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Rhabdomyolysis is a life-threatening syndrome associated with direct or indirect muscle damage that is rarely reported with dipeptidyl peptidase (DPP)-4 inhibitors. Here we presented a case in which a 58-year-old female suffered from severe swelling and pain in bilateral lower limbs and oliguria after a suicidal vildagliptin overdose. Drug-induced rhabdomyolysis and drug-induced liver injury were diagnosed based on laboratory and radiological findings. The patient was treated with fluid resuscitation, insulin, electrolyte replacement, diuretics, urine alkalizing agents, anticoagulants, antioxidants, and 24-h bedside ECG monitoring and suicide prevention. After 20 days of hospitalization and close monitoring, the patient was discharged without sequelae. Risk factors, diagnostic criteria, disease mechanisms, and outcomes were also discussed. This case illustrated that overdose of oral anti-diabetic medications may result in clinically significant adverse events, such as rhabdomyolysis in this case with a DPP-4 inhibitor. Although the incidence is low, special attention should be paid to intentional or accidental exposure to anti-diabetic medications during suicide attempts, especially in depressed patients with diabetes.

BackgroundSeveral studies have reported on the clinical phenotype of the 17q12 microduplication syndrome, a rare autosomal dominant genetic disorder, in children and adults, but few have reported on its prenatal diagnosis. This study analyzed the prenatal ultrasound phenotypes of the 17q12 microduplication syndrome to improve the understanding, diagnosis, and monitoring of this disease in fetuses.MethodsA retrospective analysis of 8,200 pregnant women who had received an invasive antenatal diagnosis at tertiary referral hospitals between January 2016 and August 2021 was performed. Amniotic fluid or cord blood was sampled from the pregnant women for karyotyping and chromosome microarray analysis (CMA).ResultsThe CMA revealed microduplication in the 17q12 region of the genome in five fetuses, involving fragments of about 1.5–1.9 Mb. Five fetuses with the 17q12 microduplication syndrome had different prenatal ultrasound phenotypes, including duodenal obstruction (two fetuses); mild ventriculomegaly, dysplasia of the septum pellucidum, agenesis of the corpus callosum (one fetus); and a strong echo in the left ventricle only (one fetus). The ultrasound phenotype of one fetus was normal. Among the five fetuses with the 17q12 microduplication syndrome, the parents of three refused CNV segregation analysis, while CNV segregation analysis was performed for the remaining two fetuses to confirm whether the disorder was inherited maternally or paternally, with normal phenotypes. After genetic counseling, the parents of those two fetuses chose to terminate the pregnancy, while the parents of the three unverified fetuses continued the pregnancy, with normal follow-up after birth.ConclusionAlthough prenatal ultrasound phenotypes in fetuses with the 17q12 microduplication syndrome are highly variable, our study has highlighted the distinct association between duodenal obstruction and the 17q12 microduplication syndrome. Understanding the relationship between the pathogenesis of the 17q12 microduplication in prenatal ultrasound phenotypes and its long-term prognosis will contribute to better genetic counseling concerning the 17q12 microduplication syndrome, which is still a challenge.

Aim: It has been found that the co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. But, whether this pharmacokinetic drug-drug interaction (DDI) between nifedipine and apatinib could enhance the antihypertensive effect of nifedipine, causing sever changes of blood pressure was unknown. Therefore, the aim of the present study was to conduct the pharmacokinetic/pharmacodynamic (PK/PD) modelling to evaluate the effect of pharmacokinetic changes on the antihypertensive effect of nifedipine. Thus, the results could guide the co-administration of these two drugs in clinic.Methods: A physiologically-based pharmacokinetic (PBPK) model was first developed for nifedipine. The pharmacokinetic DDI between nifedipine and apatinib was evaluated. Then the verified PBPK models were linked to a PD model for investigating whether the exposure changes of nifedipine could cause severe changes in blood pressure. Furthermore, the changes in blood pressure caused by combination with apatinib were also assessed in patients with hepatic impairment via the PBPK/PD models.Results: The predicted area under plasma concentration-time profile (AUC), maximum concentration (Cmax), area under effect-time profile (AUE), and maximum reduction in systolic blood pressure (Rmax) are all within 0.5–2.0-fold of the observed data, indicating that the PBPK/PD models for nifedipine are successfully established. The increases of predicted AUC and Cmax of nifedipine in the presence of apatinib are 1.73 and 1.41-fold, respectively. Co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. However, the predicted AUE and Rmax changes of nifedipine in the presence to the absence of apatinib in cancer patients as well as in patients with hepatic impairment are all within 1.25-fold. The results indicate that the exposure changes of nifedipine caused by combination of apatinib has little effect on the changes of systolic blood pressure both in cancer patients and patients with hepatic impairment.Conclusion: The pharmacokinetic changes of nifedipine caused by co-administration with apatinib has little impact on the antihypertensive effect of nifedipine. Apatinib is unlikely to cause severe pharmacodynamic DDI via inhibition of CYP3A4. It is suggested that nifedipine could be used in combination with apatinib without dose adjustment in clinic.

Amino acids are essential plant compounds serving as the building blocks of proteins, the predominant forms of nitrogen (N) distribution, and signaling molecules. Plant amino acids derive from root acquisition, nitrate reduction, and ammonium assimilation. Many amino acid transporters (AATs) mediating transfer processes of amino acids have been functionally characterized in Arabidopsis, whereas the function and regulation of the vast majority of AATs in rice (Oryza sativa L.) and other crops remain unknown. In this review, we summarize the current understanding of amino acids in the rhizosphere and in metabolism. We describe their function as signal molecules and in regulating plant architecture, flowering time, and defense against abiotic stress and pathogen attack. AATs not only function in root acquisition and translocation of amino acids from source to sink organs, regulating N uptake and use efficiency, but also as transporters of non-amino acid substrates or as amino acid sensors. Several AAT genes show natural variations in their promoter and coding regions that are associated with altered uptake rate of amino acids, grain N content, and tiller number. Development of an amino acid transfer model in plants will advance the manipulation of AATs for improving rice architecture, grain yield and quality, and N-use efficiency.

Pebble flow characteristics can be significantly affected by the configuration of pebble bed, especially for HTGR pebble beds. How to achieve a desired uniform flow pattern without stagnation is the top priority for reactor design. Pebbles flows inside some specially designed pebble bed with arc-shaped contraction configurations at the bottom, including both concave-inward and convex-outward shapes are explored based on discrete element method. Flow characteristics including pebble retention, residence-time frequency density, flow uniformity as well as axial velocity are investigated. The results show that the traditionally designed pebble bed with cone-shape bottom is not the most preferred structure with respect to flow pattern for reactor design. By improving the contraction configuration, the flow performance can be significantly enhanced. The flow in the convex-shape configuration featured by uniformity, consistency and less stagnation, is much more desirable for pebble bed design. In contrast, when the shape is from convex-forward to concave-inward, the flow shows more nonuniformity and stagnation in the corner although the average cross-section axial velocity is the largest due to the dominant middle pebbles.

The operating environment of rolling bearings in mine hoists is complicated, and detecting their faults is hindered by a weak and unstable initial vibration signal. This directly affects the ability to extract pertinent fault features. This paper puts forward an adaptive fault diagnosis method for rolling bearings that combines the Variational Modal Decomposition (VMD) model and Vision Transformer (ViT) deep learning network model. The objective was to address the difficulty of extracting relevant fault features from bearing vibration signals in environments with strong noise levels. First, an improved VMD+ViT model was used to remove the strong noise from the original bearing signal and adaptively classify the fault types; then, the impacts of modal components and encoder numbers on the accuracy of fault diagnosis were explored. Finally, the proposed methodology was validated by applying it to actual rolling bearing fault data, including both open-source and fault test datasets. The research findings indicated that employing a VMD+ViT integrated model consisting of one modal component with the highest Pearson correlation coefficient and eight encoders resulted in high accuracy in diagnosing faults, even in the presence of high levels of noise in the bearing’s vibration signal. The proposed diagnostic method achieved a diagnostic accuracy of over 92.70% on the open-source bearing dataset with strong interference noise and over 98.62% on the fault test dataset. The proposed method exhibited high accuracy and strong robustness, making it suitable for effectively diagnosing and accurately identifying different categories of rolling bearing faults in mine hoists, even in environments with high levels of noise.

In this paper, we propose an adaptive path tracking algorithm based on the BP (back propagation) neural network to increase the performance of vehicle path tracking in different paths. Specifically, based on the kinematic model of the vehicle, the front wheel steering angle of the vehicle was derived with the PP (Pure Pursuit) algorithm, and related parameters affecting path tracking accuracy were analyzed. In the next step, BP neural networks were introduced and vehicle speed, radius of path curvature, and lateral error were used as inputs to train models. The output of the model was used as the control coefficient of the PP algorithm to improve the accuracy of the calculation of the front wheel steering angle, which is referred to as the BP–PP algorithm in this paper. As a final step, simulation experiments and real vehicle experiments are performed to verify the algorithm’s performance. Simulation experiments show that compared with the traditional path tracking algorithm, the average tracking error of BP–PP algorithm is reduced by 0.025 m when traveling at a speed of 3 m/s on a straight path, and the average tracking error is reduced by 0.27 m, 0.42 m, and 0.67 m, respectively, at a speed of 1.5 m/s with a curvature radius of 6.8 m, 5.5 m, and 4.5 m, respectively. In the real vehicle experiment, an electric patrol vehicle with an autonomous tracking function was used as the experimental platform. The average tracking error was reduced by 0.1 m and 0.086 m on a rectangular road and a large curvature road, respectively. Experimental results show that the proposed algorithm performs well in both simulation and actual scenarios, improves the accuracy of path tracking, and enhances the robustness of the system. Moreover, facing paths with changes in road curvature, the BP–PP algorithm achieved significant improvement and demonstrated great robustness. In conclusion, the proposed BP–PP algorithm reduced the interference of nonlinear factors on the system and did not require complex calculations. Furthermore, the proposed algorithm has been applied to the autonomous driving patrol vehicle in the park and achieved good results.

Humoral immunity confers protection against COVID-19. The longevity of antibody responses after receiving an inactivated vaccine in individuals with previous SARS-CoV-2 infection is unclear. Plasma samples were collected from 58 individuals with previous SARS-CoV-2 infection and 25 healthy donors (HDs) who had been vaccinated with an inactivated vaccine. The neutralizing antibodies (NAbs) and S1 domain-specific antibodies against the SARS-CoV-2 wild-type and Omicron strains and nucleoside protein (NP)-specific antibodies were measured using a chemiluminescent immunoassay. Statistical analysis was performed using clinical variables and antibodies at different timepoints after SARS-CoV-2 vaccination. NAbs targeting the wild-type or Omicron strain were detected in individuals with previous SARS-CoV-2 infection at 12 months after infection (wild-type: 81%, geometric mean (GM): 20.3 AU/mL; Omicron: 44%, GM: 9.4 AU/mL), and vaccination provided further enhancement of these antibody levels (wild-type: 98%, GM: 53.3 AU/mL; Omicron: 75%, GM: 27.8 AU/mL, at 3 months after vaccination), which were significantly higher than those in HDs receiving a third dose of inactivated vaccine (wild-type: 85%, GM: 33.6 AU/mL; Omicron: 45%, GM: 11.5 AU/mL). The level of NAbs in individuals with previous infection plateaued 6 months after vaccination, but the NAb levels in HDs declined continuously. NAb levels in individuals with previous infection at 3 months post-vaccination were strongly correlated with those at 6 months post-vaccination, and weakly correlated with those before vaccination. NAb levels declined substantially in most individuals, and the rate of antibody decay was negatively correlated with the neutrophil-to-lymphocyte ratio in the blood at discharge. These results suggest that the inactivated vaccine induced robust and durable NAb responses in individuals with previous infection up to 9 months after vaccination.

Abstract Background Some ultrasonic soft markers can be found during ultrasound examination. However, the etiology of the fetuses with ultrasonic soft markers is still unknown. This study aimed to evaluate the genetic etiology and clinical value of chromosomal abnormalities and copy number variations (CNVs) in fetuses with ultrasonic soft markers. Methods Among 1131 fetuses, 729 had single ultrasonic soft marker, 322 had two ultrasonic soft markers, and 80 had three or more ultrasonic soft markers. All fetuses underwent conventional karyotyping, followed by single nucleotide polymorphism (SNP) array analysis. Results Among 1131 fetuses with ultrasonic soft markers, 46 had chromosomal abnormalities. In addition to the 46 fetuses with chromosomal abnormalities consistent with the results of the karyotyping analysis, the SNP array identified additional 6.1% (69/1131) abnormal CNVs. The rate of abnormal CNVs in fetuses with ultrasonic soft marker, two ultrasonic soft markers, three or more ultrasonic soft markers were 6.2%, 6.2%, and 5.0%, respectively. No significant difference was found in the rate of abnormal CNVs among the groups. Conclusions Genetic abnormalities affect obstetrical outcomes. The SNP array can fully complement conventional karyotyping in fetuses with ultrasonic soft markers, improve detection rate of chromosomal abnormalities, and affect pregnancy outcomes.

Abstract 2D transition metal dichalcogenides (TMDCs) have been extensively attractive for nano-electronics and nano-optoelectronics due to their unique properties. Especially, WSe2, having bipolar carrier transport ability and sizable bandgap, is a promising candidate for future photodetectors. Here, we report an in-plane WSe2 homojunction formed by the interface gate of the substrate. In this architecture, an insulated h-BN flake was used to make only part of WSe2 flake contact substrate directly. Finally, the structures of WSe2/substrate and WSe2/h-BN/substrate construct an in-plane homojunction. Interestingly, the device can operate in both photovoltaic and photoconductive modes at different biases. As a result, a responsivity of 1.07 A W−1 with a superior detectivity of over 1012 jones and a fast response time of 106 μs are obtained simultaneously. Compared with previously reported methods adopted by chemical doping or electrostatic gating with extra bias voltages, our design provides a more facile and efficient way for the development of high-performance WSe2-based photodetectors.

Fluid flows around a pointed object, e.g. the flow around a triangular prism, are often encountered. In this study, numerical simulation of the flow around a triangular prism was carried out using COMSOL Multiphysics® software. Two cases were considered: the entire area of the triangular prism is fixed; and only the center is fixed. The first case is divided into three different flow models according to the flow state: the separation bubble model, the edge separation model and the attached flow model. The effects of different flow models on the lift coefficient, drag coefficient and Strouhal number were discussed from the perspective of fluid flow. For the second case, the triangular prism periodically rotates while the vortices are separated from the surface. It was found that a stable rotation stage exists after a certain period of time for prisms with different initial positions. The lift and drag coefficients of the triangular prism satisfy the jagged and sinusoidal variation.

Time sensitive networks support deterministic schedules over Ethernet networks. Due to their high determinism, high reliability and high bandwidth, they have been considered as a good choice for the backbone network of industrial internet of things. In industrial applications, the backbone network connects multiple industrial field networks together and has to carry massive real-time packets. However, the off-the-shelf time-sensitive network (TSN) switches can deterministically schedule no more than 1024 real-time flows due to the limited number of schedule table entries. The excess real-time flows have to be delivered by best-effort services because the switch only supports the two scheduling services. The best-effort services can reduce average delay, but cannot guarantee the hard real-time constraints of industrial applications. To make the limited number of schedule table entries support more real-time flows, first, we relax scheduling rules to reduce the requirement for schedule table entries and formulate the process of transmitting packets as a satisfiability modulo theories (SMT) specification. Then, we divide the SMT specification into multiple optimization modulo theories (OMT) specifications so that the execution time of solvers can be reduced to an acceptable range. Second, we propose fast heuristic algorithms that combine schedule tables and packet injection control to eliminate scheduling conflicts. Finally, we conduct extensive evaluations. The evaluation results indicate that, compared to existing algorithms, our proposed algorithm requires only one-twentieth the number of schedule entries to schedule the same flow set.

Ferroptosis is a recently discovered category of programmed cell death. It is much different from other types of cell death such as apoptosis, necrosis and autophagy. The main pathological feature of ferroptosis is the accumulation of iron-dependent lipid peroxidation. The typical changes in the morphological features of ferroptosis include cell volume shrinkage and increased mitochondrial membrane area. The mechanisms of ferroptosis may be mainly related to lipid peroxidation accumulation, imbalance in amino acid antioxidant system, and disturbance of iron metabolism. Besides, hypoxia-inducible factor (HIF), nuclear factor-E2-related factor 2 (Nrf2), and p53 pathway have been demonstrated to be involved in ferroptosis. At present, the molecular mechanisms of ferroptosis pathway are still unmapped. In this review, an outlook has been put forward about the crucial role of apurinic/apyrimidinic endodeoxyribonuclease 1 (APEX1) in the regulation of ferroptosis. APEX1 plays an important role in the regulation of intracellular redox balance and can be used as a potential inhibitor of ferroptotic cell death. Bioinformatics analysis indicated that the mRNA level of APEX1 is decreased in cases of ferroptosis triggered by erastin. Besides, it was found that there was a significant correlation between APEX1 and genes in the ferroptosis pathway. We have discussed the possibility to employ APEX1 inducers or inhibitors in the regulation of ferroptosis as a new strategy for the treatment of various human diseases.

Based on the steel box girder curve incremental launching project of SW ramp bridge in Harbin East Third Ring Road, the geometric alignment and structural internal force of the steel box girder during the incremental launching process were monitored in the whole process. The curve incremental launching coordinate position control method was adopted, and the relevant parameters were modified according to the site construction situation and the initial stress conditions of the girders, and the corrected theoretical value was used as the control and evaluation basis of the monitoring value. The results showed that the original theoretical deflection value was −33.10 mm, the modified theoretical deflection value was −64.10 mm, and the actual monitoring value was −53.20 mm. The modified theoretical value agreed well with the monitoring value, and the error rate between the monitoring value and the theoretical value under each working condition was −17.82%∼14.48%. The geometric alignment and internal force of the steel box girder met the monitoring requirements, ensuring that the steel box girder can meet the design requirements under various working conditions.

The concrete-filled square steel tubular (S-CFST) structure has been widely used as a resistance system against earthquakes due to its good seismic performance. However, the application of the S-CFST structure is limited by its complex joint formulation. To overcome this shortcoming, a sleeve semirigid joint has been proposed, while its seismic performance has not been well examined. This study aims to discuss the behavior of sleeve joints with different parameters under low cyclic loading. The analysis results show that the simulation results of the finite element model established by ABAQUS were in good agreement with the experimental results, which further verified the good energy dissipation performance of the sleeve joint, and gave the design suggestions of the joint under different parameters to promote the engineering application of this type of joint.

When wavelength modulation spectroscopy is used for gas detection in open space, the second harmonic signal is modified due to the interference of optical noise, uncontrollable environmental noise, etc., resulting in the distortion of the line shape, which affects the measurement accuracy. In this study, the harmonic signal distortion is theoretically analyzed, and a distortion correction method of the line shape is proposed based on harmonic detection. By correcting the zero line offset and line shape distortion, the effect of interference is reduced. Furthermore, a monitoring system based on the harmonic technology is established, and a series of experiments are conducted to validate the efficacy of the proposed method. The experimental results reveal that after background noise elimination and zero line offset correction, the maximum fluctuation of the spectral signal in the non-absorption side of the sidelobe is reduced from 0.093 to 0.055 V on the left side and from −0.111 to −0.032 V on the right side. Furthermore, the standard deviation of the peak height ratio before and after the distortion correction is 0.283 and 0.001, respectively, and the standard deviation of the Euclidean distance is 2.601 and 0.007 pm, respectively. The proposed method is compared with traditional 2f concentration inversion and I2f/I1f methods. The mean values for the three methods are 2.80, 2.80, and 2.83 ppm, respectively. The standard deviation of the proposed method is 0.018 ppm, and the Allan analysis result is 2.65 × 10−8 (1 s). These results verify the accuracy of the proposed method.

Various navigation tasks involving dynamic scenarios require mobile robots to meet the requirements of a high planning success rate, fast planning, dynamic obstacle avoidance, and shortest path. PRM (probabilistic roadmap method), as one of the classical path planning methods, is characterized by simple principles, probabilistic completeness, fast planning speed, and the formation of asymptotically optimal paths, but has poor performance in dynamic obstacle avoidance. In this study, we use the idea of hierarchical planning to improve the dynamic obstacle avoidance performance of PRM by introducing D* into the network construction and planning process of PRM. To demonstrate the feasibility of the proposed method, we conducted simulation experiments using the proposed PRM-D* (probabilistic roadmap method and D*) method for maps of different complexity and compared the results with those obtained by classical methods such as SPARS2 (improving sparse roadmap spanners). The experiments demonstrate that our method is non-optimal in terms of path length but second only to graph search methods; it outperforms other methods in static planning, with an average planning time of less than 1 s, and in terms of the dynamic planning speed, our method is two orders of magnitude faster than the SPARS2 method, with a single dynamic planning time of less than 0.02 s. Finally, we deployed the proposed PRM-D* algorithm on a real vehicle for experimental validation. The experimental results show that the proposed method was able to perform the navigation task in a real-world scenario.

Aiming to solve the problem of oil-air lubrication failure caused by the high working temperature of high-speed rolling bearings, this study proposes a method, based on the theory of gas-solid two-phase flow and bearing tribology, of predicting the dynamic temperature rise of nonlinear high-speed rolling bearings under oil-air lubrication conditions. The accuracy of the fluid–structure coupling model is verified by comparing the temperature rise test results of angular contact ball bearing at different speeds. The characteristics of oil-air lubrication circulation and the relationship between the lubrication parameters and the heat balance of the high-speed rolling bearings have been studied. The results show that the gas supply pressure of the system has a significant influence on the continuity and fluctuation of the oil film in the oil pipe nozzle. The initial rise in temperature of the inner and outer rings of the bearing and the fluid domain has a speed threshold value, and the temperature increases linearly with the bearing speed. With the increase in the oil supply and lube oil viscosity of the system, the temperature rise of the outer ring of the bearing increases first, then decreases, and finally increases again. There is an optimal oil supply 5.5 mL and optimize viscosity 68 cSt for the bearing in the work condition.

In VANETs, owing to the openness of wireless communication, it is necessary to change pseudonyms frequently to realize the unlinkability of vehicle identity. Moreover, identity authentication is needed, which is usually completed by digital certificates or a trusted third party. The storage and the communication overhead are high. This paper proposes a triple pseudonym authentication scheme for VANETs based on the Cuckoo Filter and Paillier homomorphic encryption (called TriNymAuth). TriNymAuth applies Paillier homomorphic encryption, a Cuckoo Filter combining filter-level and bucket-level, and a triple pseudonym (homomorphic pseudonym, local pseudonym, and virtual pseudonym) authentication to the vehicle identity authentication scheme. It reduces the dependence on a trusted third party and ensures the privacy and security of vehicle identity while improving authentication efficiency. Experimental results show that the insert overhead of the Cuckoo Filter is about 10 μs, and the query overhead reaches the ns level. Furthermore, TriNymAuth has significant cost advantages, with an OBU enrollment cost of only 0.884 ms. When the data rate in VANETs dr≤ 180 kbps, TriNymAuth has the smallest total transmission delay cost and is suitable for shopping malls and other places with dense traffic.

Aim: Apatinib is an orally administered vascular epidermal growth factor receptor (VEGFR)-tyrosine kinase inhibitors approved for the treatment of advanced gastric adenocarcinoma or gastric esophageal junction adenocarcinoma. Apatinib is predominantly metabolized by CYP3A4/5, followed by CYP2D6. The present study aimed to evaluate the potential drug–drug interaction (DDI) and drug–disease interaction (DDZI) risks of apatinib in Chinese volunteers.Methods: Modeling and simulation were conducted using Simcyp Simulator. The input parameters required for modeling were obtained from literature research or experiments. Then, the developed physiologically based pharmacokinetic (PBPK) models were applied to evaluate single-dose DDI potential in Chinese healthy volunteers with weak and moderate CYP3A inhibitors, strong CYP2D6 inhibitors, as well as CYP3A4 inducers. The DDZI potential was also predicted in patients with hepatic or renal impairment.Results: The developed PBPK models accurately assessed apatinib pharmacokinetics following single-dose administration in Chinese healthy volunteers and cancer patients. The DDI simulation showed 2–4-fold changes in apatinib exposures by moderate CYP3A4 inhibitors and CYP3A4 inducers. A moderate increase of apatinib exposure (1.25–2-fold) was found with strong CYP2D6 inhibitor. In the DDZI simulation with hepatic impairment, the AUC of apatinib was significantly increased by 2.25-fold and 3.04-fold for Child–Pugh B and Child–Pugh C, respectively, with slightly decreased Cmax by 1.54 and 1.67-fold, respectively.Conclusion: The PBPK models developed in the present study would be highly beneficial to quantitatively predict the pharmacokinetic changes of apatinib under different circumstances, which might be difficult to evaluate clinically, so as to avoid some risks in advance.

Background: Today's machine-learning based dermatologic research has largely focused on pigmented/non-pigmented lesions concerning skin cancers. However, studies on machine-learning-aided diagnosis of depigmented non-melanocytic lesions, which are more difficult to diagnose by unaided eye, are very few.Objective: We aim to assess the performance of deep learning methods for diagnosing vitiligo by deploying Convolutional Neural Networks (CNNs) and comparing their diagnosis accuracy with that of human raters with different levels of experience.Methods: A Chinese in-house dataset (2,876 images) and a world-wide public dataset (1,341 images) containing vitiligo and other depigmented/hypopigmented lesions were constructed. Three CNN models were trained on close-up images in both datasets. The results by the CNNs were compared with those by 14 human raters from four groups: expert raters (>10 years of experience), intermediate raters (5–10 years), dermatology residents, and general practitioners. F1 score, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity metrics were used to compare the performance of the CNNs with that of the raters.Results: For the in-house dataset, CNNs achieved a comparable F1 score (mean [standard deviation]) with expert raters (0.8864 [0.005] vs. 0.8933 [0.044]) and outperformed intermediate raters (0.7603 [0.029]), dermatology residents (0.6161 [0.068]) and general practitioners (0.4964 [0.139]). For the public dataset, CNNs achieved a higher F1 score (0.9684 [0.005]) compared to the diagnosis of expert raters (0.9221 [0.031]).Conclusion: Properly designed and trained CNNs are able to diagnose vitiligo without the aid of Wood's lamp images and outperform human raters in an experimental setting.

A submetric spatial resolution Raman optical time-domain reflectometry (ROTDR) temperature sensor assisted by the Wiener deconvolution postprocessing algorithm has been proposed and experimentally demonstrated. Without modifying the typical configuration of the ROTDR sensor and the adopted pump pulse width, the Wiener demodulation algorithm is able to recover temperature perturbations of a smaller spatial scale by deconvoluting the acquired Stokes and anti-Stokes signals. Numerical simulations have been conducted to analyze the spatial resolution achieved by the algorithm. Assisted by the algorithm, a typical ROTDR sensor adopting pump pulses of 20 ns width can realize the distributed temperature sensing with a spatial resolution of 0.5 m and temperature accuracy of 1.99 °C over a 2.1-km sensing fiber.

To better understand the flow features of the particle cluster in a particle bed, discharging of the particle entangled cluster is simulated by the discrete element method (DEM). The particle entangled cluster is composed of eight particles connected by rigid bonds, and the simulated entangled cluster models are divided into two types: axisymmetric u-particles and distorted z-particles. The simulation starts with the closed discharge outlet, and the bonded clusters with different IDs are randomly added from the entrance section. The particles fall freely and accumulate freely in the particle bed. The discharge hole opens after all the particles are stationary for a period. Then, the particles are discharged from the particle bed under gravity. The discharging process has time-dependent bulk-movement behavior. There is not much mixing between layers on the boundary. The vertical end not only makes the packing loose but also intensifies the interaction between particles due to entanglement. Consequently, the discharge features of particle entangled clusters of different included angles were quantified. The results show that the particle discharging speeds depend on the entanglement angle (α of u-particles and η of z-particles) and discharging outlet diameter. A large included angle may play the role of retarding or inhibiting the discharging flow rate. Therefore, the entanglement of particle components also always plays the key role of retarding the discharge.

In the existing heterogeneous cellular networks (HCN),the rapid increasing of small cells caused a problem that the hotspots where users were clustered generated a huge amount of energy consumption.To improve the energy efficiency of the networks,the spatial model was researched.The users in hotspots in the HCN were modeled as the Thomas cluster process,combined with the max mean bias received signal power (max-BRP) strategy to achieve base station load balancing,and the user’s association probability,coverage probability and the network’s energy efficiency were derived using tool from stochastic geometry.The simulation shows that the derived formulas are accurate,and the network’s energy efficiency can be greatly improved by setting appropriate bias factors.

Abstract Background Multidrug resistance (MDR) generally leads to breast cancer treatment failure. The most common mechanism of MDR is the overexpression of ATP-binding cassette (ABC) efflux transporters such as P-glycoprotein (P-gp) that reduce the intracellular accumulation of various chemotherapeutic agents. Celecoxib (CXB), a selective COX-2 inhibitor, can dramatically enhance the cytotoxicity of doxorubicin (DOX) in breast cancer cells overexpressing P-gp. Thus it can be seen that the combination of DOX and CXB maybe obtain synergistic effects against breast cancer by overcoming drug resistance. Results In this study, we designed a pH and redox dual-responsive nanocarrier system to combine synergistic effects of DOX and CXB against drug resistant breast cancer. This nanocarrier system denoted as HPPDC nanoparticles showed good in vitro stability and significantly accelerated drug releases under the acidic and redox conditions. In drug-resistant human breast cancer MCF-7/ADR cells, HPPDC nanoparticles significantly enhanced the cellular uptake of DOX through the endocytosis mediated by CD44/HA specific binding and the down-regulated P-gp expression induced by COX-2 inhibition, and thus notably increased the cytotoxicity and apoptosis-inducing activity of DOX. In MCF-7/ADR tumor-bearing nude mice, HPPDC nanoparticles showed excellent tumor-targeting ability, remarkably enhanced tumor chemosensitivity and reduced COX-2 and P-gp expressions in tumor tissues. Conclusion All results demonstrated that HPPDC nanoparticles can efficiently overcome drug resistance in breast cancer both in vitro and in vivo by combining chemotherapy and COX-2 inhibitor. In a summary, HPPDC nanoparticles show a great potential for combination treatment of drug resistant breast cancer.