Exploiting Longitudinal Speech Sessions via Voice Assistant Systems for Early Detection of Cognitive Decline.

Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's disease (AD), a form of neurodegenerative disorder. Early identification of MCI is crucial for delaying its progression through timely interventions. Existing research has demonstrated the feasibility of detecting MCI using speech collected from clinical interviews or digital devices. However, these approaches typically analyze data collected at limited time points, limiting their ability to identify cognitive changes over time. This paper presents a longitudinal study using voice assistant systems (VAS) to remotely collect seven-session speech data at three-month intervals across 18 months. We propose two methods to improve MCI detection and the prediction of cognitive changes. The first method incorporates historical data, while the second predicts cognitive changes at two time points. Our results indicate improvements when incorporating historical data: the average F1-score for MCI detection improves from 58.6% to 71.2% (by 12.6%) in the case of acoustic features and from 62.1% to 75.1% (by 13.0%) in the case of linguistic features. Additionally, the prediction of cognitive changes achieves an F1-score of 73.7% in the case of acoustic features. These results confirm the potential of VAS-based speech sessions for early detection of cognitive decline.

A Real-Time and Interactive Fluid Modeling System for Mixed Reality.

Within the realm of mixed reality, the capability to dynamically render environmental effects with high realism plays a crucial role in amplifying user engagement and interaction. Fluid dynamics, in particular, stand out as essential elements for crafting immersive virtual settings. This includes the simulation of phenomena like smoke, fire, and clouds, which are instrumental in enriching the virtual experience. This work showcases a cutting-edge system developed to produce dynamic and interactive fluid effects that mirror real captured data in real-time for mixed reality applications. This innovative system seamlessly incorporates fluid reconstruction alongside velocity estimation processes within the Unity engine environment. Our approach leverages a novel physics-based differentiable rendering technique, grounded in the principles of light transport in participating media, to simulate the intricate behaviors of fluid while ensuring high fidelity in visual appearance. To further enhance realism, we have expanded our framework to include the estimation of velocity fields, addressing the critical need for fluid motion simulation. The practical application of these techniques demonstrates the system's capacity to offer a robust platform for fluid modeling in mixed reality environments. Through extensive evaluations, we illustrate the effectiveness of our approach in various scenes, underscoring its potential to transform mixed reality content creation by providing developers with the tools to incorporate highly realistic and interactive fluid seamlessly.

Reutilization of post-adsorption lanthanum-loaded straw alleviates phosphorus pollution in rice-wheat system: Subsequent performance and underlying mechanisms.

Adsorption technology for phosphorus (P) removal is considered promising and reutilization of post-adsorbent can contribute to promoting sustainable agricultural production. However, the long-lasting impact of the post-adsorbent on crop growth and P remains unclear. This study assessed the effects of P-adsorbed lanthanum-modified straw (La@straw-P) on the rice yield, P fractionation and associated water quality parameters. The findings indicated that, compared with traditional fertilizer regimes, La@straw-P expedited the P reduction in the flooding water achieving a rate of decline to the tertiary standard for surface water (0.20 mg/L) 3.8 times faster and enhanced increased the P harvest index by 17.00 %. Economic estimation proved the positive benefits of La@straw-P in planting-breeding combination system. Redundancy analysis (RDA) and co-occurrence network analysis (CONA) revealed that electrical conductivity (EC) and dissolved Fe played primary roles in regulating total P. Fourier transform infrared spectra (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectra (XPS), and soil P fractions collectively demonstrated that the abundant adsorption sites on La@straw-P could facilitate the transformation of active P into moderately Ca-bound P. This study proposes a strategy for recycling P-adsorbed materials to mitigate agricultural non-point P pollution.

Insight into the mechanism of digestibility inhibition by interaction between corn starch with different gelatinization degree and water extractable arabinoxylan.

On the basis of revealing the interaction mechanism between corn starch (CS) and water-extractable arabinoxylan (WEAX) with high/low molecular weight (H-WEAX, L-WEAX), the degree of gelatinization (DG) on structural behaviors and in vitro digestibility of CS-WEAX complexes (CS/H, CS/L) was evaluated. With the increased DG from 50 % to 95 %, the water adsorption capacity of CS/L was increased 64 %, 58 %, 47 %, which were higher than that of CS/H (39 %, 54 %, 33 %). The gelatinization of starch was inhibited by WEAX, resulting in the enhancement of crystallinity, short-range ordered structure and molecular size of CS-WEAX complexes. Stronger interaction was detected in CS/L than with CS/H as proved by the increased hydrogen bonds and electrostatic force. Complexes exhibited higher resistant starch content (RS) at diverse DG, especially for CS/L. Notability, RS content of samples with 50 % DG were increased from 27.72 % to 32.89 % (CS/H), 36.96 % (CS/L). Except for the reduction of gelatinization degree by adding WEAX, the other possible mechanisms of retarding digestibility were explained as the small steric hindrance of L-WEAX promoted encapsulation of starch granules, limiting enzyme accessibility. Additionally, the fragmentation of CS granules with high DG promoted the movement of H-WEAX, reducing the difference in digestibility compared to CS/L.

Targeting metabolism to enhance immunotherapy within tumor microenvironment.

Cancer metabolic reprogramming has been considered an emerging hallmark in tumorigenesis and the antitumor immune response. Like cancer cells, immune cells within the tumor microenvironment or premetastatic niche also undergo extensive metabolic reprogramming, which profoundly impacts anti-tumor immune responses. Numerous evidence has illuminated that immunosuppressive TME and the metabolites released by tumor cells, including lactic acid, Prostaglandin E2 (PGE2), fatty acids (FAs), cholesterol, D-2-Hydroxyglutaric acid (2-HG), adenosine (ADO), and kynurenine (KYN) can contribute to CD8+ T cell dysfunction. Dynamic alterations of these metabolites between tumor cells and immune cells can similarly initiate metabolic competition in the TME, leading to nutrient deprivation and subsequent microenvironmental acidosis, which impedes immune response. This review summarizes the new landscape beyond the classical metabolic pathways in tumor cells, highlighting the pivotal role of metabolic disturbance in the immunosuppressive microenvironment, especially how nutrient deprivation in TME leads to metabolic reprogramming of CD8+ T cells. Likewise, it emphasizes the current therapeutic targets or strategies related to tumor metabolism and immune response, providing therapeutic benefits for tumor immunotherapy and drug development in the future. Cancer metabolic reprogramming has been considered an emerging hallmark in tumorigenesis and the antitumor immune response. Dynamic alterations of metabolites between tumor cells and immune cells initiate metabolic competition in the TME, leading to nutrient deprivation and subsequent microenvironmental acidosis, which impedes immune response.

Proteomic Analysis of Milk Fat Globule Membrane Protein Modulation of Differently Expressed Proteins in Lactobacillus plantarum under Bile Salt Stress.

Tolerance to bile stress is a crucial property for lactic acid bacteria (LAB) to survive in the gastrointestinal tract and exert their beneficial effects. Whey powder enriched with milk fat globule membrane proteins (M-WPI) as a functional component is protective for strains under stress conditions. The current study investigated the key mechanisms of action involved in Lactobacillus plantarum (L. plantarum) CGMCC 23701 survival in the presence of bile and the protective mechanism of M-WPI. According to proteomic analysis (proteomics), there could be several reasons for the greater protective effect of M-WPI. These include promoting the synthesis of fatty acids and peptidoglycans to repair the structure of the cell surface, regulating the metabolism of carbohydrates and amino acids to release energy and produce a range of precursors, enabling the expression of the repair system to repair damaged DNA, and promoting the expression of proteins associated with the multidrug efflux pump, which facilitates the exocytosis of intracellular bile salts. This study helps us to better understand the changes in proteome of L. plantarum CGMCC 23701 under bile salt stress and M-WPI protection, which will provide a new method for the protection and development of functional LAB.

Large-scale soil application of hydrochar: Reducing its polycyclic aromatic hydrocarbon content and toxicity by heating.

The beneficial roles of hydrochar in carbon sequestration and soil improvement are widely accepted. Despite few available reports regarding polycyclic aromatic hydrocarbons (PAHs) generated during preparation, their potential negative impacts on ecosystems remain a concern. A heating treatment method was employed in this study for rapidly removing PAHs and reducing the toxicity of corn stover-based hydrochar (CHC). The result showed total PAHs content (∑PAH) decreased and then sharply increased within the temperature range from 150 °C to 400 °C. The ∑PAH and related toxicity in CHC decreased by more than 80% under 200 °C heating temperature, compared with those in the untreated sample, representing the lowest microbial toxicity. Benzo(a)pyrene produced a significant influence on the ecological toxicity of the hydrochar among the 16 types of PAHs. The impact of thermal treatment on the composition, content, and toxicity of PAHs was significantly influenced by the adsorption, migration, and desorption of PAHs within hydrochar pores, as well as the disintegration and aggregation of large molecular polymers. The combination of hydrochar with carbonized waste heat and exhaust gas collection could be a promising method to efficiently and affordably reduce hydrochar ecological toxicity.

In Silico Discovery of Stapled Peptide Inhibitor Targeting the Nur77-PPARγ Interaction and Its Anti-Breast-Cancer Efficacy.

The binding of peroxisome proliferator-activated receptor γ (PPARγ) to the orphan nuclear receptor Nur77 facilitates the ubiquitination and degradation of Nur77, and leads to aberrant fatty acid uptake for breast cancer progression. Because of its crucial role in clinical prognosis, the interaction between Nur77 and PPARγ is an attractive target for anti-breast-cancer therapy. However, developing an inhibitor of the Nur77-PPARγ interaction poses a technical challenge due to the absence of the crystal structure of PPARγ and its corresponding interactive model with Nur77. Here, ST-CY14, a stapled peptide, is identified as a potent modulator of Nur77 with a KD value of 3.247 × 10-8 M by in silico analysis, rational design, and structural modification. ST-CY14 effectively increases Nur77 protein levels by blocking the Nur77-PPARγ interaction, thereby inhibiting lipid metabolism in breast tumor cells. Notably, ST-CY14 significantly suppresses breast cancer growth and bone metastasis in mice. The findings demonstrate the feasibility of exploiting directly Nur77-PPARγ interaction in breast cancer, and generate what to the best knowledge is the first direct inhibitor of the Nur77-PPARγ interaction available for impeding fatty acid uptake and therapeutic development.

Desmoglein 2 and desmocollin 2 depletions promote malignancy through distinct mechanisms in triple-negative and luminal breast cancer.

BACKGROUND: Aberrant expressions of desmoglein 2 (Dsg2) and desmocollin 2(Dsc2), the two most widely distributed desmosomal cadherins, have been found to play various roles in cancer in a context-dependent manner. Their specific roles on breast cancer (BC) and the potential mechanisms remain unclear. METHODS: The expressions of Dsg2 and Dsc2 in human BC tissues and cell lines were assessed by using bioinformatics analysis, immunohistochemistry and western blotting assays. Wound-healing and Transwell assays were performed to evaluate the cells' migration and invasion abilities. Plate colony-forming and MTT assays were used to examine the cells' capacity of proliferation. Mechanically, Dsg2 and Dsc2 knockdown-induced malignant behaviors were elucidated using western blotting assay as well as three inhibitors including MK2206 for AKT, PD98059 for ERK, and XAV-939 for ß-catenin. RESULTS: We found reduced expressions of Dsg2 and Dsc2 in human BC tissues and cell lines compared to normal counterparts. Furthermore, shRNA-mediated downregulation of Dsg2 and Dsc2 could significantly enhance cell proliferation, migration and invasion in triple-negative MDA-MB-231 and luminal MCF-7 BC cells. Mechanistically, EGFR activity was decreased but downstream AKT and ERK pathways were both activated maybe through other activated protein tyrosine kinases in shDsg2 and shDsc2 MDA-MB-231 cells since protein tyrosine kinases are key drivers of triple-negative BC survival. Additionally, AKT inhibitor treatment displayed much stronger capacity to abolish shDsg2 and shDsc2 induced progression compared to ERK inhibition, which was due to feedback activation of AKT pathway induced by ERK inhibition. In contrast, all of EGFR, AKT and ERK activities were attenuated, whereas ß-catenin was accumulated in shDsg2 and shDsc2 MCF-7 cells. These results indicate that EGFR-targeted therapy is not a good choice for BC patients with low Dsg2 or Dsc2 expression. Comparatively, AKT inhibitors may be more helpful to triple-negative BC patients with low Dsg2 or Dsc2 expression, while therapies targeting ß-catenin can be considered for luminal BC patients with low Dsg2 or Dsc2 expression. CONCLUSION: Our finding demonstrate that single knockdown of Dsg2 or Dsc2 could promote proliferation, motility and invasion in triple-negative MDA-MB-231 and luminal MCF-7 cells. Nevertheless, the underlying mechanisms were cellular context-specific and distinct.

Laplacian Projection Based Global Physical Prior Smoke Reconstruction.

We present a novel framework for reconstructing fluid dynamics in real-life scenarios. Our approach leverages sparse view images and incorporates physical priors across long series of frames, resulting in reconstructed fluids with enhanced physical consistency. Unlike previous methods, we utilize a differentiable fluid simulator (DFS) and a differentiable renderer (DR) to exploit global physical priors, reducing reconstruction errors without the need for manual regularization coefficients. We introduce divergence-free Laplacian eigenfunctions (div-free LE) as velocity bases, improving computational efficiency and memory usage. By employing gradient-related strategies, we achieve better convergence and superior results. Extensive experiments demonstrate the effectiveness of our method, showcasing improved reconstruction quality and computational efficiency compared to existing approaches. We validate our approach using both synthetic and real data, highlighting its practical potential.

Using Voice Assistant Systems to Improve Dietary Recall among Older Adults: Perspectives of Registered Dietitians.

Dietary assessments are important clinical tools used by Registered Dietitians (RDs). Current methods pose barriers to accurately assess the nutritional intake of older adults due to age-related increases in risk for cognitive decline and more complex health histories. Our qualitative study explored whether implementing Voice assistant systems (VAS) could improve current dietary recall from the perspective of 20 RDs. RDs believed the implementing VAS in dietary assessments of older adults could potentially improve patient accuracy in reporting food intake, recalling portion sizes, and increasing patient-provider efficiency during clinic visits. RDs reported that low technology literacy in older adults could be a barrier to implementation. Our study provides a better understanding of how VAS can better meet the needs of both older adults and RDs in managing and assessing dietary intake.

Progress in RAS-targeted therapeutic strategies: From small molecule inhibitors to proteolysis targeting chimeras.

As a widely considerable target in chemical biology and pharmacological research, rat sarcoma (RAS) gene mutations play a critical driving factor in several fatal cancers. Despite the great progress of RAS subtype-specific inhibitors, rapid acquired drug resistance could limit their further clinical applications. Proteolysis targeting chimera (PROTAC) has emerged as a powerful tool to handle "undruggable" targets and exhibited significant therapeutic benefit for the combat of drug resistance. Owing to unique molecular mechanism and binding kinetics, PROTAC is expected to become a feasible strategy to break the bottleneck of classical RAS inhibitors. This review aims to discuss the current advances of RAS inhibitors and especially focus on PROTAC strategy targeting RAS mutations and their downstream effectors for relevant cancer treatment.

Enhancing Targeted Therapy in Hepatocellular Carcinoma through a pH-Responsive Delivery System: Folic Acid-Modified Polydopamine-Paclitaxel-Loaded Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Nanoparticles.

Currently, there is an inherent contradiction between the multifunctionality and excellent biocompatibility of anticancer drug nanocarriers, which limits their application. Therefore, to overcome this limitation, we aimed to develop a biocompatible drug delivery system for the treatment of hepatocellular carcinoma (HCC). In this study, we employed poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) as the fundamental framework of the nanocarrier and utilized the emulsion solvent evaporation method to fabricate nanoparticles loaded with paclitaxel (PTX), known as PTX-PHBV NPs. To enhance the tumor-targeting capability, a dopamine self-polymerization strategy was employed to form a pH-sensitive coating on the surface of the nanoparticles. Then, folic acid (FA)-targeting HCC was conjugated to the nanoparticles with a polydopamine (PDA) coating by using the Michael addition reaction, resulting in the formation of HCC-targeted nanoparticles (PTX-PHBV@PDA-FA NPs). The PTX-PHBV@PDA-FA NPs were characterized and analyzed by using dynamic light scattering, scanning electron microscopy, fourier-transform infrared spectroscopy, X-ray diffraction, differential scanning calorimetry, and thermogravimetric analysis. Encouragingly, PTX-PHBV@PDA-FA NPs exhibited remarkable anticancer efficacy in an HCC xenograft mouse model. Furthermore, compared to raw PTX, PTX-PHBV@PDA-FA NPs showed less toxicity in vivo. In conclusion, these results demonstrate the potential of PTX-PHBV@PDA-FA NPs for HCC treatment and biocompatibility.

Part-Aware Point Cloud Completion through Multi-Modal Part Segmentation.

Point cloud completion aims to generate high-resolution point clouds using incomplete point clouds as input and is the foundational task for many 3D visual applications. However, most existing methods suffer from issues related to rough localized structures. In this paper, we attribute these problems to the lack of attention to local details in the global optimization methods used for the task. Thus, we propose a new model, called PA-NET, to guide the network to pay more attention to local structures. Specifically, we first use textual embedding to assist in training a robust point assignment network, enabling the transformation of global optimization into the co-optimization of local and global aspects. Then, we design a novel plug-in module using the assignment network and introduce a new loss function to guide the network's attention towards local structures. Numerous experiments were conducted, and the quantitative results demonstrate that our method achieves novel performance on different datasets. Additionally, the visualization results show that our method efficiently resolves the issue of poor local structures in the generated point cloud.

Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising.

In many human-computer interaction applications, fast and accurate hand tracking is necessary for an immersive experience. However, raw hand motion data can be flawed due to issues such as joint occlusions and high-frequency noise, hindering the interaction. Using only current motion for interaction can lead to lag, so predicting future movement is crucial for a faster response. Our solution is the Multi-task Spatial-Temporal Graph Auto-Encoder (Multi-STGAE), a model that accurately denoises and predicts hand motion by exploiting the inter-dependency of both tasks. The model ensures a stable and accurate prediction through denoising while maintaining motion dynamics to avoid over-smoothed motion and alleviate time delays through prediction. A gate mechanism is integrated to prevent negative transfer between tasks and further boost multi-task performance. Multi-STGAE also includes a spatial-temporal graph autoencoder block, which models hand structures and motion coherence through graph convolutional networks, reducing noise while preserving hand physiology. Additionally, we design a novel hand partition strategy and hand bone loss to improve natural hand motion generation. We validate the effectiveness of our proposed method by contributing two large-scale datasets with a data corruption algorithm based on two benchmark datasets. To evaluate the natural characteristics of the denoised and predicted hand motion, we propose two structural metrics. Experimental results show that our method outperforms the state-of-the-art, showcasing how the multi-task framework enables mutual benefits between denoising and prediction.

Feasibility of using the Automated Self-Administered 24-hour (ASA-24) dietary assessment tool in older adults.

Background: Dietary patterns can impact the trajectories of healthy aging. However, dietary assessment tools can be challenging to use. With the increased use of technology in older adults, we aimed to evaluate the feasibility of older adults completing the online, Automated Self-Administered 24-h (ASA-24) dietary assessment tool. Methods: We conducted a randomized, two-period, two-sequence, crossover design of twenty community-dwelling older adults (≥65 years) comparing their preference for completing the ASA-24 alone versus with a research assistant (RA). Participants were recruited via ResearchMatch.com and randomly allocated 1:1 to a sequence of completing both an ASA-24 alone or with an RA, separated by one week. After each session, participants completed an online 11-item feasibility survey (Likert-scale range of 1-5, strongly disagree to strongly agree). Mean and standard deviations were reported for each question. Results: Mean age was 69 ± 3.5 years (90% females), with no differences were observed for sex, age, race, ethnicity, education, or income. Neither group felt a need for RA assistance (p = 0.34). However, both groups felt the system was easier to follow with the help of an RA (RA: 4.4 ± 1.3, vs. SA 4.6 ± 0.5, p = 0.65), particularly when they completed the ASA-24 alone, first (p = 0.04). When conducting the ASA-24 alone, there was less confidence the system could be learned quickly (SA 4.5 ± 0.5→3.4 ± 1.0 vs RA 3.4 ± 1.0→3.4 ± 0.7, p = 0.001). The ASA-24 was thought to be less cumbersome after repeated exposure in those concluding with the RA. Conclusion: While older adults were able to complete the ASA-24 independently, the use of an RA led to improved confidence. Enhancing the sample diversity in a larger number of participants could provide helpful data to improve the science of dietary assessment.

Physics-Based Differentiable Rendering for Efficient and Plausible Fluid Modeling from Monocular Video.

Realistic fluid models play an important role in computer graphics applications. However, efficiently reconstructing volumetric fluid flows from monocular videos remains challenging. In this work, we present a novel approach for reconstructing 3D flows from monocular inputs through a physics-based differentiable renderer coupled with joint density and velocity estimation. Our primary contributions include the proposed efficient differentiable rendering framework and improved coupled density and velocity estimation strategy. Rather than relying on automatic differentiation, we derive the differential form of the radiance transfer equation under single scattering. This allows the direct computation of the radiance gradient with respect to density, yielding higher efficiency compared to prior works. To improve temporal coherence in the reconstructed flows, subsequent fluid densities are estimated via a coupled strategy that enables smooth and realistic fluid motions suitable for applications that require high efficiency. Experiments on synthetic and real-world data demonstrated our method's capacity to reconstruct plausible volumetric flows with smooth dynamics efficiently. Comparisons to prior work on fluid motion reconstruction from monocular video revealed over 50-170x speedups across multiple resolutions.

An ultrasensitive method for detecting mutations from short and rare cell-free DNA.

Circulating tumor DNA (ctDNA) was short and rare, making the detection performance of the current targeted sequencing methods unsatisfying. We developed the One-PrimER Amplification (OPERA) system and examined its performance in detecting mutations of low variant allelic frequency (VAF) in various samples with short-sized DNA fragments. In cell line-derived samples containing sonication-sheared DNA fragments with 50-150 bp, OPERA was capable of detecting mutations as low as 0.0025% VAF, while CAPP-Seq only detected mutations of >0.03% VAF. Both single nucleotide variant and insertion/deletion can be detected by OPERA. In synthetic fragments as short as 80 bp with low VAF (0.03%-0.1%), the detection sensitivity of OPERA was significantly higher compared to that of droplet digital polymerase chain reaction. The error rate was 5.9×10-5 errors per base after de-duplication in plasma samples collected from healthy volunteers. By suppressing "single-strand errors", the error rate can be further lowered by >5 folds in EGFR T790M hotspot. In plasma samples collected from lung cancer patients, OPERA detected mutations in 57.1% stage I patients with 100% specificity and achieved a sensitivity of 30.0% in patients with tumor volume of less than 1 cm3. OPERA can effectively detect mutations in rare and highly-fragmented DNA.

Lightweight Co3O4/CC Composites with High Microwave Absorption Performance.

With the rapid development of electronic and communication technology for military radars, the demand for microwave-absorbing materials in the low-frequency range with thin layers is growing. In this study, flexible Co3O4/CC (carbon cloth) composites derived from Co-MOFs (metal-organic frameworks) and CC are prepared using hydrothermal and thermal treatment processes. The flexible precursors of the Co-MOFs/CC samples are calcined with different calcination temperatures, for which the material structure, dielectric properties, and microwave absorption performance are changed. With the increases in calcination temperature, the minimum reflection loss of the corresponding Co3O4/CC composites gradually moves to the lower frequency with a thinner thickness. In addition, the Co3O4/CC composites with the 25 wt% filler loading ratio exhibit the minimum reflection loss (RL) of -46.59 dB at 6.24 GHz with a 4.2 mm thickness. When the thickness is 3.70 mm, the effective absorption bandwidth is 3.04 GHz from 5.84 to 8.88 GHz. This study not only proves that the Co3O4/CC composite is an outstanding microwave-absorbing material with better flexibility but also provides useful inspiration for research on wideband microwave absorption materials below 10 GHz.

Rapid Identification of Pathogens in Severe Pneumonia by Species-specific Bacterial Detector (SSBD).

Fast and accurate detection of pathogenic bacterial infection in patients with severe pneumonia is significant to its treatment. The traditional culture method currently used by most medical institutions relies on a time-consuming culture process (over two days) that is unable to meet clinical needs. Rapid, accurate, and convenient species-specific bacterial detector (SSBD) has been developed to provide timely information on pathogenic bacteria. The SSBD was designed based on the fact that Cas12a indiscriminately cleaves any DNA following the binding of the crRNA-Cas12a complex to the target DNA molecule. SSBD involves two processes, starting with PCR of the target DNA using primers specific for the pathogen, followed by detection of the existence of pathogen target DNA in the PCR product using the corresponding crRNA and Cas12a protein. Compared to the culture test, the SSBD can obtain accurate pathogenic information in only a few hours, dramatically shortening the detection time and allowing more patients to benefit from timely clinical treatment.