Berberine inhibits intracellular Ca2+ signals in mouse pancreatic acinar cells through M3 muscarinic receptors: Novel target, mechanism, and implication.

Berberine, a natural isoquinoline alkaloid, exhibits a variety of pharmacological effects, but the pharmacological targets and mechanisms remain elusive. Here, we report a novel finding that berberine inhibits acetylcholine (ACh)-induced intracellular Ca2+ oscillations, mediated through an inhibition of the muscarinic subtype 3 (M3) receptor. Patch-clamp recordings and confocal Ca2+ imaging were applied to acute dissociated pancreatic acinar cells prepared from CD1 mice to examine the effects of berberine on ACh-induced Ca2+ oscillations. Whole-cell patch-clamp recordings showed that berberine (from 0.1 to 10 µM) reduced ACh-induced Ca2+ oscillations in a concentration-dependent manner, and this inhibition also depended on ACh concentrations. The inhibitory effect of berberine neither occurred in intracellular targets nor extracellular cholecystokinin (CCK) receptors, chloride (Cl-) channels, and store-operated Ca2+ channels. Together, the results demonstrate that berberine directly inhibits the muscarinic M3 receptors, further confirmed by evidence of the interaction between berberine and M3 receptors in pancreatic acinar cells.

Automatic height measurement of central serous chorioretinopathy lesion using a deep learning and adaptive gradient threshold based cascading strategy.

Accurately quantifying the height of central serous chorioretinopathy (CSCR) lesion is of great significance for assisting ophthalmologists in diagnosing CSCR and evaluating treatment efficacy. The manual measurement results dominated by single optical coherence tomography (OCT) B-scan image in clinical practice face the dilemma of weak reference, poor reproducibility, and experience dependence. In this context, this paper constructs two schemes: Scheme Ⅰ draws on the idea of ensemble learning, namely, integrating multiple models for locating starting key point in the height direction of lesion in the inference stage, which appropriately improves the performance of a single model. Scheme Ⅱ designs an adaptive gradient threshold (AGT) technique, followed by the construction of cascading strategy, which involves preliminary location of starting key point through deep learning, and then employs AGT for precise adjustment. This strategy not only achieves effective location for starting key point, but also significantly reduces the large appetite of deep learning model for training samples. Subsequently, AGT continues to play a crucial role in locating the terminal key point in the height direction of lesion, further demonstrating its feasibility and effectiveness. Quantitative and qualitative key point location experiments in the height direction of lesion on 1152 samples, as well as the final height measurement display, consistently conveys the superiority of the constructed schemes, especially the cascading strategy, expanding another potential tool for the comprehensive analysis of CSCR.

Long-term air pollution and adverse meteorological factors might elevate the osteoporosis risk among adult Chinese.

Objective: This study aims to investigate the relationship between exposure to air pollution and adverse meteorological factors, and the risk of osteoporosis. Methods: We diagnosed osteoporosis by assessing bone mineral density through Dual-Energy X-ray absorptiometry in 2,361 participants from Jiangsu, China. Additionally, we conducted physical examinations, blood tests, and questionnaires. We evaluated pollution exposure levels using grid data, considering various lag periods (ranging from one to five years) based on participants' addresses. We utilized logistic regression analysis, adjusted for temperature, humidity, and individual factors, to examine the connections between osteoporosis and seven air pollutants: PM1, PM2.5, PM10, SO2, NO2, CO, and O3. We assessed the robustness of our study through two-pollutant models and distributed lag non-linear models (DLNM) and explored susceptibility using stratified analyses. Results: In Jiangsu, China, the prevalence of osteoporosis among individuals aged 40 and above was found to be 15.1%. A consistent association was observed between osteoporosis and the five-year average exposure to most pollutants, including PM2.5, PM10, CO, and O3. The effects of PM10 and CO remained stable even after adjusting for the presence of a second pollutant. However, the levels of PM1 and PM2.5 were significantly influenced by O3 levels. Individuals aged 60 and above, those with a BMI of 25 or higher, and males were found to be more susceptible to the effects of air pollution. Interestingly, males showed a significantly higher susceptibility to PM1 and PM2.5 compared to females. This study provides valuable insights into the long-term effects of air pollution on osteoporosis risk among the adult population in China. Conclusion: This study indicates a potential association between air pollutants and osteoporosis, particularly with long-term exposure. The risk of osteoporosis induced by air pollution is found to be higher in individuals aged 60 and above, those with a BMI greater than 25, and males. These findings underscore the need for further research and public health interventions to mitigate the impact of air pollution on bone health.

Deterministic Magnetization Switching via Tunable Noncollinear Spin Configurations in Canted Magnets.

Spin obit torque (SOT) driven magnetization switching has been used widely for encoding consumption-efficient memory and logic. However, symmetry breaking under a magnetic field is required to realize the deterministic switching in synthetic antiferromagnets with perpendicular magnetic anisotropy (PMA), which limits their potential applications. Herein, we report all electric-controlled magnetization switching in the antiferromagnetic Co/Ir/Co trilayers with vertical magnetic imbalance. Besides, the switching polarity could be reversed by optimizing the Ir thickness. By using the polarized neutron reflection (PNR) measurements, the canted noncollinear spin configuration was observed in Co/Ir/Co trilayers, which results from the competition of magnetic inhomogeneity. In addition, the asymmetric domain walls demonstrated by micromagnetic simulations result from introducing imbalance magnetism, leading to the deterministic magnetization switching in Co/Ir/Co trilayers. Our findings highlight a promising route to electric-controlled magnetism via tunable spin configuration, improve our understanding of physical mechanisms, and significantly promote industrial applications in spintronic devices.

External Fields Assisted Highly Efficient Oxygen Evolution Reaction of Confined 1T-VSe2 Ferromagnetic Nanoparticles.

As a clean and effective approach, the introduction of external magnetic fields to improve the performance of catalysts has attracted extensive attention. Owing to its room-temperature ferromagnetism, chemical stability, and earth abundance, VSe2 is expected to be a promising and cost-effective ferromagnetic electrocatalyst for the accomplishment of high-efficient spin-related OER kinetics. In this work, a facile pulsed laser deposition (PLD) method combined with rapid thermal annealing (RTA) treatment is used to successfully confine monodispersed 1T-VSe2 nanoparticles in amorphous carbon matrix. As expected, with external magnetic fields of 800 mT stimulation, the confined 1T-VSe2 nanoparticles exhibit highly efficient oxygen evolution reaction (OER) catalytic activity with an overpotential of 228 mV for 10 mA cm-2 and remarkable durability without deactivation after >100 h OER operation. The experimental results together with theoretical calculations illustrate that magnetic fields can facilitate the surface charge transfer dynamics of 1T-VSe2 , and modify the adsorption-free energy of *OOH, thus finally improving the intrinsic activity of the catalysts. This work realizes the application of ferromagnetic VSe2 electrocatalyst in highly efficient spin-dependent OER kinetics, which is expected to promote the application of transition metal chalcogenides (TMCs) in external magnetic field-assisted electrocatalysis.

Study on molecular mechanisms of CD4 dependency and independency of HIV-1 gp120.

Different HIV-1 strains have different antibody neutralization phenotypes (or CD4-dependencies). However, the molecular mechanisms underlying these differences remain to be elucidated. In this study, we constructed gp120 structural models from the CD4-dependent, neutralization-resistant JR-FL strain and the CD4-independent, neutralization-sensitive R2 strain and carried out several conventional molecular dynamics (MD) simulations and free energy landscape (FEL) constructions. Comparative analyses of the MD simulations and FELs indicated that R2 gp120 had higher global structural flexibility and greater conformational diversity than JR-FL gp120. This provides the preconditions for R2 gp120 to adopt a more open conformation than JR-FL gp120. Essential dynamics (ED) analysis showed that the collective motions of R2 gp120 tend towards an open state while those of JR-FL gp120 tend to retain a closed state. Based on conformational selection theory, R2 gp120's more readily sampled open state makes it more sensitive to neutralizing antibodies (or more CD4-independent) than JR-FL gp120, which may explain why the HIV-1 R2 and JR-FL strains show CD4-independent and -dependent phenotypes, respectively. Our study provides thermodynamic and kinetic insights into the CD4-dependent and -independent molecular mechanisms of HIV-1 gp120 and helps shed light on HIV-1 immune evasion.

A multi-modal fundus image based auxiliary location method of lesion boundary for guiding the layout of laser spot in central serous chorioretinopathy therapy.

The lesion boundary of central serous chorioretinopathy (CSCR) is the guarantee to guide the ophthalmologist to accurately arrange the laser spots, so as to enable this ophthalmopathy to be treated precisely. Currently, the accuracy and rapidity of manually locating CSCR lesion boundary in clinic based on single-modal fundus image are limited by imaging quality and ophthalmologist experience, which is also accompanied by poor repeatability, weak reliability and low efficiency. Consequently, a multi-modal fundus image-based lesion boundary auxiliary location method is developed. Firstly, the initial location module (ILM) is employed to achieve the preliminary location of key boundary points of CSCR lesion area on the optical coherence tomography (OCT) B-scan image, then followed by the joint location module (JLM) created based on reinforcement learning for further enhancing the location accuracy. Secondly, the scanning line detection module (SLDM) is constructed to realize the location of lesion scanning line on the scanning laser ophthalmoscope (SLO) image, so as to facilitate the cross-modal mapping of key boundary points. Finally, a simple yet effective lesion boundary location module (LBLM) is designed to assist the automatic cross-modal mapping of key boundary points and enable the final location of lesion boundary. Extensive experiments show that each module can perform well on its corresponding sub task, such as JLM, which makes the correction rate (CR) of ILM increase to 92.11%, comprehensively indicating the effectiveness and feasibility of this method in providing effective lesion boundary guidance for assisting ophthalmologists to precisely arrange the laser spots, and also opening a new research idea for the automatic location of lesion boundary of other fundus diseases.

Identification of and Mechanistic Insights into SARS-CoV-2 Main Protease Non-Covalent Inhibitors: An In-Silico Study.

The indispensable role of the SARS-CoV-2 main protease (Mpro) in the viral replication cycle and its dissimilarity to human proteases make Mpro a promising drug target. In order to identify the non-covalent Mpro inhibitors, we performed a comprehensive study using a combined computational strategy. We first screened the ZINC purchasable compound database using the pharmacophore model generated from the reference crystal structure of Mpro complexed with the inhibitor ML188. The hit compounds were then filtered by molecular docking and predicted parameters of drug-likeness and pharmacokinetics. The final molecular dynamics (MD) simulations identified three effective candidate inhibitors (ECIs) capable of maintaining binding within the substrate-binding cavity of Mpro. We further performed comparative analyses of the reference and effective complexes in terms of dynamics, thermodynamics, binding free energy (BFE), and interaction energies and modes. The results reveal that, when compared to the inter-molecular electrostatic forces/interactions, the inter-molecular van der Waals (vdW) forces/interactions are far more important in maintaining the association and determining the high affinity. Given the un-favorable effects of the inter-molecular electrostatic interactions-association destabilization by the competitive hydrogen bond (HB) interactions and the reduced binding affinity arising from the un-compensable increase in the electrostatic desolvation penalty-we suggest that enhancing the inter-molecular vdW interactions while avoiding introducing the deeply buried HBs may be a promising strategy in future inhibitor optimization.

An Automatic Image Processing Method Based on Artificial Intelligence for Locating the Key Boundary Points in the Central Serous Chorioretinopathy Lesion Area.

Accurately and rapidly measuring the diameter of central serous chorioretinopathy (CSCR) lesion area is the key to judge the severity of CSCR and evaluate the efficacy of the corresponding treatments. Currently, the manual measurement scheme based on a single or a small number of optical coherence tomography (OCT) B-scan images encounters the dilemma of incredibility. Although manually measuring the diameters of all OCT B-scan images of a single patient can alleviate the previous issue, the situation of inefficiency will thus arise. Additionally, manual operation is subject to subjective factors of ophthalmologists, resulting in unrepeatable measurement results. Therefore, an automatic image processing method (i.e., a joint framework) based on artificial intelligence (AI) is innovatively proposed for locating the key boundary points of CSCR lesion area to assist the diameter measurement. Firstly, the initial location module (ILM) benefiting from multitask learning is properly adjusted and tentatively achieves the preliminary location of key boundary points. Secondly, the location task is formulated as a Markov decision process, aiming at further improving the location accuracy by utilizing the single agent reinforcement learning module (SARLM). Finally, the joint framework based on the ILM and SARLM is skillfully established, in which ILM provides an initial starting point for SARLM to narrow the active region of agent, and SARLM makes up for the defect of low generalization of ILM by virtue of the independent exploration ability of agent. Experiments reveal the AI-based method which joins the multitask learning, and single agent reinforcement learning paradigms enable agents to work in local region, alleviating the time-consuming problem of SARLM, performing location task in a global scope, and improving the location accuracy of ILM, thus reflecting its effectiveness and clinical application value in the task of rapidly and accurately measuring the diameter of CSCR lesions.

Differences in the prevalence and risk factors of osteoporosis in chinese urban and rural regions: a cross-sectional study.

BACKGROUND: Bone mineral density (BMD) and prevalence of osteoporosis may differ between urban and rural populations. This study aimed to investigate the differences in BMD characteristics between urban and rural populations in Jiangsu, China. METHODS: A total of 2,711 participants aged 20 years and older were included in the cross-sectional study. Multistage and stratified cluster random sampling was used as the sampling strategy. BMD was measured by the method of dual-energy x-ray absorptiometry (DXA). Data were collected through questionnaires/interview. BMD values at the lumbar spine (L1-L4), femoral neck, total hip, and greater trochanter were collected. Descriptive statistics were used to demonstrate the characteristics of urban and rural participants. Multivariate logistic regression analysis was utilized to analyze the factors that may be associated with osteoporosis in urban and rural populations. RESULTS: Of these participants, 1,540 (50.49%) were females and 1,363 (42.14%) were from urban. The prevalence of osteoporosis in urban and rural populations was 5.52% and 10.33%, respectively. In terms of gender, the prevalence of osteoporosis was 2.68% in males and 13.82% in females. For menopausal status, the prevalence of osteoporosis was 30.34% in postmenopausal females and 4.78% in premenopausal females. In urban populations, older age [adjusted odds ratio (AOR) = 2.36, 95%CI, 2.35-2.36), hypertension (AOR = 1.37, 95%CI, 1.36-1.37), unmarried (AOR = 4.04, 95%CI, 3.99-4.09), smoking everyday (AOR = 2.26, 95%CI, 2.23-2.28), family history of osteoporosis (AOR = 1.66, 95%CI, 1.65-1.67), dyslipidemia (AOR = 1.05, 95%CI, 1.04-1.05), and higher ß-crosslaps (ß-CTX) level (AOR = 1.02, 95%CI, 1.02-1.02) were associated with an increased risk of osteoporosis, while males (AOR = 0.04, 95%CI, 0.04-0.04), higher education level (AOR = 0.95, 95%CI, 0.95-0.95), and aquatic product intake (AOR = 0.99, 95%CI, 0.99-0.99) were related to decreased risk of osteoporosis. Similar results were also observed in rural populations, and (all P < 0.05). CONCLUSION: The prevalence of osteoporosis in rural populations was higher than that in urban populations, and the factors associated with the risk of osteoporosis were similar in urban and rural populations.

Fast Ion Transport Mechanism and Electrochemical Stability of Trivalent Metal Iodide-based Na Superionic Conductors Na3XI6 (X = Sc, Y, La, and In).

The exploration of solid-state sodium superionic conductors with high sodium-ion conductivity, structural and electrochemical stability, and grand interface compatibility has become the key to the next-generation energy storage applications with high energy density and long cycling life. Among them, halide-based compounds exhibit great potential with the higher electronegativity of halogens than that of the sulfur element. In this work, combined with first-principles calculation and ab initio molecular dynamic simulation, the investigation of trivalent metal iodide-based Na superionic conductors C2/m-Na3XI6 (X = Sc, Y, La, and In) was conducted, including the fast ion transport mechanism, structural stability, and interface electrochemical compatibility with electrode materials. Along with the tetrahedral-center saddle site-predominant three-dimensional octahedral-tetrahedral-octahedral diffusion network, C2/m-Na3XI6 possesses the merits of high Na ionic conductivities of 0.36, 0.35, and 0.20 mS cm-1 for Na3ScI6, Na3YI6, and Na3LaI6, respectively. Benefiting from its structural stabilities, C2/m-Na3XI6 exhibits lower interface reaction energy and better electrochemical compatibility in contact with both Na metal and high-voltage poly-anion (fluoro)phosphate cathode materials than those of sulfide-based ones. Our theoretical work provides rational design principles for screening and guiding iodide-based C2/m-Na3XI6 (X = Sc, Y, La, and In) as promising Na superionic conductor candidates used in all-solid-state energy storage applications.

An intelligent location method of key boundary points for assisting the diameter measurement of central serous chorioretinopathy lesion area.

The diameter of central serous chorioretinopathy (CSCR) lesion is one of the important indicators to evaluate the severity of CSCR and the efficacy of corresponding treatment schemes. Traditional manual measurement by ophthalmologists is usually based on a single or a small number of optical coherence tomography (OCT) B-scan images. This measurement scheme may not be convincing, vulnerable to subjective factors and lower efficiency. To alleviate the above situation, this paper proposes an intelligent key boundary point location method for all B-scan images of a single patient to assist in the rapid and accurate diameter measurement of the CSCR lesion area. Firstly, an initial location module (ILM) based on the multi-task learning paradigm is appropriately adjusted and introduced into the key boundary point location task, which preliminarily realizes the rapid location of key boundary points. Secondly, to further ameliorate the ILM, a gradient based correction module (GBCM) is designed, followed by the construction of the cascade model (ILM-GBCM) which improves the location accuracy of key boundary points as a whole. Extensive experiments based on five different convolutional neural network (CNN) backbones are carried out, revealing the feasibility of ILM in this task and the effectiveness of ILM-GBCM. On 912 testing images, the maximum correction ratio reaches 83.66%, and the minimum location time at the image level is as low as 0.1754 s, which not only confirms the necessity of correction operation, but also greatly reduce the time cost of ophthalmologists' manual measurement operation in clinic.

Degradation Effect and Magnetoelectric Transport Properties in CrBr3 Devices.

Two-dimensional (2D) magnetic materials exhibiting unique 2D-limit magnetism have attracted great attention due to their potential applications in ultrathin spintronic devices. These 2D magnetic materials and their heterostructures provide a unique platform for exploring physical effect and exotic phenomena. However, the degradation of most 2D magnetic materials at ambient conditions has so far hindered their characterization and integration into ultrathin devices. Furthermore, the effect of degradation on magnetoelectric transport properties, which is measured for the demonstration of exotic phenomena and device performance, has remained unexplored. Here, the first experimental investigation of the degradation of CrBr3 flakes and its effect on magnetoelectric transport behavior in devices is reported. The extra magnetic compounds derived from oxidation-related degradation play a significant role in the magnetoelectric transport in CrBr3 devices, greatly affecting the magnetoresistance and conductivity. This work has important implications for studies concerning 2D magnetic materials measured, stored, and integrated into devices at ambient conditions.

Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2.

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (RBDCoV2) has a higher binding affinity to the human receptor angiotensin-converting enzyme 2 (ACE2) than the SARS-CoV RBD (RBDCoV). Here, we performed molecular dynamics (MD) simulations, binding free energy (BFE) calculations, and interface residue contact network (IRCN) analysis to explore the mechanistic origin of different ACE2-binding affinities of the two RBDs. The results demonstrate that, when compared to the RBDCoV2-ACE2 complex, RBDCoV-ACE2 features enhanced dynamicsand inter-protein positional movements and increased conformational entropy and conformational diversity. Although the inter-protein electrostatic attractive interactions are the primary determinant for the high ACE2-binding affinities of both RBDs, the significantly enhanced electrostatic attractive interactions between ACE2 and RBDCoV2 determine the higher ACE2-binding affinity of RBDCoV2 than of RBDCoV. Comprehensive comparative analyses of the residue BFE components and IRCNs between the two complexes reveal that it is the residue changes at the RBD interface that lead to the overall stronger inter-protein electrostatic attractive force in RBDCoV2-ACE2, which not only tightens the interface packing and suppresses the dynamics of RBDCoV2-ACE2, but also enhances the ACE2-binding affinity of RBDCoV2. Since the RBD residue changes involving gain/loss of the positively/negatively charged residues can greatly enhance the binding affinity, special attention should be paid to the SARS-CoV-2 variants carrying such mutations, particularly those near or at the binding interfaces with the potential to form hydrogen bonds and/or salt bridges with ACE2.

A Few-Shot Learning-Based Retinal Vessel Segmentation Method for Assisting in the Central Serous Chorioretinopathy Laser Surgery.

Background: The location of retinal vessels is an important prerequisite for Central Serous Chorioretinopathy (CSC) Laser Surgery, which does not only assist the ophthalmologist in marking the location of the leakage point (LP) on the fundus color image but also avoids the damage of the laser spot to the vessel tissue, as well as the low efficiency of the surgery caused by the absorption of laser energy by retinal vessels. In acquiring an excellent intra- and cross-domain adaptability, the existing deep learning (DL)-based vessel segmentation scheme must be driven by big data, which makes the densely annotated work tedious and costly. Methods: This paper aims to explore a new vessel segmentation method with a few samples and annotations to alleviate the above problems. Firstly, a key solution is presented to transform the vessel segmentation scene into the few-shot learning task, which lays a foundation for the vessel segmentation task with a few samples and annotations. Then, we improve the existing few-shot learning framework as our baseline model to adapt to the vessel segmentation scenario. Next, the baseline model is upgraded from the following three aspects: (1) A multi-scale class prototype extraction technique is designed to obtain more sufficient vessel features for better utilizing the information from the support images; (2) The multi-scale vessel features of the query images, inferred by the support image class prototype information, are gradually fused to provide more effective guidance for the vessel extraction tasks; and (3) A multi-scale attention module is proposed to promote the consideration of the global information in the upgraded model to assist vessel localization. Concurrently, the integrated framework is further conceived to appropriately alleviate the low performance of a single model in the cross-domain vessel segmentation scene, enabling to boost the domain adaptabilities of both the baseline and the upgraded models. Results: Extensive experiments showed that the upgraded operation could further improve the performance of vessel segmentation significantly. Compared with the listed methods, both the baseline and the upgraded models achieved competitive results on the three public retinal image datasets (i.e., CHASE_DB, DRIVE, and STARE). In the practical application of private CSC datasets, the integrated scheme partially enhanced the domain adaptabilities of the two proposed models.

Antiferromagnetic Phase Induced by Nitrogen Doping in 2D Cr2S3.

Exploration for the new members of air-stable 2D antiferromagnetic magnets to widen the magnetic families has drawn great attention due to its potential applications in spintronic devices. In addition to seeking the intrinsic antiferromagnets, externally introducing antiferromagnetic ordering in existing 2D materials, such as structural regulation and phase engineering, may be a promising way to modulate antiferromagnetism in the 2D limit. In this work, the in situ nitrogen doping growth of ultrathin 2D Cr2S3 nanoflakes has been achieved. Antiferromagnetic ordering in 2D Cr2S3 nanoflakes can be triggered by nitrogen doping induced new phase (space group P3¯1c). This work provides a new route to realize antiferromagnetism in atomically thin 2D magnets and greatly extend applications of 2D magnets in valleytronics and spintronics.

Interfacial Effect on Photo-Modulated Magnetic Properties of Core/Shell-Structured NiFe/NiFe2O4 Nanoparticles.

Photo-modulated magnetism has become an emerging method for technological applications, such as magneto-optical devices. In this work, by introducing oxygen during rapid thermal annealing, NiFe/NiFe2O4 core/shell nanoparticles were successfully fabricated by pulsed laser deposition. Obvious photo-modulated ferromagnetism was observed in core/shell nanoparticles confined in Al2O3 film. Theoretical and experimental investigations indicate much more photogenerated electrons are captured at the interface of NiFe/NiFe2O4 compared with NiFe nanoparticles due to interfacial effect, resulting in the improved ferromagnetism under light irradiation. This work provides a promising strategy for optical engineering design of optical information storage, high-speed wireless communication, and magneto-optical semiconductor devices.

Research on the Segmentation of Biomarker for Chronic Central Serous Chorioretinopathy Based on Multimodal Fundus Image.

At present, laser surgery is one of the effective ways to treat the chronic central serous chorioretinopathy (CSCR), in which the location of the leakage area is of great importance. In order to alleviate the pressure on ophthalmologists to manually label the biomarkers as well as elevate the biomarker segmentation quality, a semiautomatic biomarker segmentation method is proposed in this paper, aiming to facilitate the accurate and rapid acquisition of biomarker location information. Firstly, the multimodal fundus images are introduced into the biomarker segmentation task, which can effectively weaken the interference of highlighted vessels in the angiography images to the location of biomarkers. Secondly, a semiautomatic localization technique is adopted to reduce the search range of biomarkers, thus enabling the improvement of segmentation efficiency. On the basis of the above, the low-rank and sparse decomposition (LRSD) theory is introduced to construct the baseline segmentation scheme for segmentation of the CSCR biomarkers. Moreover, a joint segmentation framework consisting of the above method and region growing (RG) method is further designed to improve the performance of the baseline scheme. On the one hand, the LRSD is applied to offer the initial location information of biomarkers for the RG method, so as to ensure that the RG method can capture effective biomarkers. On the other hand, the biomarkers obtained by RG are fused with those gained by LRSD to make up for the defect of undersegmentation of the baseline scheme. Finally, the quantitative and qualitative ablation experiments have been carried out to demonstrate that the joint segmentation framework performs well than the baseline scheme in most cases, especially in the sensitivity and F1-score indicators, which not only confirms the effectiveness of the framework in the CSCR biomarker segmentation scene but also implies its potential application value in CSCR laser surgery.

RBD-Modified Bacterial Vesicles Elicited Potential Protective Immunity against SARS-CoV-2.

The disease caused by SARS-CoV-2 infection threatens human health. In this study, we used high-pressure homogenization technology not only to efficiently drive the bacterial membrane to produce artificial vesicles but also to force the fusion protein ClyA-receptor binding domain (RBD) to pass through gaps in the bacterial membrane to increase the contact between ClyA-RBD and the membrane. Therefore, the load of ClyA-RBD on the membrane is substantially increased. Using this technology, we constructed a "ring-like" bacterial biomimetic vesicle (BBV) loaded with polymerized RBD (RBD-BBV). RBD-BBVs injected subcutaneously can accumulate in lymph nodes, promote antigen uptake and processing, and elicit SARS-CoV-2-specific humoral and cellular immune responses in mice. In conclusion, we evaluated the potential of this novel bacterial vesicle as a vaccine delivery system and provided a new idea for the development of SARS-CoV-2 vaccines.

A novel multi-modal fundus image fusion method for guiding the laser surgery of central serous chorioretinopathy.

The angiography and color fundus images are of great assistance for the localization of central serous chorioretinopathy (CSCR) lesions. However, it brings much inconvenience to ophthalmologists because of these two modalities working independently in guiding laser surgery. Hence, a novel fundus image fusion method in non-subsampled contourlet transform (NSCT) domain, aiming to integrate the multi-modal CSCR information, is proposed. Specifically, the source images are initially decomposed into high-frequency and low-frequency components based on NSCT. Then, an improved deep learning-based method is employed for the fusion of low-frequency components, which helps to alleviate the tedious process of manually designing fusion rules and enhance the smoothness of the fused images. The fusion of high-frequency components based on pulse-coupled neural network (PCNN) is closely followed to facilitate the integration of detailed information. Finally, the fused images can be obtained by applying an inverse transform on the above fusion components. Qualitative and quantitative experiments demonstrate the proposed scheme is superior to the baseline methods of multi-scale transform (MST) in most cases, which not only implies its potential in multi-modal fundus image fusion, but also expands the research direction of MST-based fusion methods.