Measurement of Hyperfine Structure and the Zemach Radius in

We investigate the 2^{3}S_{1}-2^{3}P_{J} (J=0, 1, 2) transitions in ^{6}Li^{+} using the optical Ramsey technique and achieve the most precise values of the hyperfine splittings of the 2^{3}S_{1} and 2^{3}P_{J} states, with smallest uncertainty of about 10 kHz. The present results reduce the uncertainties of previous experiments by a factor of 5 for the 2^{3}S_{1} state and a factor of 50 for the 2^{3}P_{J} states, and are in better agreement with theoretical values. Combining our measured hyperfine intervals of the 2^{3}S_{1} state with the latest quantum electrodynamic (QED) calculations, the improved Zemach radius of the ^{6}Li nucleus is determined to be 2.44(2) fm, with the uncertainty entirely due to the uncalculated QED effects of order mα^{7}. The result is in sharp disagreement with the value 3.71(16) fm determined from simple models of the nuclear charge and magnetization distribution. We call for a more definitive nuclear physics value of the ^{6}Li Zemach radius.

Artificial intelligence-driven electrochemical immunosensing biochips in multi-component detection.

Electrochemical Immunosensing (EI) combines electrochemical analysis and immunology principles and is characterized by its simplicity, rapid detection, high sensitivity, and specificity. EI has become an important approach in various fields, such as clinical diagnosis, disease prevention and treatment, environmental monitoring, and food safety. However, EI multi-component detection still faces two major bottlenecks: first, the lack of cost-effective and portable detection platforms; second, the difficulty in eliminating batch differences and accurately decoupling signals from multiple analytes. With the gradual maturation of biochip technology, high-throughput analysis and portable detection utilizing the advantages of miniaturized chips, high sensitivity, and low cost have become possible. Meanwhile, Artificial Intelligence (AI) enables accurate decoupling of signals and enhances the sensitivity and specificity of multi-component detection. We believe that by evaluating and analyzing the characteristics, benefits, and linkages of EI, biochip, and AI technologies, we may considerably accelerate the development of EI multi-component detection. Therefore, we propose three specific prospects: first, AI can enhance and optimize the performance of the EI biochips, addressing the issue of multi-component detection for portable platforms. Second, the AI-enhanced EI biochips can be widely applied in home care, medical healthcare, and other areas. Third, the cross-fusion and innovation of EI, biochip, and AI technologies will effectively solve key bottlenecks in biochip detection, promoting interdisciplinary development. However, challenges may arise from AI algorithms that are difficult to explain and limited data access. Nevertheless, we believe that with technological advances and further research, there will be more methods and technologies to overcome these challenges.

Expression Pattern of Cytokines in Patients with Chronic Hepatitis B Receiving PEGinterferon Therapy.

Purpose: Chronic hepatitis B virus (CHB) infection is a worldwide health problem. Polyethylene glycol (PEG)ylated interferon (PEG-IFN) is an available therapy for CHB that has antiviral and immunomodulatory effects. However, PEG-IFN therapy is limited by the fact that only a subset of patients show a sustained response, its severe side effects, and high cost. The aim of this study was to explore novel biomarkers for the early prediction of PEG-IFN treatment response and to uncover its underlying mechanism. Patients and Methods: We enrolled 10 paired patients with Hepatitis B e antigen (HBeAg)-positive CHB who received PEG-IFN-α2a monotherapy. Patient serum samples were collected at 0, 4, 12, 24, and 48 weeks and serum samples were collected from eight healthy people as healthy controls. For confirmation, we enrolled 27 patients with HBeAg-positive CHB receiving PEG-IFN therapy and serum samples at 0 and 12 weeks were obtained. Serum samples were analyzed using Luminex technology. Results: Among 27 assessed cytokines, 10 cytokines were identified to have high expression levels. Among them, six cytokines had significant differences in their levels between the patients with HBeAg-positive CHB and the healthy controls (P < 0.05). Potentially, treatment response could be predicted using the early time points of 4, 12, and 24 weeks. Moreover, after 12 weeks of PEG-IFN treatment, increased levels of pro-inflammatory cytokines and decreased levels of anti-inflammatory cytokines were observed. The fold change of IP-10 between 12 weeks and 0 weeks correlated with the decrease in ALT levels from 0 to 12 weeks (r = 0.2675, P = 0.0024). Conclusion: In patients with CHB, we observed a certain pattern in the levels of cytokines during treatment with PEG-IFN, and the cytokine IP-10 might be a potential biomarker for treatment response.

A Newly Identified Spike Protein Targeted Linear B-Cell Epitope Based Dissolvable Microneedle Array Successfully Eliciting Neutralizing Activities against SARS-CoV-2 Wild-Type Strain in Mice.

Vaccination is a cost-effective medical intervention. Inactivated whole virusor large protein fragments-based severe acute respiratory syndrome coronavirus (SARS-CoV-2) vaccines have high unnecessary antigenic load to induce allergenicity and/orreactogenicity, which can be avoided by peptide vaccines of short peptide fragments that may induce highly targeted immune response. However, epitope identification and peptide delivery remain the major obstacles in developing peptide vaccines. Here, a multi-source data integrated linear B-cell epitope screening strategy is presented and a linear B-cell epitope enriched hotspot region is identified in Spike protein, from which a monomeric peptide vaccine (Epitope25) is developed and applied to subcutaneously immunize wildtype BALB/c mice. Indirect ELISA assay reveals specific and dose-dependent binding between Epitope25 and serum IgG antibodies from immunized mice. The neutralizing activity of sera from vaccinated mice is validated by pseudo and live SARS-CoV-2 wild-type strain neutralization assays. Then a dissolvable microneedle array (DMNA) is developed to pain-freely deliver Epitope25. Compared with intramuscular injection, DMNA and subcutaneous injection elicit neutralizing activities against SARS-CoV-2 wild-type strain as demonstrated by live SARS-CoV-2 virus neutralization assay. No obvious damages are found in major organs of immunized mice. This study may lay the foundation for developing linear B-cell epitope-based vaccines against SARS-CoV-2.

Development of an AlphaLISA assay for sensitive and accurate detection of influenza B virus.

Objective: Influenza B virus (IBV) is highly contagious, spreads rapidly, and causes seasonal epidemic respiratory disease in the human population, especially in immunocompromised people and young children. Clinical manifestations in this high-risk population are often more severe than in immunocompetent hosts and sometimes atypical. Therefore, rapid, and accurate detection of IBV is important. Methods: An amplified luminescent proximity homogeneous assay linked immunosorbent assay (AlphaLISA) was developed for detection of IBV by optimizing the ratio of IBV antibody-labeled receptor beads, streptavidin-conjugated donor beads and biotinylated IBV antibody, as well as the optimal temperature and time conditions for incubation. Assay sensitivity, specificity and reproducibility were evaluated. A total of 228 throat swab samples and inactivated influenza B virus were tested by AlphaLISA and lateral flow colloidal gold-based immunoassay (LFIA). Results: AlphaLISA produced the best results for detection of inactivated influenza B virus when IBV antibody-labeled acceptor beads were 50 µg/ mL, streptavidin-conjugated donor beads were 40 µg/mL, and biotinylated IBV antibody was 0.5 µg/mL at 37°C for 15-10 min. Under these conditions, AlphaLISA had a limit of detection of 0.24 ng/mL for the detection of influenza B nucleoprotein, did not cross react with other common respiratory viruses, and showed good reproducibility with inter-assay coefficient of variation (CV) and intra-assay CV < 5%. The results of 228 clinical throat swab samples showed good agreement between AlphaLISA and LFIA (Kappa = 0.982), and AlphaLISA showed better sensitivity than LFIA for detecting inactivated influenza B virus. Conclusion: AlphaLISA showed higher sensitivity and throughput in the detection of IBV and can be used for IBV diagnosis and epidemic control.

Transformer-based multilevel region and edge aggregation network for magnetic resonance image segmentation.

To improve the quality of magnetic resonance (MR) image edge segmentation, some researchers applied additional edge labels to train the network to extract edge information and aggregate it with region information. They have made significant progress. However, due to the intrinsic locality of convolution operations, the convolution neural network-based region and edge aggregation has limitations in modeling long-range information. To solve this problem, we proposed a novel transformer-based multilevel region and edge aggregation network for MR image segmentation. To the best of our knowledge, this is the first literature on transformer-based region and edge aggregation. We first extract multilevel region and edge features using a dual-branch module. Then, the region and edge features at different levels are inferred and aggregated through multiple transformer-based inference modules to form multilevel complementary features. Finally, the attention feature selection module aggregates these complementary features with the corresponding level region and edge features to decode the region and edge features. We evaluated our method on a public MR dataset: Medical image computation and computer-assisted intervention atrial segmentation challenge (ASC). Meanwhile, the private MR dataset considered infrapatellar fat pad (IPFP). Our method achieved a dice score of 93.2% for ASC and 91.9% for IPFP. Compared with other 2D segmentation methods, our method improved a dice score by 0.6% for ASC and 3.0% for IPFP.

Multiresolution Mutual Assistance Network for Cardiac Magnetic Resonance Images Segmentation.

The automatic segmentation of cardiac magnetic resonance (MR) images is the basis for the diagnosis of cardiac-related diseases. However, the segmentation of cardiac MR images is a challenging task due to the inhomogeneity of MR images intensity distribution and the unclear boundaries between adjacent tissues. In this paper, we propose a novel multiresolution mutual assistance network (MMA-Net) for cardiac MR images segmentation. It is mainly composed of multibranch input module, multiresolution mutual assistance module, and multilabel deep supervision. First, the multibranch input module helps the network to extract local and global features more pertinently. Then, the multiresolution mutual assistance module implements multiresolution feature interaction and progressively improves semantic features to more completely express the information of the tissue. Finally, the multilabel deep supervision is proposed to generate the final segmentation map. We compare with state-of-the-art medical image segmentation methods on the medical image computing and computer-assisted intervention (MICCAI) automated cardiac diagnosis challenge datasets and the MICCAI atrial segmentation challenge datasets. The mean dice scores of our method in the left atrium, right ventricle, myocardium, and left ventricle are 0.919, 0.920, 0.881, and 0.960, respectively. The analysis of evaluation indicators and segmentation results shows that our method achieves the best performance in cardiac magnetic resonance images segmentation.

Multiresolution Aggregation Transformer UNet Based on Multiscale Input and Coordinate Attention for Medical Image Segmentation.

The latest medical image segmentation methods uses UNet and transformer structures with great success. Multiscale feature fusion is one of the important factors affecting the accuracy of medical image segmentation. Existing transformer-based UNet methods do not comprehensively explore multiscale feature fusion, and there is still much room for improvement. In this paper, we propose a novel multiresolution aggregation transformer UNet (MRA-TUNet) based on multiscale input and coordinate attention for medical image segmentation. It realizes multiresolution aggregation from the following two aspects: (1) On the input side, a multiresolution aggregation module is used to fuse the input image information of different resolutions, which enhances the input features of the network. (2) On the output side, an output feature selection module is used to fuse the output information of different scales to better extract coarse-grained information and fine-grained information. We try to introduce a coordinate attention structure for the first time to further improve the segmentation performance. We compare with state-of-the-art medical image segmentation methods on the automated cardiac diagnosis challenge and the 2018 atrial segmentation challenge. Our method achieved average dice score of 0.911 for right ventricle (RV), 0.890 for myocardium (Myo), 0.961 for left ventricle (LV), and 0.923 for left atrium (LA). The experimental results on two datasets show that our method outperforms eight state-of-the-art medical image segmentation methods in dice score, precision, and recall.

Digital long-term laser frequency stabilization with an optical frequency comb.

Laser frequency stabilization plays an important role in high-precision spectroscopic measurements. Since high-accuracy commercial wavemeters became available, wavemeter-based frequency stabilization has found a broad application due to its convenience, flexibility, and wide applicability. However, such stabilization schemes frequently suffer from long-term drift, since the accuracy of the wavelength measurement of a wavemeter is affected by ambient temperature fluctuation. In this work, we demonstrate that such long-term drift can be suppressed by regularly calibrating the frequency of a wavemeter-locked laser utilizing an optical frequency comb, which has much better long-term stability. Under this dual-referenced locking scheme, the Allan deviation is reduced to 3.5 E-12 at 4000 s for a fiber laser operated at 548 nm, which when used in the optical Ramsey spectroscopic measurement of 7Li+, reduces the standard deviation by as much as 40%, compared to the case when only wavemeter locking is applied.

RON in hepatobiliary and pancreatic cancers: Pathogenesis and potential therapeutic targets.

The receptor protein tyrosine kinase RON belongs to the c-MET proto-oncogene family. Research has shown that RON has a role in cancer pathogenesis, which places RON on the frontline of the development of novel cancer therapeutic strategies. Hepatobiliary and pancreatic (HBP) cancers have a poor prognosis, being reported as having higher rates of cancer-related death. Therefore, to combat these malignant diseases, the mechanism underlying the aberrant expression and signaling of RON in HBP cancer pathogenesis, and the development of RON as a drug target for therapeutic intervention should be investigated. Abnormal RON expression and signaling have been identified in HBP cancers, and also act as tumorigenic determinants for HBP cancer malignant behaviors. In addition, RON is emerging as an important mediator of the clinical prognosis of HBP cancers. Thus, not only is RON significant in HBP cancers, but also RON-targeted therapeutics could be developed to treat these cancers, for example, therapeutic monoclonal antibodies and small-molecule inhibitors. Among them, antibody-drug conjugates have become increasingly popular in current research and their potential as novel anti-cancer biotherapeutics will be determined in future clinical trials.

Precision Calculation of Hyperfine Structure and the Zemach Radii of

The hyperfine structures of the 2^{3}S_{1} states of the ^{6}Li^{+} and ^{7}Li^{+} ions are investigated theoretically to extract the Zemach radii of the ^{6}Li and ^{7}Li nuclei by comparing with precision measurements. The obtained Zemach radii are larger than the previous values of Puchalski and Pachucki [Phys. Rev. Lett. 111, 243001 (2013)PRLTAO0031-900710.1103/PhysRevLett.111.243001] and disagree with them by about 1.5 and 2.2 standard deviations for ^{6}Li and ^{7}Li, respectively. Furthermore, our Zemach radius of ^{6}Li differs significantly from the nuclear physics value, derived from the nuclear charge and magnetic radii [Phys. Rev. A 78, 012513 (2008)PLRAAN1050-294710.1103/PhysRevA.78.012513] by more than 6σ, indicating an anomalous nuclear structure for ^{6}Li. The conclusion that the Zemach radius of ^{7}Li is about 40% larger than that of ^{6}Li is confirmed. The obtained Zemach radii are used to calculate the hyperfine splittings of the 2^{3}P_{J} states of ^{6,7}Li^{+}, where an order of magnitude improvement over the previous theory has been achieved for ^{7}Li^{+}.

Adaptation of SARS-CoV-2 in BALB/c mice for testing vaccine efficacy.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has prioritized the development of small-animal models for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We adapted a clinical isolate of SARS-CoV-2 by serial passaging in the respiratory tract of aged BALB/c mice. The resulting mouse-adapted strain at passage 6 (called MASCp6) showed increased infectivity in mouse lung and led to interstitial pneumonia and inflammatory responses in both young and aged mice after intranasal inoculation. Deep sequencing revealed a panel of adaptive mutations potentially associated with the increased virulence. In particular, the N501Y mutation is located at the receptor binding domain (RBD) of the spike protein. The protective efficacy of a recombinant RBD vaccine candidate was validated by using this model. Thus, this mouse-adapted strain and associated challenge model should be of value in evaluating vaccines and antivirals against SARS-CoV-2.

Investigation of HIV-1 Gag binding with RNAs and lipids using Atomic Force Microscopy.

Atomic Force Microscopy was utilized to study the morphology of Gag, ΨRNA, and their binding complexes with lipids in a solution environment with 0.1Å vertical and 1nm lateral resolution. TARpolyA RNA was used as a RNA control. The lipid used was phospha-tidylinositol-(4,5)-bisphosphate (PI(4,5)P2). The morphology of specific complexes Gag-ΨRNA, Gag-TARpolyA RNA, Gag-PI(4,5)P2 and PI(4,5)P2-ΨRNA-Gag were studied. They were imaged on either positively or negatively charged mica substrates depending on the net charges carried. Gag and its complexes consist of monomers, dimers and tetramers, which was confirmed by gel electrophoresis. The addition of specific ΨRNA to Gag is found to increase Gag multimerization. Non-specific TARpolyA RNA was found not to lead to an increase in Gag multimerization. The addition PI(4,5)P2 to Gag increases Gag multimerization, but to a lesser extent than ΨRNA. When both ΨRNA and PI(4,5)P2 are present Gag undergoes comformational changes and an even higher degree of multimerization.

A low-energy compact Shanghai-Wuhan electron beam ion trap for extraction of highly charged ions.

A low-energy, compact, and superconducting electron beam ion trap (the Shanghai-Wuhan EBIT or SW-EBIT) for extraction of highly charged ions is presented. The magnetic field in the central drift tube of the SW-EBIT is approximately 0.21 T produced by a pair of high-temperature superconducting coils. The electron-beam energy of the SW-EBIT is in the range of 30-4000 eV, and the maximum electron-beam current is up to 9 mA. Acting as a source of highly charged ions, the ion-beam optics for extraction is integrated, including an ion extractor and an einzel lens. A Wien filter is then used to measure the charge-state distribution of the extracted ions. In this work, the tungsten ions below the charge state of 15 have been produced, extracted, and analyzed. The charge-state distributions and spectra in the range of 530-580 nm of tungsten ions have been measured simultaneously with the electron-beam energy of 279 eV and 300 eV, which preliminarily indicates that the 549.9 nm line comes from W14+.

Crystal-to-Gel Transformation Stimulated by a Solid-State E→Z Photoisomerization.

The molecule (E)-(5-(3-anthracen-9-yl-allylidene)-2,2-dimethyl-[1,3] dioxane-4,6-dione) (E-AYAD) undergoes E→Z photoisomerization. In the solid state, this photoisomerization process can initiate a physical transformation of the crystal that is accompanied by a large volume expansion (ca. 10 times), loss of crystallinity, and growth of large pores. This physical change requires approximately 10 % conversion of the E isomer to the Z isomer and results in a gel-like solid with decreased stiffness that still retains its mechanical integrity. The induced porosity allows the expanding gel to engulf superparamagnetic nanoparticles from the surrounding liquid. The trapped superparamagnetic nanoparticles impart a magnetic susceptibility to the gel, allowing it to be moved by a magnetic field. The photoinduced phase transition, starting with a compact crystalline solid instead of a dilute solution, provides a new route for in situ production of functional porous materials.

Saturated fluorescence spectroscopy measurement apparatus based on metastable Li+ beam with low energy.

The apparatus for fluorescence spectroscopy measurement is developed to determine the fine structure (FS)/hyperfine structure (HFS) splittings of 1s2p 3PJ(J=0,1,2) states of Li+. The instrument is composed of a low energy Li+ ion source and a saturated fluorescence spectroscopic probing system. A low energy Li+ ion source, containing 1.8(7)% of 1s2s 3S1 metastable ions with an energy of ∼500 eV, is obtained by an electron bombardment process. The ion current can stay more than 250 h with the variation of ∼0.3%, and the divergence of ion beam is ∼0.5 mrad. The symmetric profile of Lamb dip signals of 1s2s 3S1--1s2p 3PJ transitions with linewidths of ∼50 MHz are obtained after subtracting Doppler background from the saturated fluorescence signals. A back-and-forth scan method is adopted to determine the FS/HFS splittings of 1s2p 3PJ states. Under these conditions, as a preliminary test, several splittings of 7Li+ are measured. The statistical uncertainties of the FS/HFS splittings are estimated to be less than 50 kHz, and the results are one order of magnitude better than previous results. The apparatus is feasible to precisely determine the splittings of energy levels of alkali and alkaline earth ions.

Melatonin inhibits the migration of human gastric carcinoma cells at least in part by remodeling tight junction.

The recurrence and metastasis is one of the major reasons for malignant tumor treatment failure. Melatonin, a naturally occuring hormone, could reduce the recurrence and metastasis of various tumors. However, the underlying molecular mechanisms of melatonin on tumor metastasis inhibition have not been fully elucidated. In the present study, we explored the impact of melatonin on the migratory capability of human gastric carcinoma cells using wound healing assay, and further investigated if the inhibition on migration ability of melatonin was embodied by relocating tight junction proteins zo-1 and occludin onto the cells surface to remodel tight junction structure. Immunofluorescence assay and Western blot analysis were performed to detect the expression and cell location of the tight junction proteins. The migration distance was decreased as the cells were treated with melatonin. And melatonin increased the membrane location of tight junction proteins, zo-1 and occludin, showed by immunofluorescence staining and Western blot analysis. The results we got show that melatonin makes tight junction proteins anchored more on the cells membrane to remodel cells tight junction, which increase cells adhesion and decrease motility, resulting in the inhibition of gastric cancer cells migration and metastasis ability.