Multifunctional pressure and humidity sensor modulated by electrostatic interactions and hydrogen bonds for wearable health monitoring.

Breathing and urination, are vital physiological activities of the human body, continuous real-time monitoring of these physiological behaviors could offer timely feedback on an individual's health status. However, current monitoring techniques predominantly rely on cumbersome and intricate medical apparatuses, posing challenges in adapting to the diverse requirements of multi-scenario detection. Consequently, there is a growing interest in developing wearable devices capable of monitoring breathing and urination. In this work, we developed a multifunctional sensor integrating humidity and pressure sensing modes using a simple dip-coating process. By introducing sodium carboxymethyl cellulose and conductive polyaniline hybrid intercalation between MXene layers, a stable conductive network is established through hydrogen bonds and electrostatic interactions among materials. The overall electromechanical properties of the composites will be well improved. And, the effects of different conductive filler ratios and the number of dipping times on the construction of conductive networks are investigated. The multifunctional sensor exhibited improved sensing characteristics, including detecting pressures up to 532 kPa and a sensitivity of 19.58 kPa-1. Furthermore, it also demonstrates good humidity-sensing capabilities. Tests on volunteers demonstrated the potential in the detection of breathing and urination. In addition, the sensors are capable of transmitting Morse code. This interesting application will offer the possibility of normal communication for people with speech impairments. Given its utility and sustainability, the sensor has potential for applications in wearable health monitoring, intelligent life and telemedicine.

Wearable Applicability of Respiratory Airflow Transducers: Current Approaches and Future Directions.

Advanced technologies employed in modern respiratory airflow transducers have exhibited powerful capabilities in accurately measuring respiratory flow under controlled and sedentary conditions, particularly in clinical settings. However, the wearable applicability of these transducers as face-mounted electronics for use in occupational and sporting activities remains unexplored. The present review addresses the critical wearability issue associated with current respiratory airflow transducers, including pneumotachographs, orifice flowmeters, turbine flowmeters, hot wire anemometers, ultrasound flowmeters, and piezoelectric airflow transducers. Furthermore, a comprehensive analysis and comparison of all factors that impact the wearable applicability of respiratory airflow transducers are conducted, considering dynamic accuracy, long-term usability, power consumption, calibration frequency, and cleaning requirements. The findings indicate that the piezoelectric airflow transducer stands out as a more viable option for wearables compared to other devices. We expect that this review will serve as a valuable engineering reference, guiding future research efforts in designing and developing wearable respiratory airflow transducers for ambulatory respiratory flow monitoring.

Double-camouflaged tellurium nanoparticles for enhanced photothermal immunotherapy of tumor.

The photothermal conversion properties of tellurium (Te) nanoparticles have been extensively investigated, rendering them a promising candidate for tumor photothermal therapy. However, there is still room for improvement in the development of efficient Te-based drug delivery systems. Here, Te nanoparticles are mineralized with bioactive molecules within attenuated Salmonella (S-Te), which are subsequently taken up by macrophages (RAW264.7) to construct a double-camouflaged delivery platform (RS-Te). Remarkably, RS-Te retains superior photothermal properties under near-infrared irradiation. The mineralization process eliminates bacterial proliferation potential, thereby mitigating the risk of excessive bacterial growth in vivo. Furthermore, the uptake of bacteria by macrophages not only polarizes them into M1 macrophages to induce an anti-tumor immune response but also circumvents any adverse effects caused by complex antigens on the bacterial surface. The results show that RS-Te can effectively accumulate and retain in tumors. RS-Te-mediated photothermal immunotherapy largely promotes the maturation of dendritic cells and priming of cytotoxic T cells induced by near-infrared laser irradiation. Moreover, RS-Te can switch the activation of macrophages from an immunosuppressive M2 phenotype to a more inflammatory M1 state. The double-camouflaged delivery system may offer highly efficient and safe cancer treatment.

A Bio-Inspired Magnetic Soft Robotic Fish for Efficient Solar-Energy Driven Water Purification.

Solar-driven water evaporation is a promising solution for global water scarcity but is still facing challenges due to its substantial energy requirements. Here, a magnetic soft robotic bionic fish is developed by combining magnetic nanoparticles (Fe3O4), poly(N-isopropylacrylamide), and carboxymethyl chitosan. This bionic fish can release liquid water through hydrophilic/hydrophobic phase transition and dramatically reduce energy consumption. The introduced Fe3O4 nanoparticles endow the bionic fish with magnetic actuation capability, allowing for remote operation and recovery. Additionally, the magnetic actuation process accelerates the water absorption rate of the bionic fish as confirmed by the finite element simulations. The results demonstrate that bionic fish can effectively remove not only organic molecular dyes dissolved in water but also harmful microbes and insoluble microparticles from natural lakes. Moreover, the bionic fish maintains a good purification efficiency even after five recycling cycles. Furthermore, the bionic fish possesses other functions, such as salt purification and salt rejection. Finally, the mechanism of water purification is explained in conjunction with molecular dynamics calculations. This work provides a new approach for efficient solar-energy water purification by phase transition behavior in soft robotics.

Radiocatalytic ammonia synthesis from nitrogen and water.

The development of alternative methods to the Haber-Bosch process for ammonia (NH3) synthesis is a pressing and formidable challenge. Nuclear energy represents a low-carbon, efficient and stable source of power. The harnessing of nuclear energy to drive nitrogen (N2) reduction not only allows 'green' NH3 synthesis, but also offers the potential for the storage of nuclear energy as a readily transportable zero-carbon fuel. Herein, we explore radiocatalytic N2 fixation to NH3 induced by γ-ray radiation. Hydrated electrons (e- aq) that are generated from water radiolysis enable N2 reduction to produce NH3. Ru-based catalysts synthesized by using γ-ray radiation with excellent radiation stability substantially improve NH3 production in which the B5 sites of Ru particles may play an important role in the activation of N2. By benefitting from the remarkable penetrating power of γ-ray radiation, radiocatalytic NH3 synthesis can proceed in an autoclave under appropriate pressure conditions, resulting in an NH3 concentration of ≤5.1 mM. The energy conversion efficiency of the reaction is as high as 563.7 mgNH3·MJ-1. This radiocatalytic chemistry broadens the research scope of catalytic N2 fixation while offering promising opportunities for converting nuclear energy into chemical energy.

The Pb capture mechanism of soil prophylactic agents prepared from phosphorus tailings and the influence of phosphorus speciation on its slow-release mechanism.

This research activated phosphorus tailings to prepare a high­phosphorus core (HPC) for multi-species composite slow-release heavy metal soil prophylactic agents (MCP), aiming to extend the slow-release period of MCP and enhance the efficiency of Pb stabilization. During the preparation of HPC, the proportion of non-apatitic inorganic phosphorus (NAIP) and apatite phosphorus (AP) continuously decreased with increasing polymerization temperature. At 400 °C, polyphosphates (PP) began to form, reaching 74.26 % at 600 °C. Initially, the rapidly soluble NAIP remained the major component of HPC, but the proportion of AP increased with higher polymerization temperatures, reaching 40.8 % at 600 °C. After 120 days of cultivation with four MCPs (MCP 300-21, MCP 400-12, MCP 500-14, MCP 600-14), the total soil phosphorus (TSP), soil organic matter (SOM), and Pb stabilization capacity of the cultivated soil showed significant improvements, reaching maximum values of 2.39 mg/g, 38.16 mg/g, and 45.4 mg/g, respectively, which are 9.9, 4.4, and 5.9 times higher than those of the CK soil. KEGG (Kyoto Encyclopedia of Genes and Genomes) functional prediction analysis indicated that MCPs contribute directly or indirectly to the forms and chemical stability of Pb by stimulating soil physiological and biochemical processes. This research proposes a novel approach for using phosphates in soil heavy metal management strategies and provides new insights into the mechanisms of heavy metal stabilization in soil using environmental functional materials.

2-Ethylhexyl diphenyl phosphate aggravates colitis-induced neuroinflammation and behavioral abnormalities by inhibiting the PI3K-AKT-NF-κB and Wnt/GSK3ß signaling pathways.

2-Ethylhexyl diphenyl phosphate (EHDPHP), a widely used organophosphorus flame retardant (OPFR), is ubiquitous in daily life because of its extensive application in plastic production. EHDPHPs, which are only superficially applied and not chemically bonded to products, are released into the environment, posing potential health risks. With increasing environmental concentrations, EHDPHP is a growing threat, particularly to individuals with preexisting health conditions who are more susceptible to environmental pollutants. This study examined the effects of EHDPHP exposure in a colitis model, reflecting a rising chronic health issue, by assessing changes in neuroinflammation and neurobehavioral abnormalities. Healthy and dextran sulfate sodium (DSS)-induced colitis C57BL/6 J mice were treated with either 0.2 % Tween or EHDPHP solution (10 mg/kg body weight/day) for 28 days. The study revealed significant increases in the serum and expression levels of TNFα and IL-1ß, accompanied by depressive and anxiety-like behaviors. Coexposure to EHDPHP and DSS exacerbated these neurobehavioral impairments. RNA sequencing confirmed that EHDPHP triggered inflammation via the PI3K-Akt-NF-κB and Wnt/GSK3ß signaling pathways, as confirmed by Western blot analysis. These findings suggest that EHDPHP aggravates colitis-induced neuroinflammation and neurobehavioral abnormalities, highlighting the harmful impact of EHDPHP, particularly in individuals with preexisting inflammatory conditions.

Engineering Steep Subthreshold Swings in High-Performance Organic Field-Effect Transistor Sensors.

Organic field-effect transistor (OFET)-based sensors have gained considerable attention for information perception and processing in developing artificial intelligent systems owing to their amplification function and multiterminal regulation. Over the last few decades, extensive research has been conducted on developing OFETs with steep subthreshold swings (SS) to achieve high-performance sensing. In this review, based on an analysis of the critical factors that are unfavorable for a steep SS in OFETs, the corresponding representative strategies for achieving steep SS are summarized, and the advantages and limitations of these strategies are comprehensively discussed. Furthermore, a bridge between SS and OFET sensor performance is established. Subsequently, the applications of OFETs with steep SS in sensor systems, including pressure sensors, photosensors, biochemical sensors, and electrophysiological signal sensors. Lastly, the challenges faced in developing OFET sensors with steep SS are discussed. This study provides insights into the design and application of high-performance OFET sensor systems.

Osteoprotective effect of Achyranthes bidentata root extract on osteoporotic rats: a systematic review and meta-analysis.

CONTEXT: Achyranthes bidentata Blume (ABB), a plant of Amaranthaceae family, has been one of the more commonly used phytomedicine remedies for thousands of years, and recent studies have highlighted the efficacy of its extracts in the treatment of osteoporosis. Nonetheless, a thorough analysis of its benefits is currently absent. OBJECTIVE: This meta-analysis assessed the effects of ABB root extract (ABBRE) on osteoporotic rats and provides a rationale for future clinical studies. METHODS: Searches were conducted in seven different Chinese and English databases, and the search period was from their establishment to January 2024. This study was registered in PROSPERO (CRD42023418917). Selected research regarding the ABBRE treatment of osteoporotic rats, and the corresponding research has distinctly reported outcomes, and the data on the bone mineral density (BMD), bone histomorphometrics, biomechanical parameters, and bone biochemical markers of osteoporotic rats can be extracted. RESULTS: Through screening, 11 studies met the eligibility requirements for inclusion, in which 222 animals were studied. The treatment group with ABBRE exhibited increased bone mineral density (standardized mean difference [SMD] = 1.64, 95% CI = 0.52 to 2.77). Based on subgroup analysis, the greatest increase in bone mineral density was observed when the dose of ABBRE was ≤ 400 mg/kg/day and the duration of treatment was ≤ 12 weeks. CONCLUSIONS: ABBRE is a phytomedicine that can effectively promote the enhancement of bone mineral density and ease osteoporosis. It can be developed into a new alternative therapy by conducting experiments and clinical studies on larger samples.

Inhibition of HIF-2α expression in cardiomyocytes attenuates PCB126-induced cardiotoxicity associated with decreased apoptosis through the PI3K/Akt and p53 signaling pathways.

PCB126, a type of polychlorinated biphenyl (PCB), is a persistent pollutant found in both biotic and abiotic environments and poses significant public health risks due to its potential to cause cardiac damage with prolonged exposure. Hypoxia-inducible factor-2α (HIF-2α) is part of the hypoxia-inducible factor (HIF) transcription complex family. Previous studies have shown that knocking out or inhibiting HIF-2α expression can ameliorate pulmonary hypertension and right ventricular dysfunction. This study aimed to investigate whether cardiac-specific knockout of HIF-2α can alleviate the cardiotoxicity caused by PCB126. In this study, cardiac-specific knockout mice and wild-type mice were orally administered PCB126 or corn oil (50 µg/kg/week) for eight weeks. Our findings indicated that PCB126 induces cardiotoxicity and myocardial injury, as evidenced by elevated cardiac enzyme levels and increased cardiac collagen fibers. RNA sequencing revealed that PCB126-induced cardiotoxicity involves the PI3K/Akt and p53 signaling pathways, which was confirmed by western blot analysis. Notably, cardiac-specific knockout of HIF-2α mitigated the damage caused by PCB126, reducing the expression of cardiac enzymes, inflammatory cytokines, and myocardial collagen fibers. Under normal conditions, conditional knockout (CKO) of the HIF-2α gene in cardiomyocytes did not affect the morphology or function of the mouse heart. However, HIF-2α CKO in the heart reduced the cardiotoxic effects of PCB126 by decreasing apoptosis through the PI3K/Akt and p53 signaling pathways. In conclusion, inhibiting HIF-2α expression in cardiomyocytes attenuated PCB126-induced cardiotoxicity by modulating apoptosis through these signaling pathways.

Combinatory effect of ALA-PDT and itraconazole in the treatment of cutaneous protothecosis.

BACKGROUND: As a rare subcutaneous infection, protothecosis is easily misdiagnosed. Similar to other subcutaneous infection, there is no unified standard for treatment, for cases not suitable for surgery, clinicians often use antifungal drugs based on their experience, and the course of treatment varies from several months to several years. Based on the fact that there are few relevant materials and researches on photodynamic therapy (PDT), we conducted a study based on a clinical case that used oral itraconazole combined with 5-aminolevylinic acid photodynamic therapy (ALA-PDT) to treat a patient with cutaneous protothecosis caused by Prototheca wicherhamii. METHODS: Different concentrations of ALA and different light doses were used to investigate the effects of ALA-PDT on the growth inhibition of P. wickerhamii in vitro with Colony-counting Methods. And we used transmission electron microscopy (TEM) to visualize the structural changes and the effects of ALA-PDT treating on cellular structures of the P. wickerhamii. Futher, we performed the susceptibility test of P. wickerhamii to itraconazole before and after ALA-PDT in vitro. RESULTS: We have successfully treated a patient with cutaneous protothecosis caused by P. wickerhamii by using combination therapy in a total of 9-week course of treatment. In vitro, ALA-PDT can inhibit the growth of P. wickerhamii when the ALA concentration was 5 mg/mL (P < 0.01), and this effect became stronger as the concentration of ALA or light dose is increased. Using TEM, we confirmed that ALA-PDT can disrupt the cell wall structure and partition structure of P. wickerhamii, which may contribute to its inhibitory effect. Further studies showed that the MIC of itraconazole for P. wickerhamii was decreased after ALA-PDT. CONCLUSIONS: ALA-PDT combined with oral itraconazole can be used to treat cutaneous protothecosis. Accordingly, ALA-PDT can destroy the cell wall and partition structure of P. wickerhamii leading to an inhibitory effect on it in vitro, and the effect is enhanced with the increase of ALA concentration and light dose. Also, the sensitivity of P. wickerhamii to itraconazole is observed increased after ALA-PDT. So our study provides a theoretical basis for the promising treatment against cutaneus protothecosis.

The First Case of Intra-portal Islet Implantation During Liver Machine Perfusion Allowing Simultaneous Islet-liver Transplantation in A Human: A New and Safe Treatment for End-stage Liver Disease Combined With Diabetes Mellitus.

OBJECTIVE: Evaluating the safety and efficacy of implanting a liver with islet grafts into patients with end-stage liver disease and diabetes mellitus (DM). BACKGROUND: DM and end-stage liver diseases are significant health concern worldwide, often coexisting and mutually influencing each other. Addressing both diseases simultaneously is paramount. METHODS: We utilized the islet transplantation combined ischemia-free liver transplantation (ITIFLT) technique to treat a patient with hepatocellular carcinoma (HCC) and type 2 diabetes mellitus (T2DM). The liver was procured and preserved using the ischemia-free liver transplantation (IFLT) technique, and during normothermic machine perfusion (NMP), isolated and purified islet grafts were transplanted into the liver through the portal vein. Finally, the liver, incorporating with the transplant islet grafts, was implanted into the recipient without interruption of blood supply. RESULTS: The patient received both liver and islet graft from the same donor. The patient achieved insulin-independence by post-transplant day (PTD) 9, and both liver and islet function remained robust. The patient was discharged on PTD 18 and experienced no surgical or transplantation-related complications during the follow-up period. Furthermore, islet grafts presence was observed in liver biopsies after islet transplantation. CONCLUSIONS: This landmark case marks the inaugural application of ITIFLT in humans, signifying its potential as a promising treatment modality for end-stage liver disease with DM.

Association of triglyceride-glucose index with severity of coronary artery disease among male patients.

The correlation between diabetes and coronary artery disease (CAD) is well established. Insulin resistance (IR) is considered a primary contributor to elevated CAD risk in diabetic individuals. The triglyceride-glucose (TyG) index serves as a straightforward surrogate marker for insulin resistance. However, few studies have explored their correlations with myocardial infarction and CAD severity. Therefore, our study aimed to investigate the association between the TyG index and the occurrence of myocardial infarction, as well as the severity of coronary artery disease. We conducted a retrospective study involving 3865 consecutive patients who underwent coronary angiography at the First Affiliated Hospital of Zhejiang University, School of Medicine. Of these, 1724 patients were diagnosed with coronary artery disease. Demographic, biochemical, clinical, and angiographic data were gathered. A robust correlation exists between the TyG index and CAD subtypes, suggesting its potential as an independent clinical diagnostic marker. Moreover, the TyG index exhibited a significant positive correlation with disease severity, as assessed by the Gensini score. Elevated TyG index was associated with an increased predisposition to severe CAD, as indicated by the Gensini score, and myocardial infarction, even after adjusting for well-established cardiovascular risk factors.

Insight into the compositional variation of volatile and polar compounds of Radix Bupleuri from different processing technologies by GC-MS and UHPLC-Q-TOF/MS metabolomics.

INTRODUCTION: Insight into comparing key active ingredients of Radix Bupleuri (RB) based on different processing technologies is a key step to reveal the material basis of drug efficacy and a challenging task for developing traditional Chinese medicine (TCM). OBJECTIVE: This work aims to establish a comprehensive comparative analysis method of TCM and its processed products, which can be used to analyze the changing trend of active components of RB before and after processing. METHODS: First, RB was processed with rice vinegar, rice wine, and honey. Then, ultra-high-performance liquid chromatography (UHPLC) and gas chromatography (GC) coupled with mass spectrometry (MS) technology as well as multiple statistical analyses were used to comprehensively evaluate the compositional variation of polar and volatile compounds in RB under different processing processes. Meanwhile, in UHPLC-MS, a sequential window acquisition of all theoretical fragment ion spectral and information-dependent acquisition mutual authentication (SIMA) was developed. RESULTS: A total of 30 polar components and 33 volatile components were identified as chemical markers (mainly type II saikosaponins, terpenes, and fatty acid esters). These may be the material basis for giving unique pharmacological activities to RB and its processed products. CONCLUSIONS: These findings provided a solid foundation for the differentiated clinical application of RB, and the SIMA method held great potential for achieving accurate analysis of TCM processing ingredients.

Artificial intelligence-enabled multipurpose smart detection in active-matrix electrowetting-on-dielectric digital microfluidics.

An active-matrix electrowetting-on-dielectric (AM-EWOD) system integrates hundreds of thousands of active electrodes for sample droplet manipulation, which can enable simultaneous, automatic, and parallel on-chip biochemical reactions. A smart detection system is essential for ensuring a fully automatic workflow and online programming for the subsequent experimental steps. In this work, we demonstrated an artificial intelligence (AI)-enabled multipurpose smart detection method in an AM-EWOD system for different tasks. We employed the U-Net model to quantitatively evaluate the uniformity of the applied droplet-splitting methods. We used the YOLOv8 model to monitor the droplet-splitting process online. A 97.76% splitting success rate was observed with 18 different AM-EWOD chips. A 99.982% model precision rate and a 99.980% model recall rate were manually verified. We employed an improved YOLOv8 model to detect single-cell samples in nanolitre droplets. Compared with manual verification, the model achieved 99.260% and 99.193% precision and recall rates, respectively. In addition, single-cell droplet sorting and routing experiments were demonstrated. With an AI-based smart detection system, AM-EWOD has shown great potential for use as a ubiquitous platform for implementing true lab-on-a-chip applications.

Magnetic Field Assisted Enhanced Sensitivity of Nonferromagnetic Materials Boosting the Carrier Transfer: Mechanistic Studies.

The performance of semiconductor sensors is determined by reaction kinetics, conductivity, and electron mobility, which are undoubtedly closely related to the electron motion behavior. Therefore, the effective regulation of electronic states is crucial for improving gas sensing properties. Previous methods of enhancing the gas-sensing performance have induced complex material modifications, and the extent of performance improvement is usually very limited. Further optimization of the gas sensing performance requires continuous efforts to advance new technologies. Toward this issue, a novel magnetic field-induced strategy is adopted to boost the carrier transfer efficiency of nonferromagnetic semiconductors. The gas sensing investigation results manifest that the applied magnetic field can effectively enhance the sensitivity and reduce the baseline resistance. The In2O3 NC-2 (In2O3 nanocubes) with an applied magnetic field have a greatly enhanced response of 161.4 toward 100 ppm formaldehyde, which is 2.5 times higher than that without magnetic field. The enhanced gas sensing properties can be mainly attributed to magnetization of reactive materials, which makes the orientation of electronic magnetic moments consistent, thus greatly contributing to reactivity. This work introduces a practical approach to effectively improve gas sensing performance without further morphology optimization, noble metal catalysis, structural modification, and material cladding. The results of this study provide new insights for designing novel gas sensors to improve the gas sensing performance.

Jasmonic acid plays an important role in mediating retrograde signaling under mitochondrial translational stress to balance plant growth and defense.

Proper mitochondrial function is crucial to plant growth and development. Inhibition of mitochondrial translation leads to mitochondrial proteotoxic stress, which triggers a protective transcriptional response that regulates nuclear gene expression, commonly referred to as the mitochondrial unfolded protein response (UPRmt). Although UPRmt has been extensively studied in yeast and mammals, very little is known about UPRmt in plants. Here, we show that mitochondrial translational stress inhibits plant growth and development by inducing jasmonic acid (JA) biosynthesis and signaling. The inhibitory effect of mitochondrial translational stress on plant growth was alleviated in JA signaling defective mutants coi1-2, myc2, and myc234. Genetic analysis indicates that Arabidopsis mitochondrial ribosomal protein L1 (MRPL1), a key factor in UPRmt, regulates plant growth in a CORONATINE-INSENSITIVE1 (COI1)-dependent manner. Moreover, under mitochondrial translational stress, MYC2 showed direct binding to G-boxes in the ETHYLENE RESPONSE FACTOR 109 (ERF109) promoter. The induction of ERF109 expression enhances hydrogen peroxide (H2O2) production, which acts as a feedback loop to inhibit root growth. In addition, mutation of MRPL1 increases JA accumulation, reduces plant growth, and enhances biotic stress resistance. Overall, our findings reveal that JA plays an important role in mediating retrograde signaling under mitochondrial translational stress to balance plant growth and defense.

Practical Performance Analysis of MDI-QKD with Orbital Angular Momentum on UAV Relay Platform.

The integration of terrestrial- and satellite-based quantum key distribution (QKD) experiments has markedly advanced global-scale quantum networks, showcasing the growing maturity of quantum technologies. Notably, the use of unmanned aerial vehicles (UAVs) as relay nodes has emerged as a promising method to overcome the inherent limitations of fiber-based and low-Earth orbit (LEO) satellite connections. This paper introduces a protocol for measurement-device-independent QKD (MDI-QKD) using photon orbital angular momentum (OAM) encoding, with UAVs as relay platforms. Leveraging UAV mobility, the protocol establishes a secure and efficient link, mitigating threats from untrusted UAVs. Photon OAM encoding addresses reference frame alignment issues exacerbated by UAV jitter. A comprehensive analysis of atmospheric turbulence, state-dependent diffraction (SDD), weather visibility, and pointing errors on free-space OAM-state transmission systems was conducted. This analysis elucidates the relationship between the key generation rate and propagation distance for the proposed protocol. Results indicate that considering SDD significantly decreases the key rate, halving previous data results. Furthermore, the study identifies a maximum channel loss capacity of 26 dB for the UAV relay platform. This result is pivotal in setting realistic parameters for the deployment of UAV-based quantum communications and lays the foundation for practical implementation strategies in the field.

Artificial Intelligence Measurement of Preoperative Radiographs in Adolescent Idiopathic Scoliosis Based on Multiple-View Semantic Segmentation.

STUDY DESIGN: Cross-sectional study. OBJECTIVES: Imaging classification of adolescent idiopathic scoliosis (AIS) is directly related to the surgical strategy, but the artificial classification is complex and depends on doctors' experience. This study investigated deep learning-based automated classification methods (DL group) for AIS and validated the consistency of machine classification and manual classification (M group). METHODS: A total of 506 cases (81 males and 425 females) and 1812 AIS full spine images in the anteroposterior (AP), lateral (LAT), left bending (LB) and right bending (RB) positions were retrospectively used for training. The mean age was 13.6 ± 1.8. The mean maximum Cobb angle was 46.8 ± 12.0. U-Net semantic segmentation neural network technology and deep learning methods were used to automatically segment and establish the alignment relationship between multiple views of the spine, and to extract spinal features such as the Cobb angle. The type of each test case was automatically calculated according to Lenke's rule. An additional 107 cases of adolescent idiopathic scoliosis imaging were prospectively used for testing. The consistency of the DL group and M group was compared. RESULTS: Automatic vertebral body segmentation and recognition, multi-view alignment of the spine and automatic Cobb angle measurement were implemented. Compare to the M group, the consistency of the DL group was significantly higher in 3 aspects: type of lateral convexity (0.989 vs 0.566), lumbar curvature modifier (0.932 vs 0.738), and sagittal plane modifier (0.987 vs 0.522). CONCLUSIONS: Deep learning enables automated Cobb angle measurement and automated Lenke classification of idiopathic scoliosis whole spine radiographs with higher consistency than manual measurement classification.

Deep Learning in Gene Regulatory Network Inference: A Survey.

Understanding the intricate regulatory relationships among genes is crucial for comprehending the development, differentiation, and cellular response in living systems. Consequently, inferring gene regulatory networks (GRNs) based on observed data has gained significant attention as a fundamental goal in biological applications. The proliferation and diversification of available data present both opportunities and challenges in accurately inferring GRNs. Deep learning, a highly successful technique in various domains, holds promise in aiding GRN inference. Several GRN inference methods employing deep learning models have been proposed; however, the selection of an appropriate method remains a challenge for life scientists. In this survey, we provide a comprehensive analysis of 12 GRN inference methods that leverage deep learning models. We trace the evolution of these major methods and categorize them based on the types of applicable data. We delve into the core concepts and specific steps of each method, offering a detailed evaluation of their effectiveness and scalability across different scenarios. These insights enable us to make informed recommendations. Moreover, we explore the challenges faced by GRN inference methods utilizing deep learning and discuss future directions, providing valuable suggestions for the advancement of data scientists in this field.