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Abstract Preeclampsia (PE) is a severe pregnancy complication characterized by significant alterations in coagulation function. This study aims to analyze the correlation between coagulation function, platelet parameters, and pregnancy outcomes in PE patients. Clinical data, along with blood and urine samples, were collected from 168 PE patients and 128 healthy pregnant women. General demographic and laboratory testing data were recorded, and maternal and fetal outcomes were followed up. Data were analyzed using Kaplan–Meier and logistic regression analyses. In mild PE patients, thrombin time (p = .000), platelet distribution width (PDW) (p = .000), and clot formation time (p = .000) were increased, while prothrombin time (p = .000) and fibrinogen (p = .045) were reduced. With increasing PE severity, prothrombin time (p = .000), platelet count (PLT) (p = .000), mean platelet volume (MPV) (p = .000), plateletcrit (p = .000), maximum amplitude (MA) (p = .000), and coagulation index (p = .001) decreased, whereas activated partial thromboplastin time (APTT) (p = .000), thrombin time (p = .002), D‐dimer (p = .026), and PDW (p = .000) increased. Lower prothrombin time (p = .048), PLT (p = .004), and coagulation index (p = .026) or higher APTT (p = .032), thrombin time (p = .044), D‐dimer (p = .023), and PDW (p = .016) were associated with a higher risk of poor pregnancy outcomes. Thrombin time was identified as an independent risk factor (p = .025, OR = 2.918, 95% CI: 1.145–7.436), whereas gestational age was an independent protective factor (p = .000, OR = 0.244, 95% CI: 0.151–0.395). This study demonstrates that specific coagulation and platelet parameters are significantly associated with PE severity and adverse pregnancy outcomes. These findings highlight the importance of monitoring coagulation function in PE patients to improve clinical management and outcomes.

Objective To analyze the epidemiological characteristics and spatial clustering of severe fever with thrombocytopenia syndrome (SFTS) in Dalian from 2011 to 2023, and provide evidence for the prevention and control of SFTS. Method The incidence data of SFTS wer obtained from the National Disease Reporting Information System of Chinese Center for Disease Control and Prevention and referral tracking of all SFTS confirmed cases by CDC in all districts, cities and counties under the jurisdiction of Dalian Municipality. The epidemiological charac-teristics and spatial aggregation of SFTS were analyzed by descriptive analysis, Joinpoint regression analysis, and spatial autocorrelation analysis. Result From 2011 to 2023, a total of 701 laboratory confirmed cases of SFTS, including 166 deaths. The annual average morbidity rate was 0.77/100 000 (0.15/100 000 – 1.93/100 000), and the CFR was 23.68%. The overall morbidity rate of SFTS in Dalian had an increasing trend from 2011 to 2023 was in increase with an average annual percentage change (AAPC) of 24.00% (P < 0.05). And the mortality rate had a increasing trend from 2011 to 2023 with an average annual percentage change (AAPC) of 20.95% (P < 0.05). The cases mainly occurred from Apirl to October and the incidence peak was in summer. The middle-aged and elderly farmers were the main SFTS population.The top three areas of incidence number were 228 cases of Zhuanghe city, 194 cases of Pulandian city, 156 cases of Wafangdian city. Global spatial autocorrelation analysis showed that the spatial aggeration occurred in the incidence of SFTS from 2017 to 2023 (P < 0.05). Local spatial autocorrelation analysis showed that "High-high clustering" areas were mainly concentrated in the mountainous areas of northern Dalian such as Zhuanghe, Pulandian and Wafangdian. Conclution From 2011 – 2023, the incidence of SFTS increased in Dalian, and the spread and obvious spatially cluesterd were observed. The morbidity and mortality risk were high in the elderly. The incidence of SFTS was seasonal.

Abstract Continuous and quantitative monitoring of knee joint function has clinical value in rehabilitation assessment and the timing of return to play for anterior cruciate ligament injury patients. However, the existing approaches, including clinical examination, arthrometry and inertial solutions, can only be used for qualitative, off‐line and low‐quality evaluations, respectively. Burgeoning Kirigami stretchable sensors could be a disruptive candidate solution, but they usually suffer from structural buckling issues when used for large strain applications, such as knee joint motion capture where the buckling degrades sensor reliability and repeatability. Here, we propose a buckling‐resistant stretchable and wearable sensor for knee joint motion capture. It enables continuous and precise motion signal capture of the knee joint and provides high wearing comfort and reliability. Clinical tests were conducted on 30 patients in the field, tracking data provided by the sensor from their initial hospitalization to later surgery. And the full rehabilitation of one subject was recorded and analyzed. The test results show that our sensor can dynamically assess knee function in real time and recommend the best timing for return to play, which paves the way for personalized and telerehabilitation.

ABSTRACTSoil salinisation has led to increasing abandonment of farmlands in the arid region of northwest China, and the cultivation of cash crops has become an important way to reuse abandoned farmlands and remediate saline soils. In this study, the effects of cotton (Cot), alfalfa (Alf), and rapeseed (Rap) cropping on the bacterial and fungal communities in saline soil were compared based on high-throughput sequencing. The results showed that soil pH and electrical conductivity (EC) of the Cot, Alf, and Rap groups decreased significantly compared with those of bare land (CK). Especially, soil pH (8.3) and EC (0.93 mS cm-1) of the Alf group decreased the most, and the contents of total nitrogen (TN) and total phosphorus (TP) increased the most, which increased by 250% and 91.4%, respectively compared with those of the CK (p < 0.05). Actinobacteriota and Proteobacteria were the dominant bacterial phyla in the three groups, Ascomycota and Basidiomycota were the dominant fungal phyla. The diversity of soil bacterial and fungal communities in the Alf group was higher than that in the Cot and Rap groups. The results of RDA and PERMANOVA analysis showed that soil pH, EC, C/N ratio, and TN were the main factors affecting soil bacterial and fungal communities in the three groups. In general, Cot, Alf, and Rap cropping all could reduce soil pH and EC and improve soil microbial community structure and diversity, but Alf cropping had the best effects in improving saline soil quality and bacterial and fungal diversity.

Infection with Plasmodium falciparum is often deadly when it results in cerebral malaria, which is associated with neuropathology described as an overwhelming inflammatory response and mechanical obstruction of cerebral microvascular. PI3Kγ is a critical component of intracellular signal transduction and plays a central role in regulating cell chemotaxis, migration, and activation. The purpose of this study was to examine the relationship between inhibiting the PI3Kγ pathway and the outcome of experimental cerebral malaria (ECM) in C57BL/6J mice infected with the mouse malaria parasite, Plasmodium berghei ANKA. We observed that oral administration of the PI3Kγ inhibitor IPI549 after infection completely protected mice from ECM. IPI549 treatment significantly dampened the magnitude of inflammatory responses, with reduced production of pro-inflammatory factors, decreased T cell activation, and altered differentiation of antigen-presenting cells. IPI549 treatment protected the infected mice from neuropathology, as assessed by an observed reduction of pathogenic T cells in the brain. Treating the infected mice with IPI549 three days after parasite inoculation improved the murine blood brain barrier (BBB) integrity and helped the mice pass the onset of ECM. Together, these data indicate that oral administration of the PI3Kγ inhibitor IPI549 has a suppressive role in host inflammation and alleviates cerebral pathology, which supports IPI549 as a new malaria treatment option with potential therapeutic implications for cerebral malaria.

BackgroundWith the rapid aging of the global population, the prevalence of mild cognitive impairment (MCI) and dementia is anticipated to surge worldwide. MCI serves as an intermediary stage between normal aging and dementia, necessitating more sensitive and effective screening tools for early identification and intervention. The BrainFx SCREEN is a novel digital tool designed to assess cognitive impairment. This study evaluated its efficacy as a screening tool for MCI in primary care settings, particularly in the context of an aging population and the growing integration of digital health solutions. ObjectiveThe primary objective was to assess the validity, reliability, and applicability of the BrainFx SCREEN (hereafter, the SCREEN) for MCI screening in a primary care context. We conducted an exploratory study comparing the SCREEN with an established screening tool, the Quick Mild Cognitive Impairment (Qmci) screen. MethodsA concurrent mixed methods, prospective study using a quasi-experimental design was conducted with 147 participants from 5 primary care Family Health Teams (FHTs; characterized by multidisciplinary practice and capitated funding) across southwestern Ontario, Canada. Participants included health care practitioners, patients, and FHT administrative executives. Individuals aged ≥55 years with no history of MCI or diagnosis of dementia rostered in a participating FHT were eligible to participate. Participants were screened using both the SCREEN and Qmci. The study also incorporated the Geriatric Anxiety Scale–10 to assess general anxiety levels at each cognitive screening. The SCREEN’s scoring was compared against that of the Qmci and the clinical judgment of health care professionals. Statistical analyses included sensitivity, specificity, internal consistency, and test-retest reliability assessments. ResultsThe study found that the SCREEN’s longer administration time and complex scoring algorithm, which is proprietary and unavailable for independent analysis, presented challenges. Its internal consistency, indicated by a Cronbach α of 0.63, was below the acceptable threshold. The test-retest reliability also showed limitations, with moderate intraclass correlation coefficient (0.54) and inadequate κ (0.15) values. Sensitivity and specificity were consistent (63.25% and 74.07%, respectively) between cross-tabulation and discrepant analysis. In addition, the study faced limitations due to its demographic skew (96/147, 65.3% female, well-educated participants), the absence of a comprehensive gold standard for MCI diagnosis, and financial constraints limiting the inclusion of confirmatory neuropsychological testing. ConclusionsThe SCREEN, in its current form, does not meet the necessary criteria for an optimal MCI screening tool in primary care settings, primarily due to its longer administration time and lower reliability. As the number of digital health technologies increases and evolves, further testing and refinement of tools such as the SCREEN are essential to ensure their efficacy and reliability in real-world clinical settings. This study advocates for continued research in this rapidly advancing field to better serve the aging population. International Registered Report Identifier (IRRID)RR2-10.2196/25520

This paper presents the design, fabrication, and characterization of cantilever-type resonators with a novel stacked structure. Aluminum nitride is adopted as the material for both the structural layer and the piezoelectric layer; this simplifies the fabrication process and improves the quality factor of the resonator. Both in-plane and out-of-plane flexural modes were investigated. The effect of the structural dimensions and electrode patterns on the resonator’s performance were also studied. Finite-element simulations and experiments examining anchor loss and thermoelastic damping, which are the main loss mechanisms affecting the quality factor of these resonators, were carried out. The optimal structural dimensions and electrode patterns of the cantilever-type resonators are presented. A quality factor of 7922 with a motional impedance of 88.52 kΩ and a quality factor of 8851 with a motional impedance of 67.03 kΩ were achieved for the in-plane and out-of-plane flexural-mode resonators, respectively. The proposed resonator design will contribute to the development of high-performance devices such as accelerometers, gyroscopes, and pressure sensors.

Abstract Mechanotransduction in endothelial cells is critical to maintain vascular homeostasis and can contribute to disease development, yet the molecules responsible for sensing flow remain largely unknown. Here, we demonstrate that the discoidin domain receptor 1 (DDR1) tyrosine kinase is a direct mechanosensor and is essential for connecting the force imposed by shear to the endothelial responses. We identify the flow-induced activation of endothelial DDR1 to be atherogenic. Shear force likely causes conformational changes of DDR1 ectodomain by unfolding its DS-like domain to expose the buried cysteine-287, whose exposure facilitates force-induced receptor oligomerization and phase separation. Upon shearing, DDR1 forms liquid-like biomolecular condensates and co-condenses with YWHAE, leading to nuclear translocation of YAP. Our findings establish a previously uncharacterized role of DDR1 in directly sensing flow, propose a conceptual framework for understanding upstream regulation of the YAP signaling, and offer a mechanism by which endothelial activation of DDR1 promotes atherosclerosis.

The continuously emerging SARS-CoV-2 variants pose a great challenge to the efficacy of current drugs, this necessitates the development of broad-spectrum antiviral drugs. In the previous study, we designed a recombinant protein, heptad repeat (HR) 121, as a variant-proof vaccine. Here, we found it can act as a fusion inhibitor and demonstrated broadly neutralizing activities against SARS-CoV-2 and its main variants. Structure analysis suggested that HR121 targets the HR2 domain in SARS-CoV-2 spike (S) 2 subunit to block virus-cell fusion. Functional experiments demonstrated that HR121 can bind HR2 at serological-pH and endosomal-pH, highlighting its inhibition capacity when SARS-CoV-2 enters via either cellular membrane fusion or endosomal route. Importantly, HR121 can effectively inhibit SARS-CoV-2 and Omicron variant pseudoviruses entering the cells, as well as block authentic SARS-CoV-2 and Omicron BA.2 replications in human pulmonary alveolar epithelial cells. After intranasal administration to Syrian golden hamsters, it can protect hamsters from SARS-CoV-2 and Omicron BA.2 infection. Together, our results suggest that HR121 is a potent drug candidate with broadly neutralizing activities against SARS-CoV-2 and its variants.

Abstract Analyzing highly individual-specific genomic data to understand genetic interactions in cancer development is still challenging, with significant implications for the discovery of individual biomarkers as well as personalized medicine. With the rapid development of deep learning, graph neural networks (GNNs) have been employed to analyze a wide range of biomolecular networks. However, many neural networks are limited to black box models, which are only capable of making predictions, and they are often challenged to provide reliable biological and clinical insights. In this research, for sample-specific networks, a novel end-to-end hierarchical graph neural network with interpretable modules is proposed, which learns structural features at multiple scales and incorporates a soft mask layer in extracting subgraphs that contribute to classification. The perturbations caused by the input graphs' deductions are used to evaluate key gene clusters, and the samples are then grouped into classes to produce both sample- and stage-level explanations. Experiments on four gene expression datasets from The Cancer Genome Atlas (TCGA) show that the proposed model not only rivals the advanced GNN methods in cancer staging but also identifies key gene clusters that have a great impact on classification confidence, providing potential targets for personalized medicine.

Abstract Fundus image captures rear of an eye which has been studied for disease identification, classification, segmentation, generation, and biological traits association using handcrafted, conventional, and deep learning methods. In biological traits estimation, most of the studies have been carried out for the age prediction and gender classification with convincing results. The current study utilizes the cutting-edge deep learning (DL) algorithms to estimate biological traits in terms of age and gender together with associating traits to retinal visuals. For the trait’s association, we embed aging as the label information into the proposed DL model to learn knowledge about the effected regions with aging. Our proposed DL models named FAG-Net and FGC-Net, which correspondingly estimates biological traits (age and gender) and generates fundus images. FAG-Net can generate multiple variants of an input fundus image given a list of ages as conditions. In this study, we analyzed fundus images and their corresponding association in terms of aging and gender. Our proposed models outperform randomly selected state-of-the-art DL models.

Abstract Healing of the cutaneous wound requires macrophage recruitment at the sites of injury, where chemotactic migration of macrophages toward the wound is regulated by local inflammation. Recent studies suggest a positive contribution of DNA methyltransferase 1 (Dnmt1) to macrophage pro-informatory responses; however, its role in regulating macrophage motility remains unknown. In this study, myeloid-specific depletion of Dnmt1 in mice promoted cutaneous wound healing and de-suppressed the lipopolysaccharides (LPS)-inhibited macrophage motility. Dnmt1 inhibition in macrophages eliminated the LPS-stimulated changes in cellular mechanical properties in terms of elasticity and viscoelasticity. LPS increased the cellular accumulation of cholesterol in a Dnmt1-depedent manner; cholesterol content determined cellular stiffness and motility. Lipidomic analysis indicated that Dnmt1 inhibition altered the cellular lipid homeostasis, probably through down-regulating the expression of cluster of differentiation 36 CD36 (facilitating lipid influx) and up-regulating the expression of ATP-binding cassette transporter ABCA1 (mediating lipid efflux) and sterol O-acyltransferase 1 SOAT1 (also named ACAT1, catalyzing the esterification of cholesterol). Our study revealed a Dnmt1-dependent epigenetic mechanism in the control of macrophage mechanical properties and the related chemotactic motility, indicating Dnmt1 as both a marker of diseases and a potential target of therapeutic intervention for wound healing.

This paper is focused on electrode design for piezoelectric tuning fork resonators. The relationship between the performance and electrode pattern of aluminum nitride piezoelectric tuning fork resonators vibrating in the in-plane flexural mode is investigated based on a set of resonators with different electrode lengths, widths, and ratios. Experimental and simulation results show that the electrode design impacts greatly the multimode effect induced from torsional modes but has little influence on other loss mechanisms. Optimizing the electrode design suppresses the torsional mode successfully, thereby increasing the ratio of impedance at parallel and series resonant frequencies (Rp/Rs) by more than 80% and achieving a quality factor (Q) of 7753, an effective electromechanical coupling coefficient (kteff2) of 0.066%, and an impedance at series resonant frequency (Rm) of 23.6 kΩ. The proposed approach shows great potential for high-performance piezoelectric resonators, which are likely to be fundamental building blocks for sensors with high sensitivity and low noise and power consumption.

The µTAS/LOC, a highly integrated microsystem, consolidates multiple bioanalytical functions within a single chip, enhancing efficiency and precision in bioanalysis and biomedical operations. Microfluidic centrifugation, a key component of LOC devices, enables rapid capture and enrichment of tiny objects in samples, improving sensitivity and accuracy of detection and diagnosis. However, microfluidic systems face challenges due to viscosity dominance and difficulty in vortex formation. Acoustic-based centrifugation, particularly those using surface acoustic waves (SAWs), have shown promise in applications such as particle concentration, separation, and droplet mixing. However, challenges include accurate droplet placement, energy loss from off-axis positioning, and limited energy transfer from low-frequency SAW resonators, restricting centrifugal speed and sample volume. In this work, we introduce a novel ring array composed of eight Lamb wave resonators (LWRs), forming an Ultra-Fast Centrifuge Tunnel (UFCT) in a microfluidic system. The UFCT eliminates secondary vortices, concentrating energy in the main vortex and maximizing acoustic-to-streaming energy conversion. It enables ultra-fast centrifugation with a larger liquid capacity (50 μL), reduced power usage (50 mW) that is one order of magnitude smaller than existing devices, and greater linear speed (62 mm/s), surpassing the limitations of prior methods. We demonstrate successful high-fold enrichment of 2 μm and 10 μm particles and explore the UFCT’s potential in tissue engineering by encapsulating cells in a hydrogel-based micro-organ with a ring structure, which is of great significance for building more complex manipulation platforms for particles and cells in a bio-compatible and contactless manner.

Microelectromechanical system (MEMS) cantilever resonators suffer from high motional impedance (Rm). This paper investigates the use of mechanically coupled multi-cantilever piezoelectric MEMS resonators in the resolution of this issue. A double-sided actuating design, which utilizes a resonator with a 2.5 μm thick AlN film as the passive layer, is employed to reduce Rm. The results of experimental and finite element analysis (FEA) show agreement regarding single- to sextuple-cantilever resonators. Compared with a standalone cantilever resonator, the multi-cantilever resonator significantly reduces Rm; meanwhile, the high quality factor (Q) and effective electromechanical coupling coefficient (Kteff2) are maintained. The 30 μm wide quadruple-cantilever resonator achieves a resonance frequency (fs) of 55.8 kHz, a Q value of 10,300, and a series impedance (Rs) as low as 28.6 kΩ at a pressure of 0.02 Pa; meanwhile, the smaller size of this resonator compared to the existing multi-cantilever resonators is preserved. This represents a significant advancement in MEMS resonators for miniaturized ultra-low-power oscillator applications.

By leveraging the benefits of a high energy density, miniaturization and integration, acoustic-wave-driven micromotors have recently emerged as powerful tools for microfluidic actuation. In this study, a Lamb-wave-driven micromotor is proposed for the first time. This motor consists of a ring-shaped Lamb wave actuator array with a rotor and a fluid coupling layer in between. On a driving mechanism level, high-frequency Lamb waves of 380 MHz generate strong acoustic streaming effects over an extremely short distance; on a mechanical design level, each Lamb wave actuator incorporates a reflector on one side of the actuator, while an acoustic opening is incorporated on the other side to limit wave energy leakage; and on electrical design level, the electrodes placed on the two sides of the film enhance the capacitance in the vertical direction, which facilitates impedance matching within a smaller area. As a result, the Lamb-wave-driven solution features a much lower driving voltage and a smaller size compared with conventional surface acoustic-wave-driven solutions. For an improved motor performance, actuator array configurations, rotor sizes, and liquid coupling layer thicknesses are examined via simulations and experiments. The results show the micromotor with a rotor with a diameter of 5 mm can achieve a maximum angular velocity of 250 rpm with an input voltage of 6 V. The proposed micromotor is a new prototype for acoustic-wave-driven actuators and demonstrates potential for lab-on-a-chip applications.

Developing effective strategies for the flexible control of fluid is vital for microfluidic electrochemical biosensing. In this study, a gigahertz (GHz) acoustic streaming (AS) based sonoelectrochemical system was developed to realize an on-chip surface modification and sensitive hydrogen peroxide (H2O2) detection from living cells. The flexible and controlled fluid surrounding the electrochemical chip was optimized theoretically and applied in the sonoelectrochemical deposition of Au nanoparticles (AuNPs) first. Under the steady and fast flow stimulus of AS, AuNPs could be synthesized with a smaller and evener size distribution than the normal condition, allowing AuNPs to show an excellent peroxidase-like activity. Moreover, the AS also accelerated the mass transport of target molecules and improved the catalytic rate, leading to the enhancement of H2O2 detection, with an extremely low detection limit of 32 nM and a high sensitivity of 4.34 μA/ (mM·mm2). Finally, this system was successfully applied in tracking H2O2 release from different cell lines to distinguish the cancer cells from normal cells. This study innovatively integrated the surface modification and molecules detection process on a chip, and also proposed a simple but sensitive platform for microfluidic biosensing application.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease caused by the SFTS virus (SFTSV) and with a high fatality rate. Thrombocytopenia is a major clinical manifestation observed in SFTS patients, but the underlying mechanism remains largely unclear. Here, we explored the effects of SFTSV infection on platelet function in vivo in severely infected SFTSV IFNar−/− mice and on mouse and human platelet function in vitro. Results showed that SFTSV-induced platelet clearance acceleration may be the main reason for thrombocytopenia. SFTSV-potentiated platelet activation and apoptosis were also observed in infected mice. Further investigation showed that SFTSV infection induced platelet reactive oxygen species (ROS) production and mitochondrial dysfunction. In vitro experiments revealed that administration of SFTSV or SFTSV glycoprotein (Gn) increased activation, apoptosis, ROS production, and mitochondrial dysfunction in separated mouse platelets, which could be effectively ameliorated by the application of antioxidants (NAC (N-acetyl-l-cysteine), SKQ1 (10-(6′-plastoquinonyl) decyltriphenylphosphonium) and resveratrol). In vivo experiments showed that the antioxidants partially rescued SFTSV infection-induced thrombocytopenia by improving excessive ROS production and mitochondrial dysfunction and down-regulating platelet apoptosis and activation. Furthermore, while SFTSV and Gn directly potentiated human platelet activation, it was completely abolished by antioxidants. This study revealed that SFTSV and Gn can directly trigger platelet activation and apoptosis in an ROS-MAPK-dependent manner, which may contribute to thrombocytopenia and hemorrhage during infection, but can be abolished by antioxidants.

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. Antibody resistance dampens neutralizing antibody therapy and threatens current global Coronavirus (COVID-19) vaccine campaigns. In addition to the emergence of resistant SARS-CoV-2 variants, little is known about how SARS-CoV-2 evades antibodies. Here, we report a novel mechanism of extracellular vesicle (EV)-mediated cell-to-cell transmission of SARS-CoV-2, which facilitates SARS-CoV-2 to escape from neutralizing antibodies. These EVs, initially observed in SARS-CoV-2 envelope protein-expressing cells, are secreted by various SARS-CoV-2-infected cells, including Vero E6, Calu-3, and HPAEpiC cells, undergoing infection-induced pyroptosis. Various SARS-CoV-2-infected cells produce similar EVs characterized by extra-large sizes (1.6–9.5 μm in diameter, average diameter > 4.2 μm) much larger than previously reported virus-generated vesicles. Transmission electron microscopy analysis and plaque assay reveal that these SARS-CoV-2-induced EVs contain large amounts of live virus particles. In particular, the vesicle-cloaked SARS-CoV-2 virus is resistant to neutralizing antibodies and able to reinfect naïve cells independent of the reported receptors and cofactors. Consistently, the constructed 3D images show that intact EVs could be taken up by recipient cells directly, supporting vesicle-mediated cell-to-cell transmission of SARS-CoV-2. Our findings reveal a novel mechanism of receptor-independent SARS-CoV-2 infection via cell-to-cell transmission, provide new insights into antibody resistance of SARS-CoV-2 and suggest potential targets for future antiviral therapeutics.

Vascular smooth muscle cell (vSMC) is highly plastic as its phenotype can change in response to mechanical cues inherent to the extracellular matrix (ECM). VSMC may be activated from its quiescent contractile phenotype to a proinflammatory phenotype, whereby the cell secretes chemotactic and inflammatory cytokines, e.g. MCP1 and IL6, to functionally regulate monocyte and macrophage infiltration during the development of various vascular diseases including arteriosclerosis. Here, by culturing vSMCs on polyacrylamide (PA) substrates with variable elastic moduli, we discovered a role of discoidin domain receptor 1 (DDR1), a receptor tyrosine kinase that binds collagens, in mediating the mechanical regulation of vSMC gene expression, phenotype, and proinflammatory responses. We found that ECM stiffness induced DDR1 phosphorylation, oligomerization, and endocytosis to repress the expression of DNA methyltransferase 1 (DNMT1), very likely in a collagen-independent manner. The DDR1-to-DNMT1 signaling was sequentially mediated by the extracellular signal-regulated kinases (ERKs) and p53 pathways. ECM stiffness primed vSMC to a proinflammatory phenotype and this regulation was diminished by DDR1 inhibition. In agreement with the in vitro findings, increased DDR1 phosphorylation was observed in human arterial stiffening. DDR1 inhibition in mouse attenuated the acute injury or adenine diet-induced vascular stiffening and inflammation. Furthermore, mouse vasculature with SMC-specific deletion of Dnmt1 exhibited proinflammatory and stiffening phenotypes. Our study demonstrates a role of SMC DDR1 in perceiving the mechanical microenvironments and down-regulating expression of DNMT1 to result in vascular pathologies and has potential implications for optimization of engineering artificial vascular grafts and vascular networks.

Rehabilitation therapy is beneficial for patients with ischemic stroke. Our previous study showed that treadmill training is conducive to neurological function in rats that underwent middle cerebral artery occlusion (MCAO). However, whether exercise benefits cerebral edema and the underlying mechanism remain unclear. This study investigated the influence of treadmill exercise on brain edema and the mechanism of its formation and elimination. The MCAO model was established with Sprague-Dawley (SD) rats, and lentivirus-mediated caveolin-1 shRNA was used to investigate the role of caveolin-1 in brain edema. As expected, we found that treadmill exercise has a beneficial effect on brain edema after stroke. Training led to a significant increase in the expression of caveolin-1 and TRPV4; and reduced brain water content and blood-brain barrier (BBB) damage. This treatment also changed the localization of aquaporin-4 (AQP4). Moreover, the effect of treadmill training on the polar expression of AQP4 differed over time. The results showed that early treadmill training inhibited the polar expression of AQP4, and later promoted its expression. However, the rats that were injected with the caveolin-1 shRNA lentivirus exhibited enhanced edema. Caveolin-1 shRNA eliminated the protective effect induced by exercise, which is consistent with the downregulation of TRPV4 expression. The findings indicate that treadmill training improves brain edema through the caveolin-1/TRPV4/AQP4 pathway.

Abstract Wireless power transfer is one of the enabling technologies for powering implantable biomedical devices. Biocompatibility and CMOS compatibility of wireless power transfer devices are highly desired due to safety and footprint concerns. Toward implantable applications, this paper presents an ultrasound-induced wireless power supply based on AlN piezoelectric micromachined ultrasonic transducer (PMUT). The wireless power supply integrates wireless power transfer, power management and energy storage functions. The PMUT array is used as a passive wireless power receiver, followed by electrical impedance matching networks and a voltage multiplier for efficient power transmission and rectification. The output power intensity of the wireless receiver reaches 7.36 μW/mm2 with an incident ultrasound power below the FDA safety limit. The output power of the wireless power supply reaches 18.8 μW and a 100-μF capacitor is fully charged to 3.19 V after power management, which are sufficient to power many low-power implantable biomedical devices such as for neural electrical stimulation, biosensors and intrabody communication applications. The wireless power supply is implemented in a PCB with a diameter of 1 cm. With biocompatibility and CMOS compatibility of AlN thin film compared to commonly used PZT, the proposed solution paves the way for safer and ultraminiaturized wireless power supplies with further development incorporating all the functions on a monolithic chip in the future.

ObjectiveTo study the worldwide prevalence and associated factors of epilepsy in children and adolescents with Cerebral Palsy (CP) and to analyze the differences between various subgroups.MethodWe identified all potential studies on the prevalence of epilepsy in children and adolescents with CP from PubMed, Web of Science, and Embase. The search time was from the establishment of the database to November 2022. Randomized effects meta-analysis models were used to calculate the prevalence of epilepsy in CP. Subgroup analysis and meta-regression were utilized to further explore heterogeneity between articles and prevalence disparities between subgroups. The funnel plot and Egger's test were used to investigate potential publication bias.ResultsSeventy-two articles, comprising 53,969 children and adolescents with CP, were included in this study. The results indicated a total epilepsy prevalence of 38.0% (95% CI: 34.8%–41.2%) in CP. The prevalence of epilepsy was 46.4% (95% CI: 41.4%–51.5%) in clinical sample-based studies and 31.6% (95% CI: 28.7%–34.5%) in population-based studies. Meta-regression demonstrated that the sample source, neonatal seizure, family history of epilepsy, EEG or cranial imaging abnormalities, intellectual/cognitive impairment, and topographical types of CP were heterogeneous contributors to the epilepsy prevalence in CP.ConclusionApproximately one-third of children and adolescents with CP have epilepsy, and the sample source can significantly impact the total prevalence of epilepsy. Neonatal seizures, family history of epilepsy, EEG abnormalities, cranial imaging abnormalities, severe intellectual disability, and quadriplegia may be contributing factors to epilepsy comorbid in CP. Further study is required to verify the strength of these associations with epilepsy. This study aids in identifying the clinical characteristics of young people with CP at risk of developing epilepsy, which may assist clinicians in the early prevention and diagnosis of epilepsy within this population.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=367766, identifier CRD42022367766.

Abstract At the single-cell level, cellular parameters, gene expression and cellular function are assayed on an individual but not population-average basis. Essential to observing and analyzing the heterogeneity and behavior of these cells/clusters is the ability to prepare and manipulate individuals. Here, we demonstrate a versatile microsystem, a stereo acoustic streaming tunnel, which is triggered by ultrahigh-frequency bulk acoustic waves and highly confined by a microchannel. We thoroughly analyze the generation and features of stereo acoustic streaming to develop a virtual tunnel for observation, pretreatment and analysis of cells for different single-cell applications. 3D reconstruction, dissociation of clusters, selective trapping/release, in situ analysis and pairing of single cells with barcode gel beads were demonstrated. To further verify the reliability and robustness of this technology in complex biosamples, the separation of circulating tumor cells from undiluted blood based on properties of both physics and immunity was achieved. With the rich selection of handling modes, the platform has the potential to be a full-process microsystem, from pretreatment to analysis, and used in numerous fields, such as in vitro diagnosis, high-throughput single-cell sequencing and drug development.

Single image super-resolution (SISR) typically reconstructs higher-resolution (HR) images from the corresponding low-resolution (LR) images in the presence of natural HR images. SISR is highly important in generating high-quality images in forensic scenarios since it facilitates close investigation and examination of captured shoeprints. However, it becomes more challenging when there are no available natural HR ground truth images that correspond to the input LR images. In such cases, HR reconstruction becomes even more crucial for providing HR versions that retain the natural characteristics of shoeprints. For this purpose, we propose IPAS-Net, which utilizes U-Net for feature extraction, shares the learned parameters from LR space in HR space, and innovatively upscales, refines, and enhances the HR space via special treatments. The upsampling-and-refinement block comprises a parallel pipeline composed of attention mechanism block (AMB) and one-step-high-iteration (OSHI). All upsampling solutions are infused so that distinct upscaling can compensate each others’ weaknesses. The generated HR shoeprints are evaluated using blind/non-reference evaluation metrics, and the proposed method outperforms the state of the art (SOTA) deep learning modalities on low-quality shoeprints.

Abstract Eye blinking is closely related to human physiology and psychology. It is an effective method of communication among people and can be used in human–machine interactions. Existing blink monitoring methods include video-oculography, electro-oculograms and infrared oculography. However, these methods suffer from uncomfortable use, safety risks, limited reliability in strong light or dark environments, and infringed informational security. In this paper, we propose an ultrasound-based portable approach for eye-blinking activity monitoring. Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system (MEMS) ultrasonic transducers seamlessly integrated on glasses. The size, weight and power consumption of the transducers are 2.5 mm by 2.5 mm, 23.3 mg and 71 μW, respectively, which provides better portability than conventional methods using wearable devices. Eye-blinking activities were characterized by open and closed eye states and validated by experiments on different volunteers. Finally, real-time eye-blinking monitoring was successfully demonstrated with a response time less than 1 ms. The proposed solution paves the way for ultrasound-based wearable eye-blinking monitoring and offers miniaturization, light weight, low power consumption, high informational security and biosafety.

Abstract Stretchable electronic skin (e‐skin) paves the way for applications that exceed the scope of intrinsic rigid devices and hard‐to‐stretch sensors. The broad application range of flexible e‐skins benefits from device architectures that can simultaneously provide mechanical flexibility and superior sensitivity. Classic fractal design provides a simple architecture to achieve the desired flexibility through structural design for improved wear comfort, but at the expense of sensor sensitivity. In this study, the proposed method addresses the trade‐off between stretchability and sensitivity in fractal design. A high‐sensitivity e‐skin is obtained by eliminating the effect of negative charge on the output by applying the concept of electromechanical coupling. This concept for designing e‐skins with high sensitivity is validated through the delicate patterning of hard‐to‐stretch functional materials. Further, human speech signals are acquired through the integration of e‐skin with signal processing circuits, and speech pattern recognition is realized using machine learning. The stretchable e‐skin with an enhanced gauge factor illustrates the wider application of this concept for improving the sensitivity of stretchable electronic functional materials.

Mechanistic models have been used for centuries to describe complex interconnected processes, including biological ones. As the scope of these models has widened, so have their computational demands. This complexity can limit their suitability when running many simulations or when real-time results are required. Surrogate machine learning (ML) models can be used to approximate the behaviour of complex mechanistic models, and once built, their computational demands are several orders of magnitude lower. This paper provides an overview of the relevant literature, both from an applicability and a theoretical perspective. For the latter, the paper focuses on the design and training of the underlying ML models. Application-wise, we show how ML surrogates have been used to approximate different mechanistic models. We present a perspective on how these approaches can be applied to models representing biological processes with potential industrial applications (e.g., metabolism and whole-cell modelling) and show why surrogate ML models may hold the key to making the simulation of complex biological systems possible using a typical desktop computer.

Severe fever with thrombocytopenia syndrome virus (SFTSV), an emerging bunyavirus, causes severe fever with thrombocytopenia syndrome (SFTS), with a high fatality rate of 20%–30%. At present, however, the pathogenesis of SFTSV remains largely unclear and no specific therapeutics or vaccines against its infection are currently available. Therefore, animal models that can faithfully recapitulate human disease are important to help understand and treat SFTSV infection. Here, we infected seven Chinese rhesus macaques (Macaca mulatta) with SFTSV. Virological and immunological changes were monitored over 28 days post-infection. Results showed that mild symptoms appeared in the macaques, including slight fever, thrombocytopenia, leukocytopenia, increased aspartate aminotransferase (AST) and creatine kinase (CK) in the blood. Viral replication was persistently detectable in lymphoid tissues and bone marrow even after viremia disappeared. Immunocyte detection showed that the number of T cells (mainly CD8+ T cells), B cells, natural killer (NK) cells, and monocytes decreased during infection. In detail, effector memory CD8+ T cells declined but showed increased activation, while both the number and activation of effector memory CD4+ T cells increased significantly. Furthermore, activated memory B cells decreased, while CD80+/CD86+ B cells and resting memory B cells (CD27+CD21+) increased significantly. Intermediate monocytes (CD14+CD16+) increased, while myeloid dendritic cells (mDCs) rather than plasmacytoid dendritic cells (pDCs) markedly declined during early infection. Cytokines, including interleukin-6 (IL-6), interferon-inducible protein-10 (IP-10), and macrophage inflammatory protein 1 (MCP-1), were substantially elevated in blood and were correlated with activated CD4+ T cells, B cells, CD16+CD56+ NK cells, CD14+CD16+ monocytes during infection. Thus, this study demonstrates that Chinese rhesus macaques infected with SFTSV resemble mild clinical symptoms of human SFTS and provides detailed virological and immunological parameters in macaques for understanding the pathogenesis of SFTSV infection.

Abstract Colorectal carcinoma is one of the most common types of malignancy and a leading cause of cancer‐related death. Although clinicopathological parameters provide invaluable prognostic information, the accuracy of prognosis can be improved by using molecular biomarker signatures. Using a large dataset of immunohistochemistry‐based biomarkers (n = 66), this study has developed an effective methodology for identifying optimal biomarker combinations as a prognostic tool. Biomarkers were screened and assigned to related subsets before being analysed using an iterative algorithm customised for evaluating combinatorial interactions between biomarkers based on their combined statistical power. A signature consisting of six biomarkers was identified as the best combination in terms of prognostic power. The combination of biomarkers (STAT1, UCP1, p‐cofilin, LIMK2, FOXP3, and ICOS) was significantly associated with overall survival when computed as a linear variable (χ2 = 53.183, p

To enhance trustworthiness of AI systems, a number of solutions have been proposed to document how such systems are built and used. A key facet of realizing trust in AI is how to make such systems accountable - a challenging task, not least due to the lack of an agreed definition of accountability and differing perspectives on what information should be recorded and how it should be used (e.g., to inform audit). Information originates across the life cycle stages of an AI system and from a variety of sources (individuals, organizations, systems), raising numerous challenges around collection, management, and audit. In our previous work, we argued that semantic Knowledge Graphs (KGs) are ideally suited to address those challenges and we presented an approach utilizing KGs to aid in the tasks of modelling, recording, viewing, and auditing accountability information related to the design stage of AI system development. Moreover, as KGs store data in a structured format understandable by both humans and machines, we argued that this approach provides new opportunities for building intelligent applications that facilitate and automate such tasks. In this paper, we expand our earlier work by reporting additional detailed requirements for knowledge representation and capture in the context of AI accountability; these extend the scope of our work beyond the design stage, to also include system implementation. Furthermore, we present the RAInS ontology which has been extended to satisfy these requirements. We evaluate our approach against three popular baseline frameworks, namely, Datasheets, Model Cards, and FactSheets, by comparing the range of information that can be captured by our KGs against these three frameworks. We demonstrate that our approach subsumes and extends the capabilities of the baseline frameworks and discuss how KGs can be used to integrate and enhance accountability information collection processes.

Abstract Background Cerebral palsy (CP) is a kind of disability that influences motion, and children with CP also exhibit depression-like behaviour. Inflammation has been recognized as a contributor to CP and depression, and some studies suggest that the gut-brain axis may be a contributing factor. Our team observed that Saccharomyces boulardii (S. boulardii) could reduce the inflammatory level of rats with hyperbilirubinemia and improve abnormal behaviour. Both CP and depression are related to inflammation, and probiotics can improve depression by reducing inflammation. Therefore, we hypothesize that S. boulardii may improve the behaviour and emotions of spastic CP rats through the gut-brain axis pathway. Methods Our new rat model was produced by resecting the cortex and subcortical white matter. Seventeen-day-old CP rats were exposed to S. boulardii or vehicle control by gastric gavage for 9 days, and different behavioural domains and general conditions were tested. Inflammation was assessed by measuring the inflammatory markers IL-6 and TNF-α. Hypothalamic–pituitary–adrenal (HPA) axis activity was assessed by measuring adrenocorticotropic hormone and corticosterone in the serum. Changes in the gut microbiome were detected by 16S rRNA. Results The hemiplegic spastic CP rats we made with typical spastic paralysis exhibited depression-like behaviour. S. boulardii treatment of hemiplegic spastic CP rats improves behaviour and general conditions and significantly reduces the level of inflammation, decreases HPA axis activity, and increases gut microbiota diversity. Conclusions The model developed in this study mimics a hemiplegic spastic cerebral palsy. Damage to the cortex and subcortical white matter of 17-day-old Sprague–Dawley (SD) rats led to spastic CP-like behaviour, and the rats exhibited symptoms of depression-like behaviour. Our results indicate that S. boulardii might have potential in treating hemiplegic spastic CP rat models or as an add-on therapy via the gut-brain axis pathway.

Abstract Background As the transmission routes of human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) are similar, previous studies based on separate research on HIV-1 and HCV assumed a similar transmission pattern. However, few studies have focused on the possible correlation of the spatial dynamics of HIV-1 and HCV among HIV-1/HCV coinfected patients. Methods A total of 310 HIV-1/HCV coinfected drug users were recruited in Yingjiang and Kaiyuan prefectures, Yunnan Province, China. HIV-1 env, p17, pol and HCV C/E2, NS5B fragments were amplified and sequenced from serum samples. The genetic characteristics and spatial dynamics of HIV-1 and HCV were explored by phylogenetic, bootscanning, and phylogeographic analyses. Results Among HIV-1/HCV coinfected drug users, eight HCV subtypes (1a, 1b, 3a, 3b, 6a, 6n, 6v, and 6u) and two HIV-1 subtypes (subtype B and subtype C), three HIV-1 circulating recombinant forms (CRF01_AE, CRF07_BC and CRF08_BC), and four unique recombinant forms (URF_BC, URF_01B, URF_01C and URF_01BC) were identified. HCV subtype 3b was the most predominant subtype in both Yingjiang and Kaiyuan prefectures. The dominant circulating HIV-1 subtypes for drug users among the two areas were CRF08_BC and URF_BC. Maximum clade credibility trees revealed that both HIV-1 and HCV were transmitted from Yingjiang to Kaiyuan. Conclusions The spatial dynamics of HIV-1 and HCV among HIV-1/HCV coinfected drug users seem to have high consistency, providing theoretical evidence for the prevention of HIV-1 and HCV simultaneously.

Contactless acoustic manipulation of micro/nanoscale particles has attracted considerable attention owing to its near independence of the physical and chemical properties of the targets, making it universally applicable to almost all biological systems. Thin-film bulk acoustic wave (BAW) resonators operating at gigahertz (GHz) frequencies have been demonstrated to generate localized high-speed microvortices through acoustic streaming effects. Benefitting from the strong drag forces of the high-speed vortices, BAW-enabled GHz acoustic streaming tweezers (AST) have been applied to the trapping and enrichment of particles ranging in size from micrometers to less than 100 nm. However, the behavior of particles in such 3D microvortex systems is still largely unknown. In this work, the particle behavior (trapping, enrichment, and separation) in GHz AST is studied by theoretical analyses, 3D simulations, and microparticle tracking experiments. It is found that the particle motion in the vortices is determined mainly by the balance between the acoustic streaming drag force and the acoustic radiation force. This work can provide basic design principles for AST-based lab-on-a-chip systems for a variety of applications.

Abstract Backgroud It is important to expound the opposite clinical outcomes between children and adulthood for eradicate malaria. There remains unknown about the correlation between adaptive immune response and age-related in malaria. Methods 4 and 8-week-old mice were used to mimic children and adulthood, respectively. Parasitemia and the survival rate were monitored. The proportion and function of Th1 and Th2 cells were detected by FACS. The levels of IFN-γ, IL-4, total IgG, IgG1, IgG2a and Plasmodium yoelii MSP-1-specific IgG were measured by ELISA. Results The adult group showed greater resistance to P. yoelii 17XL infection, with lower parasitemia. Compared with 4-week-old mice, the percentage of CD4+T-bet+IFN-γ+ Th1 cells as well as IFN-γ production were significantly increased on day 5 p.i. in the 8-week-old mice after P. yoelii 17XNL infection. The percentage of CD4+GATA3+IL-4+ Th2 cells and CD4+CXCR5+ Tfh cells, and IL-4 production in the 8-week-old mice significantly increased on day 5 and day 10 after P. yoelii 17XNL infection. Notably, the levels of total IgG, IgG1, IgG2a and P. yoelii MSP-1-specific IgG were also significantly increased in the 8-week-old mice. PD-1, a marker of exhaustion, was up-regulated on CD4+ or activated CD4+ T cells in the 8-week-old mice as compared to the 4-week-old group. Conclusions Thus, we consider that enhanced cellular and humoral adaptive immunity might contribute to rapid clearance of malaria among adults, likely in a PD-1-dependent manner due to induction of CD4+ T cells exhaustion in P. yoelii 17XNL infected 8-week-old mice.

Abstract Background Although the morbidity of gastric cancer has decreased, the incidence of adenocarcinoma of the esophagogastric junction (AEG) is increasing. Furthermore, no consensus exists on which surgical approach should be applied for Siewert type II AEG. The purpose of our study was to evaluate the technical safety and feasibility of a new surgical approach. Methods Sixty patients with Siewert type II AEG underwent laparoscopic total gastrectomy with the total laparoscopic transabdominal-transdiaphragmatic (TLTT) approach, which needs an incision in the diaphragm. Results The median operative time, reconstruction time, and estimated blood loss were 214.8 ± 41.6 min, 29.40 ± 7.1 min, and 209.0 ± 110.3 ml, respectively. All of the patients had negative surgical margins. Conclusion There were no intraoperative complications or conversions to open surgery. Our surgical procedure provides a unique option for the safe application of laparoscopic lower mediastinal lymph node dissection and gastrointestinal reconstruction. Trial registration Chinese Clinical Trial Registry, ChiCTR1800014336. Registered on 31 December 2017 - Prospectively registered, http://www.chictr.org.cn/edit.aspx?pid=23111&htm=4 .

Clustering data with both numeric and categorical attributes is of great importance as such data are ubiquitous in real-world problems. Multi-view learning approaches have proven to be more effective and having better generalisation ability compared to single-view learning in many problems. However, most of the existing clustering algorithms developed for mixed numeric and categorical data are single-view. In this research, we propose a novel multi-view clustering algorithm based on the k-prototypes (which we term Multi-view K-Prototypes) for clustering mixed data. To the best of our knowledge, our proposed Multi-view K-Prototypes is the first multi-view version of the well-known k-prototypes algorithm. To cluster the mixed data over multiple views, we present a novel representation prototype of cluster centres in the scenario of multiple views, and we also devise formulas for updating the cluster centres over each view. Then we propose the concept of consensus cluster centres to output the final clustering result. Finally, we carried out a series of experiments on four benchmark datasets to assess the performance of the proposed Multi-view K-Prototypes clustering. Experimental results show that the Multi-view K-Prototypes algorithm outperforms the seven state-of-the-art algorithms in most cases.

The presence of chemical warfare agents (CWAs) in the environment is a serious threat to human safety, but there are many problems with the currently available detection methods for CWAs. For example, gas chromatography–mass spectrometry cannot be used for in-field detection owing to the rather large size of the equipment required, while commercial sensors have the disadvantages of low sensitivity and poor selectivity. Here, we develop a portable gas sensing instrument for CWA detection that consists of a MEMS-fabricated micro-preconcentrator (μPC) and a film bulk acoustic resonator (FBAR) gas sensor. The μPC is coated with a nanoporous metal–organic framework material to enrich the target, while the FBAR provides rapid detection without the need for extra carrier gas. Dimethyl methylphosphonate (DMMP), a simulant of the chemical warfare agent sarin, is used to test the performance of the instrument. Experimental results show that the μPC provides effective sample pretreatment, while the FBAR gas sensor has good sensitivity to DMMP vapor. The combination of μPC and FBAR in one instrument gives full play to their respective advantages, reducing the limit of detection of the analyte. Moreover, both the μPC and the FBAR are fabricated using a CMOS-compatible approach, and the prototype instrument is compact in size with high portability and thus has potential for application to in-field detection of CWAs.

Objective Autoantibodies to the α3 chain noncollagen 1 domain of type IV collagen (α3(IV)NC1) are a serological hallmark in the diagnosis of anti-glomerular basement membrane (GBM) disease. The objective of our study was to compare the performance of anti-glomerular basement membrane (GBM) antibody detection by chemiluminescence immunoassay (CIA) and by enzyme-linked immunosorbent assays (ELISAs). Methods Sera from outpatients who were suspected to have anti-GBM disease and 31 patients with biopsy-proven anti-GBM disease were collected. Thirty normal controls were also included. All samples were tested for anti-GBM antibodies by CIA and commercial ELISA. The anti-GBM antibody-positive samples were confirmed by a homemade ELISA coated with recombinant human α3(IV)NC1. Results Compared with detection of anti-GBM antibodies with ELISA, detection of anti-GBM antibodies with CIA showed a positivity agreement of 70% and a negativity agreement of 98.6%. Among the 4 patients with different results, the anti-GBM antibody detection by CIA was in agreement with the homemade ELISA coated with recombinant human α3(IV)NC1 and the clinical diagnosis. In 31 patients with anti-GBM disease, good agreement was achieved in the detection of anti-GBM antibodies with CIA, commercial ELISA and the homemade ELISA (100%, 100%). The AUC for CIA and commercial ELISA was 0.987 and 0.966, respectively. Conclusions The detection of anti-GBM antibodies with CIA demonstrated good sensitivity and specificity and was in good agreement with our homemade ELISA, which seems better than the commercial ELISA in suspected anti-GBM disease patients. The three assays performed in parallel in the diagnosis of anti-GBM disease patients.

Clustering analysis, as an important technique in data mining, aims to identify the nature groups or clusters of data objects in the attribute space. Data objects in real-world applications are commonly described by both numeric and categorical attributes. In this research, considering that the partitional clustering algorithms designed for this type of mixed data are prone to get trapped into local optima and the cuckoo search approach is efficient in solving global optimization problems, we propose CCS-K-Prototypes, a novel partitional Clustering algorithm based on Cuckoo Search and K-Prototypes, for clustering mixed numeric and categorical data. To deal with different types of attributes, we develop a novel representation for candidate solutions, and suggest two formulas for the cuckoo to search for the potential solution around the existing solutions or in the entire attribute space. Finally, the performance of the proposed algorithm is assessed by a series of experiments on five benchmark datasets.

This article presents the modeling and solution of an extended type of split delivery vehicle routing problem (SDVRP). In SDVRP, the demands of customers need to be met by efficiently routing a given number of capacitated vehicles, wherein each customer may be served multiple times by more than one vehicle. Furthermore, in many real-world scenarios, consumption of vehicles en route is the same as the goods being delivered to customers, such as food, water and fuel in rescue or replenishment missions in harsh environments. Moreover, the consumption may also be in virtual forms, such as time spent in constrained tasks. We name such a real-world SDVRP as Split Delivery Vehicle Routing Problem with Goods Consumed during Transit (SDVRP-GCT). In this paper, we give mathematical formulas to model SDVRP-GCT and provide solutions by extending three ant colony algorithms. To the best of our knowledge, this is the first research work specifically focussing on the SDVRP-GCT problem and its solutions. To assess the effectiveness of our proposed ant colony algorithms, we first apply them on widely adopted SDVRP benchmarking instances on different scales and their correspondingly extended SDVRP-GCT instances. Then, we formulate a real-world SDVRP-GCT instance for further assessment. Based on the extensive experimental results, we discuss the pros and cons of our proposed solutions and subsequently suggest their preferable application scenarios. In summary, our proposed solutions are shown as highly efficient in solving SDVRP-GCT instances.

Support Vector Regression (SVR) and its variants are widely used regression algorithms, and they have demonstrated high generalization ability. This research proposes a new SVR-based regressor: v-minimum absolute deviation distribution regression (v-MADR) machine. Instead of merely minimizing structural risk, as with v-SVR, v-MADR aims to achieve better generalization performance by minimizing both the absolute regression deviation mean and the absolute regression deviation variance, which takes into account the positive and negative values of the regression deviation of sample points. For optimization, we propose a dual coordinate descent (DCD) algorithm for small sample problems, and we also propose an averaged stochastic gradient descent (ASGD) algorithm for large-scale problems. Furthermore, we study the statistical property of v-MADR that leads to a bound on the expectation of error. The experimental results on both artificial and real datasets indicate that our v-MADR has significant improvement in generalization performance with less training time compared to the widely used v-SVR, LS-SVR, ε-TSVR, and linear ε-SVR. Finally, we open source the code of v-MADR at https://github.com/AsunaYY/v-MADR for wider dissemination.

Recently, many Deep Learning models have been employed to classify different kinds of plant diseases, but very little work has been done for disease severity detection. However, it is more important to master the severities of plant diseases accurately and timely, as it helps to make effective decisions to protect the plants from being further infected and reduce financial loss. In this paper, based on the Huanglongbing (HLB)-infected leaf images obtained from PlantVillage and crowdAI, we created a dataset with 5,406 citrus leaf images infected by HLB. Then six different kinds of popular models were trained to perform the severity detection of citrus HLB with the goal to find which types of models are more suitable to detect HLB severity with the same training circumstance. The experimental results show that the Inception_v3 model with epochs=60 can achieve higher accuracy than that of other models for severity detection with an accuracy of 74.38% due to its highly computational efficiency and small number of parameters. Additionally, aiming for evaluating whether GANs-based data augmentation can contribute to improve the model learning performance, we adopted DCGANs (Deep Convolutional Generative Adversarial Networks) to augment the original training dataset up to two times itself. Finally, a new training dataset with 14,056 leaf images composed by the original training images and the augmented ones were used to train the Inception_v3 model. As a result, we achieved an accuracy of 92.60%, about 20% higher than that of the Inception_v3 model trained by the original training dataset, which suggested that the GANs-based data augmentation is very useful to improve the model learning performance.

In recent years, convolutional neural network (CNN)-based artificial intelligence algorithms have been widely applied to object recognition and image classification tasks. However, the high performance of convolutional neural networks comes at the cost of high-intensity computing and enormous numbers of parameters, which pose substantial challenges to terminal implementations. An end-to-end FPGA-based accelerator is proposed in this work that efficiently processes fine-grained pruned CNNs. A group pruning algorithm with group sparse regularization (GSR) is introduced to solve internal buffer misalignments and load imbalances of the accelerator after fine-grained pruning. A mathematical model of accelerator access and transmission is established to explore the optimal design scale and calculation mode. The accelerator is optimized by designing sparse processing elements and by scheduling the on- and off-chip buffers. The proposed approach reduces the computation of a state-of-the-art large-scale CNN, VGG16, by 86.9% with an accuracy loss on CIFAR-10 of only 0.48%. The accelerator achieves 188.41 GOPS at 100 MHz and consumes 8.15 W when implemented on a Xilinx VC707, making it more energy-efficient than previous approaches.

A number of governmental and nongovernmental organizations have made significant efforts to encourage the development of artificial intelligence in line with a series of aspirational concepts such as transparency, interpretability, explainability, and accountability. The difficulty at present, however, is that these concepts exist at a fairly abstract level, whereas in order for them to have the tangible effects desired they need to become more concrete and specific. This article undertakes precisely this process of concretisation, mapping how the different concepts interrelate and what in particular they each require in order to move from being high-level aspirations to detailed and enforceable requirements. We argue that the key concept in this process is accountability, since unless an entity can be held accountable for compliance with the other concepts, and indeed more generally, those concepts cannot do the work required of them. There is a variety of taxonomies of accountability in the literature. However, at the core of each account appears to be a sense of “answerability”; a need to explain or to give an account. It is this ability to call an entity to account which provides the impetus for each of the other concepts and helps us to understand what they must each require.

Feature detection and correct matching are the basis of the image stitching process. Whether the matching is correct and the number of matches directly affect the quality of the final stitching results. At present, almost all image stitching methods use SIFT+RANSAC pattern to extract and match feature points. However, it is difficult to obtain sufficient correct matching points in low-textured or repetitively-textured regions, resulting in insufficient matching points in the overlapping region, and this further leads to the warping model being estimated erroneously. In this paper, we propose a novel and flexible approach by increasing feature correspondences and optimizing hybrid terms. It can obtain sufficient correct feature correspondences in the overlapping region with low-textured or repetitively-textured areas to eliminate misalignment. When a weak texture and large parallax coexist in the overlapping region, the alignment and distortion often restrict each other and are difficult to balance. Accurate alignment is often accompanied by projection distortion and perspective distortion. Regarding this, we propose hybrid terms optimization warp, which combines global similarity transformations on the basis of initial global homography and estimates the optimal warping by adjusting various term parameters. By doing this, we can mitigate projection distortion and perspective distortion, while effectively balancing alignment and distortion. The experimental results demonstrate that the proposed method outperforms the state-of-the-art in accurate alignment on images with low-textured areas in the overlapping region, and the stitching results have less perspective and projection distortion.

Abstract Acoustofluidics has emerged as a promising method for submicron particle manipulation. However, ultrahigh‐frequency or focused sound waves are usually required to generate sufficient acoustic radiation force or localized streaming vortex for trapping nanoscale objects, which is more challenging in device fabrication. This work presents a novel method using a low‐frequency acoustic field actuated micro‐pillar array (APA) chip to efficiently enable programmable and parallel trapping of nanoparticles. Driven by the acoustic waves, each arrayed vibrating micropillar generates a highly localized acoustic field with enhanced acoustic radiation forces and well‐confined vortex streaming around the pillar. The APA chip is demonstrated with geometric tuning ability of regulating the trapping limit by altering the pillar size. Micropillar arrays with a diameter of 5 µm are demonstrated to trap 112 nm particles efficiently. Thanks to the convenience of using ultrasounds and arraying micropillars of different geometric sizes, the APA chip provides an alternative of submicron particle manipulation technique for programmable and high‐throughput trapping and patterning of particles, with potential for “lab‐on‐a‐chip” sample preparations.