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Accurately evaluating the local biomechanics of arterial wall is crucial for diagnosing and treating arterial diseases. Indentation measurement can be used to evaluate the local mechanical properties of the artery. However, the effects of the indenter's geometric structure and the analysis theory on measurement results remain uncertain. In this paper, four kinds of indenters were used to measure the pulmonary aorta, the proximal thoracic aorta and the distal thoracic aorta in pigs, and the arterial elastic modulus was calculated by Sneddon and Sirghi theory to explore the influence of the indenter geometry and analysis theory on the measured elastic modulus. The results showed that the arterial elastic modulus measured by cylindrical indenter was lower than that measured by spherical indenter. In addition, compared with the calculated results of Sirghi theory, the Sneddon theory, which does not take adhesion forces in account, resulted in slightly larger elastic modulus values. In conclusion, this study provides parametric support for effective measurement of arterial local mechanical properties by millimeter indentation technique.
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Aorta Torácica , Módulo de Elasticidade , Artéria Pulmonar , Animais , Suínos , Fenômenos Biomecânicos , Aorta Torácica/fisiologia , Aorta Torácica/anatomia & histologia , Artéria Pulmonar/fisiologia , Estresse Mecânico , Artérias/fisiologiaRESUMO
The utilization of sludge-based biochar, characterized by abundant pore structures, proves advantageous in enhancing sludge dewatering performance. In this study, advanced anaerobic digestion sludge underwent pyrolysis to produce biochar, subsequently employed for sludge conditioning. Results revealed that biochar, obtained at 800 °C, exhibited the highest specific surface area (105.3 m2/g) and pore volume (0.17 cm3/g). As the pyrolysis temperature increased, the sludge's functional groups tended to aromatize. When used to condition sludge, particularly at a 20 % (dry solid) dosage, biochar significantly reduced sludge capillary suction time and floc size. The addition of biochar enhanced the conditioning effect of cationic polyacrylamide by absorbing extracellular polymeric substances, creating water molecule channels, and forming skeletons for sludge flocs. These findings introduce a novel approach to sludge reuse and provide valuable data supporting the use of biochar as a sludge conditioner.
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Carvão Vegetal , Esgotos , Esgotos/química , Carvão Vegetal/química , Anaerobiose , Resinas Acrílicas/química , Pirólise , PorosidadeRESUMO
Based on multi-omics data and drug information, predicting the response of cancer cell lines to drugs is a crucial area of research in modern oncology, as it can promote the development of personalized treatments. Despite the promising performance achieved by existing models, most of them overlook the variations among different omics and lack effective integration of multi-omics data. Moreover, the explicit modeling of cell line/drug attribute and cell line-drug association has not been thoroughly investigated in existing approaches. To address these issues, we propose RedCDR, a dual relation distillation model for cancer drug response (CDR) prediction. Specifically, a parallel dual-branch architecture is designed to enable both the independent learning and interactive fusion feasible for cell line/drug attribute and cell line-drug association information. To facilitate the adaptive interacting integration of multi-omics data, the proposed multi-omics encoder introduces the multiple similarity relations between cell lines and takes the importance of different omics data into account. To accomplish knowledge transfer from the two independent attribute and association branches to their fusion, a dual relation distillation mechanism consisting of representation distillation and prediction distillation is presented. Experiments conducted on the GDSC and CCLE datasets show that RedCDR outperforms previous state-of-the-art approaches in CDR prediction. The source code is available at https://github.com/mhxu1998/RedCDR.
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Temporal graph learning aims to generate high-quality representations for graph-based tasks with dynamic information, which has recently garnered increasing attention. In contrast to static graphs, temporal graphs are typically organized as node interaction sequences over continuous time rather than an adjacency matrix. Most temporal graph learning methods model current interactions by incorporating historical neighborhood. However, such methods only consider first-order temporal information while disregarding crucial high-order structural information, resulting in suboptimal performance. To address this issue, we propose a self-supervised method called S2T for temporal graph learning, which extracts both temporal and structural information to learn more informative node representations. Notably, the initial node representations combine first-order temporal and high-order structural information differently to calculate two conditional intensities. An alignment loss is then introduced to optimize the node representations, narrowing the gap between the two intensities and making them more informative. Concretely, in addition to modeling temporal information using historical neighbor sequences, we further consider structural knowledge at both local and global levels. At the local level, we generate structural intensity by aggregating features from high-order neighbor sequences. At the global level, a global representation is generated based on all nodes to adjust the structural intensity according to the active statuses on different nodes. Extensive experiments demonstrate that the proposed model S2T achieves at most 10.13% performance improvement compared with the state-of-the-art competitors on several datasets.
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The prevalence of obesity and its primary associated comorbidities, such as type 2 diabetes and fatty liver disease, has reached epidemic proportions, with no successful treatment available at present. Heat shock protein 90 (HSP90), a crucial chaperone, plays a key role in de novo lipogenesis (DNL) by stabilizing and maintaining sterol regulatory element binding protein (SREBP) activity. Kongensin A (KA), derived from Croton kongensis, inhibits RIP3-mediated necrosis, showing promise as an anti-necrotic and anti-inflammatory agent. It is not yet clear if KA, acting as an HSP90 inhibitor, can enhance hyperlipidemia, hepatic steatosis, and insulin resistance in obese individuals by controlling lipid metabolism. In this study, we first found that KA can potentially decrease lipid content at the cellular level. C57BL/6J mice were given a high-fat diet (HFD) and received KA and lovastatin through oral administration for 7 weeks. KA improved hyperlipidemia, fatty liver, and insulin resistance, as well as reduced body weight in diet-induced obese (DIO) mice, with no significant alteration in food intake. In vitro, KA suppressed DNL and reduced the amounts of mSREBPs. KA promoted mSREBP degradation via the FBW7-mediated ubiquitin-proteasome pathway. KA decreased the level of p-Akt Ser308, and p-GSK3ß Ser9 by inhibiting the interaction between HSP90ß and Akt. Overall, KA enhanced hyperlipidemia, hepatic steatosis, and insulin resistance by blocking SREBP activity, thereby impacting the FBW7-controlled ubiquitin-proteasome pathway.
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Inorganic coagulants such as poly aluminum ferric chloride (Al/Fe) are applied conventionally to sewage sludge dewatering and can be retained in the sludge cake, causing its conductivity to increase and generate secondary pollution. To reduce these disadvantages, there is a need to develop alternative, more sustainable chemicals as substitutes for conventional inorganic coagulants. In the present investigation, the application of a polymeric chitosan quaternary ammonium salt (CQAS) is explored as a complete, or partial, replacement for Al/Fe in the context of sludge dewatering processes. Laboratory experiments using digested sewage sludge showed that CQAS could effectively substitute for over 80 % of the Al/Fe inorganic coagulant in the sludge dewatering process. This substitution resulted in a reduction of sludge cake conductivity by more than 50 %. Simulation of sludge dewatering curves and imaging of the sludge surface indicated that the addition of CQAS led to an increase in nanosized pores, and a decrease in the specific resistance of the sludge filter cake as the dosage of Al/Fe decreased to around 30 %. The variations of fluorescence emission, quantum yield and carboxylic and amino groups, suggested that the chelating of Al/Fe decreased due to the bridging effects of CQAS. The CQAS had different flocculation bridging effects on various EPS fractions, which varied the amount of protein chelated with Al/Fe in each fraction. This study provides new information about the benefits of replacing conventional inorganic coagulants with natural organic polymers for sewage sludge dewatering, in terms of reduced sludge cake conductivity and greater dry solids content.
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Quitosana , Compostos Férricos , Esgotos , Esgotos/química , Quitosana/química , Compostos Férricos/química , Compostos de Amônio Quaternário/química , Floculação , Cloretos/química , Eliminação de Resíduos Líquidos/métodos , Alumínio/químicaRESUMO
Tumor cells disseminate in various distant organs at early stages of cancer progression. These disseminated tumor cells (DTCs) can stay dormant/quiescent without causing patient symptoms for years or decades. These dormant tumor cells survive despite curative treatments by entering growth arrest, escaping immune surveillance, and/or developing drug resistance. However, these dormant cells can reactivate to proliferate, causing metastatic progression and/or relapse, posing a threat to patients' survival. It's unclear how cancer cells maintain dormancy and what triggers their reactivation. What are better approaches to prevent metastatic progression and relapse through harnessing cancer dormancy? To answer these remaining questions, we reviewed the studies of tumor dormancy and reactivation in various types of cancer using different model systems, including the brief history of dormancy studies, the intrinsic characteristics of dormant cells, and the external cues at the cellular and molecular levels. Furthermore, we discussed future directions in the field and the strategies for manipulating dormancy to prevent metastatic progression and recurrence.
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Neoplasias , Humanos , Neoplasias/patologia , Neoplasias/metabolismo , Animais , Metástase Neoplásica , Microambiente Tumoral , Progressão da Doença , Transdução de Sinais , Recidiva Local de Neoplasia/patologia , Proliferação de CélulasRESUMO
One critical mechanism through which prostate cancer (PCa) adapts to treatments targeting androgen receptor (AR) signaling is the emergence of ligand-binding domain-truncated and constitutively active AR splice variants, particularly AR-V7. While AR-V7 has been intensively studied, its ability to activate distinct biological functions compared with the full-length AR (AR-FL), and its role in regulating the metastatic progression of castration-resistant PCa (CRPC), remain unclear. Our study found that, under castrated conditions, AR-V7 strongly induced osteoblastic bone lesions, a response not observed with AR-FL overexpression. Through combined ChIP-seq, ATAC-seq, and RNA-seq analyses, we demonstrated that AR-V7 uniquely accesses the androgen-responsive elements in compact chromatin regions, activating a distinct transcription program. This program was highly enriched for genes involved in epithelial-mesenchymal transition and metastasis. Notably, we discovered that SOX9, a critical metastasis driver gene, was a direct target and downstream effector of AR-V7. Its protein expression was dramatically upregulated in AR-V7-induced bone lesions. Moreover, we found that Ser81 phosphorylation enhanced AR-V7's pro-metastasis function by selectively altering its specific transcription program. Blocking this phosphorylation with CDK9 inhibitors impaired the AR-V7-mediated metastasis program. Overall, our study has provided molecular insights into the role of AR splice variants in driving the metastatic progression of CRPC.
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Regulação Neoplásica da Expressão Gênica , Neoplasias de Próstata Resistentes à Castração , Receptores Androgênicos , Animais , Humanos , Masculino , Camundongos , Processamento Alternativo , Neoplasias Ósseas/secundário , Neoplasias Ósseas/genética , Neoplasias Ósseas/metabolismo , Neoplasias Ósseas/patologia , Linhagem Celular Tumoral , Transição Epitelial-Mesenquimal/genética , Metástase Neoplásica , Neoplasias de Próstata Resistentes à Castração/genética , Neoplasias de Próstata Resistentes à Castração/patologia , Neoplasias de Próstata Resistentes à Castração/metabolismo , Isoformas de Proteínas/genética , Isoformas de Proteínas/metabolismo , Receptores Androgênicos/genética , Receptores Androgênicos/metabolismo , Fatores de Transcrição SOX9/genética , Fatores de Transcrição SOX9/metabolismo , Transcrição GênicaRESUMO
In recent years, there has been a growing trend in the realm of parallel clustering analysis for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase Accessible Chromatin (scATAC) data. However, prevailing methods often treat these two data modalities as equals, neglecting the fact that the scRNA mode holds significantly richer information compared to the scATAC. This disregard hinders the model benefits from the insights derived from multiple modalities, compromising the overall clustering performance. To this end, we propose an effective multi-modal clustering model scEMC for parallel scRNA and Assay of Transposase Accessible Chromatin data. Concretely, we have devised a skip aggregation network to simultaneously learn global structural information among cells and integrate data from diverse modalities. To safeguard the quality of integrated cell representation against the influence stemming from sparse scATAC data, we connect the scRNA data with the aggregated representation via skip connection. Moreover, to effectively fit the real distribution of cells, we introduced a Zero Inflated Negative Binomial-based denoising autoencoder that accommodates corrupted data containing synthetic noise, concurrently integrating a joint optimization module that employs multiple losses. Extensive experiments serve to underscore the effectiveness of our model. This work contributes significantly to the ongoing exploration of cell subpopulations and tumor microenvironments, and the code of our work will be public at https://github.com/DayuHuu/scEMC.
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Cromatina , RNA Citoplasmático Pequeno , Análise da Expressão Gênica de Célula Única , Análise por Conglomerados , Aprendizagem , RNA Citoplasmático Pequeno/genética , Transposases , Análise de Sequência de RNA , Perfilação da Expressão GênicaRESUMO
BACKGROUND: Cancer and coronary artery disease (CAD) is reported to often co-exist in same individuals, however, whether cancer is directly associated with anatomical severity of CAD is rarely studied. The present study aimed to observe the relationship between newly diagnosed cancer and anatomical severity of CAD, moreover, to investigate effect of inflammation on the relationship of cancer with CAD. METHODS: 374 patients with newly diagnosed cancer who underwent coronary angiography (CAG) were enrolled. Through 1:3 propensity score matching (PSM) to cancer patients based on the age and gender among 51,106 non-cancer patients who underwent CAG, 1122 non-cancer patients were selected as control patients. Anatomical severity of CAD was assessed using SYNTAX score (SXscore) based on coronary angiographic image. SXscore ≤ 22 (highest quartile) was defined as SX-low, and SXscore > 22 as SX-high. The ratio of neutrophil to lymphocyte count (NLR) was used to describe inflammation level. Association between cancer and the anatomical severity of CAD was investigated using logistic regression. RESULTS: Univariate logistic regression analysis showed a correlation between cancer and anatomical severity of CAD (OR: 1.419, 95% CI: 1.083-1.859; P = 0.011). Cancer was associated with increased risk of SX-high after adjusted for common risk factors of CAD (OR: 1.598, 95% CI: 1.172-2.179, P = 0.003). Significant association between cancer and SX-high was revealed among patients with high inflammation (OR: 1.656, 95% CI: 1.099-2.497, P = 0.016), but not among patients with low inflammation (OR: 1.530, 95% CI: 0.973-2.498, P = 0.089). CONCLUSIONS: Cancer was associated with severity of CAD, however, the association between the two diseases was significant among patients with high inflammation rather than among patients with low inflammation.
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Doença da Artéria Coronariana , Neoplasias , Humanos , Doença da Artéria Coronariana/diagnóstico por imagem , Neoplasias/diagnóstico , Neoplasias/epidemiologia , Angiografia Coronária , Inflamação , Fatores de RiscoRESUMO
Automatically recording surgical procedures and generating surgical reports are crucial for alleviating surgeons' workload and enabling them to concentrate more on the operations. Despite some achievements, there still exist several issues for the previous works: 1) failure to model the interactive relationship between surgical instruments and tissue; and 2) neglect of fine-grained differences within different surgical images in the same surgery. To address these two issues, we propose an improved scene graph-guided Transformer, also named by SGT++, to generate more accurate surgical report, in which the complex interactions between surgical instruments and tissue are learnt from both explicit and implicit perspectives. Specifically, to facilitate the understanding of the surgical scene graph under a graph learning framework, a simple yet effective approach is proposed for homogenizing the input heterogeneous scene graph. For the homogeneous scene graph that contains explicit structured and fine-grained semantic relationships, we design an attention-induced graph transformer for node aggregation via an explicit relation-aware encoder. In addition, to characterize the implicit relationships about the instrument, tissue, and the interaction between them, the implicit relational attention is proposed to take full advantage of the prior knowledge from the interactional prototype memory. With the learnt explicit and implicit relation-aware representations, they are then coalesced to obtain the fused relation-aware representations contributing to generating reports. Some comprehensive experiments on two surgical datasets show that the proposed STG++ model achieves state-of-the-art results.
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Semântica , Cirurgiões , HumanosRESUMO
Polyester elastomers are highly flexible and elastic materials that have demonstrated considerable potential in various biomedical applications including cardiac, vascular, neural, and bone tissue engineering and bioelectronics. Polyesters are desirable candidates for future commercial implants due to their biocompatibility, biodegradability, tunable mechanical properties, and facile synthesis and fabrication methods. The incorporation of bioactive components further improves the therapeutic effects of polyester elastomers in biomedical applications. In this review, novel structural modification methods that contribute to outstanding mechanical behaviors of polyester elastomers are discussed. Recent advances in the application of polyester elastomers in tissue engineering and bioelectronics are outlined and analyzed. A prospective of the future research and development on polyester elastomers is also provided.
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Elastômeros , Poliésteres , Elastômeros/química , Poliésteres/química , Engenharia Tecidual/métodos , Materiais Biocompatíveis/químicaRESUMO
Electrochemical oxygen reduction (ORR) for the production of clean hydrogen peroxide (H2O2) is an effective alternative to industrial anthraquinone methods. The development of highly active, stable, and 2e- ORR oxygen reduction electrocatalysts while suppressing the competing 4e- ORR pathway is currently the main challenge. Herein, bimetallic doping was successfully achieved based on graphitic carbon nitride (g-C3N4) with the simultaneous introduction of K and Co, whereby 2D porous K-Co/CNNs nanosheets were obtained. The introduction of Co promoted the selectivity for H2O2, while the introduction of K not only promoted the formation of 2D nanosheets of g-C3N4, but also inhibited the ablation of H2O2 by K-Co/CNNs. Electrochemical studies showed that the selectivity of H2O2 in K-Co/CNNs under neutral electrolyte was as high as 97%. After 24 h, the H2O2 accumulation of K-Co/CNNs was as high as 31.7 g L-1. K-Co/CNNs improved the stability of H2O2 by inhibiting the ablation of H2O2, making it a good 2e- ORR catalyst and providing a new research idea for the subsequent preparation of H2O2.
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BACKGROUND: Exercise is postulated to be a promising non-pharmacological intervention for the improvement of neurodegenerative disease pathology. However, the mechanism of beneficial effects of exercise on the brain remains to be further explored. In this study, we investigated the effect of an exercise-induced metabolite, lactate, on the microglia phenotype and its association with learning and memory. RESULTS: Microglia were hyperactivated in the brains of AlCl3/D-gal-treated mice, which was associated with cognitive decline. Running exercise ameliorated the hyperactivation and increased the anti-inflammatory/reparative phenotype of microglia and improved cognition. Mice were injected intraperitoneally with sodium lactate (NaLA) had similar beneficial effects as that of exercise training. Exogenous NaLA addition to cultured BV2 cells promoted their transition from a pro-inflammatory to a reparative phenotype. CONCLUSION: The elevated lactate acted as an "accelerator" of the endogenous "lactate timer" in microglia promoting this transition of microglia polarization balance through lactylation. These findings demonstrate that exercise-induced lactate accelerates the phenotypic transition of microglia, which plays a key role in reducing neuroinflammation and improving cognitive function.
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PURPOSE: The cross-limb (CL) technique is a commonly used endovascular treatment for addressing unfavorable anatomical features in patients with abdominal aortic aneurysm (AAA). The configuration of CL stent-graft plays a critical role in determining the postoperative hemodynamic properties and physiological behaviors, which ultimately impact the efficacy and safety of endovascular AAA treatment. This study aims to investigate the relationship between hemodynamics and CL stent-graft configuration from a hemodynamic perspective. METHODS: Five distinct geometric models of cross-limb (CL) stent-graft configurations were constructed by optimizing the real clinical computed tomography angiography (CTA) data. These models varied in main body lengths and cross angles and were used to perform numerical simulations to analyze various hemodynamic parameters. Flow pattern, distribution of wall shear stress (WSS)-related parameters, localized normalized helicity (LNH), pressure drop, and the displacement force of all models were examined in this paper. RESULTS: In patient-specific cases, helical flow and WSS increase with the main body. However, it also generated secondary flow in localized areas, leading to increased oscillation in the WSS direction. Notably, increasing the stent graft's main body length or decreasing the cross angle reduced the displacement force exerted on the stent-graft. Reducing the cross angle did not significantly alter the hemodynamic characteristics. CONCLUSION: In the clinical practice of CL deployment, it is crucial to carefully consider the stent-graft configuration and the patient specific to achieve optimal postoperative outcomes. This study provides valuable insights for guiding stent selection and treatment planning in patients with abdominal aortic aneurysm undergoing CL techniques, from a hemodynamic perspective.
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BACKGROUND: Disseminated tumor cells (DTCs) can enter a dormant state and cause no symptoms in cancer patients. On the other hand, the dormant DTCs can reactivate and cause metastases progression and lethal relapses. In prostate cancer (PCa), relapse can happen after curative treatments such as primary tumor removal. The impact of surgical removal on PCa dissemination and dormancy remains elusive. Furthermore, as dormant DTCs are asymptomatic, dormancy-induction can be an operational cure for preventing metastases and relapse of PCa patients. METHODS: We used a PCa subcutaneous xenograft model and species-specific PCR to survey the DTCs in various organs at different time points of tumor growth and in response to tumor removal. We developed in vitro 2D and 3D co-culture models to recapitulate the dormant DTCs in the bone microenvironment. Proliferation assays, fluorescent cell cycle reporter, qRT-PCR, and Western Blot were used to characterize the dormancy phenotype. We performed RNA sequencing to determine the dormancy signature of PCa. A drug repurposing algorithm was applied to predict dormancy-inducing drugs and a top candidate was validated for the efficacy and the mechanism of dormancy induction. RESULTS: We found DTCs in almost all mouse organs examined, including bones, at week 2 post-tumor cell injections. Surgical removal of the primary tumor reduced the overall DTC abundance, but the DTCs were enriched only in the bones. We found that osteoblasts, but not other cells of the bones, induced PCa cell dormancy. RNA-Seq revealed the suppression of mitochondrial-related biological processes in osteoblast-induced dormant PCa cells. Importantly, the mitochondrial-related biological processes were found up-regulated in both circulating tumor cells and bone metastases from PCa patients' data. We predicted and validated the dormancy-mimicking effect of PF-562,271 (PF-271), an inhibitor of focal adhesion kinase (FAK) in vitro. Decreased FAK phosphorylation and increased nuclear translocation were found in both co-cultured and PF-271-treated C4-2B cells, suggesting that FAK plays a key role in osteoblast-induced PCa dormancy. CONCLUSIONS: Our study provides the first insights into how primary tumor removal enriches PCa cell dissemination in the bones, defines a unique osteoblast-induced PCa dormancy signature, and identifies FAK as a PCa cell dormancy gatekeeper.
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Recidiva Local de Neoplasia , Neoplasias da Próstata , Masculino , Humanos , Animais , Camundongos , Proteína-Tirosina Quinases de Adesão Focal/metabolismo , Recidiva Local de Neoplasia/metabolismo , Neoplasias da Próstata/patologia , Osteoblastos/metabolismo , Osteoblastos/patologia , Recidiva , Linhagem Celular Tumoral , Microambiente TumoralRESUMO
Background: Moderate renal artery stenosis (50-70%) may lead to uncontrolled hypertension and eventually cause irreversible damage to renal function. However, the clinical criteria for interventional treatment are still ambiguous in this condition. This study investigated the impact of the position and degree of renal artery stenosis on hemodynamics near the renal artery to assess the short-term and long-term risks associated with this disease. Methods: Calculation models with different degrees of stenosis (50%, 60%, and 70%) located at different positions in the right renal artery were established based on the computed tomography angiography (CTA) of a personalized case. And computational fluid dynamics (CFD) was used to analyze hemodynamic surroundings near the renal artery. Results: As the degree of stenosis increases and the stenosis position is far away from the aorta, there is a decrease in renal perfusion. An analysis of the wall shear stress (WSS)-related parameters indicated areas near the renal artery (downstream of the stenosis and the entrance of the right renal artery) with potential long-term risks of thrombosis and inflammation. Conclusion: The position and degree of stenosis play a significant role in judging short-term risks associated with renal perfusion. Moreover, clinicians should consider not only short-term risks but also independent long-term risk factors, such as certain regions of 50% stenosis with adequate renal perfusion may necessitate prompt intervention.
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Drugs may undergo costly preclinical studies but still fail to demonstrate their efficacy in clinical trials, which makes it challenging to discover new drugs. Both in vitro and in vivo models are essential for disease research and therapeutic development. However, these models cannot simulate the physiological and pathological environment in the human body, resulting in limited drug detection and inaccurate disease modelling, failing to provide valid guidance for clinical application. Organs-on-chips (OCs) are devices that serve as a micro-physiological system or a tissue-on-a-chip; they provide accurate insights into certain functions and the pathophysiology of organs to precisely predict the safety and efficiency of drugs in the body. OCs are faster, more economical, and more precise. Thus, they are projected to become a crucial addition to, and a long-term replacement for, traditional preclinical cell cultures, animal studies, and even human clinical trials. This paper first outlines the nature of OCs and their significance, and then details their manufacturing-related materials and methodology. It also discusses applications of OCs in drug screening and disease modelling and treatment, and presents the future perspective of OCs.
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Introduction: Fluorescent visualization of hydrogen peroxide in the tumor microenvironment (TME) is conducive to predicting malignant prognosis after chemotherapy. Two photon microscopy has been employed for in vivo hydrogen peroxide detection owing to its advantages of deep penetration and low phototoxicity. Methods: In this study, a two-photon fluorescent probe (TPFP) was protected by mesoporous silica nanoparticles (MSNs) and masked by cloaking the cancer cell membranes (CM), forming a tumor-targeted bioactive nanoprobe, termed MSN@TPFP@CM. Results: This multifunctional nanoprobe allowed for the effective and selective detection of excessive hydrogen peroxide production in chemotherapeutic Etoposide (VP-16)-challenged tumor cells using two-photon microscopy. After specific accumulation in tumors, VP-16-MSN@TPFP@CM monitored tumor-specific hydrogen peroxide levels and revealed a positive correlation between oxidative stress in the TME and chemotherapy-exacerbated malignant prognosis. Discussion: Given the recent translation of fluorescent imaging into early clinical trials and the high biocompatibility of bioactive nanoprobes, our approach may pave the way for specific imaging of oxidative stress in solid tumors after treatment and provide a promising technology for malignant prognosis predictions.
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PTHrP exerts its effects by binding to its receptor, PTH1R, a G protein-coupled receptor (GPCR), activating the downstream cAMP signaling pathway. As an autocrine, paracrine, or intracrine factor, PTHrP has been found to stimulate cancer cell proliferation, inhibit apoptosis, and promote tumor-induced osteolysis of bone. Despite these findings, attempts to develop PTHrP and PTH1R as drug targets have not produced successful results in the clinic. Nevertheless, the efficacy of blocking PTHrP and PTH1R has been shown in various types of cancer, suggesting its potential for therapeutic applications. In light of these conflicting data, we conducted a comprehensive review of the studies of PTHrP/PTH1R in cancer progression and metastasis and highlighted the strengths and limitations of targeting PTHrP or PTH1R in cancer therapy. This review also offers our perspectives for future research in this field.