Enhanced degradation of polyethylene terephthalate (PET) microplastics by an engineered Stenotrophomonas pavanii in the presence of biofilm.

Polyethylene terephthalate (PET) microplastics pose significant environmental and human health risks due to their resistance to degradation and accumulation in ecosystems. In this study, we engineered Stenotrophomonas pavanii JWG-G1, a robust biofilm-forming bacterium, to overexpress the PET hydrolase (DuraPETase) for PET microplastics degradation at ambient temperature. Nine endogenous PET hydrolases were identified through genome sequencing of S. pavanii, and were successfully expressed in Escherichia coli BL21(DE3). Among them, hydrolase Est_B achieved 100 % degradation of bis(2-hydroxyethyl) terephthalate (BHET) at an initial concentration of 0.23 mg/mL at 30 °C within 4 h, identifying it as a novel BHETase. However, the PET degradation performance of all endogenous PET hydrolases was inferior to that of DuraPETase. The engineered strain overexpressing DuraPETase demonstrated a significant enhancement in PET degradation, achieving a 38.04 µM total product release of high-crystallinity PET microplastics after 30 days at 30 °C. The degradation extent was greater than that of low biofilm-forming engineered strains, attributing to the aggregation of DuraPETase on the PET surface in the presence of biofilm. Additionally, this engineered strain also maintained PET degradation activity across various water environments and demonstrated effectiveness in degrading other polyester plastics. This is the first report demonstrating that an engineered strain of Stenotrophomonas species is capable of simultaneously secreting exogenous hydrolase and degrading polyester microplastics, representing a novel approach in the development of engineered bacteria with potential applications in bioreactor systems and environmental remediation.

International Alliance of Urolithiasis (IAU) consensus on miniaturized percutaneous nephrolithotomy.

Over the past three decades, there has been increasing interest in miniaturized percutaneous nephrolithotomy (mPCNL) techniques featuring smaller tracts as they offer potential solutions to mitigate complications associated with standard PCNL (sPCNL). However, despite this growing acceptance and recognition of its benefits, unresolved controversies and acknowledged limitations continue to impede widespread adoption due to a lack of consensus on optimal perioperative management strategies and procedural tips and tricks. In response to these challenges, an international panel comprising experts from the International Alliance of Urolithiasis (IAU) took on the task of compiling an expert consensus document on mPCNL procedures aimed at providing urologists with a comprehensive clinical framework for practice. This endeavor involved conducting a systematic literature review to identify research gaps (RGs), which formed the foundation for developing a structured questionnaire survey. Subsequently, a two-round modified Delphi survey was implemented, culminating in a group meeting to generate final evidence-based comments. All 64 experts completed the second-round survey, resulting in a response rate of 100.0%. Fifty-eight key questions were raised focusing on mPCNLs within 4 main domains, including general information (13 questions), preoperative work-up (13 questions), procedural tips and tricks (19 questions), and postoperative evaluation and follow-up (13 questions). Additionally, 9 questions evaluated the experts' experience with PCNLs. Consensus was reached on 30 questions after the second-round survey, while professional statements for the remaining 28 key questions were provided after discussion in an online panel meeting. mPCNL, characterized by a tract smaller than 18 Fr and an innovative lithotripsy technique, has firmly established itself as a viable and effective approach for managing upper urinary tract stones in both adults and pediatrics. It offers several advantages over sPCNL including reduced bleeding, fewer requirements for nephrostomy tubes, decreased pain, and shorter hospital stays. The series of detailed techniques presented here serve as a comprehensive guide for urologists, aiming to improve their procedural understanding and optimize patient outcomes.

Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed-Cohort Study Based on 16,189 Participants.

BACKGROUND: Early detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels. METHODS: A mixed-cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set. RESULTS: The BCaS3miR model, utilizing only three serum miRNAs (miR-6087, miR-1343-3p, and miR-5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984-0.991), 0.964 (95% CI: 0.936-0.984), and 0.917 (95% CI: 0.836-0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR-1343-3p/miR-6087 and miR-5100/miR-6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages. CONCLUSIONS: Using a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.

Integrative analysis regarding the correlation between collagen-related genes and prostate cancer.

PURPOSE: Prostate cancer (PCa) is a common malignancy in men, with an escalating mortality rate attributed to Recurrence and metastasis. Recent studies have illuminated collagen's critical regulatory role within the tumor microenvironment, significantly influencing tumor progression. Accordingly, this investigation is dedicated to examining the relationship between genes linked to collagen and the prognosis of PCa, with the objective of uncovering any possible associations between them. METHODS: Gene expression data for individuals with prostate cancer were obtained from the TCGA repository. Collagen-related genes were identified, leading to the development of a risk score model associated with biochemical recurrence-free survival (BRFS). A prognostic nomogram integrating the risk score with essential clinical factors was crafted and evaluated for efficacy. The influence of key collagen-related genes on cellular behavior was confirmed through various assays, including CCK8, invasion, migration, cell cloning, and wound healing. Immunohistochemical detection was used to evaluate PLOD3 expression in prostate cancer tissue samples. RESULTS: Our study identified four key collagen-associated genes (PLOD3, COL1A1, MMP11, FMOD) as significant. Survival analysis revealed that low-risk groups, based on the risk scoring model, had significantly improved prognoses. The risk score was strongly associated with prostate cancer prognosis. Researchers then created a nomogram, which demonstrated robust predictive efficacy and substantial clinical applicability.Remarkably, the suppression of PLOD3 expression notably impeded the proliferation, invasion, migration, and colony formation capabilities of PCa cells. CONCLUSION: The risk score, derived from four collagen-associated genes, could potentially act as a precise prognostic indicator for BRFS of patients. Simultaneously, our research has identified potential therapeutic targets related to collagen. Notably, PLOD3 was differentially expressed in cancer and para-cancer tissues in clinical specimens and it also was validated through in vitro studies and shown to suppress PCa tumorigenesis following its silencing.

Utilizing Liquid-liquid phase separation-related lncRNAs to predict the prognosis and treatment response of PCa.

BACKGROUND: Studies have indicated a close association between genes linked to liquid-liquid phase separation (LLPS) and the progression of prostate cancer (PCa). However, the interplay among long non-coding RNAs (lncRNAs) linked to LLPS in PCa remains elusive. Therefore, we constructed a prediction model based on LLPS-related LncRNA in PCa to explore its relationship with the prognosis and drug treatment of PCa. METHODS: We obtained clinical and sequencing data from TCGA and LLPS genes from the Phase Separation Protein Database. By analyzing the differential expression of LLPS-related genes and lncRNAs in prostate cancer, and using Poisson correlation, we identified LLPS-related lncRNAs. Prognostic LLPS-lncRNAs were found through prognostic correlation analysis and included in a Cox model to compute regression coefficients. Patients were scored and divided into high- and low-risk groups. Independent prognostic factors were integrated into a prognostic nomogram with risk and Gleason scores. We also conducted drug sensitivity analyses, GSEA, and validated the impact of key lncRNAs through functional experiments. RESULTS: Our study identified five LLPS-associated lncRNAs that are of prognostic importance. And found notable disparities in biochemical recurrence rates and survival outcomes between these risk groups, with the low-risk cohort exhibiting superior prognostic indicators. Moreover, our prediction nomogram demonstrated robust predictive accuracy and significant clinical utility. Furthermore, our model exhibited promising capabilities in forecasting patient sensitivity to various conventional therapeutic drugs, thereby highlighting its potential in personalized treatment strategies. GSEA showed that these lncRNAs may influence PCa prognosis and sensitivity to therapeutic agents by affecting pathways such as cell cycle. Knockdown of AC009812.4 could inhibit the ability of PCa cells to proliferate, migrate and invade, and compare to paracancerous tissue, AC009812.4 in PCa tissue has significantly higher expression. CONCLUSION: Our research uncovers the prognostic significance of lncRNAs associated with LLPS in PCa and established a model exhibiting excellent predictive accuracy for prognosis. Those lncRNAs may influence progress of PCa as well as sensitivity to therapy drugs through pathways such as cell cycle.

An In Vivo Assessment of a Novel Temperature Control Flexible Ureteroscope System for Monitoring and Controlling Intrarenal Temperature During Flexible Ureteroscopy.

OBJECTIVE: To evaluate the efficacy of a novel temperature control flexible ureteroscope system in the precise monitoring and control of intrarenal temperature (IRT) during ureteroscopy. METHODS: We developed a novel temperature control flexible ureteroscope system (PT-Scope), including a temperature-monitoring ureteroscope and a irrigation-suction platform for temperature regulation. A porcine thermometry model was established to observe temperature changes under varying holmium laser powers (10, 20, 30 W) and irrigation rates (0, 20, 50 mL/min), utilizing percutaneous nephrostomy thermometry and PT-Scope measurements, with subsequent evaluation of temperature variations at different distances from the laser fiber tip. A porcine kidney stone model was established while porcine was randomly assigned to two groups: In the temperature control group, PT-Scope was connected to the irrigation-suction platform with temperature regulation, while in the nontemperature control group without temperature regulation. Comparative analysis was performed to evaluate differences in IRT between the two groups. RESULTS: Across various laser powers and irrigation rates, the temperature measurement capability of the PT-Scope was precise, demonstrating consistency with percutaneous nephrostomy temperature measurements. The temperature obtained from the PT-Scope reflect the temperature approximately 0.05 cm away from the fiber tip, whereas temperatures close to fiber tip were significantly higher. The peak temperature of the temperature control group vs nontemperature control group were 31.70 ± 2.609°C and 44.37 ± 3.318 °C, respectively (P < 0.01). The mean temperature of the temperature control group vs nontemperature control group was 27.40 ± 2.107 °C vs 35.9 ± 1.921 °C (P < 0.01). CONCLUSION: PT-Scope has demonstrated the capability to precisely monitor and control IRT within a safe threshold.

Clinical-Inspired Framework for Automatic Kidney Stone Recognition and Analysis on Transverse CT Images.

The stone recognition and analysis in CT images are significant for automatic kidney stone diagnosis. Although certain contributions have been made, existing methods overlook the promoting effect of clinical knowledge on model performance and clinical interpretation. Thus, it is attractive to establish methods for detecting and evaluating kidney stones originating from the practical diagnostic process. Inspired by this, a novel clinical-inspired framework is proposed to involve the diagnostic process of urologists for better analysis. The diagnostic process contains three main steps, the localization step, the identification step and the evaluation step. Three modules integrating the decision-making mode of urologists are designed to mimic the diagnosis process. The object attention module simulates the localization step to provide the position of kidneys by embedding weight feature factor and angle loss. The feature-driven discriminative module mimics the identification step to detect stones by extracting geometric and positional features. The analysis module based on the principle of clustering and graphic combination is a quantitative analysis strategy for simulating the evaluation step. This work constructed a clinical dataset collecting 27,885 transverse CT images with stones and/or clinical interference. Experiments on the dataset show that the object attention module outperforms the well-performing Yolov7 model by +1% mAP.5:.95, and the analysis module outperforms the well-performing AR-DBSCAN model and the formula method by +21.9% average cluster accuracy and -17.35% average error. Experiments demonstrate that the proposed framework is recently the most effective solution for recognizing and evaluating kidney stones.

Virtually measuring layered material appearance.

This paper describes the design and the implementation of a virtual gonioradiometer dedicated to the analysis of layered materials BSDF. For a given material sample, interfaces between layers are represented by geometric meshes, associated with elementary reflectances. Light scattering is performed using path tracing. Our system is composed of five hemispherical sensors, whose cells have uniform solid angles, and a close-to-uniform geometry. The upper hemisphere captures the reflected radiance distribution, while the other four collect the light energy lost by the sample sides. Sensor resolutions can be set to gather very fine details of the BSDF. With the proposed system, any type of virtual surface reflection and transmission can be simulated, with several controllable surface layers, and with any type of reflection configuration, including direct reflections, two bounces of reflection, or all contributions. A series of results is provided with several types of layered materials, as well as discussion and analysis concerning the assumptions made with analytical layered BSDF models. We also propose an in-depth study of the side effects that inevitably appear when measuring such (real) material configurations. Finally, our system will be freely available to the community (open source dissemination).

Decoding chromosome organization using CheC-PLS: chromosome conformation by proximity labeling and long-read sequencing.

Genomic approaches have provided detailed insight into chromosome architecture. However, commonly deployed techniques do not preserve connectivity-based information, leaving large-scale genome organization poorly characterized. Here, we developed CheC-PLS: a proximity-labeling technique that indelibly marks, and then decodes, protein-associated sites. CheC-PLS tethers dam methyltransferase to a protein of interest, followed by Nanopore sequencing to identify methylated bases - indicative of in vivo proximity - along reads >100kb. As proof-of-concept we analyzed, in budding yeast, a cohesin-based meiotic backbone that organizes chromatin into an array of loops. Our data recapitulates previously obtained association patterns, and, importantly, exposes variability between cells. Single read data reveals cohesin translocation on DNA and, by anchoring reads onto unique regions, we define the internal organization of the ribosomal DNA locus. Our versatile technique, which we also deployed on isolated nuclei with nanobodies, promises to illuminate diverse chromosomal processes by describing the in vivo conformations of single chromosomes.

Pt-S Bond-Enabled Temperature-Dependent Phosphorescence in S-Heteroaryl Tetradentate Pt(S

This study presents the rare examples of S-heteroaryl tetradentate Pt(S^C^N^O) luminescent complexes (PtSZ and PtSZtBu) containing a Pt-S bond. The presence of the Pt-S bond allows the novel Pt(S^C^N^O) complexes to exhibit temperature-dependent phosphorescent emission behavior. The PtSZtBu exhibits dual-emission phenomena and biexponential transient decay spectra above 250 K, indicating the presence of two minimal excited states in the potential energy surface (PES) of the T1 state. Through complementary experimental and computational studies, we have identified changes in orbital composition between Pt(dxy)-S(px) and Pt(dyz)-S(pz) in excited states with increasing temperature. This results in two energy minima, enabling the excited states to decay selectively and radiatively at different temperatures. Consequently, this leads to remarkable steady-state and transient emission spectra changes. Our work not only provides valuable insights for the development of novel Pt-S bond-based tetradentate Pt(II) complexes but also enhances our understanding of the distinctive properties governed by the Pt-S bond.

Uncoupling Protein 2 Alleviates Myocardial Ischemia/Reperfusion Injury by Inhibiting Cardiomyocyte Ferroptosis.

INTRODUCTION: Following our recent finding that Ucp2 knockout promotes ferroptosis, we aimed to examine whether UCP2 alleviates myocardial ischemia/reperfusion injury (MI/RI) by inhibiting ferroptosis. METHODS: The left anterior descending coronary arteries of wild-type and Ucp2-/- C57BL/6 mice were ligated for 30 min and reperfused for 2 h to establish an MI/RI model. The effects of UCP2 on ferroptosis and MI/RI were determined by echocardiography, 2,3,5-triphenylttrazolium chloride staining, hematoxylin-eosin staining, Masson's trichrome staining, Sirius red staining, and analysis of myocardial injury markers and ferroptosis indicators. Ferrostatin-1 (Fer-1) and erastin (Era) were used to investigate whether UCP2 alleviated MI/RI by inhibiting ferroptosis and the molecular mechanism. RESULTS: UCP2 was upregulated in the MI/RI model in WT mice. Deletion of Ucp2 exacerbated ferroptosis, altered the expression levels of multiple ferroptosis-related genes, and significantly exacerbated MI/RI. Knockout of Ucp2 promoted ferroptosis induced by Era and inhibited the antiferroptotic effects of Fer-1. Knockout of Ucp2 activated the p53/TfR1 pathway to exacerbate ferroptosis. CONCLUSION: Our results showed that UCP2 inhibited ferroptosis in MI/RI, which might be related to regulation of the p53/TfR1 pathway.

Developing and validating a nomogram for penile cancer survival: A comprehensive study based on SEER and Chinese data.

OBJECTIVE: The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization. METHODS: Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat-sen Memorial Hospital of Sun Yat-sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c-index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model. RESULTS: A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c-index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system. CONCLUSION: Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision-making processes.

The predictive significance of chromobox family members in prostate cancer in humans.

PURPOSE: The Chromobox (CBX) family proteins are crucial elements of the epigenetic regulatory machinery and play a significant role in the development and advancement of cancer. Nevertheless, there is limited understanding regarding the role of CBXs in development or progression of prostate cancer (PCa). Our objective is to develop a unique prognostic model associated with CBXs to improve the accuracy of predicting outcomes of patients with PCa. METHODS: Data from TCGA and GEO databases were analyzed to assess differential expression, prognostic value, gene pathway enrichment, and immune cell infiltration. COX regression analysis was utilized to identify the independent prognostic factors that impact disease-free survival (DFS). The expression of CBX2 and FOXP3+ cells infiltration was verified by immunohistochemical staining of clinical tissue sections. In vitro proliferation, migration and invasion assay were conducted to examine the function of CBX2. RNA-seq was employed to examine the CBX2 related pathway enrichment. RESULTS: CBX2, CBX3, CBX4, and CBX8 were upregulated, while CBX6 and CBX7 were downregulated in PCa tissues. CBXs expression varied by stage and grade. Elevated expression of CBX1, CBX2, CBX3, CBX4 and CBX8 is correlated with poor outcome. CBX2 expression, T stage, and Gleason score were independent prognostic factors. The expression level of CBX2 in PCa tissues was significantly higher than that in adjacent normal tissues. More Treg infiltration was observed in the group with high CBX2 expression. CBX2 expression affected PCa cell growth, migration, and invasion. CONCLUSIONS: CBX2 is involved in the development and advancement of PCa, suggesting its potential as a reliable prognostic indicator for PCa patients.

A novel bioprospecting strategy via 13C-based high-throughput probing of active methylotrophs inhabiting oil reservoir surface soil.

Methane-oxidizing bacteria (MOB) have long been considered as a microbial indicator for oil and gas prospecting. However, due to the phylogenetically narrow breath of ecophysiologically distinct MOB, classic culture-dependent approaches could not discriminate MOB population at fine resolution, and accurately reflect the abundance of active MOB in the soil above oil and gas reservoirs. Here, we presented a novel microbial anomaly detection (MAD) strategy to quantitatively identify specific indicator methylotrophs in the surface soils for bioprospecting oil and gas reservoirs by using a combination of 13C-DNA stable isotope probing (SIP), high-throughput sequencing (HTS), quantitative PCR (qPCR) and geostatistical analysis. The Chunguang oilfield of the Junggar Basin was selected as a model system in western China, and type I methanotrophic Methylobacter was most active in the topsoil above the productive oil wells, while type II methanotrophic Methylosinus predominated in the dry well soils, exhibiting clear differences between non- and oil reservoir soils. Similar results were observed by quantification of Methylobacter pmoA genes as a specific bioindicator for the prediction of unknown reservoirs by grid sampling. A microbial anomaly distribution map based on geostatistical analysis further showed that the anomalous zones were highly consistent with petroleum, geological and seismic data, and validated by subsequent drilling. Over seven years, a total of 24 wells have been designed and drilled into the targeted anomaly, and the success rate via the MAD prospecting strategy was 83 %. Our results suggested that molecular techniques are powerful tools for oil and gas prospecting. This study indicates that the exploration efficiency could be significantly improved by integrating multi-disciplinary information in geophysics and geomicrobiology while reducing the drilling risk to a greater extent.

Perimidocarbene-Based Tetradentate Platinum(II) Complexes with an Unexpectedly Negligible 3MLCT Character.

Two novel six-membered perimidocarbene (PIC)-based tetradentate Pt(II) complexes were designed and successfully synthesized. Systematical experimental and theoretical studies suggest that the PIC moiety greatly affects the frontier orbitals, as well as the photophysical and excited-state properties of the Pt(II) complexes. PtYK2 has a broad emission spectrum peaking at 576 nm with a shoulder band at 620 nm, along with a full width at half-maximum (FWHM) value of 100.0 nm at 77 K in 2-MeTHF; however, the emission spectrum is slightly red-shifted with a dominant peak at 610 nm and a FWHM value of 125.0 nm at room temperature in a poly(methyl methacrylate) (PMMA) film. Time-dependent-density functional theory and natural transition orbital analyses reveal that PtYK2 has a 3LC (3πPIC* → πPIC)-dominated character with an unexpectedly negligible contribution of 3MLCT transition (0.68%) in the T1 state, which results in a broad emission spectrum and a relatively low quantum efficiency of 7.4% in the PMMA film.

Intricate synergistic effects between air pollution and carbon emission: An emerging evidence from China.

Due to global climate change and intensifying anthropogenic pollution, China confronts the dual challenge of controlling particulate matter 2.5 µm (PM2.5) pollution and reducing carbon emissions. Quantifying the characteristics of PM2.5 concentrations and CO2 emissions, as well as identifying the driving factors and synergistic effects of PM2.5 reduction and CO2 mitigation, are crucial steps in promoting sustainable urban development and achieving the Sustainable Development Goals (SDGs) in China. In this study, we selected 168 cities as our case-study, and quantified spatial characteristics of PM2.5 concentrations and CO2 emissions from 2015 to 2020 in China. Then we analyzed driving factors affecting the spatial heterogeneity of PM2.5 reduction and CO2 mitigation applying Multi-scale Geographically Weighted Regression (MGWR) model. By employing coupling coordination degree (CCD) model, we further detected the spatiotemporal evolution patterns of the synergistic effects between PM2.5 reduction and CO2 mitigation in key Chinese cities. The result showed that: (a) From 2015 to 2020, PM2.5 concentrations experienced a significant reduction from 59.78 µg/m3 to 49.83 µg/m3, while CO2 emissions increased from 44.88 × 106 t in 2015 to 45.77 × 106 t in 2020; (b) Green economy efficiency (gee), government attention (gover), and environmental regulation (envir) demonstrate the most pronounced synergistic effect on pollution reduction and carbon mitigation, with the drivers exhibiting obvious spatial heterogeneity; (c) The overall coupling coordination level of PM2.5 pollution and CO2 emissions in China dropped from 0.49 in 2015 to 0.46 in 2020, and the coupling coordination grade in northern cities was notably higher than that in southern cities. The result enhances our understanding of spatiotemporal patterns of synergistic effects between PM2.5 reduction and CO2 mitigation, and provides the theoretical basis for policy decision-making to realize pollution decrease and carbon neutral and regional environment governance.

Identifying Active Rather than Total Methanotrophs Inhabiting Surface Soil Is Essential for the Microbial Prospection of Gas Reservoirs.

Methane-oxidizing bacteria (MOB) have long been recognized as an important bioindicator for oil and gas exploration. However, due to their physiological and ecological diversity, the distribution of MOB in different habitats varies widely, making it challenging to authentically reflect the abundance of active MOB in the soil above oil and gas reservoirs using conventional methods. Here, we selected the Puguang gas field of the Sichuan Basin in Southwest China as a model system to study the ecological characteristics of methanotrophs using culture-independent molecular techniques. Initially, by comparing the abundance of the pmoA genes determined by quantitative PCR (qPCR), no significant difference was found between gas well and non-gas well soils, indicating that the abundance of total MOB may not necessarily reflect the distribution of the underlying gas reservoirs. 13C-DNA stable isotope probing (DNA-SIP) in combination with high-throughput sequencing (HTS) furthermore revealed that type II methanotrophic Methylocystis was the absolutely predominant active MOB in the non-gas-field soils, whereas the niche vacated by Methylocystis was gradually filled with type I RPC-2 (rice paddy cluster-2) and Methylosarcina in the surface soils of gas reservoirs after geoscale acclimation to trace- and continuous-methane supply. The sum of the relative abundance of RPC-2 and Methylosarcina was then used as specific biotic index (BI) in the Puguang gas field. A microbial anomaly distribution map based on the BI values showed that the anomalous zones were highly consistent with geological and geophysical data, and known drilling results. Therefore, the active but not total methanotrophs successfully reflected the microseepage intensity of the underlying active hydrocarbon system, and can be used as an essential quantitative index to determine the existence and distribution of reservoirs. Our results suggest that molecular microbial techniques are powerful tools for oil and gas prospecting.

The molecular modification, expression, and the antibacterial effects studies of human lysozyme.

Human lysozyme (hLYZ) has attracted considerable research attention due to its natural and efficient antibacterial abilities and widespread uses. In this study, hLYZ was modified to enhance its enzyme activity and expressed in a Pichia pastoris expression system. A combination mutant HZM(2R-K)-N88D/V110S demonstrated the highest enzyme activity (6213 ± 164 U/mL) in shake flasks, which was 4.07-fold higher when compared with the original strain. Moreover, the recombinant P. pastoris was inducted in a 3 L bioreactor plus methanol/sorbitol co-feeding. After 120 h induction, the antibacterial activity of hLYZ reached 2.23 ± 0.12 × 105 U/mL, with the specific activity increasing to 1.89 × 105 U/mg, which is currently the highest specific activity obtained through recombinant expression of hLYZ. Also, hLYZ supernatants showed 2-fold inhibitory effects toward Staphylococcus aureus and Micrococcus lysodeikticus when compared with HZM(2R-K). Our research generated a hLYZ mutant with high antibacterial capabilities and provided a method for screening of high-quality enzymes.

The growth of epitaxial graphene on SiC and its metal intercalation: a review.

High-quality epitaxial graphene (EG) on SiC is crucial to high-performance electronic devices due to the good compatibility with Si-based semiconductor technology. Metal intercalation has been considered as a basic technology to modify EG on SiC. In the past ten years, there have been extensive research activities on the structural evolution during EG fabrication, characterization of the atomic structure and electronic states of EG, optimization of the fabrication process, as well as modification of EG by metal intercalation. In this perspective, the developments and breakthroughs in recent years are summarized and future expectations are discussed. A good understanding of the growth mechanism of EG and subsequent metal intercalation effects is fundamentally important.

High-Performance Ultraviolet Organic Light-Emitting Diodes Enabled by Double Boron-Oxygen-Embedded Benzo[m]tetraphene Emitters.

Ultraviolet organic light-emitting diodes (UV OLEDs) have attracted increasing attention because of their promising applications in healthcare, industry, and agriculture; however, their development has been hindered by the shortage of robust UV emitters. Herein, we embedded double boron-oxygen units into nonlinear polycyclic aromatic hydrocarbons (BO-PAHs) to regulate their molecular configurations and excited-state properties, enabling novel bent BO-biphenyl (BO-bPh) and helical BO-naphthyl (BO-Nap) emitters with hybridized local and charge-transfer (HLCT) characteristics. They could be facilely synthesized in gram-scale amounts via a highly efficient two-step route. BO-bPh and BO-Nap showed strong UV and violet-blue photoluminescence in toluene with full width at half-maximum values of 25 and 37 nm, along with quantum efficiencies of 98 and 99%, respectively. A BO-bPh-based OLED showed high color purity UV electroluminescence peaking at 394 nm with Commission Internationale de l'Eclairage (CIE) coordinates of (0.166, 0.021). Moreover, the device demonstrated a record-high maximum external quantum efficiency (EQE) of 11.3%, achieved by successful hot exciton utilization. This work demonstrates the promising potential of double BO-PAHs as robust emitters for future UV OLEDs.