Key elements and checklist of shared decisionmaking conversation on life-sustaining treatment in emergency:a multispecialty study from China

BACKGROUND:Shared decision-making(SDM)has broad application in emergencies.Most published studies have focused on SDM for a certain disease or expert opinions on future research gaps without revealing the full picture or detailed guidance for clinical practice.This study is to investigate the optimal application of SDM to guide life-sustaining treatment(LST)in emergencies.METHODS:This study was a prospective two-round Delphi consensus-seeking survey among multiple stakeholders at the China Consortium of Elite Teaching Hospitals for Residency Education.Participants were identified based on their expertise in medicine,law,administration,medical education,or patient advocacy.All individual items and questions in the questionnaire were scored using a 5-point Likert scale,with responses ranging from"very unimportant"(a score of 1)to"extremely important"(a score of 5).The percentages of the responses that had scores of 4-5on the 5-point Likert scale were calculated.A Kendall’s W coefficient was calculated to evaluate the consensus of experts.RESULTS:A two-level framework consisting of 4 domains and 22 items as well as a ready-touse checklist for the informed consent process for LST was established.An acceptable Kendall’s W coefficient was achieved.CONCLUSION:A consensus-based framework supporting SDM during LST in an emergency department can inform the implementation of guidelines for clinical interventions,research studies,medical education,and policy initiatives.

有机化学糖类化合物教学的思政案例设计与实践

为充分挖掘有机化学课程糖类化合物章节中的思政元素,发挥专业课程在立德树人方面的重要作用,我们对该章节的学习目标进行了梳理,并据此设计了学习内容,构建了以糖类化合物知识为主体,以糖的结构和合成研究史、有机化学学科思想、中国在糖化学研究中的贡献等人文素材为主导的糖类化合物章节教学体系。

Coping with extremes:lowered myocardial phosphofructokinase activities and glucose content but increased fatty acids content in highland Eurasian Tree Sparrows

Background:Efficient and selective utilization of metabolic substrates is one of the key strategies in high-altitude animals to cope with hypoxia and hypothermia.Previous findings have shown that the energy substrate utilization of highland animals varies with evolutionary history and phylogeny.The heart is a proxy for the cardiopulmonary system,and the metabolic substrate utilization in the myocardium is also under the strong selective pressure of chronically hypoxic and hypothermic environments.However,little information is available on the physiological adjustments in relation to metabolic substrate utilization in the myocardium for coping with high-altitude environments.Methods:We compared the metabolic enzyme activities,including hexokinase(HK),phosphofructokinase(PFK),pyruvate kinase(PK),citrate synthase(CS),carnitine palmitoyl transferase 1(CPT-1),lactic dehydrogenase(LDH),and creatine kinase(CK),and metabolic substrate contents including glucose(Glu),triglyceride(TG),and free fatty acid(FFA)in the myocardium of a typical human commensal species,Eurasian Tree Sparrows(Passer montanus)between the Qinghai-Tibet Plateau(the QTP,3230 m)and low altitude population(Shijiazhuang,80 m),and between sexes.Results:Among the seven metabolic enzymes and three substrates investigated,we identified no significant differences in PK,CPT-1,HK,CS,LDH,and CK activities and TG content of the myocardium between high and low altitude populations.However,the QTP sparrows had significantly lower Glu content and PFK activities but higher FFA content relative to their lowland counterparts.In addition,male sparrows had higher myocardial HK and CS activities relative to females,independent of altitude.Conclusions:Our results showed that the QTP sparrows elevated fatty acid utilization rather than glucose preference in the myocardium relative to lowland counterpart,which contributes to uncovering both the physiological adjustments for adapting to the extreme conditions of the QTP,intraspecifically.

Life-history dependent relationships between plasma alkaline phosphatase activity and body condition in male Eurasian Tree Sparrows

Background: In temperate-breeding birds, individuals must adjust their physiological states from one life-history stage to another in response to changing conditions to maximize ecological fitness. Previous evidences have shown that body mass, size-corrected mass(SCM), and hematocrit(Hct) could be used as estimates of the energetic state of individuals to illustrate life-history trade-offs and individual quality in field physiology. Plasma alkaline phosphatase(ALP) plays critical roles in regulating the metabolism of energy but very limited information is known on its link with body mass or Hct.Methods: We determined the changes of plasma ALP levels in both early breeding and wintering stages of male Eurasian Tree Sparrows(Passer montanus), and examined the relationships between ALP and body mass, SCM, and Hct of the birds.Results: Our study showed that(1) in male Eurasian Tree Sparrows, body mass did not vary with life-history stage but plasma ALP activity significantly increased in the wintering stage compared to the breeding stage;(2) ALP activity was not correlated with individual body mass but was positively correlated with individual SCM and Hct. Such positive correlations, however, only occurred in the wintering but not in the breeding stages.Conclusions: Our results suggest that plasma ALP activities in free-living birds can be used as one of the indicators o body condition or nutritional status for analyzing individual variation in the wintering but not in the breeding stages. The life-history dependent relationships between plasma ALP activity and body condition may contribute to our better understanding of the trade-off between individual survival and reproduction in free-living animals.

Estimating Design Loads for Floating Structures Using Environmental Contours

Nonlinear time-domain simulations are often used to predict the structural response at the design stage to ensure the acceptable operation and/or survival of floating structures under extreme conditions.An environmental contour(EC)is commonly employed to identify critical sea states that serve as the input for numerical simulations to assess the safety and performance of marine structures.In many studies,marginal and conditional distributions are defined to construct bivariate joint probability distributions for variables,such as significant wave height and zero-crossing period.Then,ECs can be constructed using the inverse first-order reliability method(IFORM).This study adopts alternative models to describe the generalized dependence structure between environmental variables using copulas and discusses the Nataf transformation as a special case.ECs are constructed using measured wave data from moored buoys.Derived design loads are applied on a semisubmersible platform to assess possible differences.In addition,a linear interpolation scheme is utilized to establish a parametric model using short-term extreme tension distribution parameters and wave data,and the long-term tension response is estimated using Monte Carlo simulation.A 3D IFORM-based approach,in which the short-term extreme response that is ignored in the EC approach is used as the third variable,is proposed to help establish accurate design loads with increased accuracy.Results offer a clear illustration of the extreme responses of floating structures based on different models.

Manufactured nanoparticle:A prediction model for understanding PM2.5 toxicity to human

Epidemiological studies have demonstrated that chronic exposure to polluted concentration of fine ambient particulate matter(PM2.5)can induce markedly harmful effects on human health,however,an enormous research effort is still need to the comprehensive understanding of PM2.5 induction of new negative health outcomes.Recently,Maher and colleges[1]from Environmental Magnetism and Paleomagnetism at Lancaster University

Durable and enhanced immunity against SARS-CoV-2 elicited by manganese nanoadjuvant formulated subunit vaccine

Dear editor,Vaccines are the most efficient and effective means to prevent infectious diseases,but improving the long-term protective efficacy is still a major challenge in contemporary vaccine development.1 The waning immunity varies depending on the diversification of the pathogen and the number of booster doses.1 Strategies to overcome this warrant is using adjuvants that amplify the immune response,and drive the production of memory B and T cells or long-lived plasma cells that recognize the pathogen for durable protection.2–4 Although existing adjuvants have achieved promising results,research on generating durable protective immunity is lacking in promoting vaccine development and staying ahead of global pandemics such as coronavirus disease 2019(COVID-19).The precisely designed nanoadjuvants can enhance lymph node targeting and increase antigenpresenting cell(APCs)uptake,achieving the co-delivery of adjuvants and antigens and activating innate and adaptive immune responses.5 Previously,we reported a manganese nanoadjuvant(MnARK)and receptor-binding domain(RBD)monomer antigen formulated nanovaccine.6 MnARK transported antigens to lymph nodes,activated the STING pathway,elicited strong neutralizing abilities and increased immune memory T cell percentage against the infection of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).6 Regarding the long-term protection potential of MnARK for subunit vaccine development,we further explored the durable immune regulation abilities of MnARK to a SARS-CoV-2 RBD dimer antigen,which has been used in an approved COVID-19 subunit vaccine ZF2001 with aluminum adjuvant(alum).7,8 TEM result revealed that RBD dimer could interact with BSA on MnARK surface and epitope can be well preserved(Supplementary Fig.1a).The size and zeta potential of MnARK-RBD dimer nanovaccine was~58 nm and-14 mV,respectively(Supplementary Fig.1b,c).

Ablative behavior and mechanism of SiC_(f) /SiBCZr composites prepared by PIP process

SiC_(f)/SiBCZr composites were prepared by polymer precursor impregnation and pyrolysis process with near stoichiometric ratio SiC fiber preform as reinforcement phase and SiBCZr multiphase ceramic precursor as impregnating reagent.The results highlighted that the SiC_(f)/SiBCZr composites exhibited excellent ablative properties after ablative tests at 1200℃/3600 s and 1400℃/3600 s,and the strength retention rates of the composites reached 90%and 85%,respectively.This was mainly due to the liquid sealing effect of the ablative products represented by B2O_(3) and SiO_(2)∙B_(2)O_(3),which inhibited the ablative reaction by reducing the diffusion rate of the oxidation medium,and the solid pinning effect of the substances represented by SiO_(2),ZrO_(2),and ZrSiO_(4),which could play high viscosity and high strength characteristics to improve anti-erosion ability.The above-mentioned SiC_(f)/SiBCZr composites with corrosion resistance,oxidation resistance,and ablative resistance provided a solid material foundation and technical support for the development of reusable spacecraft hot-end components.

Ferroptosis:challenges and opportunities for nanomaterials in cancer therapy

Ferroptosis,a completely new form of regulated cell death,is mainly caused by an imbalance between oxidative damage and reductive protection and has shown great anti-cancer potential.However,existing small-molecule ferroptosis inducers have various limitations,such as poor water solubility,drug resistance and low targeting ability,hindering their clinical applications.Nanotechnology provides new opportunities for ferroptosis-driven tumor therapy.Especially,stimuli-responsive nanomaterials stand out among others and have been widely researched because of their unique spatiotemporal control advantages.Therefore,it’s necessary to summarize the application of those stimuli-responsive nanomaterials in ferroptosis.Here,we describe the physiological feature of ferroptosis and illustrate the current challenges to induce ferroptosis for cancer therapy.Then,nanomaterials that induce ferroptosis are classified and elaborated according to the external and internal stimuli.Finally,the future perspectives in the field are proposed.We hope this review facilitates paving the way for the design of intelligent nano-ferroptosis inducers.

Influence of Fe-rich phases and precipitates on the mechanical behaviour of Al-Cu-Mn-Fe-Sc-Zr alloys studied by synchrotron X-ray and neutron

A multiscale methodology using scanning and transmission electron microscope,synchrotron X-ray nano-tomography and micro-tomography,small angle neutron scattering,and in situ synchrotron X-ray diffrac-tion has been used,to reveal the effect of Fe-rich phases and precipitates on the mechanical behaviour of an Al-Cu-Mn-Fe-Sc-Zr alloy.Theα-Al grains size is reduced from 185.1μm(0 MPa)and 114.3μm(75 MPa)by applied pressure.Moreover,it has been demonstrated that suitable heat treatments modify the 3D morphology of Fe-rich phases from interconnected to a disaggregated structure that improves the mechanical properties of the alloy.The size and morphology evolution of fine precipitates under differ-ent ageing temperature and time are revealed.At ageing temperature of 160℃,the precipitates change from GP zones toθ’(around 75 nm in length)with ageing time increasing from 1 h to 24 h;the Vick-ers hardness increases from 72.0 HV to 110.7HV.The high ductility of the Sc,Zr modified Al-Cu alloy is related to the complex shape and the loss of interconnectivity of the Fe-rich particles due to the heat treatment.The evolution of the crystal lattice strains inα-Al,andβ-Fe calculated during tensile test us-ing in-situ synchrotron X-ray diffraction corroborates the influence of the microstructure in the ductility of the modified alloy.

Engineering hierarchical metal-organic@metal-DNA heterostructures for combinational tumor treatment

Development of simple methods for controlled integration of DNA molecules with metal-organic frameworks(MOFs)is important for various biomedical applications,yet remains a challenge.Herein,a simple and general approach to load DNA on the surface of MOFs is developed via one-pot self-assembly of DNA and FeII ions on nanoscale MOFs,resulting in hierarchical core-shell nanostructures of metal-organic@metal-DNA coordination polymers.The strategy enables assembly of DNA molecules on MOFs with ultra-high contents and precise controllability.By incorporation of a chemotherapeutic drug into the Fe-DNA shell,the systems allow to integrate chemotherapy and gene therapy with photodynamic therapy for combinational tumor treatment.Moreover,the hybrid nanostructures enable light-triggered production of cytotoxic singlet oxygen,which further boosts the endosomal escape of the system for an enhanced gene silencing efficacy and thus improved therapeutic outcome.This work highlights a robust approach for the construction of coordination-based drug delivery systems to combat tumor.

STING and TLR9 agonists synergistically enhance the immunogenicity of SARS-CoV-2 subunit vaccine

Vaccines that are reliable and efficacious are essential in the fight against the COVID-19 pandemic.In this study,we designed a dual-adjuvant system with two pathogen-associated molecular patterns(PAMPs),MnOx and CpG.This system can improve the retention of antigens at the injection site,facilitate pro-inflammatory cytokines secretion,further recruit and activate dendritic cells(DCs).As a result,antigens can be delivered to lymph nodes specifically,and adaptive immunity was strengthened.The immunized group showed an enhanced and broadened humoral and cellular immune response in systemic immunity and lung protection when combined with a tandem repeat-linked dimeric antigen version of the SARS-CoV-2 receptor binding domain(RBDdimer).Remarkably,even with a significant reduction in antigen dosage(three times lower)and a decrease in injection frequencies,our nanovaccine was able to produce the highest neutralizing antibody titers against various mutants.These titers were four-fold higher for the wild-type strain and two-fold higher for both the Beta and Omicron variants in comparison with those elicited by the Alum adjuvant group.In conclusion,our dual-adjuvant formulation presents a promising protein subunit-based candidate vaccine against SARS-CoV-2.

Intelligent nanomaterials for cancer therapy:recent progresses and future possibilities

Intelligent nanomedicine is currently one of the most active frontiers in cancer therapy development.Empowered by the recent progresses of nanobiotechnology,a new generation of multifunctional nanotherapeutics and imaging platforms has remarkably improved our capability to cope with the highly heterogeneous and complicated na-ture of cancer.With rationally designed multifunctionality and programmable assembly of functional subunits,the in vivo behaviors of intelligent nanosystems have become increasingly tunable,making them more efficient in performing sophisticated actions in physiological and path-ological microenvironments.In recent years,intelligent nanomaterial-based theranostic platforms have showed great potential in tumor-targeted delivery,biological barrier circumvention,multi-responsive tumor sensing and drug release,as well as convergence with precise medication approaches such as personalized tumor vaccines.On the other hand,the increasing system complexity of anti-cancer nanomedicines also pose significant challenges in charac-terization,monitoring and clinical use,requesting a more comprehensive and dynamic understanding of nano-bio interactions.This review aims to briefly summarize the recent progresses achieved by intelligent nanomaterials in tumor-targeted drug delivery,tumor immunotherapy and temporospatially specific tumor imaging,as well as impor-tant advances of our knowledge on their interaction with biological systems.In the perspective of clinical translation,we have further discussed the major possibilities provided by disease-oriented development of anti-cancer nano-materials,highlighting the critical importance clinically-oriented system design.

A special issue for the 20^(th) anniversary of National Center for Nanoscience and Technology

National Center for Nanoscience and Technology(NCNST),China,established in December 2003,is co-founded by the Chinese Academy of Sciences(CAS)and the Ministry of Education as an institution dedicated to fundamental and applied researches in the field of nanoscience and technology,especially those with important potential applications.NCNST is operated under the supervision of the Governing Board and aims to become a world-class research center,as well as public technological platform and young talents training center in the field,and to act as an important bridge for international academic exchange and collaboration.The NCNST currently has three CAS Key Laboratories:the CAS Key Laboratory for Biological Effects of Nanomaterials and Nanosafety,the CAS Key Laboratory for Standardization and Measurement for Nanotechnology and the CAS Key Laboratory for Nanosystem and Hierarchical Fabrication.In 2020,the CAS Key Laboratory of Nanophotonic Materials and Devices started construction.Besides,there are Division of Nanotechnology Development,Nanofabrication Laboratory,Intelligent Nanosensing Laboratory and Theoretical Laboratory.

针对肿瘤微环境精确设计的智能抗肿瘤纳米药物

肿瘤微环境调控概念的兴起极大推进了智能纳米药物的发展.作为治疗或递药靶点,基质和血管等微环境成分在基因层面上较肿瘤细胞更稳定,并且提供了在递药过程中绕过部分生物屏障的可能.我们的研究表明,充分利用纳米材料的固有优势和功能化潜力,针对肿瘤微环境精确设计纳米药物,对于开发和实现新的纳米抗肿瘤策略至关重要.例如,利用高精度自组装的核酸纳米机器,能够实现强效凝血分子在血液循环中的安全递送;利用多重释药的纳米结构局域性清除肿瘤相关血小板,可提高纳米药物穿透肿瘤血管内皮屏障的效率等.基于以上学术思想,近年来,我们系统研究了针对不同微环境成分或病理状态的靶向调控策略,利用智能纳米药物实现了包括肿瘤血管特异性栓塞、肿瘤基质微环境重塑、肿瘤血管通透性增强等创新性微环境调控方案.本文综述了其中的代表性进展,讨论了相关智能纳米体系在肿瘤微环境调控中的潜力和局限,并分析了智能抗肿瘤纳米药物的未来发展方向.

用于肿瘤血管栓塞治疗的智能型DNA纳米机器人

恶性肿瘤(癌症)是危害人类健康的一大杀手.肿瘤的快速增殖高度依赖于肿瘤血管的形成及血液供应,因此堵塞肿瘤血管饿死肿瘤细胞成为继放化疗、手术及免疫治疗之后的又一有效治疗策略.凝血酶(thrombin)可以高效地激活血小板并将纤维蛋白原转化为纤维蛋白,进而诱导血栓形成.而游离的凝血酶在血液中的半衰期很短,并且会引起非特异性的血栓形成,造成健康组织的损伤,大大地限制了该分子在肿瘤栓塞治疗中的应用.寻求可以将凝血酶精准递送到肿瘤组织局部的新方法,实现特异性肿瘤血管栓塞成为亟待解决的难题. DNA纳米折纸技术的快速发展使这一问题得以解决.本团队近期构建了智能响应性纳米机器人,将凝血酶精准高效地递送到肿瘤局部,诱导血栓形成,实现高效抑制肿瘤生长和转移的目的.本文将对该领域近年来的国内外研究进展和本实验室的研究成果进行简单概述,并对该技术领域的发展方向和前景提出一定的展望.

Precise nanomedicine for intelligent therapy of cancer

Precise nanomedicine has been extensively explored for efficient cancer imaging and targeted cancer therapy, as evidenced by a few breakthroughs in their preclinical and clinical explorations. Here, we demonstrate the recent advances of intelligent cancer nanomedicine, and discuss the comprehensive understanding of their structure-function relationship for smart and efficient cancer nanomedicine including various imaging and therapeutic applications, as well as nanotoxicity. In particular, a few emerging strategies that have advanced cancer nanomedicine are also highlighted as the emerging focus such as tumor imprisonment, supramolecular chemotherapy, and DNA nanorobot. The challenge and outlook of some scientific and engineering issues are also discussed in future development. We wish to highlight these new progress of precise nanomedicine with the ultimate goal to inspire more successful explorations of intelligent nanoparticles for future clinical translations.

Sensing system for mimicking cancer cell–drug interaction

Biomarker discovery for early detection and therapy of diseases has been blooming for the past two decades.Following the identification of new biomarkers,research and development of sensing platforms has started to become more urgently needed recently,in both laboratory and clinical settings.

Screen efficiency comparisons of decision tree and neural network algorithms in machine learning assisted drug design

In view of huge search space in drug design, machine learning has become a powerful method to predict the affinity between small molecular drug and targeting protein with the development of artificial intelligence technology. However, various machine learning algorithms including massive different parameters make the prediction framework choice to be quite difficult. In this work, we took a recent drug design competition(from XtalPi company on the DataCastle platform) as the typical case to find the optimized parameters for different machines learning algorithms and the most effective algorithm. After the parameter optimizations, we compared the typical machine learning methods as decision tree(XGBoost, LightGBM) and artificial neural network(MLP, CNN) with root-mean-square error(RMSE) and coefficient of determination(R^2) evaluation. As a result, decision tree is more effective than the neural network as LightGBM>XGBoost>CNN>MLP in the affinity prediction of the specific drug design problem with ～160000 samples. For a much larger screening task in a more complicated drug design study, the sophisticated neural network model may go beyond the decision tree algorithm after generalization enhancing and overfitting reducing. The advanced machine learning methods could extract more information of protein-ligand bindings than traditional ones and improve the screen efficiency of drug design up to 200–1000 times.