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1.
Neural Regen Res ; 18(6): 1321-1324, 2023 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-36453418

RESUMO

In vivo imaging of cerebral ischemia/reperfusion injury remains an important challenge. We injected porous Ag/Au@SiO2 bimetallic hollow nanoshells carrying anti-tropomyosin 4 as a molecular probe into mice with cerebral ischemia/reperfusion injury and observed microvascular changes in the brain using photoacoustic imaging with ultrasonography. At each measured time point, the total photoacoustic signal was significantly higher on the affected side than on the healthy side. Twelve hours after reperfusion, cerebral perfusion on the affected side increased, cerebrovascular injury worsened, and anti-tropomyosin 4 expression increased. Twenty-four hours after reperfusion and later, perfusion on the affected side declined slowly and stabilized after 1 week; brain injury was also alleviated. Histopathological and immunohistochemical examinations confirmed the brain injury tissue changes. The nanoshell molecular probe carrying anti-tropomyosin 4 has potential for use in early diagnosis of cerebral ischemia/reperfusion injury and evaluating its progression.

2.
Artigo em Inglês | MEDLINE | ID: mdl-36458940

RESUMO

Immune checkpoint blockade has become a paradigm-shifting treatment modality to combat cancer, while conventional administration of immune checkpoint inhibitors, such as anti-PD-L1 antibody (α-PD-L1), often shows unsatisfactory immune responses and lead to severe immune-related adverse effects (irAEs). Herein, we develop a PD-L1 aptamer (aptPD-L1) based spherical nucleic acids (SNAs), which consists of an oxaliplatin (OXA) encapsulated metal-organic framework nanoparticle core and a dense shell of aptPD-L1 (denoted as M@O-A). Upon light irradiation, such nanosystem enables concurrent photodynamic therapy (PDT), chemotherapy and enhanced immunotherapy on one shot to inhibit both primary colorectal tumors and untreated distant tumors in mice. Notably, M@O-A shows scarcely any systemic immunotoxicity in a clinical irAEs-mimic transgenic mouse model. Collectively, this study presents a novel strategy for priming robust photo-immunotherapy against cancer with enhanced safety.

3.
Med Phys ; 2022 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-36453607

RESUMO

BACKGROUND: Histopathological grading is a significant risk factor for postsurgical recurrence in hepatocellular carcinoma (HCC). Preoperative knowledge of histopathological grading could provide instructive guidance for individualized treatment decision-making in HCC management. PURPOSE: This study aims to develop and validate a newly proposed deep learning model to predict histopathological grading in HCC with improved accuracy. METHODS: In this dual-center study, we retrospectively enrolled 384 HCC patients with complete clinical, pathological and radiological data. Aiming to synthesize radiological information derived from both tumor parenchyma and peritumoral microenvironment regions, a modeling strategy based on a multi-scale and multi-region dense connected convolutional neural network (MSMR-DenseCNNs) was proposed to predict histopathological grading using preoperative contrast enhanced computed tomography (CT) images. Multi-scale inputs were defined as three-scale enlargement of an original minimum bounding box in width and height by given pixels, which correspondingly contained more peritumoral analysis areas with the enlargement. Multi-region inputs were defined as three regions of interest (ROIs) including a squared ROI, a precisely delineated tumor ROI, and a peritumoral tissue ROI. The DenseCNN structure was designed to consist of a shallow feature extraction layer, dense block module, and transition and attention module. The proposed MSMR-DenseCNN was pretrained by the ImageNet dataset to capture basic graphic characteristics from the images and was retrained by the collected retrospective CT images. The predictive ability of the MSMR-DenseCNN models on triphasic images was compared with a conventional radiomics model, radiological model and clinical model. RESULTS: MSMR-DenseCNN applied to the delayed phase (DP) achieved the highest area under the curve (AUC) of 0.867 in the validation cohort for grading prediction, outperforming those on the arterial phase (AP) and portal venous phase (PVP). Fusion of the results on triphasic images did not increase the predictive ability, which underscored the role of DP for grading prediction. Compared with a single-scale and single-region network, the DP-phase based MSMR-DenseCNN model remarkably raised sensitivity from 67.4% to 75.5% with comparable specificity of 78.6%. MSMR-DenseCNN on DP defeated conventional radiomics, radiological and clinical models, where the AUCs were correspondingly 0.765, 0.695 and 0.612 in the validation cohort. CONCLUSIONS: The MSMR-DenseCNN modeling strategy increased the accuracy for preoperative prediction of grading in HCC, and enlightens similar radiological analysis pipelines in a variety of clinical scenarios in HCC management. This article is protected by copyright. All rights reserved.

4.
Gastroenterol Rep (Oxf) ; 10: goac064, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36457374

RESUMO

Gastric cancer (GC) is one of the most common malignant tumors with high mortality. Accurate diagnosis and treatment decisions for GC rely heavily on human experts' careful judgments on medical images. However, the improvement of the accuracy is hindered by imaging conditions, limited experience, objective criteria, and inter-observer discrepancies. Recently, the developments of machine learning, especially deep-learning algorithms, have been facilitating computers to extract more information from data automatically. Researchers are exploring the far-reaching applications of artificial intelligence (AI) in various clinical practices, including GC. Herein, we aim to provide a broad framework to summarize current research on AI in GC. In the screening of GC, AI can identify precancerous diseases and assist in early cancer detection with endoscopic examination and pathological confirmation. In the diagnosis of GC, AI can support tumor-node-metastasis (TNM) staging and subtype classification. For treatment decisions, AI can help with surgical margin determination and prognosis prediction. Meanwhile, current approaches are challenged by data scarcity and poor interpretability. To tackle these problems, more regulated data, unified processing procedures, and advanced algorithms are urgently needed to build more accurate and robust AI models for GC.

5.
Water Res ; 226: 119316, 2022 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-36369691

RESUMO

As a class of emerging aquatic pollutants, alkylimidazole-based ionic liquids (AM-ILs) have received extensive attention due to the large acute toxicity to aquatic organisms. Therefore, in order to protect both aquatic organisms and human beings, it is necessary to seek an efficient and environmental-friendly technology for removal of AM-ILs from water bodies. In this work, we found that under simulated sunlight (Xe lamp) irradiation, periodate (KIO4, PI) could efficiently degrade 1-hexyl-2,3-dimethylimidazolium bromide ([HMMIm]Br), a representative AM-ILs with six carbon atoms in the side chain. Kinetics experiments on the degradation of [HMMIm]Br were performed, and the results showed that a high degradation efficiency (≥90.00%) of the cation ([HMMIm]+) was still maintained under harsh water conditions of strong acidity/alkaliny or with various non-target inorganic ions. More importantly, the anion of bromide ion (Br-) was not oxidized to the carcinogenic bromate (BrO3-) in current reaction system. The excited stated PI (marked as PI*) was detected by Laser flash photolysis, and it was an important reactive species for [HMMIm]+ degradation. As rationalized by theoretical calculations and scavenging experiments, the main oxidation mechanisms of [HMMIm]+ were hydroxyl radicals induced substitution reaction, PI* initiated electron and double oxygen transfer, and direct photolysis mediated chemical bond cleavage reaction, which contributed to 73%, 21%, and 6% of [HMMIm]+ degradation, respectively. Moreover, toxicity evaluation by ECOSAR software indicated that the oxidation products were generally less toxic to three aquatic organisms (fish, water flea, and green algae) than the target molecule [HMMIm]Br. In conclusion, this work proposed novel oxidation mechanisms of sunlight-activated PI system, and the findings may inspire further researches on the application of photoactivated hypervalent acids in water purification.


Assuntos
Líquidos Iônicos , Poluentes Químicos da Água , Animais , Humanos , Líquidos Iônicos/química , Luz Solar , Brometos , Poluentes Químicos da Água/química , Fotólise , Cinética , Imidazóis/química
6.
IEEE Trans Med Imaging ; PP2022 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-36383594

RESUMO

Identifying squamous cell carcinoma and adenocarcinoma subtypes of metastatic cervical lymphadenopathy (CLA) is critical for localizing the primary lesion and initiating timely therapy. B-mode ultrasound (BUS), color Doppler flow imaging (CDFI), ultrasound elastography (UE) and dynamic contrast-enhanced ultrasound provide effective tools for identification but synthesis of modality information is a challenge for clinicians. Therefore, based on deep learning, rationally fusing these modalities with clinical information to personalize the classification of metastatic CLA requires new explorations. In this paper, we propose Multi-step Modality Fusion Network (MSMFN) for multi-modal ultrasound fusion to identify histological subtypes of metastatic CLA. MSMFN can mine the unique features of each modality and fuse them in a hierarchical three-step process. Specifically, first, under the guidance of high-level BUS semantic feature maps, information in CDFI and UE is extracted by modality interaction, and the static imaging feature vector is obtained. Then, a self-supervised feature orthogonalization loss is introduced to help learn modality heterogeneity features while maintaining maximal task-consistent category distinguishability ofmodalities. Finally, six encoded clinical information are utilized to avoid prediction bias and improve prediction ability further. Our three-fold cross-validation experiments demonstrate that our method surpasses clinicians and other multi-modal fusion methods with an accuracy of 80.06%, a true-positive rate of 81.81%, and a true-negative rate of 80.00%. Our network provides a multi-modal ultrasound fusion framework that considers prior clinical knowledge and modality-specific characteristics. Our code will be available at: https://github.com/RichardSunnyMeng/MSMFN.

7.
BMC Med ; 20(1): 435, 2022 11 09.
Artigo em Inglês | MEDLINE | ID: mdl-36352411

RESUMO

BACKGROUND: Although immune checkpoint inhibitors (ICIs) have influenced the treatment paradigm for multiple solid tumors, increasing evidence suggests that primary and adaptive resistance may limit the long-term efficacy of ICIs. New therapeutic strategies with other drug combinations are hence warranted to enhance the antitumor efficacy of ICIs. As a novel tumor suppressor, histone deacetylase (HDAC) inhibitor tucidinostat has been successfully confirmed to act against hematological malignancies. However, the underlying mechanisms of action for tucidinostat and whether it can manipulate the tumor microenvironment (TME) in solid tumors remain unclear. METHODS: Three murine tumor models (4T1, LLC, and CT26) were developed to define the significant role of different doses of tucidinostat in TME. The immunotherapeutic effect of tucidinostat combined with anti-programmed cell death ligand 1 antibody (aPD-L1) was demonstrated. Furthermore, the effect of tucidinostat on phenotypic characteristics of peripheral blood mononuclear cells (PBMCs) from lung cancer patients was investigated. RESULTS: With an optimized dose, tucidinostat could alter TME and promote the migration and infiltration of CD8+ T cells into tumors, partially by increasing the activity of C-C motif chemokine ligand 5 (CCL5) via NF-κB signaling. Moreover, tucidinostat significantly promoted M1 polarization of macrophages and increased the in vivo antitumor efficacy of aPD-L1. Tucidinostat also enhanced the expression of the costimulatory molecules on human monocytes, suggesting a novel and improved antigen-presenting function. CONCLUSIONS: A combination regimen of tucidinostat and aPD-L1 may work synergistically to reduce tumor burden in patients with cancer by enhancing the immune function and provided a promising treatment strategy to overcome ICI treatment resistance.


Assuntos
Inibidores de Histona Desacetilases , Neoplasias Pulmonares , Humanos , Camundongos , Animais , Inibidores de Histona Desacetilases/farmacologia , Linfócitos T CD8-Positivos , Leucócitos Mononucleares/patologia , Microambiente Tumoral , Neoplasias Pulmonares/patologia , Linhagem Celular Tumoral
8.
Front Genet ; 13: 963163, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36437938

RESUMO

Background: A high level of education or intelligence (IQ) is reported to be a risk factor for Parkinson's disease (PD). The purpose of this study was to systematically examine the causal relationships between IQ, educational attainment (EA), cognitive performance, and PD. Methods: We used summary statistics from genome-wide association studies on IQ, EA, cognitive performance, and PD. Four genome-wide association study (GWAS) data for PD were used to comprehensively explore the causal relationship, including PD GWAS (regardless of sex), age at onset of PD GWAS, male with PD GWAS, and female with PD GWAS data. We conducted a two sample Mendelian randomization (MR) study using the inverse-variance weighted (IVW), weighted median, simple mode, and weighted mode methods to evaluate the causal association between these factors. MR-Egger and MR-PRESSO were used for sensitivity analysis to test and correct horizontal pleiotropy. Multivariate MR (MVMR) was also used to account for the covariation between IQ, EA, and cognition, as well as to explore potential mediating factors. Results: Genetically predicted higher IQ was associated with an increased risk of PD in the entire population, regardless of gender. In the analyses using the IVW method, the odds ratio was 1.37 (p = 0.0064). Men with a higher IQ, more years of education, or stronger cognitive ability are more likely to develop PD compared to women. MVMR showed that adjusting for education and cognition largely attenuated the association between IQ and PD, suggesting that education and cognition may mediate the effect of IQ on PD. Conclusion: This study provides genetic support for the causal link between higher IQ and an increased risk of PD.

9.
Artigo em Inglês | MEDLINE | ID: mdl-36443568

RESUMO

Lymph node metastasis is an indicator of the invasiveness and aggressiveness of cancer. It is a vital prognostic factor in clinical staging of the disease and therapeutic decision-making. Patients with positive metastatic lymph nodes are likely to develop recurrent disease, distant metastasis, and succumb to death in the coming few years. Lymph node dissection and histological analysis are needed to detect whether regional lymph nodes have been infiltrated by cancer cells and determine the likely outcome of treatment and the patient's chances of survival. However, these procedures are invasive, and tissue biopsies are prone to sampling error. In recent years, advanced molecular imaging with novel imaging probes has provided new technologies that are contributing to comprehensive management of cancer, including non-invasive investigation of lymphatic drainage from tumors, identifying metastatic lymph nodes, and guiding surgeons to operate efficiently in patients with complex lesions. In this review, first, we outline the current status of different molecular imaging modalities applied for lymph node metastasis management. Second, we summarize the multi-functional imaging probes applied with the different imaging modalities as well as applications of cancer lymph node metastasis from preclinical studies to clinical translations. Third, we describe the limitations that must be considered in the field of molecular imaging for improved detection of lymph node metastasis. Finally, we propose future directions for molecular imaging technology that will allow more personalized treatment plans for patients with lymph node metastasis.

11.
Cancer ; 2022 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-36401611

RESUMO

BACKGROUND: Neoadjuvant chemotherapy (NAC) can downstage tumors and axillary lymph nodes in breast cancer (BC) patients. However, tumors and axillary response to NAC are not parallel and vary among patients. This study aims to explore the feasibility of deep learning radiomics nomogram (DLRN) for independently predicting the status of tumors and lymph node metastasis (LNM) after NAC. METHODS: In total, 484 BC patients who completed NAC from two hospitals (H1: 297 patients in the training cohort and 99 patients in the validation cohort; H2: 88 patients in the test cohort) were retrospectively enrolled. The authors developed two deep learning radiomics (DLR) models for personalized prediction of the tumor pathologic complete response (PCR) to NAC (DLR-PCR) and the LNM status (DLR-LNM) after NAC based on pre-NAC and after-NAC ultrasonography images. Furthermore, they proposed two DLRNs (DLRN-PCR and DLRN-LNM) for two different tasks based on the clinical characteristics and DLR scores, which were generated from both DLR-PCR and DLR-LNM. RESULTS: In the validation and test cohorts, DLRN-PCR exhibited areas under the receiver operating characteristic curves (AUCs) of 0.903 and 0.896 with sensitivities of 91.2% and 75.0%, respectively. DLRN-LNM achieved AUCs of 0.853 and 0.863, specificities of 82.0% and 81.8%, and negative predictive values of 81.3% and 87.2% in the validation and test cohorts, respectively. The two DLRN models achieved satisfactory predictive performance based on different BC subtypes. CONCLUSIONS: The proposed DLRN models have the potential to accurately predict the tumor PCR and LNM status after NAC. PLAIN LANGUAGE SUMMARY: In this study, we proposed two deep learning radiomics nomogram models based on pre-neoadjuvant chemotherapy (NAC) and preoperative ultrasonography images for independently predicting the status of tumor and axillary lymph node (ALN) after NAC. A more comprehensive assessment of the patient's condition after NAC can be achieved by predicting the status of the tumor and ALN separately. Our model can potentially provide a noninvasive and personalized method to offer decision support for organ preservation and avoidance of excessive surgery.

12.
EBioMedicine ; 86: 104364, 2022 Nov 14.
Artigo em Inglês | MEDLINE | ID: mdl-36395737

RESUMO

BACKGROUND: This study, based on multicentre cohorts, aims to utilize computed tomography (CT) images to construct a deep learning model for predicting major pathological response (MPR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC) and further explore the biological basis under its prediction. METHODS: 274 patients undergoing curative surgery after neoadjuvant chemoimmunotherapy for NSCLC at 4 centres from January 2019 to December 2021 were included and divided into a training cohort, an internal validation cohort, and an external validation cohort. ShuffleNetV2x05-based features of the primary tumour on the CT scans within the 2 weeks preceding neoadjuvant administration were employed to develop a deep learning score for distinguishing MPR and non-MPR. To reveal the underlying biological basis of the deep learning score, a genetic analysis was conducted based on 25 patients with RNA-sequencing data. FINDINGS: MPR was achieved in 54.0% (n = 148) patients. The area under the curve (AUC) of the deep learning score to predict MPR was 0.73 (95% confidence interval [CI]: 0.58-0.86) and 0.72 (95% CI: 0.58-0.85) in the internal validation and external validation cohorts, respectively. After integrating the clinical characteristic into the deep learning score, the combined model achieved satisfactory performance in the internal validation (AUC: 0.77, 95% CI: 0.64-0.89) and external validation cohorts (AUC: 0.75, 95% CI: 0.62-0.87). In the biological basis exploration for the deep learning score, a high deep learning score was associated with the downregulation of pathways mediating tumour proliferation and the promotion of antitumour immune cell infiltration in the microenvironment. INTERPRETATION: The proposed deep learning model could effectively predict MPR in NSCLC patients treated with neoadjuvant chemoimmunotherapy. FUNDING: This study was supported by National Key Research and Development Program of China, China (2017YFA0205200); National Natural Science Foundation of China, China (91959126, 82022036, 91959130, 81971776, 81771924, 6202790004, 81930053, 9195910169, 62176013, 8210071009); Beijing Natural Science Foundation, China (L182061); Strategic Priority Research Program of Chinese Academy of Sciences, China (XDB38040200); Chinese Academy of Sciences, China (GJJSTD20170004, QYZDJ-SSW-JSC005); Shanghai Hospital Development Center, China (SHDC2020CR3047B); and Science and Technology Commission of Shanghai Municipality, China (21YF1438200).

13.
Artigo em Inglês | MEDLINE | ID: mdl-36450938

RESUMO

PURPOSE: To investigate the feasibility and accuracy of near-infrared fluorescence (NIRF) imaging for detecting the extent of tumor invasion in cervical cancer using indocyanine green (ICG). METHODS: We enrolled 51 patients who were diagnosed with cervical cancer with FIGO stage IB1-IIA2 disease. Patients were administered indocyanine green (ICG) at a dose of 5 mg/kg 24 h prior to surgery. A customized near-infrared fluorescence (NIRF) imaging system was used to identify the extent of tumor invasion when radical hysterectomy specimens were harvested. The relationship between tumor fluorescence intensity and clinicopathological characteristics was analyzed. RESULTS: Of the 51 enrolled patients, 3 patients did not have residual tumors after cervical conization, and tumor lesions were identified by NIRF imaging in all the remaining 48 patients. The results of NIRF imaging were in agreement with the postoperative pathological findings in 95.8% of the patients with stromal invasion, 100% of those with surgical margin invasion, 100% of those with parametrial tumor involvement, and 100% of patients with uterine corpus invasion. The mean signal-to-background ratio (SBR) of the cervical tumors was 2.91 ± 1.64, and the SBR was independent of clinicopathological characteristics. Fluorescence microscopy confirmed that ICG fluorescence was present in the tumor nests. CONCLUSIONS: NIRF imaging enables objective, accurate, and safe identification of tumor invasion during cervical cancer surgery. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT04224467.

14.
Sci Total Environ ; : 160312, 2022 Nov 17.
Artigo em Inglês | MEDLINE | ID: mdl-36403825

RESUMO

Millions of premature mortalities are caused by the air pollution of fine particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) globally per year. To effectively control the dominant emission sources and abate air pollution, source apportionment of PM2.5 is normally conducted to quantify the contributions of various sources, but the results of different methods might be inconsistent. In this study, we dynamically harmonized the results from the two dominant source apportionment methods, the source-oriented and receptor models, by updating the emission inventories of primary PM2.5 from the major sectors based on the Bayesian Inference. An adjoint model was developed to efficiently construct the source-receptor sensitivity matrix, which was the critical information for the updates, and depicted the response of measurements to the changes in the emissions of various sources in different regions. The harmonized method was applied to a measurement campaign in Beijing from January to February 2021. The results suggested a significant reduction of primary PM2.5 emissions in Beijing. Compared with the baseline emission inventory of 2017, the primary PM2.5 emissions from the local residential combustion and industry in Beijing had significantly declined by about 90 % during the investigated period of the year, and the traffic emission decreased by about 50 %. The proposed methods successfully identified the temporally dynamic changes in the emissions induced by the Spring Festival. The methods could be a promising pathway for the harmonization of source-oriented and receptor source apportionment models.

15.
Artigo em Inglês | MEDLINE | ID: mdl-36409317

RESUMO

PURPOSE: This study aimed to develop deep learning (DL) models based on multicentre biparametric magnetic resonance imaging (bpMRI) for the diagnosis of clinically significant prostate cancer (csPCa) and compare the performance of these models with that of the Prostate Imaging and Reporting and Data System (PI-RADS) assessment by expert radiologists based on multiparametric MRI (mpMRI). METHODS: We included 1861 consecutive male patients who underwent radical prostatectomy or biopsy at seven hospitals with mpMRI. These patients were divided into the training (1216 patients in three hospitals) and external validation cohorts (645 patients in four hospitals). PI-RADS assessment was performed by expert radiologists. We developed DL models for the classification between benign and malignant lesions (DL-BM) and that between csPCa and non-csPCa (DL-CS). An integrated model combining PI-RADS and the DL-CS model, abbreviated as PIDL-CS, was developed. The performances of the DL models and PIDL-CS were compared with that of PI-RADS. RESULTS: In each external validation cohort, the area under the receiver operating characteristic curve (AUC) values of the DL-BM and DL-CS models were not significantly different from that of PI-RADS (P > 0.05), whereas the AUC of PIDL-CS was superior to that of PI-RADS (P < 0.05), except for one external validation cohort (P > 0.05). The specificity of PIDL-CS for the detection of csPCa was much higher than that of PI-RADS (P < 0.05). CONCLUSION: Our proposed DL models can be a potential non-invasive auxiliary tool for predicting csPCa. Furthermore, PIDL-CS greatly increased the specificity of csPCa detection compared with PI-RADS assessment by expert radiologists, greatly reducing unnecessary biopsies and helping radiologists achieve a precise diagnosis of csPCa.

16.
Ying Yong Sheng Tai Xue Bao ; 33(11): 3065-3074, 2022 Oct.
Artigo em Chinês | MEDLINE | ID: mdl-36384841

RESUMO

Cultural landscapes are the products of combination of natural and human factors with constant change in response to human behavior. Exploring the impacts of construction land expansion on cultural landscapes is the key to understand the formal connotations and value characteristics of human activities interfering with cultural landscapes. In this study, we first classified the cultural landscape of the Hanjiang Delta and then used the landscape index to quantitatively describe the spatial and temporal evolution characteristics of the cultural landscape from 1980 to 2018. Finally, we analyzed the spatial effect between construction land expansion and the cultural landscape with a spatial panel econometric model. The results showed that a total of seven cultural landscape types were identified at the regional level. From 1980 to 2000, the cultural landscape pattern in the study area changed substantially, with increasing fragmentation, deepening irregularity, and increasing diversity. The proportion of regional construction land increased from 14.8% to 29.9%. The year 2000 was the cut-off point for the rate of construction land expansion, and the chronological characteristics of cultural landscape change coincided with it. There was a spatial dependency between the expansion of construction land and the change of cultural landscape. With the expansion of construction land, the sprawl town landscape in sand dike became the dominant type, and the paddy scattered historical villages, the wetland agglomeration town landscape, and the paddy wetland landscape in net river lowland faced extinction. Construction land expansion affected the local landscape pattern and had spatial spillover effects on neighboring areas. For a particular landscape type, the expansion of construction land led to a general increase in the degree of patch integration and an enhanced landscape agglomeration effect. For different types, this led to a decrease in inter-landscape sprawl, an increase in patch irregularity, and enhanced fragmentation. This study could provide a reference for the human history inheritance and ecological pattern optimization in the Hanjiang Delta.


Assuntos
Conservação dos Recursos Naturais , Ecossistema , Humanos , Conservação dos Recursos Naturais/métodos , China , Rios , Cidades
17.
Front Oncol ; 12: 1030626, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36387158

RESUMO

We reported a case of pure laparoscopic radical nephroureterectomy for complicated renal pelvis carcinoma combined with horseshoe kidney (HSK). The aim was to present a case report and review of the literature about renal pelvis carcinoma combined with HSK. The case report includes a history of patient data. The pure laparoscopic radical nephroureterectomy was provided with the informed consent of the patient. A 53-year-old patient was diagnosed with a right renal pelvis mass with HSK. We performed laparoscopic radical nephroureterectomy with partial cystectomy and horseshoe renal isthmus amputation. Histopathological features, computed tomography urography (CTU), and angiography (CTA) confirmed the diagnosis of renal pelvis carcinoma combined with HSK. The tumor was removed, and the patient had an uneventful recovery. Renal pelvis carcinoma combined with HSK is a rare case. Due to severe anatomical abnormalities, this disease is a major challenge for urologists. We share our successful case for readers to learn from.

18.
J Biophotonics ; 15(11): e202200126, 2022 11.
Artigo em Inglês | MEDLINE | ID: mdl-36328059

RESUMO

Cerenkov luminescence tomography (CLT) is a promising three-dimensional imaging technology that has been actively investigated in preclinical studies. However, because of the ill-posedness in the inverse problem of CLT reconstruction, the reconstruction performance is still not satisfactory for broad biomedical applications. In this study, a novel weighted auxiliary set matching pursuit (WASMP) method was explored to enhance the accuracy of CLT reconstruction. The numerical simulations and in vivo imaging studies using tumor-bearing mice models were conducted to evaluate the performance of the WASMP method. The results of the above experiments proved that the WASMP method achieved superior reconstruction performance than other approaches in terms of positional accuracy and shape recovery. It further demonstrates that the atom selection strategy proposed in this study has a positive effect on improving the accuracy of atoms. The proposed WASMP improves the accuracy for CLT reconstruction for biomedical applications.


Assuntos
Glioma , Tomografia Óptica , Animais , Camundongos , Tomografia Óptica/métodos , Luminescência , Tomografia , Tomografia Computadorizada por Raios X , Imageamento Tridimensional/métodos , Glioma/diagnóstico por imagem , Algoritmos , Imagens de Fantasmas
19.
J Org Chem ; 87(23): 15986-15997, 2022 Dec 02.
Artigo em Inglês | MEDLINE | ID: mdl-36397210

RESUMO

The asymmetric hydrogenation of α-halogenated ketones with iridium catalyst was developed, utilizing easily accessed cinchona-alkaloid-based NNP ligands. Various α-chloroacetophenones, heterocyclic thienyl and furanyl substrates, and even bromoketones were completely converted to the desired chiral halohydrins by this protocol. Both (R)- and (S)-chiral halohydrins can be prepared by changing the configurations of the chiral ligand NNP with up to 99.6% ee (enantiomeric excess) and 98.8% ee, respectively. Also, a gram-scale experiment was carried out efficiently.


Assuntos
Alcaloides de Cinchona , Cinchona , Ligantes , Hidrogenação , Cetonas
20.
Cell Mol Immunol ; 19(12): 1361-1372, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36369368

RESUMO

Myeloid-derived suppressor cells (MDSCs) comprise heterogeneous myeloid cell populations with immunosuppressive capacity that contribute to immune regulation and tolerance induction. We previously reported impaired MDSC function in patients with primary Sjögren's syndrome (pSS) and mice with experimental SS (ESS). However, the molecular mechanisms underlying MDSC dysfunction remain largely unclear. In this study, we first found that aryl hydrocarbon receptor (AhR) was highly expressed by human and murine polymorphonuclear MDSCs (PMN-MDSCs). Indole-3-propionic acid (IPA), a natural AhR ligand produced from dietary tryptophan, significantly promoted PMN-MDSC differentiation and suppressive function on CD4+ T cells. In contrast, feeding a tryptophan-free diet resulted in a decreased PMN-MDSC response, a phenotype that could be reversed by IPA supplementation. The functional importance of PMN-MDSCs was demonstrated in ESS mice by using a cell-depletion approach. Notably, AhR expression was reduced in PMN-MDSCs during ESS development, while AhR antagonism resulted in exacerbated ESS pathology and dysregulated T effector cells, which could be phenocopied by a tryptophan-free diet. Interferon regulatory factor 4 (IRF4), a repressive transcription factor, was upregulated in PMN-MDSCs during ESS progression. Chromatin immunoprecipitation analysis revealed that IRF4 could bind to the promoter region of AhR, while IRF4 deficiency markedly enhanced AhR-mediated PMN-MDSC responses. Furthermore, dietary supplementation with IPA markedly ameliorated salivary glandular pathology in ESS mice with restored MDSC immunosuppressive function. Together, our results identify a novel function of AhR in modulating the PMN-MDSC response and demonstrate the therapeutic potential of targeting AhR for the treatment of pSS.


Assuntos
Células Supressoras Mieloides , Síndrome de Sjogren , Humanos , Animais , Camundongos , Receptores de Hidrocarboneto Arílico/metabolismo , Células Mieloides , Linfócitos T
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