Search

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.