Functionalized Single Crystal Perovskite Materials for SERS and Their Potential Detection Applications.

Recent advances in detection and diagnostic tools have improved understanding and identification of plant physiological and biochemical processes. Effective and safe Surface Enhanced Raman Spectroscopy (SERS) can find objects quickly and accurately. Raman enhancement amplifies the signal by 1014-1015 to accurately quantify plant metabolites at the molecular level. This paper shows how to use functionalized perovskite substrates for SERS. These perovskite substrates have lots of surface area, intense Raman scattering, and high sensitivity and specificity. These properties eliminate sample matrix component interference. This study identified research gaps on perovskite substrates' effectiveness, precision, and efficiency in biological metabolite detection compared to conventional substrates. This article details the synthesis and use of functionalized perovskites for plant metabolites measurement. It analyzes their pros and cons in this context. The manuscript analyzes perovskite-based SERS substrates, including single-crystalline perovskites with enhanced optoelectronic properties. This manuscript aims to identify this study gap by comprehensively reviewing the literature and using it to investigate plant metabolite detection in future studies.

Correlation between the cardiometabolic index and arteriosclerosis in patients with type 2 diabetes mellitus.

BACKGROUND: The cardiometabolic index (CMI) is a new metric derived from the triglyceride-glucose index and body mass index and is considered a potential marker for cardiovascular risk assessment. This study aimed to examine the correlation between the CMI and the presence and severity of arteriosclerosis in patients with type 2 diabetes mellitus (T2DM). METHODS: This study involved 2243 patients with T2DM. The CMI was derived by dividing the triglyceride level (mmol/L) by the high-density lipoprotein level (mmol/L) and then multiplying the quotient by the waist-to-height ratio. Multivariate logistic regression was used to analyze the correlations between the CMI and BMI blood biomarkers, blood pressure, and brachial-ankle pulse wave velocity (baPWV). RESULTS: Patients were categorized into three groups based on their CMI: Group C1 (CMI < 0.775; n = 750), Group C2 (CMI: 0.775-1.355; n = 743), and Group C3 (CMI > 1.355; n = 750). Increased BMI, fasting glucose, insulin (at 120 min), total cholesterol (TC), and baPWV values were observed in Groups C2 and C3, with statistically significant trends (all trends P < 0.05). The CMI was positively correlated with systolic blood pressure (r = 0.74, P < 0.001). Multivariate analysis revealed that an increased CMI contributed to a greater risk for arteriosclerosis (OR = 1.87, 95%CI: 1.66-2.10, P < 0.001). Compared to the C1 group, the C2 group and C3 group had a greater risk of developing arteriosclerosis, with ORs of 4.55 (95%CI: 3.57-5.81, P<0.001) and 5.56 (95%CI: 4.32-7.17, P<0.001), respectively. The association was notably stronger in patients with a BMI below 21.62 kg/m² than in those with a BMI of 21.62 kg/m² or higher (OR = 4.53 vs. OR = 1.59). CONCLUSIONS: These findings suggest that the CMI is a relevant and independent marker of arteriosclerosis in patients with T2DM and may be useful in the risk stratification and management of these patients.

GUGA-based MRCI approach with core-valence separation approximation (CVS) for the calculation of the core-excited states of molecules.

We develop and demonstrate how to use the Graphical Unitary Group Approach (GUGA)-based MRCISD with Core-Valence Separation (CVS) approximation to compute the core-excited states. First, perform a normal Self-Consistent-Field (SCF) or valence MCSCF calculation to optimize the molecular orbitals. Second, rotate the optimized target core orbitals and append to the active space, form an extended CVS active space, and perform a CVS-MCSCF calculation for core-excited states. Finally, construct the CVS-MRCISD expansion space and perform a CVS-MRCISD calculation to optimize the CI coefficients based on the variational method. The CVS approximation with GUGA-based methods can be implemented by flexible truncation of the Distinct Row Table. Eliminating the valence-excited configurations from the CVS-MRCISD expansion space can prevent variational collapse in the Davidson iteration diagonalization. The accuracy of the CVS-MRCISD scheme was investigated for excitation energies and compared with that of the CVS-MCSCF and CVS-CASPT2 methods using the same active space. The results show that CVS-MRCISD is capable of reproducing well-matched vertical core excitation energies that are consistent with experiments by combining large basis sets and a rational reference space. The calculation results also highlight the fact that the dynamic correlation between electrons makes an undeniable contribution in core-excited states.

Salinization of groundwater in shale gas extraction area in the Sichuan Basin, China: Implications for water protection in shale regions with well-developed faults.

The expanding growth of shale gas development has sparked global concern over water-related environmental issues. However, research on groundwater contamination in shale gas areas in China remains limited, impeding environmentally friendly industry practices. To address this gap, we investigated the Wufeng-Longmaxi shale region in the Sichuan Basin, encompassing both operational and prospective shale gas extraction sites, to assess the effects of shale gas operations on shallow groundwater quality. We found there was no significant correlation between groundwater quality and the minimum distance from the shale gas well pads, and some groundwater samples located far from shale gas well pads, rather than those close to pads, were salinized. These findings suggest minimal impacts from shale gas drilling and hydraulic fracturing. The salinized groundwater samples are characterized by high salinity levels and ion concentrations, and are located near fault zones. The primary source of shallow groundwater salinization was derived from the Triassic formation brines confirmed through the assessment of the sensitivity and conservative mixing models. Faults in the study area were identified as pathways for the upward migration of Triassic brines, evidenced by the proximity of salinized samples to fault zones. However, further investigation is required to ascertain whether shale gas extraction activities have induced the migration of formation brines. The occurrence and reactivation of faults, induced by microseismic activities, may pose an increased risk of groundwater contamination in tectonically complex fault zones during shale gas extraction. Therefore, it is imperative to enhance extraction strategies and technologies, particularly in shale regions with well-developed faults, such as optimizing well placement regulation, controlling hydraulic fracturing scale, and strengthening environmental monitoring. By shedding light on potential environmental ramifications of shale gas extraction, especially in fault-rich regions, our study informs water protection strategies and the sustainable advancement of the shale gas industry.

Effects of polyethylene, polylactic acid, and tire particles on the sediment microbiome and metabolome at high and low temperatures.

Global warming has led to a high incidence of extreme heat events, and the frequent occurrence of extreme heat events has had extensive and far-reaching impacts on wetland ecosystems. The widespread distribution of plastics in the environment, including polyethylene (PE), polylactic acid (PLA), and tire particles (TPs), has caused various environmental problems. Here, high-throughput sequencing techniques and metabolomics were used for the first time to investigate the effects of three popular microplastic types: PE, PLA, and TP, on the sediment microbiome and the metabolome at both temperatures. The microplastics were incorporated into the sediment at a concentration of 3% by weight of the dry sediment (wt/wt), to reflect environmentally relevant conditions. Sediment enzymatic activity and physicochemical properties were co-regulated by both temperatures and microplastics producing significant differences compared to controls. PE and PLA particles inhibited bacterial diversity at low temperatures and promoted bacterial diversity at high temperatures, and TP particles promoted both at both temperatures. For bacterial richness, only PLA showed inhibition at low temperature; all other treatments showed promotion. PE, PLA, and TP microplastics changed the community structure of sediment bacteria, forming two clusters at low and high temperatures. Furthermore, PE, PLA, and TP changed the sediment metabolic profiles, producing differential metabolites such as lipids and molecules, organic heterocyclic compounds, and organic acids and their derivatives, especially TP had the most significant effect. These findings contribute to a more comprehensive understanding of the potential impact of microplastic contamination.IMPORTANCEIn this study, we added 3% (wt/wt) microplastic particles, including polyethylene, polylactic acid, and tire particles, to natural sediments under simulated laboratory conditions. Subsequently, we simulated the sediment microbial and ecosystem responses under different temperature conditions by incubating them for 60 days at 15°C and 35°C, respectively. After synthesizing these results, our study strongly suggests that the presence of microplastics in sediment ecosystems and exposure under different temperature conditions may have profound effects on soil microbial communities, enzyme activities, and metabolite profiles. This is important for understanding the potential hazards of microplastic contamination on terrestrial ecosystems and for developing relevant environmental management strategies.

Temperature-dependent effects of microplastics on sediment bacteriome and metabolome.

The increasing prevalence of microplastics in the environment has become a concern for various ecosystems, including wetland ecosystems. Here, we investigated the effects of three popular microplastic types: polyethylene, polylactic acid, and tire particles at 5 °C and 25 °C on the sediment microbiome and metabolome at the 3% (w/w) level. Results indicated that temperature greatly influenced catalase and neutral phosphatase activities, whereas the type of microplastic had a more significant impact on urease and dehydrogenase activities. The addition of microplastic, especially tire particles, increased microbial diversity and significantly altered the microbial community structure and metabolic profile, leading to the formation of different clusters of microbial communities depending on the temperature. Nonetheless, the effect of temperature on the metabolite composition was less significant. Functional prediction showed that the abundance of functional genes related to metabolism and biogeochemical cycling increased with increasing temperature, especially the tire particles treatment group affected the nitrogen cycling by inhibiting ureolysis and nitrogen fixation. These observations emphasize the need to consider microplastic type and ambient temperature to fully understand the ecological impact of microplastics on microbial ecosystems.

Novel Operation Mechanism and Multifunctional Applications of Bubble Microrobots.

Microrobots have emerged as powerful tools for manipulating particles, cells, and assembling biological tissue structures at the microscale. However, achieving precise and flexible operation of arbitrary-shaped microstructures in 3D space remains a challenge. In this study, three novel operation methods based on bubble microrobots are proposed to enable delicate and multifunctional manipulation of various microstructures. These methods include 3D turnover, fixed-point rotation, and 3D ejection. By harnessing the combined principles of the effect of the heat flow field and surface tension of an optothermally generated bubble, the bubble microrobot can perform tasks such as flipping an SIA humanoid structure, rotating a bird-like structure, and launching a hollow rocket-like structure. The proposed multi-mode operation of bubble microrobots enables diverse attitude adjustments of microstructures with different sizes and shapes in both 2D and 3D spaces. As a demonstration, a biological microenvironment of brain glioblastoma is constructed by the bubble microrobot. The simplicity, versatility, and flexibility of this proposed method hold great promise for applications in micromanipulation, assembly, and tissue engineering.

Dual-Responsive Nanorobot-Based Marsupial Robotic System for Intracranial Cross-Scale Targeting Drug Delivery.

Nanorobots capable of active movement are an exciting technology for targeted therapeutic intervention. However, the extensive motion range and hindrance of the blood-brain barrier impeded their clinical translation in glioblastoma therapy. Here, a marsupial robotic system constructed by integrating chemical/magnetic hybrid nanorobots (child robots) with a miniature magnetic continuum robot (mother robot) for intracranial cross-scale targeting drug delivery is reported. For primary targeting on macroscale, the continuum robot enters the cranial cavity through a minimally invasive channel (e.g., Ommaya device) in the skull and transports the nanorobots to pathogenic regions. Upon circumventing the blood-brain barrier, the released nanorobots perform secondary targeting on microscale to further enhance the spatial resolution of drug delivery. In vitro experiments against primary glioblastoma cells derived from different patients are conducted for personalized treatment guidance. The operation feasibility within organisms is shown in ex vivo swine brain experiments. The biosafety of the treatment system is suggested in in vivo experiments. Owing to the hierarchical targeting method, the targeting rate, targeting accuracy, and treatment efficacy have improved greatly. The marsupial robotic system offers a novel intracranial local therapeutic strategy and constitutes a key milestone in the development of glioblastoma treatment platforms.

Effect of in situ ultrasonic wave and influent ammonia nitrogen fluctuation on stability of aerobic granular sludge.

This study elucidates the impact of fluctuating influent conditions and in situ ultrasonic wave exposure on the stability of aerobic granular sludge (AGS) in the treatment of simulated wastewater emanating from rare earth mining operations. During a stable influent period spanning from Day 1 to Day 95, the seed granules underwent an initial disintegration followed by a re-granulation phase. The secondary granulation was achieved on Day 80 and Day 40 for the ultrasonic reactor (R1) and the control reactor (R2), respectively. Notably, granules formed in R1 exhibited a more porous structure compared to those generated in R2. Subsequently, when the ammonia nitrogen in the influent oscillated between 100 and 500 mg/L during Days 96-140, both reactors yielded compact and densely structured granules. Nitrogen removal profiles were comparable between the two reactors: the removal efficiencies for ammonia nitrogen and total inorganic nitrogen escalated from 95% and 80%, respectively, during Days 1-95, to 95% and 90%, respectively, post-Day 140. A suite of performance metrics indicated that steady-state granules from R1 outperformed those from R2 across several parameters. Specifically, the nitrification/denitrification rates, and relative abundance of denitrifying bacteria were all higher in granules from R1. Conversely, the relative abundance of nitrifying bacteria was comparable between granules from both reactors. However, R1 granules demonstrated lower sludge concentration and smaller average particle size than their R2 counterparts. In conclusion, the AGS system demonstrated robust resilience to fluctuating ammonia nitrogen, and the application of ultrasonic waves significantly enhanced granular activity while achieving in situ sludge reduction.

Catheter-Assisted Bioinspired Adhesive Magnetic Soft Millirobot for Drug Delivery.

Soft millirobots have evolved into various therapeutic applications in the medical field, including for vascular dredging, cell transportation, and drug delivery, owing to adaptability to their surroundings. However, most soft millirobots cannot quickly enter, retrieve, and maintain operations in their original locations after removing the external actuation field. This study introduces a soft magnetic millirobot for targeted medicine delivery that can be transported into the body through a catheter and anchored to the tissues. The millirobot has a bilayer adhesive body with a mussel-inspired hydrogel layer and an octopus-inspired magnetic structural layer. It completes entry and retrieval with the assistance of a medical catheter based on the difference between the adhesion of the hydrogel layer in air and water. The millirobot can operate in multiple modes of motion under external magnetic fields and underwater tissue adhesion after self-unfolding with the structural layer. The adaptability and recyclability of the millirobots are demonstrated using a stomach model. Combined with ultrasound (US) imaging, operational feasibility within organisms is shown in isolated small intestines. In addition, a highly efficient targeted drug delivery is confirmed using a fluorescence imaging system. Therefore, the proposed soft magnetic millirobots have significant potential for medical applications.

Temporal and spatial dynamic changes of planktonic bacteria community structure in Li River, China: a seasonal survey.

A combined temporal and spatial research approach helps us to evaluate the ecological status of a river scientifically and comprehensively. To understand the response mechanisms of bacteria in the Li River to different environments, we conducted a 1-year study (2020-2021) and collected water samples from 18 sections of the river in October, January, April, and August. 16S sequencing was used to study the composition and structure of bacterial communities in Li River at different temporal and spatial scales. The results showed that NO3--N, TP, T, pH, and DO were significantly different on spatial and temporal scales. Alpha diversity of planktonic bacteria in Li River fluctuated significantly with the season, reaching its highest in summer. Proteobacteria remained the most dominant phylum in all seasons, but the differential microorganisms varied between seasons. Although the abundance of metabolic functions of planktonic bacteria did not show significant differences between seasons, we found that DO, TP, T, and COD were the key environmental factors affecting bacterial metabolism. In addition, the co-occurrence network analysis showed that the autumn network had a higher number of nodes and edges and exhibited a high degree of complexity, while the summer network had the highest degree of modularity and exhibited greater stability. These results deepen our knowledge of the response mechanisms of river microorganisms to temporal and spatial changes and provide a scientific reference for the study of river ecosystems.

Surfactant and antibiotic co-occurrence reshaped the acidogenic process for volatile fatty acids production during sludge anaerobic fermentation.

The overuse of surfactants and antibiotics has led to their high concentration in waste activated sludge (WAS), and these exogenous pollutants have been shown to pose various influences on the subsequent anaerobic treatment process. Previous works have primarily concerned the impacts of individual pollutants on WAS anaerobic fermentation process. This work revealed the synergetic effects of sodium dodecyl benzene sulfonate (SDBS) and sulfadiazine (SDZ) co-occurrence in WAS on the biosynthesis of volatile fatty acids (VFAs). The addition of SDBS in the SDZ reactor significantly increased VFAs generation, and this increase was correlated with the concentration of SDZ. The VFAs production exhibited a 200.0-211.9 % and 5.9-20.4 % increase in comparison with the sole SDZ and SDBS reactor, respectively. The SDBS and SDZ co-occurrence facilitated the solubilization, hydrolysis, and acidification stages of WAS fermentation synchronously. SDBS was effectively to disintegrate the cemented structure of extracellular polymeric substances and meanwhile improve the SDZ solubilization, which increase the SDZ bioavailability as well as biotoxicity to the anaerobic species. Herein, the anaerobic consortia structure was evidently reshaped, and the keystone microbes Acetoanaerobium and Fususibacter, as well-tolerated hydrolytic-acidogenic bacteria, were greatly enriched. Furthermore, the functional microbial metabolic traits responsible for the substrate extracellular hydrolysis (e.g., glsA and MAN2C1), intracellular metabolism (e.g., ALDO and asdA), and fatty acid generation (e.g., aarC) were all upregulated in the SDBS/SDZ co-occurrence reactor.

A deep learning-enabled smartphone platform for rapid and sensitive colorimetric detection of dimethoate pesticide.

A novel deep learning-enabled smartphone platform is developed to assist a colorimetric aptamer biosensor for fast and highly sensitive detection of dimethoate. The colorimetric determination of dimethoate is based on the specific binding of dimethoate and aptamer, which leads to the aggregation of AuNPs in high-concentration NaCl solution, resulting in an obvious color change from red to blue. This color change provides sufficient data for self-learning enabled by a convolutional neural network (CNN) model, which is established to predict dimethoate concentration based on images acquired from a smartphone. To enhance user-friendliness for non-experts, the CNN model is then embedded into a smartphone app, enabling offline detection of dimethoate pesticide in real environments within just 15 min using a pre-configured colorimetric probe. The developed platform exhibits superior performance, achieving a regression coefficient of 0.9992 in the concentration range of 0-10 µM. Moreover, the app's performance is found to be consistent with the ELISA kit. These remarkable findings demonstrate the potential of combining colorimetric biosensors with smartphone-based deep learning methods for the development of portable and affordable tools for pesticide detection.

GraphTS: Graph-represented time series for subsequence anomaly detection.

Automatic detection of subsequence anomalies (i.e., an abnormal waveform denoted by a sequence of data points) in time series is critical in a wide variety of domains. However, most existing methods for subsequence anomaly detection often require knowing the length and the total number of anomalies in time series. Some methods fail to capture recurrent subsequence anomalies due to using only local or neighborhood information for anomaly detection. To address these limitations, in this paper, we propose a novel graph-represented time series (GraphTS) method for discovering subsequence anomalies. In GraphTS, we provide a new concept of time series graph representation model, which represents both recurrent and rare patterns in a time series. Particularly, in GraphTS, we develop a new 2D time series visualization (2Dviz) method, which compacts all 1D time series patterns into a 2D spatial temporal space. The 2Dviz method transfers time series patterns into a higher-resolution plot for easier sequence anomaly recognition (or detecting subsequence anomalies). Then, a Graph is constructed based on the 2D spatial temporal space of time series to capture recurrent and rare subsequence patterns effectively. The represented Graph also can be used to discover single and recurrent subsequence anomalies with arbitrary lengths. Experimental results demonstrate that the proposed method outperforms the state-of-the-art methods in terms of accuracy and efficiency.

Electroacupuncture at ST36 acupoint regulates stem cells during experimental autoimmune encephalomyelitis.

BACKGROUND: Electroacupuncture (EA) is given to assist in the treatment of MS, which is an effective therapeutic method. However, the therapy mechanism of EA related to stem cells in the treatment of MS is not yet known. In this study, we used a classic animal model of multiple sclerosis: experimental autoimmune encephalomyelitis (EAE) to evaluate the therapeutic effect of EA at Zusanli (ST36) acupoint in EAE and shed light on its potential roles in the effects of stem cells in vivo. METHODS: The EAE animal models were established. From the first day after immunization, EAE model mice received EA at ST36 acupoint, named the EA group. The weight and clinical score of the three groups were recorded for 28 days. The demyelination, inflammatory cell infiltration, and markers of neural stem cells (NSCs), hematopoietic stem cells (HSCs), and mesenchymal stem cells (MSCs) were compared. RESULTS: We showed that EAE mice treated with EA at ST36 acupoint, were suppressed in demyelination and inflammatory cell infiltration, and thus decreased clinical score and weight loss and mitigated the development of EAE when compared with the EAE group. Moreover, our data revealed that the proportions of NSCs, HSCs, and MSCs increased in the EA group compared with the EAE group. CONCLUSIONS: Our study suggested that EA at ST36 acupoint was an effective nonpharmacological therapeutic protocol that not only reduced the CNS demyelination and inflammatory cell infiltration in EAE disease but also increased the proportions of various stem cells. Further study is necessary to better understand how EA at the ST36 acupoint affects EAE.

Stability of aerobic granular sludge for treating inorganic wastewater with different nitrogen loading rates.

This paper investigated the effect of nitrogen loading rates (NLRs) on the stability of aerobic granular sludge (AGS) for treating simulated ionic rare earth mine wastewater with high ammonia nitrogen and extremely low organic content. Mature AGS from a sequencing batch reactor (SBR) was seeded into five identical SBRs (R1, R2, R3, R4 and R5). The five reactors were operated with different NLRs (0.2, 0.4, 0.8, 1.2 and 1.6 kg/m3·d). After 30 days of operation, R1, R2 and R5 were dominated by broken granules, while most of the granules in R3 and R4 still maintained a complete structure. The properties of granules from R1, R2, R3, R4 and R5 deteriorated to varying degrees, while the granules from R3 and R4 showed better stability than that from R1, R2 and R5. In R1, R2, R3 and R4, the steady-state ammonia nitrogen removal efficiencies were all greater than 90%, and the steady-state removal efficiencies of total inorganic nitrogen (TIN) were approximately 30%. In R5, the removal efficiencies of ammonia nitrogen and TIN were both approximately 70%. The dominant nitrifying and denitrifying bacterial genera of the granules from the five reactors were Nitrosomonas and Thauera, respectively, and their relative abundance was much higher in granules from R3 and R4. The results demonstrated that a relative equilibrium between the growth and metabolism of nitrifying/denitrifying bacteria was achieved when NLR was between 0.8 and 1.2 kg/m3·d, which could provide technical support for the stability maintenance of AGS in the treatment of ionic rare earth mine wastewater.

Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis.

Objective: By screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells. Methods: Using GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959. Then, we obtained the corresponding differentially expressed genes by analyzed 5 gene chips online by GEO2R (P < 0.05, |logFC| > 1). Then, through DAVID online platform, Cytoscape 3.6.1 software and PPI network analysis, the network was visualized and obtain the final core genes. Next, we plan to use the GEPIA, UALCAN, Kaplan-Meier plotter and Time 2.0 database for corresponding analysis. The GEPIA database was used to verify the expression of core genes in LUAD and normal lung tissues, and survival analysis was used to evaluate the value of core genes in the prognosis of LUAD patients. UALCAN was used to verify the expression of the LUAD core gene and promoter methylation status, and the predictive value of core genes was evaluated in LUAD patients by the Kaplan-Meier plotter online tool. Then, we used the Time 2.0 database to identify the relationship to immune infiltration in LUAD. Finally, we used the human protein atlas (HPA) database for online immunohistochemical analysis of the expressed proteins. Results: The expression of CCNB2 and CDC20 in LUAD were higher than those in normal lung tissues, their increased expression was negatively correlated with the overall survival rate of LUAD, and they were involved in cell cycle signal transduction, oocyte meiosis signal transduction as well as the infiltration process of immune cells in LUAD. The expression proteins of CCNB2 and CDC20 were also different in lung cancer tissue and normal lung tissue. Therefore, CCNB2 and CDC20 were identified as the vital core genes. Conclusion: CCNB2 and CDC20 are essential genes that may constitute prognostic biomarkers in LUAD, they also participate the immune infiltration process and protein expression process of LUAD, and might provides basis for clinical anti-tumor drug research.

A Multiple-Medical-Image Encryption Method Based on SHA-256 and DNA Encoding.

Ensuring the privacy and secrecy of digital medical images has become a pressing issue as a result of the quick development of smart medical technology and the exponential growth in the quantity of medical images transmitted and stored in networks. The lightweight multiple-image encryption approach for medical images that is suggested in this research can encrypt/decrypt any number of medical photos of varied sizes with just one encryption operation and has a computational cost that is similar to encrypting a single image. The plaintext images with different sizes are filled at the right and bottom of the image to ensure that the size of all plaintext images is uniform; then, all the filled images are stacked to obtain a superimposed image. The initial key, which is generated using the SHA-256 technique, is then used as the starting value of the linear congruence algorithm to create the encryption key sequence. The cipher picture is then created by encrypting the superimposed image with the encryption key and DNA encoding. The algorithm can be made even more secure by implementing a decryption mechanism that decrypts the image independently in order to reduce the possibility of information leaking during the decryption process. The outcomes of the simulation experiment demonstrate the algorithm's strong security and resistance to interference such as noise pollution and lost image content.

Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication.

Cell mechanics is essential to cell development and function, and its dynamics evolution reflects the physiological state of cells. Here, we investigate the dynamical mechanical properties of single cells under various drug conditions, and present two mathematical approaches to quantitatively characterizing the cell physiological state. It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate, and can be mathematically characterized by a linear time-invariant dynamical model. It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions. Furthermore, it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties, and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model. This study builds a relationship between the cellular mechanical properties and the cellular physiological state, adding information for evaluating drug efficacy.