Genetic and phenotypic profiling of single living circulating tumor cells from patients with microfluidics.

Accurate prediction of the efficacy of immunotherapy for cancer patients through the characterization of both genetic and phenotypic heterogeneity in individual patient cells holds great promise in informing targeted treatments, and ultimately in improving care pathways and clinical outcomes. Here, we describe the nanoplatform for interrogating living cell host-gene and (micro-)environment (NICHE) relationships, that integrates micro- and nanofluidics to enable highly efficient capture of circulating tumor cells (CTCs) from blood samples. The platform uses a unique nanopore-enhanced electrodelivery system that efficiently and rapidly integrates stable multichannel fluorescence probes into living CTCs for in situ quantification of target gene expression, while on-chip coculturing of CTCs with immune cells allows for the real-time correlative quantification of their phenotypic heterogeneities in response to immune checkpoint inhibitors (ICI). The NICHE microfluidic device provides a unique ability to perform both gene expression and phenotypic analysis on the same single cells in situ, allowing us to generate a predictive index for screening patients who could benefit from ICI. This index, which simultaneously integrates the heterogeneity of single cellular responses for both gene expression and phenotype, was validated by clinically tracing 80 non-small cell lung cancer patients, demonstrating significantly higher AUC (area under the curve) (0.906) than current clinical reference for immunotherapy prediction.

Interactive model for predicting the oncological outcome of patients with early-stage huge hepatocellular carcinoma after hepatectomy: a multicenter population-based study.

An interactive model for predicting the oncological outcome of patients with early-stage huge hepatocellular carcinoma (ES-HHCC) after hepatectomy is still lacking. This study was aimed at exploring the independent risk parameters and developing an interactive model for predicting the cancer-specific survival (CSS) of ES-HHCC. Data from patients with ES-HHCC who underwent hepatectomy were collected. The dimensionality of the clinical features was reduced by least absolute shrinkage and selection operator regression and further screened as predictors of CSS by Cox regression. Then, an interactive prediction model was developed and validated. Among the 514 screened patients, 311 and 203 of them were assigned into the training and validation cohort, respectively. Six independent variables, including alpha-fetoprotein, cirrhosis, microvascular invasion, satellite, tumor morphology, and tumor diameter, were identified and incorporated into the prediction model for CSS. The model achieved C-indices of 0.724 and 0.711 in the training and validation cohorts, respectively. Calibration curves showed general consistency in both cohorts. Compared with single predictor, the model had a better performance and greater benefit according to the time-independent receiver operating characteristic curve and decision curve analysis (P < 0.05). The calculator owned satisfactory accuracy and flexible operability for predicting the CSS of ES-HHCC, which could serve as a practical tool to stratify patients with different risks, and guide decision-making.

Association between COVID 19 exposure and expression of malignant pathological features in oral squamous cell carcinoma: A retrospective cohort study.

OBJECTIVES: To analyze the relationship between the clinical and pathological characters of OSCC and COVID 19 exposure. MATERIALS AND METHODS: A retrospective cohort study in patients with OSCC with or without COVID 19 was performed. A total of 200 OSCC patients treated with surgery from 2019 to 2023 were included. Clinical and pathological features were analysed between two groups. Characters with statistical difference were further analysed by performing univariate analysis and logistic regression analysis. RESULTS: The expression of Ki67 (n = 57, 71.3 %, P < 0.001) and CyclinD1 (n = 64, 80 %, P < 0.001) in OSCC with the exposure history of COVID 19 is higher than that in patients never exposed to COVID 19. COVID 19 exposure history is an independent influencing factor for higher expression of Ki67 (OR = 4.04, 95 % CI: 1.87-8.72, P < 0.001) and CyclinD1 (OR = 5.45, 95 % CI: 2.56-11.60, P < 0.001). CONCLUSION: COVID 19 may suggest more invasive malignant biological behavior of cancer cells in OSCC.

Fast and slow: Recording neuromodulator dynamics across both transient and chronic time scales.

Neuromodulators transform animal behaviors. Recent research has demonstrated the importance of both sustained and transient change in neuromodulators, likely due to tonic and phasic neuromodulator release. However, no method could simultaneously record both types of dynamics. Fluorescence lifetime of optical reporters could offer a solution because it allows high temporal resolution and is impervious to sensor expression differences across chronic periods. Nevertheless, no fluorescence lifetime change across the entire classes of neuromodulator sensors was previously known. Unexpectedly, we find that several intensity-based neuromodulator sensors also exhibit fluorescence lifetime responses. Furthermore, we show that lifetime measures in vivo neuromodulator dynamics both with high temporal resolution and with consistency across animals and time. Thus, we report a method that can simultaneously measure neuromodulator change over transient and chronic time scales, promising to reveal the roles of multi-time scale neuromodulator dynamics in diseases, in response to therapies, and across development and aging.

Systemic and Local Administration of a Dual-siRNA Complex Efficiently Inhibits Tumor Growth and Bone Invasion in Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) accounts for nearly 90% of oral and oropharyngeal cancer cases and is characterized by high mortality and poor prognosis. RNA-based gene therapies have been developed as an emerging option for cancer treatment, but it has not been widely explored in OSCC. In this work, we developed an efficient siRNA cationic micelle DOTAP-mPEG-PCL (DMP) by self-assembling the cationic lipid DOTAP and monomethoxy poly(ethylene glycol)-poly(ε-caprolactone) (mPEG-PCL) polymer. We tested the characteristics and transformation efficiency of this micelle and combined DMP with siRNA targeting STAT3 and TGF-ß to evaluate the antitumor effect and bone invasion interfering in vitro and in vivo. The average size of the DMP was 28.27 ± 1.62 nm with an average zeta potential of 54.60 ± 0.29 mV. The DMP/siRNA complex showed high delivery efficiency, with rates of 97.47 ± 0.42% for HSC-3. In vitro, the DMP/siSTAT3 complex exhibited an obvious cell growth inhibition effect detected by MTT assay (an average cell viability of 25.1%) and clonogenic assay (an average inhibition rate of 51.9%). Besides, the supernatant from HSC-3 transfected by DMP/siTGF-ß complexes was found to interfere with osteoclast differentiation in vitro. Irrespective of local or systemic administration, DMP/siSTAT3+siTGF-ß showed antitumor effects and bone invasion inhibition in the OSCC mice mandibular invasion model according to tumor volume assays and Micro-CT scanning. The complex constructed by DMP cationic micelles and siSTAT3+siTGF-ß represents a potential RNA-based gene therapy delivery system for OSCC.

Oncological prognosis and morbidity of hepatectomy in elderly patients with hepatocellular carcinoma: a propensity score matching and multicentre study.

PURPOSE: With increasing life expectancy, the number of elderly patients (≥ 65 years) with hepatocellular carcinoma (HCC) has steadily increased. Hepatectomy remains the first-line treatment for HCC patients. However, the prognosis of hepatectomy for elderly patients with HCC remains unclear. METHODS: Clinical and follow-up data from 1331 HCC patients who underwent surgery between 2008 and 2020 were retrospectively retrieved from a multicentre database. Patients were divided into elderly (≥ 65 years) and non-elderly (< 65 years) groups, and PSM was used to balance differences in the baseline characteristics. The postoperative major morbidity and cancer-specific survival (CSS) of the two groups were compared and the independent factors that were associated with the two study endpoints were identified by multivariable regression analysis. RESULTS: Of the 1331 HCC patients enrolled in this study, 363 (27.27%) were elderly, while 968 (72.73%) were not. After PSM, 334 matched samples were obtained. In the propensity score matching (PSM) cohort, a higher rate of major morbidity was found in elderly patients (P = 0.040) but the CSS was similar in the two groups (P = 0.087). Multivariate analysis revealed that elderly age was not an independent risk factor associated with high rates of major morbidity (P = 0.117) or poor CSS (P = 0.873). The 1-, 3- and 5-year CSS rates in the elderly and non-elderly groups were 91.0% versus 86.2%, 71.3% versus 68.8% and 55.9% versus 58.0%, respectively. Preoperative alpha fetoprotein (AFP) level, Child‒Pugh grade, intraoperative blood transfusion, extended hemi hepatectomy, and tumour diameter could affect the postoperative major morbidity and preoperative AFP level, cirrhosis, Child‒Pugh grade, macrovascular invasion, microvascular invasion (MVI), satellite nodules, and tumor diameter were independently and significantly associated with CSS. CONCLUSION: Age itself had no significant effect on the prognosis of elderly patients with HCC after hepatectomy. Hepatectomy can be safely performed in elderly patients after cautious perioperative management.

Incidence of Unintentional Intraoperative Hypothermia and Its Risk Factors in Oral and Maxillofacial Surgery: A Prospective Study.

PURPOSE: Unintentional intraoperative hypothermia is a common complication in patients who undergo open surgery, increasing the risk of adverse outcomes. However, few studies have focused on intraoperative hypothermia during oral and maxillofacial surgery. Our study aimed to analyze the prevalence and risk factors of hypothermia in patients who underwent oral and maxillofacial surgery. DESIGN: A prospective cohort study was conducted on 128 patients who underwent oral and maxillofacial surgery. METHODS: This prospective study was conducted at West China Hospital of Stomatology between December 2020 and May 2021, and each patient was followed for at least 1-month postoperatively. Patients who underwent oral and maxillofacial surgery under general anesthesia, with at least 1-month follow-up were analyzed. The primary variable was intraoperative hypothermia, defined as core body temperature less than 36°C, measured using a tympanic thermometer during the surgery. We performed univariate and multivariate logistic regression analyses to identify the risk factors of unintentional intraoperative hypothermia. FINDINGS: The mean age of the 128 patients was 31.0 ± 20.9 years, and there was a male predominance (53.1%), with male to female ratio of 1.13:1. Thirty-one patients (24.2%) developed hypothermia intraoperatively. Older age (OR = 1.068, 95% CI: 1.028-1.110, P = .001), lower weight (OR = 0.878, 95% CI: 0.807-0.955, P = .002), greater blood loss (OR = 1.003, 95% CI: 1.000-1.006, P = .034), and undergoing cancer surgery (OR = 0.210, 95% CI: 0.067-0.656, P = .007) were associated with intraoperative hypothermia. CONCLUSIONS: Unintentional intraoperative hypothermia is common in patients who undergo surgery for oral cancer. Warming interventions to prevent intraoperative hypothermia for high-risk patients (older, lower weight, or more intraoperative bleeding) should be considered. Meanwhile, with careful nursing and rehabilitation instructions, intraoperative hypothermia does not lead to serious perioperative complications.

Promotion effect of TGF-ß-Zfp423-ApoD pathway on lip sensory recovery after nerve sacrifice caused by nerve collateral compensation.

Resection of oral and maxillofacial tumors is often accompanied by the inferior alveolar nerve neurectomy, resulting in abnormal sensation in lower lip. It is generally believed that spontaneous sensory recovery in this nerve injury is difficult. However, during our follow-up, patients with inferior alveolar nerve sacrifice showed different degrees of lower lip sensory recovery. In this study, a prospective cohort study was conducted to demonstrate this phenomenon and analyze the factors influencing sensory recovery. A mental nerve transection model of Thy1-YFP mice and tissue clearing technique were used to explore possible mechanisms in this process. Gene silencing and overexpression experiments were then conducted to detect the changes in cell morphology and molecular markers. In our follow-up, 75% of patients with unilateral inferior alveolar nerve neurectomy had complete sensory recovery of the lower lip 12 months postoperatively. Patients with younger age, malignant tumors, and preservation of ipsilateral buccal and lingual nerves had a shorter recovery time. The buccal nerve collateral sprouting compensation was observed in the lower lip tissue of Thy1-YFP mice. ApoD was demonstrated to be involved in axon growth and peripheral nerve sensory recovery in the animal model. TGF-ß inhibited the expression of STAT3 and the transcription of ApoD in Schwann cells through Zfp423. Overall, after sacrificing the inferior alveolar nerve, the collateral compensation of the ipsilateral buccal nerve could innervate the sensation. And this process was regulated by TGF-ß-Zfp423-ApoD pathway.

Near-field terahertz nonlinear optics with blue light.

The coupling of terahertz optical techniques to scattering-type scanning near-field microscopy (s-SNOM) has recently emerged as a valuable new paradigm for probing the properties of semiconductors and other materials on the nanoscale. Researchers have demonstrated a family of related techniques, including terahertz nanoscopy (elastic scattering, based on linear optics), time-resolved methods, and nanoscale terahertz emission spectroscopy. However, as with nearly all examples of s-SNOM since the technique's inception in the mid-1990s, the wavelength of the optical source coupled to the near-field tip is long, usually at energies of 2.5 eV or less. Challenges in coupling of shorter wavelengths (i.e., blue light) to the nanotip has greatly inhibited the study of nanoscale phenomena in wide bandgap materials such as Si and GaN. Here, we describe the first experimental demonstration of s-SNOM using blue light. With femtosecond pulses at 410 nm, we generate terahertz pulses directly from bulk silicon, spatially resolved with nanoscale resolution, and show that these signals provide spectroscopic information that cannot be obtained using near-infrared excitation. We develop a new theoretical framework to account for this nonlinear interaction, which enables accurate extraction of material parameters. This work establishes a new realm of possibilities for the study of technologically relevant wide-bandgap materials using s-SNOM methods.

Self-Supervised Video-Centralised Transformer for Video Face Clustering.

This article presents a novel method for face clustering in videos using a video-centralised transformer. Previous works often employed contrastive learning to learn frame-level representation and used average pooling to aggregate the features along the temporal dimension. This approach may not fully capture the complicated video dynamics. In addition, despite the recent progress in video-based contrastive learning, few have attempted to learn a self-supervised clustering-friendly face representation that benefits the video face clustering task. To overcome these limitations, our method employs a transformer to directly learn video-level representations that can better reflect the temporally-varying property of faces in videos, while we also propose a video-centralised self-supervised framework to train the transformer model. We also investigate face clustering in egocentric videos, a fast-emerging field that has not been studied yet in works related to face clustering. To this end, we present and release the first large-scale egocentric video face clustering dataset named EasyCom-Clustering. We evaluate our proposed method on both the widely used Big Bang Theory (BBT) dataset and the new EasyCom-Clustering dataset. Results show the performance of our video-centralised transformer has surpassed all previous state-of-the-art methods on both benchmarks, exhibiting a self-attentive understanding of face videos.

End-to-End Video-to-Speech Synthesis Using Generative Adversarial Networks.

Video-to-speech is the process of reconstructing the audio speech from a video of a spoken utterance. Previous approaches to this task have relied on a two-step process where an intermediate representation is inferred from the video and is then decoded into waveform audio using a vocoder or a waveform reconstruction algorithm. In this work, we propose a new end-to-end video-to-speech model based on generative adversarial networks (GANs) which translates spoken video to waveform end-to-end without using any intermediate representation or separate waveform synthesis algorithm. Our model consists of an encoder-decoder architecture that receives raw video as input and generates speech, which is then fed to a waveform critic and a power critic. The use of an adversarial loss based on these two critics enables the direct synthesis of the raw audio waveform and ensures its realism. In addition, the use of our three comparative losses helps establish direct correspondence between the generated audio and the input video. We show that this model is able to reconstruct speech with remarkable realism for constrained datasets such as GRID, and that it is the first end-to-end model to produce intelligible speech for Lip Reading in the Wild (LRW), featuring hundreds of speakers recorded entirely "in the wild." We evaluate the generated samples in two different scenarios-seen and unseen speakers-using four objective metrics which measure the quality and intelligibility of artificial speech. We demonstrate that the proposed approach outperforms all previous works in most metrics on GRID and LRW.

Efficient Colon Cancer Immunogene Therapy Through Co-Delivery of IL-22BP mRNA and Tumor Cell Lysate by CLSV Nanoparticles.

Background: Messenger ribonucleic acid (mRNA)-based gene therapy has great potential in cancer treatment. However, the application of mRNA-based cancer treatment could be further developed. Elevated delivery ability and enhanced immune response are advantages for expanding the application of mRNA-based cancer therapy. It is crucial that the prepared carrier can cause an immune reaction based on the efficient delivery of mRNA. Methods: We reported DMP nanoparticle previously, which was obtained by the self-assembly of 1,2-dioleoyl-3-trimethylammonium propane (DOTAP) and (ethylene glycol)-b-poly (ε-caprolactone) (mPEG-PCL). Research demonstrated that DMP can deliver mRNA, siRNA, and plasmid. And it is applied to various tumor types. In our work, the tumor cell lysate was introduced to the internal DMP chain, fusing cell-penetrating peptides (CPPs) modification on the surface forming the CLSV system. And then mixed encoded IL-22BP (interleukin-22 binding protein) mRNA and CLSV to form CLSV/IL-22BP complex. Results: The size of the CLSV system was 213.2 nm, and the potential was 45.7 mV. The transfection efficiency of the CLSV system is up to 76.45% in C26 cells via the micropinocytosis pathway. The CLSV system also could induce an immune response and significantly elevate the expression of CD80, CD86, and MHC-II in vivo. Then, by binding with IL-22BP (Interleukin-22 binding protein) mRNA, the CLSV/IL-22BP complex inhibited tumor cell growth, with an inhibition rate of up to 82.3% in vitro. The CLSV/IL-22BP complex also inhibited tumor growth in vivo, the tumor cell growth inhibition up to 75.0% in the subcutaneous tumor model, and 84.9% in the abdominal cavity metastasis tumor model. Conclusion: Our work demonstrates that the CLSV system represents a potent potential for mRNA delivery.

Beyond conventional wisdom: unveiling quantitative insights in fluorescence lifetime imaging via realistic simulation of biological systems.

Fluorescence lifetime imaging microscopy (FLIM) and photometry (FLiP) are illuminating the dynamics of biological signals. Because fluorescence lifetime is an intensive property of a fluorophore that is insensitive to sensor expression levels, it excels over fluorescence intensity measurements by allowing comparison across animals, over chronic time periods, and quantitation of the absolute levels of biological signals. However, the insensitivity of lifetime to sensor expression level does not always hold true in biological experiments where autofluorescence, ambient light, dark currents and afterpulses of the detectors are present. To quantitatively evaluate the potential and limitations of fluorescence lifetime measurements, we introduce FLiSimBA, a flexible platform enabling realistic F luorescence Li fetime Sim ulation for B iological A pplications. FLiSimBA accurately recapitulates experimental data and provides quantitative analyses. Using FLiSimBA, we determine the photons required for minimum detectable differences in lifetime and quantify the impact of hardware innovation. Furthermore, we challenge the conventional view that fluorescence lifetime is insensitive to sensor expression levels and define the conditions in which sensor express levels do not result in statistically significant difference in biological experiments. Thus, we introduce an adaptable simulation tool that allows systematic exploration of parameters to define experimental advantages and limitations in biological applications. Moreover, we provide a statistical framework and quantitative insights into the impact of key experimental parameters on signal-to-noise ratio and fluorescence lifetime responses. Our tool and results will enable the growing community of FLIM users and developers to optimize FLIM experiments, expose limitations, and identify opportunities for future innovation of fluorescence lifetime technologies.

Overcoming the Outcoupling Limit of Perovskite Light-Emitting Diodes with Artificially Formed Nanostructures.

The external quantum efficiency (EQE) of state-of-the-art planar-structure perovskite light-emitting diodes (PeLEDs) is mainly limited by the outcoupling efficiency, which is around 20% and decreases significantly with the perovskite thickness. Here, an approach to artificially form textured perovskite films to boost the outcoupling limit of the PeLEDs is reported. By manipulating the dwell time of antisolvents, the perovskite phase precipitation mechanism, film-forming process, and surface texture can be finely controlled. The film surface roughness can be tuned from 15.3 to 241 nm, with haze increasing accordingly from 6% to >90% for films with an average thickness of 1.5 µm. The light outcoupling limit increases accordingly from 11.7% for the flat PeLEDs to 26.5% for the textured PeLEDs due to photon scattering at the interface. Consequently, the EQE is boosted significantly from around 10% to 20.5% with an extraordinarily thick emissive layer of 1.5 µm. This study provides a novel way of forming light-extraction nanostructures for perovskite optoelectronic devices.

Local and Systemic Delivery of the BimS Gene Nano-Complex for Efficient Oral Squamous Cell Carcinoma Therapy.

Purpose: Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, with more than 300,000 new cases annually. Despite advances in existing treatments, including surgery, radiation, chemotherapy, and immunotherapy, the overall survival and prognosis have remained poor. However, gene therapy based on non-viral vectors provides new ideas for the treatment of OSCC. Here, we aimed to prepare and describe the synthesis, biosafety, and preclinical efficacy of DOTAP-mPEG-PCL (DMP) in OSCC gene therapy. Methods: We prepared a nano-sized hybrid cationic micelle DMP. DMP micelles were prepared by self-assembling cationic lipid DOTAP and mPEG-PCL polymer. We evaluated the characteristics of this cationic micelle in vitro. Combined with encoding the apoptosis-inducing BimS gene, we established the DMP/phBimS complex and evaluated its anti-tumor effect in vitro. We also established a mouse tongue xenograft model to evaluate the antitumor effect of the DMP/phBimS complex in vivo through local and systemic administration prospectively. Results: The DMP cationic micelle is spherical in shape, with an average diameter of 28.32 ± 3.56 nm and an average zeta potential of 43.43 ± 0.82 mV. By activation of lipid raft-mediated endocytosis caveolin-mediated endocytosis, DMP could efficiently deliver plasmid into SCC15 cells (efficiency: 52.07% ± 1.63%), with an ideal biosecurity. When loaded by plasmid encoding the apoptosis-inducing BimS gene, the DMP/phBimS complex exhibited an obvious anti-proliferation effect of SCC15 in vitro through the apoptosis pathway (33.9% ± 2.62% apoptosis rate). By local administration, the DMP/phBimS complex showed ideal anti-tumor properties in the nude mouse tongue xenograft model, with an average tumor inhibition rate of 65.66%. Furthermore, through systematic administration, the DMP/phBimS complex obviously inhibited OSCC growth, with an average inhibition rate of 45.63% (DMP/phBimS) and an appropriate biocompatibility. Conclusion: The DMP/phBimS complex is an optional effective option for suicide gene therapy for OSCC.

Gut microbiota depletion by antibiotics ameliorates somatic neuropathic pain induced by nerve injury, chemotherapy, and diabetes in mice.

BACKGROUND: Gut microbiota has been found involved in neuronal functions and neurological disorders. Whether and how gut microbiota impacts chronic somatic pain disorders remain elusive. METHODS: Neuropathic pain was produced by different forms of injury or diseases, the chronic constriction injury (CCI) of the sciatic nerves, oxaliplatin (OXA) chemotherapy, and streptozocin (STZ)-induced diabetes in mice. Continuous feeding of antibiotics (ABX) cocktail was used to cause major depletion of the gut microbiota. Fecal microbiota, biochemical changes in the spinal cord and dorsal root ganglion (DRG), and the behaviorally expressed painful syndromes were assessed. RESULTS: Under condition of gut microbiota depletion, CCI, OXA, or STZ treatment-induced thermal hyperalgesia or mechanical allodynia were prevented or completely suppressed. Gut microbiota depletion also prevented CCI or STZ treatment-induced glial cell activation in the spinal cord and inhibited cytokine production in DRG in OXA model. Interestingly, STZ treatment failed to induce the diabetic high blood glucose and painful hypersensitivity in animals with the gut microbiota depletion. ABX feeding starting simultaneously with CCI, OXA, or STZ treatment resulted in instant analgesia in all the animals. ABX feeding starting after establishment of the neuropathic pain in CCI- and STZ-, but not OXA-treated animals produced significant alleviation of the thermal hyeralgesia or mechanical allodynia. Transplantation of fecal bacteria from SPF mice to ABX-treated mice partially restored the gut microbiota and fully rescued the behaviorally expressed neuropathic pain, of which, Akkermansia, Bacteroides, and Desulfovibrionaceae phylus may play a key role. CONCLUSION: This study demonstrates distinct roles of gut microbiota in the pathogenesis of chronic painful conditions with nerve injury, chemotherapy and diabetic neuropathy and supports the clinical significance of fecal bacteria transplantation.

Dual-RNA controlled delivery system inhibited tumor growth by apoptosis induction and TME activation.

Drug-controlled release is recognized as effective for improving compliance with treatment and obtaining better therapeutic efficacy with less toxicity in cancer treatment. However, few reports in this area are involved in nucleic acids delivery, especially in RNA therapeutics delivery. In this study, an injectable hydrogel Methacrylated gelatin (GM) scaffold was introduced into a dual-RNA hybrid delivery complex hybrid lipid particle (HLP) to form a G-HLP/RNAs system. This system can control the release of both siRNA and mRNA and was found to be efficient for protecting these RNAs from biodegradation and retaining their therapeutic effect over 7 days. Further, a tumor environment (TME)-activation function after peritumoral injection of mocked GM scaffold was observed. Then, matured DC cells and activated T-cells were detected by the addition of HLP/RNAs complex, thus verifying the immunoactivation function of GM scaffold and its ability to reserve immune cells and antigens. Finally, two doses of G-HLP/RNAs treatment efficiently suppressed C26 tumor growth in mice with a tumor weight inhibition rate of 71.9%. Owing to its ability to achieve RNA drug-controlled release, alter TME, and induce tumor apoptosis, the G-HLP/RNAs system may become a valuable tool for cancer gene therapy.

Improving Deep Metric Learning by Divide and Conquer.

Deep metric learning (DML) is a cornerstone of many computer vision applications. It aims at learning a mapping from the input domain to an embedding space, where semantically similar objects are located nearby and dissimilar objects far from another. The target similarity on the training data is defined by user in form of ground-truth class labels. However, while the embedding space learns to mimic the user-provided similarity on the training data, it should also generalize to novel categories not seen during training. Besides user-provided groundtruth training labels, a lot of additional visual factors (such as viewpoint changes or shape peculiarities) exist and imply different notions of similarity between objects, affecting the generalization on the images unseen during training. However, existing approaches usually directly learn a single embedding space on all available training data, struggling to encode all different types of relationships, and do not generalize well. We propose to build a more expressive representation by jointly splitting the embedding space and the data hierarchically into smaller sub-parts. We successively focus on smaller subsets of the training data, reducing its variance and learning a different embedding subspace for each data subset. Moreover, the subspaces are learned jointly to cover not only the intricacies, but the breadth of the data as well. Only after that, we build the final embedding from the subspaces in the conquering stage. The proposed algorithm acts as a transparent wrapper that can be placed around arbitrary existing DML methods. Our approach significantly improves upon the state-of-the-art on image retrieval, clustering, and re-identification tasks evaluated using CUB200-2011, CARS196, Stanford Online Products, In-shop Clothes, and PKU VehicleID datasets.

Spinal beta-amyloid1-42 acts as an endogenous analgesic peptide in CCI-induced neuropathic pain.

BACKGROUND: The mechanism for reduced pain sensitivity associated with Alzheimer's disease (AD) has not been illustrated. We hypothesize that amyloid beta 1-42 (Aß1-42) in the spinal cord acts as an endogenous analgesic peptide to suppress pain induced by nerve injury. METHODS: We used chronic constriction injury of the sciatic nerve (CCI) to produce neuropathic pain in Sprague-Dawley rats. Enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry were used to determine the level of Aß1-42, the expression of Wnt3a/5b and glial activation in the spinal cord. Western blotting was used to determine the expression of interleukins, the phosphorylation of NR2B and ERK1/2, and the nuclear accumulation of transcriptional factors YAP/TAZ. Thermal hyperalgesia and mechanical allodynia were assessed after CCI and pharmacological manipulations through intrathecal administration. RESULTS: Nerve injury increases spinal level of Aß1-42, while intrathecal administration of MK-8931 reduces the level of Aß1-42 and facilitates mechanical allodynia. Intrathecal administration of Aß1-42 suppresses pain behaviors in the early and late phases of neuropathy. Spinal administration of Aß1-42 regulates the expression of interleukins, reducing glial activation and phosphorylation of NR2B and ERK1/2 in the spinal cord of CCI rats. Furthermore, intrathecal administration of Aß1-42 decreases Wnt5b expression and suppresses the nuclear accumulation of YAP and TAZ. Blocking the interaction between Aß1-42 and Frizzled receptors by cSP5 reverses the analgesic effects of Aß1-42. CONCLUSIONS: These findings suggest that spinal Aß1-42 acts as an endogenous analgesic peptide through regulating cytokines and Wnt pathways. This study may provide a potential target for the development of novel analgesic peptides. SIGNIFICANCE: This study provides an explanation of reduced pain sensitivity associated with Alzheimer's disease. Furthermore, our findings propose a possible physiological function of beta-amyloid1-42 to regulate pain. This study may provide a potential target for the development of novel analgesics based on an existing endogenous peptide.