Search

The machining mechanics of the rotary ultrasonic drilling (RUD) is investigated based on the separation effect of ultrasonic vibration (SEUV), by quantifying the critical force at a certain ultrasonic vibration amplitude. Firstly, the SEUV principle is explored by establishing the kinematic trajectory of the tool. Then, the critical force of SEUV at certain ultrasonic vibration amplitude is modeled. The simulation shows that as the tool interference displacement caused by the axial force is larger than the ultrasonic vibration amplitude, the tool vibration is in a suppressed state and the SEUV effect cannot be achieved. Third, the principles of standard drilling and peck drilling are proposed. The essence of peck drilling in step motion shows advantage to assure SEUV of RUD. Last, the critical force of SEUV is measured in experiments and proves that the SEUV is suppressed as the force exceeds a certain value. The RUD verification experiment on SiC of standard drilling and peck drilling is conducted. It is found that when the cutting force exceeds the critical force in standard drilling, the SEUV is suppressed and there has no significant improvement on the drilling performance. In peck drilling, the cutting force is lower than the critical force periodically, where the SEUV is achieved and the ultrasonic vibration can make effective impacts on the material and improve drilling performance. [ABSTRACT FROM AUTHOR]

Rhizopus arrhizus is a saprotrophic, sometimes clinically- and industrially-relevant mold (Mucorales) and distributed worldwide, suggesting it can assimilate a broad spectrum of substrates. Here, 69 strains of R. arrhizus were investigated by using the Biolog FF MicroPlate for the profiles of utilizing 95 carbon and nitrogen substrates. The study showed that most R. arrhizus strains were similar in average well color development (AWCD) and substrate richness (SR). Nevertheless, 13 strains were unique in principal component analyses, heatmap, AWCD, and SR analyses, which may imply a niche differentiation within R. arrhizus. The species R. arrhizus was able to utilize all the 95 carbon and nitrogen substrates, consistent with the hypothesis of a great metabolic diversity. It possessed a substrate preference of alcohols, and seven substrates were most frequently utilized, with N-acetyl-d-galactosamine and l-phenylalanine ranking at the top of the list. Eight substrates, especially l-arabinose and xylitol, were capable of promoting sporulation and being applied for rejuvenating degenerated strains. By phenotyping R. arrhizus strains in carbon and nitrogen assimilation capacity, this study revealed the extent of intra-specific variability and laid a foundation for estimating optimum substrates that may be useful for industrial applications. [ABSTRACT FROM AUTHOR]

DNA methylation is an important epigenetic mechanism involved in the anti-tumor immune response, and DNA methyltransferase inhibitors (DNMTi) have achieved impressive therapeutic outcomes in patients with certain cancer types. However, it is unclear how inhibition of DNA methylation bridges the innate and adaptive immune responses to inhibit tumor growth. Here, we report that DNMTi zebularine reconstructs tumor immunogenicity, in turn promote dendritic cell maturation, antigen-presenting cell activity, tumor cell phagocytosis by APCs, and efficient T cell priming. Further in vivo and in vitro analyses reveal that zebularine stimulates cGAS-STING-NF-κB/IFNβ signaling to enhance tumor cell immunogenicity and upregulate antigen processing and presentation machinery (AgPPM), which promotes effective CD4+ and CD8+ T cell-mediated killing of tumor cells. These findings support the use of combination regimens that include DNMTi and immunotherapy for cancer treatment. DNA methyltransferase inhibitors potentiate anti-tumor immunity by inducing tumor immunogenicity and improving antigen processing through the STING-dependent type I interferon response. [ABSTRACT FROM AUTHOR]

A new approach is presented in this paper for the dynamic modeling of the chemical and isotopic evolution of C1–3 during the hydrocarbon generation process. Based on systematic data obtained from published papers for the pyrolysis of various hydrocarbon sources (type I kerogen/source rock, type II kerogen/source rock, type III kerogen/source rock, crude oil, and asphalt, etc.), the empirical evolution framework of the chemical and isotopic composition of C1–3 during the hydrocarbon generation process was built. Although the empirical framework was built only by fitting a large amount of pyrolysis data, the chemical and isotopic composition of C1–3 derived from the pyrolysis experiments all follow evolution laws, convincing us that it is applicable to the thermal evolution process of various hydrocarbon sources. Based on the simplified formula of the isotopic composition of mixed natural gas at different maturities (δ13Cmixed), δ13Cmixed = X × n i A × δ 13 C i A + Y × n i B × δ 13 C i B X × n i A + Y × n i B , it can be derived that the cumulative isotopic composition of alkane generated in a certain maturity interval can be expressed by the integral of the product of the instantaneous isotopic composition and instantaneous yield at a certain maturity point, and then divided by the cumulative yield of alkane generated in the corresponding maturity interval. Thus, the cumulative isotopic composition (A(X)), cumulative yield (B(X)), instantaneous isotope (C(X)), and instantaneous yield (D(x)) in the dynamic model, comply with the following formula during the maturity interval of (X0~X). A(X) = ∫ X 0 X C X × D X d x B (X) , where A(X) and B(X) can be obtained by the fitting of pyrolysis data, and D(x) can also be obtained from the derivation of B(X). The dynamic model was applied on the pyrolysis data of Pingliang Shale to illustrate the quantitative evolution of the cumulative yield, instantaneous yield, cumulative isotope, and instantaneous isotope of C1–3 with increasing maturity. The dynamic model can quantify the yield of methane, ethane, and propane, as well as δ13C1, δ13C2, and δ13C3, respectively, during the hydrocarbon generation process. This model is of great significance for evaluating the natural gas resources of hydrocarbon source rock of different maturities and for identifying the origin and evolutionary process of hydrocarbons by chemical and isotopic data. Moreover, this model provides an approach to study the dynamic evolution of the isotope series of C1–3 (including reversed isotopic series), which is promising for revealing the mechanism responsible for isotopic reversal when combined with post-generation studies. [ABSTRACT FROM AUTHOR]

Introduction: There are only four sizes of implantable collamer lens (ICL) available for selection, which cannot completely fit all patients as a result of the discontinuity of ICL sizes. Sizing an optimal ICL and predicting postoperative vault are still unresolved problems. This study aimed to develop and validate innovative data-level data-balancing machine learning-based models for predicting ICL size and postoperative vault. Methods: The patients were randomly assigned to training and internal validation sets in a 4:1 ratio. Feature selection was performed using analysis of variance (ANOVA) and Kruskal–Wallis feature importance methods. Traditional linear regression model and machine learning-based models were used. The accuracy of models was assessed using the area under the curve (AUC) and confusion matrix. Results: A total of 564 patients (1127 eyes) were eligible for this study, consisting of 808 eyes in the training set, 202 eyes in the internal validation set, and 117 eyes in the external validation set. Compared with the traditional linear regression method, the machine learning model bagging tree showed the best performance for ICL size selection, with an accuracy of 84.5% (95% confidence interval (CI) 83.2–85.8%), and the AUC ranged from 0.88 to 0.99; the prediction accuracy of 12.1 mm and 13.7 mm ICL sizes was improved by 49% and 59%, respectively. The bagging tree model achieved the best accuracy [90.2%, (95% CI 88.9–91.5%)] for predicting the postoperative vault, and the AUC ranged from 0.90 to 0.94. The prediction accuracies of internal and external validation dataset for ICL sizing were 82.2% (95% CI 81.1–83.3%) and 82.1% (95% CI 81.1–83.1%), respectively. Conclusions: The innovative data-level data balancing-based machine learning model can be used to predict ICL size and postoperative vault more accurately, which can assist surgeons in choosing optimal ICL size, thus reducing risks of postoperative complications and secondary surgery. [ABSTRACT FROM AUTHOR]

• A common carbon nitride delivers great 2eORR activity for H 2 O 2 production in presence of lactic acid as sacrificial agent. • Pyruvic acid is simultaneously produced from selective dehydrogenation of lactic acid. • Other hydroxycarboxylic acids are selectively dehydrogenated into corresponding aldehydic or keto acids. • In-depth experimental and theoretical investigations reveal the detailed reaction mechanism. Photocatalytic H 2 O 2 production is emerging as an alternative technology to contribute H 2 O 2 -based advanced oxidation applications. However, the present reaction systems rarely consider the selective oxidation of sacrificial agent along with oxygen reduction reaction. Herein, we design a reaction system by using hydroxycarboxylic acids as additives to boost photocatalytic H 2 O 2 production. More importantly, hydroxycarboxylic acids could simultaneously be dehydrogenated into aldehydic/keto acids with high selectivity. Lactic acid as one of the typical hydroxycarboxylic acids reveals the feasibility of this hypothesis, delivering 6.56 mM/h of H 2 O 2 generation along with > 70 % pyruvic acid selectivity. The universality of this reaction system is demonstrated by using other hydroxycarboxylic acids. This works sheds new light on coupling H 2 O 2 generation with value-added chemicals production by mild photocatalytic approach. [ABSTRACT FROM AUTHOR]

Here, we demonstrate the selective cellobiose (building block of cellulose) photoreforming for gluconic acid and syngas co-production in acidic conditions by rationally designing a bifunctional polymeric carbon nitride (CN) with potassium/sulfur co-dopant. This heteroatomic doped CN photocatalyst possesses enhanced visible light absorption, higher charge separation efficiency than pristine CN. Under acidic conditions, cellobiose is not only more efficiently hydrolyzed into glucose but also promotes the syngas and gluconic acid production. Density functional theory (DFT) calculations reveal the favorable generation of •O 2 − during the photocatalytic reaction, which is essential for gluconic acid production. Consequently, the fine-designed photocatalyst presents excellent cellobiose conversion (>80%) and gluconic acid selectivity (>70%) together with the co-production of syngas (∼56 μmol g−1 h−1) under light illumination. The current work demonstrates the feasibility of biomass photoreforming with value-added chemicals and syngas co-production under mild condition. [Display omitted] • Bifunctional CN with K, S co-doping is synthesized via a facile calcination process. • Acidic cellobiose photoreforming to simultaneously obtain gluconic acid and syngas. • Cellobiose conversion (>80%) and gluconic acid selectivity (>70%) can be achieved. • Favorable generation of •O 2 − proved by DFT is essential for gluconic acid production. [ABSTRACT FROM AUTHOR]

• Three phosphate ester-based MOFs (UiO-66-(OPO 3) X) containing different amounts and spatial positions were prepared. • UiO-66-(OPO 3) X can efficiently remove Pb2+ from aqueous solution. • Even at pH = 2 and pH = 3, UiO-66-(OPO 3) X maintains a high removal efficiency of Pb2+. • UiO-66-(OPO 3) X has excellent selectivity and anti-interference ability for Pb2+. • The adsorption mechanism was investigated in detail by experiment combined with DFT. Metal-organic framework (MOF) materials have emerged as promising candidates for treating heavy metal wastewater because of their controllable pore size, high specific surface area, and abundant active sites. Nevertheless, the currently reported MOFs usually require near-neutral environments (pH = 5–6) to achieve efficient removal of Pb2+ and cannot be applied to acidic environments (pH = 2–3). In this work, the structurally stabilized zirconium-based MOF UiO-66 was chosen as the object of study. Three phosphate ester-based MOFs (UiO-66-(OPO 3) X) containing different amounts and spatial positions were designed and prepared by simple chemical modification and used to remove Pb2+. Adsorption experiments showed that they could reach adsorption equilibrium in 30 min with excellent adsorption rate. Owing to the unique ionization ability of the phosphate ester group, UiO-66-(OPO3) X maintains a high removal efficiency of Pb2+ even at pH = 2 and pH = 3. In addition, selectivity and competition experiments demonstrated that UiO-66-(OPO 3) X possessed excellent selectivity and anticompetitive ability towards Pb2+.The excellent regeneration performance demonstrates their value for practical application. Moreover, the adsorption mechanism was investigated in detail by experiment combined with density functional theory (DFT). [ABSTRACT FROM AUTHOR]

The seismic response is a critical aspect of structural engineering, as it directly influences the design and safety evaluation of such systems. Structural seismic response becomes more complicated when unavoidable uncertainties in the structure are considered. Therefore, solving and analyzing the stochastic dynamic response of structures efficiently and accurately is of great significance. Various uncertainty quantification methods such as the stochastic finite element method, Monte Carlo method, and polynomial chaos expansion method have made significant progress in this field. However, these methods do not provide a comprehensive study of the seismic response of stochastic structures and efficiency problems rapidly emerge as the number of random variables increases. This paper delivers a comprehensive study of the seismic dynamic response of space truss and reticulated shell structure considering uncertainties in material properties, geometry, and loading. To this end, the finite element model of the structure was first modeled and the deterministic solutions were obtained. Then, polynomial surrogates are modeled for the natural frequency, mode participation factor, mode superposition response, and transient response of the structure under stochastic uncertainties. The sparse grid technique is used to select sparse quadrature points, which overcomes the curse of dimensionality caused by full grid integration. The results demonstrate that the sparse grid-based polynomial chaos expansion is more efficient. Uncertainty quantification reveals the uncertainty of modal analysis, response spectrum analysis, and transient response analysis of space truss and reticulated shell under seismic excitation. In summary, this study provides valuable insights and an efficient and accurate uncertainty quantification tool for the seismic dynamic analysis of stochastic structures, ultimately contributing to safer and more robust structural designs. • Analyzing the seismic dynamic response of stochastic structures comprehensively. • Sparse grid-based PCE for quantifying uncertainty in stochastic dynamics. • Addressing the dimensional catastrophe of traditional non-intrusive PCE. • Sparse grid-based PCE metamodel for post-processing is more efficient and accurate. [ABSTRACT FROM AUTHOR]

To address the issue of low accuracy resulting from approximation errors in conventional interval finite element methods, this study presents an ɛ -accelerated bivariate dimension-reduction interval finite element method. The proposed method aims to accurately and efficiently predict the static response of structures with high dimensionality and large uncertainty parameters. We first approximate the structural interval equilibrium equation using a bivariate dimension-reduction method. An explicit expression for the sequence of displacements is derived by approximating the inverse of the structural interval stiffness matrix using the Neumann series. Adjoint-based sensitivity analysis can effectively avoid the response interval expansion caused by parameter coupling. For improving the convergence speed and computational accuracy, the displacement response sequence is accelerated by a vector ɛ acceleration algorithm and an adaptive strategy. Finally, three engineering structures with uncertain-but-bounded parameters are analyzed with the proposed method. Compared with conventional interval analysis methods, the proposed method effectively balances computational accuracy and efficiency, making it more suitable for non-linear and large uncertainty problems with multiple interval parameters. The study shows that ɛ -accelerated bivariate dimension-reduction interval finite element method has a promising application. • An interval finite element method based on bivariate dimension-reduction is proposed. • Explicit sequences and errors for the bounds of displacements were derived. • Dependencies between parameters are addressed by adjoint-based sensitivity analysis. • Convergence speed and accuracy are improved by the adaptive ɛ algorithm. • Structural response intervals are efficiently and accurately predicted. [ABSTRACT FROM AUTHOR]

In the present study, two new Conidiobolus s.s. species were described relying on the morphological studies and phylogenetic analysis utilizing nuclear large subunit of rDNA (nucLSU), mitochondrial small subunit of rDNA (mtSSU), and elongation-factor-like gene (EFL) sequences. Conidiobolus jiangxiensis sp. nov. is distinguished by its short primary conidiophores, a feature not commonly observed in other Conidiobolus s.s. species. Conversely, Conidiobolus marcoconidius sp. nov. is characterized by larger primary conidia and the emergence of 2–5 secondary conidia from each branched secondary conidiophores. Additionally, the taxonomic reassessment of C. polyspermus confirms its distinct status within the genus Conidiobolus s.s. Moreover, molecular analyses, incorporating the nucLSU , mtSSU , and EFL sequences, provide robust support for the phylogenetic placement of the two newly described species and the taxonomic identity of C. polyspermus. This investigation contributes valuable insights into the species diversity of Conidiobolaceae in China, enhancing our understanding of the taxonomy within this fungal family. [ABSTRACT FROM AUTHOR]

[Display omitted] Photorefining of biomass is increasingly recognized as a pivotal technology for the simultaneous production of hydrogen and value-added chemicals. The intrinsic recalcitrance of lignocellulosic biomass puts high demands on the rational design of bifunctional photocatalyst. Herein, Ni 2 P/CdS with a strong interfacial effect in this work was designed to overcome lignocellulosic biomass photorefining. The strong interfacial effect between Ni 2 P and CdS not only improved the light absorbance, but also optimized the spatial redistribution of photogenerated electrons and holes. Therefore, Ni 2 P/CdS exhibited an unprecedented H 2 evolution activity (ca. 199.7 mmol·h−1·g−1) in the presence of lactic acid as the traditional sacrificial agent. Considerable H 2 generation was also achieved in the presence of lignin (ca. 322.8 μmol·h−1·g−1), cellulose (ca. 534.3 μmol·h−1·g−1) and hemicellulose (ca. 382.2 μmol·h−1·g−1) as the electron donor respectively. Theoretical calculation results indicated that establishing the interfacial effect between Ni 2 P and CdS optimized their work functions. This optimization fosters improved the redistribution between electrons and holes, as a result, photocatalytic hydrogen production from biomass solution was greatly enhanced. Significantly, Ni 2 P/CdS showed dual functionalities to produce H 2 and value-added compounds from raw biomass directly. This present work demonstrates the potential of raw biomass photorefining through astutely designing photocatalysts. [ABSTRACT FROM AUTHOR]

Background: Neurodevelopmental disorders (NDD), such as autism spectrum disorders (ASD) and intellectual disorders (ID), are highly debilitating childhood psychiatric conditions. Genetic factors are recognized as playing a major role in NDD, with a multitude of genes and genomic regions implicated. While the functional validation of NDD-associated genes has predominantly been carried out using mouse models, the significant differences in brain structure and gene function between mice and humans have limited the effectiveness of mouse models in exploring the underlying mechanisms of NDD. Therefore, it is important to establish alternative animal models that are more evolutionarily aligned with humans. Results: In this study, we employed CRISPR/Cas9 and somatic cell nuclear transplantation technologies to successfully generate a knockout miniature pig model of the MIR137 gene, which encodes the neuropsychiatric disorder-associated microRNA miR-137. The homozygous knockout of MIR137 (MIR137–/–) effectively suppressed the expression of mature miR-137 and led to the birth of stillborn or short-lived piglets. Transcriptomic analysis revealed significant changes in genes associated with neurodevelopment and synaptic signaling in the brains of MIR137–/– miniature pig, mirroring findings from human ASD transcriptomic data. In comparison to miR-137-deficient mouse and human induced pluripotent stem cell (hiPSC)-derived neuron models, the miniature pig model exhibited more consistent changes in critical neuronal genes relevant to humans following the loss of miR-137. Furthermore, a comparative analysis identified differentially expressed genes associated with ASD and ID risk genes in both miniature pig and hiPSC-derived neurons. Notably, human-specific miR-137 targets, such as CAMK2A, known to be linked to cognitive impairments and NDD, exhibited dysregulation in MIR137–/– miniature pigs. These findings suggest that the loss of miR-137 in miniature pigs affects genes crucial for neurodevelopment, potentially contributing to the development of NDD. Conclusions: Our study highlights the impact of miR-137 loss on critical genes involved in neurodevelopment and related disorders in MIR137–/– miniature pigs. It establishes the miniature pig model as a valuable tool for investigating neurodevelopmental disorders, providing valuable insights for potential applications in human research. [ABSTRACT FROM AUTHOR]

Smart windows with excellent near-infrared (NIR) light shielding capacity and controlled visible light transmittance are expected to reduce building energy consumption and improve indoor comfort. However, the ability of current thermochromic materials to regulate solar gain with the tunable extinction of phase-change materials is still far from optimum. In this work, an fluorine (F)-doped ATO (FATO) nanocrystals (NCs) are designed as a photothermal material to optimize the solar modulation of thermochromic hydrogels. F ion doping can modify the electronic structure of ATO, resulting in a high concentration of oxygen vacancies and free electrons, thereby enhancing the NIR absorption performance and photothermal conversion performance of the ATO NCs. On this premise, the designed smart window based on FATO NCs and thermochromic hydrogels exhibits the remarkable features of excellent NIR shielding, high initial visible transmittance and fast response speed. The window is capable of shielding 99.5% of the solar radiation from 300 to 2500 nm and permitting 75.0% of initial visible light. Moreover, the simulated indoor temperature of the smart window was 17.2 °C lower compared with the black one, demonstrating potentials in practical application of building energy saving. [Display omitted] • Novel chain-like FATO NCs were prepared by precipitation-hydrothermal method. • F-doping optimized electronic structure of ATO and improved the LSPR absorption. • The fabrication of FATO-PNC hydrogel provides a novel idea for smart window. • The smart window could shield 99.5% of solar radiation after optical switching. [ABSTRACT FROM AUTHOR]

Fluorescence in situ hybridization (FISH) is a powerful cytogenetic method used to precisely detect and localize nucleic acid sequences. This technique is proving to be an invaluable tool in medical diagnostics and has made significant contributions to biology and the life sciences. However, the number of cells is large and the nucleic acid sequences are disorganized in the FISH images taken using the microscope. Processing and analyzing images is a time-consuming and laborious task for researchers, as it can easily tire the human eyes and lead to errors in judgment. In recent years, deep learning has made significant progress in the field of medical imaging, especially the successful application of introducing the attention mechanism. The attention mechanism, as a key component of deep learning, improves the understanding and interpretation of medical images by giving different weights to different regions of the image, enabling the model to focus more on important features. To address the challenges in FISH image analysis, we combined medical imaging with deep learning to develop the SEAM-Unet++ automated cell contour segmentation algorithm with integrated attention mechanism. The significant advantage of this algorithm is that it improves the accuracy of cell contours in FISH images. Experiments have demonstrated that by introducing the attention mechanism, our method is able to segment cells that are adherent to each other more efficiently. [ABSTRACT FROM AUTHOR]

High efficiency extractants play a necessary role in the selective removal of uranium from rare earth minerals. In this paper, a novel cyclic bidentate diamine extractant, 1, 4-dioctyl-1, 4-dihydroquinoxaline-2, 3-dione (DODQ), was synthesized, and the complexation and extraction of UO 2 2+ in nitric acid medium were systematically studied. The results indicate that DODQ exhibits a unique combination of properties in removing UO 2 2+, with an extraction capacity 132 times higher than that of DODPhOA (acyclic structure). Extraction isotherm experiments and slope analyses illustrate the formation of a 1:1 DODQ/UO 2 2+ regime during the extraction process. Electrospray mass spectrometry, fluorescence spectroscopy, and X-ray crystal diffraction analyses further corroborated its stoichiometric properties. In addition, DODQ can remove UO 2 2+ from rare earth solutions containing UO 2 2+ with high selectivity. This study provides an alternative method to separate uranium from the leaching solution of rare earth ore and has a new understanding of the coordination and complexing behavior of UO 2 2+ with bidentate oxygen-containing ligands. Due to the design of the bidentate oxygen of the extractant structure itself, which is orthogonal to the uranyl ion, DODQ has a good extraction ability and selectivity towards UO 2 2+, and achieves the separation of UO 2 2+ and Ln3+. [Display omitted] • A new and effective extractant for UO 2 2+ is synthesized and characterized. • Fixing the orientation of carbonyl groups (C=O) onto the extractant structure. • The extraction capacity of DODQ was determined to be 132 times higher. • The extraction ability of 0.1 mol/L DODQ is better than that of 0.1 mol/L TBP. • DODQ can selectively concentrate UO 2 2+ in a rare earth ore simulation solution. [ABSTRACT FROM AUTHOR]

Lactate is a glycolysis end product, and its levels are markedly associated with disease severity, morbidity, and mortality in sepsis. It modulates key functions of immune cells, including macrophages. In this investigation, transcriptomic analysis was performed using lactic acid, sodium lactate, and hydrochloric acid-stimulated mouse bone marrow-derived macrophages (iBMDM), respectively, to identify lactate-associated signaling pathways. After 24 h of stimulation, 896 differentially expressed genes (DEG) indicated were up-regulation, whereas 792 were down-regulated in the lactic acid group, in the sodium lactate group, 128 DEG were up-regulated, and 41 were down-regulated, and in the hydrochloric acid group, 499 DEG were up-regulated, and 285 were down-regulated. Subsequently, clinical samples were used to further verify the eight genes with significant differences, among which Tssk6, Ypel4, Elovl3, Trp53inp1, and Cfp were differentially expressed in patients with high lactic acid, indicating their possible involvement in lactic acid-induced inflammation and various physiological diseases caused by sepsis. However, elongation of very long chain fatty acids protein 3 (Elovl3) was negatively correlated with lactic acid content in patients. The results of this study provide a necessary reference for better understanding the transcriptomic changes caused by lactic acid and explain the potential role of high lactic acid in the regulation of macrophages in sepsis. • Transcriptomic analysis of iBMDM stimulated with lactic acid, sodium lactate, and hydrochloric acid. • TSSK6, YPEL4, ELOVL3, TRP53INP1, and CFP were highly expressed in septic patients with hyperlactic acid. • Elovl3 was negatively correlated with lactic acid content in patients with sepsis. [ABSTRACT FROM AUTHOR]

Enhanced visible-light-driven porous O/P-C 3 N 4 for persulfate photoactivation to remove refractory organic pollutants (bisphenol A and 2-mercaptobenzothiazole) and depolymerize lignin to vanillic acid and various gases. [Display omitted] • Surface electron density on HAPA-CN was enhanced by oxygen and phosphorus doping. • 0.05 HAPA-CN exhibits excellent performance for persulfate photoactivation to remove BPA and MBT. • In-depth exploration of the intermediate products during the photodegradation. • Remarkable sodium lignosulfonate conversion and vanillic acid selectivity achieved. • The transformation of sodium lignosulfonate synergistically produces a variety of gases (H 2 , CO, CH 4 , C 2 H 4 , C 2 H 6). In this research, an enhanced visible light response of oxygen and phosphorus-doped porous g-C 3 N 4 (HAPA-CN) was prepared by thermo-polymerization of urea, hydroxyacetic acid and phytic acid. Its internal structure was verified by solid-state nuclear magnetism (NMR) and secondary ion mass spectrometry (SIMS). The surface electron density on HAPA-CN was enhanced by the inclusion of oxygen and phosphorus. The boosted photocatalytic activity was attributed to the high spectral utilization of sunlight and meliorated charge separation efficiency. The experimental results showed that the 0.05 HAPA-CN/persulfate (PS) system exhibited a higher efficiency in the photodegradation process of bisphenol A (BPA) and 2-mercaptobenzothiazole (MBT). Compared with ordinary g-C 3 N 4 , the integration of photocatalysis and persulfate oxidation led to an increase in the removal of BPA and MBT pollutants, which increased by 68.11 and 11.18 times, respectively. 0.05 HAPA-CN also exhibited a certain photodegradation of BPA under long-wavelength light irradiation such as blue, green, and red light. In the photocatalytic conversion of sodium lignosulfonate (SL), the 0.05 HAPA-CN/PS system achieved a maximum yield of 134.34 mg/g SL vanillic acid at 30 min, which was significantly better than that of g-C 3 N 4. Synergistic gas production (H 2 , CO, CH 4 , C 2 H 4 , C 2 H 6) was also significantly enhanced. Combined with theoretical calculations, the mechanism was also analyzed. This work provides new insights for exploring high efficiency photocatalyst that combine porous structure, oxygen and phosphorus co-doping and PS activation technology for removal of organic pollutants and lignin valorization. [ABSTRACT FROM AUTHOR]

AbstractSNX29 is a potential functional gene associated with meat production traits. Previous studies have shown that SNX29 copy number variation (CNV) could be implicated with phenotype in goats. However, in Diannan small-ear (DSE) pigs, the genetic impact of SNX29 CNV on growth traits remains unclear. Therefore, this study investigated the associations between SNX29 CNVs (CNV10810 and CNV10811) and growth traits in 415 DSE pigs. The results revealed that the CNV10810 mutation was significantly associated with backfat thickness in DSE pigs at 12 and 15 months old (P < 0.05), while the CNV10811 mutation had significant effects on various growth traits at 6 and 12 months old, particularly for body weight, body height, back height and backfat thickness (P < 0.05 or P < 0.001). In conclusion, our results confirm that SNX29 CNV plays a role in regulating growth and development in pigs, thus suggesting its potential application for pig breeding programmes. [ABSTRACT FROM AUTHOR]