Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.

OBJECTIVE: To investigate the value of radiomics analysis of dual-layer spectral-detector computed tomography (DLSCT)-derived iodine maps for predicting tumor deposits (TDs) preoperatively in patients with colorectal cancer (CRC). MATERIALS AND METHODS: A total of 264 pathologically confirmed CRC patients (TDs + (n = 80); TDs - (n = 184)) who underwent preoperative DLSCT from two hospitals were retrospectively enrolled, and divided into training (n = 124), testing (n = 54), and external validation cohort (n = 86). Conventional CT features and iodine concentration (IC) were analyzed and measured. Radiomics features were derived from venous phase iodine maps from DLSCT. The least absolute shrinkage and selection operator (LASSO) was performed for feature selection. Finally, a support vector machine (SVM) algorithm was employed to develop clinical, radiomics, and combined models based on the most valuable clinical parameters and radiomics features. Area under receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis were used to evaluate the model's efficacy. RESULTS: The combined model incorporating the valuable clinical parameters and radiomics features demonstrated excellent performance in predicting TDs in CRC (AUCs of 0.926, 0.881, and 0.887 in the training, testing, and external validation cohorts, respectively), which outperformed the clinical model in the training cohort and external validation cohorts (AUC: 0.839 and 0.695; p: 0.003 and 0.014) and the radiomics model in two cohorts (AUC: 0.922 and 0.792; p: 0.014 and 0.035). CONCLUSION: Radiomics analysis of DLSCT-derived iodine maps showed excellent predictive efficiency for preoperatively diagnosing TDs in CRC, and could guide clinicians in making individualized treatment strategies. CLINICAL RELEVANCE STATEMENT: The radiomics model based on DLSCT iodine maps has the potential to aid in the accurate preoperative prediction of TDs in CRC patients, offering valuable guidance for clinical decision-making. KEY POINTS: Accurately predicting TDs in CRC patients preoperatively based on conventional CT features poses a challenge. The Radiomics model based on DLSCT iodine maps outperformed conventional CT in predicting TDs. The model combing DLSCT iodine maps radiomics features and conventional CT features performed excellently in predicting TDs.

The Value of Radiomics Features Based on HRCT in Predicting whether the Lung Sub-Centimeter Pure Ground Glass Nodule is Benign or Malignant.

OBJECTIVE: In this study, a radiomics model was created based on High-Resolution Computed Tomography (HRCT) images to noninvasively predict whether the sub-centimeter pure Ground Glass Nodule (pGGN) is benign or malignant. METHODS: A total of 235 patients (251 sub-centimeter pGGNs) who underwent preoperative HRCT scans and had postoperative pathology results were retrospectively evaluated. The nodules were randomized in a 7:3 ratio to the training (n=175) and the validation cohort (n=76). The volume of interest was delineated in the thin-slice lung window, from which 1316 radiomics features were extracted. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to select the radiomics features. Univariate and multivariable logistic regression were used to evaluate the independent risk variables. The performance was assessed by obtaining Receiver Operating Characteristic (ROC) curves for the clinical, radiomics, and combined models, and then the Decision Curve Analysis (DCA) assessed the clinical applicability of each model. RESULTS: Sex, volume, shape, and intensity mean were chosen by univariate analysis to establish the clinical model. Two radiomics features were retained by LASSO regression to build the radiomics model. In the training cohort, the Area Under the Curve (AUC) of the radiomics (AUC=0.844) and combined model (AUC=0.871) was higher than the clinical model (AUC=0.773). In evaluating whether or not the sub-centimeter pGGN is benign, the DCA demonstrated that the radiomics and combined model had a greater overall net benefit than the clinical model. CONCLUSION: The radiomics model may be useful in predicting the benign and malignant sub-centimeter pGGN before surgery.

Quantitative assessment of bone marrow infiltration and characterization of tumor burden using dual-layer spectral CT in patients with multiple myeloma.

BACKGROUND: The aim of the study was to evaluate whether virtual calcium subtraction (VNCa) image extracted from dual-layer spectral CT could estimate bone marrow (BM) infiltration with MRI as the reference standard and characterize tumor burden in patients with multiple myeloma (MM). PATIENTS AND METHODS: Forty-seven patients with newly diagnosed MM were retrospectively enrolled. They had undergone whole-body low-dose dual-layer spectral CT (DLCT) and whole-body MRI within one week. VNCa images with calcium-suppressed (CaSupp) indices ranging from 25 to 95 at an interval of 10 and apparent diffusion coefficient (ADC) maps were quantitatively analyzed on vertebral bodies L1-L5 at the central slice of images. The optimal combination was selected by correlation analysis between CT numbers and ADC values. Then, it was used to characterize tumor burden by correlation analysis and receiver operating characteristic (ROC) curves analysis, including plasma cell infiltration rate (PCIR), high serum-free light chains (SFLC) ratio and the high-risk cytogenetic (HRC) status. RESULTS: The most significant quantitative correlation between CT numbers of VNCa images and ADC values could be found at CaSupp index 85 for averaged L1-L5 (r = 0.612, p < 0.001). It allowed quantitative evaluation of PCIR (r = 0.835, p < 0.001). It could also anticipate high SFLC ratio and the HRC status with area under the curve (AUC) of 0.876 and 0.760, respectively. CONCLUSIONS: The VNCa measurements of averaged L1-L5 showed the highest correlation with ADC at CaSupp index 85. It could therefore be used as additional imaging biomarker for non-invasive assessment of tumor burden if ADC is not feasible.

Pharmacokinetics and Safety of Eptinezumab in Healthy Chinese Participants: A Randomized Clinical Trial.

BACKGROUND AND OBJECTIVE: Most evidence suggests that the pharmacokinetics of monoclonal antibodies (mAbs) are not meaningfully altered by patient characteristics, including racial/ethnic differences. Nevertheless, the pharmacokinetic profile of eptinezumab has not been evaluated in a Chinese population. This study was designed to confirm the hypothesis that the pharmacokinetic profile of the anti-calcitonin gene-related peptide mAb, eptinezumab, is similar in healthy Chinese individuals to that of healthy non-Asian individuals and non-Asian patients with migraine. METHODS: Over a study period of 12 weeks, healthy adult Chinese participants (N = 20) were randomized (1:1) to receive a single intravenous dose of eptinezumab 100 mg (n = 10) or 300 mg (n = 10) in a prospective, single-site, open-label parallel-group trial. Blood samples for the evaluation of plasma eptinezumab concentrations were obtained over 84 days, and standard pharmacokinetic parameters were derived. RESULTS: Mean maximum plasma concentrations (Cmax) of eptinezumab occurred 1.0-1.5 h post start of infusion, were similar between the 100 mg and 300 mg dose groups, and slowly declined in a biphasic manner. Cmax and area under the drug concentration-time curve (AUC) increased in a dose-proportional manner. Volume of distribution and clearance were similar between the 100 mg and 300 mg dose groups, and half-life was 22.5-28.1 days. Eptinezumab was generally well tolerated with no new safety signals identified. Only one participant, randomized to the 100 mg dose group, was positive for eptinezumab anti-drug antibodies, but negative for neutralizing antibodies, with no impact on pharmacokinetics. CONCLUSION: The pharmacokinetic profile of eptinezumab in healthy Chinese individuals was generally similar to that reported for non-Asian populations with migraine, and eptinezumab was generally well tolerated. Evaluation of immunogenicity showed no evidence of an impact of anti-drug antibodies or neutralizing antibodies on safety profiles. This supports the globally approved doses of 100 mg and 300 mg as being appropriate for Chinese patients with episodic migraine or chronic migraine.

Multiregional-based magnetic resonance imaging radiomics model for predicting tumor deposits in resectable rectal cancer.

PURPOSE: To establish and validate an integrated model incorporating multiregional magnetic resonance imaging (MRI) radiomics features and clinical factors to predict tumor deposits (TDs) preoperatively in resectable rectal cancer (RC). METHODS: This study retrospectively included 148 resectable RC patients [TDs+ (n = 45); TDs- (n = 103)] from August 2016 to August 2022, who were divided randomly into a testing cohort (n = 45) and a training cohort (n = 103). Radiomics features were extracted from the volume of interest on T2-weighted images (T2WI) and diffusion-weighted images (DWI) from pretreatment MRI. Model construction was performed after feature selection. Finally, five classification models were developed by support vector machine (SVM) algorithm to predict TDs in resectable RC using the selected clinical factor, single-regional radiomics features (extracted from primary tumor), and multiregional radiomics features (extracted from the primary tumor and mesorectal fat). Receiver-operating characteristic (ROC) curve analysis was employed to assess the discrimination performance of the five models. The AUCs of five models were compared by DeLon's test. RESULTS: The training and testing cohorts included 31 (30.1%) and 14 (31.1%) patients with TDs, respectively. The AUCs of multiregional radiomics, single-regional radiomics, and the clinical models for predicting TDs were 0.839, 0.765, and 0.793, respectively. An integrated model incorporating multiregional radiomics features and clinical factors showed good predictive performance for predicting TDs in resectable RC (AUC, 0.931; 95% CI, 0.841-0.988), which demonstrated superiority over clinical model (P = 0.016), the single-regional radiomics model (P = 0.042), and the multiregional radiomics model (P = 0.025). CONCLUSION: An integrated model combining multiregional MRI radiomic features and clinical factors can improve prediction performance for TDs and guide clinicians in implementing treatment plans individually for resectable RC patients.

Deep Learning for Dental Diagnosis: A Novel Approach to Furcation Involvement Detection on Periapical Radiographs.

Furcation defects pose a significant challenge in the diagnosis and treatment planning of periodontal diseases. The accurate detection of furcation involvements (FI) on periapical radiographs (PAs) is crucial for the success of periodontal therapy. This research proposes a deep learning-based approach to furcation defect detection using convolutional neural networks (CNN) with an accuracy rate of 95%. This research has undergone a rigorous review by the Institutional Review Board (IRB) and has received accreditation under number 202002030B0C505. A dataset of 300 periapical radiographs of teeth with and without FI were collected and preprocessed to enhance the quality of the images. The efficient and innovative image masking technique used in this research better enhances the contrast between FI symptoms and other areas. Moreover, this technology highlights the region of interest (ROI) for the subsequent CNN models training with a combination of transfer learning and fine-tuning techniques. The proposed segmentation algorithm demonstrates exceptional performance with an overall accuracy up to 94.97%, surpassing other conventional methods. Moreover, in comparison with existing CNN technology for identifying dental problems, this research proposes an improved adaptive threshold preprocessing technique that produces clearer distinctions between teeth and interdental molars. The proposed model achieves impressive results in detecting FI with identification rates ranging from 92.96% to a remarkable 94.97%. These findings suggest that our deep learning approach holds significant potential for improving the accuracy and efficiency of dental diagnosis. Such AI-assisted dental diagnosis has the potential to improve periodontal diagnosis, treatment planning, and patient outcomes. This research demonstrates the feasibility and effectiveness of using deep learning algorithms for furcation defect detection on periapical radiographs and highlights the potential for AI-assisted dental diagnosis. With the improvement of dental abnormality detection, earlier intervention could be enabled and could ultimately lead to improved patient outcomes.

Effect of post-rewarming fever after targeted temperature management in cardiac arrest patients: a systematic review and meta-analysis.

BACKGROUND: Targeted temperature management (TTM), as a therapeutic temperature control strategy for cardiac arrest (CA), is recommended by guidelines. However, the relationship between post-rewarming fever (PRF) and the prognosis of CA patients is unclear. Therefore, we aim to summarize the studies regarding the influence of PRF on patients with CA. METHODS: EMBASE, PubMed, and Cochrane Central databases were searched from inception to March 13, 2022. Randomized clinical trials (RCTs) and cohort studies on PRF in CA patients were included. According to the heterogeneity, the meta-analysis was performed using a random effects model or fixed effects model to calculate the pooled odds ratios (ORs) and corresponding 95% confidence intervals (CI s). The outcome data were unfavorable neurological outcome and mortality. RESULTS: The meta-analysis included 11 observational studies involving 3,246 patients. The results of the meta-analysis show that PRF (body temperature >38.0 °C) has no effect on the neurological outcome of CA patients (OR 0.71, 95% CI 0.43-1.17, I 2 82%) and has a significant relationship with lower mortality (OR 0.63; 95% CI 0.49-0.80, I 2 39%). However, PRF with a stricter definition (body temperature >38.5 °C ) was associated with worse neurological outcome (OR 1.44, 95% CI 1.08-1.92, I 2 45%) and higher mortality (OR 1.71, 95% CI 1.25-2.35, I 2 47%). CONCLUSION: This study suggests that PRF >38.0 °C may not affect the neurological outcome and have a lower mortality in CA patients who completed TTM. However, PRF >38.5 °C is a potential prognostic factor for worse outcomes in CA patients.

Home-based rehabilitation versus hospital-based rehabilitation for stroke patients in post-acute care stage: Comparison on the quality of life.

BACKGROUND: This study focused on the integrated post-acute care (PAC) stage of stroke patients, and employed a retrospective study to examine the satisfaction with life quality in two groups, one that received home-based rehabilitation and one that received hospital-based rehabilitation. A secondary purpose was to analyze the correlations among the index and components concerning their quality of life (QOL) and compare the advantages and disadvantages of these two approaches to PAC. METHODS: This research was a retrospective study of 112 post-acute stroke patients. The home-based group received rehabilitation for one to two weeks, and two to four sessions per week. The hospital-based group received the rehabilitation for three to six weeks, and 15 sessions per week. The home-based group mainly received the training and guidance of daily activities at the patients' residence. The hospital-based group mainly received physical facilitation and functional training in the hospital setting. RESULTS: The mean scores of QOL assessment for both groups were found to be significantly improved after intervention. Between-group comparisons showed that the hospital-based group had better improvement than the home-based group in mobility, self-care, pain/discomfort and depression/anxiety. In the home-based group, the MRS score and the participant's age can explain 39.4% of the variance of QOL scores. CONCLUSION: The home-based rehabilitation was of lower intensity and duration than the hospital-based one, but it still achieved a significant improvement in QOL for the PAC stroke patients. The hospital-based rehabilitation offered more time and treatment sessions. Therefore hospital-based patients responded with better QOL outcomes than the home-based patients.

Recent Progress and Perspective of an Evolving Carbon Family From 0D to 3D: Synthesis, Biomedical Applications, and Potential Challenges.

A variety of imaging techniques are available for detecting biological processes with sufficient penetration depth and temporal resolution. However, inflammation, cardiovascular, and cancer-related disorders might be difficult to diagnose with typical bioimaging methods because of the lack of resolution in the imaging of deep tissues. Therefore, nanomaterials are the most promising candidate to overcome this hurdle. This review is on the utilization of carbon-based nanomaterials (CNMs), ranging from zero-dimension (0D) to three-dimension (3D), in the development of fluorescence (FL) imaging, photoacoustic imaging (PAI), and biosensing for the early detection of cancer. Nanoengineered CNMs, such as graphene, carbon nanotubes (CNTs), and functional carbon quantum dots (QDs), are being further studied for multimodal biometrics and targeted therapy. CNMs have many advantages over conventional dyes in FL sensing and imaging, including clear emission spectra, long photostability, low cost, and high FL intensity. Nanoprobe production, mechanical illustrations, and diagnostic therapeutic applications are the key areas of focus. The bioimaging technique has facilitated a greater understanding of the biochemical events underlying multiple disease etiologies, consequently facilitating disease diagnosis, evaluation of therapeutic efficacy, and drug development. This review may lead to the development of interdisciplinary research in bioimaging and sensing as well as possible future concerns for researchers and medical physicians.

Safety and immunogenicity of a modified COVID-19 mRNA vaccine, SW-BIC-213, as a heterologous booster in healthy adults: an open-labeled, two-centered and multi-arm randomised, phase 1 trial.

BACKGROUND: We assessed the safety and immunogenicity of a core-shell structured lipopolyplex (LPP) based COVID-19 mRNA vaccine, SW-BIC-213, as a heterologous booster in healthy adults. METHODS: We conducted an open-labeled, two-centered, and three-arm randomised phase 1 trial. Healthy adults, who had completed a two-dose of inactivated COVID-19 vaccine for more than six months, were enrolled and randomized to receive a booster dose of COVILO (inactivated vaccine) (n = 20) or SW-BIC-213-25µg (n = 20), or SW-BIC-213-45µg (n = 20). The primary study endpoint was adverse events within 30 days post-boosting. The secondary endpoint was the titers of binding antibodies and neutralizing antibodies against the wild-type (WT) of SARS-CoV-2 as well as variants of concern in serum. The exploratory endpoint was the cellular immune responses. This trial was registered with http://www.chictr.org.cn (ChiCTR2200060355). FINDINGS: Between Jun 6 and Jun 22, 2022, 60 participants were enrolled and randomized to receive a booster dose of SW-BIC-213 (25 µg, n = 20, or 45 µg, n = 20) or COVILO (n = 20). The baseline demographic characteristics of the participants at enrollment were similar among the treatment groups. For the primary outcome, injection site pain and fever were more common in the SW-BIC-213 groups (25 µg and 45 µg). Grade 3 fever was reported in 25% (5/20) of participants in the SW-BIC-213-45µg group but was resolved within 48 h after onset. No fatal events or adverse events leading to study discontinuation were observed. For secondary and exploratory outcomes, SW-BIC-213 elicited higher and longer humoral and cellular immune responses than that in the COVILO group. INTERPRETATION: SW-BIC-213, a core-shell structured lipopolyplex (LPP) based mRNA vaccine, was safe, tolerable, and immunogenic as a heterologous booster in healthy Chinese adults. FUNDING: Shanghai Municipal Government, the Science and Technology and Economic Commission of Shanghai Pudong New Area, and mRNA Innovation and Translation Center of Shanghai.

Scutebarbatine A induces ROS-mediated DNA damage and apoptosis in breast cancer cells by modulating MAPK and EGFR/Akt signaling pathway.

Scutebarbatine A (SBT-A), a diterpenoid alkaloid, has exerted cytotoxicity on hepatocellular carcinoma cells in our previous works. Here, the antitumor activity of SBT-A in breast cancer cells and the underlying mechanism were explored. The anti-proliferative effect of SBT-A was measured by trypan blue staining, 5-ethynyl-2'-deoxyuridine (EdU) incorporation and colony formation assay. DNA double-strand breaks (DSBs) were evaluated by observing the nuclear focus formation of γ-H2AX. Cell cycle distribution was assessed by flow cytometry. Apoptosis was determined by a TUNEL assay. Intracellular reactive oxygen species (ROS) generation and superoxide production were measured with 2', 7'-dichlorofluorescein diacetate (DCFH-DA) and dihydroethidium (DHE) staining, respectively. The results indicated that SBT-A showed a dose-dependent cytotoxic effect against breast cancer cells while revealing less toxicity toward MCF-10A breast epithelial cells. Moreover, SBT-A remarkably induced DNA damage, cell cycle arrest and apoptosis in both MDA-MB-231 and MCF-7 cells. SBT-A treatment increased the levels of ROS and cytosolic superoxide production. Pretreatment with N-acetyl cysteine (NAC), a ROS scavenger, was sufficient to block viability reduction, DNA damage, apoptosis and endoplasmic reticulum (ER) stress caused by SBT-A. By exposure to SBT-A, the phosphorylation of c-Jun N-terminal kinase (JNK) and p38 mitogen-activated protein kinase (p38MAPK) was upregulated, while the phosphorylation of extracellular signal-regulated kinase (ERK) was downregulated. In addition, SBT-A inhibited the EGFR signaling pathway by decreasing EGFR expression and phosphorylation of Akt and p70S6K. As mentioned above, SBT-A has a potent inhibitory effect on breast cancer cells through induction of DNA damage, apoptosis and ER stress via ROS generation and modulation of MAPK and EGFR/Akt signaling pathway.

P T symmetry in a superconducting hybrid quantum system with longitudinal coupling.

We propose a scheme consisting of coupled nanomechanical cantilever resonators and superconducting flux qubits to engineer a parity-time- (P T-) symmetric phononic system formed by active and passive modes. The effective gain (loss) of the phonon mode is achieved by the longitudinal coupling of the resonator and the fast dissipative superconducting qubit with a blue-sideband driving (red-sideband driving). A P T-symmetric to broken-P T-symmetric phase transition can be observed in both balanced gain-to-loss and unbalanced gain-to-loss cases. Applying a resonant weak probe field to the dissipative resonator, we find that (i) for balanced gain and loss, the acoustic signal absorption to amplification can be tuned by changing the coupling strength between resonators; (ii) for unbalanced gain and loss, both acoustically induced transparency and anomalous dispersion can be observed around Δ = 0, where the maximum group delay is also located at this point. Our work provides an experimentally feasible scheme to design P T-symmetric phononic systems and a powerful platform for controllable acoustic signal transmission in a hybrid quantum system.

Radiomics-based intracranial thrombus features on preoperative noncontrast CT predicts successful recanalization of mechanical thrombectomy in acute ischemic stroke.

Background: To evaluate the predictive value of radiomics features extracted from the thrombus on preoperative computed tomography images to identify successful recanalization after stent retrieve (SR) treatment in patients with acute ischemic stroke (AIS). Methods: Two hundred fifty-six patients newly diagnosed AIS between March 2017 and September 2020 from two institutes, including the first affiliated hospital of Soochow university (institute I) and Northern Jiangsu People's hospital (institute II), were enrolled continuously and retrospectively. Patients with unsatisfactory image quality were excluded. The remaining patients of institute I were randomly divided into the training and internal validation cohorts at a ratio of 7 to 3, and patients of institute II were collected as the external validation cohort. After extraction and selection of the optimal radiomics features from training cohort, six machine learning (ML) classifiers including naïve Bayes (NB), random forest (RF), logistic regression (LR), linear support vector machine (L.SVM), radial SVM (R.SVM), and an artificial neural network (ANN) were developed to predict successful recanalization with SR treatment and compared. A combined model based on the optimal ML classifier was constructed using the optimal radiomics model and clinical-radiological risk variables. Finally, the performance of the model was selected based on the Matthews correlation coefficient (MCC) and the area under the receiver operating (AUC) and independently evaluated on the internal validation and external validation cohorts. Results: We automatically extracted 1,130 radiomics features from the voxel of interest (VOI) using PyRadiomics. The eight most relevant radiomics features were identified using Intraclass coefficient, single-factor logistic regression analysis, and least absolute shrinkage and selection operator algorithm in the training cohort. Among the six ML classifiers, the ANN classifier using thrombus radiomics features achieved the best prediction of early recanalization under SR with MCCs of 0.913, 0.693 and 0.505 in training, internal and external validation cohorts, respectively. Moreover, receiver operating characteristic curves showed that the combined model [AUC =0.860, 95% confidence interval (CI): 0.731-0.936; AUC =0.849, 95% CI: 0.759-0.831] was not significantly better than radiomics model based on the ANN classifier alone (AUC =0.873, 95% CI: 0.803-0.891; AUC =0.805, 95% CI: 0.864-0.971) (P>0.05, Delong test) in internal and external validation cohorts. Conclusions: A radiomics model based on the ANN classifier has the ability to predict successful recanalization after SR in patients with AIS, thus allowing a potentially better selection of mechanical thrombectomy treatment.

Identification and functional characterization of novel variants of MAPT and GRN in Chinese patients with frontotemporal dementia.

Frontotemporal dementia (FTD) is the second most common cause of dementia after Alzheimer's disease, characterized by distinct changes in behavior, personality, and language. Our study performed whole exome sequencing and repeat-primed PCR analysis in 29 unrelated FTD patients. Consequently, 2 known pathogenic variants (MAPT: p.P301L; TBK1: p.I450Kfs), and 4 novel variants (MAPT: p.R406Q, p.D430H, p.A330D; GRN: c.350-2A>G) were identified. The functional analysis results showed that phosphorylated tau levels were higher in cells expressing p.R406Q and p.D430H tau than those expressing wild-type tau, especially at the Thr205, Thr231, and Ser396 phosphorylation epitopes. Besides, the p.R406Q and p.D430H variants of MAPT impaired the ability of tau to bind to the microtubules and increased tau self-aggregation. Furthermore, we found that the c.350-2A>G variant caused exon 5 skipping. Our results showed that p.R406Q, p.D430H, and c.350-2A>G variants were classified as pathogenic. Finally, we summarized the clinical characterization of patients carrying pathogenic variants of MAPT in the East Asia populations. Our results broaden the genetic spectrum of FTD with MAPT and GRN variants.

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To assess the dynamics and spectral characteristics of dissolved organic matter of twig litter in continuous increase stage, peak stage, and continuous decrease stage of twig litter production in different types of Castanopsis carlesii forest in middle subtropical China, a field experiment was conducted in C. carlesii natural forest, secondary forest and plantation. The results showed that litter production stage and forest type significantly affected the content and spectral characteristics of dissolved organic matter of twig litter were . Compared with the secondary forest and plantation, natural forest had higher dissolved organic carbon (DOC) content and lower special ultraviolet-visible absorption values at 254, 260 and 280 nm (SUVA254, SUVA260, SUVA280) at the continuous decrease stage of twig litter production, indicating high twig litter quality of natural forest and high cycling efficiency with dissolved organic matter in the natural forest at this stage. In contrast, the higher contents of total nitrogen (TN), total phosphorus (TP), total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), and lower DOC:TDP and TDN:TDP ratios of twig litter in the plantation were observed at the peak stage of twig litter production, while no differences were detected in dissolved organic matter contents and spectral values in the secondary forest among the stages. In addition, the DOC, TDN, TDP of twig litter were negatively correlated with temperature and precipitation in the natural forests and secondary forests, but TDN and TDP of twig litter were positively correlated with temperature and precipitation in the plantations. These results suggested that the higher nutrient content at the peak stage of twig litter production in the C. carlesii plantation might lead to more efficient material cycling and that there would be a higher efficiency of material cycling for twig litter dissolved organic matter in C. carlesii natural forest at reduction stage of twig litter production.

Licochalcone B induces DNA damage, cell cycle arrest, apoptosis, and enhances TRAIL sensitivity in hepatocellular carcinoma cells.

Hepatocellular carcinoma (HCC) is a highly fatal disease recognized as a growing global health crisis. Traditional Chinese herbal medicines have been used to treat patients with cancer for many years in China. This study investigated the effects of licochalcone B (LCB), a flavonoid compound isolated from the root of Glycyrrhiza uralensis Fisch., on cell proliferation, DNA damage and TNF-related apoptosis-inducing ligand (TRAIL)-mediated apoptosis in HCC cells. Our results showed that LCB inhibited cell proliferation and induced DNA damage, cell cycle arrest and apoptosis. Treatment with LCB significantly inhibited the Akt/mTOR pathway and activated endoplasmic reticulum (ER) stress and mitogen-activated protein kinase (MAPK) signaling pathway. Moreover, combined treatment with LCB and TRAIL yielded evident enhancements in the viability reduction and apoptosis. LCB upregulated death receptor 4 (DR4) and death receptor 5 (DR5) protein in a concentration- and time-dependent manner. The knockdown of DR5 significantly suppressed TRAIL-induced cleavage of PARP, which was enhanced by LCB. Treatment with an extracellular-regulated kinase (ERK) inhibitor (PD98059) or c-Jun N-terminal kinase (JNK) inhibitor (SP600125) markedly reduced the LCB-induced upregulation of DR5 expression and attenuated LCB-mediated TRAIL sensitization. In summary, LCB exhibits cytotoxic activity through modulation of the Akt/mTOR, ER stress and MAPK pathways in HCC cells and effectively enhances TRAIL sensitivity through the upregulation of DR5 expression in ERK- and JNK-dependent manner. Combination therapy with LCB and TRAIL may be an alternative treatment strategy for HCC.

Development and assessment of deep learning system for the location and classification of rib fractures via computed tomography.

PURPOSE: The purpose of this study was to evaluate the performance of a deep learning system for the automatic diagnosis and classification of rib fractures. METHODS: This retrospective study analyzed computed tomography (CT) data of patients diagnosed with a rib fracture between 1 January 2019 and 23 July 2020 in two hospitals, including 591 patients from Suzhou TCM hospital and 75 patients from Jintan TCM hospital. A deep learning system (Dr.Wise@ChestFracture v1.0) based on a convolutional neural network framework was used as a diagnostic tool, and a human-model comparison experiment was designed to compare the diagnostic efficiencies of the deep learning system and radiologists. Furthermore, a secondary classification model was established to distinguish the different types of fracture. First, a classification model to differentiate between fresh and old fractures was developed. Second, a submodel to determine any misalignment in fresh fractures was established. RESULTS: For all fracture types, the detection efficiency (recall) of the system was statistically significantly better than that of radiologists with different levels of experience (all p < 0.0167 except for senior radiologists). The F1-score of the system for diagnosing rib fractures was similar to that of the radiologists. The system was much faster than the radiologists in assessing rib fractures (all p < 0.0167). The two classification models can distinguish between fresh and old fractures (accuracy = 87.63%) and determine whether there is any misalignment in fresh fractures (accuracy = 95.22%) or not. CONCLUSION: The use of a deep learning system can accurately, automatically, and rapidly diagnose and classify rib fractures, helping doctors improve the diagnostic efficiency and reducing their workload. The classification models can distinguish different types of rib fracture well.

Survival Benefit from Surgical Resection in Lung Cancer Patients with Brain Metastases: a Single-Center, Propensity-Matched Analysis Cohort Study.

BACKGROUND: Brain metastases (BMs) are the most serious complication of lung cancer, affecting the prognosis of lung cancer patients, and pose distinct clinical challenges. This study was designed to explore the prognostic factors related to lung cancer BM and the value of surgical resection in BMs from lung cancer. METHODS: A retrospective analysis was performed on 714 patients with lung cancer BMs screened between January 2010 and January 2018 at the Sun Yat-sen University Cancer Center. A 1:1 propensity score matching analysis was performed to reduce the potential bias between the surgery and the nonsurgery group. In both the raw and the propensity-score matched dataset, univariate and multivariate Cox proportional hazards regression analyses were used to evaluate risk factors for survival. RESULTS: After matching, 258 patients (129 surgery, 129 no surgery) were analyzed. Multivariate analyses after propensity score matching demonstrated that surgical resection was an independent protective factor for overall survival (OS), and older age, lower Karnofsky Performance Scale (KPS) score, and extracranial metastases were independent risk factors for worse OS. Patients without extracranial metastases, without synchronous BM and with a single BM had a better prognosis. CONCLUSIONS: The findings showed that surgical resection, age, KPS score, and extracranial metastases are independent prognostic factors for predicting the OS of patients with lung cancer BMs, and surgical resection for brain metastatic lesions could significantly improve the OS. However, only certain groups of patients with BMs can benefit from intracranial lesion resection, such as no extracranial metastases and metachronous metastases.

The role of shear wave elastography in the assessment of placentas in healthy pregnancy women during third-trimester: A preliminary study.

OBJECTIVE: The study aimed to analysis the elasticity value of placenta in healthy women during third trimester by shear wave elastography (SWE), and tried to investigate the relationship between clinical characteristics and placental elasticity. METHODS: Singleton healthy pregnant women who had routine ultrasound examination between 28 and 37 weeks were enrolled. SWE of the frontier placentas were evaluated by transabdominal ultrasound elastography. Only placentas at front wall were enrolled. The placenta was divided into three areas for SWE examination: the central area (Area A), the periphery area (Area B) and the area between central and edge of placenta (Area C). Then, the subjects with normal delivery were evaluated and analyze the relationship between clinical features and placental elasticity. RESULTS: A total of 43 pregnant women were included in this study. The mean value of SWE in the central area was 5.67±2.51 kPa. And it was 6.50±2.57 kPa in the periphery area, 5.17±2.25 kPa in the area C. There were no significant differences except area B and C. In different age group, there were no significant differences except area C. The history of childbearing and uterine operation and the gestational age were no significant correlation with the SWE value of placenta. There were also no significant differences between birth weight percentile and placental elasticity. CONCLUSION: The placental elasticity is stable in healthy women during third trimester. Shear wave elastography is helpful to assess the placental elasticity and can be used as a supplemental technique to existing methods for monitoring the placental function. But the normal elasticity range in some certain areas of placenta should be confirmed by further study.