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Deep learning models can accurately predict molecular properties and help making the search for potential drug candidates faster and more efficient. Many existing methods are purely data driven, focusing on exploiting the intrinsic topology and construction rules of molecules without any chemical prior information. The high data dependency makes them difficult to generalize to a wider chemical space and leads to a lack of interpretability of predictions. Here, to address this issue, we introduce a chemical element-oriented knowledge graph to summarize the basic knowledge of elements and their closely related functional groups. We further propose a method for knowledge graph-enhanced molecular contrastive learning with functional prompt (KANO), exploiting external fundamental domain knowledge in both pre-training and fine-tuning. Specifically, with element-oriented knowledge graph as a prior, we first design an element-guided graph augmentation in contrastive-based pre-training to explore microscopic atomic associations without violating molecular semantics. Then, we learn functional prompts in fine-tuning to evoke the downstream task-related knowledge acquired by the pre-trained model. Extensive experiments show that KANO outperforms state-of-the-art baselines on 14 molecular property prediction datasets and provides chemically sound explanations for its predictions. This work contributes to more efficient drug design by offering a high-quality knowledge prior, interpretable molecular representation and superior prediction performance.

Interactions between the microbiota and their colonized environments mediate critical pathways from biogeochemical cycles to homeostasis in human health. Here we report a soil-inspired chemical system that consists of nanostructured minerals, starch granules and liquid metals. Fabricated via a bottom-up synthesis, the soil-inspired chemical system can enable chemical redistribution and modulation of microbial communities. We characterize the composite, confirming its structural similarity to the soil, with three-dimensional X-ray fluorescence and ptychographic tomography and electron microscopy imaging. We also demonstrate that post-synthetic modifications formed by laser irradiation led to chemical heterogeneities from the atomic to the macroscopic level. The soil-inspired material possesses chemical, optical and mechanical responsiveness to yield write-erase functions in electrical performance. The composite can also enhance microbial culture/biofilm growth and biofuel production in vitro. Finally, we show that the soil-inspired system enriches gut bacteria diversity, rectifies tetracycline-induced gut microbiome dysbiosis and ameliorates dextran sulfate sodium-induced rodent colitis symptoms within in vivo rodent models.

Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative method to identify spatially variable cell subpopulations by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We benchmark scSpace with both simulated and biological datasets, and demonstrate that scSpace can accurately and robustly identify spatially variated cell subpopulations. When employed to reconstruct the spatial architectures of complex tissue such as the brain cortex, the small intestinal villus, the liver lobule, the kidney, the embryonic heart, and others, scSpace shows promising performance on revealing the pairwise cellular spatial association within single-cell data. The application of scSpace in melanoma and COVID-19 exhibits a broad prospect in the discovery of spatial therapeutic markers.

A two-dimensional phononic crystal sensor model with high-quality factor and excellent sensitivity for sensing acetone solutions and operating at 25–45 kHz is proposed. The model for filling solution cavities is based on reference designs of quasi-crystal and gradient cavity structures. The transmission spectrum of sensor is simulated by the finite element method. High-quality factor of 45,793.06 and sensitivity of 80,166.67 Hz are obtained for the acetone concentration with 1–9.1%, and quality factor of 61,438.09 and sensitivity of 24,400.00 Hz are obtained for the acetone concentration range of 10–100%, which indicated the sensor could still achieve high sensitivity and quality factor at operating frequencies from 25 to 45 kHz. To verify the application of the sensor to sensing other solutions, the sensitivity for sound velocity and density is calculated as 24.61 m-1 and 0.7764 m3/(kg × s), respectively. It indicates the sensor is sensitive to acoustic impedance changes of the solution and equally suitable for sensing other solutions. The simulation results reveal the phononic crystal sensor possessed high-performance in composition capture in pharmaceutical production and petrochemical industry, which can provide theoretical reference for the design of new biochemical sensors for reliable detection of solution concentration.

Background A significant proportion of women with preeclampsia (PE) exhibit persistent postpartum hypertension (PHTN) at 3 months postpartum associated with cardiovascular morbidity. This study aimed to screen patients with PE to identify the high-risk population with persistent PHTN. Methods This retrospective cohort study enrolled 1,000 PE patients with complete parturient and postpartum blood pressure (BP) profiles at 3 months postpartum. The enrolled patients exhibited new-onset hypertension after 20 weeks of pregnancy, while those with PE superimposed upon chronic hypertension were excluded. Latent class cluster analysis (LCCA), a method of unsupervised learning in machine learning, was performed to ascertain maternal exposure clusters from eight variables and 35 subordinate risk factors. Logistic regression was applied to calculate odds ratios (OR) indicating the association between clusters and PHTN. Results The 1,000 participants were classified into three exposure clusters (subpopulations with similar characteristics) according to persistent PHTN development: high-risk cluster (31.2%), medium-risk cluster (36.8%), and low-risk cluster (32.0%). Among the 1,000 PE patients, a total of 134 (13.4%) were diagnosed with persistent PHTN, while the percentages of persistent PHTN were24.68%, 10.05%, and 6.25% in the high-, medium-, and low-risk clusters, respectively. Persistent PHTN in the high-risk cluster was nearly five times higher (OR, 4.915; 95% confidence interval (CI), 2.92–8.27) and three times (OR, 2.931; 95% CI, 1.91–4.49) than in the low- and medium-risk clusters, respectively. Persistent PHTN did not differ between the medium- and low-risk clusters. Subjects in the high-risk cluster were older and showed higher BP, poorer prenatal organ function, more adverse pregnancy events, and greater medication requirement than the other two groups. Conclusion Patients with PE can be classified into high-, medium-, and low-risk clusters according to persistent PHTN severity; each cluster has cognizable clinical features. This study’s findings stress the importance of controlling persistent PHTN to prevent future cardiovascular disease.

Motivated by the existing circuit model of quantum convolutional neural network, a new quantum convolutional neural network circuit model is devised, which is combined with quantum chaotic map to construct a symmetric cryptosystem. Quantum chaotic map produces key stream for encryption and decryption. The cryptosystem simulates the basic process of communication. Theoretical analysis manifests that the cryptosystem is effective. Additionally, simulation experiments based on MNIST data set show that the cryptosystem is secure. Furthermore, the proposed cryptosystem can be applied not only for image data, but for text data. Therefore, the grid data can be encrypted by utilizing the cryptosystem.

Introduction The human JC polyomavirus (JCPyV) has been detected in colorectal cancer (CRC) tissues and is suggested to contribute to CRC tumorigenesis. The rearrangement of the JCPyV regulatory region is supposedly associated with CRC development. The progression of CRC involves the stepwise accumulation of mutations. The large tumor antigen (LT) of JCPyV can trigger uncontrolled cell cycle progression by targeting oncogenes, and tumor suppressor genes, and causing chromosome instability. Few studies have focused on the presence of JCPyV DNA in the higher grade of CRC tissues. Methods We collected 95 tissue blocks from samples of stages I, II, III, and IV CRC. Nested PCR targeting the regulatory region of the viral genome was performed to determine the presence of JCPyV DNA in the various stages of colorectal cancer tissues. Results The nested PCR results showed that the positive rate of JCPyV DNA increased with the progression of CRC stages. The archetypal-like, non-rearrangement genotype of JCPyV with subtle mutations was the major genotype found in CRC samples. Conclusions This finding in our study suggests that there may be an association between JCPyV and CRC progression.

Real-world bioelectronics applications, including drug delivery systems, biosensing, and electrical modulation of tissues and organs, largely require biointerfaces at the macroscopic level. However, traditional macroscale bioelectronic electrodes usually exhibit invasive or power-inefficient architectures, inability to form uniform and subcellular interfaces, or faradaic reactions at electrode surfaces. Here, we develop a micelle-enabled self-assembly approach for a binder-free and carbon-based monolithic device, aimed at large-scale bioelectronic interfaces. The device incorporates a multiscale porous material architecture, an interdigitated microelectrode layout, and a supercapacitor-like performance. In cell training processes, we use the device to modulate the contraction rate of primary cardiomyocytes at the subcellular level to target frequency in vitro. We also achieve capacitive control of the electrophysiology in isolated hearts, retinal tissues, and sciatic nerves, as well as bioelectronic cardiac sensing. Our results support the exploration of device platforms already used in energy research to identify new opportunities in bioelectronics.

Taiwan has witnessed a surge in the incidence of colorectal cancer (CRC), of which 40–60% metastasize. Continuous updating of cytoreductive strategies in metastatic CRC (mCRC) has contributed to median overall survival reaching 40 months. In this changing scenario, to standardize the approaches across Taiwan, a group of experts from the Taiwan Society of Colon and Rectal Surgeons (TSCRS) convened to establish evidence- and opinion-based recommendations for defining the criteria of “resectability” in mCRC. Over the course of one-on-one consultations, lasting 30–40 min each, with 30 medical specialists (19 colorectal surgeons, 4 general surgeons, and 7 medical oncologists) from 16 hospitals in Taiwan followed by a 2-h meeting with 8 physician experts (3 general surgeons, 4 colorectal surgeons, and 1 thoracic surgeon), 12 key questions on cytoreduction were addressed. This was further contextualized based on published literature. The final consensus includes eight recommendations regarding the criteria for metastasis resection, role of local control treatment in liver potentially resectable patients, management of synchronous liver metastases, approach for peritoneal metastasis, place for resection in multiple-organ metastasis, and general criteria for resectability. mCRC patients undergoing R0 resection have the greatest survival advantage following surgery. Our role as a multidisciplinary team (MDT) should be to treat potentially resectable mCRC patients as rapidly and safely as possible, and achieve R0 resection as far as possible and for as long as possible (continuum of care). This TSCRS consensus statement aims to help build clinical capacity within the MDTs, while making better use of existing healthcare resources.

The Sanchi oil tanker collision in the East China Sea on January 6th, 2018 has caused worldwide attention due to its uniqueness. A considerable amount of highly volatile natural-gas condensate oil was spilled, burned and sank with the Sanchi tanker, this entirely new kind of maritime disaster has posed massive unknowns to the public. In this study, for better understanding of the evaporative behavior of condensate oils, two condensate oils were investigated under various laboratory conditions. The overall result demonstrates that the evaporation of condensate oils is highly dependent on the air-exposed time and the total loss of condensate oils could be more than 90% within a short time. However, a certain amount of the high-molecular weight and toxic oil contents such as phenanthrenes still highly remain in the aquatic system even after a long evaporation process, indicating their detrimental potentials to the aquatic organisms. Based on these data, for the Sanchi oil spill accident, it is assumed that although the evaporation weathering of the total condensate oil mass is probably tremendous, the long-term ecological risks of the remaining oil components in the marine environment are strongly recommended to be carefully evaluated.

This study investigated the effect of environmental physical factors on the relative abundance of bacteria and the consequential landscape evolution in karst topography, focusing mainly on the effects of ureolytic microbial CaCO3 precipitation. The narrow-sky located in the upper part of Tangshan is a small gulch of Pleistocene coralline limestone formation in southern Taiwan. A 16S-metagenomic approach was used to determine the relationship of microbial community structures on the landscapes in various habitats. Our results showed that the biomass of habitats in the opening of the gulch was two times higher than the inside where light penetration was lower. We also found that speleothems only occurred at the inner wall inside the gulch, where the environment exhibited water drips running through the surface of speleothems and less light penetration. The sequence reads of operational taxonomic units relative to urease-producing bacteria and weathering-associated bacteria from each habitat were determined by NCBI database. Our data revealed that the 16S-metagenomics of the inner wall and water samples exhibited more sequences that were similar to those of urease-producing bacteria, whereas the outer wall showed more sequences that were similar to those of weathering-associated bacteria, suggesting that bacteria facilitated the formation of limestone weathering and calcite precipitation for various habitats. The semi-quantitative PCR for determining bacterial urease gene (ureC) levels confirmed that the inner limestone habitat had higher ureC gene levels than the outer limestone habitat. This study revealed the pivotal role of microorganisms in governing the geological evolution in the lightless limestone landscape.

This paper attempts to shed empirical light on one of the oldest debates in the literature on infrastructure—whether infrastructure capital contributes to aggregate output in the long run, and related to that, whether investing in infrastructure is an effective tool to promote regional development. Drawing from a panel data set of 29 Chinese provinces over the period 1985–2012, it constructs a synthetic infrastructure index and employs panel time series techniques. The findings suggest that infrastructure is, on average, a strong determinant of economic growth and that there are provincial differences in the marginal productivity of infrastructure due probably to differences in the relative shortage or overprovision of infrastructure stocks. Therefore, policy makers should use infrastructure investment as a means of boosting output or promoting regional development only to the extent that it does not lead to oversupply of infrastructure.

Silicon-based materials have been widely used. However, remotely controlled and interconnect-free silicon configurations have been rarely explored, because of limited fundamental understanding of the complex physicochemical processes that occur at interfaces between silicon and biological materials. Here, we describe rational design principles, guided by biology, for establishing intracellular, intercellular and extracellular silicon-based interfaces, where the silicon and the biological targets have matched properties. We focused on light-induced processes at these interfaces, and developed a set of matrices to quantify and differentiate the capacitive, Faradaic and thermal outputs from about 30 different silicon materials in saline. We show that these interfaces are useful for the light-controlled non-genetic modulation of intracellular calcium dynamics, of cytoskeletal structures and transport, of cellular excitability, of neurotransmitter release from brain slices, and of brain activity in vivo.

Three-dimensional nanowire transistors with curvilinear tips record intracellular signals from neurons.

The aim of this paper is to propose the concept of the interval-valued least square prenucleolus of interval-valued cooperative games and develop a direct and an effective simplified method for solving a special subclass of interval-valued cooperative games. In this method, through adding some conditions, the least square prenucleolus of cooperative games is proved to be a monotonic and non-decreasing function of coalitions’ values. Hence, the interval-valued least square prenucleolus of coalition size monotonicity-like interval-valued cooperative games can directly obtained via determining its lower and upper bounds by using the lower and upper bounds of the interval-valued coalitions’ payoffs, respectively. Thus, the proposed method may overcome the issues resulted from the Moore’s interval subtraction and the partial subtraction operator. Examples are used to illustrate the proposed method and comparison analysis is conducted to show its applicability and superiority. Moreover, some important properties of the interval-valued least square prenucleolus of coalition size monotonicity-like interval-valued cooperative games are discussed.

Background The anti-tumor activities of Natural compounds and their derivatives are of great interest to pharmaceutical industries. Fisetin is one of prospective natural compounds in this regard but unfortunately with poor hydrophilicity. Methods The effects of unmodified and modified fisetin in cultured ovarian cancer cells were compared by transmission electronmicroscopy to determine apoptotic bodies, MTT assay to quantitate cell numbers, and fluorescence activated cell sorting analyse of various markers to determine the apoptotic state. In addition, the efficacy of fisetin and fisetin-micelles in vivo was determined by using immunocompromised mice. Apoptosis was measured by established markers using both western blot analysis and immunochemistry. Angiogenesis in a xenograft mouse model carring SKOV3 cells was evaluated by color Doppler ultrasound and immunohistochemistry. Result Multiple lines of evidence indicated that fisetin and fisetin micelles induce apoptosis in ovarian cancer cells in a dose-dependent manner. Histological analysis, terminal deoxynucleotidyltransferase-mediated nick-end labeling assay, western blot, immunohistochemical detection and microvessel density detection demonstrated that fisetin and fisetin micelles induced increased tumor apoptosis, proliferation suppression and antiangiogenesis activities. Conclusion As far as we know, the present study is the first time to demonstrate the potency of both fisetin and fisetin micelles inducing apoptosis in ovarian cancer cells. Further studies will be needed to validate the therapeutic potential of fisetin and fisetin micelles in ovarian cancer treatment.