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"Wei, Jing"
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Motivating role of type H vessels in bone regeneration
Coupling between angiogenesis and osteogenesis has an important role in both normal bone injury repair and successful application of tissue‐engineered bone for bone defect repair. Type H blood vessels are specialized microvascular components that are closely related to the speed of bone healing. Interactions between type H endothelial cells and osteoblasts, and high expression of CD31 and EMCN render the environment surrounding these blood vessels rich in factors conducive to osteogenesis and promote the coupling of angiogenesis and osteogenesis. Type H vessels are mainly distributed in the metaphysis of bone and densely surrounded by Runx2+ and Osterix+ osteoprogenitors. Several other factors, including hypoxia‐inducible factor‐1α, Notch, platelet‐derived growth factor type BB, and slit guidance ligand 3 are involved in the coupling of type H vessel formation and osteogenesis. In this review, we summarize the identification and distribution of type H vessels and describe the mechanism for type H vessel‐mediated modulation of osteogenesis. Type H vessels provide new insights for detection of the molecular and cellular mechanisms that underlie the crosstalk between angiogenesis and osteogenesis. As a result, more feasible therapeutic approaches for treatment of bone defects by targeting type H vessels may be applied in the future.
Type H vessels are mainly distributed in the metaphyseal region and sub‐periosteum and show strong positive staining for CD31 and EMCN. They are specialized microvascular components and closely related to bone healing speed through the crosstalk between angiogenesis and osteogenesis.
Journal Article
A radiomics nomogram may improve the prediction of IDH genotype for astrocytoma before surgery
ObjectivesTo develop and validate a radiomics nomogram to preoperative prediction of isocitrate dehydrogenase (IDH) genotype for astrocytomas, which might contribute to the pretreatment decision-making and prognosis evaluating.MethodsOne hundred five astrocytomas (Grades II–IV) with contrast-enhanced T1-weighted imaging (CE-T1WI), T2 fluid-attenuated inversion recovery (T2FLAIR), and apparent diffusion coefficient (ADC) map were enrolled in this study (training cohort: n = 74; validation cohort: n = 31). IDH1/2 genotypes were determined using Sanger sequencing. A total of 3882 radiomics features were extracted. Support vector machine algorithm was used to build the radiomics signature on the training cohort. Incorporating radiomics signature and clinico-radiological risk factors, the radiomics nomogram was developed. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess these models. Kaplan–Meier survival analysis and log rank test were performed to assess the prognostic value of the radiomics nomogram.ResultsThe radiomics signature was built by six selected radiomics features and yielded AUC values of 0.901 and 0.888 in the training and validation cohorts. The radiomics nomogram based on the radiomics signature and age performed better than the clinico-radiological model (training cohort, AUC = 0.913 and 0.817; validation cohort, AUC = 0.900 and 0.804). Additionally, the survival analysis showed that prognostic values of the radiomics nomogram and IDH genotype were similar (log rank test, p < 0.001; C-index = 0.762 and 0.687; z-score test, p = 0.062).ConclusionsThe radiomics nomogram might be a useful supporting tool for the preoperative prediction of IDH genotype for astrocytoma, which could aid pretreatment decision-making.Key Points• The radiomics signature based on multiparametric and multiregional MRI images could predict IDH genotype of Grades II–IV astrocytomas.• The radiomics nomogram performed better than the clinico-radiological model, and it might be an easy-to-use supporting tool for IDH genotype prediction.• The prognostic value of the radiomics nomogram was similar with that of the IDH genotype, which might contribute to prognosis evaluating.
Journal Article
Investigating the Mechanism of Hyperglycemia-Induced Fetal Cardiac Hypertrophy
Hyperglycemia in diabetic mothers enhances the risk of fetal cardiac hypertrophy during gestation. However, the mechanism of high-glucose-induced cardiac hypertrophy is not largely understood. In this study, we first demonstrated that the incidence rate of cardiac hypertrophy dramatically increased in fetuses of diabetic mothers using color ultrasound examination. In addition, human fetal cardiac hypertrophy was successfully mimicked in a streptozotocin (STZ)-induced diabetes mouse model, in which mouse cardiac hypertrophy was diagnosed using type-M ultrasound and a histological assay. PH3 immunofluorescent staining of mouse fetal hearts and in vitro-cultured H9c2 cells indicated that cell proliferation decreased in E18.5, E15.5 and E13.5 mice, and cell apoptosis in H9c2 cells increased in the presence of high glucose in a dose-dependent manner. Next, we found that the individual cardiomyocyte size increased in pre-gestational diabetes mellitus mice and in response to high glucose exposure. Meanwhile, the expression of β-MHC and BMP-10 was up-regulated. Nkx2.5 immunofluorescent staining showed that the expression of Nkx2.5, a crucial cardiac transcription factor, was suppressed in the ventricular septum, left ventricular wall and right ventricular wall of E18.5, E15.5 and E13.5 mouse hearts. However, cardiac hypertrophy did not morphologically occur in E13.5 mouse hearts. In cultured H9c2 cells exposed to high glucose, Nkx2.5 expression decreased, as detected by both immunostaining and western blotting, and the expression of KCNE1 and Cx43 was also restricted. Taken together, alterations in cell size rather than cell proliferation or apoptosis are responsible for hyperglycemia-induced fetal cardiac hypertrophy. The aberrant expression of Nkx2.5 and its regulatory target genes in the presence of high glucose could be a principal component of pathogenesis in the development of fetal cardiac hypertrophy.
Journal Article
Wide-temperature-range thermoelectric n-type Mg3(Sb,Bi)2 with high average and peak zT values
Mg
3
(Sb,Bi)
2
is a promising thermoelectric material suited for electronic cooling, but there is still room to optimize its low-temperature performance. This work realizes >200% enhancement in room-temperature
zT
by incorporating metallic inclusions (Nb or Ta) into the Mg
3
(Sb,Bi)
2
-based matrix. The electrical conductivity is boosted in the range of 300–450 K, whereas the corresponding Seebeck coefficients remain unchanged, leading to an exceptionally high room-temperature power factor >30 μW cm
−1
K
−2
; such an unusual effect originates mainly from the modified interfacial barriers. The reduced interfacial barriers are conducive to carrier transport at low and high temperatures. Furthermore, benefiting from the reduced lattice thermal conductivity, a record-high average
zT
> 1.5 and a maximum
zT
of 2.04 at 798 K are achieved, resulting in a high thermoelectric conversion efficiency of 15%. This work demonstrates an efficient nanocomposite strategy to enhance the wide-temperature-range thermoelectric performance of n-type Mg
3
(Sb,Bi)
2
, broadening their potential for practical applications.
The utilization of Mg
3
(Sb,Bi)
2
in thermoelectric devices is hindered by its low performance near room temperature. Here, authors report thermoelectric performance enhancement of Mg
3
(Sb,Bi)
2
within a wide temperature range by incorporating metallic inclusions at grain boundaries. (279 in total)
Journal Article
Evolution of defect structures leading to high ZT in GeTe-based thermoelectric materials
GeTe is a promising mid-temperature thermoelectric compound but inevitably contains excessive Ge vacancies hindering its performance maximization. This work reveals that significant enhancement in the dimensionless figure of merit (
ZT
) could be realized by defect structure engineering from point defects to line and plane defects of Ge vacancies. The evolved defects including dislocations and nanodomains enhance phonon scattering to reduce lattice thermal conductivity in GeTe. The accumulation of cationic vacancies toward the formation of dislocations and planar defects weakens the scattering against electronic carriers, securing the carrier mobility and power factor. This synergistic effect on electronic and thermal transport properties remarkably increases the quality factor. As a result, a maximum
ZT
> 2.3 at 648 K and a record-high average
ZT
(300-798 K) were obtained for Bi
0.07
Ge
0.90
Te in lead-free GeTe-based compounds. This work demonstrates an important strategy for maximizing the thermoelectric performance of GeTe-based materials by engineering the defect structures, which could also be applied to other thermoelectric materials.
The intrinsic high-concentration Ge vacancies in GeTe-based thermoelectric materials hinder their performance maximization. Here, the authors find that defect structure engineering strategy is effective for performance enhancement.
Journal Article
Deep Learning Methods for Remote Heart Rate Measurement: A Review and Future Research Agenda
Heart rate (HR) is one of the essential vital signs used to indicate the physiological health of the human body. While traditional HR monitors usually require contact with skin, remote photoplethysmography (rPPG) enables contactless HR monitoring by capturing subtle light changes of skin through a video camera. Given the vast potential of this technology in the future of digital healthcare, remote monitoring of physiological signals has gained significant traction in the research community. In recent years, the success of deep learning (DL) methods for image and video analysis has inspired researchers to apply such techniques to various parts of the remote physiological signal extraction pipeline. In this paper, we discuss several recent advances of DL-based methods specifically for remote HR measurement, categorizing them based on model architecture and application. We further detail relevant real-world applications of remote physiological monitoring and summarize various common resources used to accelerate related research progress. Lastly, we analyze the implications of research findings and discuss research gaps to guide future explorations.
Journal Article
Development and interpretation of a pathomics-based model for the prediction of microsatellite instability in Colorectal Cancer
Microsatellite instability (MSI) has been approved as a pan-cancer biomarker for immune checkpoint blockade (ICB) therapy. However, current MSI identification methods are not available for all patients. We proposed an ensemble multiple instance deep learning model to predict microsatellite status based on histopathology images, and interpreted the pathomics-based model with multi-omics correlation. Methods: Two cohorts of patients were collected, including 429 from The Cancer Genome Atlas (TCGA-COAD) and 785 from an Asian colorectal cancer (CRC) cohort (Asian-CRC). We established the pathomics model, named Ensembled Patch Likelihood Aggregation (EPLA), based on two consecutive stages: patch-level prediction and WSI-level prediction. The initial model was developed and validated in TCGA-COAD, and then generalized in Asian-CRC through transfer learning. The pathological signatures extracted from the model were analyzed with genomic and transcriptomic profiles for model interpretation. Results: The EPLA model achieved an area-under-the-curve (AUC) of 0.8848 (95% CI: 0.8185-0.9512) in the TCGA-COAD test set and an AUC of 0.8504 (95% CI: 0.7591-0.9323) in the external validation set Asian-CRC after transfer learning. Notably, EPLA captured the relationship between pathological phenotype of poor differentiation and MSI (P < 0.001). Furthermore, the five pathological imaging signatures identified from the EPLA model were associated with mutation burden and DNA damage repair related genotype in the genomic profiles, and antitumor immunity activated pathway in the transcriptomic profiles. Conclusions: Our pathomics-based deep learning model can effectively predict MSI from histopathology images and is transferable to a new patient cohort. The interpretability of our model by association with pathological, genomic and transcriptomic phenotypes lays the foundation for prospective clinical trials of the application of this artificial intelligence (AI) platform in ICB therapy.
Journal Article
Adjuvant sintilimab in resected high-risk hepatocellular carcinoma: a randomized, controlled, phase 2 trial
Hepatocellular carcinoma (HCC), particularly when accompanied by microvascular invasion (MVI), has a markedly high risk of recurrence after liver resection. Adjuvant immunotherapy is considered a promising avenue. This multicenter, open-label, randomized, controlled, phase 2 trial was conducted at six hospitals in China to assess the efficacy and safety of adjuvant sintilimab, a programmed cell death protein 1 inhibitor, in these patients. Eligible patients with HCC with MVI were randomized (1:1) into the sintilimab or active surveillance group. The sintilimab group received intravenous injections every 3 weeks for a total of eight cycles. The primary endpoint was recurrence-free survival (RFS) in the intention-to-treat population. Key secondary endpoints included overall survival (OS) and safety. From September 1, 2020, to April 23, 2022, a total of 198 eligible patients were randomly allocated to receive adjuvant sintilimab (
n
= 99) or undergo active surveillance (
n
= 99). After a median follow-up of 23.3 months, the trial met the prespecified endpoints. Sintilimab significantly prolonged RFS compared to active surveillance (median RFS, 27.7 versus 15.5 months; hazard ratio 0.534, 95% confidence interval 0.360–0.792;
P
= 0.002). Further follow-up is needed to confirm the difference in OS. In the sintilimab group, 12.4% of patients experienced grade 3 or 4 treatment-related adverse events, the most common of which were elevated alanine aminotransferase levels (5.2%) and anemia (4.1%). These findings support the potential of immune checkpoint inhibitors as effective adjuvant therapy for these high-risk patients. Chinese Clinical Trial Registry identifier:
ChiCTR2000037655
.
Results from a multicenter, randomized phase 2 trial in China show that adjuvant anti-PD-1 therapy in patients with resected hepatocellular carcinoma with microvascular invasion leads to prolonged recurrence-free survival compared to active surveillance.
Journal Article