The Functions of N-methyladenosine (m6A) Modification on HIV-1 mRNA.

In recent years, there has been a growing interest in the study of RNA modifications, with some researchers focusing specifically on the connection between these modifications and viruses, as well as the impact they have on viral mRNA and its functionality. The most common type of RNA chemical modification is m6A, which involves the addition of a methyl group covalently to the N6 position of adenosine. It is a widely observed and evolutionarily conserved RNA modification. The regulation of m6A modification primarily involves methyltransferases (writers) and demethylases (erasers) and is mediated by m6A-binding proteins (readers). In HIV-1, m6A sites are predominantly located in the 5' untranslated region (5'UTR) and 3' untranslated region (3'UTR). Additionally, m6A modifications are also present in the RRE RNA of HIV-1. This review provides a detailed account of the effects of these m6A modifications on HIV-1 functionality.

Another Perspective of Over-Smoothing: Alleviating Semantic Over-Smoothing in Deep GNNs.

Graph neural networks (GNNs) are widely used for analyzing graph-structural data and solving graph-related tasks due to their powerful expressiveness. However, existing off-the-shelf GNN-based models usually consist of no more than three layers. Deeper GNNs usually suffer from severe performance degradation due to several issues including the infamous "over-smoothing" issue, which restricts the further development of GNNs. In this article, we investigate the over-smoothing issue in deep GNNs. We discover that over-smoothing not only results in indistinguishable embeddings of graph nodes, but also alters and even corrupts their semantic structures, dubbed semantic over-smoothing. Existing techniques, e.g., graph normalization, aim at handling the former concern, but neglect the importance of preserving the semantic structures in the spatial domain, which hinders the further improvement of model performance. To alleviate the concern, we propose a cluster-keeping sparse aggregation strategy to preserve the semantic structure of embeddings in deep GNNs (especially for spatial GNNs). Particularly, our strategy heuristically redistributes the extent of aggregations for all the nodes from layers, instead of aggregating them equally, so that it enables aggregate concise yet meaningful information for deep layers. Without any bells and whistles, it can be easily implemented as a plug-and-play structure of GNNs via weighted residual connections. Last, we analyze the over-smoothing issue on the GNNs with weighted residual structures and conduct experiments to demonstrate the performance comparable to the state-of-the-arts.

DWSSA: Alleviating over-smoothness for deep Graph Neural Networks.

Graph Neural Networks (GNNs) have demonstrated great potential in achieving outstanding performance in various graph-related tasks, e.g., graph classification and link prediction. However, most of them suffer from the following issue: shallow networks capture very limited knowledge. Prior works design deep GNNs with more layers to solve the issue, which however introduces a new challenge, i.e., the infamous over-smoothness. Graph representation over emphasizes node features but only considers the static graph structure with a uniform weight are the key reasons for the over-smoothness issue. To alleviate the issue, this paper proposes a Dynamic Weighting Strategy (DWS) for addressing over-smoothness. We first employ Fuzzy C-Means (FCM) to cluster all nodes into several groups and get each node's fuzzy assignment, based on which a novel metric function is devised for dynamically adjusting the aggregation weights. This dynamic weighting strategy not only enables the intra-cluster interactions, but also inter-cluster aggregations, which well addresses undifferentiated aggregation caused by uniform weights. Based on DWS, we further design a Structure Augmentation (SA) step for addressing the issue of underutilizing the graph structure, where some potentially meaningful connections (i.e., edges) are added to the original graph structure via a parallelable KNN algorithm. In general, the optimized Dynamic Weighting Strategy with Structure Augmentation (DWSSA) alleviates over-smoothness by reducing noisy aggregations and utilizing topological knowledge. Extensive experiments on eleven homophilous or heterophilous graph benchmarks demonstrate the effectiveness of our proposed method DWSSA in alleviating over-smoothness and enhancing deep GNNs performance.

Biomimetic "Gemini nanoimmunoregulators" orchestrated for boosted photoimmunotherapy by spatiotemporally modulating PD-L1 and tumor-associated macrophages.

A novel strategy of not only stimulating the immune cycle but also modulating the immunosuppressive tumor microenvironment is of vital importance to efficient cancer immunotherapy. Here, a new type of spatiotemporal biomimetic "Gemini nanoimmunoregulators" was engineered to activate robust systemic photoimmunotherapy by integrating the triple-punch of amplified immunogenic cell death (ICD), tumor-associated macrophages (TAMs) phenotype reprogramming and programmed cell death ligand 1 (PD-L1) degradation. The "Gemini nanoimmunoregulators" PM@RM-T7 and PR@RM-M2 were constructed by taking the biocompatible mesoporous polydopamine (mPDA) as nanovectors to deliver metformin (Met) and toll-like receptor 7/8 agonist resiquimod (R848) to cancer cells and TAMs by specific biorecognition via wrapping of red blood cell membrane (RM) inlaid with T7 or M2 peptides. mPDA/Met@RM-T7 (abbreviated as PM@RM-T7) was constructed to elicit an amplified in situ ICD effect through the targeted PTT and effectively stimulated the anticancer immunity. Meanwhile, PD-L1 on the remaining cancer cells was degraded by the burst metformin to prevent immune evasion. Subsequently, mPDA/R848@RM-M2 (abbreviated as PR@RM-M2) specifically recognized TAMs and reset the phenotype from M2 to M1 state, thus disrupting the immunosuppressive microenvironment and further boosting the function of cytotoxic T lymphocytes. This pair of sister nanoimmunoregulators cooperatively orchestrated the comprehensive anticancer activity, which remarkably inhibited the growth of primary and distant 4T1 tumors and prevented malignant metastasis. This study highlights the spatiotemporal cooperative modalities using multiple nanomedicines and provides a new paradigm for efficient cancer immunotherapy against metastatic-prone tumors.

Roles of rRNA N-methyladenosine modification in the function of ribosomes.

The N-methyladenosine (m6A) modification of ribosomal RNA (rRNA) plays critical roles in regulating the function of ribosomes, the essential molecular machines that translate genetic information from mRNA into proteins. Specifically, m6A modification affects ribosome biogenesis, stability, and function by regulating the processing and maturation of rRNA, the assembly and composition of ribosomes, and the accuracy and efficiency of translation. Furthermore, m6A modification allows for dynamic regulation of translation in response to environmental and cellular signals. Therefore, a deeper understanding of the mechanisms and functions of m6A modification in rRNA will advance our knowledge of ribosome-mediated gene expression and facilitate the development of new therapeutic strategies for ribosome-related diseases.

Laser Direct Writing of Flexible Thermal Flow Sensors.

Thin film-based thermal flow sensors afford applications in healthcare and industries owing to their merits in preserving initial flow distributions. However, traditional thermal flow sensors are primarily applied to track flow intensities based on hot-wire or hot-film sensing mechanisms due to their relatively facile device configurations and fabrication strategies. Herein, a calorimetric thermal flow sensor is proposed based on laser direct writing to form laser-induced graphene as heaters and temperature sensors, resulting in monitoring both flow intensities and orientations. Via homogeneously surrounding spiral heaters with multiple temperature sensors, the device exhibits high sensitivity (∼162 K·s/m) at small flows with an extended flow detection range (∼25 m/s). Integrating the device with a data-acquisition board and a dual-mode graphical user interface enables wirelessly and dynamically monitoring respiration and the motion of robotic arms. This versatile flow sensor with facile manufacturing affords potentials in health inspection, remote monitoring, and studying hydrodynamics.

Characteristics and mechanisms of latency-reversing agents in the activation of the human immunodeficiency virus 1 reservoir.

The "Shock and Kill" method is being considered as a potential treatment for eradicating HIV-1 and achieving a functional cure for acquired immunodeficiency syndrome (AIDS). This approach involves using latency-reversing agents (LRAs) to activate human immunodeficiency virus (HIV-1) transcription in latent cells, followed by treatment with antiviral drugs to kill these cells. Although LRAs have shown promise in HIV-1 patient research, their widespread clinical use is hindered by side effects and limitations. In this review, we categorize and explain the mechanisms of these agonists in activating HIV-1 in vivo and discuss their advantages and disadvantages. In the future, combining different HIV-1 LRAs may overcome their respective shortcomings and facilitate a functional cure for HIV-1.

Machine Learning-Enabled Tactile Sensor Design for Dynamic Touch Decoding.

Skin-like flexible sensors play vital roles in healthcare and human-machine interactions. However, general goals focus on pursuing intrinsic static and dynamic performance of skin-like sensors themselves accompanied with diverse trial-and-error attempts. Such a forward strategy almost isolates the design of sensors from resulting applications. Here, a machine learning (ML)-guided design of flexible tactile sensor system is reported, enabling a high classification accuracy (≈99.58%) of tactile perception in six dynamic touch modalities. Different from the intuition-driven sensor design, such ML-guided performance optimization is realized by introducing a support vector machine-based ML algorithm along with specific statistical criteria for fabrication parameters selection to excavate features deeply concealed in raw sensing data. This inverse design merges the statistical learning criteria into the design phase of sensing hardware, bridging the gap between the device structures and algorithms. Using the optimized tactile sensor, the high-quality recognizable signals in handwriting applications are obtained. Besides, with the additional data processing, a robot hand assembled with the sensor is able to complete real-time touch-decoding of an 11-digit braille phone number with high accuracy.

Meta-analysis of the impact of physical activity on the recovery of physical function in COVID-19 patients.

Background: The decrease in physical function resulting from COVID-19 infection exerts a substantial negative influence on the quality of life of individuals. Physical activity plays a crucial and irreplaceable role in hastening the elimination of adverse effects on the body caused by acute and chronic diseases. Nevertheless, there have been reports of unfavorable events following physical activity post-COVID-19 infection, sparking debate regarding the efficacy of physical activity as a rehabilitation method to enhance the physical function of COVID-19 patients. Objective: The aim of this study is to investigate the impact of physical activity on promoting the restoration of physical function among individuals with COVID-19, and to offer guidance for the advancement and consideration of physical activity in the rehabilitation treatment of COVID-19 patients. Methods: A search was conducted on the PubMed and Web of Science core collection databases, with the search period set from January 1, 2020, to February 6, 2023. The included literature was assessed for risk of bias and methodological quality according to the Cochrane Handbook for Systematic Reviews of Interventions, utilizing Review Manager 5.1 software. The outcome measures from the included studies were analyzed, and the quality of evidence for the outcome measures was graded using the GRADE classification criteria. Results: The effect of physical activity intervention on improving the 6-Minute Walk Test score in COVID-19 patients was better than that of conventional treatment [WMD = 69.19(95%CI = 39.38, 98.99), I2 = 57%(p = 0.03)]. The effect of physical activity on improving the 30-Second Sit-to-Stand Test score was better than that of conventional treatment [WMD = 2.98(95%CI = 1.91, 4.04), I2 = 0%(p = 0.56)]. There was no significant difference between physical activity and conventional treatment in improving Grip strength in COVID-19 patients [WMD = 2.35(95%CI = -0.49, 5.20), I2 = 0%(p = 0.80)]. The effect of physical activity on improving the Timed Up and Go test score in COVID-19 patients was better than that of conventional treatment [WMD = -1.16(95%CI = -1.98, -0.34), I2 = 4%(p = 0.35)]. The effect of physical activity on improving Forced Vital Capacity in COVID-19 patients was better than that of conventional treatment [WMD = 0.14(95%CI = 0.08, 0.21), I2 = 0%(p = 0.45)]. The effect of physical activity on improving Forced Expiratory Volume in the first second in COVID-19 patients was better than that of conventional treatment [WMD = 0.08(95%CI = 0.02, 0.15), I2 = 52%(p = 0.10)]. Conclusions: Physical activity plays a crucial role in facilitating the recovery of exercise capacity and pulmonary function in COVID-19 patients, helping to expedite the restoration of overall physical health. It is crucial for COVID-19 patients to undergo an accurate assessment of their physical condition before engaging in any physical activity.

Biomimetic Nano-Immunoactivator via Ionic Metabolic Modulation for Strengthened NIR-II Photothermal Immunotherapy.

Reprogramming the immunologically "cold" environment of solid tumors is currently becoming the mainstream strategy to elicit powerful and systemic anticancer immunity. Here, a facile and biomimetic nano-immunnoactivator (CuS/Z@M4T1 ) is detailed by engineering a Zn2+ -bonded zeolitic imidazolate framework-8 (ZIF-8) with CuS nanodots (NDs) and cancer cell membrane for amplified near-infrared-II (NIR-II) photothermal immunotherapy via Zn2+ metabolic modulation. Taking advantage of the NIR-II photothermal effect of CuS NDs and the acidic responsiveness of ZIF-8, CuS/Z@M4T1 rapidly causes intracellular Zn2+ pool overload and disturbs the metabolic flux of 4T1 cells, which effectively hamper the production of heat shock proteins and relieve the resistance of photothermal therapy (PTT). Thus, amplified immunogenic cell death is evoked and initiates the immune cascade both in vivo and in vitro as demonstrated by dendritic cells maturation and T-cell infiltration. Further combination with antiprogrammed death 1 (aPD-1) achieves escalated antitumor efficacy which eliminates the primary, distant tumor and avidly inhibits lung metastasis due to cooperation of enhanced photothermal stimulation and empowerment of cytotoxic T lymphocytes by aPD-1. Collectively, this work provides the first report of using the intrinsic modulation property of meta-organometallic ZIF-8 for enhanced cancer photoimmunotherapy together with aPD-1, thereby inspiring a novel combined paradigm of ion-rich nanomaterials for cancer treatment.

NIR/pH-triggered aptamer-functionalized DNA origami nanovehicle for imaging-guided chemo-phototherapy.

Targeted chemo-phototherapy has received widespread attention in cancer treatment for its advantages in reducing the side effects of chemotherapeutics and improving therapeutic effects. However, safe and efficient targeted-delivery of therapeutic agents remains a major obstacle. Herein, we successfully constructed an AS1411-functionalized triangle DNA origami (TOA) to codeliver chemotherapeutic drug (doxorubicin, DOX) and a photosensitizer (indocyanine green, ICG), denoted as TOADI (DOX/ICG-loaded TOA), for targeted synergistic chemo-phototherapy. In vitro studies show that AS1411 as an aptamer of nucleolin efficiently enhances the nanocarrier's endocytosis more than 3 times by tumor cells highly expressing nucleolin. Subsequently, TOADI controllably releases the DOX into the nucleus through the photothermal effect of ICG triggered by near-infrared (NIR) laser irradiation, and the acidic environment of lysosomes/endosomes facilitates the release. The downregulated Bcl-2 and upregulated Bax, Cyt c, and cleaved caspase-3 indicate that the synergistic chemo-phototherapeutic effect of TOADI induces the apoptosis of 4T1 cells, causing ~ 80% cell death. In 4T1 tumor-bearing mice, TOADI exhibits 2.5-fold targeted accumulation in tumor region than TODI without AS1411, and 4-fold higher than free ICG, demonstrating its excellent tumor targeting ability in vivo. With the synergetic treatment of DOX and ICG, TOADI shows a significant therapeutic effect of ~ 90% inhibition of tumor growth with negligible systemic toxicity. In addition, TOADI presents outstanding superiority in fluorescence and photothermal imaging. Taken together, this multifunctional DNA origami-based nanosystem with the advantages of specific tumor targeting and controllable drug release provides a new strategy for enhanced cancer therapy.

Preparation and identification of novel antioxidant peptides from camel bone protein.

Collagen hydrolysates are a vital source of bioactive peptides. The objective of this study was to prepare camel bone collagen hydrolysates with antioxidant activity, and to identify the peptides responsible for the antioxidant activity. To this end, single-factor and orthogonal tests were performed to explore the optimum preparation conditions. A hydrolysis time of 5 h, enzyme:substrate ratio of 1200 U/g, pH of 7.0, and a material:water ratio of 1:3.0 were adopted. Subsequently, the hydrolysates were purified using a series of chromatography procedures, and three novel peptides, GPPGPPGPPGPPGPPSGGFDF (hydroxylation), PATGDLTDFLK, and GSPGPQGPPGSIGPQ, possessing antioxidant abilities, were identified from the fraction using liquid chromatography-tandem mass spectrometry. The peptide PATGDLTDFLK showed excellent DPPH scavenging activity (39%) and a good cytoprotective effect on H2O2-induced oxidative stress damage in HepG2 cells with a 21.1% increase observed.

Stimulus-Detonated Biomimetic "Nanobomb" with Controlled Release of HSP90 Inhibitor to Disrupt Mitochondrial Function for Synergistic Gas and Photothermal Therapy.

Photothermal therapy (PTT) is considered a promising treatment for tumors; however, its efficacy is restricted by heat shock proteins (HSPs). Herein, a stimuli-responsive theranostic nanoplatform (M/D@P/E-P) is designed for synergistic gas therapy and PTT. This nanoplatform is fabricated by a load of manganese carbonyl (MnCO, CO donor) in dendritic mesoporous silicon (DMS), followed by the coating with polydopamine (PDA) and loading of epigallocatechin gallate (EGCG, HSP90 inhibitor). Upon near-infrared (NIR) irradiation, the photothermal effect of PDA can kill tumor cells and allow for the controlled drug release of MnCO and EGCG. Moreover, the acidity and H2 O2 -rich tumor microenvironment enable the decomposition of the released MnCO, accompanied by the production of CO. CO-initiated gas therapy can realize to disrupt the mitochondrial function, which will accelerate cell apoptosis and down-regulate HSP90 expression by decreasing intracellular ATP. The combination of EGCG and MnCO can significantly minimize the thermo-resistance of tumors and improve PTT sensitivity. In addition, the released Mn2+ enables T1 -weighted magnetic imaging of tumors. The therapeutic efficacy of the nanoplatform is methodically appraised and validated both in vitro and in vivo. Taken together, this study affords a prime paradigm for applying this strategy for enhanced PTT via mitochondrial dysfunction.

Automatic prediction model for online diaphragm motion tracking based on optical surface monitoring by machine learning.

Background: The aim of this study was to establish a correlation model between external surface motion and internal diaphragm apex movement using machine learning and to realize online automatic prediction of the diaphragm motion trajectory based on optical surface monitoring. Methods: The optical body surface parameters and kilovoltage (kV) X-ray fluoroscopic images of 7 liver tumor patients were captured synchronously for 50 seconds. The location of the diaphragm apex was manually delineated by a radiation oncologist and automatically detected with a convolutional network model in fluoroscopic images. The correlation model between the body surface parameters and the diaphragm apex of each patient was developed through linear regression (LR) based on synchronous datasets before radiotherapy. Model 1 (M1) was trained with data from the first 30 seconds of the datasets and tested with data from the following 20 seconds of the datasets in the first fraction to evaluate the intra-fractional prediction accuracy. Model 2 (M2) was trained with data from the first 30 seconds of the datasets in the next fraction. The motion trajectory of the diaphragm apex during the following 20 seconds in the next fraction was predicted with M1 and M2, respectively, to evaluate the inter-fractional prediction accuracy. The prediction errors of the 2 models were compared to analyze whether the correlation model needed to be re-established. Results: The average mean absolute error (MAE) and root mean square error (RMSE) using M1 trained with automatic detection location for the first fraction were 3.12±0.80 and 3.82±0.98 mm in the superior-inferior (SI) direction and 1.38±0.24 and 1.74±0.32 mm in the anterior-posterior (AP) direction, respectively. The average MAE and RMSE of M1 versus M2 in the AP direction were 2.63±0.71 versus 1.28±0.48 mm and 3.26±0.90 versus 1.61±0.60 mm, respectively. The average MAE and RMSE of M1 versus M2 in the SI direction were 5.84±1.22 versus 3.37±0.43 mm and 7.22±1.45 versus 4.07±0.54 mm, respectively. The prediction accuracy of M2 was significantly higher than that of M1. Conclusions: This study shows that it is feasible to use optical body surface information to automatically predict the diaphragm motion trajectory. At the same time, it is necessary to establish a new correlation model for the current fraction before each treatment.

A tumor-specific ROS self-supply enhanced cascade-responsive prodrug activation nanosystem for amplified chemotherapy against multidrug-resistant tumors.

Chemotherapy remains the mainstay of cancer treatment, and doxorubicin (DOX) is recommended as a first-line chemotherapy drug against cancer. However, systemic adverse drug reactions and multidrug resistance limit its clinical applications. Here, a tumor-specific reactive oxygen species (ROS) self-supply enhanced cascade responsive prodrug activation nanosystem (denoted as PPHI@B/L) was developed to optimize multidrug resistance tumor chemotherapy efficacy while minimizing the side effects. PPHI@B/L was constructed by encapsulating the ROS-generating agent ß-lapachone (Lap) and the ROS-responsive doxorubicin prodrug (BDOX) in acidic pH-sensitive heterogeneous nanomicelles. PPHI@B/L exhibited particle size decrease and charge increase when it reached the tumor microenvironment due to acid-triggered PEG detachment, to favor its endocytosis efficiency and deep tumor penetration. Furthermore, after PPHI@B/L internalization, rapidly released Lap was catalyzed by the overexpressed quinone oxidoreductase-1 (NQO1) enzyme NAD(P)H in tumor cells to selectively raise intracellular ROS levels. Subsequently, ROS generation further promoted the specific cascade activation of the prodrug BDOX to exert the chemotherapy effects. Simultaneously, Lap-induced ATP depletion reduced drug efflux, synergizing with increased intracellular DOX concentrations to assist in overcoming multidrug resistance. This tumor microenvironment-triggered cascade responsive prodrug activation nanosystem potentiates antitumor effects with satisfactory biosafety, breaking the chemotherapy limitation of multidrug resistance and significantly improving therapy efficiency. STATEMENT OF SIGNIFICANCE: Chemotherapy remains the mainstay of cancer treatment, and doxorubicin (DOX) is recommended as a first-line chemotherapy drug against cancer. However, systemic adverse drug reactions and multidrug resistance limit its clinical applications. Here, a tumor-specific reactive oxygen species (ROS) self-supply enhanced cascade responsive prodrug activation nanosystem (denoted as PPHI@B/L) was developed to optimize multidrug resistance tumor chemotherapy efficacy while minimizing the side effects. The work provides a new sight for simultaneously addressing the molecular mechanisms and physio-pathological disorders to overcome MDR in cancer treatment.

Quality monitoring of Shenmai injection by HPLC pharmacodynamic fingerprinting.

A probable problem of disconnection between chemical fingerprints and drug effects for TCMs would be contrary to the original intention of fingerprint research, and limits the development and application of fingerprints. In this study, Shenmai injection, as a treatment dosage form of coronary heart disease, shock, and viral myocarditis clinically, was applied as the research object. The fingerprint of Shenmai injection was constructed, and the pharmacodynamic test of antioxidant effect was carried out to obtain quantitative characteristics and pharmacodynamic data. On this basis, a monitoring model based on the HPLC pharmacodynamic fingerprint was established to evaluate the quality of Shenmai injections from different batches and different manufacturers. Results showed that the optimized HPLC method had good repeatability, precision, and stability. A total of 28 characteristic peaks were identified to provide more chemical information. Furthermore, 13 ginsenosides and notoginsenoside have been selected as characteristic components of LC/MS fingerprint method. 8 peaks closely related to antioxidant properties by multiple linear regression method, which were identified as Rg1, Re, Rf, Rb1, and some other ginsenosides using MS analysis. The monitoring model based on HPLC pharmacodynamic fingerprint could successfully identify quality differences for Shenmai injections. Based on the case study of Shenmai injection, the novel and practical fingerprint analytical strategy could be further applied to monitor or predict the quality of TCMs.

Bio-inspired Oxidative Stress Amplifier for Suppressing Cancer Metastasis and Imaging-Guided Combination Therapy.

Antioxidant-defense systems of tumor cells protect them from oxidative damage and is strongly associated with tumor metastasis. In this work, a mussel-inspired multifunctional nanomedicine (ZS-MB@P) has been designed for inhibiting tumor growth and metastasis through amplified oxidative stress and photothermal/magnetothermal/photodynamic triple-combination therapy. This nanomedicine was fabricated via loading a silica shell on the magnetic nano-octahedrons [zinc-doped magnetic Fe3O4 nano-octahedrons] by encapsulating photosensitizer methylene blue (MB) and subsequently coating polydopamine (PDA) shells as "gatekeeper." The nanomedicine could realize photothermal therapy, photodynamic therapy, and magnetic hyperthermia after treatment with near-infrared (NIR) irradiation and applied magnetic field. Under pH and NIR stimulation, controlled amount of MB was released to produced exogenous reactive oxygen species. Noteworthy, PDA can amplify intracellular oxidative stress by depleting glutathione, thus inhibiting breast cancer metastasis effectively since oxidative stress is an important barrier to tumor metastasis. The outstanding ability to suppress tumor growth and metastasis was comprehensively assessed and validated both in vitro and in vivo. Moreover, the nanomedicine showed outstanding T2 magnetic resonance imaging for tracking the treatment process. Taken together, this work offers an innovative approach in the synergistic treatment of recalcitrant breast cancer.

A Medical Assistive Robot for Telehealth Care During the COVID-19 Pandemic: Development and Usability Study in an Isolation Ward.

BACKGROUND: The COVID-19 pandemic is affecting the mental and emotional well-being of patients, family members, and health care workers. Patients in the isolation ward may have psychological problems due to long-term hospitalization, the development of the epidemic, and the inability to see their families. A medical assistive robot (MAR), acting as an intermediary of communication, can be deployed to address these mental pressures. OBJECTIVE: CareDo, a MAR with telepresence and teleoperation functions, was developed in this work for remote health care. The aim of this study was to investigate its practical performance in the isolation ward during the pandemic. METHODS: Two systems were integrated into the CareDo robot. For the telepresence system, a web real-time communications solution is used for the multiuser chat system and a convolutional neural network is used for expression recognition. For the teleoperation system, an incremental motion mapping method is used for operating the robot remotely. A clinical trial of this system was conducted at First Affiliated Hospital, Zhejiang University. RESULTS: During the clinical trials, tasks such as video chatting, emotion detection, and medical supplies delivery were performed via the CareDo robot. Seven voice commands were set for performing system wakeup, video chatting, and system exiting. Durations from 1 to 3 seconds of common commands were set to improve voice command detection. The facial expression was recorded 152 times for a patient in 1 day for the psychological intervention. The recognition accuracy reached 95% and 92.8% for happy and neutral expressions, respectively. CONCLUSIONS: Patients and health care workers can use this MAR in the isolation ward for telehealth care during the COVID-19 pandemic. This can be a useful approach to break the chains of virus transmission and can also be an effective way to conduct remote psychological intervention.

Corrigendum to "Remodeling tumor immunosuppressive microenvironment via a novel bioactive nanovaccines potentiates the efficacy of cancer immunotherapy" [Bioactive Mater. 16 107-119].

[This corrects the article DOI: 10.1016/j.bioactmat.2022.03.008.].