A Combined Molecular Cloning and Mass Spectrometric Method to Identify, Characterize, and Design Frenatin Peptides from the Skin Secretion of Litoria infrafrenata

Amphibian skin secretions are unique sources of bioactive molecules, particularly bioactive peptides. In this study, the skin secretion of the white-lipped tree frog (Litoria infrafrenata) was obtained to identify peptides with putative therapeutic potential. By utilizing skin secretion-derived mRNA, a cDNA library was constructed, a frenatin gene was cloned and its encoded peptides were deduced and confirmed using RP-HPLC, MALDI-TOF and MS/MS. The deduced peptides were identified as frenatin 4.1 (GFLEKLKTGAKDFASAFVNSIKGT) and a post-translationally modified peptide, frenatin 4.2 (GFLEKLKTGAKDFASAFVNSIK.NH2). Antimicrobial activity of the peptides was assessed by determining their minimal inhibitory concentrations (MICs) using standard model microorganisms. Through studying structure–activity relationships, analogues of the two peptides were designed, resulting in synthesis of frenatin 4.1a (GFLEKLKKGAKDFASALVNSIKGT) and frenatin 4.2a (GFLLKLKLGAKLFASAFVNSIK.NH2). Both analogues exhibited improved antimicrobial activities, especially frenatin 4.2a, which displayed significant enhancement of broad spectrum antimicrobial efficiency. The peptide modifications applied in this study, may provide new ideas for the generation of leads for the design of antimicrobial peptides with therapeutic applications

Advances in Molecularly Imprinted Polymers for Bone Biomarker Detection and Therapeutic Applications

This review explores the application of molecularly imprinted polymers (MIPs) in detecting bone turnover biomarkers and advancing osteogenic treatment strategies. MIPs, designed to mimic biological recognition sites, offer innovative solutions for precise molecular recognition in bone health management. Chemical methodologies for MIPs synthesis and their integration into diagnostic systems for detecting bone resorption markers are highlighted. Furthermore, MIP‐driven therapeutic advancements, including controlled drug release, cell imprinting for osteogenic differentiation, and functional scaffolds for tissue regeneration, are emphasized. This review underscores MIPs’ potential to revolutionize bone disease management and calls for further exploration into chemical designs to optimize their clinical and practical applications

Detecting Backdoors in Pre-trained Encoders

Self-supervised learning in computer vision trains on unlabeled data, such as images or (image, text) pairs, to obtain an image encoder that learns high-quality embeddings for input data. Emerging backdoor attacks towards encoders expose crucial vulnerabilities of self-supervised learning, since downstream classifiers (even further trained on clean data) may inherit backdoor behaviors from encoders. Existing backdoor detection methods mainly focus on supervised learning settings and cannot handle pre-trained encoders especially when input labels are not available. In this paper, we propose DECREE, the first backdoor detection approach for pre-trained encoders, requiring neither classifier headers nor input labels. We evaluate DECREE on over 400 encoders trojaned under 3 paradigms. We show the effectiveness of our method on image encoders pre-trained on ImageNet and OpenAI's CLIP 400 million image-text pairs. Our method consistently has a high detection accuracy even if we have only limited or no access to the pre-training dataset.Comment: Accepted at CVPR 2023. Code is available at https://github.com/GiantSeaweed/DECRE

LOTUS: Evasive and Resilient Backdoor Attacks through Sub-Partitioning

Backdoor attack poses a significant security threat to Deep Learning applications. Existing attacks are often not evasive to established backdoor detection techniques. This susceptibility primarily stems from the fact that these attacks typically leverage a universal trigger pattern or transformation function, such that the trigger can cause misclassification for any input. In response to this, recent papers have introduced attacks using sample-specific invisible triggers crafted through special transformation functions. While these approaches manage to evade detection to some extent, they reveal vulnerability to existing backdoor mitigation techniques. To address and enhance both evasiveness and resilience, we introduce a novel backdoor attack LOTUS. Specifically, it leverages a secret function to separate samples in the victim class into a set of partitions and applies unique triggers to different partitions. Furthermore, LOTUS incorporates an effective trigger focusing mechanism, ensuring only the trigger corresponding to the partition can induce the backdoor behavior. Extensive experimental results show that LOTUS can achieve high attack success rate across 4 datasets and 7 model structures, and effectively evading 13 backdoor detection and mitigation techniques. The code is available at https://github.com/Megum1/LOTUS.Comment: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024

Signatures of a gapless quantum spin liquid in the Kitaev material Na3_3Co2−x_{2-x}Znx_xSbO6_6

The honeycomb-lattice cobaltate Na$_3$Co$_2$SbO$_6$ has recently been proposed to be a proximate Kitaev quantum spin liquid~(QSL) candidate. However, non-Kitaev terms in the Hamiltonian lead to a zigzag-type antiferromagnetic~(AFM) order at low temperatures. Here, we partially substitute magnetic Co$^{2+}$ with nonmagnetic Zn$^{2+}$ and investigate the chemical doping effect in tuning the magnetic ground states of Na$_3$Co$_{2-x}$Zn$_x$SbO$_6$. X-ray diffraction characterizations reveal no structural transition but quite tiny changes on the lattice parameters over our substitution range $0\leq x\leq0.4$. Magnetic susceptibility and specific heat results both show that AFM transition temperature is continuously suppressed with increasing Zn content $x$ and neither long-range magnetic order nor spin freezing is observed when $x\geq0.2$. More importantly, a linear term of the specific heat representing fermionic excitations is captured below 5~K in the magnetically disordered regime, as opposed to the $C_{\rm m}\propto T^3$ behavior expected for bosonic excitations in the AFM state. Based on the data above, we establish a magnetic phase diagram of Na$_3$Co$_{2-x}$Zn$_x$SbO$_6$. Our results indicate the presence of gapless fractional excitations in the samples with no magnetic order, evidencing a potential QSL state induced by doping in a Kitaev system.Comment: 10 pages, 5 figure

Evolution of gene regulation in ruminants differs between evolutionary breakpoint regions and homologous synteny blocks

The role of chromosome rearrangements in driving evolution has been a long-standing question of evolutionary biology. Here we focused on ruminants as a model to assess how rearrangements may have contributed to the evolution of gene regulation. Using reconstructed ancestral karyotypes of Cetartiodactyls, Ruminants, Pecorans, and Bovids, we traced patterns of gross chromosome changes. We found that the lineage leading to the ruminant ancestor after the split from other cetartiodactyls was characterized by mostly intrachromosomal changes, whereas the lineage leading to the pecoran ancestor (including all livestock ruminants) included multiple interchromosomal changes. We observed that the liver cell putative enhancers in the ruminant evolutionary breakpoint regions are highly enriched for DNA sequences under selective constraint acting on lineage-specific transposable elements (TEs) and a set of 25 specific transcription factor (TF) binding motifs associated with recently active TEs. Coupled with gene expression data, we found that genes near ruminant breakpoint regions exhibit more divergent expression profiles among species, particularly in cattle, which is consistent with the phylogenetic origin of these breakpoint regions. This divergence was significantly greater in genes with enhancers that contain at least one of the 25 specific TF binding motifs and located near bovidae-to-cattle lineage breakpoint regions. Taken together, by combining ancestral karyotype reconstructions with analysis of cis regulatory element and gene expression evolution, our work demonstrated that lineage-specific regulatory elements colocalized with gross chromosome rearrangements may have provided valuable functional modifications that helped to shape ruminant evolution

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data