SHP2-Triggered Endothelial Cell Activation Fuels Estradiol-Independent Endometrial Sterile Inflammation.

Sterile inflammation occurs in various chronic diseases due to many nonmicrobe factors. Examples include endometrial hyperplasia (EH), endometriosis, endometrial cancer, and breast cancer, which are all sterile inflammation diseases induced by estrogen imbalances. However, how estrogen-induced sterile inflammation regulates EH remains unclear. Here, a single-cell RNA-Seq is used to show that SHP2 upregulation in endometrial endothelial cells promotes their inflammatory activation and subsequent transendothelial macrophage migration. Independent of the initial estrogen stimulation, IL1ß and TNFα from macrophages then create a feedforward loop that enhances endothelial cell activation and IGF1 secretion. This endothelial cell-macrophage interaction sustains sterile endometrial inflammation and facilitates epithelial cell proliferation, even after estradiol withdrawal. The bulk RNA-Seq results and phosphoproteomic analysis show that endothelial SHP2 mechanistically enhances RIPK1 activity by dephosphorylating RIPK1Tyr380. This event activates downstream activator protein 1 (AP-1) and instigates the inflammation response. Furthermore, targeting SHP2 using SHP099 (an allosteric inhibitor) or endothelial-specific SHP2 deletion alleviates endothelial cell activation, macrophage infiltration, and EH progression in mice. Collectively, the findings demonstrate that SHP2 mediates the transition of endothelial activation from estradiol-driven acute inflammation to macrophage-amplified chronic inflammation. Targeting sterile inflammation mediated by endothelial cell activation is a promising strategy for nonhormonal intervention in estrogen-related diseases.

China's progress in synergetic governance of climate change and multiple environmental issues.

Advancing the synergetic control of climate change and environmental crisis is crucial for achieving global sustainable development goals. This study evaluates synergetic governance levels over climate change and four environmental issues at the provincial level in China from 2009 to 2020. Our findings reveal significant progress in China's coordinated efforts to mitigate carbon emissions, reduce air pollutants, and conserve water resources. However, there remains room for improvement in managing solid waste and protecting ecological systems and overall progress in synergetic governance has slowed since 2015. Employing a random forest model, we identify socio-economic factors with great influence on synergetic climate change and environmental governance, such as energy intensity, service sector development, electronic equipment manufacturing, and transportation. Additionally, we reveal nonlinear relationships between some factors and performance of environmental subsystems, including both plateau effects (e.g. output in the smelting of ferrous metals) and U-shaped patterns (e.g. output in the manufacturing of metal products), possibly attributed to constraints in end-of-pipe treatment capacities and complexities in supply chain networks. Furthermore, through hierarchical clustering analysis, we classify provinces into four groups and provide tailored recommendations for policymakers to enhance synergetic governance levels in their respective regions. The framework established in this study also serves as a valuable reference for countries seeking to develop practical and context-specific solutions to mitigate climate and environmental risks.

Development of an agroinfiltration-based transient hairpin RNA expression system in pak choi leaves (Brassica rapa ssp. chinensis) for RNA interference against Liriomyza sativae.

The vegetable leafminer (Liriomyza sativae) is a devastating invasive pest of many vegetable crops and horticultural plants worldwide, causing serious economic loss. Conventional control strategy against this pest mainly relies on the synthetic chemical pesticides, but widespread use of insecticides easily causes insecticide resistance development and is harmful to beneficial organisms and environment. In this context, a more environmentally friendly pest management strategy based on RNA interference (RNAi) has emerged as a powerful tool to control of insect pests. Here we report a successful oral RNAi in L. sativae after feeding on pak choi (Brassica rapa ssp. chinensis) that transiently express hairpin RNAs targeting vital genes in this pest. First, potentially lethal genes are identified by searching an L. sativae transcriptome for orthologs of the widely used V-ATPase A and actin genes, then expression levels are assessed during different life stages and in different adult tissues. Interestingly, the highest expression levels for V-ATPase A are observed in the adult heads (males and females) and for actin in the abdomens of adult females. We also assessed expression patterns of the target hairpin RNAs in pak choi leaves and found that they reach peak levels 72 h post agroinfiltration. RNAi-mediated knockdown of each target was then assessed by letting adult L. sativae feed on agroinfiltrated pak choi leaves. Relative transcript levels of each target gene exhibit significant reductions over the feeding time, and adversely affect survival of adult L. sativae at 24 h post infestation in genetically unmodified pak choi plants. These results demonstrate that the agroinfiltration-mediated RNAi system has potential for advancing innovative environmentally safe pest management strategies for the control of leaf-mining species.

Microwave Remote Sensing with Hybrid Quantum Receiver.

Detecting a microwave signal that is emitted or reflected by distant targets is a powerful tool in fundamental science and industrial technology. Solid-state spins provide an opportunity to realize quantum-enhanced remote sensing under ambient conditions. However, the weak interaction between the free-space signal and atomic size sensor limits the sensitivity. This hinders the realization of practical quantum remote sensing. Here, we demonstrate active microwave remote sensing with a diamond-based hybrid quantum receiver by combining electromagnetic field localization at nanoscale with quantum spin manipulation. A method of differential spin refocusing (DSR) is developed to overcome the challenge of reducing the impact of inhomogeneities in spin-signal interaction, while the strength of interaction is enhanced by more than 3 orders with nanostructure. It improves the coherent interaction time of quantum receiver by 30-fold, substantially enhancing the sensitivity and stability. By detecting the reflected microwave with picotesla sensitivity, diamond remote sensing monitors the real-time status of a centimeter-sized target at 2 m distance. Our method is general to various solid-state spins. The results will expand the applications of solid-state spin quantum sensors in areas ranging from medical imaging to resource survey.

circ_SMA4 promotes gastrointestinal stromal tumors malignant progression by sponging miR-494-3p/KIT axis and activating JAK/STAT pathway.

Recent evidence has demonstrated that abnormal expression and regulation of circular RNA (circRNAs) are implicated in the development and progression of various tumors. The aim of this study was to investigate the effects of circ_SMA4 in Gastrointestinal Stromal Tumors (GISTs) malignant progression. Human circRNAs microarray analysis was conducted to identify differentially expressed (DE) circRNAs in GISTs. The effect of circ_SMA4 on cell proliferation, invasion, migration, and apoptosis was assessed in both in vitro and in vivo settings. Dual-luciferase reporter assay, RT-qPCR, Western-blot, and rescue assay were employed to confirm the interaction between circ_SMA4/miR-494-3p/ KIT axis. The results revealed that circ_SMA4 was significantly upregulated in GISTs, and exhibited high diagnostic efficiency with an AUC of 0.9824 (P < 0.01). circ_SMA4 promoted cell proliferation, invasion, migration, while inhibiting apoptosis in GISTs cells, both in vitro and in vivo. Silencing circ_SMA4 partially inhibited GISTs malignant progression. Additionally, circ_SMA4 acted as a competing endogenous RNA (ceRNA) by targeting miR-494-3p, and KIT was identified as a functional gene for miR-494-3p in GISTs. Furthermore, the results confirmed that circ_SMA4/miR-494-3p/ KIT axis plays a role in activating the JAK/STAT signaling pathway in GISTs. Therefore, for the first time, we have identified and emphasized that circ_SMA4 is significantly upregulated and plays an oncogenic role in GISTs by sponging miR-494-3p to activate the KIT/JAK/STAT pathway. These findings underscore circ_SMA4 may serve as a novel diagnostic biomarker and therapeutic target for GISTs.

The importance of high total body water/fat free mass ratio and serial changes in body composition for predicting hospital mortality in patients with severe pneumonia: a prospective cohort study.

PURPOSE: This study aimed to investigate the impact of body composition variables on hospital mortality compared to other predictive factors among patients with severe pneumonia. Additionally, we aimed to monitor the dynamic changes in body composition variables over the course on days 1, 3, and 8 after intensive care unit (ICU) admission for each patient. METHODS: We conducted a prospective study, enrolling patients with severe pneumonia admitted to the medical intensive care unit at Kaohsiung Chang Gung Memorial Hospital from February 2020 to April 2022. We collected clinical data from all patients and assessed their body composition at 1, 3, and 8 days post-ICU admission. On day 1, we analyzed clinical and body composition variables to predict in-hospital mortality. RESULTS: Multivariate analysis identified the Modified Nutrition Risk in the Critically Ill (mNUTRIC) score and the ratio of total body water to fat-free mass (TBW/FFM) as independent factors associated with in-hospital mortality in severe pneumonia patients. Receiver operating characteristic analysis determined that the TBW/FFM ratio was the most reliable predictive parameter of in-hospital mortality, with a cutoff value of 0.74. General linear regression with repeated measures analysis showed that hospital non-survivors displayed notable fluctuations in body water, fat, and muscle variables over the course of days 1, 3, and 8 after ICU admission. CONCLUSIONS: The mNUTRIC score and TBW/FFM ratio emerged as independent factors for predicting hospital mortality, with the TBW/FFM ratio demonstrating the highest reliability as a predictive parameter.

Advances and future directions of environmental risk research: A bibliometric review.

Environmental risk is one of the world's most significant threats, projected to be the leading risk over the next decade. It has garnered global attention due to increasingly severe environmental issues, such as climate change and ecosystem degradation. Research and technology on environmental risks are gradually developing, and the scope of environmental risk study is also expanding. Here, we developed a tailored bibliometric method, incorporating co-occurrence network analysis, cluster analysis, trend factor analysis, patent primary path analysis, and patent map methods, to explore the status, hotspots, and trends of environment risk research over the past three decades. According to the bibliometric results, the publications and patents related to environmental risk have reached explosive growth since 2018. The primary topics in environmental risk research mainly involve (a) ecotoxicology risk of emerging contaminants (ECs), (b) environmental risk induced by climate change, (c) air pollution and health risk assessment, (d) soil contamination and risk prevention, and (e) environmental risk of heavy metal. Recently, the hotspots of this field have shifted into artificial intelligence (AI) based techniques and environmental risk of climate change and ECs. More research is needed to assess ecological and health risk of ECs, to formulize mitigation and adaptation strategies for climate change risks, and to develop AI-based environmental risk assessment and control technology. This study provides the first comprehensive overview of recent advances in environmental risk research, suggesting future research directions based on current understanding and limitations.

Migration and availability of Ni and Cd in industrial soils under different leaching conditions: Insights from DGT and DIFS models.

Rainfall runoff can mobilize heavy metals in industrial soils, posing environmental risks. The mobility and distribution of heavy metals in different industrial soil layers are often overlooked. This study employed dynamic leaching experiments in layered soil columns with DGT (the diffusive gradients in thin films) measurements and DIFS (DGT-induced fluxes in soils and sediments) model to describe the migration, availability, and resupply ability of metals at different depths in surface and deep soil columns of industrial soils. Results showed significantly higher available concentrations (CDGT and CSoln) of Ni and Cd in surface soils compared to deep soils, likely due to the differences in soil physiochemical properties (contamination, pH, and soil texture). Continuous leaching promoted the migration of available Ni and Cd in surface soils. Maximum values of RNi (0.79-0.91) and RCd (0.75-0.80) were observed in the top layer (0-4 cm) of the surface soil, consistent with the trends of RFe. Combined DGT and DIFS model analysis implied higher potential availability and resupply of Ni and Cd in surface soil columns. These findings highlight the importance of considering dynamic leaching effects on heavy metal transport, availability, and release in industrial soils.

Paospora carinifang n. gen., n. sp. (Microsporidia: Spragueidae), a parasite of the ridgetail white prawn, Palaemon carinicauda.

A new microsporidian disease of the pond-reared ridgetail white prawn, Palaemon carinicauda, was found in China. Light microscopy, pathology, and scanning electron microscopy showed that the parasite infected the host's skeletal muscle tissue and formed spherical sporophorous vesicles (SPOVs). Electron microscopy revealed that its merogonic life stages developed in direct contact with the host cytoplasm. The sporogonic life stages underwent octosporoblastic sporogony with the formation of eight uninucleate spores in each SPOV. Fresh SPOVs were 5.4 ± 0.55 µm in diameter. The octospores were oval and measured 2.3 × 1.5 µm (fresh) and 1.96 × 1.17 µm (fixed). The isofilar polar filament was coiled with 9-10 turns and arranged in two rows. Phylogenetic analysis based on the SSU rRNA gene suggests that this microsporidium has close affinities with members of the genera Potaspora and Apotaspora, but represents an independent generic taxon. We therefore propose the establishment of a new genus and species (Paospora carinifang n. gen., n. sp.) within the family Spragueidae. We also propose a taxonomic revision to transfer Potaspora macrobrachium to this new genus and reclassify it as Paospora macrobrachium comb. nov.

Measuring climate change perception in China using mental images: A nationwide open-ended survey.

Current knowledge about public climate change perception mainly covers belief, concern, and attitudes. However, how this discourse is interpreted using individuals' own frame of reference remains largely unknown, particularly in many large emitters from non-Annex I countries such as China. This study, for the first time, performs a nationwide open-ended survey covering 4,037 respondents and collected 12,100 textual answers. Using a semiautomated coding method, we find seven mental images that exclusively represent the Chinese interpretation of the climate change issue, including global warming, distant icons, natural disasters, environmental degradation, cause, solution, and weather. Analysis of influencing factors shows that females, those with lower education levels, lower income, and older individuals tend to connect climate change with natural weather phenomena. Younger and well-educated residents in developed cities are more aware of various consequences and anthropogenic causes of climate change. People with stronger climate change beliefs, policy support, and personal experience of extreme weather are more likely to mention disastrous impacts, carbon emission as causes, and potential solutions. Employing the multilevel regression and post-stratification technique, we map the prevalence of mental images in China at the prefecture-city level. The results reveal significant geographical heterogeneity, with estimated national means ranging from a high of 55% (weather) to a low of 11% (solution). Our findings reveal diverse perspectives and a widespread misconception of climate change in China, suggesting the need for tailored clarification strategies to gain public consent.

Serum Uric Acid Levels Associated with Outcomes of Neurodegenerative Disorders and Brain Health: Findings from the UK Biobank.

BACKGROUND: The relationship between serum uric acid (SUA) levels and brain-related health remains uncertain. OBJECTIVES: This study aimed to investigate the relationship between SUA levels and some neurodegenerative disorders and brain structure. DESIGN: A longitudinal study. SETTING AND PARTICIPANTS: 384,517 participants who did not have stroke, dementia, and Parkinsonism, with complete urate testes and covariates were included. MEASUREMENTS: Cox proportional hazards models, competing risk models, and restricted cubic spine models were applied. RESULTS: During the median follow-up time of 12.7 years (interquartile range [IQR]:12.0, 13.5), 7821 (2.0%) participants developed stroke, 5103 (1.3%) participants developed dementia, and 2341 (0.6%) participants developed Parkinsonism. Nonlinear relationships were identified between SUA levels and stroke (J-shaped), dementia, and Parkinsonism (U-shaped). SUA levels of 4.2 mg/dl, 6.4 mg/dl, and 6.6 mg/dl yielded the lowest risk of stroke, dementia, and Parkinsonism, respectively. Besides, we found high SUA levels reduced the volumes of total brain, grey matter, white matter, grey matter in the hippocampus, and hippocampus, but increased lateral-ventricle volume. Inflammation accounted for 9.1% and 10.0% in the association of SUA with stroke and lateral-ventricle volume. CONCLUSIONS: Lower SUA levels increased the risk of Parkinsonism, while both lower and higher SUA levels were positively associated with increased risk of stroke and dementia. Moreover, high SUA levels reduced brain structure volumes. Our findings suggest the association between SUA levels and brain-related disorders and highlight the importance of SUA management.

A Deep-Learning-Enabled Electrocardiogram and Chest X-Ray for Detecting Pulmonary Arterial Hypertension.

The diagnosis and treatment of pulmonary hypertension have changed dramatically through the re-defined diagnostic criteria and advanced drug development in the past decade. The application of Artificial Intelligence for the detection of elevated pulmonary arterial pressure (ePAP) was reported recently. Artificial Intelligence (AI) has demonstrated the capability to identify ePAP and its association with hospitalization due to heart failure when analyzing chest X-rays (CXR). An AI model based on electrocardiograms (ECG) has shown promise in not only detecting ePAP but also in predicting future risks related to cardiovascular mortality. We aimed to develop an AI model integrating ECG and CXR to detect ePAP and evaluate their performance. We developed a deep-learning model (DLM) using paired ECG and CXR to detect ePAP (systolic pulmonary artery pressure > 50 mmHg in transthoracic echocardiography). This model was further validated in a community hospital. Additionally, our DLM was evaluated for its ability to predict future occurrences of left ventricular dysfunction (LVD, ejection fraction < 35%) and cardiovascular mortality. The AUCs for detecting ePAP were as follows: 0.8261 with ECG (sensitivity 76.6%, specificity 74.5%), 0.8525 with CXR (sensitivity 82.8%, specificity 72.7%), and 0.8644 with a combination of both (sensitivity 78.6%, specificity 79.2%) in the internal dataset. In the external validation dataset, the AUCs for ePAP detection were 0.8348 with ECG, 0.8605 with CXR, and 0.8734 with the combination. Furthermore, using the combination of ECGs and CXR, the negative predictive value (NPV) was 98% in the internal dataset and 98.1% in the external dataset. Patients with ePAP detected by the DLM using combination had a higher risk of new-onset LVD with a hazard ratio (HR) of 4.51 (95% CI: 3.54-5.76) in the internal dataset and cardiovascular mortality with a HR of 6.08 (95% CI: 4.66-7.95). Similar results were seen in the external validation dataset. The DLM, integrating ECG and CXR, effectively detected ePAP with a strong NPV and forecasted future risks of developing LVD and cardiovascular mortality. This model has the potential to expedite the early identification of pulmonary hypertension in patients, prompting further evaluation through echocardiography and, when necessary, right heart catheterization (RHC), potentially resulting in enhanced cardiovascular outcomes.

An ensemble machine learning model to uncover potential sites of hazardous waste illegal dumping based on limited supervision experience.

With the soaring generation of hazardous waste (HW) during industrialization and urbanization, HW illegal dumping continues to be an intractable global issue. Particularly in developing regions with lax regulations, it has become a major source of soil and groundwater contamination. One dominant challenge for HW illegal dumping supervision is the invisibility of dumping sites, which makes HW illegal dumping difficult to be found, thereby causing a long-term adverse impact on the environment. How to utilize the limited historic supervision records to screen the potential dumping sites in the whole region is a key challenge to be addressed. In this study, a novel machine learning model based on the positive-unlabeled (PU) learning algorithm was proposed to resolve this problem through the ensemble method which could iteratively mine the features of limited historic cases. Validation of the random forest-based PU model showed that the predicted top 30% of high-risk areas could cover 68.1% of newly reported cases in the studied region, indicating the reliability of the model prediction. This novel framework will also be promising in other environmental management scenarios to deal with numerous unknown samples based on limited prior experience.

Gefitinib (an EGFR tyrosine kinase inhibitor) plus anlotinib (an multikinase inhibitor) for untreated, EGFR-mutated, advanced non-small cell lung cancer (FL-ALTER): a multicenter phase III trial.

Dual inhibition of vascular endothelial growth factor and epidermal growth factor receptor (EGFR) signaling pathways offers the prospect of improving the effectiveness of EFGR-targeted therapy. In this phase 3 study (ClinicalTrial.gov: NCT04028778), 315 patients with treatment-naïve, EGFR-mutated, advanced non-small cell lung cancer (NSCLC) were randomized (1:1) to receive anlotinib or placebo plus gefitinib once daily on days 1-14 per a 3-week cycle. At the prespecified final analysis of progression-free survival (PFS), a significant improvement in PFS was observed for the anlotinib arm over the placebo arm (hazards ratio [HR] = 0.64, 95% CI, 0.48-0.80, P = 0.003). Particularly, patients with brain metastasis and those harboring EGFR amplification or high tumor mutation load gained significant more benefits in PFS from gefitinib plus anlotinib. The incidence of grade 3 or higher treatment-emergent adverse events was 49.7% of the patients receiving gefitinib plus anlotinib versus 31.0% of the patients receiving gefitinib plus placebo. Anlotinib plus gefitinib significantly improves PFS in patients with treatment-naïve, EGFR-mutated, advanced NSCLC, with a manageable safety profile.

Artificial Intelligence-Enabled Electrocardiography Predicts Future Pacemaker Implantation and Adverse Cardiovascular Events.

Medical advances prolonging life have led to more permanent pacemaker implants. When pacemaker implantation (PMI) is commonly caused by sick sinus syndrome or conduction disorders, predicting PMI is challenging, as patients often experience related symptoms. This study was designed to create a deep learning model (DLM) for predicting future PMI from ECG data and assess its ability to predict future cardiovascular events. In this study, a DLM was trained on a dataset of 158,471 ECGs from 42,903 academic medical center patients, with additional validation involving 25,640 medical center patients and 26,538 community hospital patients. Primary analysis focused on predicting PMI within 90 days, while all-cause mortality, cardiovascular disease (CVD) mortality, and the development of various cardiovascular conditions were addressed with secondary analysis. The study's raw ECG DLM achieved area under the curve (AUC) values of 0.870, 0.878, and 0.883 for PMI prediction within 30, 60, and 90 days, respectively, along with sensitivities exceeding 82.0% and specificities over 81.9% in the internal validation. Significant ECG features included the PR interval, corrected QT interval, heart rate, QRS duration, P-wave axis, T-wave axis, and QRS complex axis. The AI-predicted PMI group had higher risks of PMI after 90 days (hazard ratio [HR]: 7.49, 95% CI: 5.40-10.39), all-cause mortality (HR: 1.91, 95% CI: 1.74-2.10), CVD mortality (HR: 3.53, 95% CI: 2.73-4.57), and new-onset adverse cardiovascular events. External validation confirmed the model's accuracy. Through ECG analyses, our AI DLM can alert clinicians and patients to the possibility of future PMI and related mortality and cardiovascular risks, aiding in timely patient intervention.

Mediating effect of social support on the relationship between social activity and depressive symptoms among older widows in Taiwan.

The purpose of this study was to investigate the mediating effect of social support on the relationship between social activity and depressive symptoms among older widows in Taiwan. A cross-sectional study was conducted that recruited 256 older widows in southern Taiwan. Data were collected on demographic characteristics, self-rated health, instrumental activities of daily living, social activity, social support, and depression. Multiple linear regressions performed examined whether social activities and social support were significantly associated with depressive symptoms and which types of social activity were significantly related to social support and depressive symptoms. Mediation analyses performed tested the mediation effect of social support between the number of different types of social activities performed (termed "number of activities" in this study) and depression. Overall, 17.2% of the participants reported having at least two depressive symptoms. The total effect of the number of activities on depressive symptoms was significant (p < .001). The direct pathway from the number of activities to depressive symptoms remained significant (p < .001), and the mediation pathway (from the number of activities to depressive symptoms through social support) was also significant (Bootstrap CI = -.072, -.003). These findings demonstrated that older widows had more social support when they participated in more social activities, which could then decrease depressive symptoms. In addition, informal community group activities and religious group activities were the most effective at increasing social support and reducing depressive symptoms among the older Taiwanese widows.

Distributed State Observer for Systems with Multiple Sensors under Time-Delay Information Exchange.

The issues of state estimations based on distributed observers for linear time-invariant (LTI) systems with multiple sensors are discussed in this paper. We deal with the scenario when the information exchange has known time delays, and aim at designing a distributed observer for each subsystem such that each distributed observer can estimate the system state asymptotically by rejecting the time delay. To begin with, by rewriting the target system in a connecting form, a subsystem which is affected by the time-delay states of other nodes is established. And then, for this subsystem, a distributed observer with time delay is constructed. Moreover, an equivalent state transformation is made for the observer error dynamic system based on the observable canonic decomposition theorem. Further, in order to ensure that the distributed observer error dynamic system is asymptotically stable even if there exists a time delay, a linear matrix inequality (LMI) which is relative to the Laplace matrix is elaborately set up, and a special Lyapunov function candidate based on the LMI is considered. Next, based on the Lyapunov function and Lyapunov stability theory, we prove that the error dynamic system of the distributed observer is asymptotically stable, and the observer gain is determined by a feasible solution of the LMI. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

A new diagnostic technique for identifying Angiostrongylus spp. larvae in intermediate snail species by examining the buccal cavity.

BACKGROUND: Angiostrongyliasis is a zoonotic parasitic disease caused by the rat lungworm Angiostrongylus cantonensis. The intermediate hosts of A. cantonensis are gastropods, and snail species such as Pomacea canaliculata play a key role in the transmission of human angiostrongyliasis. Detecting A. cantonensis infection in snails is an important component of epidemiological surveillance and the control of angiostrongyliasis. METHODS: In this study, a new method for diagnosing A. cantonensis infection in gastropods was developed by recovering larvae from the buccal cavity of three snail species. The entire buccal cavity of a snail was extracted, and the tissue was pressed between two microscope slides to observe whether A. cantonensis larvae were present. Our new method was compared with traditional pathogenic detection methods of lung microscopy, tissue homogenization, and artificial digestion. We artificially infected 160 P. canaliculata, 160 Cipangopaludina chinensis, and 160 Bellamya aeruginosa snails with A. cantonensis. Then, the four different detection methods were used to diagnose infection in each snail species at 7, 14, 21, and 28 days post exposure. RESULTS: We found no significant difference in the percentages of infected P. canaliculata snails using the four methods to detect A. cantonensis larvae. The radula pressing method had a mean detection rate of 80%, while the lung microscopy (81.3%), tissue homogenization (83.8%), and artificial digestion (85%) methods had slightly greater detection rates. Similarly, the percentages of infected C. chinensis snails that were detected using the radula pressing (80%), tissue homogenization (82.1%), and artificial digestion (83.8%) methods were not significantly different. Finally, the percentages of infected B. aeruginosa snails that were detected using the radula pressing (81.3%), tissue homogenization (81.9%), and artificial digestion (81.4%) methods were not significantly different. These results showed that the radula pressing method had a similar detection rate to traditional lung microscopy, tissue homogenization, or artificial digestion methods. CONCLUSIONS: This study demonstrates a new method for the qualitative screening of gastropods that act as intermediate hosts of A. cantonensis (and other Angiostrongylus species), provides technical support for the control of human angiostrongyliasis, and furthers research on A. cantonensis.

X-Paste improves wound healing in diabetes via NF-E2-related factor/HO-1 signaling pathway.

BACKGROUND: Diabetic foot ulcers (DFU), as severe complications of diabetes mellitus (DM), significantly compromise patient health and carry risks of amputation and mortality. AIM: To offer new insights into the occurrence and development of DFU, focusing on the therapeutic mechanisms of X-Paste (XP) of wound healing in diabetic mice. METHODS: Employing traditional Chinese medicine ointment preparation methods, XP combines various medicinal ingredients. High-performance liquid chromatography (HPLC) identified XP's main components. Using streptozotocin (STZ)-induced diabetic, we aimed to investigate whether XP participated in the process of diabetic wound healing. RNA-sequencing analyzed gene expression differences between XP-treated and control groups. Molecular docking clarified XP's treatment mechanisms for diabetic wound healing. Human umbilical vein endothelial cells (HUVECs) were used to investigate the effects of Andrographolide (Andro) on cell viability, reactive oxygen species generation, apoptosis, proliferation, and metastasis in vitro following exposure to high glucose (HG), while NF-E2-related factor-2 (Nrf2) knockdown elucidated Andro's molecular mechanisms. RESULTS: XP notably enhanced wound healing in mice, expediting the healing process. RNA-sequencing revealed Nrf2 upregulation in DM tissues following XP treatment. HPLC identified 21 primary XP components, with Andro exhibiting strong Nrf2 binding. Andro mitigated HG-induced HUVECs proliferation, metastasis, angiogenic injury, and inflammation inhibition. Andro alleviates HG-induced HUVECs damage through Nrf2/HO-1 pathway activation, with Nrf2 knockdown reducing Andro's proliferative and endothelial protective effects. CONCLUSION: XP significantly promotes wound healing in STZ-induced diabetic models. As XP's key component, Andro activates the Nrf2/HO-1 signaling pathway, enhancing cell proliferation, tubule formation, and inflammation reduction.

Changes in the recent three decades and survey on the current status of surgical treatment for esophageal cancer in China.

BACKGROUND: To review the changes and survey on status quo of the surgical treatment for esophageal cancer in China. The differences in diagnosis and treatment for esophageal cancer among hospitals in different regions across China were also investigated. METHODS: We sent questionnaires to 46 hospitals across China, investigating the volume of esophageal cancer surgeries, surgical procedures, and perioperative management under the guidance of esophageal surgery chiefs. RESULTS: A total of 46 questionnaires were sent out and collected. The survey results showed that in the past 5 years, the volume of surgeries for esophageal cancer remained stable by 23.9% of those hospitals, increased by 30.4%, and decreased by 45.7%. Of those patients treated by surgery, 19.1% were in the early stages, and 80.9% were in locally advanced stages. In terms of surgical procedures, 73.4% of the patients were treated by minimally invasive surgery and 85.7% of esophageal substitutes were a gastric conduit, 93.1% of the substitutes were pulled to the neck through the esophageal bed. For the lymph node dissection, 78.5% of the patients had a complete two-field lymph node dissection including the para-recurrent laryngeal nerve lymph nodes. Of the patients with neoadjuvant therapy, 53.5% received chemotherapy or chemotherapy plus immunotherapy (47.0%), and 43.5% had chemoradiation. CONCLUSIONS: Currently, in China, minimally invasive surgery-oriented multimodality treatment, including complete two-field lymph node dissection, has become the standard approach for esophageal cancer management. Over the past decade, this standardized approach has significantly improved prognosis compared to previous decades.