Carbon-based Nanomaterials in Photothermal Therapy Guided by Photoacoustic Imaging: State of Knowledge and Recent Advances.

Carbon-based nanomaterials (CBNM)have been widely used in various fields due to their excellent physicochemical properties. In particular, in the area of tumor diagnosis and treatment, researchers have frequently reported them for their potential fluorescence, photoacoustic (PA), and ultrasound imaging performance, as well as their photothermal, photodynamic, sonodynamic, and other therapeutic properties. As the functions of CBNM are increasingly developed, their excellent imaging properties and superior tumor treatment effects make them extremely promising theranostic agents. This review aims to integrate the considered and researched information in a specific field of this research topic and systematically present, summarize, and comment on the efforts made by authoritative scholars. In this review, we summarized the work exploring carbon-based materials in the field of tumor imaging and therapy, focusing on PA imaging-guided photothermal therapy (PTT) and discussing their imaging and therapeutic mechanisms and developments. Finally, the current challenges and potential opportunities of carbon-based materials for PA imaging-guided PTT are presented, and issues that researchers should be aware of when studying CBNM are provided.

The LMIT: Light-mediated minimally-invasive theranostics in oncology.

Minimally-invasive diagnosis and therapy have gradually become the trend and research hotspot of current medical applications. The integration of intraoperative diagnosis and treatment is a development important direction for real-time detection, minimally-invasive diagnosis and therapy to reduce mortality and improve the quality of life of patients, so called minimally-invasive theranostics (MIT). Light is an important theranostic tool for the treatment of cancerous tissues. Light-mediated minimally-invasive theranostics (LMIT) is a novel evolutionary technology that integrates diagnosis and therapeutics for the less invasive treatment of diseased tissues. Intelligent theranostics would promote precision surgery based on the optical characterization of cancerous tissues. Furthermore, MIT also requires the assistance of smart medical devices or robots. And, optical multimodality lay a solid foundation for intelligent MIT. In this review, we summarize the important state-of-the-arts of optical MIT or LMIT in oncology. Multimodal optical image-guided intelligent treatment is another focus. Intraoperative imaging and real-time analysis-guided optical treatment are also systemically discussed. Finally, the potential challenges and future perspectives of intelligent optical MIT are discussed.

The State-of-the-Art and Perspectives of Laser Ablation for Tumor Treatment.

Tumors significantly impact individuals' physical well-being and quality of life. With the ongoing advancements in optical technology, information technology, robotic technology, etc., laser technology is being increasingly utilized in the field of tumor treatment, and laser ablation (LA) of tumors remains a prominent area of research interest. This paper presents an overview of the recent progress in tumor LA therapy, with a focus on the mechanisms and biological effects of LA, commonly used ablation lasers, image-guided LA, and robotic-assisted LA. Further insights and future prospects are discussed in relation to these aspects, and the paper proposed potential future directions for the development of tumor LA techniques.

Improved outcomes of UM171-expanded cord blood transplantation compared with other graft sources: real-world evidence.

Cord blood (CB) transplantation is hampered by low cell dose and high nonrelapse mortality (NRM). A phase 1-2 trial of UM171-expanded CB transplants demonstrated safety and favorable preliminary efficacy. The aim of the current analysis was to retrospectively compare results of the phase 1-2 trial with those after unmanipulated CB and matched-unrelated donor (MUD) transplants. Data from recipients of CB and MUD transplants were obtained from the Center for International Blood and Marrow Transplant Research (CIBMTR) database. Patients were directly matched for the number of previous allogeneic hematopoietic stem cell transplants (alloHCT), disease and refined Disease Risk Index. Patients were further matched by propensity score for age, comorbidity index, and performance status. Primary end points included NRM, progression-free survival (PFS), overall survival (OS), and graft-versus-host disease (GVHD)-free relapse-free survival (GRFS) at 1 and 2 years after alloHCT. Overall, 137 patients from CIBMTR (67 CB, 70 MUD) and 22 with UM171-expanded CB were included. NRM at 1 and 2 years was lower, PFS and GRFS at 2 years and OS at 1 year were improved for UM171-expanded CBs compared with CB controls. Compared with MUD controls, UM171 recipients had lower 1- and 2-year NRM, higher 2-year PFS, and higher 1- and 2-year GRFS. Furthermore, UM171-expanded CB recipients experienced less grades 3-4 acute GVHD and chronic GVHD compared with MUD graft recipients. Compared with real-world evidence with CB and MUD alloHCT, this study suggests that UM171-expanded CB recipients may benefit from lower NRM and higher GRFS. This trial was registered at www.clinicaltrials.gov as #NCT02668315.

Investigation of functional connectivity in Bell's palsy using functional magnetic resonance imaging: prospective cross-sectional study.

Background: The most common cause of lower motor neuron facial palsy is Bell's palsy (BP). BP results in partial or complete inability to automatically move the facial muscles on the affected side and, in some cases, to close the eyelids, which can cause permanent eye damage. This study investigated changes in brain function and connectivity abnormalities in patients with BP. Methods: This study included 46 patients with unilateral BP and 34 healthy controls (HCs). Resting-state brain functional magnetic resonance imaging (fMRI) images were acquired, and Toronto Facial Grading System (TFGS) scores were obtained for all participants. The fractional amplitude of low-frequency fluctuation (fALFF) was estimated, and the relationship between the TFGS and fALFF was determined using correlation analysis for brain regions with changes in fALFF in those with BP versus HCs. Brain regions associated with TFGS were used as seeds for further functional connectivity (FC) analysis; relationships between FC values of abnormal areas and TFGS scores were also analyzed. Results: Activation of the right precuneus, right angular gyrus, left supramarginal gyrus, and left middle occipital gyrus was significantly decreased in the BP group. fALFF was significantly higher in the right thalamus, vermis, and cerebellum of the BP group compared with that in the HC group (P<0.05). The FC between the left middle occipital gyrus and right angular gyrus, left precuneus, and right middle frontal gyrus increased sharply, but decreased in the left angular gyrus, left posterior cingulate gyrus, left middle frontal gyrus, inferior cerebellum, and left middle temporal gyrus. Furthermore, the fALFF in the left middle occipital gyrus was negatively correlated with TFGS score (R=0.144; P=0.008). Conclusions: The pathogenesis of BP is closely related to functional reorganization of the cerebral cortex. Patients with BP have altered fALFF activity in cortical regions associated with facial motion feedback monitoring.

autoSMIM: Automatic Superpixel-Based Masked Image Modeling for Skin Lesion Segmentation.

Skin lesion segmentation from dermoscopic images plays a vital role in early diagnoses and prognoses of various skin diseases. However, it is a challenging task due to the large variability of skin lesions and their blurry boundaries. Moreover, most existing skin lesion datasets are designed for disease classification, with relatively fewer segmentation labels having been provided. To address these issues, we propose a novel automatic superpixel-based masked image modeling method, named autoSMIM, in a self-supervised setting for skin lesion segmentation. It explores implicit image features from abundant unlabeled dermoscopic images. autoSMIM begins with restoring an input image with randomly masked superpixels. The policy of generating and masking superpixels is then updated via a novel proxy task through Bayesian Optimization. The optimal policy is subsequently used for training a new masked image modeling model. Finally, we finetune such a model on the downstream skin lesion segmentation task. Extensive experiments are conducted on three skin lesion segmentation datasets, including ISIC 2016, ISIC 2017, and ISIC 2018. Ablation studies demonstrate the effectiveness of superpixel-based masked image modeling and establish the adaptability of autoSMIM. Comparisons with state-of-the-art methods show the superiority of our proposed autoSMIM. The source code is available at https://github.com/Wzhjerry/autoSMIM.

Carbon-Based Stimuli-Responsive Nanomaterials: Classification and Application.

Carbon-based nanomaterials, including carbon nanotubes, carbon nanospheres, and carbon nanofibers, are becoming a research hotspot due to their unique structure and good mechanical, thermal, electrical, optical, and chemical properties. With the development of material synthesis technology, they can be functionalized and used in various fields such as energy, environment, and biomedicine. In particular, stimuli-responsive carbon-based nanomaterials have stood out in recent years because of their smart behavior. Researchers have applied carbon-based nanomaterials to different disease treatments based on their stimulus-response properties. In this paper, based on stimuli-responsive carbon-based nanomaterials' morphology, we categorize them into carbon nanotubes, carbon nanospheres, and carbon nanofibers according to their morphology. Then, their applications in probes, bioimaging, tumor therapy, and other fields are discussed. Finally, we address the advantages and disadvantages of carbon-based stimuli-responsive nanomaterials and discuss their future perspective.

Evaluation of parametrial infiltration in patients with IB-IIB cervical cancer by a radiomics model integrating features from tumoral and peritumoral regions in 18 F-fluorodeoxy glucose positron emission tomography/MR images.

Parametrial infiltration (PMI) is an essential factor in staging and planning treatment of cervical cancer. The purpose of this study was to develop a radiomics model for accessing PMI in patients with IB-IIB cervical cancer using features from 18 F-fluorodeoxy glucose (18 F-FDG) positron emission tomography (PET)/MR images. In this retrospective study, 66 patients with International Federation of Gynecology and Obstetrics stage IB-IIB cervical cancer (22 with PMI and 44 without PMI) who underwent 18 F-FDG PET/MRI were divided into a training dataset (n = 46) and a testing dataset (n = 20). Features were extracted from both the tumoral and peritumoral regions in 18 F-FDG PET/MR images. Single-modality and multimodality radiomics models were developed with random forest to predict PMI. The performance of the models was evaluated with F1 score, accuracy, and area under the curve (AUC). The Kappa test was used to observe the differences between PMI evaluated by radiomics-based models and pathological results. The intraclass correlation coefficient for features extracted from each region of interest (ROI) was measured. Three-fold crossvalidation was conducted to confirm the diagnostic ability of the features. The radiomics models developed by features from the tumoral region in T2 -weighted images (F1 score = 0.400, accuracy = 0.700, AUC = 0.708, Kappa = 0.211, p = 0.329) and the peritumoral region in PET images (F1 score = 0.533, accuracy = 0.650, AUC = 0.714, Kappa = 0.271, p = 0.202) achieved the best performances in the testing dataset among the four single-ROI radiomics models. The combined model using features from the tumoral region in T2 -weighted images and the peritumoral region in PET images achieved the best performance (F1 score = 0.727, accuracy = 0.850, AUC = 0.774, Kappa = 0.625, p < 0.05). The results suggest that 18 F-FDG PET/MRI can provide complementary information regarding cervical cancer. The radiomics-based method integrating features from the tumoral and peritumoral regions in 18 F-FDG PET/MR images gave a superior performance for evaluating PMI.

Designing biomimetic scaffolds for skin tissue engineering.

There is a general increase in the number of patients with non-healing skin wounds, imposing a huge social and economic burden on patients and healthcare systems. Severe skin injury is an important clinical challenge. There is a lack of skin donors, and skin defects and scarring after surgery can lead to impaired skin function and skin integrity. Researchers worldwide have made great efforts to create human skin organs but are limited by the lack of key biological structural features of the skin. Tissue engineering repairs damaged tissue by incorporating cells into biocompatible and biodegradable porous scaffolds. Skin tissue engineered scaffolds not only have appropriate physical and mechanical properties but also exhibit skin-like surface topography and microstructure, which can promote cell adhesion, proliferation, and differentiation. At present, skin tissue engineering scaffolds are being developed into clinical applications that can overcome the limitations of skin transplantation, promote the process of wound healing, and repair skin tissue damage. This provides an effective therapeutic option for the management of patients with skin lesions. This paper reviews the structure and function of skin tissue and the process of wound healing, and summarizes the materials and manufacturing methods used to fabricate skin tissue engineering scaffolds. Next, the design considerations of skin tissue engineering scaffolds are discussed. An extensive review of skin scaffolds and clinically approved scaffold materials is presented. Lastly, some important challenges in the construction of skin tissue engineering scaffolds are presented.

A 3D Tumor-Mimicking In Vitro Drug Release Model of Locoregional Chemoembolization Using Deep Learning-Based Quantitative Analyses.

Primary liver cancer, with the predominant form as hepatocellular carcinoma (HCC), remains a worldwide health problem due to its aggressive and lethal nature. Transarterial chemoembolization, the first-line treatment option of unresectable HCC that employs drug-loaded embolic agents to occlude tumor-feeding arteries and concomitantly delivers chemotherapeutic drugs into the tumor, is still under fierce debate in terms of the treatment parameters. The models that can produce in-depth knowledge of the overall intratumoral drug release behavior are lacking. This study engineers a 3D tumor-mimicking drug release model, which successfully overcomes the substantial limitations of conventional in vitro models through utilizing decellularized liver organ as a drug-testing platform that uniquely incorporates three key features, i.e., complex vasculature systems, drug-diffusible electronegative extracellular matrix, and controlled drug depletion. This drug release model combining with deep learning-based computational analyses for the first time permits quantitative evaluation of all important parameters associated with locoregional drug release, including endovascular embolization distribution, intravascular drug retention, and extravascular drug diffusion, and establishes long-term in vitro-in vivo correlations with in-human results up to 80 d. This model offers a versatile platform incorporating both tumor-specific drug diffusion and elimination settings for quantitative evaluation of spatiotemporal drug release kinetics within solid tumors.

A Totipotent "All-In-One" Peptide Sequentially Blocks Immune Checkpoint and Reverses the Immunosuppressive Tumor Microenvironment.

Immune checkpoint blockade combined with reversal of the immunosuppressive tumor microenvironment (TME) can dramatically enhance anti-tumor immunity, which can be achieved by using multiple-agent therapy. However, the optimal dose and order of administration of different agents remain elusive. To address this dilemma, multiple agents are often grafted together to construct "all-in-one" totipotent drugs, but this usually comes at the cost of a lack of synergy between the agents. Herein, by comprehensively analyzing the conserved sites of the immune checkpoint and TME drug targets, peptide secondary structures, assembly properties, and other physicochemical properties, a high-content peptide library is designed. By using the "3D-molecular-evolution" screening strategy, an efficient and totipotent "all-in-one" peptide (TAP) is obtained, which possesses the abilities of self-assembling, blocking the PD-1/PD-L1 axis, inhibiting Rbm38-eIF4E complex formation, and activating p53. It is shown that in mice treated with TAP, with either subcutaneous tumors or patient-derived xenografts, PD-L1 is blocked, with increased activation of both T and NK cells whilst reversing the immunosuppressive TME. Moreover, TAP can mitigate tumor activity and suppress tumor growth, showing superior therapeutic effect over antibody-based drugs.

Three-Year Outcomes in Recipients of Mismatched Unrelated Bone Marrow Donor Transplants Using Post-Transplantation Cyclophosphamide: Follow-Up from a National Marrow Donor Program-Sponsored Prospective Clinical Trial.

The use of post-transplantation cyclophosphamide (PTCy) as graft-versus-host disease (GVHD) prophylaxis has resulted in reductions in GVHD and improved outcomes in allogeneic hematopoietic cell transplantation (HCT) using HLA-mismatched related donors. We report the 3-year outcomes of the first multicenter prospective clinical trial using PTCy in the setting of mismatched unrelated donor (MMUD) bone marrow HCT. The study enrolled 80 patients, treated with either myeloablative conditioning (MAC; n = 40) or reduced-intensity conditioning (RIC; n = 40), with the primary endpoint of 1-year overall survival (OS). The median follow-up for this study was 34 months (range, 12 to 46 months) in the RIC group and 36 months (range, 18 to 49 months) in the MAC group. Three-year OS and nonrelapse mortality were 70% and 15%, respectively, in the RIC group and 62% and 10% in the MAC group. No GVHD was reported after 1 year. The incidence of relapse was 29% in the RIC group and 51% in the MAC group. OS did not differ based on HLA match grade (63% in the 7/8 strata and 71% in the 4 to 6/8 strata). These encouraging outcomes, which were sustained for 3 years post-HCT, support the continued exploration of MMUD HCT using a PTCy platform. Important future areas to address include relapse reduction and furthering our understanding of optimal donor selection based on HLA and non-HLA factors.

Violet Phosphorus Nanosheet: A Biocompatible and Stable Platform for Stimuli-Responsive Multimodal Cancer Phototherapy.

As a functional 2D material, black phosphorus (BP) has garnered wide attention from many researchers in recent years. BP has a wide NIR absorption window and is a promising candidate for cancer phototherapy including photothermal therapy (PTT) and photodynamic therapy (PDT). However, due to its rapid degradation and short shelf-life in conventional water, the application of BP in the field of cancer therapy is limited. Violet phosphorus (VP), the more stable allotrope of phosphorus, has not yet been investigated for its function and biological application. In this study, VP nanosheets are successfully fabricated by liquid-phase exfoliation and demonstrated that their shelf-life in deionized water could be as long as 10 days, which is much longer than that of BP. Through in vivo and in vitro experiments, the PDT, PTT, and catalytic therapeutic effects of VP, as well as its excellent biosafety for the first time are shown. VP effectively inhibits tumor growth without causing major side effects. The current study provides new ideas and strategies for the biological application of 2D sheets of phosphorus isotope and lays the foundation for further studies on exploring the biomedical application of phosphorus isotopes.

Automatic Segmentation of Laser-Induced Injury OCT Images Based on a Deep Neural Network Model.

Optical coherence tomography (OCT) has considerable application potential in noninvasive diagnosis and disease monitoring. Skin diseases, such as basal cell carcinoma (BCC), are destructive; hence, quantitative segmentation of the skin is very important for early diagnosis and treatment. Deep neural networks have been widely used in the boundary recognition and segmentation of diseased areas in medical images. Research on OCT skin segmentation and laser-induced skin damage segmentation based on deep neural networks is still in its infancy. Here, a segmentation and quantitative analysis pipeline of laser skin injury and skin stratification based on a deep neural network model is proposed. Based on the stratification of mouse skins, a laser injury model of mouse skins induced by lasers was constructed, and the multilayer structure and injury areas were accurately segmented by using a deep neural network method. First, the intact area of mouse skin and the damaged areas of different laser radiation doses are collected by the OCT system, and then the labels are manually labeled by experienced histologists. A variety of deep neural network models are used to realize the segmentation of skin layers and damaged areas on the skin dataset. In particular, the U-Net model based on a dual attention mechanism is used to realize the segmentation of the laser-damage structure, and the results are compared and analyzed. The segmentation results showed that the Dice coefficient of the mouse dermis layer and injury area reached more than 0.90, and the Dice coefficient of the fat layer and muscle layer reached more than 0.80. In the evaluation results, the average surface distance (ASSD) and Hausdorff distance (HD) indicated that the segmentation results are excellent, with a high overlap rate with the manually labeled area and a short edge distance. The results of this study have important application value for the quantitative analysis of laser-induced skin injury and the exploration of laser biological effects and have potential application value for the early noninvasive detection of diseases and the monitoring of postoperative recovery in the future.

Triarylboron-Doped Acenethiophenes as Organic Sonosensitizers for Highly Efficient Sonodynamic Therapy with Low Phototoxicity.

The development of efficient organic sonosensitizers is crucial for sonodynamic therapy (SDT) in the field of cancer treatment. Herein, a new strategy for the development of efficient organic sonosensitizers based on triarylboron-doped acenethiophene scaffolds is presented. The attachment of boron to the linear acenethiophenes lowers the lowest unoccupied molecular orbital (LUMO) energy, resulting in redshifted absorptions and emissions. After encapsulation with the amphiphilic polymer DSPE-mPEG2000 , it is found that the nanostructured BAnTh-NPs and BTeTh-NPs (nanoparticles of BAnTh and BTeTh) shows efficient hydroxyl radical (• OH) generation under ultrasound (US) irradiation in aqueous solution with almost no phototoxicity, which can overcome the shortcomings of O2 -dependent SDT and avoid the potential cutaneous phototoxicity issue. In vitro and in vivo therapeutic results validate that boron-doped acenethiophenes as sonosensitizers enable high SDT efficiency with low phototoxicity and good biocompatibility, indicating that boron-functionalization of acenes is a promising strategy toward organic sonosensitizers for SDT.

Near-Infrared-Absorbing B-N Lewis Pair-Functionalized Anthracenes: Electronic Structure Tuning, Conformational Isomerism, and Applications in Photothermal Cancer Therapy.

B-N-fused dianthracenylpyrazine derivatives are synthesized to generate new low gap chromophores. Photophysical and electrochemical, crystal packing, and theoretical studies have been performed. Two energetically similar conformers are identified by density functional theory calculations, showing that the core unit adopts a curved saddle-like shape (x-isomer) or a zig-zag conformation (z-isomer). In the solid state, the z-isomer is prevalent according to an X-ray crystal structure of a C6F5-substituted derivative (4-Pf), but variable-temperature nuclear magnetic resonance studies suggest a dynamic behavior in solution. B-N fusion results in a large decrease of the HOMO-LUMO gap and dramatically lowers the LUMO energy compared to the all-carbon analogues. 4-Pf in particular shows significant absorbance at greater than 700 nm while being almost transparent throughout the visible region. After encapsulation in the biodegradable polymer DSPE-mPEG2000, 4-Pf nanoparticles (4-Pf-NPs) exhibit good water solubility, high photostability, and an excellent photothermal conversion efficiency of ∼41.8%. 4-Pf-NPs are evaluated both in vitro and in vivo as photothermal therapeutic agents. These results uncover B-N Lewis pair functionalization of PAHs as a promising strategy toward new NIR-absorbing materials for photothermal applications.

Hydrogel-Based Stimuli-Responsive Micromotors for Biomedicine.

The rapid development of medical micromotors draws a beautiful blueprint for the noninvasive or minimally invasive diagnosis and therapy. By combining stimuli-sensitive hydrogel materials, micromotors are bestowed with new characteristics such as stimuli-responsive shape transformation/morphing, excellent biocompatibility and biodegradability, and drug loading ability. Actuated by chemical fuels or external fields (e.g., magnetic field, ultrasound, light, and electric field), hydrogel-based stimuli-responsive (HBSR) micromotors can be utilized to load therapeutic agents into the hydrogel networks or directly grip the target cargos (e.g., drug-loaded particles, cells, and thrombus), transport them to sites of interest (e.g., tumor area and diseased tissues), and unload the cargos or execute a specific task (e.g., cell capture, targeted sampling, and removal of blood clots) in response to a stimulus (e.g., change of temperature, pH, ion strength, and chemicals) in the physiological environment. The high flexibility, adaptive capacity, and shape morphing property enable the HBSR micromotors to complete specific medical tasks in complex physiological scenarios, especially in confined, hard-to-reach tissues, and vessels of the body. Herein, this review summarizes the current progress in hydrogel-based medical micromotors with stimuli responsiveness. The thermo-responsive, photothermal-responsive, magnetocaloric-responsive, pH-responsive, ionic-strength-responsive, and chemoresponsive micromotors are discussed in detail. Finally, current challenges and future perspectives for the development of HBSR micromotors in the biomedical field are discussed.

Predictive values of the SOFA score and procalcitonin for septic shock after percutaneous nephrolithotomy.

To investigate the value of combination of the Sequential Organ Failure Assessment (SOFA) score and procalcitonin (PCT) for prediction of septic shock after percutaneous nephrolithotomy (PCNL). A total of 1328 patients receiving PCNL for renal calculi were allocated into control group (without septic shock) and septic shock group, and related data were retrospectively collected. Univariate analysis was firstly performed, and the variables with two sided P < 0.10 were then included in logistic regression analysis to determine independent risk factors. Receiver operating characteristic (ROC) curve was utilized to evaluate the predictive values. Area under curve (AUC) was compared using Z test. Postoperative septic shock was developed in 61 patients (4.6%) and not developed in 1267 patients (95.3%). Multivariate analysis demonstrated that SOFA score (OR: 1.316, 95% CI 1.125-1.922), PCT (OR: 1.205, 95% CI 1.071-1.696) and operative time (OR: 1.108, 95% CI 1.032-1.441) were independent risk factors for septic shock with adjustment for sex, history of urolithiasis surgery, positive history of urine culture and history of PCNL. The ROC curves demonstrated that the AUCs of SOFA score and PCT for predicting septic shock after PCNL were 0.896 (95% CI 0.866-0.927) and 0.792 (95% CI 0.744-0.839), respectively. The AUC of their combination was 0.971 (95% CI 0.949-0.990), which was higher than those of individual predictions (vs 0.896, Z = 4.086, P < 0.001; vs 0.792, Z = 6.983, P < 0.001). Both the SOFA score and PCT could be applied in predicting septic shock after PCNL, and their combination could further elevate the diagnostic ability.