FRAX486, a PAK inhibitor, overcomes ABCB1-mediated multidrug resistance in breast cancer cells.

The overexpression of P-glycoprotein (P-gp/ABCB1) is a leading cause of multidrug resistance (MDR). Hence, it is crucial to discover effective pharmaceuticals that counteract ABCB1-mediated multidrug resistance. FRAX486 is a p21-activated kinase (PAK) inhibitor. The objective of this study was to investigate whether FRAX486 can reverse ABCB1-mediated multidrug resistance, while also exploring its mechanism of action. The CCK8 assay demonstrated that FRAX486 significantly reversed ABCB1-mediated multidrug resistance. Furthermore, western blotting and immunofluorescence experiments revealed that FRAX486 had no impact on expression level and intracellular localization of ABCB1. Notably, FRAX486 was found to enhance intracellular drug accumulation and reduce efflux, resulting in the reversal of multidrug resistance. Docking analysis also indicated a strong affinity between FRAX486 and ABCB1. This study highlights the ability of FRAX486 to reverse ABCB1-mediated multidrug resistance and provides valuable insights for its clinical application.

Index of consciousness monitoring during general anesthesia may effectively enhance rehabilitation in elderly patients undergoing laparoscopic urological surgery: a randomized controlled clinical trial.

BACKGROUND: Based on electroencephalogram (EEG) analysis, index of consciousness (IoC) monitoring is a new technique for monitoring anesthesia depth. IoC is divided into IoC1 (depth of sedation) and IoC2 (depth of analgesia). The potential for concurrent monitoring of IoC1 and IoC2 to expedite postoperative convalescence remains to be elucidated. We investigated whether combined monitoring of IoC1 and IoC2 can effectively enhances postoperative recovery compared with bispectral index (BIS) in elderly patients undergoing laparoscopic urological surgery under general anesthesia. METHODS: In this prospective, controlled, double-blinded trail, 120 patients aged 65 years or older were arbitrarily assigned to either the IoC group or the control group (BIS monitoring). All patients underwent blood gas analysis at T1 (before anesthesia induction) and T2 (the end of operation). The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were administered to all patients at T0 (1 day before surgery) and T4 (7 days after surgery). Serum concentrations of C-reactive protein (CRP) and glial fibrillary acid protein (GFAP) were assessed at T1, T2, and T3 (24 h after surgery). Postoperative complications and the duration of hospitalization were subjected to comparative evaluation. RESULTS: The incidence of postoperative cognitive dysfunction (POCD) was notably lower in the IoC group (10%) than in the control group (31.7%) (P = 0.003). Postoperative serum CRP and GFAP concentrations exhibited significant differences at time points T2 (CRP: P = 0.000; GFAP: P = 0.000) and T3 (CRP: P = 0.003; GFAP: P = 0.008). Postoperative blood glucose levels (P = 0.000) and the overall rate of complications (P = 0.037) were significantly lower in Group IoC than in Group control. CONCLUSION: The employment of IoC monitoring for the management of elderly surgical patients can accelerate postoperative convalescence by mitigating intraoperative stress and reducing peripheral and central inflammatory injury. TRIAL REGISTRATION: Chinese Clinical Trial Registry Identifier: ChiCTR1900025241 (17/08/2019).

Optimization and validation of voxel size-related radiomics variability by combatting batch effect harmonization in pulmonary nodules: a phantom and clinical study.

Background: Broad generalization of radiomics-assisted models may be impeded by concerns about variability. This study aimed to evaluate the merit of combatting batch effect (ComBat) harmonization in reducing the variability of voxel size-related radiomics in both phantom and clinical study in comparison with image resampling correction method. Methods: A pulmonary phantom with 22 different types of nodules was scanned by computed tomography (CT) with different voxel sizes. The variability of voxel size-related radiomics features was evaluated using concordance correlation coefficient (CCC), dynamic range (DR), and intraclass correlation coefficient (ICC). ComBat and image resampling compensation methods were used to reduce variability of voxel size-related radiomics. The percentage of robust radiomics features was compared before and after optimization. Pathologically differential diagnosis of invasive adenocarcinoma (IAC) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) (AIS-MIA group) was used for clinical validation in 134 patients. Results: Before optimization, the number of excellent features in the phantom and clinical data was 26.12% and 32.31%, respectively. The excellent features were increased after image resampling and ComBat correction. For clinical optimization, the effect of the ComBat compensation method was significantly better than that of image resampling, with excellent features reaching 90.96% and poor features only amounting to 4.96%. In addition, the hierarchical clustering analysis showed that the first-order and shape features had better robustness than did texture features. In clinical validation, the area under the curve (AUC) of the testing set was 0.865 after ComBat correction. Conclusions: The ComBat harmonization can optimize voxel size-related CT radiomics variability in pulmonary nodules more efficiently than image resampling harmonization.

Risk factors for postoperative acute ischemic stroke in advanced-aged patients with previous stroke undergoing noncardiac surgery: a retrospective cohort study.

BACKGROUND: The current study aimed to investigate the incidence and risk factors for postoperative acute ischemic stroke (PAIS) in advanced-aged patients (≥ 75 years) with previous ischemic stroke undergoing noncardiac surgery. METHODS: In this single-center retrospective cohort study, all advanced-aged patients underwent noncardiac surgery from 1 January, 2019, to 30 April, 2022. Data were extracted from hospital electronic medical records. Multivariable logistic regression analysis was performed to determine predictors of PAIS. Multivariable linear or logistic regression analysis was performed to determine predictors of outcomes due to PAIS. RESULTS: Twenty-four patients (6.0%) of the 400 patients developed PAIS. Carotid endarterectomy (CEA), length of surgery and preoperative Modified Rankin scale (mRS) ≥ 3 were significant predictors of PAIS. CEA was associated with increased risk of PAIS (OR 4.14; 95%CI, 1.43-11.99). Each additional minute in length of surgery had slightly increased the risk of PAIS (OR, 1.01; 95%CI, 1.00-1.01). Compared with reference (mRS < 3), mRS ≥ 3 increased odds of PAIS (OR, 4.09;95%CI, 1.12-14.93). Surgery type and length of surgery were found to be significant predictors of in-hospital expense (P < 0.001) and hospital stays (P < 0.05). CONCLUSIONS: CEA, length of surgery and preoperative mRS ≥ 3 may increase the development of PAIS in advanced-aged patients (≥ 75 years) with previous stroke undergoing noncardiac surgery. PAIS increased in-hospital mortality and prolonged hospital stay.

Pre-incisional Preventive Precise Multimodal Analgesia May Enhance the Rehabilitation Process of Acute Postoperative Pain Following Total Laparoscopic Hysterectomy: A Randomized Controlled Trial.

BACKGROUND: There has been limited research regarding the effect of preventive precise multimodal analgesia (PPMA) on the duration of acute postoperative pain after total laparoscopic hysterectomy (TLH). This randomized controlled trial aimed to evaluate how PPMA affects pain rehabilitation. OBJECTIVES: Our primary objective was to reduce the duration of acute postoperative pain after TLH, including incisional and visceral pain. STUDY DESIGN: A double blind randomized controlled clinical trial. SETTING: Department of Anesthesiology, Xuanwu Hospital, Capital Medical University, Beijing, People's Republic of China. METHODS: Seventy patients undergoing TLH were randomized to Group PPMA or Group Control (Group C) in a 1:1 ratio. Patients in Group PPMA were given PPMA through the pre-incisional administration of parecoxib sodium 40 mg (parecoxib is not approved for use in the US) and oxycodone 0.1 mg/kg as well as local anesthetic infiltration at the incision sites. In Group C, similar doses of parecoxib sodium and oxycodone were injected during uterine removal, and a local anesthetic infiltration procedure was performed immediately before skin closure. The index of consciousness 2 was utilized to titrate the remifentanil dosage in all patients to ensure sufficient analgesia. RESULTS: Compared with the Control, PPMA shortened the durations of incisional and visceral pain at rest (median, interquartile range [IQR]: 0, 0.0- 2.5) vs 2.0, 0.0-48.0 hours, P = 0.045; 24.0, 6.0-24.0 vs 48.0, 24.0-48.0 hours, P < 0.001; and during coughing 1.0, 0.0-3.0 vs 24.0, 0.3-48.0 hours, P = 0.001; 24.0, 24.0-48.0] vs 48.0, 48.0-72.0] hours, P < 0.001). The Visual Analog Scale (VAS) scores for incisional pain within 24 hours and visceral pain within 48 hours in Group PPMA were lower than those in Group C (P < 0.05). PPMA evidently decreased the VAS scores for incisional pain during coughing at 48 hours (P < 0.05). Pre-incisional PPMA significantly reduced postoperative opioid consumption (median, IQR: 3.0 [0.0-3.0] vs 3.0 [0.8-6.0] mg, P = 0.041) and the incidence of postoperative nausea and vomiting (25.0% vs 50.0%, P = 0.039). Postoperative recovery and hospital stay were similar between the 2 groups. LIMITATIONS: This research had some limitations, including that it was a single-center research with a limited sample size. Our study cohort did not represent the overall patient population in the People's Republic of China; therefore, the external validity of our findings remains limited. Furthermore, the prevalence of chronic pain was not tracked. CONCLUSION: Pre-incisional PPMA may enhance the rehabilitation process of acute postoperative pain after TLH.

Sensitivity and specificity of magnetic resonance imaging in routine diagnosis of pulmonary lesions: a comparison with computed tomography.

Background: State-of-the-art thoracic magnetic resonance imaging (MRI) plays a complementary role in the assessment of pulmonary nodules/masses which potentially indicate to cancer. We aimed to evaluate the sensitivity and specificity of MRI in diagnosis of pulmonary nodules/masses. Methods: Sixty-eight patients with computed tomography (CT)-detected pulmonary nodules/masses underwent 3T MRI (T1-VIBE, T1-starVIBE, T2-fBLADE turbo spin-echo, and T2-SPACE). The detection rate was calculated for each of the different subgroups of pulmonary nodules according to lung imaging reporting and data system (Lung-RADS). The four MRI sequences were compared in terms of detection rate and image quality-signal to noise ratio (SNR), contrast to noise ratio (CNR) and 5-point scoring scale. Agreement of lesion size measurement between CT and MRI was assessed by intraclass correlation coefficient (ICC). The picture-SNR, lesion-SNR and CNR of each sequence were analyzed by Mann-Whitney U test. Results: In total, 232 pulmonary lesions were detected by CT. The CT showed 86 solid nodules (SNs) <6 mm, 15 SNs between 6-8 mm, 35 SNs between 8-15 mm, and 52 SNs between 15-30 mm. The T1-VIBE, T1-starVIBE, T2-fBLADE TSE and T2-SPACE sequences accurately detected 141 SNs (141/188, 75%/83.3%), 150 SNs (150/188, 79.8%/100%), 166 SNs (166/188, 88.3%/66.7%) and 169 SNs (169/188, 89.9%/53.3%), respectively. Four ground glass nodules (GGNs) (4/6) were detected by T2-fBLADE TSE. Twelve part-solid nodules (PSNs) (12/22) were detected by T1-VIBE and 20 PSNs (20/22) by T2-SPACE. A total of 100 lesions (2.2±1.4 cm, 0.8-7.3 cm) were accurately detected and measured by the four MRI sequences with ICC >0.96. The picture-SNR, lesion-SNR and CNR by T1-starVIBE were higher than those by T1-VIBE (P<0.001). The lesion-SNR and CNR by T2-fBLADE TSE were higher than those by T2-SPACE (P=0.006, 0.038). 86% of images by T1-starVIBE, 92% by T2-fBLADE TSE, 90% by T2-SPACE and 93% by T1-VIBE were scored 3 or more. Conclusions: MRI achieves high sensitivity and specificity for different type of pulmonary nodules detection and is an effective alternative to CT as a diagnostic tool for pulmonary nodules.

Association of Chinese herbal medicine use with the depression risk among the long-term breast cancer survivors: A longitudinal follow-up study.

Background: Breast cancer patients are at elevated risk of depression during treatment, thus provoking the chance of poor clinical outcomes. This retrospective cohort study aimed to investigate whether integrating Chinese herbal medicines citation(CHM) into conventional cancer therapy could decrease the risk of depression in the long-term breast cancer survivors. Methods: A cohort of patients aged 20-70 years and with newly diagnosed breast cancer during 2000-2008 was identified from a nationwide claims database. In this study, we focused solely on survivors of breast cancer at least1 year after diagnosis. After one-to-one matching for age, sex, and baseline comorbidities, breast cancer patients who received (n = 1,450) and did not receive (n = 1,450) CHM treatment were enrolled. The incidence rate and hazard ratio citation(HR) for depression between the two groups was estimated at the end of 2012. A Cox proportional hazard model was constructed to examine the impact of the CHM use on the risk of depression. Results: During the study period, the incidence rate of depression was significantly lower in the treated cohort than in the untreated cohort [8.57 compared with 11.01 per 1,000 person-years citation(PYs)], and the adjusted HR remained significant at 0.74 (95% CI 0.58-0.94) in a Cox proportional hazards regression model. The corresponding risk further decreasing to 43% among those using CHM for more than 1 year. Conclusion: Finding from this investigation indicated that the lower risk of depression observed in breast cancer patients treated with CHM, suggesting that CHM treatment should be considered for disease management toward breast cancer. Yet, the optimal administered dose should be determined in further clinical trials.

Applying a CT texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images in pulmonary nodule diagnosis.

OBJECTIVE: To investigate the feasibility and accuracy of applying a computed tomography (CT) texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images for classifying pulmonary nodules. MATERIALS AND METHODS: CT images of 102 patients, with a total of 118 pulmonary nodules (52 benign, 66 malignant) were retrospectively reconstructed with a deep-learning reconstruction (artificial intelligence iterative reconstruction [AIIR]) and a hybrid iterative reconstruction (HIR) technique. The AIIR data were divided into a training (n = 96) and a validation set (n = 22), and the HIR data were set as the test set (n = 118). Extracted texture features were compared using the Mann-Whitney U test and t-test. The diagnostic performance of the classification model was analyzed with the receiver operating characteristic curve (ROC), the area under ROC (AUC), sensitivity, specificity, and accuracy. RESULTS: Among the obtained 68 texture features, 51 (75.0%) were not influenced by the change of reconstruction algorithm (p > 0.05). Forty-four features were significantly different between benign and malignant nodules (p < 0.05) for the AIIR dataset, which were selected to build the classification model. The accuracy and AUC of the classification model were 92.3% and 0.91 (95% confidence interval [CI], 0.74-0.90) with the validation set, which were 80.0% and 0.80 (95% CI, 0.68-0.86) with the test set. CONCLUSION: With the CT texture analysis model trained with deep-learning reconstruction (AIIR) images showing favorable diagnostic accuracy in discriminating benign and malignant pulmonary nodules, it also has certain applicability to the iterative reconstruction (HIR) images.

Modeling long-range dependencies for weakly supervised disease classification and localization on chest X-ray.

Background: Computer-aided diagnosis based on chest X-ray (CXR) is an exponentially growing field of research owing to the development of deep learning, especially convolutional neural networks (CNNs). However, due to the intrinsic locality of convolution operations, CNNs cannot model long-range dependencies. Although vision transformers (ViTs) have recently been proposed to alleviate this limitation, those trained on patches cannot learn any dependencies for inter-patch pixels and thus, are insufficient for medical image detection. To address this problem, in this paper, we propose a CXR detection method which integrates CNN with a ViT for modeling patch-wise and inter-patch dependencies. Methods: We experimented on the ChestX-ray14 dataset and followed the official training-test set split. Because the training data only had global annotations, the detection network was weakly supervised. A DenseNet with a feature pyramid structure was designed and integrated with an adaptive ViT to model inter-patch and patch-wise long-range dependencies and obtain fine-grained feature maps. We compared the performance using our method with that of other disease detection methods. Results: For disease classification, our method achieved the best result among all the disease detection methods, with a mean area under the curve (AUC) of 0.829. For lesion localization, our method achieved significantly higher intersection of the union (IoU) scores on the test images with bounding box annotations than did the other detection methods. The visualized results showed that our predictions were more accurate and detailed. Furthermore, evaluation of our method in an external validation dataset demonstrated its generalization ability. Conclusions: Our proposed method achieves the new state of the art for thoracic disease classification and weakly supervised localization. It has potential to assist in clinical decision-making.

PCDHB15 as a potential tumor suppressor and epigenetic biomarker for breast cancer.

Breast cancer is among the most frequently diagnosed cancer types and the leading cause of cancer-related death in women. The mortality rate of patients with breast cancer is currently increasing, perhaps due to a lack of early screening tools. In the present study, using The Cancer Genome Atlas (TCGA) breast cancer dataset (n=883), it was determined that methylation of the protocadherin ß15 (PCDHB15) promoter was higher in breast cancer samples than that in normal tissues. A negative association between promoter methylation and expression of PCDHB15 was observed in the TCGA dataset and breast cancer cell lines. In TCGA cohort, lower PCDHB15 expression was associated with shorter relapse-free survival times. Treatment with the DNA methyltransferase inhibitor restored PCDHB15 expression in a breast cancer cell line; however, overexpression of PCDHB15 was shown to suppress colony formation. PCDHB15 methylation detected in circulating cell-free DNA (cfDNA) isolated from serum samples was higher in patients with breast cancer (40.8%) compared with that in patients with benign tumors (22.4%). PCDHB15 methylation was not correlated with any clinical parameters. Taken together, PCDHB15 is a potential tumor suppressor in cases of breast cancer, which can be epigenetically silenced via promoter methylation. PCDHB15 methylation using cfDNA is a novel minimally invasive epigenetic biomarker for the diagnosis and prognosis of breast cancer.

Arbuscular mycorrhizal symbiosis enhances tomato lateral root formation by modulating CEP2 peptide expression.

Plant lateral root (LR) growth usually is stimulated by arbuscular mycorrhizal (AM) symbiosis. However, the molecular mechanism is still unclear. We used gene expression analysis, peptide treatment and virus-induced gene alteration assays to demonstrate that C-terminally encoded peptide (CEP2) expression in tomato was downregulated during AM symbiosis to mitigate its negative effect on LR formation through an auxin-related pathway. We showed that enhanced LR density and downregulated CEP2 expression were observed during mycorrhizal symbiosis. Synthetic CEP2 peptide treatment reduced LR density and impaired the expression of genes involved in indole-3-butyric acid (IBA, the precursor of IAA) to IAA conversion, auxin polar transport and the LR-related signaling pathway; however, application of IBA or synthetic auxin 1-naphthaleneacetic acid (NAA) to the roots may rescue both defective LR formation and reduced gene expression. CEP receptor 1 (CEPR1) might be the receptor of CEP2 because its knockdown plants did not respond to CEP2 treatment. Most importantly, the LR density of CEP2 overexpression or knockdown plants could not be further increased by AM inoculation, suggesting that CEP2 was critical for AM-induced LR formation. These results indicated that AM symbiosis may regulate root development by modulating CEP2, which affects the auxin-related pathway.

Radiomics nomogram analysis of T2-fBLADE-TSE in pulmonary nodules evaluation.

OBJECTIVES: To develop and validate a radiomics nomogram for differentiating between malignant pulmonary nodules and benign nodules. METHODS: 56 benign and 51 malignant nodules from 96 patients were analyzed using manual segmentation of the T2-fBLADE-TSE, while the nodules signal intensity (SIlesion), lesion muscle ratio (LMR) and nodule size were all measured and recorded. The maximum relevance and minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select nonzero coefficients and develop the model in pulmonary nodules diagnosis. The radiomics nomogram was also developed. The clinical prediction value was determined by the decision curve analysis (DCA). RESULTS: The nodule size, SIlesion and LMR of the benign group were 1.78 ± 0.57 cm, 227.50 ± 81.39 and 2.40 ± 1.27 respectively, in contrast to the 2.00 ± 0.64 cm, 232.87 ± 82.21 and 2.17 ± 0.91, respectively, in the malignant group (P = 0.09, 0.60 and 0.579). A total of 13 radiomics features were retained. The Rad-score of the benign nodules group was lower than that of the malignant nodules group (P < 0.001 & 0.049, training & test set). The AUC of radiomics signature for nodules diagnosis was 0.82 (95% CI, 0.73-0.91) in the training set and 0.71 (95% CI, 0.51-0.90) in the test set. A nomogram, consisting of 13 radiomics features and nodule size, produced good prediction in the training set (AUC, 0.82; 95% CI, 0.73-0.91), which was significantly better than that of T2-based quantitative parameters (AUC, 0.62; 95% CI, 0.50-0.75, P = 0.003). In the test set, the performance of radiomics nomogram (AUC, 0.70; 95% CI, 0.51-0.90) was also better than that of T2-based quantitative parameters (AUC, 0.46; 95% CI, 0.25-0.67) (P = 0.145). The DCA showed that radiomics nomogram and T2-based quantitative parameter had overall net benefits, while the performance of nomogram was better. CONCLUSION: We constructed and validated a T2-fBLADE-TSE-based radiomics nomogram that can help to differentiate between malignant pulmonary nodules and benign nodules.

Non-Heme-Iron-Mediated Selective Halogenation of Unactivated Carbon-Hydrogen Bonds.

Oxidation of the iron(II) precursor [(L1 )FeII Cl2 ], where L1 is a tetradentate bispidine, with soluble iodosylbenzene (s PhIO) leads to the extremely reactive ferryl oxidant [(L1 )(Cl)FeIV =O]+ with a cis disposition of the chlorido and oxido coligands, as observed in non-heme halogenase enzymes. Experimental data indicate that, with cyclohexane as substrate, there is selective formation of chlorocyclohexane, the halogenation being initiated by C-H abstraction and the result of a rebound of the ensuing radical to an iron-bound Cl- . The time-resolved formation of the halogenation product indicates that this primarily results from s PhIO oxidation of an initially formed oxido-bridged diiron(III) resting state. The high yield of up to >70 % (stoichiometric reaction) as well as the differing reactivities of free Fe2+ and Fe3+ in comparison with [(L1 )FeII Cl2 ] indicate a high complex stability of the bispidine-iron complexes. DFT analysis shows that, due to a large driving force and small triplet-quintet gap, [(L1 )(Cl)FeIV =O]+ is the most reactive small-molecule halogenase model, that the FeIII /radical rebound intermediate has a relatively long lifetime (as supported by experimentally observed cage escape), and that this intermediate has, as observed experimentally, a lower energy barrier to the halogenation than the hydroxylation product; this is shown to primarily be due to steric effects.

Management Based on Multimodal Brain Monitoring May Improve Functional Connectivity and Post-operative Neurocognition in Elderly Patients Undergoing Spinal Surgery.

Perioperative neurocognitive disorder (PND) is a common condition in elderly patients undergoing surgery. Sedation, analgesia, regional cerebral oxygen saturation (rSO2), and body temperature are known to be associated with PND, but few studies have examined the contribution of these factors combined in detail. This prospective, randomized, controlled, double-blinded study investigated whether anesthesia management based on multimodal brain monitoring-an anesthesia management algorithm designed by our group-could improve the post-operative cognitive function and brain functional connectivity (FC) in elderly patients undergoing elective spinal surgery with general anesthesia. The patients (aged ≥65 years) were randomized into two groups [control (Group C), n = 12 and intervention (Group I), n = 14]. Patients in Group I were managed with multimodal brain monitoring (patient state index, spectral edge frequency, analgesia nociception index, rSO2, and temperature), and those in Group C were managed with routine anesthesia management. All patients were pre- and post-operatively evaluated (7 days after surgery) with the Montreal Cognitive Assessment (MoCA). Amplitude of low-frequency fluctuation (ALFF) and FC were analyzed after resting-state functional MRI. Serum C-reactive protein (CRP) and lipopolysaccharide levels were measured, and the correlation between FC and changes in inflammatory marker levels was analyzed. Mean post-operative MoCA score was higher in Group I (24.80 ± 2.09) than in Group C (22.56 ± 2.24) (p = 0.04), with no difference in PND incidence between groups (28.57 vs. 16.67%; p = 0.47). Group I also showed significantly increased ALFF values in several brain regions after surgery (p < 0.05), and FC between the left hippocampus and left orbital inferior frontal gyrus (FG), left middle FG, left superior temporal gyrus, and left precentral gyrus was enhanced (p < 0.05), which was negatively correlated with the change in serum CRP (pre vs. post-intervention) (R = -0.58, p = 0.01). These results suggest that management of elderly patients undergoing surgery by multimodal brain monitoring may improve post-operative neurocognition and FC by reducing systemic inflammation. Clinical Trial Registration: http://www.chictr.org.cn/index.aspx, identifier: ChiCTR1900028024.

Elamipretide (SS-31) Improves Functional Connectivity in Hippocampus and Other Related Regions Following Prolonged Neuroinflammation Induced by Lipopolysaccharide in Aged Rats.

Neuroinflammation has been recognized as a major cause for neurocognitive diseases. Although the hippocampus has been considered an important region for cognitive dysfunction, the influence of hippocampal neuroinflammation on brain functional connectivity (FC) has been rarely studied. In this study, lipopolysaccharide (LPS) was used to induce systemic inflammation and neuroinflammation in the aged rat brain, while elamipretide (SS-31) was used for treatment. Systemic and hippocampal inflammation were determined using ELISA, while astrocyte responses during hippocampal neuroinflammation were determined by interleukin 1 beta (IL-1ß)/tumor necrosis factor alpha (TNFα) double staining immunofluorescence. Oxidative stress was determined by reactive oxidative species (ROS), electron transport chain (ETC) complex, and superoxide dismutase (SOD). Short- (<7 days) and long-term (>30 days) learning and spatial working memory were tested by the Morris water maze (MWM). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to analyze the brain FC by placing seed voxels on the left and right hippocampus. Compared with the vehicle group, rats with the LPS exposure showed an impaired MWM performance, higher oxidative stress, higher levels of inflammatory cytokines, and astrocyte activation in the hippocampus. The neuroimaging examination showed decreased FC on the right orbital cortex, right olfactory bulb, and left hippocampus on day 3, 7, and 31, respectively, after treatment. In contrast, rats with SS-31 treatment showed lower levels of inflammatory cytokines, less astrocyte activation in the hippocampus, and improved MWM performance. Neuroimaging examination showed increased FC on the left-parietal association cortex (L-PAC), left sensory cortex, and left motor cortex on day 7 with the right flocculonodular lobe on day 31 as compared with those without SS-31 treatment. Our study demonstrated that inhibiting neuroinflammation in the hippocampus not only reduces inflammatory responses in the hippocampus but also improves the brain FC in regions related to the hippocampus. Furthermore, early anti-inflammatory treatment with SS-31 has a long-lasting effect on reducing the impact of LPS-induced neuroinflammation.

A pilot study of native T1-mapping for focal pulmonary lesions in 3.0 T magnetic resonance imaging: size estimation and differential diagnosis.

BACKGROUND: To investigate the accuracy of size estimation and potential diagnosis efficacy of native T1-mapping in focal pulmonary lesion, compared to T1-star 3D-volumetric interpolated breath-hold sequence (VIBE), T2-fBLADE turbo-spin echo (TSE), and computed tomography (CT). METHODS: Thirty-nine patients with CT-detected focal pulmonary lesions underwent thoracic 3.0-T magnetic resonance imaging (MRI) using axial free-breathing 3D T1-star VIBE, respiratory triggered T2-fBLADE TSE, breath-hold T1-Turbo fast low angle shot (FLASH) and T1-FLASH 3D. Native T1-mapping images were generated by T1-FLASH 3D with B1-filed correction by T1-Turbo FLASH. The intraclass correlation coefficient (ICC) and Bland-Altman plots were used to evaluate intra-observer agreement and inter-method reliability of diameter measurements. Native T1-values were measured and compared among the malignancy, tuberculosis, non-tuberculosis benign groups using Mann-Whitney U tests. RESULTS: Forty-five focal pulmonary lesions were displayed by CT, native T1-mapping, T1-star VIBE, and T2-fBLADE TSE. T1-mapping-based diameter measurements yielded an intra-observer ICC of 0.995. Additionally, inter-method measurements were highly consistent (T1-mapping & T1-star VIBE: ICC 0.982, T1-mapping & T2-fBLADE TSE: ICC 0.978, T1-mapping & CT: ICC 0.972). For lesions <3.00 cm, T1-mapping intra-observer (ICC 0.982) and inter-method diameter measurements were also highly consistent (T1-mapping & CT: ICC 0.823). Native T1-values of malignant tumors were lower than those of the non-tuberculosis benign lesions (P=0.003). Native T1-values of tuberculosis were lower than those of the non-tuberculosis benign lesions (P=0.002). Native T1-values showed no statistically significant differences between malignant tumors and tuberculosis (P=0.059). CONCLUSIONS: Native T1-mapping enable accurate and reliable diameter measurement. Native T1-values potentially differentiate malignant tumors or tuberculosis from non-tuberculosis benign lesions.

Radiomics nomograms of tumors and peritumoral regions for the preoperative prediction of spread through air spaces in lung adenocarcinoma.

To evaluate the clinical features and radiomics nomograms of tumors and peritumoral regions for the preoperative prediction of the presence of spread through air spaces (STAS) in patients with lung adenocarcinoma. A total of 107 STAS-positive lung adenocarcinomas were selected and matched to 105 STAS-negative lung adenocarcinomas. Thin-slice CT imaging annotation and region of interest (ROI) segmentation were performed with semi-automatic in-house software. Radiomics features were extracted from all nodules and incremental distances of 5, 10, and 15 mm outside the lesion segmentation. A radiomics nomogram was established with multivariable logistic regression based on clinical and radiomics features. The maximum diameter of the solid component and mediastinal lymphadenectasis were selected as independent predictors of STAS. The radiomics nomogram of lung nodules showed especially good prediction in the training set [area under the curve (AUC), 0.98; 95% confidence interval (CI), 0.97-1.00] and test set (AUC, 0.99; 95% CI, 0.97-1.00). The radiomics nomogram of peritumoral regions also showed good prediction, but the fitting degrees of the calibration curves were not good. Our study may provide guidance for surgical methods in patients with lung adenocarcinoma.

10H-3,6-Diazaphenothiazines triggered the mitochondrial-dependent and cell death receptor-dependent apoptosis pathways and further increased the chemosensitivity of MCF-7 breast cancer cells via inhibition of AKT1 pathways.

Breast cancer is one of the leading causes of death in cancer categories, followed by lung, colorectal, and ovarian among the female gender across the world. 10H-3,6-diazaphenothiazine (PTZ) is a thiazine derivative compound that exhibits many pharmacological activities. Herein, we proceed to investigate the pharmacological activities of PTZ toward breast cancer MCF-7 cells as a representative in vitro breast cancer cell model. The PTZ exhibited a proliferation inhibition (IC50 = 0.895 µM) toward MCF-7 cells. Further, cell cycle analysis illustrated that the S-phase checkpoint was activated to achieve proliferation inhibition. In vitro cytotoxicity test on three normal cell lines (HEK293 normal kidney cells, MCF-10A normal breast cells, and H9C2 normal heart cells) demonstrated that PTZ was more potent toward cancer cells. Increase in the levels of reactive oxygen species results in polarization of mitochondrial membrane potential (ΔΨm), together with suppression of mitochondrial thioredoxin reductase enzymatic activity suggested that PTZ induced oxidative damages toward mitochondria and contributed to improved drug efficacy toward treatment. The RT2 PCR Profiler Array (human apoptosis pathways) proved that PTZ induced cell death via mitochondria-dependent and cell death receptor-dependent pathways, through a series of modulation of caspases, and the respective morphology of apoptosis was observed. Mechanistic studies of apoptosis suggested that PTZ inhibited AKT1 pathways resulting in enhanced drug efficacy despite it preventing invasion of cancer cells. These results showed the effectiveness of PTZ in initiation of apoptosis, programmed cell death, toward highly chemoresistant MCF-7 cells, thus suggesting its potential as a chemotherapeutic drug.

Combination of generative adversarial network and convolutional neural network for automatic subcentimeter pulmonary adenocarcinoma classification.

BACKGROUND: The efficient and accurate diagnosis of pulmonary adenocarcinoma before surgery is of considerable significance to clinicians. Although computed tomography (CT) examinations are widely used in practice, it is still challenging and time-consuming for radiologists to distinguish between different types of subcentimeter pulmonary nodules. Although there have been many deep learning algorithms proposed, their performance largely depends on vast amounts of data, which is difficult to collect in the medical imaging area. Therefore, we propose an automatic classification system for subcentimeter pulmonary adenocarcinoma, combining a convolutional neural network (CNN) and a generative adversarial network (GAN) to optimize clinical decision-making and to provide small dataset algorithm design ideas. METHODS: A total of 206 nodules with postoperative pathological labels were analyzed. Among them were 30 adenocarcinomas in situ (AISs), 119 minimally invasive adenocarcinomas (MIAs), and 57 invasive adenocarcinomas (IACs). Our system consisted of two parts, a GAN-based image synthesis, and a CNN classification. First, several popular existing GAN techniques were employed to augment the datasets, and comprehensive experiments were conducted to evaluate the quality of the GAN synthesis. Additionally, our classification system processes were based on two-dimensional (2D) nodule-centered CT patches without the need of manual labeling information. RESULTS: For GAN-based image synthesis, the visual Turing test showed that even radiologists could not tell the GAN-synthesized from the raw images (accuracy: primary radiologist 56%, senior radiologist 65%). For CNN classification, our progressive growing wGAN improved the performance of CNN most effectively (area under the curve =0.83). The experiments indicated that the proposed GAN augmentation method improved the classification accuracy by 23.5% (from 37.0% to 60.5%) and 7.3% (from 53.2% to 60.5%) in comparison with training methods using raw and common augmented images respectively. The performance of this combined GAN and CNN method (accuracy: 60.5%±2.6%) was comparable to the state-of-the-art methods, and our CNN was also more lightweight. CONCLUSIONS: The experiments revealed that GAN synthesis techniques could effectively alleviate the problem of insufficient data in medical imaging. The proposed GAN plus CNN framework can be generalized for use in building other computer-aided detection (CADx) algorithms and thus assist in diagnosis.