Network and evolutionary analysis of green tide management policies in the Yellow Sea, China.

Since 2007, persistent green tides in the Yellow Sea of China (YSC) have inflicted substantial economic and social losses. In response, the Chinese government has enacted various policies to mitigate these impacts. This study introduced an evolutionary-multiple streams framework and employed Social Network Analysis (SNA) and Text Analysis from 2007 to 2023, tracing three phases of policy development: growth (2007-2012), stability (2013-2017), and explosion (2018-2023). Findings indicated that during the growth phase, the most of the policy themes were "monitoring" and "emergency"; in the stability phase, policy issuance by provincial and municipal agencies began to increase; in the explosion phase, a basic consensus was reached on source control and intergovernmental cooperation in the management of green tides. Themes such as "ecology", "extreme weather", and "green tide exploitation" have been emphasized. This analysis provides insights for future policy formulation in green tide control and broader marine environmental governance.

PET-based radiomic feature based on the cross-combination method for predicting the mid-term efficacy and prognosis in high-risk diffuse large B-cell lymphoma patients.

Objectives: This study aims to develop 7×7 machine-learning cross-combinatorial methods for selecting and classifying radiomic features used to construct Radiomics Score (RadScore) of predicting the mid-term efficacy and prognosis in high-risk patients with diffuse large B-cell lymphoma (DLBCL). Methods: Retrospectively, we recruited 177 high-risk DLBCL patients from two medical centers between October 2012 and September 2022 and randomly divided them into a training cohort (n=123) and a validation cohort (n=54). We finally extracted 110 radiomic features along with SUVmax, MTV, and TLG from the baseline PET. The 49 features selection-classification pairs were used to obtain the optimal LASSO-LASSO model with 11 key radiomic features for RadScore. Logistic regression was employed to identify independent RadScore, clinical and PET factors. These models were evaluated using receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCA) was conducted to assess the predictive power of the models. The prognostic power of RadScore was assessed using cox regression (COX) and Kaplan-Meier plots (KM). Results: 177 patients (mean age, 63 ± 13 years,129 men) were evaluated. Multivariate analyses showed that gender (OR,2.760; 95%CI:1.196,6.368); p=0.017), B symptoms (OR,4.065; 95%CI:1.837,8.955; p=0.001), SUVmax (OR,2.619; 95%CI:1.107,6.194; p=0.028), and RadScore (OR,7.167; 95%CI:2.815,18.248; p<0.001) independently contributed to the risk factors for predicting mid-term outcome. The AUC values of the combined models in the training and validation groups were 0.846 and 0.724 respectively, outperformed the clinical model (0.714;0.556), PET based model (0.664; 0.589), NCCN-IPI model (0.523;0.406) and IPI model (0.510;0.412) in predicting mid-term treatment outcome. DCA showed that the combined model incorporating RadScore, clinical risk factors, and PET metabolic metrics has optimal net clinical benefit. COX indicated that the high RadScore group had worse prognosis and survival in progression-free survival (PFS) (HR, 2.1737,95%CI: 1.2983, 3.6392) and overall survival (OS) (HR,2.1356,95%CI: 1.2561, 3.6309) compared to the low RadScore group. KM survival analysis also showed the same prognosis prediction as Cox results. Conclusion: The combined model incorporating RadScore, sex, B symptoms and SUVmax demonstrates a significant enhancement in predicting medium-term efficacy and prognosis in high-risk DLBCL patients. RadScore using 7×7 machine learning cross-combinatorial methods for selection and classification holds promise as a potential method for evaluating medium-term treatment outcome and prognosis in high-risk DLBCL patients.

TRIANGLE operation, combined with adequate adjuvant chemotherapy, can improve the prognosis of pancreatic head cancer: A retrospective study.

BACKGROUND: The TRIANGLE operation involves the removal of all tissues within the triangle bounded by the portal vein-superior mesenteric vein, celiac axis-common hepatic artery, and superior mesenteric artery to improve patient prognosis. Although previously promising in patients with locally advanced pancreatic ductal adenocarcinoma (PDAC), data are limited regarding the long-term oncological outcomes of the TRIANGLE operation among resectable PDAC patients undergoing pancreaticoduodenectomy (PD). AIM: To evaluate the safety of the TRIANGLE operation during PD and the prognosis in patients with resectable PDAC. METHODS: This retrospective cohort study included patients who underwent PD for pancreatic head cancer between January 2017 and April 2023, with or without the TRIANGLE operation. Patients were divided into the PDTRIANGLE and PDnon-TRIANGLE groups. Surgical and survival outcomes were compared between the two groups. Adequate adjuvant chemotherapy was defined as adjuvant chemotherapy ≥ 6 months. RESULTS: The PDTRIANGLE and PDnon-TRIANGLE groups included 52 and 55 patients, respectively. There were no significant differences in the baseline characteristics or perioperative indexes between the two groups. Furthermore, the recurrence rate was lower in the PDTRIANGLE group than in the PDnon-TRIANGLE group (48.1% vs 81.8%, P < 0.001), and the local recurrence rate of PDAC decreased from 37.8% to 16.0%. Multivariate Cox regression analysis revealed that PDTRIANGLE (HR = 0.424; 95%CI: 0.256-0.702; P = 0.001), adequate adjuvant chemotherapy ≥ 6 months (HR = 0.370; 95%CI: 0.222-0.618; P < 0.001) and margin status (HR = 2.255; 95%CI: 1.252-4.064; P = 0.007) were found to be independent factors for the recurrence rate. CONCLUSION: The TRIANGLE operation is safe for PDAC patients undergoing PD. Moreover, it reduces the local recurrence rate of PDAC and may improve survival in patients who receive adequate adjuvant chemotherapy.

Prognosis Prediction of Diffuse Large B-Cell Lymphoma in 18F-FDG PET Images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

Exploring Novel Sensor Design Ideas through Concentration-Induced Conformational Changes in PEG Single Chains.

Polyethylene glycol (PEG) is an artificial polymer with good biocompatibility and a low cost, which has a wide range of applications. In this study, the dynamic response of PEG single chains to different ion concentrations was investigated from a microscopic point of view based on single-molecule force spectroscopy, revealing unique interactions that go beyond the traditional sensor-design paradigm. Under low concentrations of potassium chloride, PEG single chains exhibit a gradual reduction in rigidity, while, conversely, high concentrations induce a progressive increase in rigidity. This dichotomy serves as the cornerstone for a profound understanding of PEG conformational dynamics under diverse ion environments. Capitalizing on the remarkable sensitivity of PEG single chains to ion concentration shifts, we introduce innovative sensor-design ideas. Rooted in the adaptive nature of PEG single chains, these sensor designs extend beyond the traditional applications, promising advancements in environmental monitoring, healthcare, and materials science.

Comparison of Lugano Criteria Versus RECIL and PERCIST as Prognostic Factors in Diffuse Large B-Cell Lymphoma.

OBJECTIVE: This study aimed to compare the criteria of the Lugano, RECIL, and PERCIST for prognosis in patients with diffuse large B-cell lymphoma. PATIENTS AND METHODS: We retrospectively evaluated 335 patients with diffuse large B-cell lymphoma. All patients underwent baseline 18 F-FDG PET/CT. Among them, 252 and 213 patients underwent interim PET/CT (I-PET/CT) and end-of-treatment PET/CT (EoT-PET/CT), respectively. Scans were interpreted by 2 nuclear medicine physicians using Lugano, RECIL, and PERCIST. RECIL and PERCIST were compared with Lugano for predicting progression-free survival (PFS) and overall survival (OS). RESULTS: All 3 response criteria could be used to predict PFS and OS. In I-PET/CT, the concordance index of Lugano in predicting PFS and OS was higher than that of RECIL (both P = 0.043) or PERCIST ( P = 0.008 and P = 0.034, respectively). In EoT-PET/CT, the concordance index of Lugano for predicting PFS and OS was similar to RECIL and not significantly different from PERCIST ( P = 0.597 and P = 0.231, respectively). CONCLUSIONS: For I-PET/CT, using the Lugano criteria is more accurate than RECIL or PERCIST in predicting PFS and OS. However, for EoT-PET/CT, the PERCIST criteria are minimally better.

M3S-Net: multi-modality multi-branch multi-self-attention network with structure-promoting loss for low-dose PET/CT enhancement.

Objective.PET (Positron Emission Tomography) inherently involves radiotracer injections and long scanning time, which raises concerns about the risk of radiation exposure and patient comfort. Reductions in radiotracer dosage and acquisition time can lower the potential risk and improve patient comfort, respectively, but both will also reduce photon counts and hence degrade the image quality. Therefore, it is of interest to improve the quality of low-dose PET images.Approach.A supervised multi-modality deep learning model, named M3S-Net, was proposed to generate standard-dose PET images (60 s per bed position) from low-dose ones (10 s per bed position) and the corresponding CT images. Specifically, we designed a multi-branch convolutional neural network with multi-self-attention mechanisms, which first extracted features from PET and CT images in two separate branches and then fused the features to generate the final generated PET images. Moreover, a novel multi-modality structure-promoting term was proposed in the loss function to learn the anatomical information contained in CT images.Main results.We conducted extensive numerical experiments on real clinical data collected from local hospitals. Compared with state-of-the-art methods, the proposed M3S-Net not only achieved higher objective metrics and better generated tumors, but also performed better in preserving edges and suppressing noise and artifacts.Significance.The experimental results of quantitative metrics and qualitative displays demonstrate that the proposed M3S-Net can generate high-quality PET images from low-dose ones, which are competable to standard-dose PET images. This is valuable in reducing PET acquisition time and has potential applications in dynamic PET imaging.

Do adaptive policy adjustments deliver ecosystem-agriculture-economy co-benefits in land degradation neutrality efforts? Evidence from southeast coast of China.

Ecosystem restoration projects (ERPs) facilitate land degradation neutrality (LDN). However, the response dynamics and interactions of sectors within ecosystem-agriculture-economy nexus (EAEN) have not been sufficiently explored, which constrains the coordinated efficacy of LDN efforts. To bridge the knowledge gaps, the present study selected a land restoration hotspot in southeastern China as a case to investigate the simultaneous responses of the EAEN sectors to ERPs from a novel social-ecological system (SES)-based LDN perspective. Various biophysical models and Manne-Kendall trend test as well as multi-source spatially explicit data and socioeconomic statistics were applied to quantify the co-evolution of natural and socioeconomic indicators. ERPs converting cropland to woodland and grassland promoted vegetation restoration, reduced soil erosion, and enhanced carbon sequestration. However, cropland loss initially resulted in a decline in grain productivity. Policy adjustments and improvements in ecosystem restoration efforts and agricultural production conditions improved food security and increased agricultural production capacity. Effective policymaking and favorable resident engagement accelerated the transformation from a grain-production-based agriculture to diversified industries and, by extension, economic output, income, and population. The success of socioeconomic development under the SES framework for LDN demonstrated that this strategy could achieve the desired environmental, agricultural, and economic targets. EAEN under the SES conceptual framework provides an inclusive, comprehensive LDN perspective and improves ERP efficacy. The findings of the present work might be applicable to other land restoration areas challenged by the complex interactions among multidimensional factors. Comparably successful implementation of these ERPs could be realized if individual environmental and socioeconomic conditions are thoroughly considered during the formulation of coordinated development policies.

Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study.

OBJECTIVE: To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL). METHODS: A total of 684 DLBCL patients from three independent medical centers were included in this retrospective study. Deep learning scores (DLS) were generated from PET images using deep convolutional neural network architecture known as VGG19 and DenseNet121. These DLSs were utilized to predict progression-free survival (PFS) and overall survival (OS). Furthermore, multiparametric models were designed based on results from the Cox proportional hazards model and assessed through calibration curves, concordance index (C-index), and decision curve analysis (DCA) in the training and validation cohorts. RESULTS: The DLSPFS and DLSOS exhibited significant associations with PFS and OS, respectively (P<0.05) in the training and validation cohorts. The multiparametric models that incorporated DLSs demonstrated superior efficacy in predicting PFS (C-index: 0.866) and OS (C-index: 0.835) compared to competing models in training cohorts. In external validation cohorts, the C-indices for PFS and OS were 0.760 and. 0.770 and 0.748 and 0.766, respectively, indicating the reliable validity of the multiparametric models. The calibration curves displayed good consistency, and the decision curve analysis (DCA) confirmed that the multiparametric models offered more net clinical benefits. CONCLUSIONS: The DLSs were identified as robust prognostic imaging biomarkers for survival in DLBCL patients. Moreover, the multiparametric models developed in this study exhibited promising potential in accurately stratifying patients based on their survival risk.

Prognostic value of 18F-FDG lesion dissemination features in patients with peripheral T-cell lymphoma (PTCL).

PURPOSE: To explore the prognostic value of the distance between the two lesions that were farthest apart (Dmax) on baseline 18F-FDG PET/CT in peripheral T lymphoma (PTCL) and establish a new prognostic model for predicting the survival outcomes of patients with PTCL. METHODS: In this study, a retrospective analysis of 95 patients with PTCL who underwent baseline 18F-FDG PET/CT was performed to assess the predictive value of Dmax. The total metabolic tumour volume (TMTV), total lesion glycolysis (TLG), standardized uptake value (SUV), and Dmax were calculated with LIFEx software. Progression-free survival (PFS) and overall survival (OS) were used as endpoints. The prognostic model was developed based on the results of the multivariate analysis. The time-dependent area under the ROC curve (tdAUC), calibration curves, Harrell C-index, and decision curve analysis (DCA) were used to assess the model. RESULTS: Patients were followed up for a median of 17.0 months. Multivariate analysis showed that bone marrow biopsy (BMB) and Dmax were independent predictors of PFS (HR: 1.889, P = 0.039; HR: 1.965, P = 0.047) and OS (HR: 1.923, P = 0.031; HR: 1.982, P = 0.034). The model consisting of Dmax, TMTV, and BMB had substantial prognostic value for survival outcomes of PTCL and could successfully identify four groups of patients with significantly different prognoses (χ2 = 13.731, P = 0.003 for PFS; χ2 = 11.841, P = 0.008 for OS). The tdAUC, C-index, calibration curves, and DCA supported that the model was superior to the prognostic index for T-cell lymphoma (PIT) and International Prognostic Index (IPI) scores. CONCLUSION: BMB and Dmax were independent predictors of PTCL in our study. Moreover, a prognostic model based on the Dmax, TMTV, and BMB could be useful for predicting the survival outcomes of patients with PTCL.

Effect of Dexmedetomidine on Cardiac Surgery Patients.

ABSTRACT: Dexmedetomidine, an alpha-2 adrenoreceptor agonist that is widely used as a sedative medication, is becoming more and more attractive in clinical application on cardiac surgery patients. In this review, we aim to summarize and discuss both retrospective studies and clinical trials regarding the effect of dexmedetomidine on patients who underwent cardiac surgery (including coronary artery bypass grafting, valve surgery, aortic surgery, percutaneous coronary intervention, and so on), which illustrates that the clinical effects of dexmedetomidine could effectively reduce mortality, major complications, and the intensive care unit and hospital length of stay without comprising safety. In addition, inconsistent results from both retrospective studies and clinical trials have also been demonstrated. Although the effectiveness and safety of dexmedetomidine on cardiac surgery patients is suggested, high-quality clinical trials are needed for further verification.

Achieving balance between socioeconomic development and ecosystem conservation via policy adjustments in Guangdong Province of southeastern China.

Rapid urbanization improves socioeconomic development but challenges ecosystem sustainability. Meanwhile, the gradient responses of ecosystem services (ESs) to landscape structures and associated regime shifts of the agriculture-ecosystem-economy nexus (AEEN) have not been sufficiently addressed, preventing an effective balance between socioeconomic prosperity and ecosystem conservation. To bridge this knowledge gap, this study selected the Guangdong Province of southeastern China to explore landscape dynamics from 1985 to 2020 and their spatially heterogeneous impacts on ESs and the AEEN, based on Integrated Valuation of Ecosystem Services and Trade-offs approach and other biophysical models as well as statistical records about socioeconomic factors. AEEN elements, including ESs, responded directly to policy adjustments in terms of ecosystem restoration and landscape management and presented remarkable regime shifts (i.e., phase changes) and spatial heterogeneity. Aggressive agricultural reclamation before 1999 increased crop productivity but caused vegetation degradation and biomass decline. Accelerated urban expansion and ecosystem restoration efforts have improved economic and ecological benefits but have substantially reduced crop productivity and threatened food security. However, timely policy adjustments since 2009 reversed the declining trend and maintained the grain supply. Landscape composition presented patterns of gradual decline along the urban-rural gradient, which in turn determined ES gradient patterns. For instance, water yield and nitrogen export positively correlated with each other (p < 0.0001) but negatively correlated with other ESs. Our study enriches the understandings of social-ecological systems' response to man-made interventions from AEEN perspective allowing for spatial variabilities and regime shifts, which support policy formulation for coordinating ecological and economic benefits.

The Freeze-Thaw Strength Evolution of Fiber-Reinforced Cement Mortar Based on NMR and Fractal Theory: Considering Porosity and Pore Distribution.

Predicting the strength evolution of fiber-reinforced cement mortar under freeze-thaw cycles plays an important role in engineering stability evaluation. In this study, the microscopic pore distribution characteristics of fiber-reinforced cement mortar were obtained by using nuclear magnetic resonance (NMR) technology. The change trend of T2 spectrum curve and porosity cumulative distribution curve showed that the freeze-thaw resistance of cement mortar increased first and then decreased with the fiber content. The optimal fiber content was approximately 0.5%. By conducting mechanical experiments, it is found that the uniaxial compressive strength (UCS) of the samples exhibited the 'upward convex' evolution trends with freeze-thaw cycles due to cement hydration, and based on fractal theory, the negative correlation between UCS and Dmin was established. Eventually, a freeze-thaw strength prediction model considering both porosity and pore distribution was proposed, which could accurately predict the strength deterioration law of cement-based materials under freeze-thaw conditions.

Regulation of the p38-MAPK pathway by hyperosmolarity and by WNK kinases.

p38-MAPK is a stress-response kinase activated by hyperosmolarity. Here we interrogated the pathways involved. We show that p38-MAPK signaling is activated by hyperosmotic stimulation in various solutions, cell types and colonic organoids. Hyperosmolarity sensing is detected at the level of the upstream activators of p38-MAPK: TRAF2/ASK1 (but not Rac1) and MKK3/6/4. While WNK kinases are known osmo-sensors, we found, unexpectedly, that short (2 h) inhibition of WNKs (with WNK463) led to elevated p38-MAPK activity under hyperosmolarity, which was mediated by WNK463-dependent stimulation of TAK1 or TRAF2/ASK1, the upstream activators of MKK3/6/4. However, this effect was temporary and was reversed by long-term (2 days) incubation with WNK463. Accordingly, 2 days (but not 2 h) inhibition of p38-MAPK or its upstream activators ASK1 or TAK1, or WNKs, diminished regulatory volume increase (RVI) following cell shrinkage under hyperosmolarity. We also show that RVI mediated by the ion transporter NKCC1 is dependent on p38-MAPK. Since WNKs are known activators of NKCC1, we propose a WNK- > NKCC1- > p38-MAPK pathway that controls RVI. This pathway is augmented by NHE1. Additionally, hyperosmolarity inhibited mTORC1 activation and cell proliferation. Thus, activation of p38-MAPK and WNKs is important for RVI and for cell proliferation.

Flexible, Multifunctional Micro-Sensor Applied to Internal Measurement and Diagnosis of Vanadium Flow Battery.

The vanadium redox flow battery (VRFB) system is an emerging energy storage technology with many advantages, such as high efficiency, long life, and high safety. However, during the power-generation process, if local high temperature is generated, the rate of ions passing through the membrane will increase. In addition, it will also cause vanadium pentoxide molecules (V2O5) to exist in the solid state. Once the solid is formed, it will affect the flow of the vanadium electrolyte, which will eventually cause the temperature of the VRFB to continue to rise. According to the various physical parameters of VRFB shown in the literature, they have a significant impact on the efficiency and life of VRFB. Therefore, this research proposes to develop flexible multifunction (voltage, current, temperature, and flow) micro-sensors using micro-electro-mechanical systems (MEMS) technology to meet the need for real-time micro-diagnosis in the VRFB. The device is embedded in the VRFB of real-time microscopic sensing and diagnosis. Its technical advantages are: (1) it can simultaneously locally measure four physical quantities of voltage, current, temperature, and flow; (2) due to its mall size it can be accurately embedded; (3) the high accuracy and sensitivity provides it with a fast response time; and (4) it possesses extreme environment resistance.

Pulp revascularization on an adult mandibular right second premolar: A case report.

BACKGROUND: Pulp revascularization has become a new method for the treatment of periapical diseases in young permanent teeth in recent years. Through root canal flushing and disinfection, avoiding mechanical preparation, guiding apical stem cells into the root canal and promoting the continuous development of tooth roots, it has achieved good clinical curative effects. But in adult patients with chronic periapical periodontitis with immature roots and open apices, apical barrier technology is often used to treat these teeth. CASE SUMMARY: Pulp revascularization of a 26-year-old patient's tooth was performed using cefaclor instead of minocycline and iRoot BP instead of mineral trioxide aggregate as intracanal medication. The case was followed up for 36 mo. Observations showed evidence of regression of clinical signs and symptoms, resolution of apical periodontitis and no discolouration of affected teeth. CONCLUSION: For adult patients with chronic periapical periodontitis with immature roots and open apices, pulp revascularisation showed favourable results in treating these teeth.

The complete chloroplast genome of the genus Azadirachta.

Azadirachta consists of 2 species and 1 variety indigenous to the tropical areas of the Indo-Malayan region. They are evergreen trees for multi-purpose utilization featured by containing azadirachtin. The complete chloroplast (cp) genome of Azadirachta indica, A. indica var. siamensis and Azadirachta excelsa were reported in this study, which was 160,876 bp, 160,477 bp, and 160,361 bp in length respectively. The whole cp genomes encode 131 genes (37 tRNA genes, 8 rRNA genes, and 86 protein-coding genes) in both A. indica and A. excelsa, while A. indica var. siamensis do not have the rrn4.5S gene in the inverted repeat regions. The phylogenetic analysis indicated that A. indica var. siamensis and A. exselsa were closely related and A. indica was separated from these two species, which suggested that A. siamensis could be a species rather than a variety.

Elevated intracellular Na+ and osmolarity stimulate catalytic activity of the ubiquitin ligase Nedd4-2.

Regulation of catalytic activity of E3 ubiquitin ligases is critical for their cellular functions. We identified an unexpected mode of regulation of E3 catalytic activity by ions and osmolarity; enzymatic activity of the HECT family E3 Nedd4-2/Nedd4L is enhanced by increased intracellular Na+ ([Na+]i) and by hyperosmolarity. This stimulated activity is mediated by activation of p38-MAPK and is inhibited by WNKs. Moreover, protease (Furin)-mediated activation of the epithelial Na+ channel ENaC (a bona fide Nedd4-2 substrate), which leads to increased [Na+]i and osmolarity, results in enhanced Nedd4-2 catalytic activity. This enhancement is inhibited by a Furin inhibitor, by a protease-resistant ENaC mutant, or by treatment with the ENaC inhibitor amiloride. Moreover, WNK inhibition, which stimulates catalytic activity of Nedd4-2, leads to reduced levels of cell-surface ENaC and reduced channel activity. ENaC activity does not affect Nedd4-2:ENaC binding. Therefore, these results demonstrate activation of a ubiquitin ligase by Na+ and osmotic changes. Importantly, they reveal a negative feedback loop in which active ENaC leads to stimulation of catalytic activity of its own suppressor, Nedd4-2, to protect cells from excessive Na+ loading and hyperosmotic stress and to protect the animal from hypertension.

Linking land degradation and restoration to ecosystem services balance by identifying landscape drivers: insights from the globally largest loess deposit area.

Land degradation is one of the most serious environmental challenges that profoundly affects ecosystem services (ESs), which further threaten ecosystem sustainability. However, few studies have been committed to sufficiently explore the relationship between land degradation neutrality (LDN) and the ES balance of supply and demand sides, as well as their spatial disparities and determinants. To fill the knowledge gaps, this study quantifies land dynamics and ES balance through biophysical models and an expert knowledge matrix, respectively, and explores the spatial determinants through an integrated regression method. From 1990 to 2018, the ecosystem restoration projects in the Loess Plateau substantially reduced soil loss and maintained ES surplus patterns for the entire regional scale, except for individual urban agglomerations, which suffered from ES deficits. Spatial panel models and geographically and temporally weighted regression revealed that the ES balance and soil loss were concurrently determined by socioeconomic indicators, landscape composition, and structure. In addition, the spatial determinants presented remarkable regional heterogeneities and spillover effects depending on individual environmental and socioeconomic conditions, which should be taken into account in landscape monitoring, simulation, forecasting, and planning. Therefore, ecosystem restoration and landscape management should not solely depend on individual indicators in local units, but also rely on integrated frameworks and coordinated collaborations from cross-border areas that appropriately link LDN and ES balance maintenance targets by considering common critical determinants and their external effects. This study enriches the understanding of ecosystem evolution and sustaining ES balance. The findings are expected to further support policy formulations and implementations to address land degradation challenges and enhance ecosystem sustainability.

Longitudinal genomic alternations and clonal dynamics analysis of primary malignant melanoma of the esophagus.

Primary malignant melanoma of the esophagus (PMME) is a rare gastrointestinal melanoma with a high rate of recurrence and metastasis. The standard of care for PMME has not been established yet due to a lack of understanding of its clinical and molecular pathogenesis. Thus, we performed genomic profiling on a recurrent PMME case to seek novel opportunities for the management of this rare disease. Between 2013 and 2016, 6 tissue samples including 3 from the primary tumors, 2 from the relapsed tumors, and 1 from a normal control were collected from a patient diagnosed with PMME and were subjected to whole-exome sequencing to track the dynamic genetic changes. Additionally, we also analyzed a cohort of 398 samples obtained from the TCGA skin cutanesous melanoma (TCGA-SKCM) dataset to assess the frequency and determine the clinical implications of genomic events found in the presented study. ARHGAP35 (p.L1022M) was the only mutation shared across temporal PMME lesions. The PMME samples showed higher levels of genetic instability and intra-tumor heterogeneity. They also shared several concordant copy number variations (CNV). All lesions were concordant with the evolution trajectory, and shrinkage of the founding clone caused the subclonal population to become dominant in PT1c, which was likely the reason behind metastatic seeding. ARHGAP35 mutations were found in 6% of the TCGA-SKCM cohort samples. The presence of the mutations was associated with poor progression-free survival (PFS) by both univariate and multivariate Cox regression analyses. Our study showed that the primary tumor clone disseminates earlier in PMME. This highlights the need to understand the mechanism involved in the early PMME recurrence to optimize treatment.