-RCCA secure hybrid PKEs. We first formalize the related notions and this paradigm, and also other variants of KEM plus DEM hybrid paradigm since MACs are commonly used in them. Then we show natural examples of desired probabilistic MACs under the standard DDH assumption, and find appropriate KEMs to match the message space for those MACs and then obtain natural instances of sd-RCCA secure hybrid PKEs

Effects of hydrogen sulfide on storage quality, water mobility and cell wall metabolism of strawberry fruit

The effects of hydrogen sulfide (H2S) on storage quality, cellular water distribution, and cell wall metabolism of strawberry fruit after subjected to shelf or cold storage were investigated. Fruit were fumigated with a range of aqueous NaHS solution (0.4-3.2 mmol/L), then stored at 20 degrees C for 3 d or 0 degrees C for 9 d. H2S-treated fruit significantly maintained higher fruit firmness (FF) and titratable acidity (TA) as well as lower decay compared to the control fruit. Furthermore, H2S inhibited the loss in extractable juice (EJ) and improved storage quality that not only resulted from the suppressing of respiration rate, but also from the modification of water mobility and cell wall metabolism. High FF and EJ in H2S-treated fruit were closely associated with lower exchanges of free water between vacuole and cytoplasm/free space or cell wall, water-soluble polysaccharides (WSP), and activities of cell wall-modifying enzymes. Therefore, a potential benefit of H2S on retarding softening was that the H2S can reinforce the hydrogen bonding in polysaccharides and reduce activities of cell wall-modifying enzymes, causing a stabilization of cell wall structure. Although approval of the use of H2S on foods has not yet been granted, an alternative reducing agent gas based on H2S tended to be more effective in improving strawberry quality

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness

BACKGROUND: Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins. RESULTS: Using a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs). CONCLUSION: The availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies

LLaSM: Large Language and Speech Model

Multi-modal large language models have garnered significant interest recently. Though, most of the works focus on vision-language multi-modal models providing strong capabilities in following vision-and-language instructions. However, we claim that speech is also an important modality through which humans interact with the world. Hence, it is crucial for a general-purpose assistant to be able to follow multi-modal speech-and-language instructions. In this work, we propose Large Language and Speech Model (LLaSM). LLaSM is an end-to-end trained large multi-modal speech-language model with cross-modal conversational abilities, capable of following speech-and-language instructions. Our early experiments show that LLaSM demonstrates a more convenient and natural way for humans to interact with artificial intelligence. Specifically, we also release a large Speech Instruction Following dataset LLaSM-Audio-Instructions. Code and demo are available at https://github.com/LinkSoul-AI/LLaSM and https://huggingface.co/spaces/LinkSoul/LLaSM. The LLaSM-Audio-Instructions dataset is available at https://huggingface.co/datasets/LinkSoul/LLaSM-Audio-Instructions

RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmark

Ophthalmologists have used fundus images to screen and diagnose eye diseases. However, different equipments and ophthalmologists pose large variations to the quality of fundus images. Low-quality (LQ) degraded fundus images easily lead to uncertainty in clinical screening and generally increase the risk of misdiagnosis. Thus, real fundus image restoration is worth studying. Unfortunately, real clinical benchmark has not been explored for this task so far. In this paper, we investigate the real clinical fundus image restoration problem. Firstly, We establish a clinical dataset, Real Fundus (RF), including 120 low- and high-quality (HQ) image pairs. Then we propose a novel Transformer-based Generative Adversarial Network (RFormer) to restore the real degradation of clinical fundus images. The key component in our network is the Window-based Self-Attention Block (WSAB) which captures non-local self-similarity and long-range dependencies. To produce more visually pleasant results, a Transformer-based discriminator is introduced. Extensive experiments on our clinical benchmark show that the proposed RFormer significantly outperforms the state-of-the-art (SOTA) methods. In addition, experiments of downstream tasks such as vessel segmentation and optic disc/cup detection demonstrate that our proposed RFormer benefits clinical fundus image analysis and applications. The dataset, code, and models are publicly available at https://github.com/dengzhuo-AI/Real-FundusComment: IEEE J-BHI 2022; The First Benchmark and First Transformer-based Method for Real Clinical Fundus Image Restoratio

Natural sd-RCCA Secure Public-key Encryptions from Hybrid Paradigms

The existence of natural public-key encryption (PKE) schemes satisfying secretly detectable replayable CCA (sd-RCCA) security is left as open. By introducing probabilistic message authentication codes (MACs) into popular KEM plus DEM paradigms, several instances of such schemes are presented in this paper. It is known that the encrypt-then-authenticate paradigm gives an RCCA secure DEM when the underlying MAC is regular (but not strong) secure, where forgeries for old messages might be possible. By further requiring that the validity of such forgeries can be verified only secretly, sd-RCCA secure DEMs is obtained. Combining such DEMs with CCA secure KEMs gives sd-RCCA secure hybrid PKEs. We first formalize the related notions and this paradigm, and also other variants of KEM plus DEM hybrid paradigm since MACs are commonly used in them. Then we show natural examples of desired probabilistic MACs under the standard DDH assumption, and find appropriate KEMs to match the message space for those MACs and then obtain natural instances of sd-RCCA secure hybrid PKEs

Characteristic Compounds Identification and Authenticity Evaluation of Heptapleurum Honey

In order to clarify the characteristic compounds and establish the authenticity evaluation method of heptapleurum honey, high-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (HPLC-Q/TOF-MS/MS) was used to qualitative and quantitative analysis of characteristic compounds in heptapleurum honey. Five compounds were identified including 4-(1'-cyclodiethyl ether-3'-butanediol)-3,5,5-trimethyl-2-cyclohexenone (Unedone B), 3,4,5-trimethoxy cinnamyl alcohol, 4-(1'2'-dihydroxy-3'epoxypropane) -3,5,5-2-cyclohexenone (Unedone C), trans, trans abscisic acid, and cis, trans abscisic acid. Notably, 3,4,5-trimethoxy cinnamyl alcohol was first found in honey, and it could be a marker of heptapleurum honey. Moreover, 10 raw heptapleurum honey samples with different geographic origins were collected to establish HPLC fingerprint. The authenticity of six commercial heptapleurum honey samples were evaluated by combining characteristic compound with HPLC fingerprint. The results demonstrated that three brands of sample were genuine pure heptapleurum honey, two brands of sample might be mixed with other honeys. A brand sample did not contain characteristic compound and were significantly different with the standard fingerprints of heptapleurum honey. It was inferred that the sample was not heptapleurum honey. This study provides theoretical reference for the authenticity evaluation of heptapleurum honey

BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy

Epilepsy is marked by hypersynchronous bursts of neuronal activity, and seizures can propagate variably to any and all areas, leading to brain network dynamic organization. However, the relationship between the network characteristics of scalp EEG and blood oxygenation level-dependent (BOLD) responses in epilepsy patients is still not well known. In this study, simultaneous EEG and fMRI data were acquired in 18 juvenile myoclonic epilepsy (JME) patients. Then, the adapted directed transfer function (ADTF) values between EEG electrodes were calculated to define the time-varying network. The variation of network information flow within sliding windows was used as a temporal regressor in fMRI analysis to predict the BOLD response. To investigate the EEG-dependent functional coupling among the responding regions, modulatory interactions were analyzed for network variation of scalp EEG and BOLD time courses. The results showed that BOLD activations associated with high network variation were mainly located in the thalamus, cerebellum, precuneus, inferior temporal lobe and sensorimotor-related areas, including the middle cingulate cortex (MCC), supplemental motor area (SMA), and paracentral lobule. BOLD deactivations associated with medium network variation were found in the frontal, parietal, and occipital areas. In addition, modulatory interaction analysis demonstrated predominantly directional negative modulation effects among the thalamus, cerebellum, frontal and sensorimotor-related areas. This study described a novel method to link BOLD response with simultaneous functional network organization of scalp EEG. These findings suggested the validity of predicting epileptic activity using functional connectivity variation between electrodes. The functional coupling among the thalamus, frontal regions, cerebellum and sensorimotor-related regions may be characteristically involved in epilepsy generation and propagation, which provides new insight into the pathophysiological mechanisms and intervene targets for JME

Antibacterial activity and mechanism of sanguinarine against Staphylococcus aureus by interfering with the permeability of the cell wall and membrane and inducing bacterial ROS production

Staphylococcus aureus (SA) is representative of gram-positive bacteria. Sanguinarine chloride hydrate (SGCH) is the hydrochloride form of sanguinarine (SG), one of the main extracts of Macleaya cordata (M. cordata). There are few reports on its antibacterial mechanism against SA. Therefore, in this study, we investigated the in vitro antibacterial activity and mechanism of SGCH against SA. The inhibitory zone, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) were measured, and the bactericidal activity curve was plotted. In addition, the micromorphology, alkaline phosphatase (AKP) activity, Na+K+, Ca2+Mg2+-adenosine triphosphate (ATP) activity, intracellular reactive oxygen species (ROS), and fluorescein diacetate (FDA) were observed and detected. The results showed that the inhibitory zone of SGCH against SA was judged as medium-sensitive; the MIC and MBC were 128 and 256 μg/mL, respectively; in the bactericidal activity curve, SGCH with 8 × MIC could completely kill SA within 24 h. SGCH was able to interfere with the integrity and permeability of the SA cell wall and membrane, as confirmed by the scanning electron microscopy (SEM) images, the increase in extracellular AKP and Na+ K+, Ca2+ Mg2+-ATP activities as well as the fluorescein diacetate (FDA) staining experiment results. Moreover, a high concentration of SGCH could induce SA to produce large amounts of ROS. In summary, these findings revealed that SGCH has a preferable antibacterial effect on SA, providing an experimental and theoretical basis for using SG as an antibiotic substitute in animal husbandry and for the clinical control and treatment of diseases caused by SA