Discovery of acetophenone/piperazin-2-one hybrids as selective anti-TNBC cancer agents by causing DNA damage.

Twenty-five acetophenone/piperazin-2-one (APPA) hybrids were designed and synthesized based on key pharmacophores found in anti-breast cancer drugs Neratinib, Palbociclib, and Olaparib. Compound 1j exhibited good in vitro antiproliferative activity (IC50 = 6.50 µM) and high selectivity (SI = 9.2 vs HER2-positive breast cancer cells SKBr3; SI = 7.3 vs normal breast cells MCF-10A) against triple negative breast cancer (TNBC) cells MDA-MB-468. In addition, 1j could selectively cause DNA damage, inducing the accumulation of γH2AX and P53 in MDA-MB-468 cells. It also reduced the phosphorylation level of P38 and the expression of HSP70, which further prevented the repair of DNA damage and caused cells S/G2-arrest leading to MDA-MB-468 cells death.

The aging of glymphatic system in human brain and its correlation with brain charts and neuropsychological functioning.

This study aimed to investigate the aging of the glymphatic system in healthy adults, and to determine whether this change is correlated with the brain charts and neuropsychological functioning. Two independent brain 3.0 T MRI datasets were analyzed: a public dataset and our hospital-own dataset from two hospitals. The function of the glymphatic system was quantified by diffusion analysis along the perivascular space (ALPS) index via an automatic method. Brain charts were calculated online. Correlations of the ALPS index with the brain charts, age, gender, and neuropsychological functioning, as well as differences in ALPS index across age groups, were assessed. A total of 161 healthy volunteers ranging in age from 20 to 87 years were included. ALPS index was negatively correlated with the age in both independent datasets. Compared with that of the young group, the ALPS index was significantly lower in the elderly group. No significant difference was found in the ALPS index between different genders. In addition, the ALPS index was not significantly correlated with the brain charts and neuropsychological functioning. In conclusion, the aging of glymphatic system exists in healthy adults, which is not correlated with the changes of brain charts and neuropsychological functioning.

Synthesis of C3'-Foused Aryl/Penta-1,4-Dien-3-One/Amine Hybrids as HSP90C-Terminal Inhibitors.

24 C3'-focused hybrids of aryl/penta-1,4-dien-3-one/amine (APDA) were designed and synthesized. Of these hybrids, 2 n demonstrated improved antiproliferative effects on HER2-positive breast cancer cells (SKBr3 and BT474) and triple-negative breast cancer (TNBC) cells (MDA-MB-231 and MDA-MB-468) with IC50 values ranging from 7.45 to 10.75 µM, but less toxicity to normal breast cells MCF-10A than the first generation of hybrid 1. Additionally, 2 n retained its ability to inhibit HSP90C-terminus, leading to the degradation of HSP90 client proteins HER2, EGFR, pAKT, AKT, and CDK4, without inducing a heat-shock response. Notably, 2 n also demonstrated improved thermostability compared to 1 and maintained in vitro metabolic stability in simulated intestinal fluid. These findings will provide a scientific basis for developing HSP90C-terminal inhibitors in the future.

Impact of Telemedicine on Blood Glucose Control and Ophthalmic Screenings for Patients with Diabetes in Remote Areas During the COVID-19 Pandemic: A Real-World Study in Northern Taiwan.

Introduction: The purpose of this study was to assess the impact of telemedicine on ophthalmic screening and blood glucose control for patients with diabetes in remote areas of Northern Taiwan during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Telemedicine was implemented in Shiding and Wanli Districts using a 5G platform from April 2021 to December 2022. Patients with poorly controlled diabetes received real-time consultations from endocrinologists at Far Eastern Memorial Hospital, 50 km away, for medication adjustment, diet control, and lifestyle recommendations. The study also provided cloud-upload blood glucose meters for self-monitoring and regular medical advice from hospital nurses. Ophthalmic screenings included fundus imaging, external eye image, and intraocular pressure measurement, with instant communication and diagnosis by ophthalmologists through telemedicine. A satisfaction questionnaire survey was conducted. Results: The study enrolled 196 patients with diabetes. Blood glucose and glycosylated hemoglobin levels were significantly reduced after applying telemedicine (p = 0.01 and p = 0.005, respectively). Ophthalmic screenings led to hospital referrals for 16.0% with abnormal fundus images, 15.6% with severe cataract or anterior segment disorders, and 27.9% with ocular hypertension or glaucoma. Fundus screening rates remained high at 86.3% and 80.4% in 2022, mainly using telemedicine, comparable with the traditional screening rate in the past 5 years. The overall satisfaction rate was 98.5%. Conclusions: Telemedicine showed effectiveness and high satisfaction in managing diabetes and conducting ophthalmic screenings in remote areas during the COVID-19 pandemic. It facilitated early diagnosis and treatment of ocular conditions while maintaining good blood glucose control and fundus screening rates.

Multifunctional Asymmetric Bacterial Cellulose Membrane with Enhanced Anti-Bacterial and Anti-Inflammatory Activities for Promoting Infected Wound Healing.

An asymmetric wound dressing acts as a skin-like structure serves as a protective barrier between a wound and its surroundings. It allows for the absorption of tissue fluids and the release of active substances at the wound site, thus speeding up the healing process. However, the production of such wound dressings requires the acquisition of specialized tools, expensive polymers, and solvents that contain harmful byproducts. In this study, an asymmetric bacterial cellulose (ABC) wound dressing using starch as a porogen has been developed. By incorporating silver-metal organic frameworks (Ag-MOF) and curcumin into the ABC membrane, the wound dressing gains antioxidant, reactive oxygen species (ROS) scavenging, and anti-bacterial activities. Compared to BC-based wound dressings, this dressing promotes efficient dissolution and controlled release of curcumin and silver ions. In a full-thickness skin defect model, wound dressing not only inhibits the growth of bacteria on infected wounds but also regulates the release of curcumin to reduce inflammation and promote the production of epithelium, blood vessels, and collagen. Consequently, this dressing provides superior wound treatment compared to BC-based dressing.

Nanotransducer-Enabled Wireless Spatiotemporal Tuning of Engineered Bacteria in Bumblebee.

Bumblebees are essential pollinators of wild-flowering plants and crops. It is noticed that regulating the gut microorganisms of bumblebees is of great significance for the maintenance of bumblebee health and disease treatment. Additionally, social bees are used as models to study regulatory control methods of gut bacteria in vivo. However, these methods lack precision and are not studied in bumblebees. In this study, nanotransducers are used for wireless spatiotemporal tuning of engineered bacteria in bumblebees. These nanotransducers are designed as 1D chains with smooth surfaces for easy transport in vivo, and temperature-controlled engineered bacteria colonize the guts of microbial-free bumblebees. Thermal production in the bumblebee gut is achieved using magnetothermal and photothermal methods in response to nanotransducers, resulting in significant target protein upregulation in engineered bacteria in the bumblebee gut. This advanced technology enables the precise control of engineered bacteria in the bumblebee gut. It also lays the foundation for the treatment of bumblebee intestinal parasitic diseases and the elimination of pesticide residues.

A Multicenter Study on Preoperative Assessment of Lymphovascular Space Invasion in Early-Stage Cervical Cancer Based on Multimodal MR Radiomics.

BACKGROUND: As lymphovascular space invasion (LVSI) was closely related to lymph node metastasis and prognosis, the preoperative assessment of LVSI in early-stage cervical cancer is crucial for patients. PURPOSE: To develop and validate nomogram based on multimodal MR radiomics to assess LVSI status in cervical cancer patients. STUDY TYPE: Retrospective. POPULATION: The study included 168 cervical cancer patients, of whom 129 cases (age 51.36 ± 9.99 years) from institution 1 were included as the training cohort and 39 cases (age 52.59 ± 10.23 years) from institution 2 were included as the external test cohort. FIELD STRENGTH/SEQUENCE: There were 1.5 T and 3.0 T MRI scans (T1-weighted imaging [T1WI], fat-saturated T2-weighted imaging [FS-T2WI], and contrast-enhanced [CE]). ASSESSMENT: Six machine learning models were built and selected to construct the radiomics signature. The nomogram model was constructed by combining the radiomics signature with the clinical signature, which was then validated for discrimination, calibration, and clinical usefulness. STATISTICAL TESTS: The clinical characteristics were compared using t-tests, Mann-Whitney U tests, or chi-square tests. The Spearman and LASSO methods were used to select radiomics features. The receiver operating characteristic (ROC) analysis was performed, and the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated. RESULTS: The logistic regression (LR) model performed best in each sequence. The AUC of CE-T1-T2WI-combined was the highest in the LR model, with an AUC of 0.775 (95% CI: 0.570-0.979) in external test cohort. The nomogram showed high predictive performance in the training (AUC: 0.883 [95% CI: 0.823-0.943]) and test cohort (AUC: 0.830 [95% CI: 0.657-1.000]) for predicting LVSI. Decision curve analysis demonstrated that the nomogram was clinically useful. DATA CONCLUSION: Our findings suggest that the proposed nomogram model based on multimodal MRI of CE T1WI-T2WI-combined could be used to assess LVSI status in early cervical cancer. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

The crescent-like Golgi ribbon is shaped by the Ajuba/PRMT5/Aurora-A complex-modified HURP.

BACKGROUND: Golgi apparatus (GA) is assembled as a crescent-like ribbon in mammalian cells under immunofluorescence microscope without knowing the shaping mechanisms. It is estimated that roughly 1/5 of the genes encoding kinases or phosphatases in human genome participate in the assembly of Golgi ribbon, reflecting protein modifications play major roles in building Golgi ribbon. METHODS: To explore how Golgi ribbon is shaped as a crescent-like structure under the guidance of protein modifications, we identified a protein complex containing the scaffold proteins Ajuba, two known GA regulators including the protein kinase Aurora-A and the protein arginine methyltransferase PRMT5, and the common substrate of Aurora-A and PRMT5, HURP. Mutual modifications and activation of PRMT5 and Aurora-A in the complex leads to methylation and in turn phosphorylation of HURP, thereby producing HURP p725. The HURP p725 localizes to GA vicinity and its distribution pattern looks like GA morphology. Correlation study of the HURP p725 statuses and GA structure, site-directed mutagenesis and knockdown-rescue experiments were employed to identify the modified HURP as a key regulator assembling GA as a crescent ribbon. RESULTS: The cells containing no or extended distribution of HURP p725 have dispersed GA membranes or longer GA. Knockdown of HURP fragmentized GA and HURP wild type could, while its phosphorylation deficiency mutant 725A could not, restore crescent Golgi ribbon in HURP depleted cells, collectively indicating a crescent GA-constructing activity of HURP p725. HURP p725 is transported, by GA membrane-associated ARF1, Dynein and its cargo adaptor Golgin-160, to cell center where HURP p725 forms crescent fibers, binds and stabilizes Golgi assembly factors (GAFs) including TRIP11, GRASP65 and GM130, thereby dictating the formation of crescent Golgi ribbon at nuclear periphery. CONCLUSIONS: The Ajuba/PRMT5/Aurora-A complex integrates the signals of protein methylation and phosphorylation to HURP, and the HURP p725 organizes GA by stabilizing and recruiting GAFs to its crescent-like structure, therefore shaping GA as a crescent ribbon. Therefore, the HURP p725 fiber serves a template to construct GA according to its shape. Video Abstract.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study.

OBJECTIVES: To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma. METHODS: A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models. RESULTS: Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model. CONCLUSIONS: DLCT has added value for STAS prediction in lung adenocarcinoma. CLINICAL RELEVANCE STATEMENT: Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future. KEY POINTS: • Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

Prediction of response to preoperative neoadjuvant chemotherapy in extremity high-grade osteosarcoma using X-ray and multiparametric MRI radiomics.

PURPOSE: This study aims to evaluate the value of applying X-ray and magnetic resonance imaging (MRI) models based on radiomics feature to predict response of extremity high-grade osteosarcoma to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: A retrospective dataset was assembled involving 102 consecutive patients (training dataset, n = 72; validation dataset, n = 30) diagnosed with extremity high-grade osteosarcoma. The clinical features of age, gender, pathological type, lesion location, bone destruction type, size, alkaline phosphatase (ALP), and lactate dehydrogenase (LDH) were evaluated. Imaging features were extracted from X-ray and multi-parametric MRI (T1-weighted, T2-weighted, and contrast-enhanced T1-weighted) data. Features were selected using a two-stage process comprising minimal-redundancy-maximum-relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression. Logistic regression (LR) modelling was then applied to establish models based on clinical, X-ray, and multi-parametric MRI data, as well as combinations of these datasets. Each model was evaluated using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI). RESULTS: AUCs of 5 models using clinical, X-ray radiomics, MRI radiomics, X-ray plus MRI radiomics, and combination of all were 0.760 (95% CI: 0.583-0.937), 0.706 (95% CI: 0.506-0.905), 0.751 (95% CI: 0.572-0.930), 0.796 (95% CI: 0.629-0.963), 0.828 (95% CI: 0.676-0.980), respectively. The DeLong test showed no significant difference between any pair of models (p > 0.05). The combined model yielded higher performance than the clinical and radiomics models as demonstrated by net reclassification improvement (NRI) and integrated difference improvement (IDI) values, respectively. This combined model was also found to be clinically useful in the decision curve analysis (DCA). CONCLUSION: Modelling based on combination of clinical and radiomics data improves the ability to predict pathological responses to NAC in extremity high-grade osteosarcoma compared to the models based on either clinical or radiomics data.

The PRMT5/HURP axis retards Golgi repositioning by stabilizing acetyl-tubulin and Golgi apparatus during cell migration.

The Golgi apparatus (GA) translocates to the cell leading end during directional migration, thereby determining cell polarity and transporting essential factors to the migration apparatus. The study provides mechanistic insights into how GA repositioning (GR) is regulated. We show that the methyltransferase PRMT5 methylates the microtubule regulator HURP at R122. The HURP methylation mimicking mutant 122F impairs GR and cell migration. Mechanistic studies revealed that HURP 122F or endogenous methylated HURP, that is, HURP m122, interacts with acetyl-tubulin. Overexpression of HURP 122F stabilizes the bundling pattern of acetyl-tubulin by decreasing the sensitivity of the latter to a microtubule disrupting agent nocodazole. HURP 122F also rigidifies GA via desensitizing the organelle to several GA disrupting chemicals. Similarly, the acetyl-tubulin mimicking mutant 40Q or tubulin acetyltransferase αTAT1 can rigidify GA, impair GR, and retard cell migration. Reversal of HURP 122F-induced GA rigidification, by knocking down GA assembly factors such as GRASP65 or GM130, attenuates 122F-triggered GR and cell migration. Remarkably, PRMT5 is found downregulated and the level of HURP m122 is decreased during the early hours of wound healing-based cell migration, collectively implying that the PRMT5-HURP-acetyl-tubulin axis plays the role of brake, preventing GR and cell migration before cells reach empty space.

NCAPG promotes the proliferation of hepatocellular carcinoma through the CKII-dependent regulation of PTEN.

BACKGROUND: NCAPG, non-SMC subunit in the concentrate I complex, might promote the proliferation of hepatocellular carcinoma (HCC), but the mechanism is unclear. The aim of this study was to explore how NCAPG affects PTEN to influence the proliferation of HCC. METHODS: Western blotting, qRT-PCR and immunohistochemistry were used to detect NCAPG expression in HCC tissues. The effect of NCAPG on the proliferation of HCC cell lines was evaluated using an EdU incorporation assay, a Cell Counting Kit-8 assay and Fluorescence in situ hybridization (FISH). BALB/c-nu/nu mice were used for the in vivo proliferation experiment. Transcriptome sequencing was used to determine the relationship between NCAPG and PTEN. Immunocoprecipitation-mass spectrometry (IP-MS), proteomic sequencing and Co-immunoprecipitation (CO-IP) were used to identify and examine the interaction between the NCAPG and CKII proteins. RESULTS: We confirmed that NCAPG was abnormally overexpressed in HCC and promoted the proliferation of HCC cells. Transcriptome sequencing revealed that NCAPG inhibited the transcription of PTEN and promoted the activation of the PI3K-AKT pathway. We found a close association between NCAPG and CKII through proteomic sequencing; their interaction was confirmed by Co-IP. There was a positive correlation between NCAPG and CKII that promoted the phosphorylation of PTEN and thus inhibited its transcription and functions. We also proved that CKII was the key factor in the induction of proliferation by NCAPG. CONCLUSION: We revealed the mechanism by which NCAPG regulates the proliferation of HCC: NCAPG inhibits PTEN through its interaction with CKII, and then activates the PI3K-AKT pathway to promote the proliferation of HCC.

Metabolic signatures of hepatolithiasis using ultra-high performance liquid chromatography-tandem mass spectrometry.

BACKGROUND & AIMS: A metabolomic study of hepatolithiasis has yet to be performed. The purpose of the present study was to characterize the metabolite profile and identify potential biomarkers of hepatolithiasis using a metabolomic approach. METHODS: We comprehensively analyzed the serum metabolites from 30 patients with hepatolithiasis and 20 healthy individuals using ultra-high performance liquid chromatography-tandem mass spectrometry operated in negative and positive ionization modes. Statistical analyses were performed using univariate (Student's t-test) and multivariate (orthogonal partial least-squares discriminant analysis) statistics and R language. Receiver operator characteristic (ROC) curve analysis was performed to identify potential predictors of hepatolithiasis. RESULTS: We identified 277 metabolites that were significantly different between hepatolithiasis serum group and healthy control serum group. These metabolites were principally lipids and lipid-like molecules and amino acid metabolites. The steroid hormone biosynthesis pathway was enriched in hepatolithiasis serum group. In all specific metabolites, 75 metabolites were over-expressed in hepatolithiasis serum group. The AUC values for 60 metabolites exceeded 0.70, 4 metabolites including 18-ß-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) exceeded 0.90. CONCLUSIONS: We have identified serum metabolites that are associated with hepatolithiasis for the first time. 60 potential metabolic biomarkers were identified, 18-ß-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) may have the potential clinical utility in hepatolithiasis.

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer.

INTRODUCTION: Improving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer. METHODS: A total of 119 (range, 28-69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (Ktrans; Kep; Ve; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction. RESULTS: The Ktrans, Kep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined Ktrans, Kep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively. CONCLUSIONS: The results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

IVIM using convolutional neural networks predicts microvascular invasion in HCC.

OBJECTIVES: The study aimed to investigate the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using convolutional neural networks (CNNs). METHODS: This retrospective study included 114 patients with pathologically confirmed HCC from December 2014 to August 2021. All patients underwent MRI examination including IVIM sequence with 9 b-values preoperatively. First, 9 b-value images were superimposed in the channel dimension, and a b-value volume with a shape of 32 × 32 × 9 dimension was obtained. Secondly, an image resampling method was performed for data augmentation to generate more samples for training. Finally, deep features to predict MVI in HCC were directly derived from a b-value volume based on the CNN. Moreover, a deep learning model based on parameter maps and a fusion model combined with deep features of IVIM, clinical characteristics, and IVIM parameters were also constructed. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance for MVI prediction in HCC. RESULTS: Deep features directly extracted from IVIM-DWI (0.810 (range 0.760, 0.829)) using CNN yielded better performance for prediction of MVI than those from IVIM parameter maps (0.590 (range 0.555, 0.643)). Furthermore, the performance of the fusion model combined with deep features of IVIM-DWI, clinical features (α-fetoprotein (AFP) level and tumor size), and apparent diffusion coefficient (ADC) (0.829 (range 0.776, 0.848)) was slightly improved. CONCLUSIONS: Deep learning with CNN based on IVIM-DWI can be conducive to preoperative prediction of MVI in patients with HCC. KEY POINTS: • Deep learning assessment of IVIM data for prediction of MVI in HCC can overcome the unstable and low performance of IVIM parameters. • Deep learning model based on IVIM performs better than parameter values, clinical features, and deep learning model based on parameter maps. • The fusion model combined with deep features of IVIM, clinical characteristics, and ADC yields better performance for prediction of MVI than the model only based on IVIM.

Evaluation of peripheral nerve acute crush injury in rabbits: comparison among diffusion kurtosis imaging, diffusion tensor imaging and electromyography.

OBJECTIVE: Diffusion kurtosis imaging (DKI) has been proven to provide additional value for assessing many central nervous system diseases compared with conventional diffusion tensor imaging (DTI); however, whether it has the same value in peripheral nerve injury is unclear. This study aimed to investigate the performance of DKI, DTI, and electromyography (EMG) in evaluating peripheral nerve crush injury (PNCI) in rabbits. MATERIALS AND METHODS: A total of 27 New Zealand white rabbits were selected to establish a PNCI model. Longitudinal DTI, DKI, and EMG were evaluated before surgery and 1 day, 3 days, 1 week, 2 weeks, 4 weeks, 6 weeks, and 8 weeks after surgery. At each time point, two rabbits were randomly selected for pathological examination. RESULTS: The results showed that fractional anisotropy (FA) derived from both DKI and DTI demonstrated a significant difference between injured and control nerves at all time points (all P < 0.005) mean kurtosis of the injured nerve was lower than that on the control side after 2-8 weeks (all P < 0.05). No statistically significant difference was found in radial kurtosis, axial kurtosis, and apparent diffusion coefficient at almost every time point. The difference in compound muscle action potential (CMAP) of the bilateral gastrocnemius at each time point was statistically significant (all P < 0.001). CONCLUSIONS: CMAP was a sensitive and reliable method to assess acute PNCI without being affected by perineural edema. DKI may not be superior to DTI in evaluating peripheral nerves, DTI with a shorter scanning time was preferred as an effective choice for evaluating acute peripheral nerve traumatic injury.

A computed tomography-based radiomic nomogram for predicting lymph node metastasis in patients with early-stage papillary thyroid carcinoma.

BACKGROUND: Accurate assessment of lymph node metastasis (LNM) is important for the selection of the optimal therapeutic strategy in patients with papillary thyroid carcinoma (PTC). PURPOSE: To develop and validate a radiomics nomogram based on computed tomography (CT) for predicting LNM in patients with early-stage PTC. MATERIAL AND METHODS: A total of 92 patients with pathologically confirmed PTC were divided into a training cohort (n = 64) and validation cohort (n = 28). Radiomic features of the tumor and peritumoral interstitium were extracted from contrast-enhanced CT images. The radiomic signature was constructed and the radiomic score (Rad-score) was calculated. Combined with the Rad-score and independent clinical factors, a radiomic nomogram was constructed and its performance was assessed by receiver operating characteristic (ROC) curves and calibration plots. The comparison of ROC curves was performed with DeLong's test. RESULTS: A combined nomogram model of the thyroid tumor and peritumoral interstitium was constructed based on the Rad-score, tumor location, maximum diameter, and T stage, and it had areas under the ROC curve of 0.956 (95% confidence interval [CI] = 0.913-1.000) and 0.876 (95% CI = 0.741-1.000) in the training and validation cohorts, respectively. Decision curve analysis suggested that the combined nomogram model had better clinical usefulness than the other models. CONCLUSION: A CT-based radiomics nomogram incorporating the radiomic signature and the selected clinical predictors can be a reliable approach to preoperatively predict the LNM status in patients with early-stage PTC, which is helpful for treatment decisions and prognosis.

Association between Nephrotoxic Drug Combinations and Acute Kidney Injury in the Neonatal Intensive Care Unit.

OBJECTIVE: To determine the incidence of acute kidney injury (AKI) in infants exposed to nephrotoxic drug combinations admitted to 268 neonatal intensive care units managed by the Pediatrix Medical Group. STUDY DESIGN: We included infants born at 22-36 weeks gestational age, ≤120 days postnatal age, exposed to nephrotoxic drug combinations, with serum creatinine measurements available, and discharged between 2007 and 2016. To identify risk factors associated with a serum creatinine definition of AKI based on the Kidney Disease: Improving Global Outcomes criteria, we performed multivariable logistic and Cox regression adjusting for gestational age, sex, birth weight, postnatal age, race/ethnicity, sepsis, respiratory distress syndrome, baseline serum creatinine, and duration of combination drug exposure. The adjusted odds of AKI were determined relative to gentamicin + indomethacin for the following nephrotoxic drug combinations: chlorothiazide + ibuprofen; chlorothiazide + indomethacin; furosemide + gentamicin; furosemide + ibuprofen; furosemide + tobramycin; ibuprofen + spironolactone; and vancomycin + piperacillin-tazobactam. RESULTS: Among 8286 included infants, 1384 (17%) experienced AKI. On multivariable analysis, sepsis, lower baseline creatinine, and duration of combination therapy were associated with increased odds of AKI. Furosemide + tobramycin and vancomycin + piperacillin-tazobactam were associated with a decreased risk of AKI relative to gentamicin + indomethacin in both the multivariable and Cox regression models. CONCLUSIONS: In this cohort, infants receiving longer durations of nephrotoxic combination therapy had an increased odds of developing AKI.

Atypical presentations of coronavirus disease 2019 (COVID-19) from onset to readmission.

BACKGROUND: To investigate the CT imaging and clinical features of three atypical presentations of coronavirus disease 2019 (COVID-19), namely (1) asymptomatic, (2) CT imaging-negative, and (3) re-detectable positive (RP), during all disease stages. METHODS: A consecutive cohort of 79 COVID-19 patients was retrospectively recruited from five independent institutions. For each presentation type, all patients were classified into atypical vs. typical groups (i.e., asymptomatic vs.symptomatic, CT imaging-negative vs. CT imaging-positive, and RP and non-RP,respectively). The chi-square test, Student's t test, and Kruskal-Wallis H test were performed to compare CT imaging and clinical features of atypical vs. typical patients for all three presentation categories. RESULTS: In our COVID-19 cohort, we found 12.7% asymptomatic patients, 13.9% CT imaging-negative patients, and 8.9% RP patients. The asymptomatic patients had fewer hospitalization days (P=0.043), lower total scores for bilateral lung involvement (P< 0.001), and fewer ground-glass opacities (GGOs) in the peripheral area (P< 0.001) than symptomatic patients. The CT imaging-negative patients were younger (P=0.002), had a higher lymphocyte count (P=0.038), had a higher lymphocyte rate (P=0.008), and had more asymptomatic infections (P=0.002) than the CT imaging-positive patients. The RP patients with moderate COVID-19 had lower total scores of for bilateral lung involvement (P=0.030) and a smaller portion of the left lung affected (P=0.024) than non-RP patients. Compared to their first hospitalization, RP patients had a shorter hospitalization period (P< 0.001) and fewer days from the onset of illness to last RNA negative conversion (P< 0.001) at readmission. CONCLUSIONS: Significant CT imaging and clinical feature differences were found between atypical and typical COVID-19 patients for all three atypical presentation categories investigated in this study, which may help provide complementary information for the effective management of COVID-19.

Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features.

BACKGROUND: To explore the characteristics of myocardial textures on coronary computed tomography angiography (CCTA) images in patients with coronary atherosclerotic heart disease, a classification model was established, and the diagnostic effectiveness of CCTA for myocardial ischaemia patients was explored. METHODS: This was a retrospective analysis of the CCTA images of 155 patients with clinically diagnosed coronary heart disease from September 2019 to January 2020, 79 of whom were considered positive (myocardial ischaemia) and 76 negative (normal myocardial blood supply) according to their clinical diagnoses. By using the deep learning model-based CQK software, the myocardium was automatically segmented from the CCTA images and used to extract texture features. All patients were randomly divided into a training cohort and a test cohort at a 7:3 ratio. The Spearman correlation and least absolute shrinkage and selection operator (LASSO) method were used for feature selection. Based on the selected features of the training cohort, a multivariable logistic regression model was established. Finally, the test cohort was used to verify the regression model. RESULTS: A total of 387 features were extracted from the CCTA images of the 155 coronary heart disease patients. After performing dimensionality reduction with the Spearman correlation and LASSO, three texture features were selected. The accuracy, area under the curve, specificity, sensitivity, positive predictive value and negative predictive value of the constructed multivariable logistic regression model with the test cohort were 0.783, 0.875, 0.733, 0.875, 0.650 and 0.769, respectively. CONCLUSION: CCTA imaging texture features of the myocardium have potential as biomarkers for diagnosing myocardial ischaemia.