Hemodynamic Effects of Tortuosity and Stenosis in Superficial Temporal Artery-Middle Cerebral Artery Bypass for Moyamoya Disease.

BACKGROUND: Superficial temporal artery (STA)-middle cerebral artery (MCA) bypass surgery has been widely adopted in treating moyamoya disease (MMD). Geometric variations including high tortuosity and stenosis exist in many cases, but the hemodynamic effects have not been comprehensively evaluated. We aim to evaluate the hemodynamic effects of bypass geometry variations based on patient-specific data. METHODS: In total, 17 patients with MMD who underwent STA-MCA bypass surgery with highly tortuous bypass geometry were included. For each patient, the original 3-dimensional structure of STA-MCA bypass was reconstructed from clinical imaging data. The bypass structure was virtually improved by removing the tortuosity and stenosis. Computational fluid dynamics simulation was performed on both bypass structures under identical patient-specific condition. The simulated hemodynamic parameters of the bypass and its distal branches were compared between the original and virtually improved bypass geometries in all cases using paired t-test or Wilcoxon signed-rank test. The changes of hemodynamic parameters were compared between the cases with and without mild-to-moderate stenosis (44.0-70.3% in diameter) in the bypass using t-test or Mann-Whitney U test. RESULTS: The virtual improvement of bypass geometry significantly increased the flow rate of the bypass and its distal branches (P < 0.05) and decreased the transcranial flow resistance (P < 0.05). The hemodynamic changes in cases with stenosis removal were significantly greater than those without stenosis (P < 0.05). CONCLUSIONS: High tortuosity and stenosis can significantly change the hemodynamics of STA-MCA bypass, and the optimization of bypass geometry deserves further consideration.

Diagnostic Performance of Angiography-Derived Quantitative Flow Ratio in Complex Coronary Lesions.

BACKGROUND: Quantitative flow ratio derived from computed tomography angiography (CT-QFR) and invasive coronary angiography (Murray law-based quantitative flow ratio [µQFR]) are novel approaches enabling rapid computation of fractional flow reserve without the use of pressure guidewires and vasodilators. However, the feasibility and diagnostic performance of both CT-QFR and µQFR in evaluating complex coronary lesions remain unclear. METHODS: Between September 2014 and September 2021, 240 patients with 30% to 90% coronary diameter stenosis who underwent both coronary computed tomography angiography and invasive coronary angiography with fractional flow reserve within 60 days were retrospectively enrolled. The diagnostic performance of CT-QFR and µQFR in detecting functional ischemia among all lesions, especially complex coronary lesions, was analyzed using fractional flow reserve as the reference standard. RESULTS: CT-QFR and µQFR analyses were performed on 309 and 289 vessels, respectively. The diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for CT-QFR in all lesions at the per-vessel level were 91% (with a 95% CI of 84%-96%), 92% (95% CI, 88%-95%), 83% (95% CI, 75%-90%), 96% (95% CI, 93%-98%), and 92% (95% CI, 88%-95%), with values for µQFR of 90% (95% CI, 81%-95%), 97% (95% CI, 93%-99%), 92% (95% CI, 84%-97%), 96% (95% CI, 92%-98%), and 94% (95% CI, 91%-97%), respectively. Among bifurcation, tandem, and moderate-to-severe calcified lesions, the diagnostic values of CT-QFR and µQFR showed great correlation and agreement with those of invasive fractional flow reserve, achieving an area under the receiver operating characteristic curve exceeding 0.9 for each complex lesion at the vessel level. Furthermore, the accuracies of CT-QFR and µQFR in the gray zone were 85% and 84%, respectively. CONCLUSIONS: Angiography-derived quantitative flow ratio (CT-QFR and µQFR) demonstrated remarkable diagnostic performance in complex coronary lesions, indicating its pivotal role in the management of patients with coronary artery disease.

Phantom study of a self-shielded X-ray bone age assessment instrument against scattered radiation in children.

Hand-wrist radiography is the most common and accurate method for evaluating children's bone age. To reduce the scattered radiation of radiosensitive organs in bone age assessment, we designed a small X-ray instrument with radioprotection function by adding metal enclosure for X-ray shielding. We used a phantom operator to compare the scattered radiation doses received by sensitive organs under three different protection scenarios (proposed instrument, radiation personal protective equipment, no protection). The proposed instrument showed greater reduction in the mean dose of a single exposure compared with radiation personal protective equipment especially on the left side which was proximal to the X-ray machine (≥80.0% in eye and thyroid, ≥99.9% in breast and gonad). The proposed instrument provides a new pathway towards more convenient and efficient radioprotection.

Compare image quality of T2-weighted imaging with different phase acceleration factors.

Previous studies demonstrated that adjusting the phase acceleration (PA) factors could influence image quality. To improve image quality and decrease respiratory artifacts of lesions in the liver on T2-weighted image by adjusting PA factor and number of excitation (NEX). Sixty consecutive patients with hepatic lesions were enrolled in this prospective research between May 2020 and June 2020. All patients had 3.0T magnetic resonance imaging with 4 sequences (combining PA factors and NEXs, the former was 2 and 3, the latter were 1.5 and 2, respectively, with the same other scanning parameters). Two readers used 5-point quality scales to assess image quality. The signal intensity was measured by drawing regions of interest in the liver, spleen, and background on the T2-weighted imaging. Artifacts, overall image impression, and vascular conspicuity were better when the PA factor was 3 than 2. Artifacts and vascular conspicuity were better when NEX was 2 than 1.5. PA factor 3 and NEX 2 got a higher score in 5-point quality scales and less scan time than the other 3 sequences. Meanwhile, the signal-to-noise ratio of PA factor 3 and NEX 2 was best among these 4 sequences. PA factor and NEX could influence the imaging quality and lesion-to-hepatic contrast in detecting hepatic lesions on T2-weighted images. PA factor 3 and NEX 2 may have a positive effect in the clinic, especially for those with irregular respiration, as it decreased artifacts and reduced scan time.

Efficacy assessment of superficial temporal artery-middle cerebral artery bypass surgery in treating moyamoya disease from a hemodynamic perspective: a pilot study using computational modeling and perfusion imaging.

BACKGROUND: Superficial temporal artery-middle cerebral artery (STA-MCA) bypass is a common surgery in treating moyamoya disease (MMD) with occluded MCA. Computational fluid dynamics (CFD) simulation might provide a simple, non-invasive, and low-cost tool to evaluate the efficacy of STA-MCA surgery. AIM: We aim to quantitatively investigate the treatment efficacy of STA-MCA surgery in improving the blood flow of MMD patients using CFD simulation. METHODS: This retrospective study included 11 MMD patients with occlusion around proximal MCA who underwent STA-MCA bypass surgery. CFD simulation was performed using patient-specific blood pressure and postoperative artery geometry. The volumetric flow rates of STA and the bypass, average flow velocity in the proximal segment of transcranial bypass, transcranial pressure drop, and transcranial flow resistance were measured and compared with a postoperative increment of cerebral blood flow (CBF) in MCA territories derived from perfusion imaging. Per-branch pressure drop from model inlet to bypass branch outlet was calculated. RESULTS: The volumetric flow rates of STA and the bypass were 80.84 ± 14.54 mL/min and 46.03 ± 4.21 mL/min. Average flow velocity in proximal bypass, transcranial pressure drop, and transcranial flow resistance were 0.19 ± 0.07 m/s, 3.72 ± 3.10 mmHg, and 6.54 ± 5.65 10-8 Pa s m-3. Postoperative mean increment of CBF in MCA territories was 16.03 ± 11.72 mL·100 g-1·min-1. Per-branch pressure drop was 10.96 ± 5.59 mmHg and 7.26 ± 4.25 mmHg in branches with and without stenosis. CONCLUSIONS: CFD simulation results are consistent with CBF observation in verifying the efficacy of STA-MCA bypass, where postoperative stenosis may influence the hemodynamics.

A phantom study of a protective trolley for neonatal radiographic imaging: new equipment to protect the operator from scatter radiation.

Chest radiography is commonly performed as a diagnostic tool of neonatal diseases. Contact-based radiation personal protective equipment (RPPE) has been widely used for radiation protection, but it does not provide full body protection and it is often shared between users, which has become a major concern during the coronavirus disease 2019 (COVID-19) pandemic. To address these issues, we developed a novel trolley to protect radiographers against X-ray radiation by reducing scatter radiation during neonatal radiographic examinations. We measured the scatter radiation doses from a standard neonatal chest radiograph to the radiosensitive organs using a phantom operator in three protection scenarios (trolley, radiation personal protective equipment [RPPE], no protection) and at three distances. The results showed that the scatter radiation surface doses were significantly reduced when using the trolley compared with RPPE and with no protection at a short distance (P<0.05 for both scenarios in all radiosensitive organs). The novel protective trolley provides a non-contact protective tool for radiographers against the hazard of scatter radiation during neonatal radiography examinations.

Genome-wide analysis of basic helix-loop-helix genes in Dendrobium catenatum and functional characterization of DcMYC2 in jasmonate-mediated immunity to Sclerotium delphinii.

Dendrobium catenatum, belonging to the Orchidaceae, is a precious Chinese herbal medicine. Sclerotium delphinii (P1) is a broad-spectrum fungal disease, which causes widespread loss in the near-wild cultivation of D. catenatum. Thus, resistance breeding of D. catenatum has become the key to solve this problem. The basic helix-loop-helix (bHLH) gene family is closely related to plant resistance to external stresses, but the related research in D. catenatum is not deep enough yet. Phylogenetic analysis showed that 108 DcbHLH genes could be divided into 23 subgroups. Promoter cis-acting elements revealed that DcbHLHs contain a large number of stress-related cis-acting elements. Transcriptome analysis of MeJA and P1 treatment manifested that exogenous MeJA can change the expression pattern of most bHLH genes, especially the IIIe subgroup, including inhibiting the expression of DcbHLH026 (MYC2a) and promoting the expression of DcbHLH027 (MYC2b). Subcellular localization indicated that they were located in the nucleus. Furthermore, exogenous MeJA treatment significantly delayed disease time and reduced lesion size after infection with P1. DcMYC2b-overexpression Arabidopsis lines showed significantly smaller lesions after being infected with P1 than the wild type, indicating that DcMYC2b functions as an important positive regulator in D. catenatum defense against P1. Our findings shed more insights into the critical role of the DcbHLH family in plants and the resistance breeding of D. catenatum.

Jasmonate Signaling Pathway Modulates Plant Defense, Growth, and Their Trade-Offs.

Lipid-derived jasmonates (JAs) play a crucial role in a variety of plant development and defense mechanisms. In recent years, significant progress has been made toward understanding the JA signaling pathway. In this review, we discuss JA biosynthesis, as well as its core signaling pathway, termination mechanisms, and the evolutionary origin of JA signaling. JA regulates not only plant regeneration, reproductive growth, and vegetative growth but also the responses of plants to stresses, including pathogen as well as virus infection, herbivore attack, and abiotic stresses. We also focus on the JA signaling pathway, considering its crosstalk with the gibberellin (GA), auxin, and phytochrome signaling pathways for mediation of the trade-offs between growth and defense. In summary, JA signals regulate multiple outputs of plant defense and growth and act to balance growth and defense in order to adapt to complex environments.

P2X7/P2X4 Receptors Mediate Proliferation and Migration of Retinal Microglia in Experimental Glaucoma in Mice.

Microglia are involved in the inflammatory response and retinal ganglion cell damage in glaucoma. Here, we investigated how microglia proliferate and migrate in a mouse model of chronic ocular hypertension (COH). In COH retinas, the microglial proliferation that occurred was inhibited by the P2X7 receptor (P2X7R) blocker BBG or P2X7R knockout, but not by the P2X4R blocker 5-BDBD. Treatment of primary cultured microglia with BzATP, a P2X7R agonist, mimicked the effects of cell proliferation and migration in COH retinas through the intracellular MEK/ERK signaling pathway. Transwell migration assays showed that the P2X4R agonist CTP induced microglial migration, which was completely blocked by 5-BDBD. In vivo and in vitro experiments demonstrated that ATP, released from activated Müller cells through connexin43 hemichannels, acted on P2X7R to induce microglial proliferation, and acted on P2X4R/P2X7R (mainly P2X4R) to induce microglial migration. Our results suggest that inhibiting the interaction of Müller cells and microglia may attenuate microglial proliferation and migration in glaucoma.

Interplay between Müller cells and microglia aggravates retinal inflammatory response in experimental glaucoma.

BACKGROUND: Glaucoma, the leading cause of irreversible blindness, is a retinal neurodegenerative disease, which results from progressive apoptotic death of retinal ganglion cells (RGCs). Although the mechanisms underlying RGC apoptosis in glaucoma are extremely complicated, an abnormal cross-talk between retinal glial cells and RGCs is generally thought to be involved. However, how interaction of Müller cells and microglia, two types of glial cells, contributes to RGC injury is largely unknown. METHODS: A mouse chronic ocular hypertension (COH) experimental glaucoma model was produced. Western blotting, immunofluorescence, quantitative real-time polymerase chain reaction (q-PCR), transwell co-culture of glial cells, flow cytometry assay, ELISA, Ca2+ image, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) techniques were employed to investigate the interaction of Müller cells and microglia, and its underlying mechanisms in COH retina. RESULTS: We first showed that Müller cell activation in mice with COH induced microglia activation through the ATP/P2X7 receptor pathway. The activation of microglia resulted in a significant increase in mRNA and protein levels of pro-inflammatory factors, such as tumor necrosis factor-α and interleukin-6. These inflammatory factors in turn caused the up-regulation of mRNA expression of pro-inflammatory factors in Müller cells through a positive feedback manner. CONCLUSIONS: These findings provide robust evidence, for the first time, that retinal inflammatory response may be aggravated by an interplay between activated two types of glial cells. These results also suggest that to reduce the interplay between Müller cells and microglia could be a potential effective strategy for preventing the loss of RGCs in glaucoma.

Collaborative Low-Rank Matrix Approximation-Assisted Fast Hyperspectral Raman Imaging and Tip-Enhanced Raman Spectroscopic Imaging.

Fast acquisition of Raman images is essential for accurately characterizing the analytes' information. In this paper, we developed a collaborative low-rank matrix approximation method for fast hyperspectral Raman imaging as well as tip-enhanced Raman spectroscopy (TERS) imaging. This method combines high signal-to-noise ratio (SNR) data with the target data to perform collaborative singular value decomposition. The high-quality reference data can impose constraints on factorization, which will force its components to approximate the true signal or noise components. The simulation demonstrated that this method offers state-of-the-art signal extraction performance and, thus, can be used to accelerate data acquisition. Specifically, the results indicate that the CLRMA can largely decrease the root-mean-square error by 20.92-54.12% compared with the baseline method of our previous study. We then applied this method to the fast TERS imaging of a Au/Pd bimetallic surface and significantly decreased the integration time down to 0.1 s/pixel, which is about 10 times faster than that of conventional experiments. High-SNR TERS spectra and clear TERS images that are well consistent with scanning tunneling microscopy (STM) images can be obtained even under such a weak signal condition. We further applied this method to the fast Raman imaging of HeLa cells and obtained clear Raman images at a short integration time of 2 s/line, which is about 5 times faster than that of conventional experiments. This method offers a promising tool for TERS imaging as well as conventional Raman imaging where fast data acquisition is required.

Role of competitive endogenous RNA networks in the pathogenesis of coronary artery disease.

BACKGROUND: The present study aimed to construct a network of competitive endogenous RNAs (ceRNAs) related to the pathogenesis of coronary artery disease (CAD), to provide a novel rationale for CAD treatment. METHODS: Bioinformatics methods were applied to screen for differentially expressed long non-coding RNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs) from the GSE68506, GSE59421, and GSE20129 datasets of the Gene Expression Omnibus (GEO) database. The miRcode database was used to predict lncRNA-binding miRNAs. The miRTarBase, miRDB, and TargetScan databases were used to predict the target genes of these miRNAs. An mRNA-miRNA-lncRNA ceRNA network of CAD was established. RESULTS: Between the CAD and normal control groups there were 264 DElncRNAs, 106 DEmiRNAs, and 1,879 DEmRNAs. We screened these differentially expressed gens (DEGs) respectively. There were 21 DElncRNAs, 13 DEmiRNAs, and 143 DEmRNAs in the ceRNA network by using Cytoscape application. The DEmRNAs were involved in the PI3K-Akt signaling pathway and the NF-κB signaling pathway. The key genes in the protein-protein interaction (PPI) network were HSP90AA1, CDKN1A, MCL1, MDM2, MAPK1, ABL1, LYN, CRK, CDK9, and FAS. CONCLUSIONS: The ceRNA network constructed in this study identified new candidate molecules for the treatment of CAD, providing some more comprehensive and higher-quality choices for the target treatment of CAD.

LncRNA BCAR4 expression predicts the clinical response to neoadjuvant chemotherapy in patients with locally advanced breast cancer.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is an important treatment for locally advanced breast cancer (LABC). However, there are no effective biomarkers to predict the efficacy. Therefore, there is an urgent need for new biomarkers to predict the response of LABC to NAC. LncRNA BCAR4 has been detected in a variety of malignant tumor tissues and used as a new biomarker for diagnosis and prognosis. However, LncRNA BCAR4 predicts the response of LABC to NAC is unclear. OBJECTIVE: Explore the predictive effect of LncRNA BCAR4 on the efficacy of NAC for LABC in three different evaluation systems. METHODS: First, the TCGA database was used to analyze the expression of LncRNA BCAR4 in 33 kinds of malignant tumors, and further explore its expression in breast cancer and its impact on the survival and prognosis of breast cancer. Furthermore, quantitative methods were used to measure the expression level of LncRNA BCAR4 in cancer tissues of 48 LABC patients, and the correlation between LncRNA BCAR4 and clinicopathological status and response to NAC under the evaluation system of 3, RECIST1.1, Miller-Payne (MP) score and whether it reaches pCR,was analyzed. RESULTS: TCGA data analysis found that LncRNA is highly expressed in a variety of malignant tumor tissues, including breast cancer. And relatively low expression, the shorter the overall survival time of high expression patients. The high expression of LncRNA BCAR4 is related to the size of the tumor, and there are differences in expression between stage I and other stages, but there is no obvious correlation with the positive lymph node and hormone receptor status. Among the three evaluation systems, only in the RECIST 1.1 evaluation system LncRNA BCAR4 has a predictive effect on NAC for LABC. The expression of LncRNA BCAR4 has no significant correlation with clinical stage, Ki-67% and hormone receptor status, and has no significant correlation with whether patients with locally advanced breast cancer obtain pCR during neoadjuvant chemotherapy. CONCLUSION: LncRNA BCAR4 is highly expressed in LABC tissues and may be an effective marker for predicting the efficacy of NAC for LABC.

Do medullary thyroid carcinoma patients with high calcitonin require bilateral neck lymph node clearance? A case report.

BACKGROUND: In clinical work, 85%-90% of malignant thyroid diseases are papillary thyroid cancer (PTC); thus, clinicians neglect other types of thyroid cancer, such as medullary thyroid carcinoma (MTC). CASE SUMMARY: We report a 53-year-old female patient with a preoperative calcitonin level of 345 pg/mL. There was no definitive diagnosis of MTC by preoperative fine-needle aspiration cytology or intraoperative frozen pathology, but the presence of PTC and MTC was confirmed by postoperative paraffin pathology. The patient underwent total thyroidectomy and bilateral central lymph node dissection. Close follow-up at 1.5 years after surgery revealed no signs of recurrence or metastasis. CONCLUSION: The issue in clinical work-up regarding types of thyroid cancer provides a novel and challenging idea for the surgical treatment of MTC. In the absence of central lymph node metastasis, it is worth addressing whether patients with high calcitonin can undergo total thyroidectomy and bilateral central lymph node dissection without bilateral lateral neck lymph node dissection.

Deep Learning for Biospectroscopy and Biospectral Imaging: State-of-the-Art and Perspectives.

With the advances in instrumentation and sampling techniques, there is an explosive growth of data from molecular and cellular samples. The call to extract more information from the large data sets has greatly challenged the conventional chemometrics method. Deep learning, which utilizes very large data sets for finding hidden features therein and for making accurate predictions for a wide range of applications, has been applied in an unbelievable pace in biospectroscopy and biospectral imaging in the recent 3 years. In this Feature, we first introduce the background and basic knowledge of deep learning. We then focus on the emerging applications of deep learning in the data preprocessing, feature detection, and modeling of the biological samples for spectral analysis and spectroscopic imaging. Finally, we highlight the challenges and limitations in deep learning and the outlook for future directions.

Tumor necrosis factor-alpha aggravates gliosis and inflammation of activated retinal Müller cells.

Tumor necrosis factor-alpha (TNF-α), a major inflammatory factor released from activated retinal glial cells, is implicated in the pathogenesis of glaucoma. In this study, we investigated whether and how TNF-α may affect functional conditions of activated retinal Müller cells. Our results showed that in the group I metabotropic glutamate receptor (mGluR I) agonist DHPG-activated cultured Müller cells, TNF-α treatment aggravated cell gliosis, as evidenced by significantly increased expression of glial fibrillary acidic protein (GFAP). TNF-α treatment of the DHPG-activated Müller cells decreased cell proliferation and induced cell apoptosis. In normal Müller cells, TNF-α treatment increased the mRNA levels of leukocyte inhibitory factor (LIF), intercellular cell adhesion molecule (ICAM), vascular cell adhesion molecule (VCAM), and chemokine C-C-motif ligand 2 (CCL2), which could be significantly attenuated when Müller cells were pre-activated. However, TNF-α-induced elevation in mRNA levels of inflammatory factors, such as TNF-α, inducible nitric oxide synthase (iNOS), and interleukin-6 (IL-6), in normal Müller cells still kept higher levels when Müller cells were pre-activated. Furthermore, the TNF-α-induced changes of cytokines were partially mediated by NF-κB signaling pathway. Our results suggest that TNF-α may promote gliosis and inflammatory response of activated Müller cells, thus aggravating RGC injury in glaucoma.

Development of Weak Signal Recognition and an Extraction Algorithm for Raman Imaging.

Improving time resolution of Raman imaging is essential for the observation of dynamic processes involved in interfacial catalysis and biological systems. The crucial step is how to recognize and extract weak Raman signals overwhelmed in the strong noise under the low signal-to-noise ratio (SNR) condition. Here, by exploring the relationship between the SNR of a single Raman spectrum and the structural similarity (SSIM; the key parameter evaluating the image quality) of the whole image, we determined a semiempirical threshold with SNR = 0 dB for clear imaging for the first time. Therefore, we proposed one signal processing algorithm for fast Raman imaging by reconstructing the Raman spectrum with the aid of weak signal processing: extracting the reliable Raman signal of the target under the low SNR and then determining the suitable scanning time to obtain the Raman image with a trustworthy image quality. In the first step, fast Fourier transform (FFT), least squares, and 2-D median filter are sequentially applied to improve the SNR of each raw Raman spectrum. In the second step, a local SNR evaluation strategy is developed to predict image quality as well as the determination of clear imaging. The proposed method was successfully applied to the fast imaging of the cell under the low SNR condition.

Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network.

Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the current Raman imaging methods to monitor the dynamic process of living cells. In this paper, we developed an artificial intelligence assisted fast Raman imaging method over the already fast line scan Raman imaging method. The reduced imaging time is realized by widening the slit and laser beam, and scanning the sample with a large scan step. The imaging quality is improved by a data-driven approach to train a deep convolutional neural network, which statistically learns to transform low-resolution images acquired at a high speed into high-resolution ones that previously were only possible with a low imaging speed. Accompanied with the improvement of the image resolution, the deteriorated spectral resolution as a consequence of a wide slit is also restored, thereby the fidelity of the spectral information is retained. The imaging time can be reduced to within 1 min, which is about five times faster than the state-of-the-art line scan Raman imaging techniques without sacrificing spectral and spatial resolution. We then demonstrated the reliability of the current method using fixed cells. We finally used the method to monitor the dynamic evolution process of living cells. Such an imaging speed opens a door to the label-free observation of cellular events with conventional Raman microscopy.