BackgroundPredicting drug-protein interactions (DPI) is essential for effective and safe drug discovery. Although deep learning methods have been extensively applied to DPI prediction, effectively leveraging the multi-structural and multimodal data on drugs and proteins to enhance prediction accuracy remains a significant challenge.ResultsThis study proposes CMMSCL-DPI, a cross-modal multi-structural contrastive learning model. CMMSCL-DPI applies contrastive learning to the multi-dimensional structural features of proteins and drugs separately and integrates interaction features from a DPI heterogeneous graph network to facilitate cross-modal contrastive learning. This approach effectively captures the key differences and similarities between proteins and drugs, significantly enhancing the model's generalization capabilities for novel drug-target pairs. Experimental results across four benchmark datasets demonstrate that CMMSCL-DPI outperforms five state-of-the-art baseline models in overall performance. Additionally, the model successfully identified an unreported drug-protein interaction, which was subsequently validated through all-atom molecular dynamics simulations.ConclusionsThis case study not only confirms the predictive accuracy of CMMSCL-DPI but also underscores its potential in discovering novel protein-ligand interactions.

INTRODUCTION:DNA microarray synthesis enables the large-scale and precise generation of DNA sequences for genomic research, data storage, and synthetic biology. However, the order of nucleotide addition significantly affects synthesis efficiency and accuracy. This study aims to model DNA microarray in situ synthesis as a traveling salesman problem (TSP) and to develop an optimized synthesis strategy. METHODS:A mathematical model for in situ microarray synthesis was established, and both greedy algorithms and a simulated annealing algorithm were applied to optimize the nucleotide addition order. The performance of these approaches was evaluated by comparing the number of synthesis cycles required at different sequence scales, ranging from 10 × 10 nt to 10000 × 120 nt arrays. RESULTS:The optimized synthesis schemes effectively reduced the total number of synthesis cycles. At the 10 × 10 nt scale, simulated annealing reduced cycles by 40.65% compared to the traditional scheme and by 8.52% compared to the greedy algorithm. At larger scales (100 × 100 nt to 10000 × 120 nt), cycle reductions ranged from 33.80% to 37.26%, with simulated annealing outperforming the greedy algorithm by 2.68% to 3.42%. These reductions translated into significant savings in synthesis time, reagent consumption, and overall cost. DISCUSSION:The simulated annealing-based optimization strategy demonstrates clear advantages in improving DNA microarray synthesis efficiency while reducing material usage and waste, thereby enhancing cost-effectiveness. Such improvements offer practical benefits for applications, including gene editing, drug development, and DNA data storage.

Changes in diet, cleanliness, stress, and exercise patterns may contribute to the disappearance of various gut microbes in humans who relocate to developed countries from developing countries. To explore the impact of environmental cleanliness on the gut microbiota, adult mice housed in a general animal room were divided into three groups. The control group was subjected to an unchanged living environment, SPF mice were moved to a specific pathogen-free (SPF) animal room with higher environmental cleanliness, and SPFL (specific pathogen-free specific with a fecal leakage grid) mice were moved to the SPF animal room and reared in cages with the function of preventing mice from eating feces as much as possible. Metagenome sequencing results showed that the gut microbial diversity decreased after the environmental change, accompanied by a substantial loss in gut microbiota, including genera known to have protective effects against allergies and those involved in short-chain fatty acid production. Additionally, the abundance of functional genes involved in short-chain fatty acid metabolism, amino acid synthesis, vitamin metabolism, flagellar assembly, and bacterial chemotaxis decreased. The environmental hygiene improvement also resulted in significant increases in total serum IgE, IL-4, IL-5, and IL-13 levels in mice with artificially induced chronic inflammatory dermatosis. Compared with SPF mice, preventing mice from eating feces as much as possible decreased the gut microbial diversity but did not markedly change functional gene expression or total serum cytokine levels. IMPORTANCE:Research has indicated that the human gut microbial diversity gradually decreases, while the prevalence of allergic diseases increases after movement from developing countries to developed countries. A healthy gut microbiota is necessary for proper human immune function. Movement from undeveloped to developed regions is often accompanied by an increase in environmental cleanliness. However, whether changes in environmental cleanliness are an important factor contributing to the decreased gut microbial diversity and increased prevalence of allergic diseases has not been reported. This study demonstrates the impact of increased environmental cleanliness on gut microbiota and susceptibility to allergic diseases and contributes to a better understanding of the increased incidence rate of various chronic diseases.

The breakout of African swine fever virus (ASFV) has severely impacted food safety and public health. Here, a point‐of‐care testing method based on solvent‐responsive magnetic beads suitable for large‐area diagnosis and mutation screening in remote areas is developed to detect it by combining bioluminescent pyrophosphate in real‐time (BART) technology and recombinase‐aid amplification (RAA) technology. The combined testing method includes selection of different deoxyadenosine triphosphate modification structures and DNA polymerases. The method is conducted on plasmids of ASFV at various concentrations. Based on above, the detection device is developed and achieved detection in real‐time. The detection limit is around 10 copies, with no cross‐reaction of nucleic acid samples from other viruses. Then, it is applied on clinical samples and showed good specificity and detection efficiency. Moreover, this method is also compatible with a digital testing method and digital POCT devices based on RAA‐BART device and a mobile phone shell (based on bionic hydrogel) are developed here. Finally, the sensitive of them are tested and showed a comparable detection limit of single copy.

OBJECTIVE:To investigate the regulatory effects of two traditional mineral medicines (TMMs), Gypsum Fibrosum (Shigao, GF) and Terra Flava Usta (Zaoxintu, TFU), on gut-beneficial bacteria in mice, and preliminarily explore their mechanisms of action. METHODS:Mice were randomly divided into 3 groups (n=10 per group): the control group (standard diet), the GF group (diet supplemented with 2% GF), and the TFU group (diet supplemented with 2% TFU). After 4-week intervention, 16S rRNA gene sequencing was used to analyze the changes in the gut microbiota (GM). Scanning electron microscopy, in combination with coumarin A tetramethyl rhodamine conjugate and Hoechst stainings, was used to observe the bacteria and biofilm formation. RESULTS:Principal coordinate analysis revealed that GF and TFU significantly altered the GM composition in mice. Further analysis revealed that GF and TFU affected different types of gut bacteria, suggesting that different TMMs may selectively modulate specific bacterial populations. For certain bacteria, such as Faecalibaculum and Ileibacterium, both GF and TFU exhibited growth-promoting effects, implying that they may be sensitive to TMMs and that different TMMs can increase their abundance through their respective mechanisms. Notably, Lactobacillus reuteri, a widely recognized and used probiotic, was significantly enriched in the GF group. Random forest analysis identified Ileibacterium valens as a potential indicator bacterium for TMMs' impact on GM. Further mechanistic studies showed that gut bacteria formed biofilm structures on the TFU surface. CONCLUSIONS:This study provides new insights into the interaction between TMMs and GM. As safe and effective natural clays, GF and TFU hold promise as potential candidates for prebiotic development.

Background: DNA electrochemical synthesis, which utilizes electrochemical reactions to synthesize oligonucleotides, has gained attention for its potential in high-throughput applications. Gold, with its excellent electron conductivity, strong chemical stability, and process compatibility, is widely used for DNA electrochemical synthesis chips. Its ability to be chemically modified for initiating oligonucleotide synthesis makes it the material of choice. However, when gold electrodes are used as reaction substrates, metal layer delamination occurs due to the combined effects of voltage and electrolyte, which negatively affects DNA synthesis stability. The problem addressed in this study is the metal layer delamination that hinders reliable DNA synthesis. Results: This study demonstrates that pulsed DC voltage effectively mitigates metal layer delamination on gold electrodes during DNA electrochemical synthesis. The delamination rate decreases significantly with higher pulse frequencies, from 54.61 % under continuous DC voltage to 17.98 % under pulsed DC voltage at the same voltage magnitude and a pulse frequency of 0.4 Hz. Notably, the electrochemical deprotection process causes minimal electrode damage even under short-term electrolytic action. Over longer operation times, pulsed DC voltage significantly extends electrode lifespan, with electrodes exhibiting enhanced stability and durability compared to continuous DC voltage. Fluorescence characterization of electrochemically synthesized DNA shows that synthesis quality is comparable under both pulsed and continuous DC voltages, provided the input voltage and operational time are consistent. This approach ensures the stable operation of gold electrodes, even in challenging chemical environments, and demonstrates clear advantages over traditional continuous DC voltage methods for preventing delamination. Significance and Novelty: This work introduces the use of pulsed DC voltage to enhance electrode stability, effectively preventing metal layer delamination and ensuring high-quality DNA synthesis. By extending electrode lifespan and minimizing degradation, this method addresses key challenges in electrochemical DNA synthesis and supports the development of large-scale, high-throughput applications in the field.

Abstract Here, a new‐rising technology (DNA storage) in which the binary digital information/data is converted into a DNA sequence composed of distinct nucleotides, providing a dense, stable, energy‐efficient, and sustainable data storage solution is studied. In principle, this technology offers substantial data density. However, the theoretical limit of DNA storage has not been achieved yet. In this study, a new DNA storage system is proposed based on hydrogels with SiO2 layer (their pore size can be regulated). The highest data density of the hydrogels is obtained to be 6.3 × 109 GB g−1. Further, by coupling them with digital polymerase chain reaction (dPCR), the recovery limit reaches five copies of DNA. Subsequently, three‐dimensional (3D) printing is used to explore the effect of macrostructures on the DNA storage capacity. Finally, bionic‐structure thermally‐responsive robust (Best) hydrogels with four different structures are developed, which achieve a data density of 1.04 × 1010 GB g−1.

Summary The decline in gut microbial diversity of modern human is closely associated with the rising prevalence of various diseases. It is imperative to investigate the underlying causes of gut microbial loss and the rescue measures. Although the impact of non-perinatal antibiotic use on gut microbiota has been recognized, its intergenerational effects remain unexplored. Our previous research has highlighted soil in the farm environment as a key prebiotic for gut microbiome health by restoring gut microbial diversity and balance. In this study, we investigated the intergenerational consequences of antibiotic exposure and the therapeutic potential of soil prebiotics. We treated mice with vancomycin and streptomycin for 2 weeks continuously, followed by 4-8 weeks of withdrawal period before breeding. The process was repeated across 3 generations. Half of the mice in each generation received an oral soil prebiotic intervention. We assessed gut microbial diversity, anxiety behavior, microglia reactivity, and gut barrier integrity across generations. The antibiotics exposure led to a decrease in gut microbial diversity over generations, along with aggravated anxiety behavior, microglia abnormalityies, and altered intestinal tight junction protein expression. Notably, the third generation of male mice exhibited impaired reproductive capacity. Oral sterile soil intervention restored gut microbial diversity in adult mice across generations, concomitantly rescuing abnormalities in behavior, microglia activity, and intestinal barrier integrity. In conclusion, this study simulated an important process of the progressive loss gut microbiota diversity in modern human and demonstrated the potential of sterile soil as a prebiotic to reverse this process. The study provides a theoretical and experimental basis for the research and therapeutic interventions targeting multiple modern chronic diseases related to intestinal microorganisms.

BackgroundA low-clean living environment (LCLE) can increase gut microbial diversity and prevent allergic diseases, whereas gut microbial dysbiosis is closely related to the pathogenesis of asthma. Our previous studies suggested that soil in the LCLE is a key factor in shaping intestinal microbiota. We aimed to explore whether sterilized soil intake as a prebiotic while being incubated with microbes in the air can attenuate mouse asthma inflammation by modifying gut microbiota.Methods16S rRNA gene sequencing was used to analyze the gut microbial composition, in combination with immune parameters measured in the lung and serum samples.Results16S rRNA gene sequencing results showed significant differences in the fecal microbiota composition between the test and control mice, with a higher abundance of Allobaculum, Alistipes, and Lachnospiraceae_UCG-001, which produce short-chain fatty acids and are beneficial for health in the test mice. Soil intake significantly downregulated the concentrations of IL-4 and IL-9 in serum and increased the expression of IFN-γ, which regulated the Th1/Th2 balance in the lung by polarizing the immune system toward Th1, alleviating ovalbumin-induced asthma inflammation. The effect of sensitization on gut microbiota was greater than that of air microbes and age together but weaker than that of soil.ConclusionsSoil intake effectively reduced the expression of inflammatory cytokines in asthmatic mice, possibly by promoting the growth of multiple beneficial bacteria. The results indicated that the development of soil-based prebiotic products might be used for allergic asthma management, and our study provides further evidence for the hygiene hypothesis.

We proposed a single-color fluorogenic DNA decoding sequencing method designed to improve sequencing accuracy, increase read length and throughput, as well as decrease scanning time. This method involves the incorporation of a mixture of four types of 3’-O-modified nucleotide reversible terminators into each reaction. Among them, two nucleotides are labeled with the same fluorophore, while the remaining two are unlabeled. Only one nucleotide can be extended in each reaction, and an encoding that partially defines base composition can be obtained. Through cyclic interrogation of a template twice with different nucleotide combinations, two sets of encodings are sequentially obtained, enabling the determination of the sequence. We demonstrate the feasibility of this method using established sequencing chemistry, achieving a cycle efficiency of approximately 99.5 %. Notably, this strategy exhibits remarkable efficacy in the detection and correction of sequencing errors, achieving a theoretical error rate of 0.00016 % at a sequencing depth of ×2, which is lower than Sanger sequencing. This method is theoretically compatible with the existing sequencing-by-synthesis (SBS) platforms, and the instrument is simpler, which may facilitate further reductions in sequencing costs, thereby broadening its applications in biology and medicine. Moreover, we demonstrate the capability to detect known mutation sites using information from only a single sequencing run. We validate this approach by accurately identifying a mutation site in the human mitochondrial DNA.

A correctable two-color fluorogenic DNA decoding sequencing, which can significantly improve sequencing accuracy and throughput by employing a dual-nucleotide addition combined with fluorogenic sequencing-by-synthesis (SBS) chemistry.

The accurate identification of drug-protein interactions (DPIs) is crucial in drug development, especially concerning G protein-coupled receptors (GPCRs), which are vital targets in drug discovery. However, experimental validation of GPCR-drug pairings is costly, prompting the need for accurate predictive methods. To address this, we propose MFD-GDrug, a multimodal deep learning model. Leveraging the ESM pretrained model, we extract protein features and employ a CNN for protein feature representation. For drugs, we integrated multimodal features of drug molecular structures, including three-dimensional features derived from Mol2vec and the topological information of drug graph structures extracted through Graph Convolutional Neural Networks (GCN). By combining structural characterizations and pretrained embeddings, our model effectively captures GPCR-drug interactions. Our tests on leading GPCR-drug interaction datasets show that MFD-GDrug outperforms other methods, demonstrating superior predictive accuracy.

In this study, a revolutionary air filtration technology, the F-MAX multilayer composite plate, is introduced, offering high efficiency and environmental sustainability. This innovative system is designed to capture a wide range of pollutants, including harmful viruses and bacteria, enhancing air quality significantly. The F-MAX combines multiple layers, each tailored to target specific particles, with features like an electrostatically charged melt-blown fabric and eco-friendly materials like lithium brine by-product magnesia. Its durability, antiviral, and antibacterial properties make it a sustainable choice for air purification, suitable for both commercial and residential use. This system represents healthier living environments, effectively removing airborne contaminants, and demonstrating a commitment to a sustainable future. Additionally, the study introduces the F-robot specifically designed for laboratory environments to ensure pristine air quality.

The improved abstract which especially take the suggestions above can be seen as follow:This study addresses the challenge of pathogen regulation in confined spaces by introducing the T-robot, an innovative air filtration robot featuring the F-MAX multilayer composite plate. Designed to capture a wide range of pollutants, including harmful viruses and bacteria, the T-robot significantly enhances air quality. The experimental setup used magnesium phosphate cement, electrostatically charged melt-blown fabric, and eco-friendly materials such as lithium brine by-product magnesia. Key results include a virus removal rate of 99.99% and an antibacterial rate of 98%.The F-MAX system combines multiple layers, each targeting specific particles, with features like the self-healing Desert Rose (DR) coating and high-speed air circulation. The T-robot's high filtration efficiency and sustainable design make it superior to traditional methods, suitable for both commercial and residential use. Its durability and advanced filtration capabilities help reduce airborne contaminants, creating healthier living spaces and demonstrating a commitment to a sustainable future.

Background The cost of synthetic DNA has limited applications in frontier science and technology fields such as synthetic biology, DNA storage, and DNA chips. Objective The objective of this study is to find an algorithm-optimized scheme for the in situ synthesis of DNA microarrays, which can reduce the cost of DNA synthesis. Methods Here, based on the characteristics of in situ chemical synthesis of DNA microarrays, an optimization algorithm was proposed. Through data grading, the sequences with the same base at as many different features as possible were synthesized in parallel to reduce synthetic cycles. Results and Discussion The simulation results of 10 and 100 randomly selected sequences showed that when level=2, the reduction ratio in the number of synthetic cycles was the largest, 40% and 32.5%, respectively. Subsequently, the algorithm-optimized scheme was applied to the electrochemical synthesis of 12,000 sequences required for DNA storage. The results showed that compared to the 508 cycles required by the conventional synthesis scheme, the algorithm-optimized scheme only required 342 cycles, which reduced by 32.7%. In addition, the reduced 166 cycles reduced the total synthesis time by approximately 11 hours. Conclusions The algorithm-optimized synthesis scheme can not only reduce the synthesis time of DNA microarrays and improve synthesis efficiency, but more importantly, it can also reduce the cost of DNA synthesis by nearly 1/3. In addition, it is compatible with various in situ synthesis methods of DNA microarrays, including soft-lithography, photolithography, a photoresist layer, electrochemistry and photoelectrochemistry. Therefore, it has very important application value.

Although numerous approaches were proposed for the nucleic acid (NA)-based SARS-CoV-2 detection, the nonideal NA desorption efficiency of conventional magnetic beads (MBs) limits their widespread application. In this study, we developed solvent-responsive MBs (called responsive MBs), which, in the presence of buffers, modulated the absorption and desorption capacities of NA by flipping the surface -COO-. Relative to other commercial MBs, responsive MBs exhibited similar absorption profiles and markedly enhanced desorption profiles. When applied for NA detection of complex samples, responsive MBs exhibited better performance of RNA detection than DNA, with obvious advantages in sensitivity. Specifically, the RNA and DNA desorption rates of commercial MBs were ∼85 and 82.5%, while those of responsive MBs were nearly 94 and 93.5%, respectively. Furthermore, responsive MBs exhibited remarkable extraction ability in a wide range of tissues and better performance of RNA extraction than DNA. When applied for SARS-CoV-2 detection, the responsive MBs along with the simulated digital RT-LAMP (a previously established apparatus) further improved detection efficiency, yielding a precise quantitative detection as low as 25 copies and an ultimate sensibility detection of 5 copies/mL. It was also successfully employed in numerous NA-based technologies such as polymerase chain reaction (PCR), sequencing, and so on.

Protein sequence classification is a crucial research field in bioinformatics, playing a vital role in facilitating functional annotation, structure prediction, and gaining a deeper understanding of protein function and interactions. With the rapid development of high-throughput sequencing technologies, a vast amount of unknown protein sequence data is being generated and accumulated, leading to an increasing demand for protein classification and annotation. Existing machine learning methods still have limitations in protein sequence classification, such as low accuracy and precision of classification models, rendering them less valuable in practical applications. Additionally, these models often lack strong generalization capabilities and cannot be widely applied to various types of proteins. Therefore, accurately classifying and predicting proteins remains a chal-lenging task. In this study, we propose a protein sequence classifier called Multi-Laplacian Regularized Random Vector Functional Link (MLapRVFL). By incorporating Multi-Laplacian and L2,1 -norm regularization terms into the basic Random Vector Functional Link (RVFL) method, we effectively improve the model's generalization performance, enhance the robustness and accuracy of the classification model. The experimental results on two commonly used datasets demonstrate that MLapRVFL outperforms popular machine learning methods and achieves superior predictive performance compared to previous studies. In conclusion, the proposed MLapRVFL method makes significant contributions to protein sequence prediction.

Digital information, when converted into a DNA sequence, provides dense, stable, energy-efficient, and sustainable data storage. The most stable method for encapsulating DNA has been in an inorganic matrix of silica, iron oxide, or both, but are limited by low DNA uptake and complex recovery techniques. This study investigated a rationally designed thermally responsive functionally graded (TRFG) hydrogel as a simple and cost-effective method for storing DNA. The TRFG hydrogel shows high DNA uptake, long-term protection, and reusability due to nondestructive DNA extraction. The high loading capacity was achieved by directly absorbing DNA from the solution, which is then retained because of its interaction with a hyperbranched cationic polymer loaded into a negatively charged hydrogel matrix used as a support and because of its thermoresponsive nature, which allows DNA concentration within the hydrogel through multiple swelling/deswelling cycles. We were able to achieve a high DNA data density of 7.0 × 10 9 gigabytes per gram using a hydrogel-based system.

Next-generation sequencing (NGS) is present in all fields of life science, which has greatly promoted the development of basic research while being gradually applied in clinical diagnosis. However, the cost and throughput advantages of next-generation sequencing are offset by large tradeoffs with respect to read length and accuracy. Specifically, its high error rate makes it extremely difficult to detect SNPs or low-abundance mutations, limiting its clinical applications, such as pharmacogenomics studies primarily based on SNP and early clinical diagnosis primarily based on low abundance mutations. Currently, Sanger sequencing is still considered to be the gold standard due to its high accuracy, so the results of next-generation sequencing require verification by Sanger sequencing in clinical practice. In order to maintain high quality next-generation sequencing data, a variety of improvements at the levels of template preparation, sequencing strategy and data processing have been developed. This study summarized the general procedures of next-generation sequencing platforms, highlighting the improvements involved in eliminating errors at each step. Furthermore, the challenges and future development of next-generation sequencing in clinical application was discussed.

Background Low cleanliness living environment (LCLE) can increase gut microbial diversity and prevent allergic diseases, whereas gut microbial dysbiosis is closely related to the pathogenesis of asthma. Our previous studies suggested that soil in the LCLE is a key factor in shaping intestinal microbiota.Objective We aimed to explore if sterilized soil intake as prebiotics while being incubated with microbes in the air can attenuate mice asthma symptoms by modifying gut microbiota.Methods 16S rRNA gene sequencing was used to analyze the gut microbial composition, in combination with immune parameters measured in the lung and serum samples.Results 16S rRNA gene sequencing results showed significant differences in the fecal microbiota composition between the test and control mice, with a higher abundance of Allobaculum , Alistipes, and Lachnospiraceae_UCG-001 , which produce short-chain fatty acids and are beneficial for health in the test mice. Soil intake downregulated the concentrations of IL-6, IL-4, IL-17F, TNF-α, and IL-22 in serum and increased the expression of IFN-γ, which regulated the Th1/Th2 balance in lung by polarizing the immune system toward Th1, strongly alleviating ovalbumin-induced asthma inflammation. The effect of sensitization on gut microbiota was greater than that of air microbes and age together, but weaker than that of soil.Conclusion Soil intake had a significant therapeutic effect on mouse asthma, possibly by promoting the growth of multiple beneficial bacteria. The results indicated that the development of soil-based prebiotic products might be used for allergic asthma management and our study provides further evidence for the hygiene hypothesis.Importance Exposure to a low cleanliness living environment (LCLE), of which soil is an important component, can shape the gut microbiota and support immune tolerance, preventing allergic diseases such as eczema and asthma. However, with the rapid progress of urbanization, it is impossible to return to farm-like living and we are becoming disconnected from the soil. Here, our study found that ingesting sterilized soil and living in an LCLE have the same protective effects on asthma inflammation. Ingestion of sterilized soil significantly altered the gut microbial composition and exerted significant therapeutic effects on asthmatic mice. However, edible sterilized soil possesses more advantages than LCLE exposure, such as the absence of pathogenic bacteria, safer, and convenience. The results indicate that the development of soil-based prebiotic products might be used for allergic asthma management and our study further supports the hygiene hypothesis.Notification The article is currently undergoing peer review in the World Allergy Organization Journal.### Competing Interest StatementThe authors have declared no competing interest.