Deep learning model based on contrast-enhanced MRI for predicting post-surgical survival in patients with hepatocellular carcinoma.

Objective: To develop a deep learning model based on contrast-enhanced magnetic resonance imaging (MRI) data to predict post-surgical overall survival (OS) in patients with hepatocellular carcinoma (HCC). Methods: This bi-center retrospective study included 564 surgically resected patients with HCC and divided them into training (326), testing (143), and external validation (95) cohorts. This study used a three-dimensional convolutional neural network (3D-CNN) ResNet to learn features from the pretreatment MR images (T1WIpre, late arterial phase, and portal venous phase) and got the deep learning score (DL score). Three cox regression models were established separately using the DL score (3D-CNN model), clinical features (clinical model), and a combination of above (combined model). The concordance index (C-index) was used to evaluate model performance. Results: We trained a 3D-CNN model to get DL score from samples. The C-index of the 3D-CNN model in predicting 5-year OS for the training, testing, and external validation cohorts were 0.746, 0.714, and 0.698, respectively, and were higher than those of the clinical model, which were 0.675, 0.674, and 0.631, respectively (P = 0.009, P = 0.204, and P = 0.092, respectively). The C-index of the combined model for testing and external validation cohorts was 0.750 and 0.723, respectively, significantly higher than the clinical model (P = 0.017, P = 0.016) and the 3D-CNN model (P = 0.029, P = 0.036). Conclusions: The combined model integrating the DL score and clinical factors showed a higher predictive value than the clinical and 3D-CNN models and may be more useful in guiding clinical treatment decisions to improve the prognosis of patients with HCC.

Efficacy and Safety of Pulse Magnetic Therapy System in Insomnia Disorder: A Multicenter, Randomized, Double-Blind, Placebo-Controlled Trial.

OBJECTIVE: This study's objective is to assess the efficacy and safety of Pulsed Magnetic Therapy System (PMTS) in improving insomnia disorder. METHODS: Participants with insomnia disorder were randomly assigned to receive either PMTS or sham treatment for four weeks (n= 153; PMTS: 76, sham: 77). Primary outcomes are the Insomnia Severity Index (ISI) scores at week 0 (baseline), 1, 2, 3, 4 (treatment), and 5 (follow-up). Secondary outcomes are the Pittsburgh Sleep Quality Index at baseline and week 4, and weekly sleep diary-derived values for sleep latency, sleep efficiency, real sleep time, waking after sleep onset, and sleep duration. RESULTS: The ISI scores of the PMTS group and the sham group were 7.13±0.50, 11.07±0.51 at week 4, respectively. There was a significant group×time interaction for ISI (F3.214, 485.271=24.25, p<0.001, ηp 2=0.138). Only the PMTS group experienced continuous improvement throughout the study; in contrast, the sham group only experienced a modest improvement after the first week of therapy. At the end of the treatment and one week after it, the response of the PMTS group were 69.7% (95% confidence interval [CI]: 58.6%-79.0%), 75.0% (95% CI: 64.1%-83.4%), respectively, which were higher than the response of the sham group (p<0.001). For each of the secondary outcomes, similar group×time interactions were discovered. The effects of the treatment persisted for at least a week. CONCLUSION: PMTS is safe and effective in improving insomnia disorders.

Differentiating Peripherally Located Pulmonary Noncalcified Hamartoma From Carcinoid Using CT Radiomics Approaches.

OBJECTIVE: This article aimed to differentiate noncalcified hamartoma from pulmonary carcinoid preoperatively using computed tomography (CT) radiomics approaches. MATERIALS AND METHODS: The unenhanced CT (UECT) and contrast-enhanced CT (CECT) data of noncalcified hamartoma (n = 73) and pulmonary carcinoid (n = 54; typical/atypical carcinoid = 13/41) were retrospectively analyzed. The patients were randomly divided into the training and validation sets. A total of 396 radiomics features were extracted from UECT and CECT, respectively. The features were selected by using the minimum redundancy maximum relevance and the least absolute shrinkage and selection operator to construct a radiomics model. Clinical factors and radiomics features were integrated to build a nomogram model. The performance of clinical factors, radiomics, and nomogram models on the differential diagnosis between noncalcified hamartoma and carcinoid were investigated. Diagnostic performance of radiologists was also explored. RESULT: In regard to distinguishing noncalcified hamartoma from carcinoid, the areas under the receiver operating characteristic curves of the clinical, radiomics, and nomogram models were 0.88, 0.94, and 0.96 in the training set UECT, and were 0.85, 0.92, and 0.96 in the training set CECT, respectively. The areas under the curve of the 3 models were 0.89, 0.96, and 0.96 in the validation set UECT, and were 0.79, 0.90, and 0.94 in the validation set CECT, respectively. The nomogram model exhibited good calibration and was clinically useful by decision curve analysis. Nomogram did not show significant improvement compared with radiomics, neither for UECT nor for CECT. Diagnostic performance of radiologists was lower than both radiomics and nomogram model. CONCLUSIONS: Radiomics approaches may be useful in distinguishing peripheral pulmonary noncalcified hamartoma from carcinoid. Radiomics features extracted from CECT provided no significant benefit when compared with UECT.

Impairment of GABA inhibition in insomnia disorders: Evidence from the peripheral blood system.

Aim: To explore the change characteristics and related factors of various indexes of GABAergic system in peripheral blood of patients with insomnia disorder. Methods: In this study, a total of 30 patients who met the DSM-5 diagnostic criteria for insomnia disorder and 30 normal controls were included. All subjects had a structured clinical interview with the Brief International Neuropsychiatric Disorder Interview, and PSQI was used to evaluate the sleep status of the subjects. Enzyme-linked immunosorbent assay (ELISA) was used to detect serum γ-aminobutyric acid (GABA), and RT-PCR was used to detect GABAA receptor α1 and α2 subunit mRNA. All data were statistically analyzed using SPSS 23.0. Results: Compared with the normal control group, the mRNA levels of GABAA receptor α1 and α2 subunits in the insomnia disorder group were significantly lower, but there was no significant difference in the serum GABA levels between the two groups. And in the insomnia disorder group, there was no significant correlation between the GABA levels and the mRNA expression levels of α1 and α2 subunits of GABAA receptors. Although no significant correlation was found between PSQI and serum levels of these two subunit mRNAs, its component factors sleep quality and sleep time were negatively correlated with GABAA receptor α1 subunit mRNA levels, and daytime function was inversely correlated with GABAA receptor α2 subunit mRNA levels. Conclusion: The inhibitory function of serum GABA in patients with insomnia may be impaired, and the decreased expression levels of GABAA receptor α1 and α2 subunit mRNA may become a reliable indicator of insomnia disorder.

Can CT Radiomics Detect Acquired T790M Mutation and Predict Prognosis in Advanced Lung Adenocarcinoma With Progression After First- or Second-Generation EGFR TKIs?

Objective: To explore the potential of CT radiomics in detecting acquired T790M mutation and predicting prognosis in patients with advanced lung adenocarcinoma with progression after first- or second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) therapy. Materials and Methods: Contrast-enhanced thoracic CT was collected from 250 lung adenocarcinoma patients (with acquired T790M mutation, n = 146, without mutation, n = 104) after progression on first- or second-generation TKIs. Radiomic features were extracted from each volume of interest. The maximum relevance minimum redundancy and the least absolute shrinkage and selection operator (LASSO) regression method were used to select the optimized features in detecting acquired T790M mutation. Univariate Cox regression and LASSO Cox regression were used to establish the radiomics model to predict the progression-free survival of osimertinib treatment. Finally, nomograms (which) combined clinical factors with radscore to predict the acquired T790M mutation and prognosis were built separately. In addition, the two nomograms were validated by the concordance index (C-index), decision curve analysis (DCA), and calibration curve analysis where appropriate. Results: Clinical factors including the progression-free survival of first-line EGFR TKIs, EGFR mutation, and N stage and 12 radiomic features were useful in predicting the acquired T790M mutation. The area under the receiver operating characteristic curves (AUC) of clinical, radiomics, and nomogram models were 0.70, 0.74, and 0.78 in the training set and 0.71, 0.71, and 0.76 in the validation set, respectively. The DCA and calibration curve analysis demonstrated a good performance of the nomogram model. Clinical factors including age and first-generation EGFR TKIs and 12 radiomic features were useful in patients' outcome prediction. The C-index of the combined nomogram was 0.686 in the training set and 0.630 in the validation set, respectively. Calibration curves demonstrated a relatively poor performance of the nomogram model. Conclusion: Nomogram combined clinical factors with radiomic features might be helpful to detect whether patients developed acquired T790M mutation or not after progression on first- or second-generation EGFR TKIs. Nomogram prognostic model combined clinical factors with radiomic features might have a limited value in predicting the survival of patients harboring acquired T790M mutation treated with osimertinib.

Nomograms for Predicting Hepatocellular Carcinoma Recurrence and Overall Postoperative Patient Survival.

Background: Few studies have focused on the prognosis of patients with hepatocellular carcinoma (HCC) of Barcelona Clinic Liver Cancer (BCLC) stage 0‒C in terms of early recurrence and 5-years overall survival (OS). We sought to develop nomograms for predicting 5-year OS and early recurrence after curative resection of HCC, based on a clinicopathological‒radiological model. We also investigated whether different treatment methods influenced the OS of patients with early recurrence. Methods: Retrospective data, including clinical pathology, radiology, and follow-up data, were collected for 494 patients with HCC who underwent hepatectomy. Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. OS curves of different treatments for patients who had recurrence within 2 years after curative surgery were depicted and compared using the Kaplan-Meier method and the log-rank test. Results: Multivariate Cox regression revealed that BCLC stage, non-smooth margin, maximum tumor diameter, age, aspartate aminotransferase levels, microvascular invasion, and differentiation were prognostic factors for OS and were incorporated into the nomogram with good predictive performance in the training (C-index: 0.787) and testing cohorts (C-index: 0.711). A nomogram for recurrence-free survival was also developed based on four prognostic factors (BCLC stage, non-smooth margin, maximum tumor diameter, and microvascular invasion) with good predictive performance in the training (C-index: 0.717) and testing cohorts (C-index: 0.701). In comparison to the BCLC staging system, the C-index (training cohort: 0.787 vs. 0.678, 0.717 vs. 0.675; external cohort 2: 0.748 vs. 0.624, 0.729 vs. 0.587 respectively, for OS and RFS; external cohort1:0.716 vs. 0.627 for RFS, all p value<0.05), and model calibration curves all showed improved performance. Patients who underwent surgery after tumor recurrence had a higher reOS than those who underwent comprehensive treatments and supportive care. Conclusions: The nomogram, based on clinical, pathological, and radiological factors, demonstrated good accuracy in estimating OS and recurrence, which can guide follow-up and treatment of individual patients. Reoperation may be the best option for patients with recurrence in good condition.

The mRNA expression levels of GABAA receptor α1 and α2 subunits in patients with major depressive disorder during onset and remission.

OBJECTIVE: We aimed to investigate the expression levels of GABA and GABAA receptor α1 and α2 subunits in patients with major depressive disorder (MDD) during onset and remission. MATERIALS AND METHODS: 48 patients with MDD during onset and 45 patients with MDD during remission who were treated in our university were selected. Moreover, the control group included 46 healthy volunteers recruited in the community. The depression and anxiety symptoms were assessed by Hamilton Depression (HAMD) Scale and Hamilton Anxiety (HAMA) Scale. ELISA was used to determine the serum GABA levels. The mRNA expression of GABAA receptor α1 and α2 subunits in peripheral blood were detected by RT-PCR. RESULTS: The expression levels of serum GABA and of GABAA receptor α1 and α2 subunits in MDD depression attack group were notably decreased in comparison with those in MDD remission group and control group ((4.10 ± 0.73) v.s. (5.91 ± 1.25) and (5.83 ± 1.17) umol/L, F = 5.61, p < 0.001; (0.53 ± 0.32) v.s. (0.91 ± 0.18) and (0.93 ± 0.21), F = 8.37, p < 0.001; (1.45 ± 0.86) v.s. (2.33 ± 1.49) and (2.28 ± 1.50), F = 8.23, p < 0.001). However, there were no marked difference in the levels of these three indices between the MDD remission group and the control group (p > 0.05). Serum GABA levels were negatively correlated with HAMA total score (r = -0.34, p = 0.02), HAMD total score (r = -0.46, p = 0.01) and depression core symptom score (r = -0.32, p = 0.03). CONCLUSIONS: During the onset of MDD, there may be GABA neuronal dysfunction and abnormal expression of GABAA receptor subunits, and those changes showed a state change, which gradually returned to normal during remission.

Oreocharisqianyuensis, a new species of Gesneriaceae from Southwest, China based on morphological and molecular evidence.

Oreocharisqianyuensis, a new species of Gesneriaceae from Southwest, China, is described and illustrated based on morphological comparisons and molecular phylogenetic analyses. Phylotranscriptomic analyses of the new species in the context of a comprehensive phylogeny with dense sampling of 88% (111/126) of all species of the genus indicated that the new species was most closely-related to O.fargesii. The new species is morphologically similar to O.fargesii and O.nanchuanica in the shape, color and structure of flowers and the number of stamens, but differs in the leaf blade shape, margin and the indumentum characters of the inflorescence. Its morphological relationship with similar species is discussed, the detailed descriptions, colour photographs, distribution, as well as the IUCN threatened status based on the IUCN Red List Categories and Criteria are also provided.

Petrocosmeaduyunensis (Gesneriaceae), a new species from Guizhou, China.

Plants belonging to the genus Petrocosmea are rare and small herbs difficult to find in the wild. In the present study, a new species, Petrocosmeaduyunensis, from Guizhou, China, is described. The species is most similar to P.leiandra and differs from it by a distinctly recurved abaxial corolla lip, free anthers and included pistil. Detailed morphological comparisons are given. One population with about 100 mature individuals was found at the type locality. This new taxon was assessed as "Data Deficient" (DD) according to the IUCN standards.

Exogenous vitamin C triggered structural changes of redox-activated dual core-crosslinked biodegradable nanogels for boosting the antitumor efficiency.

Premature leakage of drugs during blood circulation and slow drug release at the tumor site are two major challenges that nanocarriers have to overcome to achieve successful cancer therapy. Herein, a dual core-crosslinked, redox-sensitive polymeric nanogel (sDL) was constructed by the self-assembly of two star-shaped amphiphilic copolymers (4sP(EG-b-LLA)-N3, 4sP(EG-b-DLA)-N3) in the presence of a redox-sensitive crosslinker (d-ss-Bu), where hydrophilic polyethylene glycol (PEG) was used as the shell and the functional hydrophobic poly(l-lactide) (PLLA) and poly(d-lactide) (PDLA) were used as the dual crosslinked core via stereocomplex formation and chemical interactions. The dual core-crosslinked structure of the nanogels allowed for almost 2-fold enhanced doxorubicin (DOX)-loading capacity, favorable structural stability to restrict the premature leakage of therapeutic drug and smaller particle size to accelerate the internalization efficiency compared to non-crosslinked nanocarriers. Furthermore, exogenous vitamin C (Vc) can trigger the breakage of redox-sensitive bonds to accelerate drug release from nanogels for improved in vitro antitumor efficacy. Notably, in vivo near-infrared imaging showed that the highly stable DOX-loaded sDL efficiently aggregated at the tumor site. Sequential administration of DOX-loaded sDL and Vc exhibited the highest tumor inhibition effect without associated systemic toxicity compared to the corresponding single injection of Vc or DOX-loaded sDL control groups for in vivo studies, indicating that exogenous administration of Vc can synergistically impact the release of DOX from sDL. Therefore, the developed nanogels proved to be promising smart carriers for achieving precise tunable-stability in response to relevant environments and the combination of Vc to activate reduction-sensitive drug delivery is a promising approach to maximize the therapeutic efficacy.

Highly stable RGD/disulfide bridge-bearing star-shaped biodegradable nanocarriers for enhancing drug-loading efficiency, rapid cellular uptake, and on-demand cargo release.

BACKGROUND: Stability, enhanced drug-loading efficiency (DLE), and specific accumulation of therapeutics at tumor sites remain major challenges for successful cancer therapy. PURPOSE: This study describes a newly developed intelligent nanosystem that integrates stealthy, active targeting, stimulus-responsiveness, and π-π interaction properties in a single carrier, based on the multifunctional star-shaped biodegradable polyester. PATIENTS AND METHODS: This highly stable, smart nanocarrier with spherical structures and a low critical micelle concentration (CMC) can provide spacious harbor and strong π-π interaction and hydrophobic interactions for hydrophobic doxorubicin (DOX). Its structure and morphology were characterized by proton nuclear magnetic resonance (1H-NMR) spectra, Fourier transform infrared (FTIR) spectra, Gel permeation chromatography (GPC), dynamic light scattering (DLS), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Antitumor effciency of polymeric micelles using CCK-8 assay, and the intracellular-activated delivery system was tracked by confocal laser scanning microscopy (CLSM) and flow cytometry. RESULTS: The synthesized copolymer can be self-assembled into nanoparticles with size of 50 nm and critical micellar concentration of 2.10 µg/mL. The drug-loading content of nanoparticles can be enhanced to 17.35%. Additionally, the stimulus-responsive evaluation and drug release study showed that the nanocarrier can rapidly respond to the intracellular reductive environment and dissociate for drug release. An in vitro study demonstrated that the nanocarrier can ferry doxorubicin selectively into tumor tissue, rapidly enter cancer cells, and controllably release its payload in response to an intracellular reductive environment, resulting in excellent antitumor activity in vitro. CONCLUSION: This study provides a facile and versatile approach for the design of multifunctional star-shaped biodegradable polyester nanovehicles for effective cancer treatment.