Reflectance spectroscopy analysis and lithium content estimation in lithium-rich rocks and stream sediments: Insights from Tuanjie Peak, Western Kunlun, China.

Lithium, a rare metal of strategic importance, has garnered heightened global attention. This investigation delves into the laboratory visible-near infrared and short-wavelength infrared reflectance (VNIR-SWIR 350 nm-2500 nm) spectral properties of lithium-rich rocks and stream sediments, aiming to elucidate their quantitative relationship with lithium concentration. This research seeks to pave new avenues and furnish innovative technical solutions for probing sedimentary lithium reserves. Conducted in the Tuanjie Peak region of Western Kunlun, Xinjiang, China, this study analyzed 614 stream sediments and 222 rock specimens. Initial steps included laboratory VNIR-SWIR spectral reflectance measurements and lithium quantification. Following the preprocessing of spectral data via Savitzky-Golay (SG) smoothing and continuum removal (CR), the absorption positions (Pos2210nm, Pos1910nm) and depths (Depth2210, Depth1910) in the rock spectra, as well as the Illite Spectral Maturity (ISM) of the rock samples, were extracted. Employing both the Successive Projections Algorithm (SPA) and genetic algorithm (GA), wavelengths indicative of lithium content were identified. Integrating the lithium-sensitive wavelengths identified by these feature selection methods, A quantitative predictive regression model for lithium content in rock and stream sediments was developed using partial least squares regression (PLSR), support vector regression (SVR), and convolutional neural network (CNN). Spectral analysis indicated that lithium is predominantly found in montmorillonite and illite, with its content positively correlating with the spectral maturity of illite and closely related to Al-OH absorption depth (Depth2210) and clay content. The SPA algorithm was more effective than GA in extracting lithium-sensitive bands. The optimal regression model for quantitative prediction of lithium content in rock samples was SG-SPA-CNN, with a correlation coefficient prediction (Rp) of 0.924 and root-mean-square error prediction (RMSEP) of 0.112. The optimal model for the prediction of lithium content in stream sediment was SG-SPA-CNN, with an Rp and RMSEP of 0.881 and 0.296, respectively. The higher prediction accuracy for lithium content in rocks compared to sediments indicates that rocks are a more suitable medium for predicting lithium content. Compared to the PLSR and SVR models, the CNN model performs better in both sample types. Despite the limitations, this study highlights the effectiveness of hyperspectral technology in exploring the potential of clay-type lithium resources in the Tuanjie Peak area, offering new perspectives and approaches for further exploration.

Natural agents derived Pickering emulsion enabled by silica nanoparticles with enhanced antibacterial activity against drug-resistant bacteria.

The emergence of antibiotic-resistant bacteria such as methicillin-resistant Staphylococcus aureus (MRSA) has become a global health challenge due to the overuse of antibiotics. Natural substances including enzymes and essential oils have shown great potential as alternative treatment options. However, the combinational use of these natural agents remains challenging due to the denaturation of enzymes upon direct contact with oil. In this study, we report the design of a Pickering emulsion containing two natural antibacterial agents, lysozyme and tea tree oil, stabilized by fractal silica nanoparticles. In this design, the enzyme activity is kept and the volatility problem of tea tree oil is mitigated. Due to synergistic bacterial cell wall digestion and membrane disruption functions, potent bactericidal efficacy in vitro against drug-resistant bacteria is achieved. The therapeutic potential is further demonstrated in a wound healing model with drug-resistant bacteria infection, better than a synthetic antibiotic, Ampicillin. This study opens new avenues for the development of natural product-based antimicrobial treatments with promising application potential.

Recent advances in porous organic cages for energy applications.

In recent years, the energy and environmental crises have attracted more and more attention. It is very important to develop new materials and technologies for energy storage and conversion. In particular, it is crucial to develop carriers that store energy or promote mass and electron transport. Emerging porous organic cages (POCs) are very suitable for this purpose because they have inherent advantages including structural designability, porosity, multifunction and post-synthetic modification. POC-based materials, such as pristine POCs, POC composites and POC derivatives also exhibit excellent energy-related properties. This latest perspective provides an overview of the progress of POC-based materials in energy storage and conversion applications, including photocatalysis, electrocatalysis (CO2RR, NO3RR, ORR, HER and OER), separation (gas separation and liquid separation), batteries (lithium-sulfur, lithium-ion and perovskite solar batteries) and proton conductivity, highlighting the unique advantages of POC-based materials in various forms. Finally, we summarize the current advances, challenges and further perspectives of POC-based materials in energy applications. This perspective will promote the design and synthesis of next-generation POC-based materials for energy applications.

Proteogenomic analysis of air-pollution-associated lung cancer reveals prevention and therapeutic opportunities.

Air pollution significantly impacts lung cancer progression, but there is a lack of a comprehensive molecular characterization of clinical samples associated with air pollution. Here, we performed a proteogenomic analysis of lung adenocarcinoma (LUAD) in 169 female never-smokers from the Xuanwei area (XWLC cohort), where coal smoke is the primary contributor to the high lung cancer incidence. Genomic mutation analysis revealed XWLC as a distinct subtype of LUAD separate from cases associated with smoking or endogenous factors. Mutational signature analysis suggested that Benzo[a]pyrene (BaP) is the major risk factor in XWLC. The BaP-induced mutation hotspot, EGFR-G719X, was present in 20% of XWLC which endowed XWLC with elevated MAPK pathway activations and worse outcomes compared to common EGFR mutations. Multi-omics clustering of XWLC identified four clinically relevant subtypes. These subgroups exhibited distinct features in biological processes, genetic alterations, metabolism demands, immune landscape, and radiomic features. Finally, MAD1 and TPRN were identified as novel potential therapeutic targets in XWLC. Our study provides a valuable resource for researchers and clinicians to explore prevention and treatment strategies for air-pollution-associated lung cancers.

Progress of fluorescence imaging in lymph node dissection surgery for prostate and bladder cancer.

Fluorescence imaging is a relatively new imaging method used to visualize different tissue structures to help guide intraoperative operations, which has potential advantages with high sensitivity and contrast compared to conventional imaging. In this work, we review fluorescent contrast agents and devices used for lymphatic system imaging. Indocyanine green is the most widely utilized due to its high sensitivity, specificity, low background fluorescence, and safety profile. In prostate and bladder cancer lymph node dissection, the complex lymphatic drainage can result in missed metastatic nodes and extensive dissection increases the risk of complications like lymphocele, presenting a significant challenge for urologists. Fluorescence-guided sentinel lymph node dissection facilitates precise tumor staging. The combination of fluorescence and radiographic imaging improves the accuracy of lymph node staging. Multimodal imaging presents new potential for precisely identifying metastatic pelvic lymph nodes.

Hierarchical Assembly of High-Nuclearity Copper(I) Alkynide Nanoclusters: Highly Effective CO2 Electroreduction Catalyst toward Hydrocarbons.

The pursuit of precision in the engineering of metal nanoparticle assemblies has long fascinated scientists, but achieving atomic-level accuracy continues to pose a significant challenge. This research sheds light on the hierarchical assembly processes of two high-nuclearity Cu(I) nanoclusters (NCs). By employing a multiligand cooperative stabilization strategy, we have isolated a series of thiacalix[4]arene (TC4A)/alkynyl coprotected Cu(I) NCs (Cux, where x = 9, 13, 17, 22). These NCs are intricately coassembled from the fundamental building units of {Cu4(TC4A)} and alkynyl-stabilized Cu5L6 in various ratios. By capturing active anion templates such as O2-, Cl-, or C22- that are generated in situ, we have further explored the secondary structural self-assembly of these clusters. Cu13 serves as a secondary assembly module for constructing Cu38 and Cu43, which exhibit the highest nuclearity reported to date among Cu(I) NCs encased in macrocyclic ligands. Notably, Cu38 demonstrates an impressive Faradaic efficiency of 62.01% for hydrocarbons at -1.57 V vs RHE during CO2 electroreduction, with 34.03% for C2H4 and 27.98% for CH4. This performance establishes it as an exceptionally rare, large, atomically precise metal NC (nuclearity >30) capable of catalyzing the formation of highly electro-reduced hydrocarbon products. Our research has introduced a new approach for constructing high-nuclearity Cu(I) NCs through a hierarchical assembly method and investigating their potential in the electrocatalytic transformation of CO2 into hydrocarbons.

Machine learning-based discovery of UPP1 as a key oncogene in tumorigenesis and immune escape in gliomas.

Introduction: Gliomas are the most common and aggressive type of primary brain tumor, with a poor prognosis despite current treatment approaches. Understanding the molecular mechanisms underlying glioma development and progression is critical for improving therapies and patient outcomes. Methods: The current study comprehensively analyzed large-scale single-cell RNA sequencing and bulk RNA sequencing of glioma samples. By utilizing a series of advanced computational methods, this integrative approach identified the gene UPP1 (Uridine Phosphorylase 1) as a novel driver of glioma tumorigenesis and immune evasion. Results: High levels of UPP1 were linked to poor survival rates in patients. Functional experiments demonstrated that UPP1 promotes tumor cell proliferation and invasion and suppresses anti-tumor immune responses. Moreover, UPP1 was found to be an effective predictor of mutation patterns, drug response, immunotherapy effectiveness, and immune characteristics. Conclusions: These findings highlight the power of combining diverse machine learning methods to identify valuable clinical markers involved in glioma pathogenesis. Identifying UPP1 as a tumor growth and immune escape driver may be a promising therapeutic target for this devastating disease.

Preparation and demulsification performance of magnetic demulsifier Fe3N@F.

Given the suboptimal emulsification performance and the potential for secondary pollution posed by existing demulsifiers, a facile and highly efficient fluorinated magnetic demulsifier (Fe3N@F) was synthesized via a one-step approach using fluorinated polyether and iron nitride as raw materials.The morphology and structure of the demulsifier were characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and X-ray photoelectron spectroscopy (XPS). The results confirm a successful fluoropolyether coating on the surface of iron nitride. The demulsifying and dehydrating properties were assessed through demulsifying and dehydrating experiments, and the influence of demulsifier addition and demulsifying temperature on the demulsification performance was investigated. Additionally, the demulsification mechanism was analyzed by the microscopic demulsification process. The results indicated that under the condition of the optimum demulsification temperature of 45 °C and the optimum demulsifier dosage of 150 mg L-1, the water removal (%) of the magnetic demulsifier containing fluorine (Fe3N@F) was the highest, and could reach 89.4%. Fe3N@F exhibited excellent magnetic response, the demulsifying rate could reach above 70% after recycling and reusing it 6 times. The application of iron nitride in demulsification presents a novel thought for the advancement of magnetic demulsifiers.

Smart paper-based materials incorporating nitrogen and boron co-doped MXene quantum dots for rapid adsorption and sensitive detection of Cr2O72.

Dichromate ion (Cr2O72-) is a highly toxic chromium-containing compound that poses significant hazards to the digestive, respiratory systems, skin, and mucous membranes. Currently, the detection and adsorption of Cr2O72- face significant challenges, including the time-consuming and low sensitivity nature of traditional analytical methods. The limited efficiency and capacity of existing adsorbents hinder their practical application in real-time water quality monitoring and environmental remediation. Herein, using polyethyleneimine-functionalized (PEI) pulp fiber paper as the substrate, we developed smart paper-based materials (designated as NB-MQDs@PP) incorporated with nitrogen and boron co-doped MXene quantum dots (NB-MQDs) for rapid adsorption and sensitive detection of Cr2O72-. Compared to undoped MQDs, NB-MQDs exhibited longer excitation wavelength and enhanced oxidation stability. As anticipated, NB-MQDs achieved rapid (response time of 10 s) and sensitive (detection limit of 1.2 µM) recognition of Cr2O72- within a wide pH range with a quenching efficiency of 99.9%. Simultaneously, two on-site detection methods, immersion and cyclic filtration, were constructed based on NB-MQDs@PP. The detection limit of the immersion method was 17.0 nM, while the cyclic filtration method had a detection limit as low as 3.8 nM, surpassing the majority of those reported literatures. Remarkably, NB-MQDs@PP exhibited outstanding enrichment capacity towards Cr2O72-, with an adsorption capacity of up to 162.4 mg/g. This work provides a novel strategy for creating unique paper-based materials with excellent capture and monitoring dual-function, which can be customized according to the requirements of various application scenarios.

Effects of short-term nitrogen addition on the recovery of alpine grassland in the Tianshan Mountains of Xinjiang, China.

The restoration of alpine grasslands has garnered significant attention across various sectors. Historically, natural restoration has been the primary approach for grassland recovery, characterized by its prolonged duration. To expedite the recovery of degraded grasslands, it is essential to identify the limiting factors of restoration, enabling efficient and rapid recovery. Appropriate nitrogen (N) addition levels have been considered a potential strategy to enhance the recovery of grassland ecosystems and augment their ecological benefits. However, the effectiveness of N addition in alpine grassland restoration remains debated. This study investigated the impact of five N addition levels (CK: control [0 g/m2]; LN: low N [5 g/m2]; MN: medium N [10 g/m2]; HN: high N [15 g/m2]; SN: severe N [20 g/m2]) and two experimental approaches (N addition once per year [NPY] and three times per year [NTY] at the same dosages) on plant and soil properties and the maximum restoration capacity of alpine meadows. Our findings reveal three key insights: The level of N addition was the primary factor influencing aboveground plant biomass and coverage. Plant diversity decreased under the NTY regime and increased with NPY in the Bayinbruck grassland. N addition significantly altered soil properties, including pH, salinity, soil organic carbon (SOC), soil-available phosphorus (AP), and soil total phosphorus (TP). Notably, soil TP, total nitrogen (TN), and AP substantially impacted plant community structure and diversity. Based on structural equation model (SEM) and analysis of variance (ANOVA), optimal grassland restoration was achieved with the HN (15 g/m2) treatment under NPY and the MN and HN (10 and 15 g/m2) treatments under NTY. Overall, our study offers crucial insights into the conservation, management, and restoration of grassland ecosystems on the Bayinbruck Plateau. It underscores the significance of N addition effects on plant communities, vegetation restoration, and soil properties.

Integrating network pharmacology, molecular docking and non-targeted serum metabolomics to illustrate pharmacodynamic ingredients and pharmacologic mechanism of Haizao Yuhu Decoction in treating hyperthyroidism.

Objective: To explore the pharmacodynamic ingredients and pharmacologic mechanism of Haizao Yuhu Decoction (HYD) in treating hyperthyroidism via an analysis integrating network pharmacology, molecular docking, and non-targeted serum metabolomics. Methods: Therapeutic targets of hyperthyroidism were searched through multi-array analyses in the Gene Expression Omnibus (GEO) database. Hub genes were subjected to the construction of a protein-protein interaction (PPI) network, and GO and KEGG enrichment analyses. Targets of active pharmaceutical ingredients (APIs) in HYD and those of hyperthyroidism were intersected to yield hub genes, followed by validations via molecular docking and non-targeted serum metabolomics. Results: 112 hub genes were identified by intersecting APIs of HYD and therapeutic targets of hyperthyroidism. Using ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) in both negative and positive ion polarity modes, 279 compounds of HYD absorbed in the plasma were fingerprinted. Through summarizing data yielded from network pharmacology and non-targeted serum metabolomics, 214 common targets were identified from compounds of HYD absorbed in the plasma and therapeutic targets of hyperthyroidism, including PTPN11, PIK3CD, EGFR, HRAS, PIK3CA, AKT1, SRC, PIK3CB, and PIK3R1. They were mainly enriched in the biological processes of positive regulation of gene expression, positive regulation of MAPK cascade, signal transduction, protein phosphorylation, negative regulation of apoptotic process, positive regulation of protein kinase B signaling and positive regulation of MAP kinase activity; and molecular functions of identical protein binding, protein serine/threonine/tyrosine kinase activity, protein kinase activity, RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding and protein binding. A total of 185 signaling pathways enriched in the 214 common targets were associated with cell proliferation and angiogenesis. Conclusion: HYD exerts a pharmacological effect on hyperthyroidism via inhibiting pathological angiogenesis in the thyroid and rebalancing immunity.

Advanced Palladium Nanosheet-Enhanced Phototherapy for Treating Wound Infection Caused by Multidrug-Resistant Bacteria.

With the increasing spread of multidrug-resistant (MDR) bacteria worldwide, it is needed to develop antibiotics-alternative strategies for the treatment of bacterial infections. This work develops a multifunctional single-component palladium nanosheet (PdNS) with broad-spectrum and highly effective bactericidal activity against MDR bacteria. PdNS exerts its endogenous nanoknife (mechanical cutting) effect and peroxidase-like activity independent of light. Under near-infrared region (NIR) light irradiation, PdNS exhibits photothermal effect to produce local heat and meanwhile possesses photodynamic effect to generate 1O2; notably, PdNS has catalase-like activity-dependent extra photodynamic effect upon H2O2 addition. PdNS+H2O2+NIR employs a collectively synergistic mechanism of nanoknife effect, peroxidase/catalase-like catalytic activity, photothermal effect, and photodynamic effect for bacterial killing. PdNS+H2O2+NIR causes compensatory elevated phospholipid biosynthesis, disordered energy metabolism, increased cellular ROS levels and excessive oxidative stress, and inhibited nucleic acid synthesis in bacteria. In mice, PdNS+H2O2+NIR gives >92.7% bactericidal rates at infected wounds and almost the full recovery of infected wounds, and it leads to extensive down-regulation of proinflammatory pathways and comprehensive up-regulation of wound healing pathways, conferring elevated inflammation resolution and meanwhile accelerated wound repair. PdNS+H2O2+NIR represents a highly efficient nanoplatform for photoenhanced treatment of superficial infections.

Exploring the significance and potential mechanisms of hippo pathway-associated genes in prognosis of glioma patients.

PURPOSE: Despite the efforts of countless researchers to develop glioma treatment strategies, the current therapeutic effect of glioma is still not ideal, and it is necessary to further explore the mechanism to guide treatment. Thus, this study aims to introduce a novel approach for predicting patient prognosis and guiding further treatment interventions. METHODS: Initially, we conducted a differential gene expression analysis to identify Hippo pathway-associated genes overexpressed in tumors and determined genes correlated with prognosis. Subsequently, employing cluster analysis, we categorized samples into two groups and performed further analyses including prediction, immune cell infiltration abundance, and drug response rates. We utilized weighted gene co-expression analysis to reveal gene sets with high co-variation, delineate inter-sample gene correlation patterns, and conduct enrichment analysis. Prognostic models were built using ten machine learning algorithms combined in 101 different combinations, followed by evaluation and validation. Immune infiltration analysis, differential expression analysis of depleted T cell-related markers, drug sensitivity analysis, and exploration of pathway dysregulation were performed for different risk groups. Quality control and batch integration were performed, and single-cell data were analyzed using dimensionality reduction clustering algorithms and annotation tools to evaluate the activity of the prognostic model in malignant cells. RESULTS: We conducted data filtering to identify genes overexpressed in tumors, intersecting these genes with Hippo pathway-related genes, identifying 62 genes correlated with prognosis, and performing cluster analysis to divide tumor tissues into two groups. Cluster 2 exhibited a poorer prognosis and demonstrated differences in immune cell infiltration. Utilizing weighted gene co-expression analysis on Cluster 2, we identified gene modules, conducted functional enrichment analysis, and delineated pathways. Employing a combined model based on ten machine learning algorithm combinations, we selected the optimal prognostic model system and validated the model's predictive ability within the dataset. Through immune-related analysis and drug sensitivity analysis, we uncovered differences in immune infiltration and varying sensitivities to chemotherapy drugs. Additionally, the enrichment analysis of gene set revealed discrepancies in upregulation within relevant pathways between the high and low-risk groups. Finally, annotation and evaluation of malignant cells via single-cell analysis showed increased activity of the prognostic model and variations in distribution across different prognostic levels in malignant cells. CONCLUSION: This study introduces a novel approach utilizing the Hippo pathway and associated genes for glioma prognosis research, demonstrating the potential and significance of this method in evaluating the outcome for patients with glioma. These findings hold substantial clinical significance in guiding therapy and predicting outcomes for individuals diagnosed with glioma, offering significant clinical utility.

Case Series Analysis of Diagnosis and Treatment of Gastrointestinal Metastasis in Lung Cancer Patients.

Objective: This study was designed to investigate the clinical, pathological, endoscopic, and imaging characteristics of gastrointestinal metastasis in patients with lung cancer. Methods: The clinical data of 20 patients with primary lung cancer with gastrointestinal metastasis. Results: This study included sixteen men and four women, ranging in age from 31 to 75 years. The time interval from the diagnosis of lung cancer to the detection of gastrointestinal metastasis ranged from 13 to 142 months. The most common sites of metastasis were the small intestine (eight cases), colon (four cases), and upper gastrointestinal tract (eight cases). The major symptoms included obstruction, perforation, abdominal pain, abdominal distension, anorexia, and anemia. The predominant pathological type was poorly differentiated adenocarcinoma (seventeen cases). A single ulcer was mostly seen on endoscopy, and some cases showed a slight depression of the intestinal wall. The CT and PET-CT scan revealed bowel wall thickening, intraluminal polypoid masses, and intestinal perforation. Conclusion: Gastrointestinal metastasis of lung cancer is mainly observed in the small intestine, colon, and stomach, and is often detected when severe complications such as gastrointestinal obstruction and perforation occurred. Regular evaluation of gastrointestinal conditions during lung cancer diagnosis and treatment is recommended to improve the diagnostic accuracy and prevent misdiagnosis.

A cross-cultural comparison of intrinsic and extrinsic motivational drives for learning.

Intrinsic motivational drives, like the autonomous feeling of control, and extrinsic motivational drives, like monetary reward, can benefit learning. Extensive research has focused on neurobiological and psychological factors that affect these drives, but our understanding of the sociocultural factors is limited. Here, we compared the effects of autonomy and rewards on episodic recognition memory between students from Dutch and Chinese universities. In an exploratory learning task, participants viewed partially obscured objects that they needed to subsequently remember. We independently manipulated autonomy, as volitional control over an exploration trajectory, as well as the chance to receive monetary rewards. The learning task was followed by memory tests for objects and locations. For both cultural groups, we found that participants learned better in autonomous than non-autonomous conditions. However, the beneficial effect of reward on memory performance was stronger for Chinese than for Dutch participants. By incorporating the sociocultural brain perspective, we discuss how differences in norms and values between Eastern and Western cultures can be integrated with the neurocognitive framework about dorsal lateral and ventral medial prefrontal cortex and dopaminergic reward modulations on learning and memory. These findings have important implications for understanding the neurocognitive mechanisms in which both autonomy and extrinsic rewards are commonly used to motivate students in the realm of education and urge more attention to investigate cultural differences in learning.

A Real-Time Global Re-Localization Framework for a 3D LiDAR-Based Navigation System.

Place recognition is widely used to re-localize robots in pre-built point cloud maps for navigation. However, current place recognition methods can only be used to recognize previously visited places. Moreover, these methods are limited by the requirement of using the same types of sensors in the re-localization process and the process is time consuming. In this paper, a template-matching-based global re-localization framework is proposed to address these challenges. The proposed framework includes an offline building stage and an online matching stage. In the offline stage, virtual LiDAR scans are densely resampled in the map and rotation-invariant descriptors can be extracted as templates. These templates are hierarchically clustered to build a template library. The map used to collect virtual LiDAR scans can be built either by the robot itself previously, or by other heterogeneous sensors. So, an important feature of the proposed framework is that it can be used in environments that have never been visited by the robot before. In the online stage, a cascade coarse-to-fine template matching method is proposed for efficient matching, considering both computational efficiency and accuracy. In the simulation with 100 K templates, the proposed framework achieves a 99% success rate and around 11 Hz matching speed when the re-localization error threshold is 1.0 m. In the validation on The Newer College Dataset with 40 K templates, it achieves a 94.67% success rate and around 7 Hz matching speed when the re-localization error threshold is 1.0 m. All the results show that the proposed framework has high accuracy, excellent efficiency, and the capability to achieve global re-localization in heterogeneous maps.

Advancements in Optical Resonator Stability: Principles, Technologies, and Applications.

This paper provides an overview of the study of optical resonant cavity stability, focusing on the relevant principles, key technological advances, and applications of optical resonant cavities in a variety of high-precision measurement techniques and modern science and technology. Firstly, the vibration characteristics, thermal noise, and temperature characteristics of the reference cavity are presented. Subsequently, the report extensively discusses the advances in key technologies such as mechanical vibration isolation, thermal noise control, and resistance to temperature fluctuations. These advances not only contribute to the development of theory but also provide innovative solutions for practical applications. Typical applications of optical cavities in areas such as laser gyroscopes, high-precision measurements, and gravitational wave detection are also discussed. Future research directions are envisioned, emphasising the importance of novel material applications, advanced vibration isolation technologies, intelligent temperature control systems, multifunctional integrated optical resonator design, and deepening theoretical models and numerical simulations.

Response of Plant Endophyte Communities to Heavy Metal Stress and Plant Growth Promotion by the Endophyte Serratia marcescens (Strain JG1).

Effects of heavy metals on soil microbial communities have been extensively studied due to their persistence in the environment and imposed threats to living organisms; however, there is a lack of in-depth studies of the impacts of heavy metals on plant endophyte communities. Therefore, the responses of plant endophyte communities to different concentrations of heavy metals were investigated in this study. The endophyte communities of plants existing in severely (W1, Pb, 110.49 mg/kg, Cd, 1.11 mg/kg), moderately (W2, Pb, 55.06 mg/kg, Cd, 0.48 mg/kg), and mildly (W3, Pb, 39.06 mg/kg, Cd, 0.20 mg/kg) contaminated soils were analyzed by 16s rRNA high-throughput Illumina sequencing. Furthermore, networks were constructed to illustrate the relationships between microorganisms and environmental factors. High-quality sequences were clustered at a 97% similarity level. Results revealed that the diversity of the community and relative abundance of Cyanobacteria phylum increased with decreasing levels of pollution. Cyanobacteria and Proteobacteria were found to be the dominant phylum, while Methylobacterium and Sphingomonas were observed as the dominant genus. Tukey's HSD test showed that the relative abundances of Cyanobacteria and Proteobacteria phyla and Methylobacterium and Sphingomonas genera differed significantly (p < 0.01) among the plants of the three sample sites. Environmental factor analysis revealed a significant negative correlation (p < 0.01) of Cyanobacteria and a significant positive correlation (p < 0.01) of Methylobacterium with the heavy metal content in the environment. These findings suggest that Cyanobacteria and Methylobacterium may be phylum and genus indicators, respectively, of heavy metal toxicity. Tax4Fun analysis showed the effect of heavy metal toxicity on the abundance of genes involved in plant metabolism. In addition, culturable endophytic strains were isolated to study their resistance to heavy metal stress and their ability to promote plant growth. The potting tests showed that the JG1 strain was tolerant to heavy metals, and it could significantly promote the growth of the host plant under stress caused by multiple heavy metals. Compared to the control, the JG1-treated plants showed a 23.14% increase in height and a 12.84% increase in biomass. Moreover, AP, AK, and HN contents in JG1-treated plants were 20.87%, 12.55%, and 9.03% higher, respectively, under heavy metal stress. The results of this study provide a scientific basis for the construction of an efficient plant endophyte restoration system.

Complicated atrial myxoma with coro-cameral fistula arising from its feeding branch: a case report.

A 56-year-old man with a 5-year history of paroxysmal palpitations, which have worsened over the past year, was diagnosed with atrial fibrillation. During evaluation, transesophageal echocardiography revealed a left atrium (LA) tumoral mass attached to the atrial septal fossa ovale, with intra-tumoral blood flow and blood stream draining from the mass. Both coronary computed tomography angiography and coronary angiography demonstrated a coro-cameral fistula connection between the left circumflex artery (LCX) branch and the LA. In addition, they showed feeding arteries of the mass arising from the LCX. The patient underwent surgical resection of the LA mass and repair of the coronary artery fistula. Intraoperative exploration revealed a 1.7 cm × 1.0 cm jelly-like, brittle LA mass and confirmed a rupture of the supplying artery, leading to a coronary artery-left atrial fistula. Surgical ligation was executed to ensure complete sealing of the supplying coronary branch within the atrial septum. Histopathological examination confirmed the diagnosis of left atrial myxoma. The 6-month follow-up indicated no recurrence of the myxoma and restoration of sinus rhythm after radiofrequency ablation. In the literature, cases of a left circumflex artery branch-left atrial fistula due to rupture of the artery supplying a left atrial myxoma are rare.