Predicting hepatocellular carcinoma: A new non-invasive model based on shear wave elastography.

BACKGROUND: Integrating conventional ultrasound features with 2D shear wave elastography (2D-SWE) can potentially enhance preoperative hepatocellular carcinoma (HCC) predictions. AIM: To develop a 2D-SWE-based predictive model for preoperative identification of HCC. METHODS: A retrospective analysis of 884 patients who underwent liver resection and pathology evaluation from February 2021 to August 2023 was conducted at the Oriental Hepatobiliary Surgery Hospital. The patients were divided into the modeling group (n = 720) and the control group (n = 164). The study included conventional ultrasound, 2D-SWE, and preoperative laboratory tests. Multiple logistic regression was used to identify independent predictive factors for malignant liver lesions, which were then depicted as nomograms. RESULTS: In the modeling group analysis, maximal elasticity (Emax) of tumors and their peripheries, platelet count, cirrhosis, and blood flow were independent risk indicators for malignancies. These factors yielded an area under the curve of 0.77 (95% confidence interval: 0.73-0.81) with 84% sensitivity and 61% specificity. The model demonstrated good calibration in both the construction and validation cohorts, as shown by the calibration graph and Hosmer-Lemeshow test (P = 0.683 and P = 0.658, respectively). Additionally, the mean elasticity (Emean) of the tumor periphery was identified as a risk factor for microvascular invasion (MVI) in malignant liver tumors (P = 0.003). Patients receiving antiviral treatment differed significantly in platelet count (P = 0.002), Emax of tumors (P = 0.033), Emean of tumors (P = 0.042), Emax at tumor periphery (P < 0.001), and Emean at tumor periphery (P = 0.003). CONCLUSION: 2D-SWE's hardness value serves as a valuable marker for enhancing the preoperative diagnosis of malignant liver lesions, correlating significantly with MVI and antiviral treatment efficacy.

Landscape and Treatment Options of Shapeshifting Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a deadly neuroendocrine malignancy, notorious for its rapid tumor growth, early metastasis, and relatively "cold" immune environment. Only standard chemotherapies and a few immune checkpoint inhibitors have been approved for SCLC treatment, revealing an urgent need for novel therapeutic approaches. Moreover, SCLC has been recently recognized as a malignancy with high intratumoral and intertumoral heterogeneity, which explains the modest response rate in some patients and the early relapse. Molecular subtypes defined by the expression of lineage-specific transcription factors (ASCL1, NEUROD1, POU2F3, and, in some studies, YAP1) or immune-related genes display different degrees of neuroendocrine differentiation, immune cell infiltration, and response to treatment. Despite the complexity of this malignancy, a few biomarkers and targets have been identified and many promising drugs are currently undergoing clinical trials. In this review, we integrate the current progress on the genomic landscape of this shapeshifting malignancy, the characteristics and treatment vulnerabilities of each subtype, and promising drugs in clinical phases.

GIWAXS experimental methods at the NFPS-BL17B beamline at Shanghai Synchrotron Radiation Facility.

The BL17B beamline at the Shanghai Synchrotron Radiation Facility was first designed as a versatile high-throughput protein crystallography beamline and one of five beamlines affiliated to the National Facility for Protein Science in Shanghai. It was officially opened to users in July 2015. As a bending magnet beamline, BL17B has the advantages of high photon flux, brightness, energy resolution and continuous adjustable energy between 5 and 23 keV. The experimental station excels in crystal screening and structure determination, providing cost-effective routine experimental services to numerous users. Given the interdisciplinary and green energy research demands, BL17B beamline has undergone optimization, expanded its range of experimental methods and enhanced sample environments for a more user-friendly testing mode. These methods include single-crystal X-ray diffraction, powder crystal X-ray diffraction, wide-angle X-ray scattering, grazing-incidence wide-angle X-ray scattering (GIWAXS), and fully scattered atom pair distribution function analysis, covering structure detection from crystalline to amorphous states. This paper primarily presents the performance of the BL17B beamline and the application of the GIWAXS methodology at the beamline in the field of perovskite materials.

Upgrade of crystallography beamline BL19U1 at the Shanghai Synchrotron Radiation Facility.

BL19U1, an energy-tunable protein complex crystallography beamline at the Shanghai Synchrotron Radiation Facility, has emerged as one of the most productive MX beamlines since opening to the public in July 2015. As of October 2023, it has contributed to over 2000 protein structures deposited in the Protein Data Bank (PDB), resulting in the publication of more than 1000 scientific papers. In response to increasing interest in structure-based drug design utilizing X-ray crystallography for fragment library screening, enhancements have been implemented in both hardware and data collection systems on the beamline to optimize efficiency. Hardware upgrades include the transition from MD2 to MD2S for the diffractometer, alongside the installation of a humidity controller featuring a rapid nozzle exchanger. This allows users to opt for either low-temperature or room-temperature data collection modes. The control system has been upgraded from Blu-Ice to MXCuBE3, which supports website-mode data collection, providing enhanced compatibility and easy expansion with new features. An automated data processing pipeline has also been developed to offer users real-time feedback on data quality.

Multi-Task Scenario Encrypted Traffic Classification and Parameter Analysis.

The widespread use of encrypted traffic poses challenges to network management and network security. Traditional machine learning-based methods for encrypted traffic classification no longer meet the demands of management and security. The application of deep learning technology in encrypted traffic classification significantly improves the accuracy of models. This study focuses primarily on encrypted traffic classification in the fields of network analysis and network security. To address the shortcomings of existing deep learning-based encrypted traffic classification methods in terms of computational memory consumption and interpretability, we introduce a Parameter-Efficient Fine-Tuning method for efficiently tuning the parameters of an encrypted traffic classification model. Experimentation is conducted on various classification scenarios, including Tor traffic service classification and malicious traffic classification, using multiple public datasets. Fair comparisons are made with state-of-the-art deep learning model architectures. The results indicate that the proposed method significantly reduces the scale of fine-tuning parameters and computational resource usage while achieving performance comparable to that of the existing best models. Furthermore, we interpret the learning mechanism of encrypted traffic representation in the pre-training model by analyzing the parameters and structure of the model. This comparison validates the hypothesis that the model exhibits hierarchical structure, clear organization, and distinct features.

Vehicle Trajectory Prediction Method for Task Offloading in Vehicular Edge Computing.

Real-time computation tasks in vehicular edge computing (VEC) provide convenience for vehicle users. However, the efficiency of task offloading seriously affects the quality of service (QoS). The predictive-mode task offloading is limited by computation resources, storage resources and the timeliness of vehicle trajectory data. Meanwhile, machine learning is difficult to deploy on edge servers. In this paper, we propose a vehicle trajectory prediction method based on the vehicle frequent pattern for task offloading in VEC. First, in the initialization stage, a T-pattern prediction tree (TPPT) is constructed based on the historical vehicle trajectory data. Secondly, when predicting the vehicle trajectory, the vehicle frequent itemset with the largest vehicle trajectory support is found in the vehicle frequent itemset of the TPPT. Finally, in the update stage, the TPPT is updated in real time with the predicted vehicle trajectory results. Meanwhile, based on the proposed prediction method, the strategies of task offloading and optimization algorithm are designed to minimize energy consumption with time constraints. The experiments are carried out on real-vehicle datasets and the Capital Bikeshare datasets. The results show that compared with the baseline T-pattern method, the accuracy of the prediction method is improved by more than 10% and the prediction efficiency is improved by more than 6.5 times. The vehicle trajectory prediction method based on the vehicle frequent pattern has high accuracy and prediction efficiency, which can solve the problem of vehicle trajectory prediction for task offloading.

Single-cell RNA sequencing analysis of the temporomandibular joint condyle in 3 and 4-month-old human embryos.

BACKGROUND: The temporomandibular joint (TMJ) is a complex joint consisting of the condyle, the temporal articular surface, and the articular disc. Functions such as mastication, swallowing and articulation are accomplished by the movements of the TMJ. To date, the TMJ has been studied more extensively, but the types of TMJ cells, their differentiation, and their interrelationship during growth and development are still unclear and the study of the TMJ is limited. The aim of this study was to establish a molecular cellular atlas of the human embryonic temporomandibular joint condyle (TMJC) by single-cell RNA sequencing, which will contribute to understanding and solving clinical problems. RESULTS: Human embryos at 3 and 4 months of age are an important stage of TMJC development. We performed a comprehensive transcriptome analysis of TMJC tissue from human embryos at 3 and 4 months of age using single-cell RNA sequencing. A total of 16,624 cells were captured and the gene expression profiles of 15 cell clusters in human embryonic TMJC were determined, including 14 known cell types and one previously unknown cell type, "transition state cells (TSCs)". Immunofluorescence assays confirmed that TSCs are not the same cell cluster as mesenchymal stem cells (MSCs). Pseudotime trajectory and RNA velocity analysis revealed that MSCs transformed into TSCs, which further differentiated into osteoblasts, hypertrophic chondrocytes and tenocytes. In addition, chondrocytes (CYTL1high + THBS1high) from secondary cartilage were detected only in 4-month-old human embryonic TMJC. CONCLUSIONS: Our study provides an atlas of differentiation stages of human embryonic TMJC tissue cells, which will contribute to an in-depth understanding of the pathophysiology of the TMJC tissue repair process and ultimately help to solve clinical problems.

Association between cardiopulmonary function, health-related quality of life and cognitive impairment among the older nursing home residents in Shanghai, China.

BACKGROUND: This study aimed to examine the association between cardiopulmonary function, health-related quality of life (HRQOL) and cognitive function among nursing home residents aged 80 years and over. METHODS: A nursing home-based, cross-sectional study was implemented among 677 aged over 80 years in Shanghai, China. A total of 197 participants underwent effective cardiopulmonary function examinations. Mini-Mental Status Examination (MMSE) and Short Form-36 scales (SF-36) were used to assess cognitive function and HRQOL, respectively. RESULTS: Decline in left ventricular ejection fractions (LVEF) [adjusted odds ratio (AOR), 1.98; 95% confidential interval (CI), 1.03-3.81)] and vital capacity (VC) (AOR, 2.08; 95%CI, 1.07-4.04) was associated with cognitive impairment. After adjusting confounding factors, relationships between cognitive function and physical functioning (PF) (AOR, 0.98; 95%CI, 0.97-0.99) still existed. CONCLUSIONS: Healthcare professionals should pay more attention to cardiopulmonary health and HRQOL in the nursing home residents. Actions of public health strategies focus on the improvement of cardiopulmonary function, and PF among older nursing home residents with cognitive impairment is required.

MDSN: A Module Detection Method for Identifying High-Order Epistatic Interactions.

Epistatic interactions are referred to as SNPs (single nucleotide polymorphisms) that affect disease development and trait expression nonlinearly, and hence identifying epistatic interactions plays a great role in explaining the pathogenesis and genetic heterogeneity of complex diseases. Many methods have been proposed for epistasis detection; nevertheless, they mainly focus on low-order epistatic interactions, two-order or three-order for instance, and often ignore high-order interactions due to computational burden. In this paper, a module detection method called MDSN is proposed for identifying high-order epistatic interactions. First, an SNP network is constructed by a construction strategy of interaction complementary, which consists of low-order SNP interactions that can be obtained from fast computations. Then, a node evaluation measure that integrates multi-topological features is proposed to improve the node expansion algorithm, where the importance of a node is comprehensively evaluated by the topological characteristics of the neighborhood. Finally, modules are detected in the constructed SNP network, which have high-order epistatic interactions associated with the disease. The MDSN was compared with four state-of-the-art methods on simulation datasets and a real Age-related Macular Degeneration dataset. The results demonstrate that MDSN has higher performance on detecting high-order interactions.

Differential diagnosis of different types of solid focal liver lesions using two-dimensional shear wave elastography.

BACKGROUND: The clinical management and prognosis differ between benign and malignant solid focal liver lesions (FLLs), as well as among different pathological types of malignant FLLs. Accurate diagnosis of the possible types of solid FLLs is important. Our previous study confirmed the value of shear wave elastography (SWE) using maximal elasticity (Emax) as the parameter in the differential diagnosis between benign and malignant FLLs. However, the value of SWE in the differential diagnosis among different pathological types of malignant FLLs has not been proved. AIM: To explore the value of two-dimensional SWE (2D-SWE) using Emax in the differential diagnosis of FLLs, especially among different pathological types of malignant FLLs. METHODS: All the patients enrolled in this study were diagnosed as benign, malignant or undetermined FLLs by conventional ultrasound. Emax of FLLs and the periphery of FLLs was measured using 2D-SWE and compared between benign and malignant FLLs or among different pathological types of malignant FLLs. RESULTS: The study included 32 benign FLLs in 31 patients and 100 malignant FLLs in 96 patients, including 16 cholangiocellular carcinomas (CCCs), 72 hepatocellular carcinomas (HCCs) and 12 liver metastases. Thirty-five FLLs were diagnosed as undetermined by conventional ultrasound. There were significant differences between Emax of malignant (2.21 ± 0.57 m/s) and benign (1.59 ± 0.37 m/s) FLLs (P = 0.000), and between Emax of the periphery of malignant (1.52 ± 0.39 m/s) and benign (1.36 ± 0.44 m/s) FLLs (P = 0.040). Emax of liver metastases (2.73 ± 0.99 m/s) was significantly higher than that of CCCs (2.14 ± 0.34 m/s) and HCCs (2.14 ± 0.46 m/s) (P = 0.002). The sensitivity, specificity and accuracy were 71.00%, 84.38% and 74.24% respectively, using Emax > 1.905 m/s (AUC 0.843) to diagnose as malignant and 23 of 35 (65.74%) FLLs with undetermined diagnosis by conventional ultrasound were diagnosed correctly. CONCLUSION: Malignant FLLs were stiffer than benign ones and liver metastases were stiffer than primary liver carcinomas. 2D-SWE with Emax was a useful complement to conventional ultrasound for the differential diagnosis of FLLs.

UHRF1 overexpression promotes osteosarcoma metastasis through altered exosome production and AMPK/SEMA3E suppression.

Loss-of-function mutations at the retinoblastoma (RB1) gene are associated with increased mortality, metastasis, and poor therapeutic outcome in several cancers, including osteosarcoma. However, the mechanism(s) through which RB1 loss worsens clinical outcome remains understudied. Ubiquitin-like with PHD and Ring Finger domains 1 (UHRF1) has been identified as a critical downstream effector of the RB/E2F signaling pathway that is overexpressed in various cancers. Here, we determined the role and regulatory mechanisms of UHRF1 in rendering osteosarcoma cells more aggressive. Higher UHRF1 expression correlated with malignancy in osteosarcoma cell lines, clinical samples, and genetically engineered mouse models. Gain- and loss-of-function assays revealed that UHRF1 has cell-intrinsic and extrinsic functions promoting cell proliferation, migration, invasion, angiogenesis, and metastasis. UHRF1 overexpression induced angiogenesis by suppressing AMPK activation and Semaphorin 3E (SEMA3E) expression. Further, UHRF1-mediated migration and metastasis resulted, at least in part, through altered expression of extracellular vesicles and their cargo, including urokinase-type plasminogen activator (uPA). Novel osteosarcoma genetically engineered mouse models confirmed that knocking out Uhrf1 considerably decreased metastasis and reversed the poorer survival associated with Rb1 loss. This presents a new mechanistic insight into RB1 loss-associated poor prognosis and novel oncogenic roles of UHRF1 in the regulation of angiogenesis and exosome secretion, both critical for osteosarcoma metastasis. This provides substantial support for targeting UHRF1 or its downstream effectors as novel therapeutic options to improve current treatment for osteosarcoma.

Multi-Objective Artificial Bee Colony Algorithm Based on Scale-Free Network for Epistasis Detection.

In genome-wide association studies, epistasis detection is of great significance for the occurrence and diagnosis of complex human diseases, but it also faces challenges such as high dimensionality and a small data sample size. In order to cope with these challenges, several swarm intelligence methods have been introduced to identify epistasis in recent years. However, the existing methods still have some limitations, such as high-consumption and premature convergence. In this study, we proposed a multi-objective artificial bee colony (ABC) algorithm based on the scale-free network (SFMOABC). The SFMOABC incorporates the scale-free network into the ABC algorithm to guide the update and selection of solutions. In addition, the SFMOABC uses mutual information and the K2-Score of the Bayesian network as objective functions, and the opposition-based learning strategy is used to improve the search ability. Experiments were performed on both simulation datasets and a real dataset of age-related macular degeneration (AMD). The results of the simulation experiments showed that the SFMOABC has better detection power and efficiency than seven other epistasis detection methods. In the real AMD data experiment, most of the single nucleotide polymorphism combinations detected by the SFMOABC have been shown to be associated with AMD disease. Therefore, SFMOABC is a promising method for epistasis detection.

Early pregnancy stage 1 hypertension and high mean arterial pressure increased risk of adverse pregnancy outcomes in Shanghai, China.

We aimed to evaluate the influence of early pregnancy stage 1 hypertension and mean arterial pressure (MAP) on the risk of pregnancy complications, including gestational diabetes mellitus (GDM) and adverse pregnancy outcomes. Pregnant women without early pregnancy hypertension were consecutively recruited in 2010 in Shanghai, China. Total 6104 women with blood pressure (BP) <140/90 mmHg were categorized according to early pregnancy BP and MAP levels, respectively. Multivariate adjusted logistic regression and cox regression was used to test the potential associations. Finally 313 (5.1%) pregnant women identified as stage 1 hypertension. Compared with normotensive women, women with early pregnancy stage 1 hypertension increased the risk of gestational hypertension (GH) [Adjust odds ratio (AOR) 2.295, 95% confidence interval (CI) 1.578-3.338], GDM [AOR 1.185, 95% CI 1.010-1.391], preeclampsia [AOR 2.295 95% CI 1.578-3.338], preterm delivery [AOR 1.326, 95% CI 1.026-1.713]and infants with low-birth weight [AOR 1.487, 95% CI 1.082-2.045]; Compared women with MAP < 76 mmHg, the risk of GDM increased, with an adjust hazard ratio (AHR) of 1.387 (95%CI 1.048-1.835) for 76 ≤ MAP < 88 mmHg and an AHR of 1.451 (95%CI 1.053-1.998) for MAP ≥ 88 mmHg. Especially, high MAP levels (≥ 88 mmHg) are associated with GH [AOR 2.775, 95%CI 1.805-4.266], preeclampsia [AOR 3.936, 95%CI 2.358-6.570] and preterm delivery [AOR 1.412, 95%CI 1.035-1.926]. In summary early pregnancy stage 1 hypertension is associated with adverse pregnancy outcomes. Relative higher BP levels in early pregnancy, especially elevated MAP levels should be aware by clinicians to decrease the risk of pregnancy complications.

Discovery and Development of Macrolides as Anticancer Agents.

Cancer is a life-threatening destructive disease. In the past several decades, the incidence of cancer has been dramatically increased mostly due to lifestyle changes. Chemotherapy plays an important role in the treatment of cancer, but the development of resistance against chemotherapeutic agents, the side effects, and non-specific toxicity threatens the efficiency of anticancer agents. Accordingly, it is important to develop novel anticancer drugs. Beyond the classical antibacterial activity, macrolides also demonstrated potential effects against both drug-sensitive and drug-resistant cancers through modulating diverse targets and signaling pathways, so rational design of macrolides may generate valuable therapeutic interventions for the treatment of cancers. The purpose of the present review article is to outline the current developments in macrolides with an emphasis on anticancer activity, structure-activity relationships, and mechanisms of action to lay the path for the development of novel macrolide anticancer candidates.

Association Between Blood Pressure Indicators and Stroke in Aged Population: A Community-Based Nested Case-Control Study.

BACKGROUND AND AIM: Any single discrete blood pressure (BP) measurement is not enough to estimate adverse cardiovascular events. We aim to comprehensively investigate the association between BP indicators and stroke. METHODS: An observational cohort study was conducted among 2888 Shanghai community-aged residents from 2014 to 2018, and a nested case-control study was designed to identify the association between BP indicators and stroke. In total 415 cases of stroke detected during the study period were selected as the case group and 415 non-stroke subjects, matched with factors of age and gender, were randomly selected from the cohort as control group. RESULTS: Multivariate logistic regression analysis revealed that systolic blood pressure (SBP) (adjusted odds ratio [AOR] 1.02, 95% confidence interval [CI] 1.02-1.03), pulse pressure (PP) (AOR 1.03, 95% CI 1.02-1.04), mean arterial pressure (MAP) (AOR1.02, 95% CI 1.01-1.04) and pulse pressure index (PPI) (AOR 25.68, 95% CI 3.19-206.90) increased the risk of stroke, respectively. After fitting both BP indicators and covariates, isolated abnormal SBP (AOR 2.55, 95% CI 1.74-3.72) or PP ≥50 mmHg (AOR 1.66, 95% CI 1.08-2.56) independently increased risk of stroke. CONCLUSION: Besides SBP, PP and multiple factors, assessment should be taken into account comprehensively for stroke prevention and management.

Structural and Functional Insights into an Archaeal Lipid Synthase.

The UbiA superfamily of intramembrane prenyltransferases catalyzes an isoprenyl transfer reaction in the biosynthesis of lipophilic compounds involved in cellular physiological processes. Digeranylgeranylglyceryl phosphate (DGGGP) synthase (DGGGPase) generates unique membrane core lipids for the formation of the ether bond between the glycerol moiety and the alkyl chains in archaea and has been confirmed to be a member of the UbiA superfamily. Here, the crystal structure is reported to exhibit nine transmembrane helices along with a large lateral opening covered by a cytosolic cap domain and a unique substrate-binding central cavity. Notably, the lipid-bound states of this enzyme demonstrate that the putative substrate-binding pocket is occupied by the lipidic molecules used for crystallization, indicating the binding mode of hydrophobic substrates. Collectively, these structural and functional studies provide not only an understanding of lipid biosynthesis by substrate-specific lipid-modifying enzymes but also insights into the mechanisms of lipid membrane remodeling and adaptation.

A unique DNA-binding mode of African swine fever virus AP endonuclease.

African swine fever virus (ASFV) is highly contagious and can cause lethal disease in pigs. ASFV is primarily replicated in the cytoplasm of pig macrophages, which is oxidative and caused constant damage to ASFV genome. ASFV AP endonuclease (AsfvAP) catalyzes DNA cleavage reaction at the abasic site and is a key enzyme of ASFV base excision repair (BER) system. Although it plays an essential role in ASFV survival in host cells, the basis underlying substrate binding and cleavage by AsfvAP remains unclear. Here, we reported the structural and functional studies of AsfvAP, showing that AsfvAP adopts a novel DNA-binding mode distinct from other APs. AsfvAP possesses many unique structural features, including one narrower nucleotide-binding pocket at the active site, the C16-C20 disulfide bond-containing region, and histidine-rich loop. As indicated by our mutagenesis, in vitro binding and cleavage assays, these features are important for AsfvAP to suit the acidic and oxidative environment. Owing to their functional importance, these unique features could serve as targets for designing small molecule inhibitors that could disrupt the repair process of ASFV genome and help fight against this deadly virus in the future.

Chromatin remodeling protein HELLS is critical for retinoblastoma tumor initiation and progression.

Retinoblastoma is an aggressive childhood cancer of the developing retina that initiates by biallelic RB1 gene inactivation. Tumor progression in retinoblastoma is driven by epigenetics, as retinoblastoma genomes are stable, but the mechanism(s) that drive these epigenetic changes remain unknown. Lymphoid-specific helicase (HELLS) protein is an epigenetic modifier directly regulated by the RB/E2F pathway. In this study, we used novel genetically engineered mouse models to investigate the role of HELLS during retinal development and tumorigenesis. Our results indicate that Hells-null retinal progenitor cells divide, undergo cell-fate specification, and give rise to fully laminated retinae with minor bipolar cells defects, but normal retinal function. Despite the apparent nonessential role of HELLS in retinal development, failure to transcriptionally repress Hells during retinal terminal differentiation due to retinoblastoma (RB) family loss significantly contributes to retinal tumorigenesis. Loss of HELLS drastically reduced ectopic division of differentiating cells in Rb1/p107-null retinae, significantly decreased the incidence of retinoblastoma, delayed tumor progression, and increased overall survival. Despite its role in heterochromatin formation, we found no evidence that Hells loss directly affected chromatin accessibility in the retina but functioned as transcriptional co-activator of E2F3, decreasing expression of cell cycle genes. We propose that HELLS is a critical downstream mediator of E2F-dependent ectopic proliferation in RB-null retinae. Together with the nontoxic effect of HELLS loss in the developing retina, our results suggest that HELLS and its downstream pathways could serve as potential therapeutic targets for retinoblastoma.