SARS-CoV-2 vaccine research and development: Conventional vaccines and biomimetic nanotechnology strategies

The development of a massively producible vaccine against severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),a novel coronavirus,is essential for stopping the current coronavirus disease(COVID-19)pandemic.A vaccine must stimulate effective antibody and T cell responses in vivo to induce long-term protection.Scientific researchers have been developing vaccine candidates for the severe acute respiratory syndrome(SARS)and Middle East respiratory syndrome(MERS)since the outbreaks of these diseases.The prevalence of new biotechnologies such as genetic engineering has shed light on the generation of vaccines against novel viruses.In this review,we present the status of the development of coronavirus vaccines,focusing particularly on the biomimetic nanoparticle technology platform,which is likely to have a major role in future developments of personalized medicine.

Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning

Label-free surface-enhanced Raman scattering(SERS)technique with ultra-sensitivity becomes more and more desirable in biomedical analysis,which is yet hindered by inefficient follow-up data analysis.Here we report an integrative method based on SERS and Artificial Intelligence for Cancer Screening(SERS-AICS)for liquid biopsy such as serum via silver nanowires,combining molecular vibrational signals processing with large-scale data mining algorithm.According to 382 healthy controls and 1582 patients from two independent cohorts,SERS-AICS not only distinguishes pan-cancer patients from health controls with 95.81% overall accuracy and 95.87% sensitivity at 95.40% specificity,but also screens out those samples at early cancer stage.The supereminent efficiency potentiates SERS-AICS a promising tool for detecting cancer with broader types at earlier stage,accompanying with the establishment of a data platform for further deep analysis.

A self-monitoring microneedle patch for light-controlled synergistic treatment of melanoma

Melanoma is the most aggressive and malignant form of skin cancer.Current melanoma treatment methods generally suffer from frequent drug administration as well as difficulty in direct monitoring of drug release.Here,a self-monitoring microneedle(MN)-based drug delivery system,which integrates a dissolving MN patch with aggregation-induced emission(AIE)-active PATC microparticles,is designed to achieve light-controlled pulsatile chemo-photothermal synergistic therapy of melanoma.The PATC polymeric particles,termed D/I@PATC,encapsulate both of chemotherapeutic drug doxorubicin(DOX)and the photothermal agent indocyanine green(ICG).Upon light illumination,PATC gradually dissociates into smaller particles,causing the release of encapsulated DOX and subsequent fluorescence intensity change of PATC particles,thereby not only enabling direct observation of the drug release process under light stimuli,but also facilitating verification of drug release by fluorescence recovery after light trigger.Moreover,encapsulation of ICG in PATC particles displays significant improvement of its photothermal stability both in vitro and in vivo.In a tumor-bearing mouse,the application of one D/I@PATC MN patch combining with two cycles of light irradiation showed excellent controllable chemo-photothermal efficacy and exhibited~97%melanoma inhibition rate without inducing any evident systemic toxicity,suggesting a great potential for skin cancer treatment in clinics.

Serum ficolin-2 concentrations are significantly changed in patients with hepatitis B virus infection and liver diseases

Human ficolin-2 is an important lectin complement pathway activator that is secreted from liver cells and has been implicated as an anti-infection innate immune molecule. However, the role of ficolin-2 protein and its dynamic changes over the course of and in the prognosis of chronic hepatitis B(CHB) and hepatocellular carcinoma(HCC) remain unclear. In this study, we analyzed ficolin-2 protein expression in a cohort of individuals with CHB infection, HCC and cirrhosis. A sandwich enzyme-linked immunosorbent assay(ELISA) method was used to measure serum ficolin-2 concentrations. Ficolin-2 expression in liver tissues was detected by immunohistochemical staining. Serum ficolin-2 concentrations in CHB patients were significantly higher than in healthy controls and HBV carriers. After 48 weeks of routine amelioration liver function treatment, serum ficolin-2 concentrations decreased and were positively correlated with favorable alanine aminotransferase(ALT), HBV DNA and HBe Ag-seroconversion outcomes. Interestingly, we observed much lower expression of serum and intrahepatic ficolin-2 in HCC and cirrhosis compared with healthy controls. Our findings suggest that serum and intrahepatic ficolin-2 levels may be considered one of the indicators for the response of chronic HBV infection, HCC and cirrhosis.

Touchable cell biophysics property recognition platforms enable multifunctional blood smart health care

As a crucial biophysical property,red blood cell(RBC)deformability is pathologically altered in numerous disease states,and biochemical and structural changes occur over time in stored samples of otherwise normal RBCs.However,there is still a gap in applying it further to point-of-care blood devices due to the large external equipment(high-resolution microscope and microfluidic pump),associated operational difficulties,and professional analysis.Herein,we revolutionarily propose a smart optofluidic system to provide a differential diagnosis for blood testing via precise cell biophysics property recognition both mechanically and morphologically.Deformation of the RBC population is caused by pressing the hydrogel via an integrated mechanical transfer device.The biophysical properties of the cell population are obtained by the designed smartphone algorithm.Artificial intelligence-based modeling of cell biophysics properties related to blood diseases and quality was developed for online testing.We currently achieve 100%diagnostic accuracy for five typical clinical blood diseases(90 megaloblastic anemia,78 myelofibrosis,84 iron deficiency anemia,48 thrombotic thrombocytopenic purpura,and 48 thalassemias)via real-world prospective implementation;furthermore,personalized blood quality(for transfusion in cardiac surgery)monitoring is achieved with an accuracy of 96.9%.This work suggests a potential basis for next-generation blood smart health care devices.