A thermoresponsive nanocomposite integrates NIR-II-absorbing small molecule with lonidamine for pyroptosis-promoted synergistic immunotherapy

Photothermal immunotherapy is regarded as the ideal cancer therapeutic modality to against malignant solid tumors; however, its therapeutic benefits are often modest and require improvement. In this study, a thermoresponsive nanoparticle (BTN@LND) composed of a photothermal agent (PTA) and pyroptosis inducer (lonidamine) were developed to enhance immunotherapy applications. Specifically, our "two-step" donor engineering strategy produced the strong NIR-II-absorbing organic small-molecule PTA (BTN) that exhibited high NIR-II photothermal performance (ε1064 = 1.51 × 104 M-1 cm-1, η = 75.8%), and this facilitates the diagnosis and treatment of deep tumor tissue. Moreover, the fabricated thermally responsive lipid nanoplatform based on BTN efficiently delivered lonidamine to the tumor site and achieved spatiotemporal release triggered by the NIR-II photothermal effect. In vitro and in vivo experiments demonstrated that the NIR-II photothermal therapy (PTT)-mediated on-demand release of cargo effectively faciliated tumor cell pyroptosis, thereby intensifying the immunogenic cell death (ICD) process to promote antitumor immunotherapy. As a result, this intelligent component bearing photothermal and chemotherapy can maximally suppress the growth of tumors, thus providing a promising approach for pyroptosis/NIR-II PTT synergistic therapy against tumors.

Programmable, High-resolution Printing of Spatially Graded Perovskites for Multispectral Photodetectors

Micro/nanostructured perovskites with spatially graded compositions and bandgaps are promising in filter-free, chip-level multispectral, and hyperspectral detection. However, achieving high-resolution patterning of perovskites with controlled graded compositions is challenging. Here, a programmable mixed electrohydrodynamic printing (M-ePrinting) technique is presented to realize the one-step direct-printing of arbitrary spatially graded perovskite micro/nanopatterns for the first time. M-ePrinting enables in situ mixing and ejection of solutions with controlled composition/bandgap by programmatically varying driving voltage applied to a multichannel nozzle. Composition can be graded over a single dot, line or complex pattern, and the printed feature size is down to 1 µm, which is the highest printing resolution of graded patterns to the knowledge. Photodetectors based on micro/nanostructured perovskites with halide ions gradually varying from Br to I are constructed, which successfully achieve multispectral detection and full-color imaging, with a high detectivity and responsivity of 3.27 × 1015 Jones and 69.88 A W-1, respectively. The presented method provides a versatile and competitive approach for such miniaturized bandgap-tunable perovskite spectrometer platforms and artificial vision systems, and also opens new avenues for the digital fabrication of composition-programmable structures.

A computable biomedical knowledge system: Toward rapidly building candidate-directed acyclic graphs

AIM

It is essential for health researchers to have a systematic understanding of third-party variables that influence both the exposure and outcome under investigation, as shown by a directed acyclic graph (DAG). The traditional construction of DAGs through literature review and expert knowledge often needs to be more systematic and consistent, leading to potential biases. We try to introduce an automatic approach to building network linking variables of interest.

METHODS

Large-scale text mining from medical literature was utilized to construct a conceptual network based on the Semantic MEDLINE Database (SemMedDB). SemMedDB is a PubMed-scale repository of the "concept-relation-concept" triple format. Relations between concepts are categorized as Excitatory, Inhibitory, or General.

RESULTS

To facilitate the use of large-scale triple sets in SemMedDB, we have developed a computable biomedical knowledge (CBK) system (https://cbk.bjmu.edu.cn/), a website that enables direct retrieval of related publications and their corresponding triples without the necessity of writing SQL statements. Three case studies were elaborated to demonstrate the applications of the CBK system.

CONCLUSIONS

The CBK system is openly available and user-friendly for rapidly capturing a set of influencing factors for a phenotype and building candidate DAGs between exposure-outcome variables. It could be a valuable tool to reduce the exploration time in considering relationships between variables, and constructing a DAG. A reliable and standardized DAG could significantly improve the design and interpretation of observational health research.

The scaling of elemental stoichiometry and growth rate over the course of bamboo ontogeny

Stoichiometric rules may explain the allometric scaling among biological traits and body size, a fundamental law of nature. However, testing the scaling of elemental stoichiometry and growth to size over the course of plant ontogeny is challenging. Here, we used a fast-growing bamboo species to examine how the concentrations and contents of carbon (C), nitrogen (N) and phosphorus (P), relative growth rate (G), and nutrient productivity scale with whole-plant mass (M) at the culm elongation and maturation stages. The whole-plant C content vs M and N content vs P content scaled isometrically, and the N or P content vs M scaled as a general 3/4 power function across both growth stages. The scaling exponents of G vs M and N (and P) productivity in newly grown mass vs M relationships across the whole growth stages decreased as a -1 power function. These findings reveal the previously undocumented generality of stoichiometric allometries over the course of plant ontogeny and provide new insights for understanding the origin of ubiquitous quarter-power scaling laws in the biosphere.

Experimental Demonstration of Secure Relay in Quantum Secure Direct Communication Network

Quantum secure direct communication (QSDC) offers a practical way to realize a quantum network which can transmit information securely and reliably. Practical quantum networks are hindered by the unavailability of quantum relays. To overcome this limitation, a proposal has been made to transmit the messages encrypted with classical cryptography, such as post-quantum algorithms, between intermediate nodes of the network, where encrypted messages in quantum states are read out in classical bits, and sent to the next node using QSDC. In this paper, we report a real-time demonstration of a computationally secure relay for a quantum secure direct communication network. We have chosen CRYSTALS-KYBER which has been standardized by the National Institute of Standards and Technology to encrypt the messages for transmission of the QSDC system. The quantum bit error rate of the relay system is typically below the security threshold. Our relay can support a QSDC communication rate of 2.5 kb/s within a 4 ms time delay. The experimental demonstration shows the feasibility of constructing a large-scale quantum network in the near future.

Practical Real-Time Phase Drift Compensation Scheme for Quantum Communication Systems

Quantum communication systems are susceptible to various perturbations and drifts arising from the operational environment, with phase drift being a crucial challenge. In this paper, we propose an efficient real-time phase drift compensation scheme in which only existing data from the quantum communication process is used to establish a stable closed-loop control subsystem for phase tracking. This scheme ensures the continuous operation of transmission by tracking and compensating for phase drift in the phase-encoding quantum communication system. The experimental results demonstrate the effectiveness and feasibility of the proposed scheme with an average quantum bit error rate of 1.60% and a standard deviation of 0.0583% for 16 h of continuous operation.

Plant-based dietary patterns, genetic predisposition and risk of colorectal cancer: a prospective study from the UK Biobank

BACKGROUND

Plant-based dietary patterns may affect colorectal cancer (CRC) related outcomes, while risks differ in the quality of plant foods. We aimed to examine the association of plant-based diet quality with risks of CRC incidence and mortality and whether this association was modified by genetic risk.

METHODS

This prospective cohort study included 186,675 participants free of cancer when the last dietary recall was completed. We calculated three plant-based diet indices (PDIs), i.e., the overall plant-based diet index (PDI), the healthful plant-based diet index (hPDI), and the unhealthful plant-based diet index (uPDI) representing adherence to plant-based diets with diverse quality. Genetic risk was characterized using a weighted polygenic risk score (PRS), capturing overall risk variants associated with CRC. Hazard ratios (HR) and 95% confidential intervals (CI) were estimated by the cause-specific Cox proportional hazards model.

RESULTS

Over a follow-up of 9.5 years, 2163 cases and 466 deaths from CRC were documented. The HR of CRC incidence was 0.88 (95% CI, 0.81-0.96) and 0.91 (95% CI, 0.84-0.99) per 10-score increase in PDI and hPDI, respectively. Compared to the lowest quartile, PDI, hPDI, and uPDI in the highest quartile were associated with a 13% decrease, a 15% decrease, and a 14% increase in risk of incident CRC, respectively. We found a joint association of genetic risk and PDIs with incident CRC, with the highest hazard observed in those carrying higher PRS and adhering to lower-quality PDIs. The inverse association of PDI and hPDI with CRC mortality was pronounced in males.

CONCLUSIONS

Our results suggested that better adherence to overall and healthful plant-based diets was associated with a lower risk of CRC, whereas an unhealthful plant-based diet was associated with a higher CRC risk. Consumption of a higher-quality plant-based diet combined with decreased genetic risk conferred less susceptibility to CRC. Our findings highlighted the importance of food quality when adhering to a plant-based dietary pattern for CRC prevention in the general population.

Viscous-capillary entrainment on bioinspired millimetric structure for sustained liquid transfer

Liquid entrainment with a solid architecture passing through the fluid-fluid interface is ubiquitous and widely used in industrial processes as a liquid transfer method. Besides liquid properties, solid structures play a core role in entrainment. Although the influence of its macroscopic curvatures and microscale roughness has attracted years of research, the effect and potential of the commonly seen millimetric structures have not been sufficiently explored and exploited. Here, we demonstrate enhanced liquid entrainment on the millimetric structured surface by the co-effect of viscosity and capillarity for sustained liquid transfer of small deviation, including high-quantity uptake and practically operational drainage with small and relatively uniform droplet dripping time of varied liquid viscosities. With the overall process of viscous-capillary entrainment, we achieve stable cyclical arrayed liquid transport, showing its potential for sustained liquid transfer in intractable situations in laboratory, industry, and even daily life.

DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins

Allergies have become an emerging public health problem worldwide. The most effective way to prevent allergies is to find the causative allergen at the source and avoid re-exposure. However, most of the current computational methods used to identify allergens were based on homology or conventional machine learning methods, which were inefficient and still had room to be improved for the detection of allergens with low homology. In addition, few methods based on deep learning were reported, although deep learning has been successfully applied to several tasks in protein sequence analysis. In the present work, a deep neural network-based model, called DeepAlgPro, was proposed to identify allergens. We showed its great accuracy and applicability to large-scale forecasts by comparing it to other available tools. Additionally, we used ablation experiments to demonstrate the critical importance of the convolutional module in our model. Moreover, further analyses showed that epitope features contributed to model decision-making, thus improving the model's interpretability. Finally, we found that DeepAlgPro was capable of detecting potential new allergens. Overall, DeepAlgPro can serve as powerful software for identifying allergens.

Interfacial Regulation for 3D Printing based on Slice-Based Photopolymerization

3D printing, also known as additive manufacturing, can turn computer-aided designs into delicate structures directly and on demand by eliminating expensive molds, dies, or lithographic masks. Among the various technical forms, light-based 3D printing mainly involved the control of polymer-based matter fabrication and realized a field of manufacturing with high tunability of printing format, speed, and precision. Emerging slice- and light-based 3D-printing methods have prosperously advanced in recent years but still present challenges to the versatility of printing continuity, printing process, and printing details control. Herein, the field of slice- and light-based 3D printing is discussed and summarized from the view of interfacial regulation strategies to improve the printing continuity, printing process control, and the character of printed results, and several potential strategies to construct complex 3D structures of distinct characteristics with extra external fields, which are favorable for the further improvement and development of 3D printing, are proposed.

Prevalence of Diabetes in Patients with Hyperuricemia and Gout: A Systematic Review and Meta-analysis

PURPOSE OF REVIEW

To perform a systematic review and meta-analysis of the prevalence of diabetes in patients with hyperuricemia and gout.

RECENT FINDINGS

Previous studies have confirmed that hyperuricemia and gout are associated with an increased risk of diabetes. A previous meta-analysis indicated that the prevalence of diabetes in patients with gout is 16%. Thirty-eight studies (458,256 patients) were included in the meta-analysis. The combined prevalence of diabetes among patients with hyperuricemia and gout were 19.10% (95% confidence interval [CI]: 17.60-20.60; I² = 99.40%) and 16.70% (95% CI: 15.10-18.30; I² = 99.30%), respectively. Patients from North America showed a higher prevalence of diabetes (hyperuricemia: 20.70% [95% CI: 16.80-24.60], gout: 20.70% [95% CI: 16.80-24.60]) than those from other continents. Older patients with hyperuricemia and those using diuretics showed a higher prevalence of diabetes than younger patients and those who were not using diuretics. Studies with a small sample size, case-control design, and low quality score had a higher prevalence of diabetes than studies with a large sample size, other designs, and a high quality score. The prevalence of diabetes among patients with hyperuricemia and gout is high. Controlling plasma glucose and uric acid levels of patients with hyperuricemia and gout is critical for the prevention of diabetes.

[Effects of three medical nutrition therapies for weight loss on metabolic parameters and androgen level in overweight/obese patients with polycystic ovary syndrome]

Objective: To investigate the effects of calorie-restricted diet (CRD), high protein diet (HPD), high protein, and high dietary fiber diet (HPD+HDF) on metabolic parameters and androgen level in overweight/obese patients with polycystic ovary syndrome(PCOS). Methods: Ninety overweight/obese patients with PCOS from Peking University First Hospital from October 2018 to February 2020 were given medical nutrition weight loss therapy for 8 weeks and were randomly divided into CRD group, HPD group, and HPD+HDF group, with 30 patients in each group. Body composition, insulin resistance, and androgen level were detected before and after weight loss, and the efficacy of three weight loss therapies was compared through variance analysis and Kruskal-Wallis H test. Results: Eight patients in CRD group quit because they could not strictly complete the follow-up, therefore at the end of weight loss, 22, 30, and 30 patients in CRD group, HPD group and HPD+HDF group, respectively, were included in the final analysis. The baseline ages of the three groups were (31±2) years, (32±5) years and (31±5) years, respectively (P=0.952). After weight loss, the relevant indicators in HPD group and HPD+HDF group decreased more than those in CRD group. The body weight of CRD group, HPD group and HPD+HDF group decreased by 4.20 (11.92, 1.80), 5.00 (5.10, 3.32) and 6.10 (8.10, 3.07) kg, respectively (P=0.038); BMI of the three groups decreased by 0.80 (1.70, 0.40), 0.90 (1.23, 0.50) and 2.20 (3.30, 1.12) kg/m², respectively (P=0.002); homeostatic model assessment-insulin resistance(HOMA-IR) index decreased by 0.48(1.93, 0.05), 1.21(2.91, 0.18) and 1.22(1.75, 0.89), respectively (P=0.196); and free androgen index(FAI) decreased by 0.23(0.67, -0.04), 0.41(0.64, 0.30) and 0.44(0.63, 0.24), respectively (P=0.357). Conclusions: The three medical nutrition therapies can effectively reduce the weight of overweight/obese patients with PCOS, and improve insulin resistance and hyperandrogenism. Compared with CRD group, HPD group, and HPD+HDF group have better fat-reducing effect, and can better preserve muscle and basal metabolic rate while losing weight.

Characterization of Key Odorants in Lingtou Dancong Oolong Tea and Their Differences Induced by Environmental Conditions from Different Altitudes

Lingtou Dancong oolong tea is a famous Chinese oolong tea due to its special honey-like aroma. However, little is known about its specific aroma profile and key contributors. Furthermore, whether the aroma characteristics of Lingtou Dancong oolong tea are affected by the environmental conditions at different altitudes is unknown. In this study, the aromas in Lingtou Dancong oolong tea were extracted and analyzed by stir-bar sorptive extraction (SBSE) combined with gas chromatography-olfactometry (GC-O) and GC-mass spectrometry (GC-MS), and the aroma profiles of tea plants grown at different altitudes were compared. We detected 59 odor compounds in Lingtou Dancong oolong tea. Eight compounds with honey and floral odors were identified as key components on the basis of GC-O, GC-MS, odor activity value, and flavor dilution analyses. Differences in the contents of precursor geranyl diphosphate and transcript levels of structural genes were found to be responsible for the differential accumulation of linalool and hotrienol among plants grown at different altitudes. This is the first report on the aroma characteristics and key contributors of Lingtou Dancong oolong tea and their differences, as affected by altitude. These results provide details of the chemical basis of the aroma quality of Lingtou Dancong oolong tea.

A highly sensitive and selective nanosensor for near-infrared potassium imaging

Potassium ion (K⁺) concentration fluctuates in various biological processes. A number of K⁺ probes have been developed to monitor such fluctuations through optical imaging. However, the currently available K⁺ probes are far from being sensitive enough in detecting physiological fluctuations in living animals. Furthermore, the monitoring of deep tissues is not applicable because of short-wavelength excitation prevailingly used so far. Here, we report a highly sensitive and selective nanosensor for near-infrared (NIR) K⁺ imaging in living cells and animals. The nanosensor is constructed by encapsulating upconversion nanoparticles (UCNPs) and a commercial K⁺ indicator in the hollow cavity of mesoporous silica nanoparticles, followed by coating a K⁺-selective filter membrane. The membrane adsorbs K⁺ from the medium and filters out interfering cations. The UCNPs convert NIR to ultraviolet light, which excites the K⁺ indicator, thus allowing the detection of the fluctuations of K⁺ concentration in cultured cells and intact mouse brains.