Accelerating the Discovery of Anticancer Peptides through Deep Forest Architecture with Deep Graphical Representation.

Cancer is one of the leading diseases threatening human life and health worldwide. Peptide-based therapies have attracted much attention in recent years. Therefore, the precise prediction of anticancer peptides (ACPs) is crucial for discovering and designing novel cancer treatments. In this study, we proposed a novel machine learning framework (GRDF) that incorporates deep graphical representation and deep forest architecture for identifying ACPs. Specifically, GRDF extracts graphical features based on the physicochemical properties of peptides and integrates their evolutionary information along with binary profiles for constructing models. Moreover, we employ the deep forest algorithm, which adopts a layer-by-layer cascade architecture similar to deep neural networks, enabling excellent performance on small datasets but without complicated tuning of hyperparameters. The experiment shows GRDF exhibits state-of-the-art performance on two elaborate datasets (Set 1 and Set 2), achieving 77.12% accuracy and 77.54% F1-score on Set 1, as well as 94.10% accuracy and 94.15% F1-score on Set 2, exceeding existing ACP prediction methods. Our models exhibit greater robustness than the baseline algorithms commonly used for other sequence analysis tasks. In addition, GRDF is well-interpretable, enabling researchers to better understand the features of peptide sequences. The promising results demonstrate that GRDF is remarkably effective in identifying ACPs. Therefore, the framework presented in this study could assist researchers in facilitating the discovery of anticancer peptides and contribute to developing novel cancer treatments.

A Robust Drug-Target Interaction Prediction Framework with Capsule Network and Transfer Learning.

Drug-target interactions (DTIs) are considered a crucial component of drug design and drug discovery. To date, many computational methods were developed for drug-target interactions, but they are insufficiently informative for accurately predicting DTIs due to the lack of experimentally verified negative datasets, inaccurate molecular feature representation, and ineffective DTI classifiers. Therefore, we address the limitations of randomly selecting negative DTI data from unknown drug-target pairs by establishing two experimentally validated datasets and propose a capsule network-based framework called CapBM-DTI to capture hierarchical relationships of drugs and targets, which adopts pre-trained bidirectional encoder representations from transformers (BERT) for contextual sequence feature extraction from target proteins through transfer learning and the message-passing neural network (MPNN) for the 2-D graph feature extraction of compounds to accurately and robustly identify drug-target interactions. We compared the performance of CapBM-DTI with state-of-the-art methods using four experimentally validated DTI datasets of different sizes, including human (Homo sapiens) and worm (Caenorhabditis elegans) species datasets, as well as three subsets (new compounds, new proteins, and new pairs). Our results demonstrate that the proposed model achieved robust performance and powerful generalization ability in all experiments. The case study on treating COVID-19 demonstrates the applicability of the model in virtual screening.

Guidelines for Installation of Sensors in Smart Sensing Platforms in Underground Spaces.

The purpose of this study is to propose guidelines for sensor installation in different types of underground space smart sensing platforms. Firstly, we classify the underground space, analyze the scene requirements according to the classification of underground space, and sort out the requirements for sensors in various types of underground space. Secondly, according to the requirements of underground space scenes for sensors, the types of sensors and corresponding parameters are clarified. After that, the system design and sensor installation guidelines of the underground space smart sensing platform are proposed by sorting out the data acquired by the sensor.

Revealing the Immune Heterogeneity between Systemic Lupus Erythematosus and Rheumatoid Arthritis Based on Multi-Omics Data Analysis.

The pathogenesis of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are greatly influenced by different immune cells. Nowadays both T-cell receptor (TCR) and B-cell receptor (BCR) sequencing technology have emerged with the maturity of NGS technology. However, both SLE and RA peripheral blood TCR or BCR repertoire sequencing remains lacking because repertoire sequencing is an expensive assay and consumes valuable tissue samples. This study used computational methods TRUST4 to construct TCR repertoire and BCR repertoire from bulk RNA-seq data of both SLE and RA patients' peripheral blood and analyzed the clonality and diversity of the immune repertoire between the two diseases. Although the functions of immune cells have been studied, the mechanism is still complicated. Differentially expressed genes in each immune cell type and cell-cell interactions between immune cell clusters have not been covered. In this work, we clustered eight immune cell subsets from original scRNA-seq data and disentangled the characteristic alterations of cell subset proportion under both SLE and RA conditions. The cell-cell communication analysis tool CellChat was also utilized to analyze the influence of MIF family and GALECTIN family cytokines, which were reported to regulate SLE and RA, respectively. Our findings correspond to previous findings that MIF increases in the serum of SLE patients. This work proved that the presence of LGALS9, PTPRC and CD44 in platelets could serve as a clinical indicator of rheumatoid arthritis. Our findings comprehensively illustrate dynamic alterations in immune cells during pathogenesis of SLE and RA. This work identified specific V genes and J genes in TCR and BCR that could be used to expand our understanding of SLE and RA. These findings provide a new insight inti the diagnosis and treatment of the two autoimmune diseases.

Deep Learning-Enabled Label-Free On-Chip Detection and Selective Extraction of Cell Aggregate-Laden Hydrogel Microcapsules.

Microfluidic encapsulation of cells/tissues in hydrogel microcapsules has attracted tremendous attention in the burgeoning field of cell-based medicine. However, when encapsulating rare cells and tissues (e.g., pancreatic islets and ovarian follicles), the majority of the resultant hydrogel microcapsules are empty and should be excluded from the sample. Furthermore, the cell-laden hydrogel microcapsules are usually suspended in an oil phase after microfluidic generation, while the microencapsulated cells require an aqueous phase for further culture/transplantation and long-term suspension in oil may compromise the cells/tissues. Thus, real-time on-chip selective extraction of cell-laden hydrogel microcapsules from oil into aqueous phase is crucial to the further use of the microencapsulated cells/tissues. Contemporary extraction methods either require labeling of cells for their identification along with an expensive detection system or have a low extraction purity (<≈30%). Here, a deep learning-enabled approach for label-free detection and selective extraction of cell-laden microcapsules with high efficiency of detection (≈100%) and extraction (≈97%), high purity of extraction (≈90%), and high cell viability (>95%) is reported. The utilization of deep learning to dynamically analyze images in real time for label-free detection and on-chip selective extraction of cell-laden hydrogel microcapsules is unique and may be valuable to advance the emerging cell-based medicine.

Structured H∞ Control for Spacecraft with Flexible Appendages.

Spacecraft with large flexible appendages are characterized by multiple system modes. They suffer from inherent low-frequency disturbances in the operating environment that consequently result in considerable interference in the operational performance of the system. It is required that the control design ensures the system's high pointing precision, and it is also necessary to suppress low-frequency resonant interference as well as take into account multiple performance criteria such as attitude stability and bandwidth constraints. Aiming at the comprehensive control problem of this kind of flexible spacecraft, we propose a control strategy using a structured H-infinity controller with low complexity that was designed to meet the multiple performance requirements, so as to reduce the project cost and implementation difficulty. According to the specific resonant mode of the system, the design strategy of adding an internal mode controller, a trap filter, and a series PID controller to the structured controller is proposed, so as to achieve the comprehensive control goals through cooperative control of multiple control modules. A spacecraft with flexible appendages (solar array) is presented as an illustrative example in which a weighted function was designed for each performance requirement of the system (namely robustness, stability, bandwidth limit, etc.), and a structured comprehensive performance matrix with multiple performance weights and decoupled outputs was constructed. A structured H-infinity controller meeting the comprehensive performance requirements is given, which provides a structured integrated control method with low complexity for large flexible systems that is convenient for engineering practice, and provides a theoretical basis and reference examples for structured H-infinity control. The simulation results show that the proposed controller gives better control performance compared with the traditional H-infinity one, and can successfully suppress the vibration of large flexible appendages at 0.12 Hz and 0.66 Hz.

Cold-Responsive Nanoparticle Enables Intracellular Delivery and Rapid Release of Trehalose for Organic-Solvent-Free Cryopreservation.

Conventional cryopreservation of mammalian cells requires the use of toxic organic solvents (e.g., dimethyl sulfoxide) as cryoprotectants. Consequently, the cryopreserved cells must undergo a tedious washing procedure to remove the organic solvents for their further applications in cell-based medicine, and many of the precious cells may be lost or killed during the procedure. Trehalose has been explored as a nontoxic alternative to traditional cryoprotectants. However, mammalian cells do not synthesize trehalose or express trehalose transporters in their membranes, and the lack of an approach for the efficient intracellular delivery of trehalose has been a major hurdle for its use in cell cryopreservation. In this study, a cold-responsive polymer (poly(N-isopropylacrylamide-co-butyl acrylate)) is utilized to synthesize nanoparticles for the encapsulation and intracellular delivery of trehalose. The trehalose-laden nanoparticles can be efficiently taken up by mammalian cells. The nanoparticles quickly and irreversibly disassemble upon cold treatment, enabling the controlled and rapid release of trehalose from the nanoparticles inside cells. The latter is confirmed by an evident increase in cell volume upon cold treatment. This rapid cold-triggered intracellular release of trehalose is crucial to developing a fast protocol to cryopreserve cells using trehalose. Cells with intracellular trehalose delivered using the nanoparticles show comparable postcryopreservation viability compared to that of cells treated with DMSO, eliminating the need for the tedious and cell-damaging washing procedure required for using the DMSO-cryopreserved cells in vivo. This cold-responsive nanoparticle may greatly facilitate the use of trehalose as a nontoxic cryoprotectant for banking cells and tissues to meet their high demand by modern cell-based medicine.

Cold-Responsive Nanocapsules Enable the Sole-Cryoprotectant-Trehalose Cryopreservation of ß Cell-Laden Hydrogels for Diabetes Treatment.

Islet transplantation has been one promising strategy in diabetes treatment, which can maintain patient's insulin level long-term and avoid periodical insulin injections. However, donor shortage and temporal mismatch between donors and recipients has limited its widespread use. Therefore, searching for islet substitutes and developing efficient cryopreservation technology (providing potential islet bank for transplantation on demand) is in great need. Herein, a novel cryopreservation method is developed for islet ß cells by combining microfluidic encapsulation and cold-responsive nanocapsules (CR-NCs). The cryopreserved cell-laden hydrogels (calcium alginate hydrogel, CAH) can be transplanted for diabetes treatment. During the freezing process, trehalose is released inside ß cells through the CR-NCs and serves as the sole cryoprotectant (CPA). Additionally, CAH helps cells to survive the freeze-thaw process and provide cells with a natural immune barrier in vivo. Different from traditional cryopreservation methods, this method combining the CR-NCs and hydrogel encapsulation replaces the toxic CPAs with natural trehalose. Great preservation results are obtained and transplantation experiments of diabetic rats further prove the excellent glucose regulation ability of such ß cell-laden hydrogels post cryopreservation. This novel cryopreservation method helps to establish a reliable and ready-to-use bank of biological samples for transplantation therapy and other biomedical applications.

Evaluation of holographic imaging cytometer holomonitor M4® motility applications.

Digital holographic cytometry (DHC) and other methods of quantitative phase imaging permit extended time-lapse imaging of mammalian cells in the absence of induced cellular toxicity. Manufactured DHC platforms equipped with semi-automated image acquisition, segmentation, and analysis software packages (or modules) for assessing cell behavior are now commercially available. When housed in mammalian cell incubators these cytometers offer the potential to monitor and quantify a range of cellular behaviors without disrupting routine culture. Realization of this potential requires validation against established standards. Two proprietary software modules for assessing cellular motility available using the HoloMonitor M4 DHC platform were evaluated on human melanoma cells lines with known relative motility and metastatic potential. One such software package, the Track Cells module, was run during routine culture. In addition, the Wound Healing module was conducted in parallel with established transwell migration and invasion assays. Each module was evaluated for reproducibility and correlation to established assays. Both software modules reliably recorded increased cellular motility in the metastatic 1205Lu line as compared with the non-metastatic WM793 line. In a direct comparison of the two propriety DHC software modules and two established transwell assays, the relative cell motilities were well correlated. The granularity of data provided by the Track Cells module permitted the additional identification of rare hyper-motile cells in the metastatic population and the distinction of motility from division associated displacement. The two HoloMonitor M4 DHC proprietary software modules for assessing cellular motility yielded reproducible results that were well-correlated with established standards. © 2018 International Society for Advancement of Cytometry.

Simultaneous Measurements of Geometric and Viscoelastic Properties of Hydrogel Microbeads Using Continuous-Flow Microfluidics with Embedded Electrodes.

Geometric and mechanical characterizations of hydrogel materials at the microscale are attracting increasing attention due to their importance in tissue engineering, regenerative medicine, and drug delivery applications. Contemporary approaches for measuring the these properties of hydrogel microbeads suffer from low-throughput, complex system configuration, and measurement inaccuracy. In this work, a continuous-flow device is developed to measure geometric and viscoelastic properties of hydrogel microbeads by flowing the microbeads through a tapered microchannel with an array of interdigitated microelectrodes patterned underneath the channel. The viscoelastic properties are derived from the trajectories of microbeads using a quasi-linear viscoelastic model. The measurement is independent of the applied volumetric flow rate. The results show that the geometric and viscoelastic properties of Ca-alginate hydrogel microbeads can be determined independently and simultaneously. The bulky high-speed optical systems are eliminated, simplifying the system configuration and making it a truly miniaturized device. A throughput of up to 394 microbeads min-1 is achieved. This study may provide a powerful tool for mechanical profiling of hydrogel microbeads to support their wide applications.

Modeling and experimental studies of enhanced cooling by medical gauze for cell cryopreservation by vitrification.

Vitrification is considered as an important alternative approach to traditional slow freezing method for cryopreservation of cells. A typical cell vitrification procedure involves a non-equilibrium cooling process commonly accomplished in liquid nitrogen, while in which film boiling is believed to greatly hinder heat transfer surrounding the sample, resulting in incomplete vitrification or a much higher critical concentration. In this study, we developed a simple while effective approach, wrapping traditional French-type straw with medical gauze, to greatly enhance convective heat transfer during cooling by suppress film boiling. We further established a coupled heat transfer model for cooling and warming of cell suspensions to investigate the inherent thermodynamic mechanism in this approach. The model describes both the macroscale thermal distributions in extracellular solution and the microscale ice crystallization inside the cells. The simulation indicated that straws wrapped with medical gauze would increase cell survival subject to vitrification cryopreservation by significantly increasing the cooling rate to inhibit intracellular ice formation (IIF). Our experiments on human umbilical vein endothelial cells (HUVECs) further confirmed the predictions in that the cell survival rate was significantly increased by wrapping straws with medical gauze.

Some Physical Properties of Protein Moiety of Alkali-Extracted Tea Polysaccharide Conjugates Were Shielded by Its Polysaccharide.

Polysaccharide conjugates were alkali-extracted from green tea (TPC-A). Although it contained 11.80% covalently binding proteins, TPC-A could not bind to the Coomassie Brilliant Blue dyes G250 and R250. TPC-A had no expected characteristic absorption peak of protein in the UV-vis spectrum scanning in the range of 200-700 nm. The UV-vis wavelength of 280 nm was not suitable to detect the presence of the protein portion of TPC-A. The zeta potential of TPC-A merely presented the negative charge properties of polysaccharides instead of the acid-base property of its protein section across the entire pH range. Furthermore, TPC-A was more stable when the pH of solution exceeded 4.0. In addition, no precipitation or haze was generated in the TPC-A/(-)-epigallocatechin gallate (EGCG) mixtures during 12 h storage. TPC-A has emulsifying activity, which indicated that its protein moiety formed hydrophobic groups. Thus, it was proposed that some physical properties of TPC-A protein were shielded by its olysaccharide, since the protein moiety was wrapped by its polysaccharide chains.

Study on evolving phases of accelerating generalized polygon beams.

Recently, accelerating beam is becoming a hotspot in optics research. In this paper, we studied the evolving phases of accelerating generalized polygon beams (AGPBs) and proposed a novel method to generate this beam family. An important discovery has been made about reconstructing AGPBs only by evolving low-frequency phases in high power region, which confirms the dominant role of phase terms in the AGPBs' evolution. We also succeeded controlling the size and quantity of AGPB's intensity peaks in an easy and direct manner by manipulating the evolving phases in low frequency. This result not only explains the self-healing property of AGPBs but also confirms that AGPBs can be a great candidate to function as an optical tweezer to trap and free microparticles and microcreatures for certain purpose.

Measurement of Airy-vortex beam topological charges based on a pixelated micropolarizer array.

In this paper, we numerically studied the intensity patterns and screw phases of an embedded optical vortex in an Airy beam generated by a 3/2 phase pattern imposed on a spatial light modulator. It is found that the optical vortex and the Airy beam's main lobe approach each other during propagation, which means the energy of the Airy beam's intensity peaks can be taken advantage of by the imposed vortices. Based on a pixelated micropolarizer array in the interference path, we succeeded in measuring the integer topological charges up to -10 according to the phase jump. In addition, fractional topological charges were also obtained in the experiment. Both of the experimental results are acquired in a high-precision and robust way. This work will promote potential application of Airy-vortex beams in fields such as optical manipulation, laser processing, and photon entanglement.

Preventive Effects of Catechins on Cardiovascular Disease.

Catechins are polyphenolic phytochemicals with many important physiological activities that play a multifaceted health care function in the human body, especially in the prevention of cardiovascular disease. In this paper, various experimental and clinical studies have revealed the role of catechins in the prevention and treatment of cardiovascular disorders, and we review the preventive effects of catechins on cardiovascular disease from the following aspects: Regulating lipid metabolism, regulating blood lipid metabolism, vascular endothelial protection, and reducing blood pressure.

Real-time phase measurement of optical vortices based on pixelated micropolarizer array.

The special spiral phase structure of an optical vortex leads to an intriguing study in modern singular optics. This paper proposes a real-time phase measurement method of vortex beam based on pixelated micropolarizer array (PMA). Four phase-shifting fringe images can be obtained from a single interference image, thus the vortex beam phase can be obtained in real-time. The proposed method can achieve full-field phase measurement of the vortex beam with the advantages of lower computation and vibration resistance. In the experiments, the typical phases of vortex with different topological charges are loaded on a spatial light modulator (SLM) to generate diffraction vortex beam, and the phase distribution of vortex beam is obtained in real-time, which confirm the robustness of this method. This method is of great significance in promoting the study of optical vortices.

Effect of hydroxyapatite nanoparticles on osmotic responses of pig iliac endothelial cells.

In order to fully explore the potential applications of nanoparticles in biopreservation, it is necessary to study the effect of nanoparticles on cell membrane permeabilities. The aim of this study is therefore to comparatively evaluate the osmotic responses of pig iliac endothelial cells in the absence and presence of commercially available hydroxyapatite nanoparticles. The results indicate that, after the introduction of 0.0 1 wt% hydroxyapatite nanoparticles, the dependence of cell membrane hydraulic conductivity (Lp) on temperature still obeys the Arrhenius relationship, while the reference value of the hydraulic conductivity of the cell membrane at 273.15K (Lpg) and the activation energy for water transport across cell membrane (ELp) change from 0.77 × 10(-14)m/Pa/s and 15.65 kJ/mol to 0.65 × 10(-14)m/Pa/s and 26.14 kJ/mol. That is to say, the reference value of the hydraulic conductivity of the cell membrane has been slightly decreased while the activation energy for water transport across cell membrane has been greatly enhanced, and thus it implies that the hydraulic conductivity of cell membrane are more sensitive to temperature in the presence of nanoparticles. These findings are of potential significance to the optimization of nanoparticles-aided cryopreservation.

Effect of vascular network and nanoparticles on heat transfer and intracellular ice formation in tumor tissues during cryosurgery.

BACKGROUND: Cryosurgery is a physical therapy of tumor treatment which is welcome in clinics for its minimally invasive advantage. However, the high recurrence rate makes the conventional cryosurgery unsatisfactory, which needs adjuvant treatment such as introduction of nanoparticles. OBJECTIVE: This study is to examine the effects of vascular network and MgO nanoparticles on heat transfer and intracellular ice formation in tumor tissues during cryosurgery. METHOD: We developed a multi-scale model to study the efficiency of cryosurgery, including the macro-level (mass tumor tissue) heat transfer and the micro-level (tumor cells) probability of intracellular ice formation (PIF). The model is used to examine the effects of fractal vascular network (VN) and nanoparticles with different concentration on heat transfer and PIF during cryosurgery in the breast cancer tissue (MCF-7 cells). The nucleation rate kinetic parameter and the thermodynamic parameter of MCF-7 cells are determined by nonlinear curve-fitting the published experimental data, and then the probability of intracellular ice formation of the picked points in the tumor tissue are determined using the classic model for intracellular ice nucleation with the simulated thermal profiles at those points during cryosurgery. RESULTS AND CONCLUSION: The introduction of nanoparticles have significantly enhanced the heat transfer in the mass tumor tissue and increased the PIF of tumor cells, indicating the nanocryosurgery is more efficient than conventional cryosurgery.