Causal relationship between air pollution, lung function, gastroesophageal reflux disease, and non-alcoholic fatty liver disease: univariate and multivariate Mendelian randomization study.

Background: The association between air pollution, lung function, gastroesophageal reflux disease, and Non-alcoholic fatty liver disease (NAFLD) remains inconclusive. Previous studies were not convincing due to confounding factors and reverse causality. We aim to investigate the causal relationship between air pollution, lung function, gastroesophageal reflux disease, and NAFLD using Mendelian randomization analysis. Methods: In this study, univariate Mendelian randomization analysis was conducted first. Subsequently, Steiger testing was performed to exclude the possibility of reverse association. Finally, significant risk factors identified from the univariate Mendelian analysis, as well as important factors affecting NAFLD from previous observational studies (type 2 diabetes and body mass index), were included in the multivariable Mendelian randomization analysis. Results: The results of the univariable Mendelian randomization analysis showed a positive correlation between particulate matter 2.5, gastroesophageal reflux disease, and NAFLD. There was a negative correlation between forced expiratory volume in 1 s, forced vital capacity, and NAFLD. The multivariable Mendelian randomization analysis indicated a direct causal relationship between gastroesophageal reflux disease (OR = 1.537, p = 0.011), type 2 diabetes (OR = 1.261, p < 0.001), and NAFLD. Conclusion: This Mendelian randomization study confirmed the causal relationships between air pollution, lung function, gastroesophageal reflux, and NAFLD. Furthermore, gastroesophageal reflux and type 2 diabetes were identified as independent risk factors for NAFLD, having a direct causal connection with the occurrence of NAFLD.

Combined Machine Learning and High-Throughput Calculations Predict Heyd-Scuseria-Ernzerhof Band Gap of 2D Materials and Potential MoSi2N4 Heterostructures.

We present a novel target-driven methodology devised to predict the Heyd-Scuseria-Ernzerhof (HSE) band gap of two-dimensional (2D) materials leveraging the comprehensive C2DB database. This innovative approach integrates machine learning and density functional theory (DFT) calculations to predict the HSE band gap, conduction band minimum (CBM), and valence band maximum (VBM) of 2176 types of 2D materials. Subsequently, we collected a comprehensive data set comprising 3539 types of 2D materials, each characterized by its HSE band gaps, CBM, and VBM. Considering the lattice disparities between MoSi2N4 (MSN) and 2D materials, our analysis predicted 766 potential MSN/2D heterostructures. These heterostructures are further categorized into four distinct types based on the relative positions of their CBM and VBM: Type I encompasses 230 variants, Type II comprises 244 configurations, Type III consists of 284 permutations, and 0 band gap comprises 8 types.

CT-derived Radiomics Predicts the Efficacy of Tyrosine Kinase Inhibitors in Osteosarcoma Patients with Pulmonary Metastasis.

BACKGROUND: To construct and validate the CT-based radiomics model for predicting the tyrosine kinase inhibitors (TKIs) effects in osteosarcoma (OS) patients with pulmonary metastasis. METHODS: OS patients with pulmonary metastasis treated with TKIs were randomly separated into training and testing cohorts (2:1 ratio). Radiomic features were extracted from the baseline unenhanced chest CT images. The random survival forest (RSF) and Kaplan-Meier survival analyses were performed to construct and evaluate radiomics signatures (R-model-derived). The univariant and multivariant Cox regression analyses were conducted to establish clinical (C-model) and combined models (RC-model). The discrimination abilities, goodness of fit and clinical benefits of the three models were assessed and validated in both training and testing cohorts. RESULTS: A total of 90 patients, 57 men and 33 women, with a mean age of 18 years and median progression-free survival (PFS) of 7.2 months, were enrolled. The R-model was developed with nine radiomic features and demonstrated significant predictive and prognostic values. In both training and testing cohorts, the time-dependent area under the receiver operating characteristic curves (AUC) of the R-model and RC-model exhibited obvious superiority over C-model. The calibration and decision curve analysis (DCA) curves indicated that the accuracy of the R-model was comparable to RC-model, which exhibited significantly better performance than C-model. CONCLUSIONS: The R-model showed promising potential as a predictor for TKI responses in OS patients with pulmonary metastasis. It can potentially identify pulmonary metastatic OS patients most likely to benefit from TKIs treatment and help guide optimized clinical decisions.

Understanding and exploring the diversity of soil microorganisms in tea (Camellia sinensis) gardens: toward sustainable tea production.

Leaves of Camellia sinensis plants are used to produce tea, one of the most consumed beverages worldwide, containing a wide variety of bioactive compounds that help to promote human health. Tea cultivation is economically important, and its sustainable production can have significant consequences in providing agricultural opportunities and lowering extreme poverty. Soil parameters are well known to affect the quality of the resultant leaves and consequently, the understanding of the diversity and functions of soil microorganisms in tea gardens will provide insight to harnessing soil microbial communities to improve tea yield and quality. Current analyses indicate that tea garden soils possess a rich composition of diverse microorganisms (bacteria and fungi) of which the bacterial Proteobacteria, Actinobacteria, Acidobacteria, Firmicutes and Chloroflexi and fungal Ascomycota, Basidiomycota, Glomeromycota are the prominent groups. When optimized, these microbes' function in keeping garden soil ecosystems balanced by acting on nutrient cycling processes, biofertilizers, biocontrol of pests and pathogens, and bioremediation of persistent organic chemicals. Here, we summarize research on the activities of (tea garden) soil microorganisms as biofertilizers, biological control agents and as bioremediators to improve soil health and consequently, tea yield and quality, focusing mainly on bacterial and fungal members. Recent advances in molecular techniques that characterize the diverse microorganisms in tea gardens are examined. In terms of viruses there is a paucity of information regarding any beneficial functions of soil viruses in tea gardens, although in some instances insect pathogenic viruses have been used to control tea pests. The potential of soil microorganisms is reported here, as well as recent techniques used to study microbial diversity and their genetic manipulation, aimed at improving the yield and quality of tea plants for sustainable production.

Surface plasmon enhancement in silver nanowires and bilayer two-dimensional materials.

In order to improve the low light absorption of two-dimensional (2D) transition metal dichalcogenides (TMDCs), surface plasmon (SP) nanostructures have been widely studied. However, the impact of interlayer twist on such nanostructures has rarely been studied. Here, we construct two different composite structures of silver nanowires (Ag NWs) and pristine bilayer MoS2 (pBLM) or twisted bilayer MoS2 (tBLM). The interlayer twist can further promote the light utilization of MoS2, resulting in an ∼4-fold higher spectral enhancement in Ag/tBLM than that in Ag/pBLM. In addition, the photocurrent and detectivity of the phototransistor based on the Ag/tBLM composite structure were improved by 7-fold and ∼100-fold, respectively, compared to those of the Ag/pBLM phototransistor. Theoretical simulations show that the enhancement of photocurrent can be attributed to the enhancement of the local electric field at the interface between Ag NWs and the tBLM film, which is called the 'hot spot'. These results provide a reference for understanding the modulation mechanism of SPs and interlayer twist on the optoelectronic properties of 2D materials.

Three New Species of Russulaceae (Russulales, Basidiomycota) from Southern China.

The characterization of natural fungal diversity impacts our understanding of ecological and evolutionary processes and can lead to novel bioproduct discovery. Russula and Lactarius, both in the order Russulales, represent two large genera of ectomycorrhizal fungi that include edible as well as toxic varieties. Based on morphological and phylogenetic analyses, including nucleotide sequences of the internal transcribed spacer (ITS), the 28S large subunit of ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), the ribosomal mitochondrial small subunit (mtSSU), and the translation elongation factor 1-α (TEF1-α) gene sequences, we here describe and illustrate two new species of Russula and one new species of Lactarius from southern China. These three new species are: R. junzifengensis (R. subsect. Virescentinae), R. zonatus (R. subsect. Crassotunicatae), and L. jianyangensis (L. subsect. Zonarii).

Achieving Molecular-Level Selective Detection of Volatile Organic Compounds through a Strong Coupling Effect of Ultrathin Nanosheets and Au Nanoparticles.

The high density of surface active sites, high efficiency of interfacial carrier transport, and molecular diffusion path determine the efficiency of the electrochemical sensors. The ultrathin structures have atomic-level thickness, carrier migration and heat diffusion are limited in the two-dimensional plane, resulting in excellent conductivity and high carrier concentration. A one-step chemical method is applied to synthesize defect-rich Au-SnO2 in an ultrathin nanosheet form (thickness of 2-3 nm). The strong interaction between Au and SnO2 via the Au-O-Sn bonding and the catalytic effect of Au can prolong the service life via decreasing the optimal operating temperature (55 °C) and promote the Au-SnO2 sensor to exclusively detect formaldehyde at the ppb level (300 ppb). The experimental findings along with theoretical study reveal that Au nanoparticles have a different effect on the competitive adsorption and chemical reaction over the surface of the Au-SnO2 with formaldehyde and other interfering VOC gases, such as methanol, ethanol, and acetone. This study provides mechanistic insights into the correlation between operating temperature and the performance of the Au-SnO2 chemiresistive sensor. This work allows the development of highly efficient and stable electrochemical sensors to detect VOC gases at room temperature in the future.

Potential prognostic biomarkers of hepatocellular carcinoma based on 4D label-free quantitative proteomics analysis pilot investigation.

BACKGROUND: Hepatocellular carcinoma carries a poor prognosis and poses a serious threat to global health. Currently, there are few potential prognostic biomarkers available for the prognosis of hepatocellular carcinoma. METHODS: This pilot study used 4D label-free quantitative proteomics to compare the proteomes of hepatocellular carcinoma and adjacent non-tumor tissue. A total of 66,075 peptides, 6363 identified proteins, and 772 differentially expressed proteins were identified in specimens from three hepatocellular carcinoma patients. Through functional enrichment analysis of differentially expressed proteins by Gene Ontology, KEGG pathway, and protein domain, we identified proteins with similar functions. RESULTS: Twelve differentially expressed proteins (RPL17, RPL27, RPL27A, RPS5, RPS16, RSL1D1, DDX18, RRP12, TARS2, YARS2, MARS2, and NARS1) were selected for identification and validation by parallel reaction monitoring. Subsequent Western blotting confirmed overexpression of RPL27, RPS16, and TARS2 in hepatocellular carcinoma compared to non-tumor tissue in 16 pairs of clinical samples. Analysis of The Cancer Genome Atlas datasets associated the increased expression of these proteins with poor prognosis. Tissue microarray revealed a negative association between high expression of RPL27 and TARS2 and the prognosis of hepatocellular carcinoma patients, although RPS16 was not significant. CONCLUSIONS: These data suggest that RPL27 and TARS2 play an important role in hepatocellular carcinoma progression and may be potential prognostic biomarkers of overall survival in hepatocellular carcinoma patients.

Dynamic nomogram for predicting hungry bone syndrome before parathyroidectomy.

PURPOSE: The objective of this study was to develop a dependable and uncomplicated prediction model utilizing clinical information readily accessible to patients before surgery. This model aimed to assess the likelihood of hungry bone syndrome occurrence in post-surgery patients with secondary hyperparathyroidism (SHPT), and to assist clinicians in adjusting treatment plans promptly. METHODS: In this study, we constructed an online nomogram utilizing independent variables determined through multiple logistic regression to predict the probability of HBS occurrence after parathyroidectomy in patients with secondary hyperparathyroidism. To evaluate the precision and dependability of the nomogram, we used receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: Multivariate logistic regression analyses on 136 eligible patients identified age, parathyroid hormone (PTH), and blood calcium as independent HBS risk factors, which were then integrated into the nomogram. The area under ROC curve demonstrated the nomogram's strong predictive accuracy. The calibration curve demonstrates consistency between the model's prediction probability and observed probability, reflecting high prediction accuracy of the nomogram. Dynamic nomograms were found to hold significant practical clinical value as demonstrated by clinical decision analysis. It can be accessed on https://min115.shinyapps.io/dynnomapp/ . CONCLUSION: In patients with secondary hyperparathyroidism, the dynamic nomogram based on age, parathyroid hormone, and blood calcium can more accurately predict the likelihood of HBS after parathyroidectomy, allowing doctors to make clinical decisions more quickly and adjust treatment plans in a timely manner to reduce the incidence of HBS.

Reduced recurrence rate and comparable functionality after wide resection and reverse total shoulder arthroplasty with allograft-prosthetic composite versus curettage for proximal humeral giant cell tumor: a multicenter retrospective study.

BACKGROUND: Giant cell tumors of bone (GCTBs) are rare, aggressive tumors, and the proximal humerus is a relatively rare location for GCTBs; limited evidence exists on which surgical approaches and reconstruction techniques are optimal. In the largest case series to date, we evaluated the recurrence rate of proximal humeral GCTBs and the functional outcomes of different resection and reconstruction options in this multicenter study. METHODS: All 51 patients included in this study received initial surgical treatment for proximal humeral GCTBs from January 2007 to December 2020, with a minimum 2-year follow-up period. Local recurrence and functional outcomes were statistically analyzed in relation to demographic, clinical, and primary surgical variables. Functional outcomes were reported by patients and were assessed by the Musculoskeletal Tumor Society score and QuickDASH instrument (shortened version of the Disabilities of the Arm, Shoulder and Hand instrument). RESULTS: The mean follow-up period was 81.5 months (range, 30-191 months), and the overall recurrence rate was 17.6% (9 of 51 patients). The majority of recurrences (n = 7) occurred in the first 2 years of follow-up. The intralesional curettage group (n = 23) showed a statistically significant difference in the recurrence rate compared with the en bloc resection group (n = 28) (34.8% vs. 3.6%, P = .007). Among shoulders receiving en bloc resection, 16 were reconstructed with hemiarthroplasty; 8, reverse total shoulder arthroplasty (rTSA) with allograft-prosthetic composite (APC) reconstruction; and 4, arthrodesis. On the basis of intention-to-treat analysis, the mean functional Musculoskeletal Tumor Society scores of the groups undergoing curettage, rTSA with APC, hemiarthroplasty, and arthrodesis were 26.0 ± 3.1, 26.0 ± 1.7, 20.3 ± 2.8, and 22.5 ± 1.3, respectively (P < .001 [with P < .001 for curettage vs. hemiarthroplasty and P = .004 for rTSA with APC vs. hemiarthroplasty]) and the mean QuickDASH scores were 14.0 ± 11.0, 11.6 ± 4.5, 33.1 ± 11.8, and 21.6 ± 4.7, respectively (P < .001 [with P < .001 for curettage vs. hemiarthroplasty and P = .003 for rTSA with APC vs. hemiarthroplasty]). CONCLUSIONS: On the basis of our data, en bloc resection followed by reverse shoulder arthroplasty showed a lower recurrence rate and no significant difference in functional outcome scores for proximal humeral GCTBs compared with intralesional curettage. Therefore, we believe that rTSA with APC may be reasonable for the initial treatment of proximal humeral GCTBs.

Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

OBJECTIVES: The current study developed an ultrasound-based deep learning model to make preoperative differentiation among hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma (cHCC-ICC). METHODS: The B-mode ultrasound images of 465 patients with primary liver cancer were enrolled in model construction, comprising 264 HCCs, 105 ICCs, and 96 cHCC-ICCs, of which 50 cases were randomly selected to form an independent test cohort, and the rest of study population was assigned to a training and validation cohorts at the ratio of 4:1. Four deep learning models (Resnet18, MobileNet, DenseNet121, and Inception V3) were constructed, and the fivefold cross-validation was adopted to train and validate the performance of these models. The following indexes were calculated to determine the differential diagnosis performance of the models, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), F-1 score, and area under the receiver operating characteristic curve (AUC) based on images in the independent test cohort. RESULTS: Based on the fivefold cross-validation, the Resnet18 outperformed other models in terms of accuracy and robustness, with the overall training and validation accuracy as 99.73% (± 0.07%) and 99.35% (± 0.53%), respectively. Furthers validation based on the independent test cohort suggested that Resnet 18 yielded the best diagnostic performance in identifying HCC, ICC, and cHCC-ICC, with the sensitivity, specificity, accuracy, PPV, NPV, F1-score, and AUC of 84.59%, 92.65%, 86.00%, 85.82%, 92.99%, 92.37%, 85.07%, and 0.9237 (95% CI 0.8633, 0.9840). CONCLUSION: Ultrasound-based deep learning algorithm appeared a promising diagnostic method for identifying cHCC-ICC, HCC, and ICC, which might play a role in clinical decision making and evaluation of prognosis.

Serum-based Comprehensive N-Glycans Profiling Analysis in Different Gastric Disease Stages by Porous Graphitic Carbon Liquid Chromatography-Mass Spectrometry Associated With Potential Marker Discovery.

BACKGROUND/AIM: N-glycans are potential serum biomarkers due to their aberrant structure and abundance alteration during disease progression. Few studies have been associated with relative quantitative N-glycans profiling during different gastric disease stages. In this study, we conducted an investigation on the profiling of N-glycans in patients with gastric disease, as well as in healthy controls. MATERIALS AND METHODS: In this study, the porous graphitization carbon chromatography-high resolution Fourier transform mass spectrometry (PGC-FTMS) method was applied to assess comprehensive N-glycans profiling in patients at different stages of gastric disease, including gastritis, atrophic gastritis, gastric ulcer, gastric polyps, and gastric cancer. RESULTS: A total of 45 N-glycans (relative abundance >0.1%) were detected, and 9 N-glycans were found to be potential biomarkers for gastric disease detection. Along with the progression of gastric disease, the abundance of sialylated N-glycans increased, while that of core-fucosylated N-glycans decreased. Multivariate statistical analysis demonstrated that N-glycans profiling between gastritis and healthy controls had significant differences. The characteristic N-glycans distinguished gastric cancer from healthy controls, which had strong clinical diagnostic value. CONCLUSION: The relative quantitative profile of N-glycans in different gastric disease stages was revealed and serum N-glycans are proposed for distinguishing gastric disease stages in clinical application.

Assessing the structure and diversity of fungal community in plant soil under different climatic and vegetation conditions.

Introduction: Understanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province. Methods: A total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline. Results: Our data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. ß-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy. Discussion: Our findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors.

A novel antimicrobial peptide Scyreptin1-30 from Scylla paramamosain exhibiting potential therapy of Pseudomonas aeruginosa early infection in a mouse burn wound model.

Antimicrobial resistance (AMR) constitutes a significant global threat to human health. In recent years, there has been a concerning surge in infections caused by multidrug-resistant bacteria, highlighting the pressing need to urgently explore novel and effective alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) have emerged as a focal point of research, capturing significant attention as promising antimicrobial agents. In this study, we have identified a novel cationic antimicrobial peptide (AMP) named Scyreptin1-30, derived from the marine invertebrate Scylla paramamosain. The results showed that Scyreptin1-30 exhibits a broad-spectrum antimicrobial activity, demonstrating significant potency against both bacteria and fungi, and even against the clinically isolated multidrug-resistant bacteria Pseudomonas aeruginosa. Moreover, Scyreptin1-30 exhibited rapid bactericidal kinetic. The results of antibacterial mechanism showed that Scyreptin1-30 destroyed the integrity of bacterial membranes, leading to bacterial death and exhibited potent anti-biofilm activity against P. aeruginosa. The activity of Scyreptin1-30 against bacteria had a favorable thermal stability, displayed a certain ion tolerance, and showed no discernible cytotoxicity when assessed against both the mammalian cell line HEK293T and the fish cell lines ZF4. In an In vivo study, Scyreptin1-30 exhibited a remarkably reduction in the bacterial load caused by multidrug-resistant P. aeruginosa at the site of infection, and promoted wound healing in a mouse model of burn infection. This study indicated that Scyreptin1-30 holds promise as an effective antibacterial agent, potentially serving as a topical skin treatment against multidrug-resistant bacterial infections, including those caused by P. aeruginosa.

Switchable NaCl cages via a MWCNTs/Ni[Fe(CN)6]2 nanocomposite for high performance desalination.

With the application of nanomaterials in seawater desalination technology increasing, the adjustable characteristics of carbon-based nanomaterials make it possible to use multiwalled carbon nanotube (MWCNT) materials in seawater desalination technology. In this study, Ni[Fe(CN)6]2 is loaded onto the inner wall of MWCNTs by the co-precipitation method to prepare MWCNTs with variable pore size, making it a switchable cage for NaCl. During the procedure, most of the Ni[Fe(CN)6]2 is transferred to the outer surface of the MWCNTs after adsorption, and NaCl is stored inside the MWCNTs (which have been proved by characterization); at the same time, Ni can improve the cell stability of Ni[Fe(CN)6]2. The effect of adsorbent reaction time and addition amount on the desalination performance of MWCNTs/Ni[Fe(CN)6]2 has been tested. According to the results, the best desalination performance of MWCNTs/Ni[Fe(CN)6]2 is 1354.6 mg g-1 when the reaction time is 0.5 h and the addition amount is 20 mg. After 3 cycles of adsorption and desorption, its desalting performance decreased to 242.3 mg g-1.

Designing advanced S-scheme CdS QDs/La-Bi2WO6 photocatalysts for efficient degradation of RhB.

Finding effective strategies to design efficient photocatalysts and decompose refractory organic compounds in wastewater is a challenging problem. Herein, by coupling element doping and constructing heterostructures, S-scheme CdS QDs/La-Bi2WO6 (CS/LBWO) photocatalysts are designed and synthesized by a simple hydrothermal method. As a result, the RhB degradation efficiency of the optimized 5% CS/LBWO reached 99% within 70 min of illumination with excellent stability and recyclability. CS/LBWO shows improvement in the adsorption range of visible light and promotes electron-hole pair generation/migration/separation, attributing the superior degradation performance. The degradation RhB mechanism is proposed by a free radical capture experiment, electron paramagnetic resonance, and high-performance liquid chromatography-mass spectrometry results, indicating that h+ and •O2 - play a significant role during four degradation processes: de-ethylation, chromophore cleavage, ring opening, and mineralization. Based on in situ irradiated X-ray photoelectron spectroscopy, Mulliken electronegativity theory, and the work function results, the S-scheme heterojunction of CS/LBWO promotes the transfer of photogenerated electron-hole pairs and promotes the generation of reactive radicals. This work not only reports that 5% CS/LBWO is a promising photocatalyst for degradation experiments but also provides an approach to design advanced photocatalysts by coupling element doping and constructing heterostructures.

Design and Construction of Carbon-Coated Fe3 O4 /Cr2 O3 Heterostructures Nanoparticles as High-Performance Anodes for Lithium Storage.

Transition metal oxides, highly motivated anodes for lithium-ion batteries due to high theoretical capacity, typically afflict by inferior conductivity and significant volume variation. Architecting heterogeneous structures with distinctive interfacial features can effectively regulate the electronic structure to favor electrochemical properties. Herein, an engineered carbon-coated nanosized Fe3 O4 /Cr2 O3 heterostructure with multiple interfaces is synthesized by a facile sol-gel method and subsequent heat treatment. Such ingenious components and structural design deliver rapid Li+ migration and facilitate charge transfer at the heterogeneous interface. Simultaneously, the strong coupling synergistic interactions between Fe3 O4 , Cr2 O3 , and carbon layers establish multiple interface structures and built-in electric fields, which accelerate ion/electron transport and effectively eliminate volume expansion. As a result, the multi-interface heterostructure, as a lithium-ion battery anode, exhibits superior cycling stability maintaining a reversible capacity of 651.2 mAh g-1 for 600 cycles at 2 C. The density functionaltheory calculations not only unravel the electronic structure of the modulation but also illustrate favorable lithium-ion adsorption kinetics. This multi-interface heterostructure strategy offers a pathway for the development of advanced alkali metal-ion batteries.

Morphological and phylogenetic analyzes reveal two new species of Melanconiella from Fujian Province, China.

Introduction: Species of Melanconiella include a diverse array of plant pathogens as well as endophytic fungi. Members of this genus have been frequently collected from the family Betulaceae (birches) in Europe and North America. Little, however, if known concerning the distribution of Melanconiella and/or their potential as pathogens of other plant hosts. Methods: Fungi were noted and isolated from diseased leaves of Loropetalum chinense (Chinese fringe flower) and Camellia sinensis (tea) in Fujian Province, China. Genomic DNA was extracted from fungal isolates and the nucleotide sequences of four loci were determined and sued to construct phylogenetic trees. Morphological characteristics of fungal structures were determined via microscopic analyses. Results: Four strains and two new species of Melanconiella were isolated from infected leaves of L. chinense and C. sinensis in Fujian Province, China. Based on morphology and a multi-gene phylogeny of the internal transcribed spacer regions with the intervening 5.8S nrRNA gene (ITS), the 28S large subunit of nuclear ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF1-α), Melanconiellaloropetali sp. nov. and Melanconiellacamelliae sp. nov. were identified and described herein. Detailed descriptions, illustrations, and a key to the known species of Melanconiella are provided. Discussion: These data identify new species of Melanconiella, expanding the potential range and distribution of these dark septate fungi. The developed keys provide a reference source for further characterization of these fungi.

The overall and domain-specific quality of life of Chinese community-dwelling older adults: the role of intrinsic capacity and disease burden.

Objective: This study aimed to investigate the impact of the different domains of intrinsic capacity (IC) and chronic disease burden on health-related quality of life (HRQoL) and domain-specific HRQoL in Chinese community-dwelling older adults. Design: A cross-sectional observational study of a community-based cohort. Participants: We evaluated Chinese older adults (n = 429, mean age, 72.91 ± 7.014 years; female proportion, 57.30%). Measurements: IC contains five domains, namely locomotion, vitality, cognition, psychological, and sensory capacity. Locomotion dysfunction was defined as grip and/or gait decline. Vitality decline was defined if two of the following three parameters were present: fatigue, physical inactivity, and weight loss or overweight. Cognition was classified into normal cognition, pre-mild cognitive impairment (pre-MCI), and MCI according to the normative z-scores of the neuropsychological test battery. Psychological dysfunction was diagnosed based on depressive symptoms. Sensory dysfunction was defined as hearing and/or vision impairment. HRQoL was assessed using the AQoL-8D scale, which comprised physical (including independent living, senses, and pain) and psychosocial (including mental health, happiness, self-worth, coping, and relationships) dimensions. Low HRQoL (HRQoL score or subscores in the highest quintile) was used as a dependent variable in logistic regression analyses adjusted for demographic, health-related, and psychological confounders. Results: Sensory impairment was an independent determinant of senses, and locomotion impairment was significantly associated with overall HRQoL, independent living, and pain in the physical dimension of HRQoL. Cognition was an independent determinant of the senses. Vitality was independently associated with overall HRQoL, senses, and pain in the physical dimension and mental health and relationships in the psychological dimension of HRQoL. The psychological domain of IC was independently associated with overall and domain-specific HRQoL apart from senses after adjustment for all confounders. The number of multimorbidities mainly had a significant impact on independent living after adjustment for all confounders. Conclusion: IC domains and chronic disease burden had heterogeneous influences on overall and domain-specific HRQoL. The impairment of sensory and locomotion domains had a synergistic impact on the overall and physical dimensions of HRQoL. The vitality and psychological domains of IC had more profound effects on HRQoL. Older people with high morbidity might have a higher risk of poor independent living.

Engineering electronic structures and optical properties of a MoSi2N4 monolayer via modulating surface hydrogen chemisorption.

Recently, a MoSi2N4 monolayer has been successfully synthesized by a delicately designed chemical vapor deposition (CVD) method. It exhibits promising (opto)electronic properties due to a relatively narrow bandgap (∼1.94 eV), high electron/hole mobility, and excellent thermal/chemical stability. Currently, much effort is being devoted to further improving its properties through engineering defects or constructing nanocomposites (e.g., van der Waals heterostructures). Herein, we report a theoretical investigation on hydrogenation as an alternative surface functionalization approach to effectively manipulate its electronic structures and optical properties. The calculation results suggested that chemisorption of H atoms on the top of N atoms on MoSi2N4 was energetically most favored. Upon H chemisorption, the band gap values gradually decreased from 1.89 eV (for intrinsic MoSi2N4) to 0 eV (for MoSi2N4-16H) and 0.25 eV (for MoSi2N4-32H), respectively. The results of optical properties studies revealed that a noticeable enhancement in light absorption intensity could be realized in the visible light range after the surface hydrogenation process. Specifically, full-hydrogenated MoSi2N4 (MoSi2N4-32H) manifested a higher absorption coefficient than that of semi-hydrogenated MoSi2N4 (MoSi2N4-16H) in the visible light range. This work can provide theoretical guidance for rational engineering of optical and optoelectronic properties of MoSi2N4 monolayer materials via surface hydrogenation towards emerging applications in electronics, optoelectronics, photocatalysis, etc.