Clinicopathological characteristics and typing of multilocular cystic renal neoplasm of low malignant potential.

BACKGROUND: Up until now, no research has been reported on the association between the clinical growth rate of multilocular cystic renal neoplasm of low malignant potential (MCRNLMP) and computed tomography (CT) imaging characteristics. Our study sought to examine the correlation between them, with the objective of distinguishing unique features of MCRNLMP from renal cysts and exploring effective management strategies. AIM: To investigate optimal management strategies of MCRNLMP. METHODS: We retrospectively collected and analyzed data from 1520 patients, comprising 1444 with renal cysts and 76 with MCRNLMP, who underwent renal cyst decompression, radical nephrectomy, or nephron-sparing surgery for renal cystic disease between January 2013 and December 2021 at our institution. Detection of MCRNLMP utilized the Bosniak classification for imaging and the 2016 World Health Organization criteria for clinical pathology. RESULTS: Our meticulous exploration has revealed compelling findings on the occurrence of MCRNLMP. Precisely, it comprises 1.48% of all cases involving simple renal cysts, 5.26% of those with complex renal cysts, and a noteworthy 12.11% of renal tumors coexisting with renal cysts, indicating a statistically significant difference (P = 0.001). Moreover, MCRNLMP constituted a significant 22.37% of the patient population whose cysts demonstrated a rapid growth rate of ≥ 2.0 cm/year, whereas it only represented 0.66% among those with a growth rate below 2.0 cm/year. Of the 76 MCRNLMP cases studied, none of the nine patients who underwent subsequent nephron-sparing surgery or radical nephrectomy following renal cyst decompression experienced recurrence or metastasis. In the remaining 67 patients, who were actively monitored over a 3-year postoperative period, only one showed suspicious recurrence on CT scans. CONCLUSION: MCRNLMP can be tentatively identified and categorized into three types based on CT scanning and growth rate indicators. In treating MCRNLMP, partial nephrectomy is preferred, while radical nephrectomy should be minimized. After surgery, active monitoring is advisable to prevent unnecessary nephrectomy.

Tackling Severe Neutrophilic Inflammation in Airway Disorders with Functionalized Nanosheets.

Severe airway inflammatory disorders impose a significant societal burden, and the available treatments are unsatisfactory. High levels of neutrophil extracellular trap (NET) and cell-free DNA (cfDNA) were detected in the inflammatory microenvironment of these diseases, which are closely associated with persistent uncontrolled neutrophilic inflammation. Although DNase has proven to be effective in mitigating neutrophilic airway inflammation in mice by reducing cfDNA and NET levels, its clinical use is hindered by severe side effects. Here, we synthesized polyglycerol-amine (PGA) with a series of hydroxyl/amine ratios and covered them with black phosphorus (BP) nanosheets. The BP nanosheets functionalized with polyglycerol-50% amine (BP-PGA50) efficiently lowered cfDNA levels, suppressed toll-like receptor 9 (TLR9) activation and inhibited NET formation in vitro. Importantly, BP-PGA50 nanosheets demonstrated substantial accumulation in inflamed airway tissues, excellent biocompatibility, and potent inflammation modulation ability in model mice. The 2D sheet-like structure of BP-PGA50 was identified as a crucial factor for the therapeutic efficacy, and the hydroxyl/amine ratio was revealed as a significant parameter to regulate the protein resistance, cfDNA-binding efficacy, and cytotoxicity. This study shows the promise of the BP-PGA50 nanosheet for tackling uncontrolled airway inflammation, which is also significant for the treatment of other neutrophilic inflammatory diseases. In addition, our work also highlights the importance of proper surface functionalization, such as hydroxyl/amine ratio, in therapeutic nanoplatform construction for inflammation modulation.

Time alignment quantum illumination based on single real-time coincidence counting.

We propose and demonstrate an improved quantum illumination protocol based on the time correlation of twin photons, for the high signal-to-noise ratio (SNR) of target detection and signal reconstruction in the strong noise environment. The Hong-Ou-Mandel (HOM) interferometer is applied after the spontaneous parametric down-conversion (SPDC) process to construct a probing twin-beam in which the photon times are precisely aligned between the beams. At the radar receiver, we put forward a single real-time coincidence counting (SRCC) method on a series of time slices to reconstruct the probe signals of pulse radar and calculate the SNR advantages against the conventional pulse radar, as well as the quantum illumination (QI) protocol. Our main achievements in this research are the realization of real-time detection of quantum information while acquiring a higher SNR than QI and classical illumination (CI) protocols, as well as its demonstration of strong robustness to noise and losses, which also proposes what we believe to be a novel way for quantum target detection.

Secular trends in the incidence of major depressive disorder and dysthymia in China from 1990 to 2019.

BACKGROUND: Depression is increasingly recognized as a worldwide serious, public health concern. A better understanding of depression is important for advancing its management and learning the difference between major depressive disorder (MDD) and dysthymia. Our aim is to conduct a concurrent analysis of the trends of both MDD and dysthymia in China. METHODS: The data on depression from 1990 to 2019 were collected from the Global Burden of Disease Study 2019 (GBD 2019). To determine the average annual percent changes (AAPC) and relative risks (RRs), joinpoint regression and the age-period-cohort models were employed, respectively. RESULTS: The incidence number of MDD and dysthymia continuously increased in China from 1990 to 2019, however, the age-standardized rates (ASR) had a decreasing trend in both men and women. The results from joinpoint regression showed that a declining trend was presented in young people (< 50 years) but an increased trend in the elderly (≥ 50 years) both in men and women, during 1990-2019. Age is the most influential factor for MDD and dysthymia. Age RRs for MDD incidence had an overall increasing trend with age. Period RR in MDD presented a U-shaped pattern, while Cohort RRs presented an inverted U-shaped pattern. On the other hand, RRs in dysthymia for period and cohort effects had no statistical significance, only the age effect presented an inverted U-shaped pattern. CONCLUSIONS: The disparities in trends observed between MDD and dysthymia during the period of 1990-2019 indicated the significance of distinguishing between these two disorders. The age, period and cohort effects all had a greater impact on MDD than on dysthymia, and age effects presented different influential patterns in these two. To alleviate the burden of depressive disorders in China, proactive measures need to be implemented, with particular attention to the elderly population.

A two-stage prediction filling method with support vector technologies optimized competitively in stages by grey wolf optimizer and particle swarm optimization for missing fasting blood glucose.

Missing values often affect the data utilization in epidemiological survey. In this study, according to the cut-off point value of the medical diagnostic standard of fasting blood glucose for diabetes, we divide fasting blood glucose test data from the China Health and Nutrition Survey (CHNS) of Shandong province in 2009 into two classes: the normal and the abnormal. Accordingly, for missing fasting blood glucose values, we propose a two-stage prediction filling method with optimized support vector technologies competitively by particle swarm optimization (PSO) or grey wolf optimizer (GWO), which is to first predict the class of the missing data with support vector machine (SVM) in the first stage and then predict the missing value with support vector regression (SVR) within the predicted class in the second stage. In addition, we use the LIBSVM as a gold standard to train both SVM and SVR in different stages. For two kinds of competitive optimizers in stages, in the first stage GWO has the highest classification accuracy (91.1%), and in the second stage PSO has the smallest in-class mean absolute error (0.48). So, GWO-SVM-PSO-SVR is determined as the optimal model and a predicted value with it serves as a fill value. The comparison results of the models in empirical analysis also show that it outdoes any of the other filling models in terms of mean absolute error and mean absolute percentage error. In addition, the sensitivity analysis shows that it presents high tolerance as the sample size changes and has a good stability.

The impact of COVID-19 pandemic on reported tuberculosis incidence and mortality in China: An interrupted time series analysis.

Background: The reported number of cases and deaths from common infectious diseases can change during major public health crises. We explored whether the coronavirus disease 2019 (COVID-19) had an impact on tuberculosis (TB) incidence and mortality in China based on routinely reported TB data. Methods: We used TB data used from the monthly national notifiable infectious disease reports in China from January 2015 to January 2023. Based on an interrupted time series (ITS) design, we applied Poisson and negative binomial regression models to assess the changes of reported TB incidence and mortality before and during the COVID-19 pandemic. Results: We found a significant and immediate decrease in the levels of both reported TB incidence (relative risk (RR) = 0.887; 95% confidence interval (CI) = 0.810-0.973) and mortality (RR = 0.448; 95% CI = 0.351-0.572) at the start of COVID-19 outbreak. During the pandemic, the slope of reported incidence decreased significantly (RR = 0.994; 95% CI = 0.989-0.999), while the slope of reported mortality increased sharply (RR = 1.032; 95% CI = 1.022-1.041) owing to an abrupt rise in reported mortality after January 2022. Conclusions: Both TB incidence and mortality decreased immediately at the start of the COVID-19 pandemic. Over a longer period, the COVID-19 pandemic had contributed to a sustained and more significant decrease in reported incidence, and a delayed but sharp increase in reported mortality.

Uniform zinc-ion deposition regulated by thin sulfonated poly(ether ketone) layer for Stabilizing Zn anodes.

Aqueous zinc-ion batteries (AZIBs) have been getting lots of attention in the field of large scale energy storage owing to their low cost, large capacity and excellent safety. However, Zn anodes have serious dendritic growth and corrosion hydrogen evolution issues, which hinder their further application. Herein, a simple drop-coating technique was used to build a thin sulfate poly(ether ketone) (SPEEK) solid-electrolyte interphase (SEI) on the surface of the Zn anode to address these issues. The sulfonated group (-SO3-） in SPEEK can provide rich coordination sites for Zn2+, controlling the uniform deposition of Zn2+. Therefore, the polymer SEI can block electrolytes and homogenize the Zn2+flux, resulting that the modified Zn (SPEEK@Zn) anode could effectively limit the formation of dendrites and side reactions. At a current density of 0.5 mA cm-2, SPEEK@Zn electrodes can maintain an ultra-long plating/stripping cycle life of 1000 h. Full batteries based on SPEEK@Zn have more superior cycle stability than the bare ones. This approach offers a straightforward and scalable remedy for high-performance Zn anode batteries.

P300/SP1 complex mediating elevated METTL1 regulates CDK14 mRNA stability via internal m7G modification in CRPC.

BACKGROUND: N7-methylguanosine (m7G) modification is, a more common epigenetic modification in addition to m6A modification, mainly found in mRNA capsids, mRNA interiors, transfer RNA (tRNA), pri-miRNA, and ribosomal RNA (rRNA). It has been found that m7G modifications play an important role in mRNA transcription, tRNA stability, rRNA processing maturation, and miRNA biosynthesis. However, the role of m7G modifications within mRNA and its "writer" methyltransferase 1(METTL1) in tumors, particularly prostate cancer (PCa), has not been revealed. METHODS: The differential expression level of METTL1 between hormone-sensitive prostate cancer (HSPC) and castrate-resistant prostate cancer (CRPC) was evaluated via RNA-seq and in vitro experiments. The effects of METTL1 on CRPC progression were investigated through in vitro and in vivo assays. The upstream molecular mechanism of METTL1 expression upregulation and the downstream mechanism of its action were explored via Chromatin Immunoprecipitation quantitative reverse transcription polymerase chain reaction (CHIP-qPCR), Co-immunoprecipitation (Co-IP), luciferase reporter assay, transcriptome-sequencing, m7G AlkAniline-Seq, and mRNA degradation experiments, etc. RESULTS AND CONCLUSION: Here, we found that METTL1 was elevated in CRPC and that patients with METTL1 elevation tended to have a poor prognosis. Functionally, the knockdown of METTL1 in CRPC cells significantly limited cell proliferation and invasive capacity. Mechanistically, we unveiled that P300 can form a complex with SP1 and bind to the promoter region of the METTL1 gene via SP1, thereby mediating METTL1 transcriptional upregulation in CRPC. Subsequently, our findings indicated that METTL1 leads to enhanced mRNA stability of CDK14 by adding m7G modifications inside its mRNA, ultimately promoting CRPC progression.

Joint effects of depressive status and body mass index on the risk of incident hypertension in aging population: evidence from a nationwide population-based cohort study.

BACKGROUND: The impact of depressive status (DS) on hypertension incidence is still controversial and has not been studied in Chinese middle-aged and elderly population. This study aimed to explore the relationship between DS and incident hypertension and analyze the joint effects of DS and body mass index (BMI) on hypertension incidence. METHODS: We conducted a prospective cohort study using data from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide population-based study. In 2013, DS was identified using scores from the 10-item Centre for Epidemiological Studies Depression Scale (CES-D-10) among eligible respondents from CHARLS, and hypertension occurrence was observed until 2018. The multiple Cox models were employed to calculate the associations between DS and hypertension incidence. In addition, we also computed the multiplicative interaction (MI) between DS and BMI of incident hypertension and assessed their additive interaction (AI) through relative excess risk due to interaction (RERI), attributable proportion (AP) or synthetic index (S). Positive AI was indicated by RERI > 0, AP > 0 or S > 1. RESULTS: Over the 5-year follow-up, depressive symptoms increased the risk of hypertension incidence by 19% (hazard ratio (HR) = 1.19, 95% confidence interval (CI): (1.01, 1.41)), while depression was associated with a 24% increased risk (HR = 1.24; 95% CI: (1.03, 1.50)). Significant MIs between DS and overweight or obesity were observed and almost all of AI indexes showed positive joint effects on incident hypertension, of which the depression-obesity combination had the largest joint effect (RERI = 4.47, 95%CI: (0.28, 8.66); AP = 0.67, 95%CI: (0.50, 0.85); S = 4.86,95%CI: (2.66, 8.86)). CONCLUSION: DS could lead to hypertension and this impact was amplified when coexisting with higher BMI. It highlighted a need for precise interventions targeting weight management and depression treatment in the aging population to prevent hypertension.

Evaluating the ecological vulnerability of Chongqing using deep learning.

This study used deep learning to evaluate the ecological vulnerability of Chongqing, China, discuss the deep learning evaluations of ecological vulnerability, and generate vulnerability maps that support local ecological environment protection and governance decisions and provide reference for future studies. The information gain ratio was used to screen the influencing factors, selecting 16 factors that influence ecological vulnerability. Deep neural network (DNN) and convolutional neural network (CNN) methods were used for modeling, and two ecological vulnerability maps of the study area were generated. The results showed that the mean absolute error and root mean square error of the DNN and CNN models were relatively small, and the fitting accuracy was high. The area under the receiver operating characteristic curve of the CNN model was 0.926, which was better than that of the DNN model (0.888). Random forest was applied to calculate the importance of the influencing factors in the two models. Because the main factor was geological features, the relative ecological vulnerability was mainly affected by karst topography. Through the analysis of the ecological vulnerability map, the areas with higher vulnerability are the karst mountains of Dabashan, Wushan, and Qiyaoshan in the northeast and southeast, as well as the valley between mountains and cities in the center and west of the study area. According to the investigation of these areas, the primary ecological problems are low forest quality, structural irregularities caused by self-geological factors, severe desertification, and soil erosion. Human activity is also an important factor that causes ecological vulnerability in the study area. In conclusion, deep learning, particularly CNN models, can be used for ecological vulnerability assessments. The ecological vulnerability maps conformed to the basic cognition of field surveys and can provide references for other deep learning vulnerability studies. While the overall vulnerability of the study area is not high, ecological problems that lead to its vulnerability should be addressed by future ecological protection and management measures.

Surface Modification of Hollow Structure TiO2 Nanospheres for Enhanced Photocatalytic Hydrogen Evolution.

Engineering the surface structure of semiconductor is one of the most promising strategies for improving the separation and transfer efficiency of charge, which is a key issue in photocatalysis. Here, we designed and fabricated the C decorated hollow TiO2 photocatalysts (C-TiO2), in which 3-aminophenol-formaldehyde resin (APF) spheres were used as template and carbon precursor. It was determined that the C content can be easily controlled by calcinating the APF spheres with different time. Moreover, the synergetic effort between the optimal C content and the formed Ti-O-C bonds in C-TiO2 were determined to increase the light absorption and greatly promote the separation and transfer of charge in the photocatalytic reaction, which is verified from UV-vis, PL, photocurrent, and EIS characterizations. Remarkably, the activity of the C-TiO2 is 5.5-fold higher than that of TiO2 in H2 evolution. A feasible strategy for rational design and construction of surface-engineered hollow photocatalysts to improve the photocatalytic performance was provided in this study.

Molecular insights into effects of PBAT microplastics on latosol microbial diversity and DOM chemodiversity.

The impact of biodegradable microplastics on the microbial community and dissolved organic matter (DOM) in latosol has not been well reported. In this study, an incubation experiment at 25 ºC for 120 days using latosol amended with low (5%) and high (10%) concentrations of polybutylene adipate terephthalate (PBAT) microplastics was carried out to explore the impacts of PBAT microplastics on soil microbial communities and DOM chemodiversity, and the intrinsic interactions between their shifts. The main bacterial and fungal phyla in soil, namely Chloroflexi, Actinobacteria, Chytridiomycota, and Rozellomycota showed a nonlinear relationship with PBAT concentration and played a pivotal role in shaping DOM chemodiversity. A higher decreased levels of lignin-like compounds and increased levels of protein-like and condensed aromatic compounds in the 5% treatment were observed than that in the 10% treatment. Furthermore, a higher increase relative abundance of CHO compounds in the 5% treatment than in the 10% treatment was ascribed to its higher oxidation degree. Co-occurrence network analysis suggested that bacteria formed more complex relationships with DOM molecules than fungi did, indicating their critical roles in DOM transformation. Our study has important implications for understanding the potential influence of biodegradable microplastics on carbon biogeochemical roles in soil.

Distinct distribution patterns and functional potentials of rare and abundant microorganisms between plastisphere and soils.

The increasing application of plastic film has caused the "white pollution" of farmlands in greenhouses. To date, most studies on the ecology of the plastisphere have focused on the whole microbial community, with few on the rare and abundant taxa, especially in the terrestrial ecosystems. To understand the plastisphere rare and abundant taxa of bacterial and fungal communities, we collected residues of plastic film from plastic-covered soils in the greenhouse. The plastisphere was significantly different from surrounding soils in terms of alpha- and beta-diversities of abundant and rare taxa. Such discrepancies were greater in rare taxa than in abundant taxa. Besides, the enrichment of soil-borne plant pathogenic fungi in the plastisphere implied that plastic film residues can act as vectors for pathogen transmission. In the plastisphere, the stochastic process governed the assemblies of rare taxa, while deterministic assemblies dominated that of abundant taxa. However, in surrounding soils, the stochastic process played a larger role in abundant taxa as compared to rare taxa. The plastisphere showed a network of less complexity, more competitive connections, and more modules compared to surrounding soils, and rare taxa played greater roles than abundant taxa. There existed obvious discrepancies in the microbial functions between surrounding soils and plastisphere, including carbon, sulfur, nitrogen, and phosphorus cycling, and rare taxa contribute large proportions to the above cycling processes. Altogether, the findings advance our understanding of ecological mechanisms of abundant and rare taxa in the plastisphere in terrestrial ecosystems.

Organic substitution stimulates ammonia oxidation-driven N2O emissions by distinctively enriching keystone species of ammonia-oxidizing archaea and bacteria in tropical arable soils.

Partial organic substitution (POS) is pivotal in enhancing soil productivity and changing nitrous oxide (N2O) emissions by profoundly altering soil nitrogen (N) cycling, where ammonia oxidation is a fundamental core process. However, the regulatory mechanisms of N2O production by ammonia oxidizers at the microbial community level under POS regimes remain unclear. This study explored soil ammonia oxidation and related N2O production, further building an understanding of the correlations between ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) activity and community structure in tropical arable soils under four-year field management regimes (CK, without fertilizer N; N, with only inorganic N; M1N1, with 1/2 organic N + 1/2 inorganic N; M1N2, with 1/3 organic N + 2/3 inorganic N). AOA contributed more to potential ammonia oxidation (PAO) than AOB across all treatments. In comparison with CK, N treatment had no obvious effects on PAO and lowered related N2O emissions by decreasing soil pH and downregulating the abundance of AOA- and AOB-amoA. POS regimes significantly enhanced PAO and N2O emissions relative to N treatment by promoting the abundances and contributions of AOA and AOB. The stimulated AOA-dominated N2O production under M1N1 was correlated with promoted development of Nitrososphaera. By contrast, the increased AOB-dominated N2O production under M1N2 was linked to the enhanced development of Nitrosospira multiformis. Our study suggests organic substitutions with different proportions of inorganic and organic N distinctively regulate the development of specific species of ammonia oxidizers to increase associated N2O emissions. Accordingly, appropriate options should be adopted to reduce environmental risks under POS regimes in tropical croplands.

Isotopic characteristics and sources of suspended particulate organic matter in a reservoir of Chinese desert grassland areas: the influence of dry and wet seasons and the role of atmospheric deposition.

It is essential to study the sources of suspended particulate organic matter (SPOM) for a comprehensive understanding of the carbon and nitrogen cycles in reservoir located in desert grassland areas. Atmospheric deposition is an important pathway for human and natural nutrients to enter water ecosystems. Previous studies have focused on hotspot areas, but neglected the impact of atmospheric deposition on reservoirs in desert grassland regions with little rainfall, long freezing periods, and a dusty climate. In this study, we measured the contents of organic carbon, total nitrogen, the isotopic composition (δ13C and δ15N), and the ratio of total organic carbon to total nitrogen (C/N ratios) for SPOM in the reservoir and its watershed across both dry and wet seasons using carbon and nitrogen isotope techniques. We also analyzed the sources of SPOM in the reservoir using the end-member mixing model. The results showed that the variation range in SPOM for δ13C was - 28.3 to - 21.8‰; for δ15N, it was 2.3 to 8.7‰; and the C/N ratios were 8.12 to 19.12. The variation range of δ13C for atmospheric particulate matter was - 20.0 to - 25.0‰; for δ15N, it was 2.3 to 11.9‰; and the C/N ratios ranged from 7.22 to 17.81. The main sources of carbon in the SPOM were atmospheric deposition and terrestrial C3 plants. The origins were significantly different between the wet and dry periods. Atmospheric nitrogen deposition and soil erosion were the primary sources of particulate nitrogen in the reservoir.

Chemolithotrophic Biological Nitrogen Fixation Fueled by Antimonite Oxidation May Be Widespread in Sb-Contaminated Habitats.

Nitrogen (N) deficiency in mining-contaminated habitats usually hinders plant growth and thus hampers tailing revegetation. Biological N fixation (BNF) is an essential biogeochemical process that contributes to the initial accumulation of N in oligotrophic mining-contaminated regions. Previous studies reported that chemolithotrophic rather than heterotrophic diazotrophs frequently dominated in the mining-contaminated regions. Chemolithotrophic diazotrophs may utilize elements abundant in such habitats (e.g., sulfur (S), arsenic (As), and antimony (Sb)) as electron donors to fix N2. BNF fueled by the oxidation of S and As has been detected in previous studies. However, BNF fueled by Sb(III) oxidation (Sb-dependent BNF) has never been reported. The current study observed the presence of Sb-dependent BNF in slurries inoculated from Sb-contaminated habitats across the South China Sb belt, suggesting that Sb-dependent BNF may be widespread in this region. DNA-stable isotope probing identified bacteria associated with Rhodocyclaceae and Rhizobiaceae as putative microorganisms responsible for Sb-dependent BNF. Furthermore, metagenomic-binning demonstrated that Rhodocyclaceae and Rhizobiaceae contained essential genes involved in Sb(III) oxidation, N2 fixation, and carbon fixation, suggesting their genetic potential for Sb-dependent BNF. In addition, meta-analysis indicated that these bacteria are widespread among Sb-contaminated habitats with different niche preferences: Rhodocyclaceae was enriched in river sediments and tailings, while Rhizobiaceae was enriched only in soils. This study may broaden our fundamental understanding of N fixation in Sb-mining regions.

Thiobacillus spp. and Anaeromyxobacter spp. mediate arsenite oxidation-dependent biological nitrogen fixation in two contrasting types of arsenic-contaminated soils.

As(III) oxidation-dependent biological nitrogen fixing (As-dependent BNF) bacteria use a novel biogeochemical process observed in tailings recently. However, our understanding of microorganisms responsible for As-dependent BNF is limited and whether such a process occurs in As-contaminated soils is still unknown. In this study, two contrasting types of soils (surface soils versus river sediments) heavily contaminated by As were selected to study the occurrence of As-dependent BNF. BNF was observed in sediments and soils amended with As(III), whereas no apparent BNF was found in the cultures without As(III). The increased abundances of the nitrogenase gene (nifH) and As(III) oxidation gene (aioA) suggest that an As-dependent BNF process was catalyzed by microorganisms harboring nifH and aioA. In addition, DNA-SIP demonstrated that Thiobacillus spp. and Anaeromyxobacter spp. were putative As-dependent BNF bacteria in As-contaminated soils and sediments, respectively. Metagenomic analysis further suggested that these taxa contained genes responsible for BNF, As(III) oxidation, and CO2 fixation, demonstrating their capability for serving as As-dependent BNF. These results indicated the occurrence of As-dependent BNF in various As-contaminated habitats. The contrasting geochemical conditions in different types of soil suggested that these conditions may enrich different As-dependent BNF bacteria (Thiobacillus spp. for soils and Anaeromyxobacter spp. for sediments).

Influencing factors of death in patients with MDR-TB based on Bayesian Cox regression model. / 基于贝叶斯Coxå›žå½’æ¨¡åž‹åˆ†æžè€å¤šè¯è‚ºç»“æ ¸æ‚£è€ æ­»äº¡çš„å½±å“å› ç´ .

OBJECTIVES: Multidrug-resistant tuberculosis (MDR-TB) has a high mortality and is always one of the major challenges in global TB prevention and control. Analyzing the factors that may impact the adverse outcomes of MDR-TB patients is helpful for improving the systematic management and optimizing the treatment strategies for MDR-TB patients. For follow-up data, the Cox proportional hazards regression model is an important multifactor analysis method. However, the method has significant limitations in its application, such as the fact that it is difficult to deal with the impacts of small sample sizes and other practical issues on the model. Therefore, Bayesian and conventional Cox regression models were both used in this study to analyze the influencing factors of death in MDR-TB patients during the anti-TB therapy, and compare the differences between these 2 methods in their application. METHODS: Data were obtained from 388 MDR-TB patients treated at Lanzhou Pulmonary Hospital from November 1, 2017 to March 31, 2021. Survival analysis was employed to analyze the death of MDR-TB patients during the therapy and its influencing factors. Conventional and Bayesian Cox regression models were established to estimate the hazard ratios (HR) and their 95% confidence interval (95% CI) for the factors affecting the death of MDR-TB patients. The reliability of parameter estimation in these 2 models was assessed by comparing the parameter standard deviation and 95% CI of each variable. The smaller parameter standard deviation and narrower 95% CI range indicated the more reliable parameter estimation. RESULTS: The median survival time (1st quartile, 3rd quartile) of the 388 MDR-TB patients included in the study was 10.18 (4.26, 18.13) months, with the longest survival time of 31.90 months. Among these patients, a total of 12 individuals died of MDR-TB and the mortality was 3.1%. The median survival time (1st quartile, 3rd quartile) for the deceased patients was 4.78(2.63, 6.93) months. The majority of deceased patients, accounting for 50%, experienced death within the first 5 months of anti-TB therapy, with the last mortality case occurring within the 13th month of therapy. The results of the conventional Cox regression model showed that the risk of death in MDR-TB patients with comorbidities was approximately 6.96 times higher than that of patients without complications (HR=6.96, 95% CI 2.00 to 24.24, P=0.002) and patients who received regular follow-up had a decrease in the risk of death by approximately 81% compared to those who did not receive regular follow-up (HR=0.19, 95% CI 0.05 to 0.77, P=0.020). In the results of Bayesian Cox regression model, the iterative history plot and Blue/Green/Red (BGR) plot for each parameter showed the good model convergence, and parameter estimation indicated that the risk of death in patients with a positive first sputum culture was lower than that of patients with a negative first sputum culture (HR=0.33, 95% CI 0.08 to 0.87). Additionally, compared to patients without complications, those with comorbidities had an approximately 6.80-fold increase in the risk of death (HR=7.80, 95% CI 1.90 to 21.91). Patients who received regular follow-up had a 90% reduction in the risk of death compared to those who did not receive regular follow-up (HR=0.10, 95% CI 0.01 to 0.30). The comparison between these 2 models showed that the parameter standard deviations and corresponding 95% CI ranges of other variables in the Bayesian Cox model were significantly smaller than those in the conventional model, except for parameter standard deviations of receiving regular follow-up (Bayesian model was 0.77; conventional model was 0.72) and pulmonary cavities (Bayesian model was 0.73; conventional model was 0.73). CONCLUSIONS: The first year of anti-TB therapy is a high-risk period for mortality in MDR-TB patients. Complications are the main risk factors of death in MDR-TB patients, while patients who received regular follow-up and had positive first sputum culture presented a lower risk of death. For data with a small sample size and low incidence of outcome, the Bayesian Cox regression model provides more reliable parameter estimation than the conventional Cox model.

Characterization of diazotrophic root endophytes in Chinese silvergrass (Miscanthus sinensis).

BACKGROUND: Phytoremediation is a potentially cost-effective way to remediate highly contaminated mine tailing sites. However, nutrient limitations, especially the deficiency of nitrogen (N), can hinder the growth of plants and impair the phytoremediation of mine tailings. Nevertheless, pioneer plants can successfully colonize mine tailings and exhibit potential for tailing phytoremediation. Diazotrophs, especially diazotrophic endophytes, can promote the growth of their host plants. This was tested in a mine-tailing habitat by a combination of field sampling, DNA-stable isotope probing (SIP) analysis, and pot experiments. RESULTS: Bacteria belonging to the genera Herbaspirillum, Rhizobium, Devosia, Pseudomonas, Microbacterium, and Delftia are crucial endophytes for Chinese silvergrass (Miscanthus sinensis) grown in the tailing, the model pioneer plant selected in this study. Further, DNA-SIP using 15N2 identified Pseudomonas, Rhizobium, and Exiguobacterium as putative diazotrophic endophytes of M. sinensis. Metagenomic-binning suggested that these bacteria contained essential genes for nitrogen fixation and plant growth promotion. Finally, two diazotrophic endophytes Rhizobium sp. G-14 and Pseudomonas sp. Y-5 were isolated from M. sinensis. Inoculation of another pioneer plant in mine tailings, Bidens pilosa, with diazotrophic endophytes resulted in successful plant colonization, significantly increased nitrogen fixation activity, and promotion of plant growth. CONCLUSIONS: This study indicated that diazotrophic endophytes have the potential to promote the growth of pioneer plant B. pilosa in mine tailings. Video Abstract.