Reduction of photodynamic damage of blood vessels in the protected region by(–)-epigallocatechin gallate

Photodynamic therapy(PDT)has been increasingly used in the clinical treatment of neoplastic,inflammatory and infectious skin diseases.However,the generation of reactive oxygen species(ROS)may induce undesired side effects in normal tissue surrounding the treatment lesion,which is a big challenge for the clinical application of PDT.To date,(–)-Epigallocatechin gallate(EGCG)has been widely proposed as an antiangiogenic and antitumor agent for the protection of normal tissue from ROS-mediated oxidative damage.This study evaluates the regulation ability of EGCG for photodynamic damage of blood vessels during hematoporphyrin monomethyl ether(Hemoporfin)-mediated PDT.The quenching rate constants of EGCG for the triplet-state Hemoporfin and photosensitized 1O2 generation are determined to be 6.8×10^(8)M^(−1)S^(−1),respectively.The vasoconstriction of blood vessels in the protected region treated with EGCG hydrogel after PDT is lower than that of the control region treated with pure hydrogel,suggesting an efficiently reduced photodamage of Hemoporfin for blood vessels treated with EGCG.This study indicates that EGCG is an efficient quencher for triplet-state Hemoporfin and 1O2,and EGCG could be potentially used to reduce the undesired photodamage of normal tissue in clinical PDT.

Tissue optical clearing enhances efficacy of vascular targeted photodynamic therapy of mouse dorsal skin

Vascular-targeted photodynamic therapy(V-PDT)is an effective treatment for port wine stains(PWS).However,repeated treatment is usually needed to achieve optimal treatment outcomes,possibly due to the limited treatment light penetration depth in the PWS lesion.The optical clearing technique can increase light penetration in depth by reducing light scattering.This study aimed to investigate the V-PDT in combination with an optical clearing agent(OCA)for the therapeutic enhancement of V-PDT in the rodent skinfold window chamber model.Vascular responses were closely monitored with laser speckle contrast imaging(LSCI),optical coherence tomography angiography,and stereo microscope before,during,and after the treatment.We further quantitatively demonstrated the effects of V-PDT in combination with OCA on the blood flow and blood vessel size of skin microvasculature.The combination of OCA and V-PDT resulted in significant vascular damage,including vasoconstriction and the reduction of blood flow.Our results indicate the promising potential of OCA for enhancing V-PDT for treating vascular-related diseases,including PWS.

Revolutionizing diabetic wound healing:The power of microneedles

Diabetic wounds significantly affect patient quality of life.Microneedles are a promising treatment to accelerate wound healing owing to their high drug-loading capacity and efficient drug delivery;however,few studies to date have comprehensively reviewed microneedles for diabetic wound healing.This up-to-date review summarizes the research progress in microneedles for diabetic wound healing,including manufacturing materials and techniques,structures,designs,release mechanisms,delivery substances,and their specific effects.This study showed that most microneedles designed for diabetic wounds are made of synthetic polymers and/or natural materials using polydimethylsiloxane micromolding.The geometric structure and design directly influence penetration ability and drug delivery capacity.Microneedles can deliver antibiotics,hypoglycemic agents,traditional Chinese medicines,metal ions,growth factors,exosomes,stem cells,and microorganisms,thus promoting diabetic wound healing through diverse mechanisms,such as antibacterial,anti-inflammatory,antioxidant,hypoglycemic,and angiogenic activities,at different stages of the healing process.In conclusion,microneedles are promising drug delivery systems for the treatment of diabetic wounds.

A Modified CycleGAN for Multi-Organ Ultrasound Image Enhancement via Unpaired Pre-Training

Handheld ultrasound devices are known for their portability and affordability,making them widely utilized in underdeveloped areas and community healthcare for rapid diagnosis and early screening.However,the image quality of handheld ultrasound devices is not always satisfactory due to the limited equipment size,which hinders accurate diagnoses by doctors.At the same time,paired ultrasound images are difficult to obtain from the clinic because imaging process is complicated.Therefore,we propose a modified cycle generative adversarial network(cycleGAN) for ultrasound image enhancement from multiple organs via unpaired pre-training.We introduce an ultrasound image pre-training method that does not require paired images,alleviating the requirement for large-scale paired datasets.We also propose an enhanced block with different structures in the pre-training and fine-tuning phases,which can help achieve the goals of different training phases.To improve the robustness of the model,we add Gaussian noise to the training images as data augmentation.Our approach is effective in obtaining the best quantitative evaluation results using a small number of parameters and less training costs to improve the quality of handheld ultrasound devices.

Alignment error modeling and control of a double-sided microlens array during precision glass molding

Double-sided microlens arrays(DSMLAs)include combinations of two single-sided MLAs to overcome positioning errors and greatly improve light transmissivity compared to other types of lenses.Precision glass molding(PGM)is used to fabricate DSMLAs,but controlling alignment errors during this process is challenging.In this paper,a mold assembly was manufactured with a novel combination of materials to improve the alignment accuracy of mold cores during PGM by using the nonlinear thermal expansion characteristics of the various materials to improve the DSMLA alignment accuracy.By establishing a mathematical model of the DSMLA alignment error and a thermal expansion model of the mold-sleeve pair,the relationship between the maximum alignment error of the DSMLA and the mold-sleeve gap was determined.This research provides a method to optimize the mold-sleeve gap and minimize the alignment error of the DSMLA.The measured DSMLA alignment error was 10.56μm,which is similar to the predicted maximum alignment error.Optical measurements showed that the uniformity of the homogenized beam spot was 97.81%,and the effective homogeneous area accounted for 91.66%of the total area.This proposed method provides a novel strategy to improve the performance of DSMLAs.

An improved pulse coupled neural networks model for semantic IoT

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data traffic.Meanwhile,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication paradigm.However,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic information.With the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to increase.In contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image transmission.However,the parameters of PCNN are determined by trial and error,which limits its application.To overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this work.The IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of images.Experimental segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation Datasets.The IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

Evaluation of embedded modular branched stent graft in treating aortic arch aneurysm using imaging-based computational flow analysis

Embedded modular branched stent graft(EMBSG)was a new option for aortic arch aneurysm.However,the therapeutic effect of this innovative stenting technique has not been fully assessed.Computational fluid dynamics and three-dimensional structural analyses were performed on three patients(Patient Ⅰ,Patient Ⅱ and Patient Ⅲ)with aortic arch aneurysm,both before and after EMBSG implantation.Patient-specific alterations from preoperative to postoperative were analyzed via morphological and functional metrics.Patient Ⅰ and Patient Ⅱ showed notable curvature changes and area reduction after intervention procedure.Three patients showed an increase in flow velocity after EMBSG implantation,while the pressure drop from ascending aorta to the aortic arch was remarkable in Patient I and Patient Ⅱ with the value of 7.09mmHg,and 10.95mmHg,respectively.Patient I and Patient Ⅱ also showed elevated time-averaged wall shear stress(TAWSS)in the stenting region,while Patient Ⅲ showed a trivial change in TAWSS after intervention procedure.Three patients showed low relative residence time after EMBSG insertion.The short-term results of EMBSG in treating aortic arch aneurysm were promising.Hemodynamic parameters have the potential to assist in the outcome evaluation and might be used to guide the stent graft design and wise selection,thereby improving the long-term therapeutic effect in managing complex vascular disease.

Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder

Thalamocortical circuitry has a substantial impact on emotion and cognition.Previous studies have demonstrated alterations in thalamocortical functional connectivity(FC),characterized by region-dependent hypo-or hyper-connectivity,among individuals with major depressive disorder(MDD).However,the dynamical reconfiguration of the thalamocortical system over time and potential abnormalities in dynamic thalamocortical connectivity associated with MDD remain unclear.Hence,we analyzed dynamic FC(dFC)between ten thalamic subregions and seven cortical subnetworks from resting-state functional magnetic resonance images of 48 patients with MDD and 57 healthy controls(HCs)to investigate time-varying changes in thalamocortical FC in patients with MDD.Moreover,dynamic laterality analysis was conducted to examine the changes in functional lateralization of the thalamocortical system over time.Correlations between the dynamic measures of thalamocortical FC and clinical assessment were also calculated.We identified four dynamic states of thalamocortical circuitry wherein patients with MDD exhibited decreased fractional time and reduced transitions within a negative connectivity state that showed strong correlations with primary cortical networks,compared with the HCs.In addition,MDD patients also exhibited increased fluctuations in functional laterality in the thalamocortical system across the scan duration.The thalamo-subnetwork analysis unveiled abnormal dFC variability involving higher-order cortical networks in the MDD cohort.Significant correlations were found between increased dFC variability with dorsal attention and default mode networks and the severity of symptoms.Our study comprehensively investigated the pattern of alteration of the thalamocortical dFC in MDD patients.The heterogeneous alterations of dFC between the thalamus and both primary and higher-order cortical networks may help characterize the deficits of sensory and cognitive processing in MDD.

Erratum to:Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder

The article(Zheng et al.,2024)unfortunately contained a mistake:in Table 3,four"I"elements in the last"LF in thalamus"column are mistaken.The four arrows should be"↑"in the following correctversion of Table3.

Synergizing Brain-Computer Interfaces,Machine Learning-enhanced Image Processing,and Big Data:A Triad for the Future of Neuroscience

The pursuit of understanding and harnessing the potential of the human brain is undoubtedly one of the most difficult and significant endeavors.The brain,an enigmatic and intricate organ,has long captivated the imagination and curiosity of scientists,philosophers,and thinkers.Presently,we find ourselves at a crucial point in neuroscience.

Injectable body temperature responsive hydrogel for encephalitis treatment via sustained release of nano-anti-inflammatory agents

Skull defects are common in the clinical practice of neurosurgery,and they are easily complicated by encephalitis,which seriously threatens the life and health safety of patients.The treatment of encephalitis is not only to save the patient but also to benefit the society.Based on the advantages of injectable hydrogels such as minimally invasive surgery,self-adaptation to irregularly shaped defects,and easy loading and delivery of nanomedicines,an injectable hydrogel that can be crosslinked in situ at the ambient temperature of the brain for the treatment of encephalitis caused by cranial defects is developed.The hydrogel is uniformly loaded with nanodrugs formed by cationic liposomes and small molecule drugs dexmedetomidine hydrochloride(DEX-HCl),which can directly act on the meninges to achieve sustained release delivery of anti-inflammatory nanodrug preparations and achieve the goal of long-term anti-inflammation at cranial defects.This is the first time that DEX-HCl has been applied within this therapeutic system,which is innovative.Furthermore,this study is expected to alleviate the long-term suffering of patients,improve the clinical medication strategies for anti-inflammatory treatment,promote the development of new materials for cranial defect repair,and expedite the translation of research outcomes into clinical practice.

Biomembrane-inspired design of medical micro/nanorobots:From cytomembrane stealth cloaks to cellularized Trojan horses

Micro/nanorobots are promising for a wide range of biomedical applications(such as targeted tumor,thrombus,and infection therapies in hard-to-reach body sites)because of their tiny size and high maneuverability through the actuation of external fields(e.g.,magnetic field,light,ultrasound,electric field,and/or heat).However,fully synthetic micro/nanorobots as foreign objects are susceptible to phagocytosis and clearance by diverse phagocytes.To address this issue,researchers have attempted to develop various cytomembrane-camouflaged micro/nanorobots by two means:(1)direct coating of micro/nanorobots with cytomembranes derived from living cells and(2)the swallowing of micro/nanorobots by living immunocytes via phagocytosis.The camouflaging with cytomembranes or living immunocytes not only protects micro/nanorobots from phagocytosis,but also endows them with new characteristics or functionalities,such as prolonging propulsion in biofluids,targeting diseased areas,or neutralizing bacterial toxins.In this review,we comprehensively summarize the recent advances and developments of cytomembrane-camouflaged medical micro/nanorobots.We first discuss how cytomembrane coating nanotechnology has been employed to engineer synthetic nanomaterials,and then we review in detail how cytomembrane camouflage tactic can be exploited to functionalize micro/nanorobots.We aim to bridge the gap between cytomembrane-cloaked micro/nanorobots and nanomaterials and to provide design guidance for developing cytomembrane-camouflaged micro/nanorobots.

A Novel Robotic Bronchoscope System for Navigation and Biopsy of Pulmonary Lesions

Transbronchial biopsy sampling,as a minimally invasive method with relatively low risk,has been proved to be a promising treatment in the field of respiratory surgery.Although several robotic bronchoscopes have been developed,it remains a great challenge to balance size and flexibility,while integrating multisensors to realize navigation during complex airway networks.This paper proposes a novel robotic bronchoscope system composed by end effector with relatively small size,relevant actuation unit,and navigation system with path planning and surgical guidance capability.The main part of the end effector is machined by bidirectional groove on a nickel-titanium tube,which can realize bending,rotation,and translation 3 degrees of freedom.A prototype of the proposed robotic bronchoscope system is designed and fabricated,and its performance is tested through several experiments to verify the stiffness,flexibility,and navigation performance.The results show that the proposed system is with good environment adaptiveness,and it can become a promising biopsy method through natural cavity of the human body.

A compact liquid chromatography-mass spectrometry instrument for the quantitation of immunosuppressants

Liquid chromatography tandem mass spectrometry(LC-MS/MS) plays an important role in clinical diagnostics. Although LC-MS/MS is superior in terms of accurately quantifying molecules in complex matrices,instrument footprint, operation and maintenance complexity also hinder its expansion as the analytical technique of choice. In this study, a compact LC-MS instrument was developed, in which an assembled liquid chromatograph was coupled with a miniature ion trap mass spectrometer. The overall instrument has a footprint of 69 cm × 31 cm × 31 cm, and it requires no gas supply as well as minimum maintenance. Furthermore, the use of LC-MS is in accord with conventional clinical diagnostic protocols, and the choice of ion trap offers tandem MS performance. The results showed that the use of LC could improve both mixture analysis capability and detection sensitivity of the miniature mass spectrometer. After optimization, feasibility of this instrument in clinical practice was demonstrated by the quantitation of four widely used immunosuppressants in blood samples. Relatively good linearities were obtained, which spanned the reference ranges of effective therapeutic concentrations of each immunosuppressant. Intraday and inter-day accuracy and precision of analytical method were also assessed. This work showed that a compact LC-MS instrument could be used in clinical diagnosis, either to replace conventional lab-scale instruments or to be used in POCT applications.

The Voice of the Body:Why AI Should Listen to It and an Archive

The sound generated by body carries important information about our health status physically and psychologically.In the past decades,we have witnessed a plethora of successes achieved in the field of body sound analysis.Nevertheless,the fundamentals of this young field are still not well established.In particular,publicly accessible databases are rarely developed,which dramatically restrains a sustainable research.To this end,we are launching and continuously calling for participation from the global scientific community to contribute to the Voice of the Body(VoB)archive.We aim to build an open access platform to collect the well-established body sound databases in a well standardized way.Moreover,we hope to organize a series of challenges to promote the development of audio-driven methods for healthcare via the proposed VoB.We believe that VoB can help break the walls between different subjects toward an era of Medicine 4.0 enriched by audio intelligence.

An Overview of In Vitro Biological Neural Networks for Robot Intelligence

In vitro biological neural networks(BNNs)interconnected with robots,so-called BNN-based neurorobotic systems,can interact with the external world,so that they can present some preliminary intelligent behaviors,including learning,memory,robot control,etc.This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems,with a particular focus on those related to robot intelligence.In this work,we first introduce the necessary biological background to understand the 2 characteristics of the BNNs:nonlinear computing capacity and network plasticity.Then,we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects:from robots to BNNs and from BNNs to robots.Next,we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity(computing capacity-dependent)or depend also on the network plasticity(network plasticity-dependent),which are then expounded respectively,with a focus on those related to the realization of robot intelligence.Finally,the development trends and challenges of the BNNbased neurorobotic systems are discussed.

Space Life Science in China

With the further advancement of China’s major manned spaceflight project,the national space laboratory was successfully built.China has also made considerable progress and breakthroughs in the field of space life sciences.This paper reviews the related biological effects under space flight conditions,mainly including epigenetic effects,skeleton remodeling and peripheral body fluid circulation effects,as well as the research and application of space life science related biotechnology in the field of microbial culture and biological regeneration life support system.

Breaking pore size limit of metal–organic frameworks:Bio-etched ZIF-8 for lactase immobilization and delivery in vivo

Expanding pore size range of metal–organic frameworks(MOFs)promotes their versatility and feasibility for various biomedical applications.However,natural pore size greatly restricts large guest molecule accommodation.Customizing and tailoring pore apertures ranging from micropores to mesopores controllably is desired but still critically challenging.Herein,we developed a facile method with super mildness based on pH-sensitive zeolitic imidazolate framework(ZIF)-8 to increase porosity,providing pore size with maximum 20 nm,which is 8 times larger than average.Glucose oxidase(GOx)was introduced in ZIF-8 for bioetching,benefitted from the resultant acidic microe-nvironment during biocatalytic process.Different synthesis methods were assessed for obtaining different morphologies and size distributions.Reaction time,GOx encapsulation efficiency,and Zn2+concentration was optimized to precisely control the mesopore size distribution of MOFs.It was found that bio-etching strategy was capable of producing stable mesopores which were large enough for loading lactase with good enzymatic activity retained,verified both in vitro and in vivo.This strategy breaks natural pore size limitation of MOFs and thereby facilitates biomolecule delivery,catalysis,and other biomedical applications with enhanced stability and performance.

Exploring Brain Age Calculation Models Available for Alzheimer's Disease

The advantages of structural magnetic resonance imaging(sMRI)-based multidimensional tensor morphological features in brain disease research are the high sensitivity and resolution of sMRI to comprehensively capture the key structural information and quantify the structural deformation.However,its direct application to regression analysis of high-dimensional small-sample data for brain age prediction may cause“dimensional catastrophe”.Therefore,this paper develops a brain age prediction method for high-dimensional small-sample data based on sMRI multidimensional morphological features and constructs brain age gap estimation(BrainAGE)biomarkers to quantify abnormal aging of key subcortical structures by extracting subcortical structural features for brain age prediction,which can then establish statistical analysis models to help diagnose Alzheimer’s disease and monitor health conditions,intervening at the preclinical stage.

Nanoscale Metal-Organic Frameworks:Stimulus-Response and Applications

Metal-organic frameworks(MOFs),a crystalline porous material with a periodic net-work structure formed by the self-assembly of transition metal ions and organic ligands,have been widely applied in various fields due to their rich composition and structural diversity.Among vari-ous types of MOFs,stimuli-responsive MOFs have gained increasing attention in recent years,because of their broad application in the field of physics,biology,and chemistry.In this review,we analyzed and classified the mechanism of stimulus-response MOFs(pH response,glucose response,GSH response,light response,temperature response)and their applications in drug delivery,adsorption and luminescence functions,magnetization and catalysis functions,probe and sensor.