Biomarkers of Prothrombotic State and Risk Assessment of Exacerbations in Patients with Chronic Obstructive Pulmonary Disease.

Background: Epidemiologic studies have shown that patients with acute exacerbation of COPD (AECOPD) suffer from morbidity and mortality from venous thromboembolism (VTE) and poor diagnosis. Von Willebrand factor (vWF) and plasminogen activator inhibitor type-1 (PAI-1) are frequently investigated in COPD as crucial parameters for coagulation and fibrinolysis. Nevertheless, the role of vWF and PAI-1 in AECOPD needs further exploration. Objective: We sought to evaluate the hypercoagulability in AECOPD and investigate the association of plasma vWF and PAI-1 with occurrence and exacerbation risk of AECOPD patients. Methods: Fifty-seven AECOPD patients and 34 control subjects were enrolled in our study. The concentrations of plasma vWF and PAI-1 antigens were measured by ELISA kit. Independent samples t-test or Wilcoxon rank sum test was applied for group comparison. Spearman correlation analysis, subject work curve (ROC) analysis, and Logistic regression were used to evaluate the role of the plasma vWF and PAI-1 in AECOPD. Results: We observed increased vWF (770.15 ± 325.52 vs 327.62 ± 210.97 ng/mL, P < 0.001) and PAI-1 (0.47 vs 0.17 ng/mL, P < 0.001) levels in AECOPD patients compared with control subjects. Both vWF and PAI-1 are closely related to COPD (vWF: AUC = 0.8741, P < 0.001; PAI-1: AUC = 0.8222, P < 0.001). Moreover, elevated vWF could be an independent risk factor for COPD (OR = 1.01, 95% CI: 1.00-1.01, P = 0.01). We also discovered higher plasma levels of vWF and PAI-1 in the COPD "E" group in contract to "AB" group (vWF: 966.29 ± 251.18 vs 552.21 ± 253.28, P < 0.0001; PAI-1: 1.02 vs 0.38, P = 0.003). And vWF levels increased with increasing COPD exacerbation risk, moreover, plasma vWF positively related with patients' CAT scores and SGRQ scores. In addition, plasma vWF and PAI-1 correlated with each other in total participants and AECOPD subgroup analysis. Conclusion: This study demonstrated that AECOPD patients have a prothrombotic state, as demonstrated by vWF and PAI-1 levels in plasma compared with those in control subjects, and the prothrombotic state increases with increasing COPD exacerbation risk.

Coexistence of Fabry Disease and Membranous Nephropathy: A Case Report.

Fabry disease (FD) is a rare X-linked genetic disease that can coexist with multiple glomerulopathies. We report a 32-year-old female patient of FD coexisting with stage II membranous nephropathy (MN), who presented with proteinuria, normal renal function, and hypo-hidrosis as the only symptom. The renal biopsy manifested a subepithelial immunocomplex deposit in the glomeruli along with basement membrane thickening on light microscopy. Electron microscopy revealed myeloid bodies in some podocytes, which suggested the patient possibly coexistence with Fabry disease. The low activity of α-galactosidase A and one pathogenic heterozygous mutation (c.335G > Ap.Arg112His) in the α-galactosidase A gene confirmed the diagnosis of Fabry disease. This patient's son had the same gene mutation as his mother but without any symptoms at the time. Treatment with ramipril turned urine protein negative. The proteinuria had reoccurred, as shown by the presence of foamy urine, a protein to creatinine ratio of 1.54 g/g, and a blood albumin level of 34.4g/L. The patient was being treated with allisartan isoproxil. However, at the time, the urine protein did not turn negative.

FK4H4-: Planar Tetracoordinate Fluorine Stabilized by Multicenter Ionic Bonding.

Planar tetracoordinate fluorine (ptF) species are very exotic and scarce due to high electronegativity of fluorine. Herein we report the ternary square ptF cluster, D4h FK4H4-, which is composed of a F center, a square K4 ring, and four outer H bridges. It is a true global minimum (GM) structure and possesses good dynamic stability. Bonding analyses indicate that there are four lone pairs for the central F atom, along with four K-H-K three-center two-electron (3c-2e) σ bonds for the peripheral K4H4 ligand ring. The stability of ptF is dominated by multicenter ionic bonds rather than the supposed σ aromaticity of the system. Excitingly, it is a pseudohalogen anion with the VDE 3.57 eV at the CCSD(T) level. The merge of ptF with pseudohalogen anion character makes the FK4H4- cluster an exotic species, which will motivate theoretical and experimental studies on novel ptF species as well as superhalogens.

Erratum: Alkaline Phosphatase Controls Lineage Switching of Mesenchymal Stem Cells by Regulating the LRP6/GSK3ß Complex in Hypophosphatasia: Erratum.

[This corrects the article DOI: 10.7150/thno.27372.].

A pathological complete response to capecitabine plus oxaliplatin regimen combined with tislelizumab in advanced gastric cancer with liver metastases: A case report.

A 66-year-old female patient presenting with dysphagia was diagnosed with stage IV unresectable gastric cancer (cTxN+M1). Multiple liver metastases were identified. The patient subsequently underwent five courses of chemotherapy and immunotherapy, including the capecitabine plus oxaliplatin (XELOX) regimen combined with tislelizumab. After fifth course treatment, it was confirmed that the liver metastases had completely disappeared and the primary tumor had significantly reduced in size. Consequently, a laparoscopy was performed, revealing a retraction-like response in the primary tumor and no obvious metastases in the abdominal cavity. Subsequently, a radical total gastrectomy was carried out through open abdominal surgery. Pathological analysis showed no remaining cancer or lymph node metastases, and the tumor regression was classified as grade 0. The patient has been now receiving additional chemotherapy and immunotherapy to manage any potential residual metastases. This case illustrated the rare and significant impact of combining chemotherapy with tislelizumab, transitioning the treatment approach from palliative to curative. It highlighted the critical role of immunotherapy in managing advanced gastric cancer with liver metastases.

SMGformer: integrating STL and multi-head self-attention in deep learning model for multi-step runoff forecasting.

Accurate runoff forecasting is of great significance for water resource allocation flood control and disaster reduction. However, due to the inherent strong randomness of runoff sequences, this task faces significant challenges. To address this challenge, this study proposes a new SMGformer runoff forecast model. The model integrates Seasonal and Trend decomposition using Loess (STL), Informer's Encoder layer, Bidirectional Gated Recurrent Unit (BiGRU), and Multi-head self-attention (MHSA). Firstly, in response to the nonlinear and non-stationary characteristics of the runoff sequence, the STL decomposition is used to extract the runoff sequence's trend, period, and residual terms, and a multi-feature set based on 'sequence-sequence' is constructed as the input of the model, providing a foundation for subsequent models to capture the evolution of runoff. The key features of the input set are then captured using the Informer's Encoder layer. Next, the BiGRU layer is used to learn the temporal information of these features. To further optimize the output of the BiGRU layer, the MHSA mechanism is introduced to emphasize the impact of important information. Finally, accurate runoff forecasting is achieved by transforming the output of the MHSA layer through the Fully connected layer. To verify the effectiveness of the proposed model, monthly runoff data from two hydrological stations in China are selected, and eight models are constructed to compare the performance of the proposed model. The results show that compared with the Informer model, the 1th step MAE of the SMGformer model decreases by 42.2% and 36.6%, respectively; RMSE decreases by 37.9% and 43.6% respectively; NSE increases from 0.936 to 0.975 and from 0.487 to 0.837, respectively. In addition, the KGE of the SMGformer model at the 3th step are 0.960 and 0.805, both of which can maintain above 0.8. Therefore, the model can accurately capture key information in the monthly runoff sequence and extend the effective forecast period of the model.

Fragmentomics of plasma mitochondrial and nuclear DNA inform prognosis in COVID-19 patients with critical symptoms.

BACKGROUND: The mortality rate of COVID-19 patients with critical symptoms is reported to be 40.5%. Early identification of patients with poor progression in the critical cohort is essential to timely clinical intervention and reduction of mortality. Although older age, chronic diseases, have been recognized as risk factors for COVID-19 mortality, we still lack an accurate prediction method for every patient. This study aimed to delve into the cell-free DNA fragmentomics of critically ill patients, and develop new promising biomarkers for identifying the patients with high mortality risk. METHODS: We utilized whole genome sequencing on the plasma cell-free DNA (cfDNA) from 33 COVID-19 patients with critical symptoms, whose outcomes were classified as survival (n = 16) and death (n = 17). Mitochondrial DNA (mtDNA) abundance and fragmentomic properties of cfDNA, including size profiles, ends motif and promoter coverages were interrogated and compared between survival and death groups. RESULTS: Significantly decreased abundance (~ 76% reduction) and dramatically shorter fragment size of cell-free mtDNA were observed in deceased patients. Likewise, the deceased patients exhibited distinct end-motif patterns of cfDNA with an enhanced preference for "CC" started motifs, which are related to the activity of nuclease DNASE1L3. Several dysregulated genes involved in the COVID-19 progression-related pathways were further inferred from promoter coverages. These informative cfDNA features enabled a high PPV of 83.3% in predicting deceased patients in the critical cohort. CONCLUSION: The dysregulated biological processes observed in COVID-19 patients with fatal outcomes may contribute to abnormal release and modifications of plasma cfDNA. Our findings provided the feasibility of plasma cfDNA as a promising biomarker in the prognosis prediction in critically ill COVID-19 patients in clinical practice.

Hypoglycemic drugs, circulating inflammatory proteins, and gallbladder diseases: A mediation mendelian randomization study.

BACKGROUND: The relationship of hypoglycemic drugs, inflammatory proteins and gallbladder diseases remain unknown. METHODS: Four hypoglycemic drugs were selected as exposure: glucagon-like peptide-1 receptor agonists (GLP-1RA), dipeptidyl peptidase-4 inhibitors (DPP-4i), sodium-glucose cotransporter 2 inhibitors (SGLT-2i), and metformin. The outcome were two gallbladder diseases: cholecystitis and cholelithiasis. Mendelian Randomization (MR) was employed to determine the association between hypoglycemic drugs and gallbladder diseases. RESULTS: DPP-4i and SGLT-2i had no effect on cholecystitis and cholelithiasis. However, a causal relationship was found between inhibition of ETFDH gene, a target of metformin expressed in cultured fibroblasts, and cholelithiasis (OR: 0.84, 95 %CI: (0.72,0.97), p = 0.021), as well as between GLP1R expression in the brain caudate basal ganglia and cholecystitis (OR: 1.29, 95 %CI: (1.11,1.49), p = 0.001). The effect of ETFDH inhibition on cholelithiasis through Interleukin-10 receptor subunit beta (IL-10RB) levels and Neurotrophin-3 (NT-3) levels, with a mediated proportion of 8 % and 8 %, respectively. CONCLUSION: Metformin plays a protective role in cholelithiasis, while GLP-1RA have a harmful effect on the risk of cholecystitis. Metformin may reduce the risk of cholelithiasis by modulating the levels of Neurotrophin-3 (NT-3) and Interleukin-10 receptor subunit beta (IL-10RB). Further clinical and mechanistic studies are required to confirm these findings.

Behaviour of M. aeruginosa-Microplastic composite pollutants in coagulation and sludge storage.

Microcystis aeruginosa (M. aeruginosa) blooms and microplastics pollution have been major global water pollution concern in lakes and reservoirs. In this study, the behaviour of M. aeruginosa-microplastic composite pollutants in inorganic coagulant (PACl) and organic coagulant (HTCC) treatment was investigated. Results showed that, in coagulation stage, the dissolved extracellular polymers secreted by M. aeruginosa could promote the adhesion of microplastics to algae, so as to combine them into the algal flocs, thus improving the sedimentation and removal efficiency of microplastics. On the other hand, whilst microplastics increased the size of algal flocs in PACl coagulation and improved algal removal efficiency, they had the opposite effect on HTCC coagulation. And the removal of algal metabolites including microcystins were improved by the presence of microplastics. In sludge storage stage, the oxidative and mechanical damage effects of microplastics promoted the rupture of M. aeruginosa cells in PACl sludge but not in HTCC sludge, which mean more potential risks in recycling of PACl sludge water. Besides, microplastics promoted the proliferation of beneficial bacteria such as Poterioochromonas and Coccomyxa, which contributed to the control of sludge pollution.

Dual cryoprotection of gelatin-tea polyphenol microgels on surimi by targeting for ice inhibition and component stabilization.

In this study, the gelatine-polyphenol microgels with dual cryoprotective roles were constructed by regulating the ratio of gelatin to tea polyphenols (1:50-1:250). The physicochemical attributes, ice recrystallization inhibition ability of microgels, and their dosage effects (1 %, 2.5 % and 4 %, w/w) on surimi were investigated. The results indicated that increased gelatin caused the reduced size and enhanced viscosity of microgels. Except for high viscosity and antioxidant activity, the GP-5 group also showed great IRI ability with minimum size distribution (125-214 µm2) of ice crystals. Furthermore, 2.5 G group and S group had a comparable TVB-N (3.81, 4.34 mg/100 g), TBARS (1.18, 1.32 mg/kg), sulfhydryl contents (29.52, 25.48 µmol/g) and Ca2+-ATPase activity (0.44, 0.36 µmolPi/gprot/h). Compared to uneven free water distribution of control group, S and 2.5 G group show more even immobilized-water distribution. Thereafter, the dual cryoprotective functions of microgels in surimi offer valuable insights for the development of effective antifreeze agents.

Simple and low-cost colorimetric method for quantification of surface oxygen vacancy in zinc oxide.

Zinc oxide (ZnO) nanoparticles with surface oxygen vacancy (OV) was found to catalyze the colorimetric reaction of 3,3',5,5'-tetramethylbenzidine (TMB)-H2O2, and the absorbance of this TMB-H2O2-ZnO system was strongly dependent the OV concentration on surface of ZnO. By taking advantage of this phenomenon, one colorimetric method was proposed for quantifying surface OV in ZnO. The surface OV amount obtained through this colorimetric method matched well with that obtained through X-ray photoelectron spectroscopy (XPS). This colorimetric method doesn't need any advanced instruments, and can be completed in any an ordinary laboratory. This colorimetric method for detecting surface OV amount was simple, rapid (about 15 min) and low-cost.

Strip clear-cutting transformations increase soil N2O emissions in abandoned Moso bamboo forests.

Forest transformation can markedly impact soil greenhouse gas emissions and soil environmental factors. Due to increasing labor costs and declining bamboo prices, the abandonment of Moso bamboo forests is sharply escalating in recent years, which weakens the carbon sequestration capacity and decreases the ecological function of forests. To improve the ecological quality of abandoned Moso bamboo forests, transformations of abandoned bamboo forests have occurred. However, the impact of such transformations on N2O emissions remains elusive. To bridge the knowledge gap, we conducted a 23-month field experiment to compare the effects of various forest management practices on soil N2O emissions and soil environmental factors in abandoned Moso bamboo forests in subtropical China. These practices included uncut abandonment as a control, intensive management, three intensities (light, moderate, and heavy) of strip clear-cutting with replanting local tree species, and clear-cutting with replanting transformation. During the experimental period, the mean soil N2O flux in abandoned Moso bamboo forests was 13.2 ± 0.1 µg m-2 h-1, representing a 44% reduction compared to intensive management forests. In comparison to the uncut control, light, moderate, and heavy strip clear-cutting and clear-cutting transformations increased soil N2O emission rates by 20%, 43%, 64%, and 94%, respectively. Soil temperature (69-71%), labile C (2-6%) and N (3-8%) were the main factors that explain N2O emissions following the transformation of abandoned Moso bamboo forests. Additionally, replanting could decrease soil N2O emissions by increasing the contribution of soil moisture. Overall, the light strip clear-cutting transformation is suggested to convert abandoned Moso bamboo forests to mitigate N2O emissions.

Enantioselective Synthesis of spiro[indoline-3,4- pyrrolo [3,4-b]pyridines] via Organocatalysed Three-Component Cascade Reaction.

Asymmetric synthesis of spiro[indoline-3,4-pyrrolo [3,4-b]pyridines] derivatives was first developed through organocatalytic cascade Knoevenagel/Michael/cyclization reaction using a quinidine -derived squaramide. Under the optimized conditions, the three-component reaction of isatins, cyanoacetates, and 3-aminomaleimides yield the desired heterocycle-fused spirooxindoles in good yields (78-91%) with 53-99% enantiomer excess (ee). Notably, this reaction enabled a broad substrate scope under mild conditions, and provided a convenient method for enantioselective construction of diverse spirooxindoles combined with dihydropyridine and maleimide skeleton, which brought great potential to build new bioactive chemical entities.

Stachyose ameliorates myocardial ischemia-reperfusion injury by inhibiting cardiomyocyte ferroptosis and macrophage pyroptosis.

Myocardial ischemia-reperfusion injury (MIRI) is a complex pathological process that results from the restoration of blood flow to ischemic myocardium, leading to a series of detrimental effects including oxidative stress and inflammation. Stachyose, a naturally occurring oligosaccharide found in traditional Chinese medicinal herbs, has been suggested to possess therapeutic properties against various pathological conditions. However, its impact on MIRI and the underlying mechanisms have not been fully elucidated. In this study, we aimed to investigate the therapeutic effects of stachyose on MIRI and to uncover the molecular mechanisms involved. Using both in vivo and in vitro models of MIRI, we evaluated the effects of stachyose on cardiac function and cell death pathways. Our results indicate that stachyose significantly improves cardiac function and reduces infarct size in MIRI mice. Mechanistically, stachyose modulates the ferroptotic pathway in cardiomyocytes by upregulating the expression of glutathione peroxidase 4 (GPX4) and reducing lipid peroxides and iron levels. Additionally, stachyose inhibits the pyroptotic pathway in macrophages by downregulating the expression of NLRP3, gasdermin D (GSMD-N), and cleaved-caspase-1, leading to decreased levels of proinflammatory cytokines interleukin (IL)-1ß and IL-18. This study demonstrates that stachyose exerts a protective effect against MIRI by targeting both ferroptosis and pyroptosis pathways, suggesting its potential as a novel therapeutic agent for the treatment of MIRI. Further research is warranted to explore the detailed mechanisms and therapeutic potential of stachyose in clinical settings.

Sliding mode control with self-adaptive parameters of a 5-DOF hybrid robot.

Due to the advantages of high stiffness, high precision, high load capacity and large workspace, hybrid robots are applicable to drilling and milling of complicated components with large sizes, for instance car panels. However, the difficulty in establishing an exact dynamic model and external disturbances affect the high accuracy control directly, which will decrease the machining accuracy and thereby affect the machining quality and efficiency of the system. Sliding mode control is an effective approach for high-order nonlinear dynamic systems since that it is very insensitive to disturbances and parameter variations. However, chattering may exist in traditional sliding mode control with fixed parameters, which results from a constant approaching speed. Besides, the approaching speed will affect the chattering strength directly. To solve these problems, a modified sliding mode controller with self-adaptive parameters is proposed to enhance the trajectory-tracking performance of a 5-degree-of-freedom hybrid robot. Firstly, the kinematic model of the robot is established. Then adopting the principle of virtual work, a rigid dynamic model of the robot is built. Based on the built dynamic model, a modified sliding mode control method is developed, of which the approaching speed is dependent on the system state. Finally, the sliding mode controller with self-adaptive parameters is created for a hybrid robot. The proposed sliding mode controller can achieve a rapid approaching speed and suppress chattering simultaneously. Simulation results demonstrate that the proposed modified sliding mode controller can achieve a comparatively accurate and smooth trajectory, which owns good robustness to external disturbances.

Establishing an induced pluripotent stem cell line (SDPHi006-A) from a healthy Chinese female donor represents an accomplishment.

We isolated peripheral blood mononuclear cells (PBMCs) from a healthy female donor, and successfully converted into induced pluripotent stem cells (iPSCs) by using non-integrating episomal vectors. These iPSCs displayed a normal karyotype, expressed markers of pluripotency, and showed the capacity to differentiate into three germ layers in vitro, which could be utilized for future research endeavors.

Photosynthetic characteristics and genetic mapping of a yellow-green leaf mutant jym165 in soybean.

BACKGROUND: Leaves are important sites for photosynthesis and can convert inorganic substances into organic matter. Photosynthetic performance is an important factor affecting crop yield. Leaf colour is closely related to photosynthesis, and leaf colour mutants are considered an ideal material for studying photosynthesis. RESULTS: We obtained a yellow-green leaf mutant jym165, using ethyl methane sulfonate (EMS) mutagenesis. Physiological and biochemical analyses indicated that the contents of chlorophyll a, chlorophyll b, carotenoids, and total chlorophyll in the jym165 mutant decreased significantly compared with those in Jiyu47 (JY47). The abnormal chloroplast development of jym165 led to a decrease in net photosynthetic rate and starch content compared with that of JY47. However, quality traits analysis showed that the sum of oil and protein contents in jym165 was higher than that in JY47. In addition, the regional yield (seed spacing: 5 cm) of jym165 increased by 2.42% compared with that of JY47 under high planting density. Comparative transcriptome analysis showed that the yellow-green leaf phenotype was closely related to photosynthesis and starch and sugar metabolism pathways. Genetic analysis suggests that the yellow-green leaf phenotype is controlled by a single recessive nuclear gene. Using Mutmap sequencing, the candidate regions related of leaf colour was narrowed to 3.44 Mb on Chr 10. CONCLUSIONS: Abnormal chloroplast development in yellow-green mutants leads to a decrease in the photosynthetic pigment content and net photosynthetic rate, which affects the soybean photosynthesis pathway and starch and sugar metabolism pathways. Moreover, it has the potentiality to increase soybean yield under dense planting conditions. This study provides a useful reference for studying the molecular mechanisms underlying photosynthesis in soybean.

The development and validation of a prognostic prediction modeling study in acute myocardial infarction patients after percutaneous coronary intervention: hemorrhea and major cardiovascular adverse events.

Background: Percutaneous coronary intervention (PCI) is one of the most important diagnostic and therapeutic techniques in cardiology. At present, the traditional prediction models for postoperative events after PCI are ineffective, but machine learning has great potential in identification and prediction of risk. Machine learning can reduce overfitting through regularization techniques, cross-validation and ensemble learning, making the model more accurate in predicting large amounts of complex unknown data. This study sought to identify the risk of hemorrhea and major adverse cardiovascular events (MACEs) in patients after PCI through machine learning. Methods: The entire study population consisted of 7,931 individual patients who underwent PCI at Jiangsu Provincial Hospital and The Affiliated Wuxi Second People's Hospital from January 2007 to January 2022. The risk of postoperative hemorrhea and MACE (including cardiac death and in-stent restenosis) was predicted by 53 clinical features after admission. The population was assigned to the training set and the validation set in a specific ratio by simple randomization. Different machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), random forest (RF), and deep learning neural network (DNN), were trained to build prediction models. A 5-fold cross-validation was applied to correct errors. Several evaluation indexes, including the area under the receiver operating characteristic (ROC) curve (AUC), accuracy (Acc), sensitivity (Sens), specificity (Spec), and net reclassification improvement (NRI), were used to compare the predictive performance. To improve the interpretability of the model and identify risk factors individually, SHapley Additive exPlanation (SHAP) was introduced. Results: In this study, 306 patients (3.9%) experienced hemorrhea, 107 patients (1.3%) experienced cardiac death, and 218 patients (2.7%) developed in-stent restenosis. In the training set and validation set, except for previous PCI and statins, there were no significant differences. XGBoost was observed to be the best predictor of every event, namely hemorrhea [AUC: 0.921, 95% confidence interval (CI): 0.864-0.978, Acc: 0.845, Sens: 0.851, Spec: 0.837 and NRI: 0.140], cardiac death (AUC: 0.939, 95% CI: 0.903-0.975, Acc: 0.914, Sens: 0.950, Spec: 0.800 and NRI: 0.148), and in-stent restenosis (AUC: 0.915; 95% CI: 0.863-0.967, Acc: 0.834, Sens: 0.778, Spec: 0.902 and NRI: 0.077). SHAP showed that the number of stents had the greatest influence on hemorrhea, while age and drug-coated balloon were the main factors in cardiogenic death and stent restenosis (all P<0.05). Conclusions: The XGBoost model (machine learning) performed better than the traditional logistic regression model in identifying hemorrhea and MACE after PCI. Machine learning models can be used as a tool for risk prediction. The machine learning model described in this study can personalize the prediction of hemorrhea and MACE after PCI for specific patients, helping clinicians adjust intervenable features.

Antifungal susceptibility, molecular epidemiology, and clinical risk factors of Candida glabrata in intensive care unit in a Chinese Tertiary Hospital.

Background: The increasing incidence and high mortality rate of Candida glabrata infection in ICU patients is an important issue. Therefore, it is imperative to investigate the antifungal susceptibility profiles and epidemiological characteristics in local regions. Methods: Herein, antifungal susceptibility testing was conducted to determine the minimum inhibitory concentrations (MICs) of eight antifungal drugs. Multilocus sequence typing (MLST) was used to study the strain genotype, geographical distribution, and susceptibility to antifungal agents among C. glabrata isolates. The mechanism of echinocandin resistance was explored by sequencing the FKS1 and FKS2 genes (encoding 1,3-ß-D-glucan synthases) of echinocandin-resistant C. glabrata strains. Moreover, we further investigated the clinical manifestations and the various risk factors of patients infected with C. glabrata in the ICU. Results: We selected 234 C. glabrata isolates from 234 patients in the ICU randomly for the follow-up study. Cross-resistance was found among the ICU C. glabrata isolates. Analysis using MLST showed that the genetic diversity among the C. glabrata isolates was low. Furthermore, sequence type showed no correlation with the antifungal resistance profiles, but was associated with geographical distribution. We also revealed novel mutations in FKS1 (S629P) and FKS2 (W1497stop) that mediated high-level echinocandin resistance (MIC >8 µg/mL). More than 14 days' stay in ICU (P=0.007), Acute Physiology and Chronic Health Evaluation II (APACHE-II) score (P=0.024), prior antifungal exposure (P=0.039) and lung disease (P=0.036) were significantly associated with antifungal resistant/non-wild-type C. glabrata infection. Conclusion: Our study shed light on the antifungal susceptibility, molecular epidemiology, and clinical risk factors of C. glabrata in the ICU of a Chinese Tertiary Hospital. Importantly, we revealed the molecular mechanism of echinocandin resistance. These results highlight the significance of continued surveillance in ICUs and provide data support for the treatment of C. glabrata in clinics.

Process and mechanism of termite impact on soil and plant.

Termites, as a kind of nesting social insects, are often confused as worldwide "pests" because some of their groups have great destructive effects. The vast majority of termites can regulate ecosystem functions and ser-vices by participating in biogeochemical cycles, known as "ecosystem engineers". We reviewed studies on the effects of termites on the physical, chemical and biological characteristics of mound soil ecosystems and the composition and diversity of plant communities. Termites could form unique soil "biogenic aggregates" and "resource heterogeneity patches", which affect microbial community structure, extracellular enzyme activity, physicochemical property and greenhouse gas emission, thereby affecting plant growth, community composition and structure, and vegetation productivity. However, this effect significantly differed among termite groups and functional groups, and was dependent on regional soil environment and microclimate conditions. Meanwhile, termite-mound could effectively improve ecosystem adaptation or resistance to environmental stress through the above process. Future research should focus on the following directions: 1) studying the trophic cascading effect of termite-centered soil multilevel biological network and the potential effect on biogeochemical cycle from microscale (aggregate level) to macroscale (landscape level); 2) exploring the potential of termite mound soil as a fertility amendment in tropical regions, and mining beneficial microbial functional genes to develop related products for termite control.