Thermal Stability of Skyrmion Tubes in Nanostructured Cuboids.

Magnetic skyrmions in bulk materials are typically regarded as two-dimensional structures. However, they also exhibit three-dimensional configurations, known as skyrmion tubes, that elongate and extend in-depth. Understanding the configurations and stabilization mechanism of skyrmion tubes is crucial for the development of advanced spintronic devices. However, the generation and annihilation of skyrmion tubes in confined geometries are still rarely reported. Here, we present direct imaging of skyrmion tubes in nanostructured cuboids of a chiral magnet FeGe using Lorentz transmission electron microscopy (TEM), while applying an in-plane magnetic field. It is observed that skyrmion tubes stabilize in a narrow field-temperature region near the Curie temperature (Tc). Through a field cooling process, metastable skyrmion tubes can exist in a larger region of the field-temperature diagram. Combining these experimental findings with micromagnetic simulations, we attribute these phenomena to energy differences and thermal fluctuations. Our results could promote topological spintronic devices based on skyrmion tubes.

[Using stacked neural network to improve the auto-segmentation accuracy of Graves' ophthalmopathy target volumes for radiotherapy].

Compared with the previous automatic segmentation neural network for the target area which considered the target area as an independent area, a stacked neural network which uses the position and shape information of the organs around the target area to regulate the shape and position of the target area through the superposition of multiple networks and fusion of spatial position information to improve the segmentation accuracy on medical images was proposed in this paper. Taking the Graves' ophthalmopathy disease as an example, the left and right radiotherapy target areas were segmented by the stacked neural network based on the fully convolutional neural network. The volume Dice similarity coefficient (DSC) and bidirectional Hausdorff distance (HD) were calculated based on the target area manually drawn by the doctor. Compared with the full convolutional neural network, the stacked neural network segmentation results can increase the volume DSC on the left and right sides by 1.7% and 3.4% respectively, while the two-way HD on the left and right sides decrease by 0.6. The results show that the stacked neural network improves the degree of coincidence between the automatic segmentation result and the doctor's delineation of the target area, while reducing the segmentation error of small areas. The stacked neural network can effectively improve the accuracy of the automatic delineation of the radiotherapy target area of Graves' ophthalmopathy.

[Feasibility Study on Location of CT Images Using Convolutional Neural Networks].

OBJECTIVE: To locate CT images by using the deep learning model based on convolutional neural network. METHODS: The AlexNet network was used as a deep learning model, which was preset by the transfer learning approach. Training samples were divided into 4 categories according to the vertebral body parts and labeled, and the data augmentation was used to improve the classification accuracy. RESULTS: The accuracy of image classification after augmentation increased from 94.95% to 97.72%, and the testing time increased from 2.05 s to 3.03 s. CONCLUSIONS: It is feasible to use the convolutional neural network to locate CT images. The data augmentation approach can increase the classification accuracy but also increase the training and testing time.

Achieving Ultralong Room-Temperature Phosphorescence in Covalent Organic Framework System.

The combination of room-temperature phosphorescence (RTP) and covalent organic frameworks (COFs) would give rise to a new class of functional materials with sensing and responsive properties. However, such organic materials have been rarely reported, especially for those with long phosphorescence lifetimes. Here we report the incorporation of RTP emitters into COFs either via chemical decoration or noncovalent doping to achieve ultralong RTP in a COF system. The RTP emitters are designed with small phosphorescence rates and consequently exhibit ultralong phosphorescence lifetimes when nonradiative decay and oxygen quenching are suppressed in COF system. The RTP-COF materials have been found to possess oxygen sensing properties with large response of phosphorescence lifetimes.

Knockdown of MAPK p38-linked genes increases the susceptibility of Chilo suppressalis larvae to various transgenic Bt rice lines.

Bacillus thuringiensis (Bt) toxins have provided exceptional control of agricultural insect pests, however, over reliance on the proteins would potentially contribute to the development of field tolerance. Developing new sustainable insect pest control methods that target the mechanisms underlying Bt tolerance can potentially support the Bt control paradigm while also providing insights into basic insect physiology. The MAPK p38 pathway is strongly associated with Bt tolerance in Chilo suppressalis, a major pest of rice. To gain insights into how this pathway impacts tolerance, high-throughput screening of C. suppressalis larval midguts initially identified eight novel target genes. Increased larval sensitivity to the transgenic cry1Ca rice strain T1C-19 was observed following RNA interference-mediated knockdown of four of the genes, Cscnc, Csgcp, Cszfp26 and CsZMYM1. Similar enhanced sensitivity to the TT51 (expressing Cry1Ab/1Ac) and T2A-1 (expressing Cry2Aa) transgenic rice lines occurred when Cszfp26 and CsZMYM1 were knocked down. All four target genes are downstream of the MAPK p38 pathway but do not participate in negative feedback loop of the pathway. These results implicate Cscnc, Csgcp, Cszfp and CsZMYM1 in the C. suppressalis transgenic cry1Ca rice tolerance mechanism regulated by MAPK p38. These findings further enhance our understanding of the MAPK p38-dependent molecular mechanisms underlying Bt tolerance in C. suppressalis and open new avenues of tolerance management to develop.

A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system.

Predictive real-time control (RTC) strategies are usually more effective than reactive strategies for the intelligent management of urban stormwater storage systems. However, it remains a challenge to ensure the practicality of RTC strategies that use accessible, non-idealized predictive information while improving their efficiency for successive rainfall events instead of specific phases. This study developed a predictive fuzzy logic and rule-based control (PFL-RBC) approach to address the continuous control of individual storage systems. This approach incorporates total rainfall depth forecast information with an intra-storm fuzzy logic system to optimize peak flow control and several rule-based strategies for pre-storm water detention, reuse, and release control. Computational experiments were conducted using a storage tank case study to test the proposed approach under various rainfall conditions and storage sizes. The results showed that PFL-RBC outperformed static rule-based control in infrequent design storms and realistic continuous rainfall events, reducing flood peaks and volumes by 55 %∼87 % and 7 %∼20 %, respectively, and significantly increasing water detention time and reuse volume. Meanwhile, PFL-RBC required less predictive information to achieve a 6 %∼15 % advantage in peak flow control compared to optimized model predictive control. More importantly, PFL-RBC was reliable in the face of input uncertainty, with <25 % performance loss for water quantity control when the realistic forecast error ranged from -50 % to +50 %. These findings suggest that the proposed approach has great potential to enhance the efficiency and practicality of stormwater storage operations.

Joint analysis of vaccination effectiveness and antiviral drug effectiveness for COVID-19: a causal inference approach.

OBJECTIVES: This study aims to estimate the causal effects of oral antivirals and vaccinations in the prevention of all-cause mortality and progression to severe COVID-19 in an integrative setting with both antivirals and vaccinations considered as interventions. METHODS: We identified hospitalized adult patients (i.e. aged 18 or above) in Hong Kong with confirmed SARS-CoV-2 infection between March 16, 2022, and December 31, 2022. An inverse probability-weighted (IPW) Andersen-Gill model with time-dependent predictors was used to address immortal time bias and produce causal estimates for the protection effects of oral antivirals and vaccinations against severe COVID-19. RESULTS: Given prescription is made within 5 days of confirmed infection, nirmatrelvir-ritonavir is more effective in providing protection against all-cause mortality and development into severe COVID-19 than molnupiravir. There was no significant difference between CoronaVac and Comirnaty in the effectiveness of reducing all-cause mortality and progression to severe COVID-19. CONCLUSIONS: The use of oral antivirals and vaccinations causes lower risks of all-cause mortality and progression to severe COVID-19 for hospitalized SARS-CoV-2 patients.

Assessing the Impact of Primary-Series Infection and Booster Vaccination on Protection against Omicron in Hong Kong: A Population-Based Observational Study.

This study aimed to assess the real-world effectiveness of vaccines and hybrid immunity in preventing infections during the Omicron prevalent period in Hong Kong. This study analyzed vaccination records and COVID-19 confirmed case records from 1 January 2022 to 28 January 2023 and included a total of 7,165,862 individuals with vaccination or infection records. This study found that an additional vaccine dose offered increased protection against Omicron BA.1/2 and BA.4 infections for individuals without prior infections in general. Hybrid immunity, acquired through vaccination and natural infection, was found to be significantly stronger than that provided by vaccines alone. The Comirnaty Original/Omicron BA.4/5 bivalent vaccine, introduced in December 2022, was associated with a lower risk of BA.4 infection when administered as a booster dose after three doses of CoronaVac. However, individuals with four doses of the CoronaVac vaccine did not exhibit a significantly lower risk of infection compared to those with three doses during the BA.4 dominant period. This study highlights the importance of promoting booster shot uptake and encouraging vaccination among those who have recovered from COVID-19 infections. The potential immune imprinting effect associated with the Comirnaty and CoronaVac vaccine underscores the need for continued surveillance and research to optimize vaccination strategies for emerging variants.

Enhanced Effects of Intermittent Fasting by Magnetic Fields in Severe Diabetes.

Intermittent fasting (IF) is a convenient dietary intervention for multiple diseases, including type 2 diabetes. However, whether it can be used as a long-term antidiabetic approach is still unknown. Here, we confirm that IF alone is beneficial for both moderate and severe diabetic mice, but its antidiabetic effects clearly diminish at later stages, especially for severe diabetic db/db mice, which have obviously impaired autophagy. We found that static magnetic fields can directly promote actin assembly and boost IF-induced autophagy. Consequently, the pancreatic islet and liver were improved, and the antidiabetic effects of IF were boosted. In fact, at later stages, combined static magnetic field and IF could reduce the blood glucose level of moderate type 2 diabetic mice by 40.5% (P < 0.001) and severe type 2 diabetes by 34.4% (P < 0.05), when IF alone no longer has significant blood glucose reduction effects. Therefore, although IF is generally beneficial for diabetes, our data reveal its insufficiency for late-stage diabetes, which can be compensated by a simple, noninvasive, long-lasting, and nonpharmacological strategy for effective long-term diabetic control.

Erratum to "Enhanced Effects of Intermittent Fasting by Magnetic Fields in Severe Diabetes".

[This corrects the article DOI: 10.34133/2022/9873203.].

Dualistic insulator states in 1T-TaS2 crystals.

While the monolayer sheet is well-established as a Mott-insulator with a finite energy gap, the insulating nature of bulk 1T-TaS2 crystals remains ambiguous due to their varying dimensionalities and alterable interlayer coupling. In this study, we present a unique approach to unlock the intertwined two-dimensional Mott-insulator and three-dimensional band-insulator states in bulk 1T-TaS2 crystals by structuring a laddering stack along the out-of-plane direction. Through modulating the interlayer coupling, the insulating nature can be switched between band-insulator and Mott-insulator mechanisms. Our findings demonstrate the duality of insulating nature in 1T-TaS2 crystals. By manipulating the translational degree of freedom in layered crystals, our discovery presents a promising strategy for exploring fascinating physics, independent of their dimensionality, thereby offering a "three-dimensional" control for the era of slidetronics.

Skyrmion-Bubble Bundles in an X-Type Sr2 Co2 Fe28 O46 Hexaferrite above Room Temperature.

Magnetic skyrmions are spin swirls that possess topological nontriviality and are considered particle-like entities. They are distinguished by an integer topological charge Q. The presence of skyrmion bundles provides an opportunity to explore the range of values for Q, which is crucial for the advancement of topological spintronic devices with multi-Q properties. In this study, a new material candidate, Sr2 Co2 Fe28 O46 hexaferrite of the X-type, which hosts small dipolar skyrmions at room temperature and above is presented. By exploiting reversed magnetic fields from metastable skyrmion bubbles at zero fields, skyrmion-bubble bundles with different interior skyrmion/bubble numbers, topological charges, and morphologies at room temperature are incorporated. These experimental findings are consistently supported by micromagnetic simulations. These results highlight the versatility of topological spin textures in centrosymmetric uniaxial magnets, thereby paving the way for the development of room-temperature topological spintronic devices with multi-Q characteristics.

Exogenously Triggered Nanozyme for Real-Time Magnetic Resonance Imaging-Guided Synergistic Cascade Tumor Therapy.

The uncontrolled treatment process and high concentration of intracellular glutathione compromise the therapeutic efficacies of chemodynamic therapy (CDT). Here, iron oxide nanocrystals embedded in N-doped carbon nanosheets (IONCNs) are designed as a near-infrared light-triggered nanozyme for synergistic cascade tumor therapy. The IONCNs can absorb and convert 980 nm light to local heat, which induces the dissolution of iron oxide for generating Fe2+/Fe3+ in a weak acid environment, apart from thermal ablation of cancer cells. The formed Fe2+ takes on the active site for the Fenton reaction. The formed Fe3+ acts as glutathione peroxidase to magnify oxidative stress, improving the antitumor performance. The IONCNs can be used to visually track the treatment process via magnetic resonance imaging. Such IONCNs demonstrate great potential as an exogenously triggered nanozyme via an integrated cascade reaction for imaging-guided synergistic cancer therapy.

Dose Prediction Models Based on Geometric and Plan Optimization Parameter for Adjuvant Radiotherapy Planning Design in Cervical Cancer Radiotherapy.

The prediction of an additional space for the dose sparing of organs at risk (OAR) in radiotherapy is still difficult. In this pursuit, the present study was envisaged to find out the factors affecting the bladder and rectum dosimetry of cervical cancer. Additionally, the relationship between the dose-volume histogram (DVH) parameters and the geometry and plan dose-volume optimization parameters of the bladder/rectum was established to develop the dose prediction models and guide the planning design for lower OARs dose coverage directly. Thirty volume modulated radiation therapy (VMAT) plans from cervical cancer patients were randomly chosen to build the dose prediction models. The target dose coverage was evaluated. Dose prediction models were established by univariate and multiple linear regression among the dosimetric parameters of the bladder/rectum, the geometry parameters (planning target volume (PTV), volume of bladder/rectum, overlap volume of bladder/rectum (OV), and overlapped volume as a percentage of bladder/rectum volume (OP)), and corresponding plan dose-volume optimization parameters of the nonoverlapping structures (the structure of bladder/rectum outside the PTV (NOS)). Finally, the accuracy of the prediction models was evaluated by tracking d = (predicted dose-actual dose)/actual in additional ten VMAT plans. V 30, V 35, and V 40 of the bladder and rectum were found to be multiple linearly correlated with the relevant OP and corresponding dose-volume optimization parameters of NOS (regression R 2 > 0.99, P < 0.001). The variations of these models were less than 0.5% for bladder and rectum. Percentage of bladder and rectum within the PTV and the dose-volume optimization parameters of NOS could be used to predict the dose quantitatively. The parameters of NOS as a limited condition could be used in the plan optimization instead of limiting the dose and volume of the entire OAR traditionally, which made the plan optimization more unified and convenient and strengthened the plan quality and consistency.

Evaluation on Auto-segmentation of the Clinical Target Volume (CTV) for Graves' Ophthalmopathy (GO) with a Fully Convolutional Network (FCN) on CT Images.

CDATA[Purpose: The aim of this study is to evaluate the accuracy and dosimetric effects for auto- segmentation of the CTV for GO in CT images based on FCN. METHODS: An FCN-8s network architecture for auto-segmentation was built based on Caffe. CT images of 121 patients with GO who have received radiotherapy at the West China Hospital of Sichuan University were randomly selected for training and testing. Two methods were used to segment the CTV of GO: treating the two-part CTV as a whole anatomical region or considering the two parts of CTV as two independent regions. Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD) were used as evaluation criteria. The auto-segmented contours were imported into the original treatment plan to analyse the dosimetric characteristics. RESULTS: The similarity comparison between manual contours and auto-segmental contours showed an average DSC value of up to 0.83. The max HD values for segmenting two parts of CTV separately was a little bit smaller than treating CTV with one label (8.23±2.80 vs. 9.03±2.78). The dosimetric comparison between manual contours and auto-segmental contours showed there was a significant difference (p<0.05) with the lack of dose for auto-segmental CTV. CONCLUSION: Based on deep learning architecture, the automatic segmentation model for small target areas can carry out auto contouring tasks well. Treating separate parts of one target as different anatomic regions can help to improve the auto-contouring quality. The dosimetric evaluation can provide us with different perspectives for further exploration of automatic sketching tools.

Current-Controlled Topological Magnetic Transformations in a Nanostructured Kagome Magnet.

Topological magnetic charge Q is a fundamental parameter that describes the magnetic domains and determines their intriguing electromagnetic properties. The ability to switch Q in a controlled way by electrical methods allows for flexible manipulation of electromagnetic behavior in future spintronic devices. Here, the room-temperature current-controlled topological magnetic transformations between Q = -1 skyrmions and Q = 0 stripes or type-II bubbles in a kagome crystal Fe3 Sn2 are reported. It is shown that reproducible and reversible skyrmion-bubble and skyrmion-stripe transformations can be achieved by tuning the density of nanosecond pulsed current of the order of ≈1010 A m-2 . Further numerical simulations suggest that spin-transfer torque combined with Joule thermal heating effects determine the current-induced topological magnetic transformations.

Preparation and characteristics of graphene oxide-blending PVDF nanohybrid membranes and their applications for hazardous dye adsorption and rejection.

Graphene oxide (GO) and lithium chloride (LiCl) were introduced into poly (vinylidene fluoride) (PVDF) membranes prepared using the immersion precipitation technique. The hydrophilicity, water flux, X-ray diffraction (XRD), zeta potential, SEM and AFM images of membranes were investigated. By adjusting the content of GO from 0wt% to 0.9 wt%, the water flux of PVDF/GO/LiCl nanohybrid membranes varied from 48.4L/m2h to 61.90L/m2h at 100kPa. Because of the synergistic effects of GO and LiCl particles, the surface free energy (|ΔGs|) of M3 (0.5wt% GO) membrane was highest (103.50mJ/m2), indicating that the hydrophilicity of M3 membrane was highest. Rhodamine B aqueous solution was firstly used to determine the adsorption and desorption ability of membranes. After 20 cycles, the decolorization rates and flux recovery ratios of nanohybrid membranes exceeded 80% and 78.2% respectively, and the Rhodamine B rejection of M3 membrane was maximum (67.8%) at 100kPa, which illustrated that nanohybrid membranes can be reused as a better ultrafiltration and dye recovery material, and the characteristic of M3 membrane was best.

[Adsorption Mechanisms Analysis of EfOM on PVDF Ultrafiltration Membranes Modified by SiO2 Using QCM-D and AFM].

To further unravel adsorption mechanisms of effluent organic matter (EfOM) on the PVDF ultrafiltration membranes modified by nano-silica particles from micro perspective during different filtration phases, the membranes were prepared by adjusting the dosage of nano-silicon. The adsorption of EfOM on the surface of the membranes and the interaction between EfOM and the membranes were measured by quartz crystal microbalance with dissipation monitoring (QCM-D) and atomic force microscopy (AFM).The QCM-D results suggested that adsorbing capacity and adsorption rate of EfOM on the hydrophilic surfaces were lower than on the hydrophobic surfaces. Meanwhile, it was found that EfOM underwent adsorption via two steps: In the initial 15 min stage, a rapid adsorption of EfOM accumulated onto the membrane surface; The change in dissipation still occurred when the EfOM adsorption frequency reached balance, which demonstrated that the adsorption of EfOM remained unchanged on the membrane surfaces, and changes in the conformation of adsorption layer still occurred. For the AFM force test, it was found that the EfOM-membranes and EfOM-EfOM interactions declined with the increase of hydrophily, which revealed the essential reason for the decrease of adsorbing capacity and adsorption rate. The combined utilization of QCM-D and AFM effectively explained the effect of modified membranes on adsorption mechanisms of EfOM.

Chemical stability of 2'-deoxy-5-methylisocytidine during oligodeoxynucleotide synthesis and deprotection.

Previous studies have encountered difficulties with degradation of some isocytidine derivatives during solid-phase synthesis and deprotection of oligonucleotides. Here we investigate the degradation of a commonly used derivative, 2'-deoxy-5-methylisocytidine, during oligodeoxynucleotide synthesis and deprotection. A small, but detectable amount of hydrolytic deamination occurred at ca. 0.5% of 2'-deoxy-5-methylisocytidine residues using routine synthesis and deprotection conditions. Depyrimidination, or cleavage of the glycosylic bond, occurred to a far lesser extent during alkaline deprotection than previously suggested. In contrast to model studies of nucleoside monomers, significant depyrimidination was not observed, even at extended incubation times.