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Cancer-associated fibroblasts (CAFs) are involved in tumor growth, angiogenesis, metastasis, and resistance to therapy. We sought to explore the CAFs characteristics in hepatocellular carcinoma (HCC) and establish a CAF-based risk signature for predicting the prognosis of HCC patients. The signal-cell RNA sequencing (scRNA-seq) data was obtained from the GEO database. Bulk RNA-seq data and microarray data of HCC were obtained from the TCGA and GEO databases respectively. Seurat R package was applied to process scRNA-seq data and identify CAF clusters according to the CAF markers. Differential expression analysis was performed to screen differentially expressed genes (DEGs) between normal and tumor samples in TCGA dataset. Then Pearson correlation analysis was used to determine the DEGs associated with CAF clusters, followed by the univariate Cox regression analysis to identify CAF-related prognostic genes. Lasso regression was implemented to construct a risk signature based on CAF-related prognostic genes. Finally, a nomogram model based on the risk signature and clinicopathological characteristics was developed. Based on scRNA-seq data, we identified 4 CAF clusters in HCC, 3 of which were associated with prognosis in HCC. A total of 423 genes were identified from 2811 DEGs to be significantly correlated with CAF clusters, and were narrowed down to generate a risk signature with 6 genes. These six genes were primarily connected with 39 pathways, such as angiogenesis, apoptosis, and hypoxia. Meanwhile, the risk signature was significantly associated with stromal and immune scores, as well as some immune cells. Multivariate analysis revealed that risk signature was an independent prognostic factor for HCC, and its value in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the stage and CAF-based risk signature was constructed, which exhibited favorable predictability and reliability in the prognosis prediction of HCC. CAF-based risk signatures can effectively predict the prognosis of HCC, and comprehensive characterization of the CAF signature of HCC may help to interpret the response of HCC to immunotherapy and provide new strategies for cancer treatment.

N-staging is a determining factor for prognostic assessment and decision-making for stage-based cancer therapeutic strategies. Visual inspection of whole-slides of intact lymph nodes is currently the main method used by pathologists to calculate the number of metastatic lymph nodes (MLNs). Moreover, even at the same N stage, the outcome of patients varies dramatically. Here, we propose a deep-learning framework for analyzing lymph node whole-slide images (WSIs) to identify lymph nodes and tumor regions, and then to uncover tumor-area-to-MLN-area ratio (T/MLN). After training, our model’s tumor detection performance was comparable to that of experienced pathologists and achieved similar performance on two independent gastric cancer validation cohorts. Further, we demonstrate that T/MLN is an interpretable independent prognostic factor. These findings indicate that deep-learning models could assist not only pathologists in detecting lymph nodes with metastases but also oncologists in exploring new prognostic factors, especially those that are difficult to calculate manually. The ratio of tumour area to metastatic lymph node area (T/MLN) is a clinical indicator that can improve prognosis prediction of gastric cancer. Here, the authors use machine learning on whole slide images to generate a method that can predict metastatic lymph nodes and obtain T/MLN.

There is increasing evidence that eye diseases and stroke frequently co-occur, but the causal relationships remain elusive. Therefore, Mendelian randomization was used to investigate possible causal relationships between eye diseases and stroke (including its subtypes). This study utilized large-scale genome-wide association study pooled genetic data from two major databases: the IEU OpenGWAS project and the FinnGen databases. We then screened for instrumental variables that met the following three conditions: showing strong associations with the exposure factors, being independent of each other and independent of any confounders, and excluding instrumental variables to ensure that the F-value was greater than 10, and used the Inverse Variance Weighted (IVW) method to conduct causal analyses using the weighted median method, MR-Egger method, MR- PRESSO test and leave-one-out sensitivity test to test the robustness, heterogeneity and horizontal pleiotropy of the results. In order to control for the false positive rate in multiple hypothesis testing, a False Discovery Rate (FDR) correction was also performed. A total of 16 eye diseases and strokes and their subtypes were investigated in this study. In the IVW model, the MR study showed a total of 20 IVWs with p-values less than 0.05. We excluded 6 results with heterogeneity or pleiotropy by sensitivity analysis, and finally the following reliable results were left: (1) patients with age-related macular degeneration had a 5%, 2%, and 7% lower risk of subarachnoid hemorrhage, ischemic stroke, and small-vessel stroke; (2) patients with keratitis had a 12% higher risk of cardioembolic; (3) patients with optic atrophy had a 3% higher risk of stroke; (4) patients with amblyopia had a 3% higher risk of stroke; and (5) patients with other inflammation of eyelid had a small-vessel had a 20% elevated risk; (6) patients with ptosis of the eye had a 17% elevated risk of cardioembolic; (7) patients with strabismus have a 23% elevated risk of small-vessel; (8) patients with stroke had a refractive error by 17%; (9) patients with intracerebral hemorrhage had a 15% increased risk of uveitis; (10) patients with IS had an 11% increased risk of diabetic retinopathy; (11) patients with large-artery atherosclerosis had a 2% increased risk of glaucoma; (12) patients with cardioembolic had a 24% increased risk of amblyopia. From a genetic standpoint, keratitis, amblyopia, other eyelid inflammations, ptosis and strabismus are associated with increased risks of the risk of stroke or its subtypes. Conversely, age-related macular degeneration is associated with reduced risks of the risk of stroke or its subtypes. Furthermore, stroke or its subtypes increase the risks of refractive error, uveitis, diabetic retinopathy, glaucoma, and amblyopia. Nevertheless, it is imperative that these causal relationships be subjected to further verification through fundamental research and Randomized Controlled Trial (RCT).

BACKGROUND: Traditional sacroiliac joint (SIJ) provocation tests have been used to diagnose SIJ pain. However, this can simply be changed to chronic SIJ dysfunction (cSIJD) manifests as mechanical changes in the pelvis and lower extremities in addition to pain. A novel composite of physical examinations based on the iliac pronation, pubic tubercle tenderness, and plantar fascia tenderness tests (IPP triple tests) was designed for the diagnosis of cSIJD. OBJECTIVES: To evaluate IPP triple tests in the diagnosis of cSIJD and differential diagnosis from lumbar disc herniation (LDH) in comparison with traditional provocation tests. STUDY DESIGN: Prospective single-blind controlled study. SETTING: This study was conducted at the Department of Spine and Spinal Cord Surgery of China Rehabilitation Research Center in Beijing, China. METHODS: One hundred and sixty-six patients were assigned into the cSIJD group, LDH group, or healthy control group. The cSIJD diagnosis was confirmed by SIJ injection. The diagnosis of LDH was confirmed according to the 2014 North American Spine Association diagnosis and treatment guidelines for LDH. All patients were examined with IPP triple tests and traditional provocation tests. The sensitivity, specificity, positive and negative likelihood ratios, and areas under the curve (AUCs) were used to evaluate the diagnostic accuracy of the composites or single of the IPP triple tests, and traditional provocation tests. The Delong’s test was used for the comparison among AUCs. The kappa analysis was used for the IPP triple tests and traditional provocation tests compared with the reference standard (REF). The independent t test and chi-square test were used to analyze the influence factors (i.e., age, gender), and group on diagnostic accuracy. RESULTS: There was no statistical difference in gender (chi-squared = 0.282, P = 0.596) and age (F = 0.096, P = 0.757) between the 3 groups. The AUC of the iliac pronation test was 0.903 when it was used alone; the AUC of the novel composites of the IPP triple tests was 0.868 (95% confidence interval [CI] = 0.802-0.919); and the diagnostic accuracy of the traditional provocation test was relatively low (AUC = 0.597, 95% CI = 0.512-0.678). The diagnostic accuracy of the IPP triple tests was higher than that of the traditional provocation test, P < 0.05. Kappa consistency comparison showed that the kappa value between the IPP triple tests and the REF was 0.229, the kappa between the traditional provocation test and the REF was 0.052. The age of the patients with inaccurate diagnosis was higher than that of the patients with accurate diagnosis in both methods (traditional tests, P = 0.599; IPP:P = 0.553). Different types of diseases (groups) affect the accuracy of diagnosis, the proportion of inaccuracy of traditional provocation tests was higher than that of the IPP triple tests (77.8% vs 23.6%) in cSIJD, while the 2 methods have high differential diagnostic accuracy in LDH (96.77%) and control groups (97.56%). LIMITATIONS: Small size of LDH patients and differences in physical tests among examiners. CONCLUSIONS: The novel composites of IPP triple tests have higher accuracy than the traditional provocation tests in diagnosing cSIJD and both have good accuracy in differentiating cSIJD from LDH. IPP triple tests may be an alternative physical examination for clinical screening of cSIJD. KEY WORDS: Sacroiliac joint dysfunction, low back pain, lumbar disc herniation, provocation test, physical examination, kinematics

Tissue sampling of biliary tract carcinomas (BTCs) for molecular characterization is challenging. The aim of this study was to investigate the possibility of identifying individual actionable mutations derived from bile cell-free DNA (cfDNA) using targeted deep sequencing. Ten BTC patients, four with gallbladder carcinomas and six with cholangiocarcinomas, were enrolled in the present study. Using targeted deep sequencing with a panel of 150 tumor-related genes, paired bile cfDNA and tumor DNA were analyzed for mutational variants individually and then compared. The present study, to the best of our knowledge, is the first to reveal that bile cfDNA is predominantly comprised of long DNA fragments, which is not the case for plasma cfDNA. Herein, paired bile cfDNA and tumors from ten BTC patients were examined using targeted deep sequencing. When comparing bile cfDNA and tumor DNA for single nucleotide variation (SNV)/insertion and deletion (Indel), the results using targeted deep sequencing revealed high sensitivity (94.7%) and specificity (99.9%). Additionally, the sensitivity of detecting a copy number variation (CNV) was 75.0%, with a specificity of 98.9%. When comparing two bile extraction methods, including percutaneous transhepatic cholangial drainage and operation, no significant difference in SNV/Indel or CNV detection sensitivity was noted. Moreover, when examining the tumor stage and incidence site, AJCC stage II and the distal bile duct both had significantly decreased CNV detection sensitivities. The present study revealed that targeted deep sequencing can reliably detect mutational variants within bile cfDNA obtained from BTC patients. These preliminary results may shed light on bile cfDNA as a promising liquid biopsy for BTC patients.

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas.

While the Agreement under the United Nations Convention on the Law of the Sea on the Conservation and Sustainable Use of Marine Biological Diversity of Areas Beyond National Jurisdiction (BBNJ Agreement) has pioneered the establishment of a benefit-sharing regime for marine genetic resources (MGRs), persistent divergences between developing and developed countries have posed substantial challenges to its implementation. The current legal framework is overly schematic and insufficient to guide practice, leaving many issues unresolved. To explore the solutions for these issues, this article adopts a legal functionalist approach grounded in the principle that “form follows function”. First, this article categorizes the unresolved issues into four types: ambiguous terms in the Agreement, uncertain legal nature of benefit-sharing modalities, weak operability resulting from incomplete guiding rules, and inadequate monitoring rules. Second, it derives potential solutions from a legal functionalist perspective. This approach emphasizes the instrumental value or functionality of law. By focusing on facilitating the achievement of the Agreement’s intended functions and goals, this approach can help steer ongoing international rule-making activities and overcome negotiation deadlocks. Under such an approach, the core guiding principle for problem solving is to make rules operational by addressing conflicts, giving due regard to diverse concerns, and fostering broad consensus among negotiating parties. Finally, this article tentatively applies this approach to specific unresolved issues, including: adopting broader definitions of key terms; designing relatively light monetary benefit-sharing rules that combine mandatory and voluntary mechanisms; facilitating ex situ access through multilateral mechanisms; clearly delineating the respective scope of application of different technology transfer modalities; and strengthening supporting information disclosure and traceability rules. Concurrently, this article suggests that the design and implementation of rules should take into account the needs of marine scientific research, data confidentiality, financial and administrative burdens, and the legitimate rights and interests of stakeholders.

Background Percutaneous endoscopic lumbar discectomy (PELD) is a promising minimally invasive treatment for lumbar disc herniation (LDH). Postoperative rehabilitation can improve patient outcomes. Not only rehabilitation for surgical trauma but also rehabilitation for lumbar spine and lower kinetic chain dysfunction should be performed. The aims of this study were to investigate the efficacy of a lumbar kinetic chain training for staged rehabilitation after PELD for LDH. Methods Fifty one LDH patients treated with PELD were studied. After surgery, patients underwent lumbar kinetic chain training for staged rehabilitation( staged group) or regular low back rehabilitation (regular group). The staged rehabilitation programme included three phases from 2 to 6, 7–12, and 13–24 weeks postoperatively, and different physical therapies were performed during these phases. The low back pain visual analogue scale (VAS), JOA score, ODI, SF-36, and cross-sectional area of the lumbar multifidus on MRI were assessed, and gait analysis was performed. Results Twenty five patients in staged group and twenty six patients in regular group were included. There were no significant differences in age or sex between the two groups at baseline ( p  > 0.05). The VAS score decreased and the JOA and SF-36 scores increased in both groups from baseline to 6 weeks ( P  < 0.05). In the staged group, compared with the regular group, the VAS and ODI scores were lower and the JOA and SF-36 scores were higher at 6 weeks ( P  < 0.05); the VAS and ODI scores were lower and the SF-36 score was higher at 12 weeks ( P  < 0.05); the SF-36 score was higher at 24 weeks ( P  < 0.05); the cross-sectional area of the lumbar multifidus showed no differences at 12 weeks ( P  > 0.05); and the left-right support ratio of gait was higher at 24 weeks ( P  < 0.05). Conclusions The staged rehabilitation programme for LDH after PELD promoted postoperative recovery, and the efficacy of lumbar kinetic chain training was higher than that of regular low back muscle exercise.

Background Postmenopausal women face a heightened risk of developing new vertebral compression fractures (NVCFs) following percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures (OVCFs). This study aimed to develop and validate a visual nomogram model capable of accurately predicting NVCF occurrence post-PKP to optimize treatment strategies and minimize occurrence. Methods This retrospective study included postmenopausal women diagnosed with OVCF who underwent PKP at the Affiliated Hospital of Shandong University of Traditional Chinese Medicine between January 2016 and January 2021. Patient data, including basic information, surgical details, imaging records, and laboratory findings, were collected. The patients were categorized into two groups based on NVCF occurrence within 2 years post-PKP: the NVCF group and the non-NVCF group. Following the utilization of least absolute shrinkage and selection operator (LASSO) regression for feature selection, a nomogram was constructed. Model differentiation, calibration, and clinical applicability were evaluated using receiver operating characteristic (ROC), calibration, and decision (DCA) curve analyses. Results In total, 357 patients were included in the study. LASSO regression analysis indicated that cement leakage, poor cement diffusion, and endplate fracture were independent predictors of NVCF. The nomogram demonstrated excellent predictive accuracy and clinical applicability. Conclusions This study used LASSO regression to identify three independent predictors of NVCF and developed a predictive model that could effectively predict NVCF occurrence in postmenopausal women. This simple prediction model can support medical decision-making and is feasible for clinical practice.

Phytophthora nicotianae is highly pathogenic to Solanaceous crops and is a major problem in tobacco production. The tobacco cultivar Beihart1000-1 (BH) is resistant, whereas the Xiaohuangjin 1025 (XHJ) cultivar is susceptible to infection. Here, BH and XHJ were used as models to identify resistant and susceptible genes using RNA sequencing (RNA-seq). Roots were sampled at 0, 6, 12, 24, and 60 h post infection. In total, 23,753 and 25,187 differentially expressed genes (DEGs) were identified in BH and XHJ, respectively. By mapping upregulated DEGs to the KEGG database, changes of the rich factor of “plant pathogen interaction pathway” were corresponded to the infection process. Of all the DEGs in this pathway, 38 were specifically regulated in BH. These genes included 11 disease-resistance proteins, 3 pathogenesis-related proteins, 4 RLP/RLKs , 2 CNGCs , 7 calcium-dependent protein kinases, 4 calcium-binding proteins, 1 mitogen-activated protein kinase kinase, 1 protein EDS1L , 2 WRKY transcription factors, 1 mannosyltransferase, and 1 calmodulin-like protein. By combining the analysis of reported susceptible ( S ) gene homologs and DEGs in XHJ, 9 S gene homologs were identified, which included 1 calmodulin-binding transcription activator, 1 cyclic nucleotide-gated ion channel, 1 protein trichome birefringence-like protein, 1 plant UBX domain-containing protein, 1 ADP-ribosylation factor GTPase-activating protein, 2 callose synthases, and 2 cellulose synthase A catalytic subunits. qRT-PCR was used to validate the RNA-seq data. The comprehensive transcriptome dataset described here, including candidate resistant and susceptible genes, will provide a valuable resource for breeding tobacco plants resistant to P. nicotianae infections.