Targeted aggregation of PETase towards surface of Stenotrophomonas pavanii for degradation of PET microplastics.

Polyethylene terephthalate (PET) is one of the most widely used plastics, but its fragmentation into microplastics poses significant environmental challenges. The recycling of PET microplastics is hindered by their low solubility and widespread dispersion in the environment, making microbial in-situ degradation a promising solution. However, existing PET-degrading strains exhibited the limited effectiveness, primarily due to the diffusion of secreted hydrolases away from the PET surface. In this study, Stenotrophomonas pavanii JWG-G1 was engineered to achieve the targeted aggregation of PET hydrolase PETase on the cell surface by fusing it with an endogenous anchor protein. This approach aims to maximise the local concentration of PETase around PET, thereby increasing the overall rate of PET degradation. The PETase surface-aggregated system, S. pavanii/PaL-PETase, demonstrated the highest degradation efficiency, achieving 63.3 % degradation of low-crystallinity PET (lcPET) and 27.3 % degradation of high-crystallinity PET bottles (hcPET) at 30 °C. This represents the highest degradation rate reported for a displayed whole-cell system at ambient temperature. Furthermore, this system exhibited broad-spectrum degradation activity against various polyesters. These findings suggest that this system offers a promising, eco-friendly solution to PET and other polyester pollution, with potential implications for environmental bioremediation strategies.

Deep-Saddle-Shaped Nanographene Induced by Four Heptagons: Efficient Synthesis and Properties.

The construction of multiple heptagonal rings in nanographene is the key step for obtaining exotic carbon nanostructures with a negative curvature and intriguing properties. Herein, a novel saddle-shaped nanographene (1) with four embedded heptagons is synthesized via a highly efficient one-shot Scholl reaction from a predesigned oligophenylene precursor. Notably, a quadruple [6]helicene intermediate was also obtained and isolated by controlling the Scholl reaction conditions. Interestingly, the single crystal structures of 1 display a saddle geometry induced by the four embedded heptagons, resulting in a deep curvature with a width of 16.5 Å and a depth of 8.0 Å. Theoretical calculations at the molecular level suggest a weak antiaromatic character of the heptagons in 1. Remarkably, compound 1 exhibits dual fluorescence from S1 and S2. The deep-saddle-shaped geometry in 1 defines host-guest interactions with fullerenes, which were explored in titration experiments and by theoretical methods. The resulting 1@C60 are stable and are subject to an electron transfer from photoexcited 1 to C60. Our current study underscores the influence of heptagon rings on the photophysical, self-assembly, and electron-donating properties of NGs.

Dissociable dorsal medial prefrontal cortex ensembles are necessary for cocaine seeking and fear conditioning in mice.

The dorsal medial prefrontal cortex (dmPFC) plays a dual role in modulating drug seeking and fear-related behaviors. Learned associations between cues and drug seeking are encoded by a specific ensemble of neurons. This study explored the stability of a dmPFC cocaine seeking ensemble over 2 weeks and its influence on persistent cocaine seeking and fear memory retrieval. In the first series of experiments, we trained TetTag c-fos-driven-EGFP mice in cocaine self-administration and tagged strongly activated neurons with EGFP during the initial day 7 cocaine seeking session. Subsequently, a follow-up seeking test was conducted 2 weeks later to examine ensemble reactivation between two seeking sessions via c-Fos immunostaining. In the second series of experiments, we co-injected viruses expressing TRE-cre and a cre-dependent inhibitory PSAM-GlyR into the dmPFC of male and female c-fos-tTA mice to enable "tagging" of cocaine seeking ensemble or cued fear ensemble neurons with inhibitory chemogenetic receptors. These c-fos-tTA mice have the c-fos promoter that drives expression of the tetracycline transactivator (tTA). The tTA can bind to the tetracycline response element (TRE) site on the viral construct, resulting in the expression of cre-recombinase, which enables the expression of cre-dependent inhibitory chemogenetic receptors and fluorescent reporters. Then we investigated ensemble contribution to subsequent cocaine seeking and fear recall during inhibition of the tagged ensemble by administering uPSEM792s (0.3 mg/kg), a selective ligand for PSAM-GlyR. In both sexes, there was a positive association between the persistence of cocaine seeking and the proportion of reactivated EGFP+ neurons within the dmPFC. More importantly, inhibition of the cocaine seeking ensemble suppressed cocaine seeking, but not recall of fear memory, while inhibition of the fear ensemble reduced conditioned freezing but not cocaine seeking. The results demonstrate that cocaine and fear recall ensembles in the dmPFC are stable, but largely exclusive from one another.

π-Extension of Multiple Resonance Core: Double Helical and Heptagon Embedded Nanographenes.

Multiple resonance (MR) boron-nitrogen doped polycyclic aromatic hydrocarbons (BN-PAHs) showed compelling thermally activated delayed fluorescence (TADF), surpassing those of their hydrocarbon analogs. However, the structural variety of π-extended BN-PAHs remains narrow. In this study, we synthesized three double helical BN-doped nanographenes (BN-NGs), 2a-2c, via the π-extension of the MR core. During the formation of 2a, a nanographene with one heptagon (1a) was obtained, whereas subsequent dehydrocyclization of the [6]helicene units within 2b-2c led to heptagon structures, yielding other two BN-NGs containing double heptagons (1b-1c). These BN-NGs (2a-2c and 1a-1c) showed pronounced redshifts of 100-190 nm compared to the parent MR core while preserving the TADF characteristics and prolonging the delayed fluorescence lifetime to the millisecond level. Furthermore, the integration of heptagon ring into 1a-1c expanded the conjugation, reduced the oxidation potentials, and yielded a more flexible framework compared to those of 2a-2c. The enantiomers of 2a-2c, 1a, and 1c were resolved and their chiroptical properties were studied. Notably, 1a and 1c exhibited the increased chiroptical dissymmetry factors.

Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis: A Bidirectional Mendelian Randomization Study.

Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization (MR) analysis. Methods Bidirectional MR was used to analyze pooled data from different genome-wide association studies (GWAS) to investigate the causal relationships between plasma metabolites and osteoporosis. The causal effect of plasma metabolites on osteoporosis was estimated using the inverse variance weighted method, intersections of statistically significant metabolites obtained from different sources of osteoporosis-related GWAS aggregated data was determined, and then sensitivity analysis was performed on these metabolites. Heterogeneity between single nucleotide polymorphisms was evaluated by Cochran's Q test. Horizontal pleiotropy was assessed through the application of the MR-Egger intercept method and the MR-PRESSO method. The causal effect of osteoporosis on plasma metabolites was also evaluated using the inverse variance weighted method. Additionally, pathway analysis was conducted to identify potential metabolic pathways involved in the regulation of osteoporosis. Results After primary analysis and a series of sensitivity analyses, 77 and 61 plasma metabolites were identified as having a causal relationship with osteoporosis from the GWAS data in the GCST90038656 and GCST90044600 datasets , respectively. Five common metabolites were identified via intersection. X-13684 levels (GCST90038656: OR = 0.999, 95% CI, 0.998-1.000, P = 0.004; GCST90044600 (OR = 0.834, 95% CI, 0.700-0.993, P = 0.042), and the glucose-to-maltose ratio (GCST90038656: OR = 0.998, 95% CI, 0.997-1.000, P = 0.025; GCST90044600: OR = 0.752, 95% CI, 0.576-0.981, P = 0.036) were negatively associated with osteoporosis, whereas glycoursodeoxycholate levels (GCST90038656: OR = 1.002, 95% CI, 1.000-1.003, P = 0.032; GCST90044600: OR = 1.331, 95% CI, 1.036-1.709, P = 0.025) and arachidoylcarnitine (C20) levels (GCST90038656: OR = 1.001, 95% CI, 1.000-1.003, P = 0.039; GCST90044600: OR = 1.237; 95% CI, 1.008-1.518, P = 0.042) were positively associated with osteoporosis. The relationship between X-11299 levels and osteoporosis showed contradictory results (GCST90038656: OR= 0.998, 95% CI, 0.997-1.000, P = 0.026; GCST90044600: OR = 1.402, 95% CI, 1.071-1.834, P = 0.014). Pathway analysis indicated that glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, galactose metabolism, arginine biosynthesis, and starch and sucrose metabolism pathways were participated in the development of osteoporosis. Conclusion We found a causal relationship between plasma metabolites and osteoporosis. These results offer novel perspectives that have implications for targeted interventions focused on metabolites in the management of osteoporosis.

Neuropathic pain has sex-specific effects on oxycodone-seeking and non-drug-seeking ensemble neurons in the dorsomedial prefrontal cortex of mice.

Approximately 50 million Americans suffer from chronic pain, and nearly a quarter of chronic pain patients have reported misusing opioid prescriptions. Repeated drug seeking is associated with reactivation of an ensemble of neurons sparsely scattered throughout the dorsomedial prefrontal cortex (dmPFC). Prior research has demonstrated that chronic pain increases intrinsic excitability of dmPFC neurons, which may increase the likelihood of reactivation during drug seeking. We tested the hypothesis that chronic pain would increase oxycodone-seeking behaviour and that the pain state would differentially increase intrinsic excitability in dmPFC drug-seeking ensemble neurons. TetTag mice self-administered intravenous oxycodone. After 7 days of forced abstinence, a drug-seeking session was performed, and the ensemble was tagged. Mice received spared nerve injury (SNI) to induce chronic pain during the period between the first and second seeking session. Following the second seeking session, we performed electrophysiology on individual neurons within the dmPFC to assess intrinsic excitability of the drug-seeking ensemble and non-ensemble neurons. SNI had no impact on sucrose seeking or intrinsic excitability of dmPFC neurons from these mice. In females, SNI increased oxycodone seeking and intrinsic excitability of non-ensemble neurons. In males, SNI had no impact on oxycodone seeking or neuron excitability. Data from females are consistent with clinical reports that chronic pain can promote drug craving and relapse and support the hypothesis that chronic pain itself may lead to neuroadaptations which promote opioid seeking.

Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.

PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for clinical treatment. METHOD: The study population was collected from the national claims database in China. A total of 4,532 patients aged 4-18 who began risperidone therapy for mania between September 2013 and October 2019 were identified. The data were randomly divided into two datasets: training (80%) and testing (20%). Five regularly used machine learning methods were employed, in addition to the SuperLearner (SL) algorithm, to develop prediction models for the continuation of atypical antipsychotic therapy. The area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI) was utilized. RESULTS: In terms of discrimination and robustness in predicting risperidone treatment continuation, the generalized linear model (GLM) performed the best (AUC: 0.823, 95% CI: 0.792-0.854, intercept near 0, slope close to 1.0). The SL model (AUC: 0.823, 95% CI: 0.791-0.853, intercept near 0, slope close to 1.0) also exhibited significant performance. Furthermore, the present findings emphasize the significance of several unique clinical and socioeconomic variables, such as the frequency of emergency room visits for nonmental health disorders. CONCLUSIONS: The GLM and SL models provided accurate predictions regarding risperidone treatment continuation in children and adolescents with episodes of mania and hypomania. Consequently, applying prediction models in atypical antipsychotic medicine may aid in evidence-based decision-making.

[Correlation of environment temperature with the incidence of testicular torsion].

Objective： To explore the influence of environment temperature on the incidence of testicular torsion. METHODS: We collected the clinical data on 172 cases of testicular torsion diagnosed in the Second Hospital of Hebei Medical University from December 2013 to December 2020. According to the local environment temperature on the day of onset, we divided the patients into groups A (below 0℃), B (0－10℃), C (10－20℃) and D (above 20℃), and compared the incidence rates of testicular torsion among the four groups, followed by correlation analysis. RESULTS: The incidence rate of testicular torsion was 12.8% (n = 22) in group A, 35.5% (n = 61) in B, 34.9% (n = 60) in C and 16.9% (n = 29) in D, the highest at 0－10℃ in group B, with statistically significant difference among the four groups (χ2 = 29.07, P <0.001). Spearman correlation analysis indicated that the incidence of testicular torsion was negatively correlated with the environment temperature (r = －0.261, P <0.01), with no statistically significant difference among different seasons (χ2 = 5.349, P >0.05), but higher in autumn and winter than in the other two seasons. CONCLUSION: The incidence of testicular torsion is negatively correlated with the environment temperature, elevated when the temperature decreases, but has no statistically significant difference among different seasons, though relatively higher in autumn and winter.

Topologically Localized Vibronic Excitations in Second-Layer Graphene Nanoribbons.

It is of fundamental importance to characterize the intrinsic properties, like the topological end states, in the on-surface synthesized graphene nanoribbons (GNRs), but the strong electronic interaction with the metal substrate usually smears out their characteristic features. Here, we report our approach to investigate the vibronic excitations of the topological end states in self-decoupled second-layer GNRs, which are grown using an on-surface squeezing-induced spillover strategy. The vibronic progressions show highly spatially localized distributions at the second-layer GNR ends, which can be ascribed to the decoupling-extended lifetime of charging through resonant electron tunneling at the topological end states. In combination with theoretical calculations, we assign the vibronic progressions to specific vibrational modes that mediate the vibronic excitations. The spatial distribution of each resolved excitation shows evident characteristics beyond the conventional Franck-Condon picture. Our work by direct growth of second-layer GNRs provides an effective way to explore the interplay between the intrinsic electronic, vibrational, and topological properties.

Pathogen-driven Pseudomonas reshaped the phyllosphere microbiome in combination with Pseudostellaria heterophylla foliar disease resistance via the release of volatile organic compounds.

BACKGROUND: Continuous monocropping obstacles are common in plants, especially medicinal plants, resulting in disease outbreaks and productivity reductions. Foliar disease, mainly caused by Fusarium oxysporum, results in a severe decrease in the yield of Pseudostellaria heterophylla annually. Determining an effective biomethod to alleviate this disease is urgently needed to improve its productivity and quality. RESULTS: This study screened thirty-two keystone bacterial genera induced by pathogens in P. heterophylla rhizosphere soil under continuous monocropping conditions. Pseudomonas, Chryseobacterium, and Flavobacterium, referred to as the beneficial microbiota, were significantly attracted by pathogen infection. The P. palleroniana strain B-BH16-1 can directly inhibit the growth and spore formation of seven primary pathogens of P. heterophylla foliar disease by disrupting fusaric acid production via the emission of volatile organic compounds (VOCs). In addition, strain B-BH16-1 enhances the disease resistance of P. heterophylla by obliterating the pathogen and assembling beneficial microbiota. CONCLUSION: Pathogen-induced Pseudomonas reshaped phyllosphere microbial communities via direct antagonism of pathogens and indirect disruption of the pathogen virulence factor biosynthesis to enhance disease suppression and improve yields. These results show that inhibiting pathogen virulence biosynthesis to reshape the plant microbial community using disease-induing probiotics will be an innovative strategy for managing plant disease, especially under continuous monoculture conditions.

Glutathione-activated biotin-targeted dual-modal imaging probe with improved PDT/PTT synergistic therapy.

BACKGROUND: Glutathione (GSH), a highly abundant thiol compound within cells, plays a critical role in physiological processes and exhibits close correlation with cancer. Among molecular imaging technologies, most probes have relatively short emission wavelengths and lack photoacoustic imaging (PA) capability, resulting in the inability to obtain tissue images with high penetration depth. The presence of GSH in the tumor microenvironment neutralizes ROS, diminishing the therapeutic effect of PDT, thus resulting in often unsatisfactory therapeutic efficacy. Therefore, it is imperative to develop a dual-modal probe for the detection of GSH and the diagnosis and treatment of cancer. RESULTS: In this study, we synthesized a novel dual-modal probe, Cy-Bio-GSH, utilizing near-infrared fluorescence (NIRF) and photoacoustic (PA) imaging techniques for GSH detection. The probe integrates cyanine dye as the fluorophore, nitroazobenzene as the recognition moiety, and biotin as the tumor-targeting moiety. Upon reacting with GSH, the probe emits NIR fluorescence at 820 nm and generates a PA signal. Significantly, this reaction activates the photodynamic and photothermal properties of the probe. By depleting GSH and employing a synergistic photothermal therapy (PTT) treatment, the therapeutic efficacy of photodynamic therapy (PDT) is remarkably enhanced. In-vivo experiments confirm the capability of the probe to detect GSH via NIRF and PA imaging. Notably, the combined tumor-targeting ability and PDT/PTT synergistic therapy enhance therapeutic outcomes for tumors and facilitate their ablation. SIGNIFICANCE: A novel tumor-targeting and dual-modal imaging probe (Cy-Bio-GSH) is synthesized, exhibiting remarkable sensitivity and selectivity to GSH, enabling the visualization of GSH in cells and the differentiation between normal and cancer cells. Cy-Bio-GSH enhances PDT/PTT with effective killing of cancer cells and makes the ablation of tumors in mice. This work represents the first tumor-targeting probe for GSH detection, and provides crucial tool for cancer diagnosis and treatment by dual-modal imaging with improved PDT/PTT synergistic therapy.

Development of a machine learning-based model to predict major adverse events after surgery for type A aortic dissection complicated by malnutrition.

Objective: This study aims to develop a predictive model for the risk of major adverse events (MAEs) in type A aortic dissection (AAAD) patients with malnutrition after surgery, utilizing machine learning (ML) algorithms. Methods: We retrospectively collected clinical data from AAAD patients with malnutrition who underwent surgical treatment at our center. Through least absolute shrinkage and selection operator (LASSO) regression analysis, we screened for preoperative and intraoperative characteristic variables. Based on the random forest (RF) algorithm, we constructed a ML predictive model, and further evaluated and interpreted this model. Results: Through LASSO regression analysis and univariate analysis, we ultimately selected seven feature variables for modeling. After comparing six different ML models, we confirmed that the RF model demonstrated the best predictive performance in this dataset. Subsequently, we constructed a model using the RF algorithm to predict the risk of postoperative MAEs in AAAD patients with malnutrition. The test set results indicated that this model has excellent predictive efficacy and clinical applicability. Finally, we employed the Shapley additive explanations (SHAP) method to further interpret the predictions of this model. Conclusion: We have successfully constructed a risk prediction model for postoperative MAEs in AAAD patients with malnutrition using the RF algorithm, and we have interpreted the model through the SHAP method. This model aids clinicians in early identification of high-risk patients for MAEs, thereby potentially mitigating adverse clinical outcomes associated with malnutrition.

Orthogonal magnetic orbitals in high spin Cu-VO units: structure, magnetism and EPR study of anisotropic heterometallic complexes.

Molecular-based magnetic materials are expected to serve as building blocks for quantum bits. To realize high-dimensional Hilbert space and addressability, we constructed anisotropic multi-level systems based on CuII and VIV with orthogonal magnetic orbitals. The crystal structures and intramolecular magnetic couplings of four CuIIVOII complexes [{CuVO(appen)2}2], [{CuVO(fhma)2EDA}2], [{CuVO(hfca)2EDA}2] and [CuVO(hfca)2DPEDA]n are characterized. Due to the orthogonal magnetic orbitals of CuII and VIV, the Cu-V pairs in the four complexes have strong ferromagnetic couplings, and the coupling strength is linearly related to the dihedral angle between the two equatorial planes of the two coordination polyhedra. Because of the triplet ground state, the system can be described by an effective Hamiltonian model consisting of two S = 1 spins coupled together. The anisotropy parameters of [{CuVO(hfca)2EDA}2] and [CuVO(hfca)2DPEDA]n were obtained by the simulation of X-band continuous wave electron paramagnetic resonance (cw-EPR) spectra, confirming that both complexes have zero-field splitting addressable on the relative energy scale. The results indicate that constructing multi-centre complexes based on orthogonal magnetic orbitals is a promising strategy for designing multidimensional quantum bits.

Risk prediction and prognostic analysis of post-implantation syndrome after thoracic endovascular aortic repair.

This study aimed to establish a predictive model for the risk of post-thoracic endovascular aortic repair (TEVAR) post-implantation syndrome (PIS) in type B aortic dissection (TBAD) patients, assisting clinical physicians in early risk stratification and decision management for high-risk PIS patients. This study retrospectively analyzed the clinical data of 547 consecutive TBAD patients who underwent TEVAR treatment at our hospital. Feature variables were selected through LASSO regression and logistic regression analysis to construct a nomogram predictive model, and the model's performance was evaluated. The optimal cutoff value for the PIS risk nomogram score was calculated through receiver operating characteristic (ROC) curve analysis, further dividing patients into high-risk group (HRG) and low-risk group (LRG), and comparing the short to midterm postoperative outcomes between the two groups. In the end, a total of 158 cases (28.9%) experienced PIS. Through LASSO regression analysis and multivariable logistic regression analysis, variables including age, emergency surgery, operative time, contrast medium volume, and number of main prosthesis stents were selected to construct the nomogram predictive model. The model achieved an area under the curve (AUC) of 0.86 in the training set and 0.82 in the test set. Results from calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC) demonstrated that the predictive model exhibited good performance and clinical utility. Furthermore, after comparing the postoperative outcomes of HRG and LRG patients, we found that the incidence of postoperative PIS significantly increased in HRG patients. The duration of ICU stay and mechanical assistance time was prolonged, and the incidence of postoperative type II entry flow and acute kidney injury (AKI) was higher. The risk of aortic-related adverse events (ARAEs) and major adverse events (MAEs) at the first and twelfth months of follow-up also significantly increased. However, there was no significant difference in the mortality rate during hospitalization. This study established a nomogram model for predicting the risk of PIS in patients with TBAD undergoing TEVAR. It serves as a practical tool to assist clinicians in early risk stratification and decision-making management for patients.

Double domain fusion improves the reverse transcriptase activity and inhibitor tolerance of Bst DNA polymerase.

To enhance the DNA/RNA amplification efficiency and inhibitor tolerance of Bst DNA polymerase, four chimeric Bst DNA polymerase by fusing with a DNA-binding protein Sto7d and/or a highly hydrophobic protein Hp47 to Bst DNA polymerase large fragment. One of chimeric protein HpStBL exhibited highest inhibitor tolerance, which retained high active under 0.1 U/µL sodium heparin, 0.8 ng/µL humic acid, 2.5× SYBR Green I, 8 % (v/v) whole blood, 20 % (v/v) tissue, and 2.5 % (v/v) stool. Meanwhile, HpStBL showed highest sensitivity (93.75 %) to crude whole blood infected with the African swine fever virus. Moreover, HpStBL showed excellent reverse transcriptase activity in reverse transcription loop-mediated isothermal amplification, which could successfully detect 0.5 pg/µL severe acute respiratory syndrome coronavirus 2 RNA in the presence of 1 % (v/v) stools. The fusion of two domains with different functions to Bst DNA polymerase would be an effective strategy to improve Bst DNA polymerase performance in direct loop-mediated isothermal amplification and reverse transcription loop-mediated isothermal amplification detection, and HpStBL would be a promising DNA polymerase for direct African swine fever virus/severe acute respiratory syndrome coronavirus 2 detection due to simultaneously increased inhibitor tolerance and reverse transcriptase activity.

The nuclear and mitochondrial genome assemblies of Tetragonisca angustula (Apidae: Meliponini), a tiny yet remarkable pollinator in the Neotropics.

BACKGROUND: The field of bee genomics has considerably advanced in recent years, however, the most diverse group of honey producers on the planet, the stingless bees, are still largely neglected. In fact, only eleven of the ~ 600 described stingless bee species have been sequenced, and only three using a long-read (LR) sequencing technology. Here, we sequenced the nuclear and mitochondrial genomes of the most common, widespread and broadly reared stingless bee in Brazil and other neotropical countries-Tetragonisca angustula (popularly known in Brazil as jataí). RESULTS: A total of 48.01 Gb of DNA data were generated, including 2.31 Gb of Pacific Bioscience HiFi reads and 45.70 Gb of Illumina short reads (SRs). Our preferred assembly comprised 683 contigs encompassing 284.49 Mb, 62.84 Mb of which (22.09%) corresponded to 445,793 repetitive elements. N50, L50 and complete BUSCOs reached 1.02 Mb, 91 contigs and 97.1%, respectively. We predicted that the genome of T. angustula comprises 17,459 protein-coding genes and 4,108 non-coding RNAs. The mitogenome consisted of 17,410 bp, and all 37 genes were found to be on the positive strand, an unusual feature among bees. A phylogenomic analysis of 26 hymenopteran species revealed that six odorant receptor orthogroups of T. angustula were found to be experiencing rapid evolution, four of them undergoing significant contractions. CONCLUSIONS: Here, we provided the first nuclear and mitochondrial genome assemblies for the ecologically and economically important T. angustula, the fourth stingless bee species to be sequenced with LR technology thus far. We demonstrated that even relatively small amounts of LR data in combination with sufficient SR data can yield high-quality genome assemblies for bees.

[Research Advances of Groundwater Nitrate Pollution and Source Apportionment in China].

Groundwater nitrate (NO3-) contamination in China has become a serious environmental problem, especially in agricultural production areas, which greatly affects the safety of drinking groundwater and requires urgent attention. In this study, the main sources of groundwater nitrate in China were reviewed, including atmospheric deposition, soil nitrogen, agricultural fertilization, and fecal sewage, among which fecal sewage and agricultural fertilization were the main reasons for the excessive groundwater nitrate. The application of hydrochemical analysis, multivariate statistical analysis, stable isotope tracer method, and microbial source tracking in the source apportionment of groundwater nitrate was summarized. All types of source apportionment methods had certain limitations. It is suggested that a variety of methods should be used to identify the source of groundwater nitrate, and the contribution rate of different pollution sources should be calculated using multivariate statistical analysis and isotope quantitative analysis models. The source apportionment of nitrate pollution has undergone a process from qualitative to quantitative research. At present, the SIAR and MixSIAR models based on δ15N-NO3-and δ18O-NO3- have been used widely to analyze the source of nitrate. However, due to the overlap of isotope characteristic values of different input end-members, the difference in δ15N-NO3-and δ18O-NO3- values under different spatial and temporal changes, and the influence of isotope fractionation in the process of nitrogen migration and transformation, the results calculated by the model remain uncertain. It is necessary to further optimize the analytical method of the model to obtain the source of nitrate pollution and its contribution rate more accurately to further aid in the scientific management of groundwater resources.

[Effect of Integrated Landscape Characteristics Around Chaohu Lake on River Water Quality Based on Watershed Units].

Considering the impact of differences in watershed characteristics on river water quality, with the Chaohu Lake Basin as the research object, based on the data of water quality, meteorology, topography, soil, and remote sensing images of the river monitoring points from October 2019 to September 2020, the watershed unit at each monitoring point was divided through digital terrain analysis, and the comprehensive landscape characteristics based on the watershed unit were explored through the comprehensive use of correlation analysis, redundancy analysis, and multiple regression analysis to investigate the influence of comprehensive landscape characteristics based on watershed units (including land use, climate, topography, soil, etc.) on the water quality of rivers around Chaohu Lake. The results showed that:① the water quality of rivers around Chaohu Lake had large spatial differences, with the main pollutants being total nitrogen and ammonia nitrogen. Most of the rivers had total nitrogen concentrations exceeding the Class V water quality standards, and the areas with serious nitrogen and phosphorus pollution were concentrated in the urban area of Hefei and the surrounding rivers, as well as in the middle and lower reaches of the Fengle and Hangbu Rivers. ② The comprehensive landscape characteristics of the watershed unit had a significant impact on the river water quality. Among them, the proportion of built-up land, the density of patches, the dispersion and juxtaposition index, and the Shannon diversity index were positively correlated with the water quality indicators, whereas the proportion of forest and grassland and the spreading index were negatively correlated with the water quality indicators. ③ In different seasons, the effect of the integrated landscape characteristics of the watershed unit on river water quality was stronger in the wet season than in the dry season, which was mainly caused by the difference in precipitation in the dry and wet seasons.

The complete mitochondrial genome of Zaomma eriococci (hymenoptera: encyrtidae).

The complete mitochondrial genome of the Zaomma eriococci (Ferrière, 1955) (Hymenoptera: Encyrtidae) was obtained through next-generation sequencing, making the first reported complete mitochondrial genome of the genus Zaomma. The mitochondrial genome is 15,648 bp in length and includes 37 classical eukaryotic mitochondrial genes along with an A + T rich region. All 13 protein-coding genes (PCGs) initiate with typical ATN codons. Of these, 10 PCG genes terminate with TAA, while three terminate with TAG. Additionally, there are 22 tRNA genes, ranging in size from 62 to 70 bp. The maximum likelihood phylogenetic tree was constructed based on 13 PCGs, indicates that Z. eriococci is closely related to Tassonia gloriae. This mitochondrial genome will serve as a valuable molecular resource for species identification, genetic analysis, and comparative genomic studies of Z. eriococci, contributing to the growing collection of mitochondrial genomes within the family Encyrtidae.