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Abstract The electronic medical record management system plays a crucial role in clinical practice, optimizing the recording and management of healthcare data. To enhance the functionality of the medical record management system, this paper develops a customized schema designed for ophthalmic diseases. A multi-modal knowledge graph is constructed, which is built upon expert-reviewed and de-identified real-world ophthalmology medical data. Based on this data, we propose an auxiliary diagnostic model based on a contrastive graph attention network (CGAT-ADM), which uses the patient’s diagnostic results as anchor points and achieves auxiliary medical record diagnosis services through graph clustering. By implementing contrastive methods and feature fusion of node types, text, and numerical information in medical records, the CGAT-ADM model achieved an average precision of 0.8563 for the top 20 similar case retrievals, indicating high performance in identifying analogous diagnoses. Our research findings suggest that medical record management systems underpinned by multimodal knowledge graphs significantly enhance the development of AI services. These systems offer a range of benefits, from facilitating assisted diagnosis and addressing similar patient inquiries to delving into potential case connections and disease patterns. This comprehensive approach empowers healthcare professionals to garner deeper insights and make well-informed decisions.

Abstract The spalt (Sal) gene family has four members (Sall1-4) in vertebrates, all of which play pivotal roles in various biological processes and diseases. However, the expression and function of SALL2 in development are still less clear. Here, we first charted SALL2 protein expression pattern during mouse embryo development by immunofluorescence, which revealed its dominant expression in the developing nervous system. With the establishment of Sall2 deficient mouse embryonic stem cells (ESCs), the in vitro neural differentiation system was leveraged to interrogate the function of SALL2, which showed impaired neural differentiation of Sall2 knockout (KO) ESCs. Furthermore, neural stem cells (NSCs) could not be derived from Sall2 KO ESCs and the generation of neural tube organoids (NTOs) was greatly inhibited in the absence of SALL2. Meanwhile, transgenic expression of E1 isoform of SALL2 restored the defects of neural differentiation in Sall2 KO ESCs. By chromatin immunoprecipitation sequencing (ChIP-seq), Tuba1a was identified as downstream target of SALL2, whose function in neural differentiation was confirmed by rescuing neural phenotypes of Sall2 KO ESCs when overexpressed. In sum, by elucidating SALL2 expression dynamics during early mouse development and mechanistically characterizing its indispensable role in neural differentiation, this study offers insights into SALL2’s function in human nervous system development, associated pathologies stemming from its mutations and relevant therapeutic strategy.

Abstract Cardiac biological pacing (BP) is one of the future directions for bradyarrhythmias intervention. Currently, cardiac pacemaker cells (PCs) used for cardiac BP are mainly derived from pluripotent stem cells (PSCs). However, the production of high-quality cardiac PCs from PSCs remains a challenge. Here, we developed a cardiac PC differentiation strategy by adopting dual PC markers and simulating the developmental route of PCs. First, two PC markers, Shox2 and Hcn4, were selected to establish Shox2:EGFP; Hcn4:mCherry mouse PSC reporter line. Then, by stepwise guiding naïve PSCs to cardiac PCs following naïve to formative pluripotency transition and manipulating signaling pathways during cardiac PCs differentiation, we designed the FSK method that increased the yield of SHOX2+; HCN4+ cells with typical PC characteristics, which was 12 and 42 folds higher than that of the embryoid body (EB) and the monolayer M10 methods respectively. In addition, the in vitro cardiac PCs differentiation trajectory was mapped by single-cell RNA sequencing (scRNA-seq), which resembled in vivo PCs development, and ZFP503 was verified as a key regulator of cardiac PCs differentiation. These PSC-derived cardiac PCs have the potential to drive advances in cardiac BP technology, help with the understanding of PCs (patho)physiology, and benefit drug discovery for PC-related diseases as well.

Abstract Parallel tidal channel systems, characterized by commonly cross-shore orientation and regular spacing, represent a distinct class of tidal channel networks in coastal environments worldwide. Intriguingly, these cross-shore oriented channel systems can develop in environments dominated by alongshore tidal currents, for which the mechanisms remain elusive. Here, we combine remote sensing imagery analysis and morphodynamic simulations to demonstrate that the deflection of alongshore tidal currents at transitions in bed elevation determines the characteristic orientation of the parallel tidal channels. Numerical results reveal that sharp changes in bed elevation lead to nearly 90-degree intersection angles, while smoother transitions in bed profiles result in less perpendicular channel alignments. These findings shed light on the potential manipulation of tidal channel patterns in coastal wetlands, thus equipping coastal managers with a broader range of strategies for the sustainable management of these vital ecosystems in the face of climate change and sea level rise.

A method for the generation of ultrarelativistic electron beams with high spin polarization is put forward, where a tightly focused linearly polarized ultraintense laser pulse interacts with a nonprepolarized transverse-size-tailored solid target. The radiative spin polarization and angular separation is facilitated by the standing wave formed via the incident and reflected laser pulses at the overdense plasma surface. Strong electron heating caused by transverse instability enhances photon emission in the density spikes injected into the standing wave near the surface. Two groups of electrons with opposite transverse polarization emerge, antialigned to the magnetic field, which are angularly separated in the standing wave due to the phase-matched oscillation of the magnetic field and the vector potential. The polarized electrons propelled into the plasma slab are focused at the exit by the self-generated quasistatic fields. Our particle-in-cell simulations demonstrate the feasibility of highly polarized electrons with a single 10 PW laser beam, e.g., with polarization of 60% and charge of 8 pC selected at energy of 200 MeV within 15 mrad angle and 10% energy spread.

Abstract The accurate perception of multiple flight parameters, such as the angle of attack, angle of sideslip, and airflow velocity, is essential for the flight control of micro air vehicles, which conventionally rely on arrays of pressure or airflow velocity sensors. Here, we present the estimation of multiple flight parameters using a single flexible calorimetric flow sensor featuring a sophisticated structural design with a suspended array of highly sensitive vanadium oxide thermistors. The proposed sensor achieves an unprecedented velocity resolution of 0.11 mm·s−1 and angular resolution of 0.1°. By attaching the sensor to a wing model, the angles of attack and slip were estimated simultaneously. The triaxial flight velocities and wing vibrations can also be estimated by sensing the relative airflow velocity due to its high sensitivity and fast response. Overall, the proposed sensor has many promising applications in weak airflow sensing and flight control of micro air vehicles.

The occurrence of a sharp turn along the upper course of the Yangtze River is referred to as the “Great Bend” and represents a large-scale drainage reorganization in response to the surface rise of the Tibetan Plateau. However, the timing and mechanism of the formation of the Great Bend remain disputed. In this paper, we report new (U–Th)/He and apatite fission track thermochronological data from the deep river valley in the Great Bend area of the southeastern margin of the Tibetan Plateau. Compared with the adjacent Jianchuan Basin, two phases of younger rapid cooling for the Great Bend area are identified based on thermal-history modeling, namely, Miocene (ca. 17 to 11–8 Ma) and Quaternary, with the former phase being contemporaneous with the formation of the anticline in the Tiger Leaping Gorge. Progressive increases in the normalized channel steepness (ksn) and the degree of river-valley incision with increasing distance downstream for tributaries of the Yangtze River in the Tiger Leaping Gorge indicate that river rerouting and formation of the Great Bend occurred during the Miocene. Samples located at the bottom of the Tiger Leaping Gorge also reveal a phase of rapid cooling since ca. 1.9 Ma, with an exhumation rate of 1.5 ± 0.2 mm/year. We hypothesize that enhanced Quaternary exhumation in the southeastern margin of the Tibetan Plateau occurred mainly within the narrow region between the Sichuan Basin and the Eastern Himalayan Syntaxis, corresponding to an episode of widespread extensional deformation superimposed above middle- to upper-crustal flexure in this region.

Abstract Background Clinical and experimental studies have shown that the myocardial inflammatory response during pathological events varies between males and females. However, the cellular and molecular mechanisms of these sex differences remain elusive. CD73/adenosine axis has been linked to anti-inflammatory responses, but its sex-specific cardioprotective role is unclear. The present study aimed to investigate whether the CD73/adenosine axis elicits sex-dependent cardioprotection during metabolic changes and myocarditis induced by hypobaric hypoxia. Methods For 7 days, male and female mice received daily injections of the CD73 inhibitor adenosine 5′- (α, β-methylene) diphosphate (APCP) 10 mg/kg/day while they were kept under normobaric normoxic and hypobaric hypoxic conditions. We evaluated the effects of hypobaric hypoxia on the CD73/adenosine axis, myocardial hypertrophy, and cardiac electrical activity and function. In addition, metabolic homeostasis and immunoregulation were investigated to clarify the sex-dependent cardioprotection of the CD73/adenosine axis. Results Hypobaric hypoxia-induced cardiac dysfunction and adverse remodeling were more pronounced in male mice. Also, male mice had hyperactivity of the CD73/adenosine axis, which aggravated myocarditis and metabolic shift compared to female mice. In addition, CD73 inhibition triggered prostatic acid phosphatase ectonucleotidase enzymatic activity to sustain adenosine overproduction in male mice but not in female mice. Moreover, dual inhibition prostatic acid phosphatase and CD73 enzymatic activities in male mice moderated adenosine content, alleviating glycolytic shift and proinflammatory response. Conclusion The CD73/adenosine axis confers a sex-dependent cardioprotection. In addition, extracellular adenosine production in the hearts of male mice is influenced by prostatic acid phosphatase and tissue nonspecific alkaline phosphatase.

BACKGROUND The lifestyle of most people was forced to change due to the COVID-19 pandemic. Perhaps after the pandemic, we will find that these subtle changes in life and from the depths of our hearts are thorough and profound. They may form our conceptual consensus and behavioral habits, becoming part of our long-term personal consciousness. This study explored the impacts of the COVID-19 pandemic on the future life behavior intentions of medical and health-related students studying at universities in China. METHODS Electronic questionnaires were distributed to students studying at 3 universities in China. A total of 251 valid questionnaires were obtained, and the chi-squared test was used to compare the corresponding groups. RESULTS In the future, students plan to pay more attention to wearing masks and maintaining social distance in public places, do more online shopping, have more meals at home or in the canteen, engage in less international travel, and have fewer gatherings with friends. However, compared with Chinese students, more non-Chinese students plan to increase domestic and international travel and reduce online learning. Furthermore, only among non-Chinese students did gender, urban or rural origin, and family economic conditions influence how the COVID-19 pandemic affected their future life behaviors. CONCLUSION The COVID-19 pandemic changed the future life behavior intentions of medical and health-related students. The future behaviors of these students will impact the entire society. This study will help the government and policymakers predict and prepare for general lifestyle changes in our society.

Rheumatoid arthritis (RA) is a chronic autoimmune disease accompanied by local and systemic bone loss. FcγRs, especially FcγRIIa (hFcγRIIa), have been implicated in the pathogenesis of RA. However, the contribution of hFcγRIIa to bone loss has not been fully elucidated. In the present study, we demonstrated the double-edged sword role of hFcγRIIa on osteoclast differentiation through investigations involving hFcγRIIa-transgenic (hFcγRIIa-Tg) mice. Our findings reveal that hFcγRIIa-Tg mice, previously shown to exhibit heightened susceptibility to collagen-induced arthritis (CIA), displayed increased osteoporosis during CIA or at advanced ages (40 weeks), accompanied by heightened in vivo osteoclast differentiation. Notably, bone marrow cells from hFcγRIIa-Tg mice exhibited enhanced efficiency in differentiating into osteoclasts and bone resorption in vitro compared to wild-type mice when stimulated with receptor activators of NF-κB ligand (RANKL). Additionally, hFcγRIIa-Tg mice exhibited augmented sensitivity to RANKL-induced bone loss in vivo, highlighting the osteoclast-promoting role of hFcγRIIa. Mechanistically, bone marrow cells from hFcγRIIa-Tg mice displayed heightened Syk self-activation, leading to mTOR-pS6 pathway activation, thereby promoting RANKL-driven osteoclast differentiation. Intriguingly, while hFcγRIIa crosslinking hindered RANKL-induced osteoclast differentiation, it activated the kinase cAbl, subsequently triggering STAT5 activation and inhibiting the expression of osteoclast-associated genes. This study provides novel insights into hFcγRIIa-mediated osteoclast biology, suggesting promising therapeutic targets for managing bone remodeling disorders.

Background and purposeSpontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a common acute cerebrovascular disease characterized by severe illness, high mortality, and potential cognitive and motor impairments. We carried out a retrospective study at Fujian Provincial Hospital to establish and validate a model for forecasting functional outcomes at 6 months in aSAH patients who underwent interventional embolization.Methods386 aSAH patients who underwent interventional embolization between May 2012 and April 2022 were included in the study. We established a logistic regression model based on independent risk factors associated with 6-month adverse outcomes (modified Rankin Scale Score ≥ 3, mRS). We evaluated the model’s performance based on its discrimination, calibration, clinical applicability, and generalization ability. Finally, the study-derived prediction model was also compared with other aSAH prognostic scales and the model’s itself constituent variables to assess their respective predictive efficacy.ResultsThe predictors considered in our study were age, the World Federation of Neurosurgical Societies (WFNS) grade of IV-V, mFisher score of 3–4, secondary cerebral infarction, and first leukocyte counts on admission. Our model demonstrated excellent discrimination in both the modeling and validation cohorts, with an area under the curve of 0.914 (p

Background: This study aimed to investigate whether dexmedetomidine provides survival benefit in critically ill patients with sepsis-induced coagulopathy (SIC).Methods: Patients with sepsis-induced coagulopathy admitted to the ICU were identified from the Medical Information Marketplace for Intensive Care (MIMIC)-IV database. They were divided into two groups: patients who started dexmedetomidine within 48 h of ICU admission and lasted for more than 4 h and patients who did not receive dexmedetomidine as a control group. The primary outcome was 28-day hospital mortality, the secondary outcome was in-hospital mortality, and the extended outcomes included duration of mechanical ventilation and vasopressor use, ICU stay, and hospital stay. Propensity score matching (PSM) analysis was used to match patients who received dexmedetomidine with those who did not, and multivariable Cox models and logistics models were used to account for baseline differences and unmeasured confounders. An external validation was performed with the Critical care database comprising patients with infection at Zigong Fourth People’s Hospital.Results: After PSM, 592 patients who received dexmedetomidine were matched with 592 patients who did not receive dexmedetomidine. In the primary and secondary endpoints, dexmedetomidine was associated with a lower risk of 28-day hospital mortality (19.3% vs. 14.2%, hazard ratio (HR) 0.71; P = 0.020) and in-hospital mortality (22.3% vs. 16.4%, odds ratio (OR) 0.68; P = 0.017) in patients with SIC. Regarding the extended outcome, dexmedetomidine was also associated with a longer length of hospital stay (median 12.54 days vs. 14.87 days, P = 0.002) and longer ICU stay (median 5.10 days vs. 6.22 days, P = 0.009). In addition, the duration of mechanical ventilation was significantly increased in the dexmedetomidine group (median 41.62 h vs. 48.00 h, p = 0.022), while the duration of vasopressor use was not significantly different (median 36.67 h vs. 39.25 h, p = 0.194). Within 48 h of ICU stay, receiving a dose of dexmedetomidine greater than 0.474 μg/kg/h and continuous dexmedetomidine administration for 24–48 h may be associated with 28-day hospitalization outcomes in patients with SIC. External cohort validation also found that the use of dexmedetomidine after admission to the ICU can reduce 28-day mortality in patients with SIC.Conclusion: Dexmedetomidine administration is associated with reduced 28-day hospital mortality and in-hospital mortality in critically ill patients with SIC, and these findings deserve further verification in randomized controlled trials.

It has been proven that the white-box ciphers with small encodings will be vulnerable to algebraic and computation attacks. By leveraging the large encodings, the self-equivalence and implicit implementations are proposed for ARXbased white-box ciphers. Unfortunately, these two types of white-box implementations are proven to be insecure under the algebraic attack. Different from algebraic attacks, computation analysis can extract the secret key from the memory access traces without software reverse engineering. It is still an open problem whether the self-equivalence and implicit implementations can resist the computation analysis. In this paper, we analyze the encoded structure of the self-equivalence/implicit whitebox ARX ciphers and discuss its resistance to the computation analysis, such as differential computation analysis (DCA) and algebraic degree computation analysis (ADCA). The results reveal that the large input, encoding, and round key can practically mitigate DCA and ADCA. To deal with the large space, we introduce a new method which is named chosen-plaintext computation analysis (CP-CA). Based on a partial key guess and deliberately chosen intermediate value, CP-CA constructs a reverse function to calculate a set of plaintexts. With the obtained plaintexts, the large affine and non-linear encodings will be reduced to a small space. Subsequently, CP-CA mounts the computation analysis on the traces to recover the secret key. Following CP-CA, we propose a CP-DCA attack and reformulate ADCA as chosen-plaintext linear encoding analysis (CP-LEA). The experimental results indicate that the selfequivalence white-box SPECK32/48/64/96/128 and implicit white-box SPECK32/64 implementations are vulnerable to CP-DCA and CP-LEA attacks.

This paper presents an advanced method for the reliable detection of failures and online calibration of airborne LiDARs and cameras in photogrammetric mapping of remote sensing imagery capture scenarios. Traditional calibration methods without targets typically depend on aligning the spatial structures of LiDAR data with texture features, but acquiring dense LiDAR data for matching and optimization in a short amount of time is challenging in real-time operations. In response to this issue, this paper proposes an image feature encoding method designed to dynamically guide the matching of LiDAR feature points, while simultaneously employing context consistency estimation for additional optimization. Importantly, our method can perceive and recalibrate extrinsic errors in real-time scenarios within natural environments, thereby enhancing the robustness of the calibration. The effectiveness and adaptability of our method are demonstrated using our unique airborne LiDAR-based LIVOX-Airborne datasets, which set a new benchmark in both numerical variability and pixel discrepancy, showcasing a variance of 5.05×10−4 and a mean error of 0.86 pixels.

Species resilience to diversified environments largely depends on their genetic diversity. Disentangling the respective roles of multiple landscape factors on population genetic variation could help us interpret the adaptive mechanism of species to environments, which is a central issue in evolutionary biology and biodiversity conservation. Herein, a typical Tibetan loach Triplophysa stenura was selected as study object to perform landscape genetics analyses inferred from mitochondrial cytochrome b gene sequences. Based on extensive sample collection, a total of 377 individuals from 20 sites in the Yarlung Tsangpo River were included in the analyses and results of genetic diversity assessment demonstrated relatively high haplotype diversity and low nucleotide diversity for most geographic populations. Genetic diversity pattern analysis proved that both haplotype and nucleotide diversity were greater in higher, colder and drier areas, which was consistent with the central-marginal hypothesis for this plateau hinterland-originated species. Degree of genetic differentiation among geographic populations varied from low level to extremely high level, with genetic variation coming mainly from within populations. Elevational and climatic divergences were detected to be principally responsible for the formation of population genetic structure of this species, coinciding with the isolation-by-environment model. On this basis, we put forward some applicable proposals that the marginal populations with relatively low elevations deserved more attentions in designing conservation scheme and those genetically differentiated populations should be treated as separate conservation units. In the context of global climate change and intensifying human activity, a sound genetic resources monitoring along elevational or climatic gradient is pivotal to develop future conservation interventions.

Abstract A novel magnetic coupling resonance wireless power transfer (MCR‐WPT) system, which has constant‐current (CC) and constant‐voltage (CV) output characteristics suiting for batteries charging, is proposed in this paper. The hybrid compensation topology is adopted; in detail, the LCL‐P circuit topology is used in the CC mode, while the LCL‐S topology is used in the CV mode. Since the switchable components are only located at the receiving side of WPT, the switching can be controlled by the receiving side based on the batteries’ state without data communication between transmitting side and receiving side. Furthermore, an adjustable frequency tuning method which is based on proportion integration (PI) closed‐loop controlled by the transmitting side is applied to maximize the current of the transmitting coil. This method also can solve the frequency splitting problem, improving the stability and power of the system while the distance of the two sides changes. The performance of the proposed WPT system is verified by simulation and experiments. The experiment results show that the load current variation is less than 3% in the CC mode and the load voltage changes less than 5% in the CV mode, as the load resister changes from 5 to 20 Ω.

The segmentation of fundus tumors is critical for ophthalmic diagnosis and treatment, yet it presents unique challenges due to the variability in lesion size and shape. Our study introduces Fundus Tumor Segmentation Network (FTSNet), a novel segmentation network designed to address these challenges by leveraging classification results and prompt learning. Our key innovation is the multiscale feature extractor and the dynamic prompt head. Multiscale feature extractors are proficient in eliciting a spectrum of feature information from the original image across disparate scales. This proficiency is fundamental for deciphering the subtle details and patterns embedded in the image at multiple levels of granularity. Meanwhile, a dynamic prompt head is engineered to engender bespoke segmentation heads for each image, customizing the segmentation process to align with the distinctive attributes of the image under consideration. We also present the Fundus Tumor Segmentation (FTS) dataset, comprising 254 pairs of fundus images with tumor lesions and reference segmentations. Experiments demonstrate FTSNet’s superior performance over existing methods, achieving a mean Intersection over Union (mIoU) of 0.8254 and mean Dice (mDice) of 0.9042. The results highlight the potential of our approach in advancing the accuracy and efficiency of fundus tumor segmentation.

Cyclists' willingness to ride is usually influenced by their subjective perception of the street riding environment. Measuring this perception is crucial for enhancing residents' willingness to ride. We propose an SSB framework (Public Security, Traffic Safety, Scenic Beauty) to quantify cyclists' subjective perception using street view imagery (SVI) and volunteer rating data. To address the issue of imbalanced class distribution in the volunteer rating data and enhance the model's ability to distinguish between positive and negative perception scenes, we employed a combination of the Kmeans Synthetic Minority Over-Sampling Technique (Kmeans-SMOTE) and the Random Forest (RF) classifier. The Kmeans SMOTE-RF model improved Area Under the Curve (AUC) by 0.327 for public safety, 0.2 for traffic safety, and 0.209 for scenic beauty compared to the RF model. Additionally, we incorporated Shapley Additive Explanations (SHAP) to examine how the visual features of SVI impact cyclists' subjective perception. Trees had a positive impact on all dimensions. Fence and sidewalk were key features for enhancing traffic safety perception, while roads positively affected public security and scenic beauty. These insights support urban planners in understanding the relationship between SVI features and cyclists' perceptions, aiding the design of cyclist-friendly street environments.

Cardiac arrest can lead to severe neurological impairment as a result of inflammation, mitochondrial dysfunction, and post-cardiopulmonary resuscitation neurological damage. Hypoxic preconditioning has been shown to improve migration and survival of bone marrow–derived mesenchymal stem cells and reduce pyroptosis after cardiac arrest, but the specific mechanisms by which hypoxia-preconditioned bone marrow–derived mesenchymal stem cells protect against brain injury after cardiac arrest are unknown. To this end, we established an in vitro co-culture model of bone marrow–derived mesenchymal stem cells and oxygen–glucose deprived primary neurons and found that hypoxic preconditioning enhanced the protective effect of bone marrow stromal stem cells against neuronal pyroptosis, possibly through inhibition of the MAPK and nuclear factor κB pathways. Subsequently, we transplanted hypoxia-preconditioned bone marrow–derived mesenchymal stem cells into the lateral ventricle after the return of spontaneous circulation in an 8-minute cardiac arrest rat model induced by asphyxia. The results showed that hypoxia-preconditioned bone marrow–derived mesenchymal stem cells significantly reduced cardiac arrest–induced neuronal pyroptosis, oxidative stress, and mitochondrial damage, whereas knockdown of the liver isoform of phosphofructokinase in bone marrow–derived mesenchymal stem cells inhibited these effects. To conclude, hypoxia-preconditioned bone marrow–derived mesenchymal stem cells offer a promising therapeutic approach for neuronal injury following cardiac arrest, and their beneficial effects are potentially associated with increased expression of the liver isoform of phosphofructokinase following hypoxic preconditioning.

In order to effectively avoid the possible drawbacks of water seal inhibiting gas resolution and reducing coal seam permeability, based on the existing air jet research foundation, theoretical analysis and laboratory experiments were used to analyze and study the punching characteristics of high-pressure air jets and the law of punching and breaking coal under the combination of jet parameters. The results show that, among the three factors affecting the experimental results, the jet pressure has the greatest influence, the impact target distance is second, and the nozzle size has the least influence on the experimental results; the optimal combination of jet parameters in the experimental range is 12 MPa, 30 mm impact target distance and 3.5 Mach number nozzle size. The effect of jet punching increases with the increase of jet pressure, when the jet pressure reaches 10 MPa, the specimen penetrates, and when it is further increased to 12 MPa, the specimen is broken; there is an optimal impact target distance for jet punching, and the jet punching effect is the best under this target distance, which is generally 6-7 times the nozzle diameter; the nozzle size has little effect on the effect of punching experiments, and the punching effect tends to be constant.

Abstract The characteristics of three‐phase imbalances are present in medium‐ and low‐voltage distribution networks. Integrating single‐phase distributed generation (DG) exacerbates network imbalances, resulting in increased power losses and potential safety hazards. To address these issues, a dynamic reconfiguration strategy (DNR) for three‐phase imbalanced distribution networks, considering soft open points (SOP), has been proposed. The objective is to alleviate the three‐phase imbalance and minimize the operational costs of the distribution network. Within the reconfiguration strategy, the constraints of DG current imbalance in practical system operations are considered. A three‐phase imbalanced DNR model that simultaneously considers the constraints of the SOP and DG current imbalances is introduced. This model aims to optimize the operation of all devices, including the SOP, to address the overall imbalance of the distribution network. This enables the authors to transform the non‐linear model into a mixed‐integer linear programming model, significantly improving the solution efficiency. To validate the proposed strategy, simulations of a modified IEEE 34‐node distribution system and an actual 78‐node distribution system were conducted. The results demonstrate that this strategy offers significant economic benefits and ensures the security of the distribution network.

Madin–Darby canine kidney (MDCK) cells are commonly used to produce cell-based influenza vaccines. However, the role of the low-serum medium on the proliferation of MDCK cells and the propagation of the influenza virus has not been well studied. In the present study, we used 5 of 15 culture methods with different concentrations of a mixed medium and neonatal bovine serum (NBS) to determine the best culture medium. We found that a VP:M199 ratio of 1:2 (3% NBS) was suitable for culturing MDCK cells. Furthermore, the stable growth of MDCK cells and the production of the influenza virus were evaluated over long-term passaging. We found no significant difference in terms of cell growth and virus production between high and low passages of MDCK cells under low-serum culture conditions, regardless of influenza virus infection. Lastly, we performed a comparison of the transcriptomics and proteomics of MDCK cells cultured in VP:M199 = 1:2 (3% NBS) with those cultured in VP:M199 = 1:2 (5% NBS) before and after influenza virus infection. The transcriptome analysis showed that differentially expressed genes were predominantly enriched in the metabolic pathway and MAPK signaling pathway, indicating an activated state. This suggests that decreasing the concentration of serum in the medium from 5% to 3% may increase the metabolic activity of cells. Proteomics analysis showed that only a small number of differentially expressed proteins could not be enriched for analysis, indicating minimal difference in the protein levels of MDCK cells when the serum concentration in the medium was decreased from 5% to 3%. Altogether, our findings suggest that the screening and application of a low-serum medium provide a background for the development and optimization of cell-based influenza vaccines.

With the advancement of computer vision and sensor technologies, many multi-camera systems are being developed for the control, planning, and other functionalities of unmanned systems or robots. The calibration of multi-camera systems determines the accuracy of their operation. However, calibration of multi-camera systems without overlapping parts is inaccurate. Furthermore, the potential of feature matching points and their spatial extent in calculating the extrinsic parameters of multi-camera systems has not yet been fully realized. To this end, we propose a multi-camera calibration algorithm to solve the problem of the high-precision calibration of multi-camera systems without overlapping parts. The calibration of multi-camera systems is simplified to the problem of solving the transformation relationship of extrinsic parameters using a map constructed by multiple cameras. Firstly, the calibration environment map is constructed by running the SLAM algorithm separately for each camera in the multi-camera system in closed-loop motion. Secondly, uniformly distributed matching points are selected among the similar feature points between the maps. Then, these matching points are used to solve the transformation relationship between the multi-camera external parameters. Finally, the reprojection error is minimized to optimize the extrinsic parameter transformation relationship. We conduct comprehensive experiments in multiple scenarios and provide results of the extrinsic parameters for multiple cameras. The results demonstrate that the proposed method accurately calibrates the extrinsic parameters for multiple cameras, even under conditions where the main camera and auxiliary cameras rotate 180°.

This paper introduces fractional-order capacitors and fractional-order inductors into the conventional integer-order cascaded H-bridge multilevel static compensator (ICHM-STATCOM), thereby constructing the main circuit of the fractional-order cascaded H-bridge multilevel static compensator (FCHM-STATCOM). Mechanism-based modeling is employed to establish switching function models and low-frequency dynamic models for the FCHM-STATCOM in the three-phase stationary coordinate system (a-b-c). Subsequently, fractional-order rotating coordinate transformation is introduced to establish the mathematical model of the FCHM-STATCOM in the synchronous rotating coordinate system (d-q). Additionally, a fractional-order proportional-integral (FOPI)-based fractional-order dual closed-loop current decoupling control strategy is proposed. Finally, this paper validates the correctness of the established mathematical models through digital simulation. Moreover, the simulation results demonstrate that by appropriately selecting the order of fractional-order capacitors and fractional-order inductors, the FCHM-STATCOM exhibits superior dynamic and static characteristics compared to the conventional ICHM-STATCOM, and the FCHM-STATCOM provides a more flexible reactive power compensation solution for power systems.

Breast tumor segmentation of ultrasound images provides valuable tumor information for early detection and diagnosis. However, speckle noise and blurred boundaries in breast ultrasound images present challenges for tumor segmentation, especially for malignant tumors with irregular shapes. Recent vision transformers have shown promising performance in handling the variation through global context modeling. Nevertheless, they are often dominated by features of large patterns and lack the ability to recognize negative information in ultrasound images, which leads to the loss of breast tumor details (e.g., boundaries and small objects). In this paper, we propose a novel noise suppression and boundary refinement network, NSBR-Net, to simultaneously alleviate speckle noise interference and blurred boundary problems of breast tumor segmentation. Specifically, we propose two innovative designs, namely, the Noise Suppression Module (NSM) and the Boundary Refinement Module (BRM). The NSM filters noise information from the coarse-grained feature maps, while the BRM progressively refines the boundaries of significant lesion objects. Our method demonstrates superior accuracy over state-of-the-art deep learning models, achieving significant improvements of 3.67% on Dataset B and 2.30% on the BUSI dataset in mDice for testing malignant tumors.

Conclusion: This research highlights the potential of PRIM2 as a biomarker for cancer diagnosis and prognosis, and as a target for immunomodulatory therapy, offering valuable insights for clinical applications.

Intertidal creek ecosystems in saltmarsh wetlands provide crucial ecological services, with burrows facilitating material exchange between these environments. Investigating burrow distribution in tidal creeks is essential, yet the underlying mechanisms remain poorly understood. Our study conducted field observations during two seasons, dividing the typical creek section into microhabitats: flat (F), gentle edge (GE), gentle slope (GS), steep slope (SS), and steep edge (SE). Comprehensive analysis of sediment samples encompassed assessments of water content, organic matter, particle size, and salinity. Burrow parameters were extracted using a deep learning method applied to sample images. Benthic biodiversity and community compositions were characterized through eDNA analysis. Our findings revealed significant variations in burrow distribution, sediment properties, and community compositions, both between and within creek sections. Temporal heterogeneity emerged as a substantial influencer of burrow characteristics, while the propensity of benthic communities to respond to topography and sediment properties constituted a chief determinant of burrow distribution. Utilizing a structural equation model based on field data, we illuminated four response pathways governing burrow distribution. Abiotic factors, especially under temporal heterogeneity, had a paramount impact, highlighting the need to explore relative biotic and abiotic influences, considering seasonal regulation. These findings establish a foundational understanding of burrow distribution and its driving mechanisms in creek ecosystems. They offer valuable insights for future field observations and research directions in this field.

IntroductionMarine epiphytic diatoms are natural diets for multiple marine invertebrates, including sea cucumbers, sea urchins, etc. They also act as bioindicators in marine waters to assess water quality of coastal ecosystems. Material and methodsWe isolated three strains of Navicula and two strains of Nitzschia from macroalgal epiphytes. Combined concentrations of four macroelements, five trace metals, and three vitamins in f/2 medium were optimized for these diatoms using single-factor and orthogonal tests. Results and discussionThe biomass productivities for 4-L enlarged cultures of the five isolated diatoms in their exclusively optimized f/2 media all increased by nearly 10-fold relative to f/2 medium, and that of Navicula-1 and Nitzschia-2 reached the highest, i.e., 29.52 ± 1.98 and 30.68 ± 2.84 g m-2 d-1, respectively. Moreover, the relative abundance of C20:5n3 in the exclusively optimized f/2 medium-cultured Navicula-1 notably rose by 24%, and that in Nitzschia-2 held stable at > 25%. Thus, Navicula-1 and Nitzschia-2 were screened out with outstanding growth traits and improved fatty acid compositions at high levels of combined nitrogen, phosphorus, iron, and silicon. The two diatoms have potential for becoming quality diets for marine aquaculture, and ideal candidates for effective nutrient removal.

ABSTRACTSeasonal influenza, causes hundreds of thousands of deaths annually, posing a severe threat to human health. Currently available influenza vaccines are targeted only at specific strains or conserved epitopes; however, these vaccines are not completely efficacious because influenza viruses can undergo mutation during circulation, leading to antigenic mismatch between recommended strains and circulating strains and elusion from the immune system. Therefore, developing an influenza vaccine that is quick, effective, and broadly protective has become crucial, and the integral part of hemagglutinin (HA) remains an ideal target for vaccine development. This study developed a lipid nanoparticle-encapsulated nucleoside-modified mRNA vaccine (mRNA-LNPs) encoding a consensus full-length HA sequence (H1c) and evaluated its protective efficacy and immunogenicity through in vitro and in vivo assays. Following two intramuscular immunizations (2, 10 µg, or 20 µg) at a 3-week interval in BALB/c mice, H1c-mRNA-LNP vaccine induced strong antibodies as shown in the hemagglutination-inhibition test and protective neutralizing antibodies against numerous heterologous H1N1 influenza viruses as shown in the microneutralization assay. Additionally, both Th1- and Th2-biased cellular immune responses were elicited, with the Th1-biased response being stronger. Two doses of the H1c-mRNA-LNP vaccine could neutralize a panel of heterologous H1N1 influenza viruses and could confer protection in mice. Taken together, these findings suggest that the H1c-mRNA-LNP vaccine encoding a consensus full-length HA is a feasible strategy for developing a cross-protective vaccine against a panel of heterologous H1N1 influenza viruses.

Abstract Frequency conversion of dissipative solitons associated with the generation of broadband optical frequency combs having a tooth spacing of hundreds of giga-hertz is a topical challenge holding the key to practical applications in precision spectroscopy and data processing. The work in this direction is underpinned by fundamental problems in nonlinear and quantum optics. Here, we present the dissipative two-colour bright-bright and dark-dark solitons in a quasi-phase-matched microresonator pumped for the second-harmonic generation in the near-infrared spectral range. We also found the breather states associated with the pulse front motion and collisions. The soliton regime is found to be typical in slightly phase-mismatched resonators, while the phase-matched ones reveal broader but incoherent spectra and higher-order harmonic generation. Soliton and breather effects reported here exist for the negative tilt of the resonance line, which is possible only via the dominant contribution of second-order nonlinearity.

The stability of nano-TATB in an environment of long-term storage or service is currently one concern since it will affect the reliability of weapon systems. To explore the effects of the residual dimethyl sulfoxide (DMSO) solvent generated during synthesis on the storage performance of nano-TATB, this study proposed a new strategy that utilized solvent atmosphere induction to simulate the effects of residual solvents for the first time and quantified the residual solvents using the equilibrium adsorption capacity (Qe) obtained from the pseudo-first-order adsorption kinetic model. Moreover, this study investigated the storage performance of nano-TATB in the DMSO atmosphere using techniques of scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy (Raman), and infrared (IR) spectroscopy. The results show that the residual DMSO can induce nano-TATB growth more significantly than stimuli in a hot and humid environment. After aging at 60 ​°C for 1 ​d in the DMSO atmosphere, a large number of particles with relatively a regular shape and a particle size of about 1 ​μm were generated in the DMSO atmosphere, with a Qe of DMSO of (1.045 ​± ​0.026) mg·g−1. After aging for 5 ​d, some nano-TATB particles grew and had a particle size of up to 5–6 ​μm, and the average density and cohesive strength of nano-TATB greatly increased. As shown by the analysis of the growth mechanism of nano-TATB in the DMSO atmosphere based on the above experimental results, the main reason for the self-assembly of nano-TATB is the surface DMSO induction caused by the interactions between nano-TATB and DMSO molecules. These results show that the key to improving the storage stability of nano-TATB is to reduce the content of residual solvents.

Abstract Polyimides are widely used in the MEMS and flexible electronics fields due to their combined physicochemical properties, including high thermal stability, mechanical strength, and chemical resistance values. In the past decade, rapid progress has been made in the microfabrication of polyimides. However, enabling technologies, such as laser-induced graphene on polyimide, photosensitive polyimide micropatterning, and 3D polyimide microstructure assembly, have not been reviewed from the perspective of polyimide microfabrication. The aims of this review are to systematically discuss polyimide microfabrication techniques, which cover film formation, material conversion, micropatterning, 3D microfabrication, and their applications. With an emphasis on polyimide-based flexible MEMS devices, we discuss the remaining technological challenges in polyimide fabrication and possible technological innovations in this field.

Magnetoencephalography data from participants with high and low trait anxiety reveals a potential role for oscillations in the anterior cingulate and medial prefrontal cortex in anxiety-associated learning.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements’ polarization in the vertical plane of the breast, while the second array has half of the elements’ polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications.

This paper addresses the force-tracking problem of aerospace electro-hydraulic load simulators under the influence of high inertia, large loads, and a strong coupling force disturbance. An accurate mathematical model is initially derived to describe the characteristics of the load simulator system, the cause of the surplus force, and the strong phase lag due to large inertia. In order to overcome the position interference of the system and the large phase lag problem, a terminal sliding mode control strategy based on the modified fast double-power reaching law is proposed, based on the accurate mathematical model. This control strategy effectively suppresses the chattering problem of the sliding control and implements the finite time convergence of the system through the design of the reaching law and terminal sliding surface, ensuring the robustness of the system and the accuracy of the force-tracking problem. Finally, a comparison of the simulation and experimental results based on the design of different strategy controllers is performed to verify the effectiveness of the control strategy and system adaptability.

The accurate segmentation and quantification of retinal fluid in Optical Coherence Tomography (OCT) images are crucial for the diagnosis and treatment of ophthalmic diseases such as age-related macular degeneration. However, the accurate segmentation of retinal fluid is challenging due to significant variations in the size, position, and shape of fluid, as well as their complex, curved boundaries. To address these challenges, we propose a novel multi-scale feature fusion attention network (FNeXter), based on ConvNeXt and Transformer, for OCT fluid segmentation. In FNeXter, we introduce a novel global multi-scale hybrid encoder module that integrates ConvNeXt, Transformer, and region-aware spatial attention. This module can capture long-range dependencies and non-local similarities while also focusing on local features. Moreover, this module possesses the spatial region-aware capabilities, enabling it to adaptively focus on the lesions regions. Additionally, we propose a novel self-adaptive multi-scale feature fusion attention module to enhance the skip connections between the encoder and the decoder. The inclusion of this module elevates the model’s capacity to learn global features and multi-scale contextual information effectively. Finally, we conduct comprehensive experiments to evaluate the performance of the proposed FNeXter. Experimental results demonstrate that our proposed approach outperforms other state-of-the-art methods in the task of fluid segmentation.

Water resources are essential to human exploration in deep space or the establishment of long-term lunar habitation. Ice discovered on the Moon may be useful in future missions to the lunar surface, necessitating the consideration of in situ resource utilization if it is present in sufficient amounts. Extraction of ice can cause the regolith to settle, which can lead to unintended structural damage. Therefore, any settlement resulting from ice extraction should be understood from a geotechnical perspective. This work reports on experimental investigation of the potential settlement caused by the extraction of ice from lunar regolith simulant containing different textures of ice. The KLS-1 simulant was prepared with different water contents and ice textures. Significant settlement occurred in simulant–ice mixtures with initial water contents of 5–10%.

Hydrodynamic pressure sensors offer an auxiliary approach for ocean exploration by unmanned underwater vehicles (UUVs). However, existing hydrodynamic pressure sensors often lack the ability to monitor subtle hydrodynamic stimuli in deep-sea environments. In this study, we present the development of a deep-sea hydrodynamic pressure sensor (DSHPS) capable of operating over a wide range of water depths while maintaining exceptional hydrodynamic sensing performance. The DSHPS device was systematically optimized by considering factors such as piezoelectric polyvinylidene fluoride–trifluoroethylene/barium titanate [P(VDF-TrFE)/BTO] nanofibers, electrode configurations, sensing element dimensions, integrated circuits, and packaging strategies. The optimized DSHPS exhibited a remarkable pressure gradient response, achieving a minimum pressure difference detection capability of approximately 0.11 Pa. Additionally, the DSHPS demonstrated outstanding performance in the spatial positioning of dipole sources, which was elucidated through theoretical charge modeling and fluid–structure interaction (FSI) simulations. Furthermore, the integration of a high Young’s modulus packaging strategy inspired by fish skull morphology ensured reliable sensing capabilities of the DSHPS even at depths of 1000 m in the deep sea. The DSHPS also exhibited consistent and reproducible positioning performance for subtle hydrodynamic stimulus sources across this wide range of water depths. We envision that the development of the DSHPS not only enhances our understanding of the evolutionary aspects of deep-sea canal lateral lines but also paves the way for the advancement of artificial hydrodynamic pressure sensors.

Employing colliding-pulse injection has been shown to enable the generation of high-quality electron beams from laser–plasma accelerators. Here, by using test particle simulations, Hamiltonian analysis, and multidimensional particle-in-cell simulations, we lay the theoretical framework for spin-polarized electron beam generation in the colliding-pulse injection scheme. Furthermore, we show that this scheme enables the production of quasi-monoenergetic electron beams in excess of 80% polarization and tens of pC charge with commercial 10-TW-class laser systems.

Many aquatic and aerial animals have evolved highly sensitive flow receptors to help them survive in challenging environments. The biological flow receptors, such as filiform hairs, lateral lines, and seal whiskers, are elegantly designed with interesting biomechanical processing principles for extreme sensitivity, exhibiting obvious morphological intelligence. For instance, superficial neuromasts on the surface of fish body have an elongated cupula to enhance flow detection with a magnified drag. The flow‐induced mechanical information is transferred to arrayed hair bundles in the neuromasts, which show spontaneous oscillation and mechanical coupling effects for a high mechanical sensitivity. In this review, the biomechanical principles of morphological intelligence in biological flow field receptors are discussed, with an emphasis on the functions of stimulus enhancement, noise reduction, and nonlinear oscillation. In addition, the recent achievements in flow sensors with morphological intelligence are summarized in this article. Though there is still a big gap in principle discovery and practical application of morphological intelligence in engineered sensors, it can be anticipated that the field of intelligent flow sensing will be significantly promoted by the establishment of morphological intelligence models.

Tumor necrosis factor receptor-associated factor 3 (TRAF3), an adaptor protein, has significant and varying effects on immunity depending on cell types. The role of TRAF3 in Madin-Darby Canine Kidney Epithelial (MDCK) cell resistance to influenza A virus (IVA) remains elusive. In the present study, CRISPR-Cas9 gene editing technology was used to construct the TRAF3 knockout MDCK cells (MDCK-TRAF3−/−). Hemagglutination assay, plaque assay, transcriptome, and quantitative real-time PCR were performed after IVA infection. The results showed that after IVA infection, HA titers and virus titers were promoted, interferon I-related pathways were significantly blocked, and transcription of several antiviral-related genes was significantly decreased in MDCK-TRAF3−/− cells. Thus, our study suggests that TRAF3 gene knockout reduced MDCK cell's resistance to IVA, thereby resulting in a promising way for IVA isolation and vaccine manufacturing.

Abstract Background Recent numerous epidemiology and clinical association studies reported that ApoE polymorphism might be associated with the risk and severity of coronavirus disease 2019 (COVID-19), and yielded inconsistent results. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection relies on its spike protein binding to angiotensin-converting enzyme 2 (ACE2) receptor expressed on host cell membranes. Methods A meta-analysis was conducted to clarify the association between ApoE polymorphism and the risk and severity of COVID-19. Multiple protein interaction assays were utilized to investigate the potential molecular link between ApoE and the SARS-CoV-2 primary receptor ACE2, ApoE and spike protein. Immunoblotting and immunofluorescence staining methods were used to access the regulatory effect of different ApoE isoform on ACE2 protein expression. Results ApoE gene polymorphism (ε4 carrier genotypes VS non-ε4 carrier genotypes) is associated with the increased risk (P = 0.0003, OR = 1.44, 95% CI 1.18–1.76) and progression (P

The tumor immune microenvironment is an important prognostic determinant in colorectal cancer (CRC). Here the authors show that tumor infiltrating neutrophils expressing high levels of CD15 interact with CD8+ T effector memory skewing them to produce GZMK, associated with tumor progression in CRC patients.

White-box implementations aim to prevent the key extraction of the cryptographic algorithm even if the attacker has full access to the execution environment. To obfuscate the round functions, Chow et al. proposed a pivotal principle of white-box implementations to convert the round functions as look-up tables which are encoded by random internal encodings. These encodings consist of a linear mapping and a non-linear nibble permutation. At CHES 2016, Bos et al. introduced differential computation analysis (DCA) to extract the secret key from the runtime information, such as accessed memory and registers. Following this attack, many computation analysis methods were proposed to break the white-box implementations by leveraging some properties of the linear internal encodings, such as Hamming weight and imbalance. Therefore, it becomes an alternative choice to use a non-linear byte encoding to thwart DCA. At CHES 2021, Carlet et al. proposed a structural attack and revealed the weakness of the non-linear byte encodings which are combined with a non-invertible linear mapping. However, such a structural attack requires the details of the implementation, which relies on extra reverse engineering efforts in practice. To the best of our knowledge, it still lacks a thorough investigation of whether the non-linear byte encodings can resist the computation analyses. In this paper, we revisit the proposed computation analyses by investigating their capabilities against internal encodings with different algebraic degrees. Particularly, the algebraic degree of encodings is leveraged to explain the key leakage on the non-linear encodings. Based on this observation, we propose a new algebraic degree computation analysis (ADCA), which targets the mappings from the inputs to each sample of the computation traces. Different from the previous computation analyses, ADCA is a higher-degree attack that can distinguish the correct key by matching the algebraic degrees of the mappings. The experimental results prove that ADCA can break the internal encodings from degree 1 to 6 with the lowest time complexity. nstead of running different computation analyses separately, ADCA can be used as a generic tool to attack the white-box implementations.

As a polycrystalline polymer, isotactic polybutene-1 (iPB-1) will form different crystalline structures when it crystallizes under different conditions. In this work, we found a simple method to manipulate the cell structure of iPB-1 foams by controlling the annealing time of crystalline form II at room temperature and employing supercritical CO2 foaming. As the content of crystalline form II increases, the storage modulus (G′) and complex viscosity (|η * |) increase, and the solubility of CO2 in iPB-1 increases. Crystalline form II has a wider foaming temperature window compared to crystalline form I and exhibits a more uniform cell structure at temperatures between 95 °C and 125 °C. The average cell diameters of crystalline form II and I are 33.9 µm and 11.2 µm at 115 °C and 15 MPa CO2, respectively. A small amount of crystalline form I acts as a heterogeneous nucleation agent during the foaming process, resulting in the formation of a “petal-like” cell structure. During the foaming saturation process, the melted portion of iPB-1 with unstable crystalline form II transforms into crystalline form I′ under high-pressure CO2, while the unmelted portion transforms into crystalline form I. As the pressure increases, the cell structure of iPB-1 undergoes a transition from “petal-like” to bimodal cell structure, ultimately achieving a more uniform structure. Moreover, increasing foaming pressure can also change the cell structure of the foamed material from closed-cell to open-cell. The occurrence of bimodal melting peaks in the foamed samples is beneficial for the adhesion of beads during the molding process.

This work describes an eco-friendly approach for the green formulation of Ag nanoparticles by Allium ampeloprasum extract, without using any toxic reducing and capping agents. The morphology, structure, and physicochemical properties were characterized by several analytical techniques such as fourier transformed infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and Ultraviolet–visible spectroscopy (UV–Vis). The nanoparticles were explored biologically in the anticancer assays. Exposure of the nanoparticles samples to non-small-cell lung cancer cells resulted in cell death, which was mostly due to necrosis but slightly due to late apoptosis. The viability of malignant cell lines reduced dose-dependently in the presence of nanoparticles. The IC50 of nanoparticles were 301, 266, 255, and 250 µg/mL against EKVX, HOP-62, A549 and NCI-H460 cancer cell lines, respectively. The green-synthesized nanoparticles induced cell death, suggesting anticancer prospects that may offer new insight into the development of an anticancer nanomedicine.

Unraveling the drivers that shape landscape genetics could help better understand the relationship between genetic structure and environmental factors and provide a scientific basis for wildlife conservation and habitat management. In this study, a typical coldwater fish on the Tibetan Plateau, Schizopygopsis younghusbandi, was selected to explore its spatial genetic structure and the determinant factors using mitochondrial cytochrome b gene as the molecular marker. The results showed a total of 80 haplotypes and 90 variable sites among 663 individuals from 25 geographical populations, with haplotype diversities (Hd) ranging from 0.636 to 0.936 and nucleotide diversities (Pi) ranging from 0.00160 to 0.00450. Significant positive correlations were observed between Hd and spatial factors (longitude and elevation) as well as the majority of single or combined bioclimatic factors. The correlations between Pi and these factors were inconclusive, revealing that Hd was more sensitive than Pi to population dynamic fluctuations. The phenomenon of greater genetic diversity in higher, colder and drier areas was consistent with the central-marginal hypothesis for this highland-origin species. The majority of genetic differentiation indices Fst indicated moderate differentiation, showing genetic heterogeneity among geographical populations. Fst was positively correlated with variations of elevation and the first principal component of bioclimatic factors, showing a weakly positive relationship with river-network distance, which demonstrated that the Isolation-by-Environment model could explain this genetic structure. In conclusion, as a highly specialized coldwater fish, S. younghusbandi retained higher genetic diversity in higher, colder and drier areas, and population differentiation was mostly related to differences of local bioclimate. For future conservation, we advocate that different geographical populations be treated as separate conservation units, with close attention paid to marginal populations, which are more vulnerable to external disturbances and exhibited less genetic variation.

BackgroundSelecting features related to postoperative infection following cardiac surgery was highly valuable for effective intervention. We used machine learning methods to identify critical perioperative infection-related variables after mitral valve surgery and construct a prediction model.MethodsParticipants comprised 1223 patients who underwent cardiac valvular surgery at eight large centers in China. The ninety-one demographic and perioperative parameters were collected. Random forest (RF) and least absolute shrinkage and selection operator (LASSO) techniques were used to identify postoperative infection-related variables; the Venn diagram determined overlapping variables. The following ML methods: random forest (RF), extreme gradient boosting (XGBoost), Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), AdaBoost, Naive Bayesian (NB), Logistic Regression (LogicR), Neural Networks (nnet) and artificial neural network (ANN) were developed to construct the models. We constructed receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) was calculated to evaluate model performance.ResultsWe identified 47 and 35 variables with RF and LASSO, respectively. Twenty-one overlapping variables were finally selected for model construction: age, weight, hospital stay, total red blood cell (RBC) and total fresh frozen plasma (FFP) transfusions, New York Heart Association (NYHA) class, preoperative creatinine, left ventricular ejection fraction (LVEF), RBC count, platelet (PLT) count, prothrombin time, intraoperative autologous blood, total output, total input, aortic cross-clamp (ACC) time, postoperative white blood cell (WBC) count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), PLT count, hemoglobin (Hb), and LVEF. The prediction models for infection after mitral valve surgery were established based on these variables, and they all showed excellent discrimination performance in the test set (AUC > 0.79).ConclusionsKey features selected by machine learning methods can accurately predict infection after mitral valve surgery, guiding physicians in taking appropriate preventive measures and diminishing the infection risk.

Microwave medical sensing and imaging (MMSI) is a highly active research field. In MMSI, electromagnetic inverse scattering (EIS) is a commonly used technique that infers the internal characteristics of the diseased area by measuring the scattered field. It is worth noting that the image formed by EIS often exhibits the super-resolution phenomenon, which has attracted much research interest over the past decade. A classical perspective is that multiple scattering leads to super-resolution, but this is subject to debate. This paper aims to analyze the super-resolution behavior for Born-iterative-type algorithms for the following three aspects. Firstly, the resolution defined by the traditional Rayleigh criterion can only be applied to point scatterers. It does not suit general scatterers. By using the Sparrow criterion and the generalized spread function, the super-resolution condition can be derived for general scatterers even under the Born approximation (BA) condition. Secondly, an iterative algorithm results in larger coefficients in the high-frequency regime of the optical transfer function compared to non-iterative BA. Due to the anti-apodization effect, the spread function of the iterative method becomes steeper, which leads to a better resolution following the definition of the Sparrow criterion mentioned above. Thirdly, the solution from the previous iteration, as the prior knowledge for the next iteration, will cause changes in the total field, which provides additional information outside the Ewald sphere and thereby gives rise to super-resolution. Comprehensive numerical examples are used to verify these viewpoints.

Abstract Large-area, programmable assembly of diverse micro-objects onto arbitrary substrates is a fundamental yet challenging task. Herein a simple wafer-level micro-assembly technique based on the light-triggered change in both surface topography and interfacial adhesion of a soft photo-sensitive polymer is proposed. In particular, the light-regulated polymer growth creates locally indented and elevated zones on the stamp surface. The light-mediated adhesion reduction, on the other hand, facilitates the inks to be released from the polymer. The interplay of these two effects makes it feasible for the programmable assembly of ultra-small components onto various substrates coated with supplementary adhesive layers. The fidelity of this technique is validated by assembling diverse materials and functional devices, with the printing size up to 4-inch. This work provides a rational strategy for large-scale and programmable assembly of diverse delicate micro-objects, bypassing the common issues of some existing techniques such as poor transfer uniformity, small printing area, and high cost.