ZnIn2S4-based multi-interface coupled photocatalyst for efficient photothermal synergistic catalytic hydrogen evolution.

Photothermal synergistic catalysis is a novel technology that converts energy. In this study, ZnIn2S4 with S-vacancy (ZIS-Vs) is combined with Nickel, Nickle Oxide and Carbon Nanofiber aggregates (Ni-NiO@CNFs) to create a multi-interface coupled photocatalyst with double Schottky barrier, double channel and mixed photothermal conversion effect. Theoretical calculation confirms that the Gibbs free energy (ΔG*H) of the S-scheme heterojunction in the composite material is -0.07 eV, which is close to 0. This promotes the adsorption of H* and accelerates the formation of H2. Internal photothermal catalysis is achieved by visible-near infrared (Vis-NIR, RT) irradiation. The internal photothermal catalytic hydrogen production rate of the best sample (0.9Ni-NiO@CNFs/ZIS-Vs) is as high as 17.24 mmol·g-1·h-1, and its photothermal conversion efficiency (η) is as high as 61.42 %. Its hydrogen production efficiency is 20.52 times that of ZIS-Vs (0.84 mmol·g-1·h-1) under visible light (Vis, RT) conditions. When the Vis-NIR light source is combined with external heating (75 ℃), the hydrogen production efficiency is further improved, and the hydrogen production efficiency (29.16 mmol·g-1·h-1) is 26.75 times that of ZIS-Vs (1.09 mmol·g-1·h-1, Vis-NIR, RT). Further analysis shows that the increase in hydrogen production resulted from the apparent activation energy (Ea) of the catalyst decreasing from 16.7 kJ·mol-1 to 9.28 kJ·mol-1. This study provides a valuable prototype for the design of an efficient photothermal synergistic catalytic system.

A modified drag coefficient model for calculating the terminal settling velocity and horizontal diffusion distance of irregular plume particles in deep-sea mining.

Deep-sea mining inevitably produces plumes, which will pose a serious threat to the marine environment with the continuous movement and diffusion of plumes along with ocean currents. The terminal settling velocity (wt) of irregular particles is one of the crucial factors for determining the plumes' diffusion range. It is generally calculated by drag coefficient (CD), while most existing CD models only consider single shape characteristic parameter or have a smaller range of Reynolds number (Re). In this study, a new shape factor (γ) of irregular particles is proposed by considering the thickness (one-dimension), the projected area (two-dimension), and the surface area (three-dimension) of irregular particles as well as their coupling effect to establish a modified CD model for calculating the wt. A modified Gaussian plume model is proposed to predict the horizontal diffusion distance of the plume particles by considering the settling velocity and diffusion effect of irregular particles. Research results show that the wt increases nearly linearly, with a gradually decreased slope and slightly then greatly with the increasing of γ, dp (diameter) and ρp (density), respectively. The modified CD model is verified to be more valid with a wider application range (Re < 3×105) than five existing CD models by the test results. The larger the ρp or dp, the larger the wt and thus the smaller the Sh. This study could provide a theoretical basis for calculating the plume diffusion range to further study the impact of deep-sea mining on the ocean environment.

Simultaneous sequencing of 102 Y-STRs on Ion Torrent ™ GeneStudio ™ S5 System.

The Precision ID NGS System from Thermo Fisher Scientific is a mainstream next-generation sequencing (NGS) platform used in forensic laboratories to detect almost all commonly used forensic markers, except for Y-chromosomal short tandem repeats (Y-STRs). This study aimed to: 1) develop a Y-STR panel compatible with the automatic workflow of the NGS system using Ion AmpliSeq Technology, 2) evaluate the panel performance following the SWGDAM guidelines, and 3) explore the possibility of using a combination workflow to detect autosomal STRs and Y-STRs (AY-STR NGS workflow). The GrandFiler Y-STR Panel was successfully designed using the 'separating' and 'merging' strategies, including 102 Y-STRs and Amelogenin with an average amplicon length of 133 bp. It is a mega Y-STR multiplex system in which up to 16 samples can be sequenced simultaneously on an Ion 530 ™ Chip. Developmental validation studies of the performance of the NGS platform, species specificity, reproducibility, concordance, sensitivity, degraded samples, case-type samples, and mixtures were conducted to unequivocally determine whether the GrandFiler Y-STR Panel is suitable for real scenarios. The newly developed Y-STR panel showed compelling run metrics and NGS performance, including 92.47% bases with ≥ Q20, 91.80% effective reads, 2106 × depth of coverage (DoC), and 97.09% inter-locus balance. Additionally, it showed high specificity for human males and 99.40% methodological and bioinformatical concordance, generated complete profiles at ≥ 0.1 ng input DNA, and recovered more genetic information from severely degraded and diverse case samples. Although the outcome when used on mixtures was not as expected, more genetic information was obtained compared to that from capillary electrophoresis (CE) methods. The AY-STR NGS workflow was established by combining the GrandFiler Y-STR Panel with the Precision ID GlobalFiler ™ NGS STR Panel v2 at a 2:1 concentration ratio. The combination workflow on NGS performance, reproducibility, concordance, and sensitivity was as stable as the single Y-STR NGS workflow, providing more options for forensic scientists when dealing with different case scenarios. Overall, the GrandFiler Y-STR Panel was confirmed as the first to effectively detect a large number of Y-STR markers on the Precision ID NGS System, which is compatible with 51 Y-STRs in commercial CE kits and 51 Y-STRs in commercial NGS kits and the STRBase. The panel is as robust, reliable, and sensitive as current CE/NGS kits, and is suitable for solving real cases, especially for severely degraded samples (degradation index > 10).

Development and clinical validation of a dual ddPCR assay for detecting carbapenem-resistant Acinetobacter baumannii in bloodstream infections.

Objective: Acinetobacter baumannii (A. baumannii, AB) represents a major species of Gram-negative bacteria involved in bloodstream infections (BSIs) and shows a high capability of developing antibiotic resistance. Especially, carbapenem-resistant Acinetobacter baumannii (CRAB) becomes more and more prevalent in BSIs. Hence, a rapid and sensitive CRAB detection method is of urgent need to reduce the morbidity and mortality due to CRAB-associated BSIs. Methods: A dual droplet digital PCR (ddPCR) reaction system was designed for detecting the antibiotic resistance gene OXA-23 and AB-specific gene gltA. Then, the specificity of the primers and probes, limit of detection (LOD), linear range, and accuracy of the assay were evaluated. Furthermore, the established assay approach was validated on 37 clinical isolates and compared with blood culture and drug sensitivity tests. Results: The dual ddPCR method established in this study demonstrated strong primer and probe specificity, distinguishing CRAB among 21 common clinical pathogens. The method showed excellent precision (3 × 10-4 ng/µL, CV < 25%) and linearity (OXA-23: y = 1.4558x + 4.0981, R2 = 0.9976; gltA: y = 1.2716x + 3.6092, R2 = 0.9949). While the dual qPCR LOD is 3 × 10-3 ng/µL, the dual ddPCR's LOD stands at 3 × 10-4 ng/µL, indicating a higher sensitivity in the latter. When applied to detect 35 patients with BSIs of AB, the results were consistent with clinical blood culture identification and drug sensitivity tests. Conclusion: The dual ddPCR detection method for OXA-23 and gltA developed in this study exhibits good specificity, excellent linearity, and a higher LOD than qPCR. It demonstrates reproducibility even for minute samples, making it suitable for rapid diagnosis and precision treatment of CRAB in BSIs.

Treating reverse osmosis brine of petrochemical wastewater using preparative vertical-flow electrophoresis (PVFE) with multi-objective optimization by response surface method.

Electrochemical desalination is an effective method for recovering salts from reverse osmosis (RO) brine. However, traditional technologies like bipolar membrane technology often face challenges related to membrane blockage. To overcome this issue, a preparative vertical-flow electrophoresis (PVFE) system was used for the first time to treat RO brine of petrochemical wastewater. In order to optimize the PVFE operation and maximize acids and bases production while minimizing energy consumption, the response surface method was employed. The independent variables selected were the electric field intensity (E) and flow rate (v), while the dependent variables were the acid-base concentration and energy consumption (EC) for acid-base production. Using the central composite design methodology, the operation parameters were optimized to be E = 154.311 V/m and v = 0.83 mL/min. Under these conditions, the base concentrations of the produced bases and acids reached 3183.06 and 2231.63 mg/L, respectively. The corresponding base EC and acid EC were calculated to be 12.57 and 11.62 kW·h/kg. In terms of the acid-base concentration and energy consumption during the PVFE process, the electric field intensity was found to have a greater influence than the flow rate. These findings provide a practical and targeted solution for recycling waste salt resources from RO brine.

Combined collection systems of sewage and rainfall runoff seriously affect the spatial distributions of natural estrogens and their conjugates in river water: Insights from the Pearl River of China.

So far, little has been known about how the combined collection systems of sewage and rainfall runoff (CCSs) affect emerging contaminants in river water. To fill up the knowledge gap, this study was conducted to investigate the spatial distributions of three natural estrogens (NEs, i.e., estrone (E1), 17ß-estradiol (E2) and estriol (E3)) and their conjugates (C-NEs) in the Pearl River in the wet and dry seasons. Results showed that the respective average concentrations of NEs and C-NEs at different locations alongside the Pearl River in the wet season were 7.3 and 1.8 times those in the dry season. Based on estrogen equivalence (EEQ), the average estimated EEQ level in the Pearl River waters in the wet season was nearly 10 times that in the dry season. These seemed to imply that the CCSs in the wet season not only cause untreated sewage into the receiving water body, but greatly decrease the removal efficiency of NEs and C-NEs in wastewater treatment plant. Furthermore, the estimated annual loads of E1, E2, and E3 to the Pearl River in the wet season accounted for about 88.6 %, 100 %, and 99.3 % of the total annual loads. Consequently, this work for the first time demonstrated that the CCSs in cities with high precipitation are unfavorable for controlling of emerging contaminants.

A new model for dynamic mapping of effective connectivity in task fMRI.

Whole-brain dynamic functional connectivity is a growing area in neuroimaging research, encompassing data-driven methods for investigating how large-scale brain networks dynamically reorganize during resting states. However, this approach has been rarely applied to functional magnetic resonance imaging (fMRI) data acquired during task performance. In this study, we first combined the psychophysiological interactions (PPI) and sliding-window methods to analyze dynamic effective connectivity of fMRI data obtained from subjects performing the N-back task within the Human Connectome Project dataset. We then proposed a hypothetical model called Condition Activated Specific Trajectory (CAST) to represent a series of spatiotemporal synchronous changes in significantly activated connections across time windows, which we refer to as a trajectory. Our finding demonstrate that the CAST model outperforms other models in terms of intra-group consistency of individual spatial pattern of PPI connectivity, overall representational ability of temporal variability and hierarchy for individual task performance and cognitive traits. This dynamic view afforded by the CAST model reflects the intrinsic nature of coherent brain activities.

Insight into the Growth Mechanism of Low-Temperature Synthesis of High-Purity Lithium Slag-Based Zeolite A.

The utilization of lithium slag (LS), a solid waste generated during the production of lithium carbonate, poses challenges due to its high sulfur content. This study presents a novel approach to enhancing the value of LS by employing alkali fusion and hydrothermal synthesis techniques to produce zeolite A at low temperatures. The synthesis of high-purity and crystalline lithium-slag-based zeolite A (LSZ) at 60 °C is reported for the first time in this research. The phase, morphology, particle size, and structure of LSZ were characterized by XRD, SEM, TEM, N2 adsorption, and UV Raman spectroscopy, respectively. High-purity and crystalline zeolite A was successfully obtained under hydrothermal conditions of 60 °C, an NaOH concentration of 2.0 mol/L, and a hydrothermal time of 8 h. The samples synthesized at 60 °C exhibited better controllability and almost no byproduct of sodalite occurred compared to zeolite A synthesized at room temperature or conventional temperature (approximately 90 °C). Additionally, the growth mechanism of LSZ was elucidated, challenging the traditional understanding of utilization of lithium and enabling the synthesis of various zeolites at lower temperatures.

Widely Targeted Metabolomics Analysis Reveals Metabolites Important for Antioxidant Properties and Quality Traits in Different Fruit Parts of Aurantii Fructus Immatures.

In traditional Chinese medicine, Aurantii Fructus Immatures (AFIs) have been utilized for more than 2000 years. The proportions of different fruit parts are crucial for evaluating AFI quality in China. However, the basis for this statement's substance is unclear. Differences in quality are intimately correlated with a plant's metabolite composition. On the basis of a widely targeted metabolome, this study intended to investigate the metabolite composition and evaluate the antioxidant capacity of the peel and pulp of an AFI. Metabolites were identified and quantified by UHPLC-QqQ-MS. To assess their antioxidant ability, DPPH and ABTS assays were carried out. There were 1327 chemical compounds identified by UHPLC-QqQ-MS. After screening the differential metabolites using a multivariate statistical analysis, it was found that there were 695 significant differences in the metabolites between the peel and the pulp. Among them, it was discovered that the content of active ingredients in the peel group was higher than that in the pulp group. Furthermore, the aqueous extracts from the peel showed stronger antioxidant capacities than those from the pulp. The metabolites and antioxidant capacities were significantly different between the peel and the pulp. This study of different fruit parts might provide a guide for AFI quality assessments.

Influence on Sample Determination for Deep Learning Electromagnetic Tomography.

Deep learning (DL) has been frequently applied in the image reconstruction of electromagnetic tomography (EMT) in recent years. It offers the potential to achieve higher-quality image reconstruction. Among these, research on samples is relatively scarce. Samples are the cornerstone for both large and small models, which is easy to ignore. In this paper, a deep learning electromagnetic tomography (DL-EMT) model with nine elements is established. Complete simulation and experimental samples are obtained based on this model. On the sample sets, the reconstruction quality is observed by adjusting the size and configuration of the training set. The Mann-Whitney U test shows that beyond a certain point, the addition of more samples to the training data fed into the deep learning network does not result in an obvious improvement statistically in the quality of the reconstructed images. This paper proposes a CC-building method for optimizing a sample set. This method is based on the Pearson correlation coefficient calculation, aiming to establish a more effective sample base for DL-EMT image reconstruction. The statistical analysis shows that the CC-building method can significantly improve the image reconstruction effect in a small and moderate sample size. This method is also validated by experiments.

Suppressing Structure Delamination for Enhanced Electrochemical Performance of Solid Oxide Cells.

Reversible solid oxide cells (rSOCs) have significant potential as efficient energy conversion and storage systems. Nevertheless, the practical application of their conventional air electrodes, such as La0.8Sr0.2MnO3-δ (LSM), Ba0.5Sr0.5Co0.8Fe0.2O3-δ (BSCF), and PrBa0.8Ca0.2Co2O5+δ (PBCC), remains unsatisfactory due to interface delamination during prolonged electrochemical operation. Using micro-focusing X-ray absorption spectroscopy (µ-XAS), a decrease (increase) in the co-valence state from the electrode surface to the electrode/electrolyte interface is observed, leading to the above delamination. Utilizing the one-pot method to incorporate an oxygen-vacancy-enriched CeO2 electrode into these air electrodes, the uniform distribution of the Co valence state is observed, alleviating the structural delamination. PBCC-CeO2 electrodes exhibited a degradation rate of 0.095 mV h-1 at 650 °C during a nearly 500-h test as compared with 0.907 mV h-1 observed during the 135-h test for PBCC. Additionally, a remarkable increase in electrolysis current density from 636 to 934 mA cm-2 under 1.3 V and a maximum power density from 912 to 989 mW cm-2 upon incorporating CeO2 into PBCC is also observed. BSCF-CeO2 and LSM-CeO2 also show enhanced electrochemical performance and prolonged stability as compared to BSCF and LSM. This work offers a strategy to mitigate the structural delamination of conventional electrodes to boost the performance of rSOCs.

Performance and characterization of 94 identity-informative SNPs in Northern Han Chinese using ForenSeq ™ DNA signature prep kit.

Target and flanking region (FR) variation at 94 identity-informative SNPs (iSNPs) are investigated in 635 Northern Han Chinese using the ForenSeq DNA Signature Prep Kit on the MiSeq FGx Forensic Genomics System. The dataset presents the following performance characteristics (average values): ≥60% bases with a quality score of 20 or higher (%≥ Q20); >700 × of depth of coverage (DoC) from both Sample Details Reports and Flanking Region Reports; >80% of effective reads; ≥60% of allele coverage ratio (ACR); and ≥70% of inter-locus balance, while some stable low-performance characteristics are also observed: low DoC at rs1736442, rs1031825, rs7041158, rs338882, rs2920816, rs1493232, rs719366, and rs2342747; high noise at rs891700; and imbalanced ACR at rs6955448 and rs338882. The average amplicon length is 69 bp, suitable for detecting degraded samples. Bioinformatic concordance achieves 99.99% between the ForenSeq Universal Analysis Software (UAS) and the Integrative Genomic Viewer (IGV) inspection. Discordance results from flanking region deletions of rs10776839, rs8078417, rs2831700, and rs1454361. Due to FR variants within amplicons detected by massively parallel sequencing (MPS), the increases in the number of unique alleles, effective alleles (Ae), and observed heterozygosity (Hobs) are 46.81%, 4.51%, and 3.29%, respectively. Twelve FR variants are first reported to dbSNP, such as rs1252699848, rs1665500714, rs1771121532, rs2097285015, rs1851671415, rs2045669877, rs2046758811, rs2044248635, rs1251308240, rs1968822112, rs1981638299, and rs1341756746. All 94 iSNPs from target and amplicon data are in Hardy-Weinberg equilibrium (HWE) and independent within autosomes. As expected, forensic parameters from the amplicon data increase significantly on the combined power of discrimination (CPD = 1 - 3.9876 × 10-38) and the combined power of exclusion (CPE = 1 - 6.6690 × 10-8). Additionally, the power of the system effectiveness (CPD = 1 - 6.7054 × 10-72 and CPE = 1 - 4.4719 × 10-20) with sequence-based 27 autosomal STRs and 94 iSNP amplicons in combination is substantially improved compared to one type of marker alone. In conclusion, we have established a traditional length-based and current sequence-based reference database with 58 STRs and 94 iSNPs in the Northern Han Chinese population. We hope these data can serve as a solid reference and foundation for forensic practice.

Deconjugation potentials of natural estrogen conjugates in sewage and wastewater treatment plant: New insights from model prediction and on-site investigations.

Natural estrogen conjugates play important roles in municipal wastewater treatment plant (WWTP), but their deconjugation potentials are poorly understood. This work is the first to investigate the relationships between the enzyme activities of arylsulfatase/ß-glucuronidase and deconjugation potentials of natural estrogen conjugates. This work led to three important findings. First, the enzyme activity of ß-glucuronidase in sewage is far higher than that of arylsulfatase, while their corresponding activities in activated sludge were similar. Second, a model based on ß-glucuronidase could successfully predict the deconjugation potentials of natural estrogen glucuronide conjugates in sewage. Third, the enzyme activity of arylsulfatase in sewage was too low to lead to evident deconjugation of sulfate conjugates, which means that the deconjugation rate of estrogen sulfates can be regarded as zero. By comparing their theoretical removal based on enzyme activity and on-site investigation, it is reasonable to conclude that reverse deconjugation of estrogen conjugates (i.e., conjugation of natural estrogens to form conjugated estrogens) likely exist in WWTP, which explains well why natural estrogen conjugates cannot be effectively removed in WWTP. Meanwhile, this work provides new insights how to improve the removal performance of WWTP on natural estrogen conjugates. SYNOPSIS: This work is the first to show how arylsulfatase/ß-glucuronidase could affect deconjugation of natural estrogen conjugates and possible way to enhance their removal in wastewater treatment plant.

Meta-structure enhanced second harmonic S0 waves for material microstructural changes monitoring.

Cumulative second harmonic Lamb waves in nonlinear media feature increasing amplitudes with propagation distance, conducive to the monitoring of material microstructural changes in structures. The phenomenon can be readily generated by zero-order symmetric (S0) mode waves in the low-frequency range. However, in a practical piezoelectric-transducer-activated system, both S0 and A0 (zero-order antisymmetric) mode Lamb waves are inevitably excited, while only the former is responsible for cumulative effects. The generation efficiency of the cumulative second harmonics is then affected by the presence of the A0 waves. To tackle the problem, this study develops a metamaterial structure, referred to as a meta-structure, to tactically enhance the cumulative second harmonic S0 Lamb waves by converting the A0 mode components into S0 mode waves. Topology optimization is conducted to design the meta-structure, which is surface-mounted onto the structure under inspection, to achieve high-efficiency A0-to-S0 wave mode conversion. Through tuning the parameters and constraints of the optimization, the designed single-sided meta-structure breaks the structural symmetry in the thickness direction, while facilitating its practical implementation. Typical scenarios with different meta-structure materials are discussed. Numerical simulations demonstrate that the strain amplitudes of the fundamental S0 mode waves can be increased by 60% with the deployment of the meta-structure, alongside an enhancement of the second harmonic S0 mode waves at different sensing distances. Finally, the designed meta-structure is fabricated via 3D printing technique and tested experimentally on an aluminum plate subjected to thermal aging treatment for monitoring the heating-induced microstructural changes inside the structure. Experimental results confirm an increase in the wave amplitudes of the linear S0 mode waves with the assistance of the meta-structure. The developed system improves the sensitivity of nonlinear Lamb wave-based monitoring methods in characterizing material microstructural changes, which shows great promise for detecting incipient damage in practical structural health monitoring applications.

Paraflavitalea pollutisoli sp. nov., Pollutibacter soli gen. nov. sp. nov., Polluticoccus soli gen. nov. sp. nov., and Terrimonas pollutisoli sp. nov., four new members of the family Chitinophagaceae from polluted soil.

A taxonomic investigation was conducted on four bacterial strains isolated from soil contaminated with polycyclic aromatic hydrocarbons and heavy metals. Phylogenetic analysis revealed that these strains belonged to the family Chitinophagaceae. Examination of the 16S rRNA genes indicated that their sequence identities were below 97.6 % compared to any known and validly nominated bacterial species. The genomes of the four strains ranged from 4.12 to 8.76 Mb, with overall G + C molar contents varying from 41.28 % to 50.39 %. Predominant cellular fatty acids included iso-C15:0, iso-C15:1 G, and iso-C17:0 3-OH. The average nucleotide identity ranged from 66.90 % to 74.63 %, and digital DNA-DNA hybridization was 12.5-12.8 %. Based on the genomic and phenotypic features of the new strains, four novel species and two new genera were proposed within the family Chitinophagaceae. The ecological distributions were investigated by data-mining of NCBI databases, and results showed that additional strains or species of the newly proposed taxa were widely distributed in various environments, including polluted soil and waters. Functional analysis demonstrated that strains H1-2-19XT, JS81T, and JY13-12T exhibited resistance to arsenite (III) and chromate (VI). The proposed names for the four novel species are Paraflavitalea pollutisoli (type strain H1-2-19XT = JCM 36460T = CGMCC 1.61321T), Terrimonas pollutisoli (type strain H1YJ31T = JCM 36215T = CGMCC 1.61343T), Pollutibacter soli (type strain JS81T = JCM 36462T = CGMCC 1.61338T), and Polluticoccus soli (type strain JY13-12T = JCM 36463T = CGMCC 1.61341T).

Experimental and numerical study of the mixed lubrication under the action of magnetic ionic liquid additives.

In this paper, the tribological characteristics of an oil-soluble magnetic fluid additive under mixed lubrication are studied by experiments and numerical simulation. [bmim][FeCl4] is dissolved in CF10W-40 lubricating oil as a magnetic liquid additive, and its friction coefficient is tested by a point contact friction tester at different temperatures, rotational speeds and magnetic field intensities. The transition condition of lubrication state is obtained through analyzing the Stribeck curves based on the experiments, and the strength model of boundary film is established accordingly. A mixed lubrication model is established by substituting the boundary film strength model and the surface roughness model into the hydrodynamic lubrication model based on Reynolds equation. The results show that the magnetic solution as an additive can obviously reduce friction and wear, and the effect is more obvious under the condition of magnetic field. The boundary film strength model can accurately reflect the transition characteristics of lubrication state in the presence of boundary film, and the mixed lubrication model based on boundary film strength model can more precisely reflect the tribological characteristics of friction pairs, so this study provides a new theoretical method for the related research on the influence of boundary film on lubrication characteristics.

Chelatococcus albus sp. nov., a bacterium isolated from hot spring microbial mat.

A Gram-stain-negative, non-endospore-forming, motile, short rod-shaped strain, designated SYSU G07232T, was isolated from a hot spring microbial mat, sampled from Rehai National Park, Tengchong, Yunnan Province, south-western China. Strain SYSU G07232T grew at 25-50 °C (optimum, 37 °C), at pH 5.5-9.0 (optimum, pH 6.0) and tolerated NaCl concentrations up to 1.0 % (w/v). Phylogenetic analysis based on the 16S rRNA gene sequences revealed that strain SYSU G07232T showed closest genetic affinity with Chelatococcus daeguensis K106T. The genomic features and taxonomic status of this strain were determined through whole-genome sequencing and a polyphasic approach. The predominant quinone of this strain was Q-10. Major cellular fatty acids comprised C19 : 0 cyclo ω8c and summed feature 8. The whole-genome length of strain SYSU G07232T was 4.02 Mbp, and the DNA G+C content was 69.26 mol%. The average nucleotide identity (ANIm ≤84.85 % and ANIb ≤76.08  %) and digital DNA-DNA hybridization (≤ 21.9 %) values between strain SYSU G07232T and the reference species were lower than the threshold values recommended for distinguishing novel prokaryotic species. Thus, based on the provided phenotypic, phylogenetic, and genetic data, it is proposed that strain SYSU G07232T (=KCTC 8141T=GDMCC 1.4178T) be designated as representing a novel species within the genus Chelatococcus, named Chelatococcus albus sp. nov.

Prevalence of depressive symptoms in patients with advanced schistosomiasis in China: A systematic review and meta-analysis.

BACKGROUND: Advanced schistosomiasis is the most serious outcome of infection and has a negative impact on both physical fitness and mental health of patients, the latter of which has long been overlooked. Therefore, we performed this systematic review and meta-analysis to estimate the overall prevalence of depressive symptoms, one of the most common mental problems, in patients with advanced schistosomiasis in China. METHODS: Six electronic databases were searched for studies reporting the prevalence of depressive symptoms in the targeted patients. Assessments were pooled using a fixed- or random-effects model based on heterogeneity test. Subgroup analyses were further performed and differences between/among groups were examined using the chi-squared test. The protocol had previously been registered in PROSPERO (CRD42023406708). RESULTS: A total of 11 studies with 1,673 participants were included. The pooled prevalence of depressive symptoms in advanced schistosomiasis in China was 62.01% (95% CI: 51.30% - 72.72%), with a significant heterogeneity among studies. Depressive symptoms were more prevalent in patients with complications and more than half of the patients suffered a mild- or moderate-level of depression. No publication bias was found, and sensitivity analysis showed a stable result. CONCLUSIONS: The overall prevalence of depressive symptoms in advanced schistosomiasis in China was high enough to warrant psychotherapeutic interventions, especially for patients with complications. This would greatly prevent or/and reduce depression and improve their quality of life.