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BackgroundTransitioning from marriage to widowhood presents inevitable and significant challenges for many older adults. This study explored the impact of widowhood on a range of mental health outcomes, including pulse pressure and fasting blood glucose levels, among older adults in nursing homes.MethodsThis cross-sectional study utilized cluster random sampling to recruit participants, with data analyzed from 388 older Chinese adults. Psychosocial traits were assessed using the Perceived Social Support from Family scale (PSS-Fa) for family support, the Generalized Anxiety Disorder 7-item scale (GAD-7) for anxiety symptoms, and the 9-item Patient Health Questionnaire (PHQ-9) for depressive symptoms and suicidal ideation. Propensity score matching (PSM) was employed to control for confounding factors. A multivariate linear regression analysis was performed to explore the relationship between widowhood, mental health outcomes, pulse pressure, and fasting blood glucose levels.ResultsAfter applying PSM, the sample size was refined to 268 (N = 134 for both married and widowed groups) from the initial 388, excluding 120 unmatched cases. Widowed older adults were found to have notably lower family support (β = −0.81, p = 0.002), increased depressive symptoms (β = 1.04, p = 0.043), elevated pulse pressure (β = 8.90, p

In modern medicine, precision diagnosis and treatment using optical materials, such as fluorescence/photoacoustic imaging-guided photodynamic therapy (PDT), are becoming increasingly popular. Photosensitizers (PSs) are the most important component of PDT. Different from conventional PSs with planar molecular structures, which are susceptible to quenching effects caused by aggregation, the distinct advantages of AIE fluorogens open up new avenues for the development of image-guided PDT with improved treatment accuracy and efficacy in practical applications. It is critical that as much of the energy absorbed by optical materials is dissipated into the pathways required to maximize biomedical applications as possible. Intersystem crossing (ISC) represents a key step during the energy conversion process that determines many fundamental optical properties, such as increasing the efficiency of reactive oxygen species (ROS) production from PSs, thus enhancing PDT efficacy. Although some review articles have summarized the accomplishments of various optical materials in imaging and therapeutics, few of them have focused on how to improve the phototherapeutic applications, especially PDT, by adjusting the ISC process of organic optics materials. In this review, we emphasize the latest advances in the reasonable design of AIE-active PSs with type I photochemical mechanism for anticancer or antibacterial applications based on ISC modulation, as well as discuss the future prospects and challenges of them. In order to maximize the anticancer or antibacterial effects of type I AIE PSs, it is the aim of this review to offer advice for their design with the best energy conversion.

To explore email request patterns in the institutional context of university settings, this study combines speech act research with conversation analysis methods to examine how native speakers of American English and native speakers of Chinese formulate email requests to faculty. 100 authentic email requests sent by Chinese and American students who studied in a U.S. university was collected. The methodology of conversation analysis was used to investigate how imposition level of emails and senders' entitlement to make the request affect students' language choices. The findings demonstrate that Chinese students have some pragmatic infelicities in their email requests, such as underuse of internal and external modifications for high-imposition requests, presenting request head acts at the beginning of emails, and pre-assuming that the requestee would grant the request. This study finally offers pedagogical implications for teaching email requests to English learners. This study contributes to our understanding of the requestive patterns of Chinese and American students as well as the similarities and differences between emails written by American students and those written by Chinese students. It contributes to the field of cross-cultural pragmatic studies on the speech act of request by L2 speakers.

Abstract Colorectal cancer (CRC) is the most common gastrointestinal malignancy, and 5-Fluorouracil (5-FU) is the principal chemotherapeutic drug used for its treatment. However, 5-FU resistance remains a significant challenge. Under stress conditions, tumor metabolic reprogramming influences 5-FU resistance. Serine metabolism plasticity is one of the crucial metabolic pathways influencing 5-FU resistance in CRC. However, the mechanisms by which CRC modulates serine metabolic reprogramming under serine-deprived conditions remain unknown. We found that exogenous serine deprivation enhanced the expression of serine synthesis pathway (SSP) genes, which in turn supported CRC cell growth and 5-FU resistance. Serine deprivation activate the ERK1/2-p-ELK1 signaling axis, leading to upregulated FOXC1 expression in CRC cells. Elevated FOXC1 emerged as a critical element, promoting the transcription of serine metabolism enzymes PHGDH, PSAT1, and PSPH, which in turn facilitated serine production, supporting CRC growth. Furthermore, through serine metabolism, FOXC1 influenced purine metabolism and DNA damage repair, thereby increasing 5-FU resistance. Consequently, combining dietary serine restriction with targeted therapy against the ERK1/2-pELK1-FOXC1 axis could be a highly effective strategy for treating CRC, enhancing the efficacy of 5-FU.

Abstract Objectives To develop and externally validate a fully automated diagnostic convolutional neural network (CNN) model for cirrhosis based on liver MRI and serum biomarkers. Methods This multicenter retrospective study included consecutive patients receiving pathological evaluation of liver fibrosis stage and contrast-enhanced liver MRI between March 2010 and January 2024. On the training dataset, an MRI-based CNN model was constructed for cirrhosis against pathology, and then a combined model was developed integrating the CNN model and serum biomarkers. On the testing datasets, the area under the receiver operating characteristic curve (AUC) was computed to compare the diagnostic performance of the combined model with that of aminotransferase-to-platelet ratio index (APRI), fibrosis-4 index (FIB-4), and radiologists. The influence of potential confounders on the diagnostic performance was evaluated by subgroup analyses. Results A total of 1315 patients (median age, 54 years; 1065 men; training, n = 840) were included, 855 (65%) with pathological cirrhosis. The CNN model was constructed on pre-contrast T1- and T2-weighted imaging, and the combined model was developed integrating the CNN model, age, and eight serum biomarkers. On the external testing dataset, the combined model achieved an AUC of 0.86, which outperformed FIB-4, APRI and two radiologists (AUC: 0.67 to 0.73, all p

Nanobody (Nb) is derived from the variable domain of heavy-chain antibody (HCAb), naturally displaying notable properties like nano-scale size, exceptional stability, high specificity, low immunogenicity, and cryptic epitope accessibility. These features contribute to its great therapeutic potential as a valuable research tool across diverse diseases, especially autoimmune diseases (AIDs). Caplacizumab (Cablivi®) is the first nanobody drug approved for treating acquired thrombotic thrombocytopenic purpura (aTTP). This review summarizes the biomolecular structure, usage of Nb as a foundation of recombinant constructs, and biochemical properties of nanobodies. As attractive therapeutic candidates, many clinical trials of Nbs have been conducted, elucidating potential therapeutic strategies for AIDs. Therefore, the preclinical development and application of Nbs in AIDs are emphasized throughout this review.

The energy consumption of office buildings has increased sharply since the 21st century with the increasing urbanization coverage. At this stage, the energy consumption of office buildings in China mainly comes from air conditioning and lighting. This paper obtains the regression equation of natural lighting illumination and radiant heat gain under different curtain conditions through experiments and simulations, and gives the theoretical calculation process of curtain regulation of office thermal and light environment and energy consumption. DeST and Ecotect software were used to analyze the thermal and light environment and energy consumption of the office. The results show that setting curtains in the room can effectively improve the indoor thermal light environment, the higher the transmittance of curtains the lower the lighting energy consumption, the higher the number of high temperature hours of natural room temperature and the greater the radiant heat gain. The room with thick curtains has the lowest energy consumption for air conditioning in summer, followed by the room with thin curtains, and the room without curtains has the highest energy consumption for air conditioning. The room without curtains has the lowest energy consumption for artificial lighting, the room with thin curtains has the second lowest, and the room with thick curtains has the highest electricity consumption for artificial lighting. The air conditioning energy consumption accounts for the main building energy consumption, followed by the lighting energy consumption. After setting curtains in the office, the air conditioning energy consumption caused by the solar radiation heat entering the room through the exterior windows is smaller than the lighting energy consumption caused by artificial lighting. Therefore, the installation of internal shading with moderate transmittance and good thermal insulation performance can make the energy saving of lighting and air conditioning energy consumption reach the optimal value.

This paper synthesizes recent advances of technologies in ophthalmology education. Advancements in three-dimensional technology are revolutionizing ophthalmology education by enhancing the visualization, understanding, and retention of complex anatomical and pathological concepts. In addition to physical models, artificial intelligence and virtual reality are emerging as significant tools. A systematic search of PubMed was carried out, with a search date from inception to 01/05/2024. A total of 6,686 articles were screened, of which 6,470 were excluded following abstract review. After reading the remaining 216 articles in full, a further 186 were excluded. A total of 30 original articles were included in the review. This review underscores the transformative impact of novel technology in ophthalmology education, offering innovative solutions to enhance learning, surgical training, and diagnostic skills. Further research and development in this field hold promise for continued improvements in ophthalmology education and practice.

Ophthalmology education is increasingly influenced by non-technical factors. This paper examines the multifaceted influences on ophthalmology education, focusing on direct and indirect factors that have shaped the training and wellbeing of ophthalmology students and residents. A systematic search of PubMed and Embase was carried out, searching date was from inception to 01/07/2024. A total of 8,232 articles were screened, of which 7,976 were excluded following abstract review. After reading the remaining 256 articles in full, a further 228 were excluded. A total of 28 original articles were included in this systematic review. The non-technical factors that influenced ophthalmology education included various crisis, inadequate curricular time, training resources, lack of training standardization and shortage of financial support and teaching resources. The review summarizes the influences on ophthalmology education of various non-technical factors, thereby helping educators improve the training methods.

PurposeThis study aims to evaluate the diagnostic performance of a machine learning model (ML model) to train junior ophthalmologists in detecting preclinical keratoconus (PKC).MethodsA total of 1,334 corneal topography images (The Pentacam HR system) from 413 keratoconus eyes, 32 PKC eyes and 222 normal eyes were collected. Five junior ophthalmologists were trained and annotated the images with or without the suggestions proposed by the ML model. The diagnostic performance of PKC was evaluated among three groups: junior ophthalmologist group (control group), ML model group and ML model-training junior ophthalmologist group (test group).ResultsThe accuracy of the ML model between the eyes of patients with KC and NEs in all three clinics (99% accuracy, area under the receiver operating characteristic (ROC) curve AUC of 1.00, 99% sensitivity, 99% specificity) was higher than that for Belin-Ambrósio enhanced ectasia display total deviation (BAD-D) (86% accuracy, AUC of 0.97, 97% sensitivity, 69% specificity). The accuracy of the ML model between eyes with PKC and NEs in all three clinics (98% accuracy, AUC of 0.96, 98% sensitivity, 98% specificity) was higher than that of BAD-D (69% accuracy, AUC of 0.73, 67% sensitivity, 69% specificity). The diagnostic accuracy of PKC was 47.5% (95%CI, 0.5–71.6%), 100% (95%CI, 100–100%) and 94.4% (95%CI, 14.7–94.7%) in the control group, ML model group and test group. With the assistance of the proposed ML model, the diagnostic accuracy of junior ophthalmologists improved with statistical significance (p

Abstract Objectives To investigate the utility of deep learning (DL) automated segmentation-based MRI radiomic features and clinical-radiological characteristics in predicting early recurrence after curative resection of single hepatocellular carcinoma (HCC). Methods This single-center, retrospective study included consecutive patients with surgically proven HCC who underwent contrast-enhanced MRI before curative hepatectomy from December 2009 to December 2021. Using 3D U-net-based DL algorithms, automated segmentation of the liver and HCC was performed on six MRI sequences. Radiomic features were extracted from the tumor, tumor border extensions (5 mm, 10 mm, and 20 mm), and the liver. A hybrid model incorporating the optimal radiomic signature and preoperative clinical-radiological characteristics was constructed via Cox regression analyses for early recurrence. Model discrimination was characterized with C-index and time-dependent area under the receiver operating curve (tdAUC) and compared with the widely-adopted BCLC and CNLC staging systems. Results Four hundred and thirty-four patients (median age, 52.0 years; 376 men) were included. Among all radiomic signatures, HCC with 5 mm tumor border ex tension and liver showed the optimal predictive performance (training set C-index, 0.696). By incorporating this radiomic signature, rim arterial phase hyperenhancement (APHE), and incomplete tumor “capsule,” a hybrid model demonstrated a validation set C-index of 0.706 and superior 2-year tdAUC (0.743) than both the BCLC (0.550; p < 0.001) and CNLC (0.635; p = 0.032) systems. This model stratified patients into two prognostically distinct risk strata (both datasets p < 0.001). Conclusion A preoperative imaging model incorporating the DL automated segmentation-based radiomic signature with rim APHE and incomplete tumor “capsule” accurately predicted early postsurgical recurrence of a single HCC. Critical relevance statement The DL automated segmentation-based MRI radiomic model with rim APHE and incomplete tumor “capsule” hold the potential to facilitate individualized risk estimation of postsurgical early recurrence in a single HCC. Key Points A hybrid model integrating MRI radiomic signature was constructed for early recurrence prediction of HCC. The hybrid model demonstrated superior 2-year AUC than the BCLC and CNLC systems. The model categorized the low-risk HCC group carried longer RFS. Graphical Abstract

In the rapidly evolving field of medical education, the integration of innovative technologies has become paramount to enhance the training and proficiency of future surgeons. Among these advancements, the application of 3D printing technology stands out as a useful tool in surgical training. The advantages of the 3D printing model include customization, re-usability and low-cost. The average cost of the 3D printing simulators was between $100–1000. However, there were extremely high potential labor cost during the 3D printing that hadn’t been calculated into. Additionally, in the current stage, the 3D printing simulator still have specific limitations. The most mentioned limitation was poor haptic feedback of the simulators, which was very important during the surgical training, since it is the key element for junior doctors to master practical procedures. Also, some simulators didn’t possess the integrated and elaborate structure as the human tissue, hence not the whole surgical procedures can be practiced by the trainees, and further improvement should be made. Although there are shortages, many studies have proved that 3D printing simulator can effectively reduce learning curves and is useful to enhance the trainees’ surgical skills.

Introduction: Noninvasive diagnoses of clinically significant portal hypertension (CSPH) and high-risk gastroesophageal varices are clinically relevant but challenging. Four-dimensional (4D) flow magnetic resonance imaging (MRI) provides comprehensive flow information and is a promising alternative. This study evaluated the efficacy of 4D flow MRI as a noninvasive method for diagnosing CSPH and high-risk varices in patients with liver cirrhosis. Methods: This prospective study enrolled consecutive patients diagnosed with liver cirrhosis at a tertiary referral center between October 2020 and March 2021. Each participant underwent abdominal 4D flow MRI. Hemodynamic parameters within the portal vein, including the average and peak flow velocities, normalized flow volume (Qnormal), and regurgitant fraction (R%), were extracted and compared between healthy individuals and patients with CSPH and between participants with high- and low-risk varices. Subsequently, these parameters were incorporated into a logistic regression (LR) model refined using L1 regularization and validated using five-fold cross-validation. The diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curves. Results: Eighty-two participants were enrolled (71 patients diagnosed with liver cirrhosis and 11 healthy individuals serving as controls). Among hemodynamic parameters, patients with CSPH exhibited a notable increase in Qnormal of 0.66 ​± ​0.19 ​ml∗m2/[cycle∗kg] (P ​= ​0.001) and an R% of 1.98 (2.05) (P ​= ​0.002). Similarly, patients with high-risk varices showed a higher Qnormal of 0.61 ​± ​0.15 ​ml∗m2/[cycle∗kg] (P ​

Abstract Background Late recurrence of hepatocellular carcinoma (HCC) after liver resection is regarded as a de novo tumor primarily related to the severity of underlying liver disease. We aimed to investigate risk factors, especially spleen volume, associated with late recurrence in patients with HCC and cirrhosis. Methods We retrospectively analyzed 301 patients with HCC and cirrhosis who received curative resection and preoperative MRI. Patients were followed for late recurrence for at least 2 years. Spleen volume was automatically measured on MRI with artificial intelligence techniques, and qualitative MRI imaging features reflecting tumor aggressiveness were evaluated. Uni- and multivariable Cox regression analyses were performed to identify independent predictors and a risk score was developed to predict late recurrence. Results Eighty-four (27.9%) patients developed late recurrence during follow-up. Preoperative spleen volume was independently associated with late recurrence, and patients with a volume > 370 cm3 had significantly higher recurrence risk (hazard ratio 2.02, 95%CI 1.31–3.12, p = 0.002). Meanwhile, no qualitative imaging features were associated with late recurrence. A risk score was developed based on the APRI score, spleen volume, and tumor number, which had time-dependent area under the curve ranging from 0.700 to 0.751. The risk score at a cutoff of 0.42 allowed for the identification of two risk categories with distinct risk of late recurrence. Conclusions Preoperative spleen volume on MRI was independently associated with late recurrence after curative-intent resection in patients with HCC and cirrhosis. A risk score was proposed for individualized risk prediction and tailoring of postoperative surveillance strategies. Critical relevance statement Spleen volume measured on MRI with the aid of AI techniques was independently predictive of late HCC recurrence after liver resection. A risk score based on spleen volume, APRI score, and tumor number was developed for accurate prediction of late recurrence. Key points • Preoperative spleen volume measured on MRI was independently associated with late recurrence after curative-intent resection in patients with HCC and cirrhosis. • Qualitative MRI features reflecting tumor aggressiveness were not associated with late recurrence. • A risk score based on spleen volume was developed for accurate prediction of late recurrence and risk stratification. Graphical Abstract

Abstract Objectives To develop and compare noninvasive models for differentiating between combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and HCC based on serum tumor markers, contrast-enhanced ultrasound (CEUS), and computed tomography (CECT). Methods From January 2010 to December 2021, patients with pathologically confirmed cHCC-CCA or HCC who underwent both preoperative CEUS and CECT were retrospectively enrolled. Propensity scores were calculated to match cHCC-CCA and HCC patients with a near-neighbor ratio of 1:2. Two predicted models, a CEUS-predominant (CEUS features plus tumor markers) and a CECT-predominant model (CECT features plus tumor markers), were constructed using logistic regression analyses. Model performance was evaluated by the area under the curve (AUC), sensitivity, specificity, and accuracy. Results A total of 135 patients (mean age, 51.3 years ± 10.9; 122 men) with 135 tumors (45 cHCC-CCA and 90 HCC) were included. By logistic regression analysis, unclear boundary in the intratumoral nonenhanced area, partial washout on CEUS, CA 19-9 > 100 U/mL, lack of cirrhosis, incomplete tumor capsule, and nonrim arterial phase hyperenhancement (APHE) volume 100 U/mL shows excellent sensitivity. Critical relevance statement Combining lack of cirrhosis, incomplete tumor capsule, and nonrim arterial phase hyperenhancement (APHE) volume 100 U/mL shows excellent sensitivity in differentiating cHCC-CCA from HCC. Key points 1. Accurate differentiation between cHCC-CCA and HCC is essential for treatment decisions. 2. The CECT-predominant model provides higher accuracy than the CEUS-predominant model for CHCC-CCA. 3. Combining CECT features and CA 19-9 levels shows a sensitivity of 93.3% in diagnosing cHCC-CCA. Graphical Abstract

Abstract Background Hepatocellular carcinoma (HCC) expressing cytokeratin (CK) 7 or CK19 has a cholangiocyte phenotype that stimulates HCC proliferation, metastasis, and sorafenib therapy resistance This study aims to noninvasively predict cholangiocyte phenotype-positive HCC and assess its prognosis after hepatectomy. Methods Between January 2010 and May 2022, preoperative contrast-enhanced MRI was performed on consecutive patients who underwent hepatectomy and had pathologically confirmed solitary HCC. Two abdominal radiologists separately assessed the MRI features. A predictive model for cholangiocyte phenotype HCC was created using logistic regression analysis and five-fold cross-validation. A receiver operating characteristic curve was used to calculate the model performance. Kaplan–Meier and log-rank methods were used to evaluate survival outcomes. Results In total, 334 patients were included in this retrospective study. Four contrast-enhanced MRI features, including “rim arterial phase hyperenhancement” (OR = 5.9, 95% confidence interval [CI]: 2.9–12.0, 10 points), “nodule in nodule architecture” (OR = 3.5, 95% CI: 2.1–5.9, 7 points), “non-smooth tumor margin” (OR = 1.6, 95% CI: 0.8–2.9, 3 points), and “non-peripheral washout” (OR = 0.6, 95% CI: 0.3–1.0, − 3 points), were assigned to the cholangiocyte phenotype HCC prediction model. The area under the curves for the training and independent validation set were 0.76 and 0.73, respectively. Patients with model-predicted cholangiocyte phenotype HCC demonstrated lower rates of recurrence-free survival (RFS) and overall survival (OS) after hepatectomy, with an estimated median RFS and OS of 926 vs. 1565 days (p

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and represents a significant global health burden with rising incidence rates, despite a more thorough understanding of the etiology and biology of HCC, as well as advancements in diagnosis and treatment modalities. According to emerging evidence, imaging features related to tumor aggressiveness can offer relevant prognostic information, hence validation of imaging prognostic features may allow for better noninvasive outcomes prediction and inform the selection of tailored therapies, ultimately improving survival outcomes for patients with HCC.

Abstract Hepatocellular carcinoma (HCC), the most prevalent type of aggressive liver cancer, accounts for the majority of liver cancer diagnoses and fatalities. Despite recent advancements in HCC treatment, it remains one of the deadliest cancers. Radiation therapy (RT) is among the locoregional therapy modalities employed to treat unresectable or medically inoperable HCC. However, radioresistance poses a significant challenge. It has been demonstrated that RT induced the upregulation of programmed death ligand 1 (PD-L1) on tumor cells, which may affect response to PD-1-based immunotherapy, providing a rationale for combining PD-1/PD-L1 inhibitors with radiation. Here, we utilized attenuated Salmonella as a carrier to explore whether attenuated Salmonella carrying siRNA-PD-L1 could effectively enhance the antitumor effect of radiotherapy on HCC-bearing mice. Our results showed that a combination of siRNA-PD-L1 and radiotherapy had a synergistic antitumor effect by inhibiting the expression of PD-L1 induced by radiation therapy. Mechanistic insights indicated that the combination treatment significantly suppressed tumor cell proliferation, promoted cell apoptosis, and stimulated immune cell infiltration and activation in tumor tissues. Additionally, the combination treatment increased the ratios of CD4+ T, CD8+ T, and NK cells from the spleen in tumor-bearing mice. This study presents a novel therapeutic strategy for HCC treatment, especially for patients with RT resistance.

Rationale and objectives: To establish a diagnostic model based on contrast-enhanced magnetic resonance imaging (MRI) and clinical characteristics for diagnosing extrahepatic cholangiocarcinoma (eCCA). Materials and methods: From April 2014 to September 2021, consecutive patients with extrahepatic bile duct lesions who underwent contrast-enhanced MRI within 1 month before pathological examination were retrospectively enrolled. Two radiologists blinded to clinicopathological information independently evaluated MR images. Univariable and multivariable logistic regression analyses were performed to identify significant clinicoradiological features associated with eCCA, which were subsequently incorporated into a diagnostic model. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve. Results: A total of 182 patients (mean age, 60.8 ± 10.0 years, 117 men) were included, 144 (79 %) of whom had pathologically confirmed eCCA. Diffusion restriction (odds ratio [OR], 8.32; 95 % confidence interval [CI]: 2.88, 25.82; P

Key points EOB-MRI features help capture the characteristics of tumor biology and heterogeneity. EOB-MRI-based HCC differentiation score allowed accurate assessment of poor tumor differentiation preoperatively. This scoring system might be useful for prompting tailored treatment selection.

Abstract With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications.

This study presents the effects of the microstructure on the corresponding fracture toughness of the Ti–5Al–5Mo–5V–1Cr–1Fe (Ti-55511) alloy by undergoing STA (α/β solution treatment plus aging) and STAA (α/β solution treatment plus first-step aging and second-step aging) processes. The results show that the microstructural evolution of Ti-55511 as well as the corresponding fracture toughness is very sensitive to the heat treatment mechanism. Here, an increase in the solution temperature can reduce the content of αp, while increasing the content of α precipitates during the STA and STAA processes. An increase in the aging temperature coarsens the α precipitate and decreases its content, which deflects the crack and consumes additional energy, thus resulting in an enhanced fracture toughness. Note that the STAA process results in the further formation of α precipitates, which will cause a larger stress concentration that promotes the growth and coalescence of voids; notably, this is inevitably accompanied by a decrease in toughness. In addition, ductile fracture dominated by dimples is mainly experienced in the crack instability and growth stage, and a higher toughness increases the size of the dimples. Overall, this study indicates that the toughness of the alloy can be controlled from 38.2 to 110 MPa⋅m0.5 by multiple heat treatments.

Summary: Vitellogenin receptor (VgR) is essential to vitellogenin uptaking and dominates ovary maturation in insects. However, the function of VgR in parasitoid wasps is largely unknown. Here, we applied the Drosophila parasitoid Leptopilina boulardi as a study model to investigate the function of VgR in parasitoids. Despite the conserved sequence characteristics with other insect VgRs, we found L. boulardi VgR (LbVgR) gene was highly expressed in head but lower in ovary. In addition, we found that LbVgR had no effects on ovary development, but participated in host-searching behavior of female L. boulardi and mating behavior of male L. boulardi. Comparative transcriptome analysis further revealed LbVgR might play crucial roles in regulating the expression of some important chemoreception genes to adjust the parasitoid behaviors. These results will broaden our knowledge of the function of VgR in insects, and contribute to develop advanced pest management strategies using parasitoids as biocontrol agents.

Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third most common cause of cancer-related death worldwide. Due to asymptomatic patients in the early stage, most patients are diagnosed at an advanced stage and lose the opportunity for radical resection. In addition, for patients who underwent procedures with curative intent for early-stage HCC, up to 70% of patients may have disease recurrence within 5 years. With the advent of an increasing number of systemic therapy medications, we now have more options for the treatment of HCC. However, data from clinical studies show that with different combinations of regimens, the objective response rate is approximately 40%, and most patients will not respond to treatment. In this setting, biomarkers for predicting treatment response are of great significance for precise treatment, reducing drug side effects and saving medical resources. In this review, we summarized the existing and emerging biomarkers in the literature, with special emphasis on the pathways and mechanism underlying the prediction value of those biomarkers for systemic treatment response.

PurposeAs a coreceptor in Wnt and HGF signaling, glypican-3 (GPC-3) promotes the progression of tumor and is associated with a poor prognosis in hepatocellular carcinoma (HCC). GPC-3 has evolved as a target molecule in various immunotherapies, including chimeric antigen receptor T cell. However, its evaluation still relies on invasive histopathologic examination. Therefore, we aimed to develop an easy-to-use and noninvasive risk score integrating preoperative gadoxetic acid–enhanced magnetic resonance imaging (EOB-MRI) and clinical indicators to predict positive GPC-3 expression in HCC.Methods and materialsConsecutive patients with surgically-confirmed solitary HCC who underwent preoperative EOB-MRI between January 2016 and November 2021 were retrospectively included. EOB-MRI features were independently evaluated by two masked abdominal radiologists and the expression of GPC-3 was determined by two liver pathologists. On the training dataset, a predictive scoring system for GPC-3 was developed against pathology via logistical regression analysis. Model performances were characterized by computing areas under the receiver operating characteristic curve (AUCs).ResultsA total of 278 patients (training set, n=156; internal validation set, n=39; external validation set, n=83) with solitary HCC (208 [75%] with positive GPC-3 expression) were included. Serum alpha-fetoprotein >10 ng/ml (AFP, odds ratio [OR]=2.3, four points) and five EOB-MR imaging features, including tumor size >3.0cm (OR=0.5, -3 points), nonperipheral “washout” (OR=3.0, five points), infiltrative appearance (OR=9.3, 10 points), marked diffusion restriction (OR=3.3, five points), and iron sparing in solid mass (OR=0.2, -7 points) were significantly associated with positive GPC-3 expression. The optimal threshold of scoring system for predicting GPC-3 positive expression was 5.5 points, with AUC 0.726 and 0.681 on the internal and external validation sets, respectively.ConclusionBased on serum AFP and five EOB-MRI features, we developed an easy-to-use and noninvasive risk score which could accurately predict positive GPC-3 HCC, which may help identify potential responders for GPC-3-targeted immunotherapy.

Cardiomyocyte differentiation derived from embryonic stem cells (ESCs) is a complex process involving molecular regulation of multiple levels. In this study, we first identify and compare differentially expressed gene (DEG) signatures of ESC-derived cardiomyocyte differentiation (ESCDCD) in humans and mice. Then, the multiscale embedded gene co-expression network analysis (MEGENA) of the human ESCDCD dataset is performed to identify 212 significantly co-expressed gene modules, which capture well the regulatory information of cardiomyocyte differentiation. Three modules respectively involved in the regulation of stem cell pluripotency, Wnt, and calcium pathways are enriched in the DEG signatures of the differentiation phase transition in the two species. Three human-specific cardiomyocyte differentiation phase transition modules are identified. Moreover, the potential regulation mechanisms of transcription factors during cardiomyocyte differentiation are also illustrated. Finally, several novel key drivers of ESCDCD are identified with the evidence of their expression during mouse embryonic cardiomyocyte differentiation. Using an integrative network analysis, the core molecular signatures and gene subnetworks (modules) underlying cardiomyocyte lineage commitment are identified in both humans and mice. Our findings provide a global picture of gene-gene co-regulation and identify key regulators during ESCDCD.

Abstract Background Low temperature limits the growth and development and geographical distribution of plants. Poa pratensis is a cool-season turfgrass mainly grown in urban areas. However, low winter temperature or cold events in spring and autumn may cause P.pratensis mortality, affecting the appearance of lawns. P.pratensis var. anceps cv. Qinghai (PQ) is widely distributed in the Qinghai-Tibet Plateau above 3000 m. PQ has greater cold tolerance than the commercially cultivated P.pratensis varieties. However, existing studies on the response mechanism of PQ to low temperatures have mainly focused on physiological and biochemical perspectives, while changes in the PQ transcriptome during the response to cold stress have not been reported. Results To investigate the molecular mechanism of the PQ cold response and identify genes to improve the low-temperature tolerance of P.pratensis, we analyzed and compared the transcriptomes of PQ and the cold-sensitive P.pratensis cv. ‘Baron’ (PB) under cold stress using RNA sequencing. We identified 5996 and 3285 differentially expressed genes (DEGs) between the treatment vs control comparison of PQ and PB, respectively, with 5612 DEGs specific to PQ. Based on the DEGs, important Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, such as “starch and sucrose metabolism”, “protein processing in endoplasmic reticulum”, “phenylalanine metabolism” and “glycolysis/gluconeogenesis” were significantly enriched in PQ, and “starch and sucrose metabolism”, “phenylpropanoid biosynthesis”, “galactose metabolism” and “glutathione metabolism” were significantly enriched in PB. In addition, the “glycolysis” and “citrate cycle (TCA cycle)” pathways were identified as involved in cold tolerance of P.pratensis. Conclusions As we know, this is the first study to explore the transcriptome of P.pratensis var. anceps cv. Qinghai. Our study not noly provides important insights into the molecular mechanisms of P.pratensis var. anceps cv. Qinghai responds to cold stress, but also systematically reveals the changes of key genes and products of glycolysis and TCA cycle in response to cold stress, which is conductive to the breeding of cold-tolerance P.pratensis genotype.

ObjectiveEarly detection and diagnosis of hepatocellular carcinoma (HCC) is essential for prognosis; however, the imaging hallmarks for tumor detection and diagnosis has remained the same for years despite the use of many new immerging imaging methods. This study aimed to evaluate the detection performance of hepatic nodules in high risk patients using either hepatobiliary specific contrast (HBSC) agent or extracellular contrast agent (ECA), and further to compare the diagnostic performances for hepatocellular carcinoma (HCC) using different diagnostic criteria with the histopathological results as reference standard.MethodsThis prospective study included 247 nodules in 222 patients (mean age, 53.32 ± 10.84 years; range, 22–79 years). The detection performance and imaging features of each nodule were evaluated in all MR sequences by three experienced abdominal radiologists. The detection performance of each nodule on all MR sequences were compared and further the diagnostic performance of various diagnostic criteria were evaluated.ResultsFor those patients who underwent ECA-MRI, the conventional imaging hallmark of “AP + PVP and/or DP” was recommended, as 60.19% diagnostic sensitivity, 80.95% specificity and 100% lesion detection rate. Additionally, for those patients who underwent HBSC-MRI, the diagnostic criteria of “DWI + HBP” was recommended. This diagnostic criteria demonstrated, both in all tumor size and for nodules ≤2 cm, higher sensitivity (93.07 and 90.16%, all p 0.05, respectively) than that of the European Association for the Study of the Liver (EASL) criteria.ConclusionsDifferent abbreviated MR protocols were recommended for patients using either ECA or HBSC. These provided imaging settings demonstrated high lesion detection rate and diagnostic performance for HCC.

The production of alloys with high strength and toughness concurrently is still a difficult challenge. Here, we designed a simple solution-ageing heat treatment system to control the morphology and density of α in Ti-15Mo-3Al-2.7Nb-0.2Si via different heat treatment temperatures. The experimental results show that Ti-15Mo-3Al-2.7Nb-0.2Si exhibits a synergistic combination of tensile strength (1364 MPa), plasticity (7.8% elongation), and fracture toughness (101 MPa·m1/2) through solutions in the α/β biphasic region and duplex ageing. Notably, the strength of the alloy after the second step of the ageing process is increased by 15% compared with that after the first step of the ageing process. However, there is less than a 5% reduction in the fracture toughness. TEM observations show that the matrix continues to precipitate denser secondary α during duplex ageing, which causes the strength to increase significantly and causes the fracture toughness to weaken. Our work may provide a novel method to optimize the mechanical properties of alloys by controlling the precipitates.

The crystal structure has a great influence on mechanical sensitivity and detonation performance of energetic materials. An efficient microfluidic platform was applied for size, morphology, and crystallinity controllable preparation of ultrafine HMX. The microfluidic platform has good mixing performance, quick response, and less reagent consumption. The ultrafine γ-HMX was first prepared at room temperature by microfluidic strategy, and the crystal type can be controlled accurately by adjusting the process parameters. With the increase in flow ratio, the particle size decreases gradually, and the crystal type changed from β-HMX to γ-HMX. Thermal behavior of ultrafine HMX shows that γ→δ is easier than β→δ, and the phase stability of HMX is β > γ > δ. Furthermore, the ultrafine β-HMX has higher thermal stability and energy release efficiency than that of raw HMX. The ultrafine HMX prepared by microfluidic not only has uniform morphology and narrow particle size distribution, but also exhibits high density and low sensitivity. This study provides a safe, facile, and efficient way of controlling particle size, morphology, and crystallinity of ultrafine HMX.

1,3,5-trinitro-1,3,5-triazacyclohexane (RDX) is a type of high energy explosive, its application in weapon systems is limited by its high mechanical sensitivity. At the same time, 1,1-diamino-2,2-dinitroethylene (FOX-7) is a famous insensitive explosive. The preparation of RDX@FOX-7 composites can meet the requirements, high energy and low sensitivity, of the weapon systems. It is difficult for the reactor to achieve uniform quality of composite material, which affects its application performance. Based on the principle of solvent-anti-solvent, the recrystallization process was precisely controlled by microfluidic technology. The RDX@FOX-7 composites with different mass ratios were prepared. At the mass ratio of 10%, the RDX@FOX-7 composites are ellipsoid of about 15 μm with uniform distribution and quality. The advantages of microscale fabrication of composite materials were verified. The results of structure characterization showed that there is no new bond formation in RDX@FOX-7, but the distribution of two components on the surface of the composite was uniform. Based on the structure characterization, we established the structure model of RDX@RDX-7 and speculated the formation process of the composites in microscale. With the increase of FOX-7 mass ratios, the melting temperature of RDX was advanced, the thermal decomposition peak of RDX changed to double peaks, and the activation energy of RDX@FOX-7 composite decreased. These changes were more pronounced between 3 and 10% but not between 10 and 30%. The ignition delay time of RDX@FOX-7 was shorter than that of RDX and FOX-7. RDX@FOX-7 burned more completely than RDX indicating that FOX-7 can assist heat transfer and improve the combustion efficiency of RDX.

Abstract Background The Liver Imaging Reporting and Data System (LI-RADS) and European Association for the Study of the Liver (EASL) criteria are widely used for diagnosing hepatocellular carcinoma (HCC). Radiomics allows further quantitative tumor heterogeneity profiling. This study aimed to compare the diagnostic accuracies of the version 2018 (v2018) EASL, LI-RADS criteria and radiomics models for HCC in high-risk patients. Methods Ethical approval by the institutional review board and informed consent were obtained for this study. From July 2015 to September 2018, consecutive high-risk patients were enrolled in our tertiary care hospital and underwent gadoxetic acid-enhanced magnetic resonance (MR) imaging and subsequent hepatic surgery. We constructed a multi-sequence-based three-dimensional whole-tumor radiomics signature by least absolute shrinkage and selection operator model and multivariate logistic regression analysis. The diagnostic accuracies of the radiomics signature was validated in an independent cohort and compared with the EASL and LI-RADS criteria reviewed by two independent radiologists. Results Two hundred twenty-nine pathologically confirmed nodules (173 HCCs, mean size: 5.74 ± 3.17 cm) in 211 patients were included. Among them, 201 patients (95%) were infected with hepatitis B virus (HBV). The sensitivity and specificity were 73 and 71% for the radiomics signature, 91 and 71% for the EASL criteria, and 86 and 82% for the LI-RADS criteria, respectively. The areas under the receiver operating characteristic curves (AUCs) of the radiomics signature (0.810), LI-RADS (0.841) and EASL criteria (0.811) were comparable. Conclusions In HBV-predominant high-risk patients, the multi-sequence-based MR radiomics signature, v2018 EASL and LI-RADS criteria demonstrated comparable overall accuracies for HCC.

Abstract Immune checkpoint blockade (ICB) represents a promising approach in cancer therapy. Owing to the peculiar biologic mechanisms of anticancer activity, checkpoint blockers are accompanied with distinctive response patterns and toxicity profiles. Medical imaging is the cornerstone for response assessment to immunotherapy and plays a critical role in monitoring of immune‐related adverse events (irAEs). Imaging‐based biomarkers have shown tremendous potential for the prediction of therapeutic efficacies and clinical outcomes in patients treated with checkpoint inhibitors. In this article, the landscape of current response assessment systems for immunotherapy was reviewed with a special focus on the latest advances in the assessment of responses to ICB. Emerging imaging biomarkers were discussed along with the challenges regarding their clinical transformation. In addition, the biological mechanisms and clinical applications of ICB and irAEs were also within the scope of this review.

Abstract Background This study was performed to prospectively develop and validate a radiomics nomogram for predicting postoperative early recurrence (≤1 year) of hepatocellular carcinoma (HCC) using whole-lesion radiomics features on preoperative gadoxetic acid-enhanced magnetic resonance (MR) images. Methods In total, 155 patients (training cohort: n = 108; validation cohort: n = 47) with surgically confirmed HCC were enrolled in this IRB-approved prospective study. Three-dimensional whole-lesion regions of interest were manually delineated along the tumour margins on multi-sequence MR images. Radiomics features were generated and selected to build a radiomics score using the least absolute shrinkage and selection operator (LASSO) method. Clinical characteristics and qualitative imaging features were identified by two independent radiologists and combined to establish a clinical-radiological nomogram. A radiomics nomogram comprising the radiomics score and clinical-radiological risk factors was constructed based on multivariable logistic regression analysis. Diagnostic performance and clinical usefulness were measured by receiver operation characteristic (ROC) and decision curves. Results In total, 14 radiomics features were selected to construct the radiomics score. For the clinical-radiological nomogram, the alpha-fetoprotein (AFP) level, gross vascular invasion and non-smooth tumour margin were included. The radiomics nomogram integrating the radiomics score with clinical-radiological risk factors showed better discriminative performance (AUC = 0.844, 95%CI, 0.769 to 0.919) than the clinical-radiological nomogram (AUC = 0.796, 95%CI, 0.712 to 0.881; P = 0.045), with increased clinical usefulness confirmed using a decision curve analysis. Conclusions Incorporating multiple predictive factors, the radiomics nomogram demonstrated great potential in the preoperative prediction of early HCC recurrence after surgery.

Gastric cancer (GC) is one of the most common cancers and one of the leading causes of cancer-related death worldwide. Precise diagnosis and evaluation of GC, especially using noninvasive methods, are fundamental to optimal therapeutic decision-making. Despite the recent rapid advancements in technology, pretreatment diagnostic accuracy varies between modalities, and correlations between imaging and histological features are far from perfect. Artificial intelligence (AI) techniques, particularly hand-crafted radiomics and deep learning, have offered hope in addressing these issues. AI has been used widely in GC research, because of its ability to convert medical images into minable data and to detect invisible textures. In this article, we systematically reviewed the methodological processes (data acquisition, lesion segmentation, feature extraction, feature selection, and model construction) involved in AI. We also summarized the current clinical applications of AI in GC research, which include characterization, differential diagnosis, treatment response monitoring, and prognosis prediction. Challenges and opportunities in AI-based GC research are highlighted for consideration in future studies.

Purpose: To assess the performance of T1 mapping and residual liver volume (RLV) on Gd-EOBDTPA-enhanced MRI in pretreatment estimation of liver function in patients with liver tumors. Indocyanine green retention rate at 15 min (ICG R-15) was used as a reference standard.Methods: Ethical approval from the institutional review board and informed consent were obtained for this prospective study. We enrolled 155 patients with liver tumors who underwent pretreatment Gd-EOB-DTPA-enhanced MRI. T1 relaxation time before (T1-pre), 20 min after (T1-post) Gd-EOB-DTPA injection and RLV were measured. The absolute reduction (ΔT1) and reduction rate (ΔT1%) of T1 relaxation time, volume-assisted ΔT1 (ΔT1*RLV) and volume-assisted ΔT1% (ΔT1%*RLV) were calculated accordingly. The correlation of MR parameters with ICG R-15 was determined using Spearman's rank correlation analysis. Patients were classified into the normal liver function (NLF) group if their ICG R-15 levels were

A computer-aided diagnosis (CAD) system based on mammograms enables early breast cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD systems remains unsatisfactory. This paper explores a breast CAD method based on feature fusion with convolutional neural network (CNN) deep features. First, we propose a mass detection method based on CNN deep features and unsupervised extreme learning machine (ELM) clustering. Second, we build a feature set fusing deep features, morphological features, texture features, and density features. Third, an ELM classifier is developed using the fused feature set to classify benign and malignant breast masses. Extensive experiments demonstrate the accuracy and efficiency of our proposed mass detection and breast cancer classification method.

This study presents a strategy for the preparation of multiscale α phase by high/low-temperature two-step aging in metastable β titanium alloy, Ti-15Mo-3Al-2.7Nb-0.2Si. The purpose of high-temperature aging is to obtain a number of micro-scale secondary α phases (αS), besides precipitation-free zones (PFZs). After that, in the second stage of low-temperature aging, the nano-scale tertiary α phase (αT) precipitates in the PFZs. The second-step aging temperature and the time at low temperature will have an important effect on αT. On the one hand, with the extension of aging time, the morphology of αT changes from dot-like to needle-like. Secondly, the increase of the second-step aging temperature will promote precipitation of αT in PFZs. The strength increases gradually with the accelerated precipitation of αT, and good plasticity is still maintained. The effect of multiscale α on fracture behavior was investigated by in situ tensile testing. Results show that cracks form a transgranular fracture along the slip line after solution treatment. After first-step aging, the crack easily passes through αS and forms an intergranular fracture. After second-step aging, the formation of multiscale α phase has a stronger effect in hindering the crack growth, which leads to crack propagation mainly by transgranular fracture. Overall, this study demonstrates that the alloy can be heat-treated to achieve an excellent match between strength and ductility, which is expected to meet the application requirements of structural materials of the new generation of aircraft.

Nitrogen-doped carbon-supported metal nano-particles show great promise as high-performance catalysts for novel energies, organic synthesis, environmental protection, and other fields. The synergistic effect between nitrogen-doped carbon and metal nano-particles enhances the catalytic properties. Thus, how to effectively combine nitrogen-doped carbon with metal nano-particles is a crucial factor for the synthesis of novel catalysts. In this paper, we report on a facile method to prepare nitrogen-doped carbon-supported metal nano-particles by using dimethylgly-oxime as ligand. The nano-particles of Pd, Ni, Cu, and Fe were successfully prepared by the pyrolysis of the corresponding clathrate of ions and dimethylglyoxime. The ligand of dimethylglyoxime is adopted as the source for the nitrogen-doped carbon. The nano-structure of the prepared Pd, Ni, Cu, and Fe particles are confirmed by X-ray diffraction, scanning electron microscopy, and trans-mission electron microscopy tests. The catalytic performances of the obtained metal nano-particles for oxygen reduction reaction (ORR) are investigated by cyclic voltammetry, Tafel, linear sweeping voltammetry, rotating disc electrode, rotating ring disc electrode, and other technologies. Results show that the nitrogen-doped carbon-supported metal nano-particles can be highly efficient catalysts for ORR. The results of the paper exhibit a facile methodology to prepare nitrogen-doped carbon-supported metal nano-particles.