Construction of Highly Accurate Machine Learning Potential Energy Surfaces for Excited-State Dynamics Simulations Based on Low-Level Data Sets.

Machine learning is capable of effectively predicting the potential energies of molecules in the presence of high-quality data sets. Its application in the construction of ground- and excited-state potential energy surfaces is attractive to accelerate nonadiabatic molecular dynamics simulations of photochemical reactions. Because of the huge computational cost of excited-state electronic structure calculations, the construction of a high-quality data set becomes a bottleneck. In the present work, we first built two data sets. One was obtained from surface hopping dynamics simulations at the semiempirical OM2/MRCI level. Another was extracted from the dynamics trajectories at the CASSCF level, which was reported previously. The ground- and excited-state potential energy surfaces of ethylene-bridged azobenzene at the CASSCF computational level were constructed based on the former low-level data set. Although non-neural network machine learning methods can achieve good or modest performance during the training process, only neural network models provide reliable predictions on the latter external test data set. The BPNN and SchNet combined with the Δ-ML scheme and the force term in the loss functions are recommended for dynamics simulations. Then, we performed excited-state dynamics simulations of the photoisomerization of ethylene-bridged azobenzene on machine learning potential energy surfaces. Compared with the lifetimes of the first excited state (S1) estimated at different computational levels, our results on the E isomer are in good agreement with the high-level estimation. However, the overestimation of the Z isomer is unimproved. It suggests that smaller errors during the training process do not necessarily translate to more accurate predictions on high-level potential energies or better performance on nonadiabatic dynamics simulations, at least in the present case.

Suppressing Jahn-Teller distortion and locking lattice water with doped Fe(III) in birnessite toward fast and stable zinc-ion batteries.

Birnessite has been regarded as a promising cathode material for aqueous zinc-ion batteries (ZIBs), but severe Jahn-Teller distortion and abrupt lattice collapse at deep charged states lead to serious problems such as poor capacity retention and short cycle life, which severely impede its practical applications. We herein report the construction of an advanced layered Fe-doped Na0.55Mn2O4·xH2O (Fe-NMO·xH2O) cathode to promote zinc-ion storage performance and electrochemical stability. An outstanding capacity of 102 mA h g-1 at a high current density of 20 A g-1 and a long cycle life of 6000 cycles have been achieved, comparable to the state-of-the-art manganese oxide-based cathodes. Both experimental measurements and theoretical calculations reveal that Fe3+ substitution and lattice water cooperatively stabilize the interlayer structure, accelerate zinc-ion diffusion, and improve electronic conductivity. Notably, Fe doping is conducive to alleviating the Jahn-Teller effect and locking lattice water, which effectively prevents phase transformation and lattice collapse during the (de)intercalation process. This work sheds light on the synergistic interplay between dopants and structural water in zinc-ion storage and demonstrates instructive strategies to regulate layered structures for ZIBs.

[Spatio-temporal Evolution of Drought and Its Impact on Key Resources in the Important Ecological Functional Area: A Case Study in the Yellow River Basin].

This study explored the characteristics of spatial and temporal changes in drought in the Yellow River Basin from 2001 to 2020 based on TVPDI, surface runoff, vegetation net primary productivity, and grain yield data. Further, the effects of drought on water resources, grain resources, and vegetation resources were also analyzed using data spatialization methods, slope trend analysis, and Pearson correlation analysis. The results showed that:① The spatial distribution of drought in the Yellow River basin was stepped from southeast to northwest, and 60.6 % of the basin was in drought. The overall trend of drought in the basin was decreasing annually, and 94 % of the basin was gradually changing from drought to wet conditions, and the trend of drought from spring to winter decreased first and then increased. ② From the spatial and temporal changes in important resources in the basin, 53 % of the key surface runoff areas showed an increasing trend and were mainly located in the southwest of the basin; the net primary productivity (NPP) of vegetation and grain yield of food resources also showed an increasing trend. ③ Drought and the three types of resources showed significant spatial correlations, and the higher the degree of drought, the more significant the effects on surface runoff, vegetation productivity, and grain yield. However, the important resources in areas that had become wetter in recent years had not increased significantly, which indicated that the effects of drought on the three types of important resources had a time lag, and their lags had significant differences in spatial distribution and geographical differentiation patterns. This study has important theoretical implications for agricultural production, drought mitigation, and ecological conservation in the Yellow River Basin.

Antioxidative Potential and Ameliorative Effects of Rice Bran Fermented with Lactobacillus against High-Fat Diet-Induced Oxidative Stress in Mice.

Rice bran is an important byproduct of the rice polishing process, rich in nutrients, but it is underutilized and often used as feed or discarded, resulting in a huge amount of waste. In this study, rice bran was fermented by Lactobacillus fermentum MF423 to obtain a product with high antioxidant activity. First, a reliable and efficient method for assessing the antioxidant capacity of the fermentation products was established using high-performance liquid chromatography (HPLC), which ensured the consistency of the batch fermentation. The fermented rice bran product (FLRB) exhibited significant antioxidant activity in cells, C. elegans, and hyperlipidemic mice. Transcriptome analysis of mouse livers showed that the expression of plin5 was upregulated in diabetic mice administered FLRB, thereby preventing the excessive production of free fatty acids (FFAs) and the subsequent generation of large amounts of reactive oxygen species (ROS). These studies lay the foundation for the application of rice bran fermentation products.

Multi-fidelity machine learning for predicting bandgaps of nonlinear optical crystals.

Nonlinear optical (NLO) materials are of great importance in modern optics and industry because of their intrinsic capability of wavelength conversion. Bandgap is a key property of NLO crystals. In recent years, machine learning (ML) has become a powerful tool to predict the bandgaps of compounds before synthesis. However, the shortage of available experimental data of NLO crystals poses a significant challenge for the exploration of new NLO materials using ML. In this work, we proposed a new multi-fidelity ML approach based on the multilevel descriptors developed by us (Z.-Y. Zhang, X. Liu, L. Shen, L. Chen and W.-H. Fang, J. Phys. Chem. C, 2021, 125, 25175-25188) and the gradient boosting regression tree algorithm. The calculated and experimental bandgaps of NLO crystals were collected as the low- and high-fidelity labels, respectively. The experimental values were predicted based on chemical compositions of crystals without prior knowledge about crystal structures. The multi-fidelity ML model overcame the performance of single-fidelity predictor. Furthermore, it was observed that less accurate predictions on the low-fidelity label may result in more accurate prediction on the high-fidelity label, at least in the present case. Using the multi-fidelity ML model with the best performance in this work, the mean absolute error on the test set of experimental bandgaps was 0.293 eV, which is smaller than that using the single-fidelity model (0.355 eV). It is far from perfect but accurate enough as an effective computational tool in the first step to discover novel NLO materials.

Comparative molecular dynamics simulations provided insights into the mechanisms of cold-adaption of alginate lyases from the PL7 family.

Alginate is an important polysaccharide that is abundant in the marine environments, including the Polar Regions, and bacterial alginate lyases play key roles in its degradation. Many reported alginate lyases show characteristics of cold-adapted enzymes, including relatively low temperature optimum of activities (Topt) and low thermal stabilities. However, the cold-adaption mechanisms of alginate lyases remain unclear. Here, we studied the cold-adaptation mechanisms of alginate lyases by comparing four members of the PL7 family from different environments: AlyC3 from the Arctic ocean (Psychromonas sp. C-3), AlyA1 from the temperate ocean (Zobellia galactanivorans), PA1167 from the human pathogen (Pseudomonas aeruginosa PAO1), and AlyQ from the tropic ocean (Persicobacter sp. CCB-QB2). Sequence comparison and comparative molecular dynamics (MD) simulations revealed two main strategies of cold adaptation. First, the Arctic AlyC3 and temperate AlyA1 increased the flexibility of the loops close to the catalytic center by introducing insertions at these loops. Second, the Arctic AlyC3 increased the electrostatic attractions with the negatively charged substrate by introducing a high portion of positively charged lysine at three of the insertions mentioned above. Furthermore, our study also revealed that the root mean square fluctuation (RMSF) increased greatly when the temperature was increased to Topt or higher, suggesting the RMSF increase temperature as a potential indicator of the cold adaptation level of the PL7 family. This study provided new insights into the cold-adaptation mechanisms of bacterial alginate lyases and the marine carbon cycling at low temperatures.

Visual Cognitive Assessment Test: Utility of the brief cognitive battery for early screening of cognitive impairment in Chongqing, China.

OBJECTIVES: Early detection of cognitive impairment is essential for timely intervention. Currently, most widely used cognitive screening tests are influenced by language and cultural differences; therefore, there is a need for the development of a language-neutral, visual-based cognitive assessment tool. The Visual Cognitive Assessment Test (VCAT), a 30-point test that assesses memory, executive function, visuospatial function, attention, and language, has demonstrated its utility in a multilingual population. In this study, we evaluated the reliability, validity, and diagnostic performance of the VCAT for screening early cognitive impairment in Chongqing, China METHODS: A total of 134 individuals (49 healthy controls (HCs), 52 with mild cognitive impairment (MCI), and 33 with mild dementia) completed the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), VCAT, and domain-specific neuropsychological assessments. The diagnostic performances of MMSE, MoCA, and VCAT were evaluated using the area under the curve (AUC), sensitivity, and specificity. Construct validity of the VCAT was assessed with well-established domain-specific cognitive assessments. Reliability was measured using Cronbach's alpha. RESULTS: The VCAT and its subdomains demonstrated both good construct validity and internal consistency (α = 0.577). The performance of VCAT was comparable to that of MoCA and MMSE in differentiating mild dementia from nondemented groups (AUC: 0.940 vs. 0.902 and 0.977, respectively; p = .098 and .053) and in distinguishing cognitive impairment (CI) from HC (AUC: 0.929 vs. 0.899 and 0.891, respectively; p = .239 and .161), adjusted for education level. The optimal score range for VCAT in determining dementia, MCI, and HC was 0-14, 15-19, and 20-30, respectively. CONCLUSION: The VCAT proves to be a reliable screening test for early cognitive impairment within our cohort. Being both language and cultural neutral, the VCAT has the potential to be utilized among a wider population within China.

Improved YOLOv8 Model for Lightweight Pigeon Egg Detection.

In response to the high breakage rate of pigeon eggs and the significant labor costs associated with egg-producing pigeon farming, this study proposes an improved YOLOv8-PG (real versus fake pigeon egg detection) model based on YOLOv8n. Specifically, the Bottleneck in the C2f module of the YOLOv8n backbone network and neck network are replaced with Fasternet-EMA Block and Fasternet Block, respectively. The Fasternet Block is designed based on PConv (Partial Convolution) to reduce model parameter count and computational load efficiently. Furthermore, the incorporation of the EMA (Efficient Multi-scale Attention) mechanism helps mitigate interference from complex environments on pigeon-egg feature-extraction capabilities. Additionally, Dysample, an ultra-lightweight and effective upsampler, is introduced into the neck network to further enhance performance with lower computational overhead. Finally, the EXPMA (exponential moving average) concept is employed to optimize the SlideLoss and propose the EMASlideLoss classification loss function, addressing the issue of imbalanced data samples and enhancing the model's robustness. The experimental results showed that the F1-score, mAP50-95, and mAP75 of YOLOv8-PG increased by 0.76%, 1.56%, and 4.45%, respectively, compared with the baseline YOLOv8n model. Moreover, the model's parameter count and computational load are reduced by 24.69% and 22.89%, respectively. Compared to detection models such as Faster R-CNN, YOLOv5s, YOLOv7, and YOLOv8s, YOLOv8-PG exhibits superior performance. Additionally, the reduction in parameter count and computational load contributes to lowering the model deployment costs and facilitates its implementation on mobile robotic platforms.

Annotation of 2,507 Saccharomyces cerevisiae genomes.

Saccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Currently, a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain. However, these genomes are distributed at different websites and a large number of them are released without annotation information. To provide one complete annotated genome data resource, we collected 2,507 Saccharomyces cerevisiae genome assemblies and re-annotated 2,506 assemblies using a custom annotation pipeline, producing a total of 15,407,164 protein-coding gene models. With a custom pipeline, all these gene sequences were clustered into families. A total of 1,506 single-copy genes were selected as marker genes, which were then used to evaluate the genome completeness and base qualities of all assemblies. Pangenomic analyses were performed based on a selected subset of 847 medium-high-quality genomes. Statistical comparisons revealed a number of gene families showing copy number variations among different organism sources. To the authors' knowledge, this study represents the largest genome annotation project of S. cerevisiae so far, providing rich genomic resources for the future studies of the model organism S. cerevisiae and its relatives.IMPORTANCESaccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Though a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain, these genomes are distributed at different websites and most are released without annotation, hindering the efficient reuse of these genome resources. Here, we collected 2,507 genomes for Saccharomyces cerevisiae, performed genome annotation, and evaluated the genome qualities. All the obtained data have been deposited at public repositories and are freely accessible to the community. This study represents the largest genome annotation project of S. cerevisiae so far, providing one complete annotated genome data set for S. cerevisiae, an important workhorse for fundamental biology, biotechnology, and industry.

Unraveling the atmospheric oxidation mechanism and kinetics of naphthalene: Insights from theoretical exploration.

Naphthalene, the most abundant polycyclic aromatic hydrocarbon in the atmosphere, significantly influences OH consumption and secondary organic aerosol (SOA) formation. Naphthoquinone (NQ) is a significant contributor to ring-retaining SOA from naphthalene degradation, impacting the redox properties and toxicity of ambient particles. However, inconsistencies persist regarding concentrations of its isomers, 1,2-NQ and 1,4-NQ. In present work, our theoretical investigation into naphthalene's reaction with OH and subsequent oxygenation unveils their role in SOA formation. The reaction kinetics of initial OH and subsequent O2 oxidation was extensively studied using high-level quantum chemical methods (DLPNO-CCSD(T)/aug-ccpVQZ//M052x-D3/6-311++G(d,p)) combined with RRKM/master equation simulations. The reactions mainly proceed through electrophilic addition and abstraction from the aromatic ring. The total rate coefficient of naphthalene + OH at 300 K and 1 atm from our calculation (7.2 × 10-12 cm3 molecule-1 s-1) agrees well with previous measurements (∼1 × 10-11 cm3 molecule-1 s-1). The computed branching ratios facilitate accurate product yield determination. The largest yield of 1-hydroxynaphthalen-1-yl radical (add1) producing the major precursor of RO2 is computed to be 93.8 % in the ambient environment. Our calculated total rate coefficient (5.2 × 10-16 cm3 molecule-1 s-1) for add1 + O2 closely matches that of limited experimental data (8.0 × 10-16 cm3 molecule-1 s-1). Peroxy radicals (RO2) generated from add1 + O2 include 4-cis/trans-(1-hydroxynaphthalen-1-yl)-peroxy radical (add1-4OOadd-cis/trans, 66.0 %/17.5 %), 2-cis/trans-(1-hydroxynaphthalen-1-yl)-peroxy radical (add1-2OOadd-cis/trans, 10.3 %/6.3 %). Regarding the debated predominance of 1,4-NQ (corresponding to the parent RO2, i.e., add1-4OOadd-cis/trans) and 1,2-NQ (corresponding to the parent RO2, i.e., add1-2OOadd-cis/trans) in the atmosphere, our findings substantiate the dominance of 1,4-NQ. This study also indicates potential weakening of 1,4-NQ's dominance due to competition from decomposition reactions of add1-4OOadd-cis/trans and add1-2OOadd-cis/trans. Precise reaction kinetics data are essential for characterizing SOA transformation derived from naphthalene and assessing their climatic impacts within modeling frameworks.

Carbon emission change based on land use in Gansu Province.

Carbon emissions from land use change have become one of the main sources of regional carbon emissions. In order to explore the changes, 87 districts and counties in Gansu Province are taken as research objects. Based on the remote sensing data and statistical data of land use, the carbon emission coefficient method was used to investigate the spatial characteristics of land use carbon emission of each district and county in Gansu Province in recent 20 years from the perspective of carbon ecological support coefficient and per capita carbon footprint. The main results are as follows: (1) the growth of land use carbon emissions in Gansu Province from 2000 to 2020 was significant, but the growth of carbon emissions after 2010 was fast, and the growth of carbon sinks was relatively slow. (2) The ecological support coefficient of carbon emissions at county level in Gansu Province showed a trend of high in the south and low in the north, high in the east and low in the west, and this trend became more and more obvious with the passage of time. (3) Based on carbon emission, county population, and carbon ecological support capacity, the per capita carbon footprint of each county in Gansu Province was analyzed. The results showed that the per capita carbon footprint in Gansu Province was increasing, indicating that the gap between carbon emission and carbon absorption in each county was widening. By the above result, the author divides the counties of Gansu Province into three regions, low-carbon maintenance area, green development area, and ecological optimization area, and puts forward development suggestions for different regions, respectively. Therefore, this paper can also provide a theoretical reference for the formulation of carbon neutral planning measures in inland northwest China.

Characteristics of carbon budget based on energy carbon emissions and vegetation carbon absorption.

How to evaluate the change characteristics of energy carbon emissions (ECE) and vegetation carbon absorption (VCA) by scientific methods is particularly important for achieving carbon peak by 2030 and carbon neutrality by 2060. Based on provincial-level energy consumption data, nighttime light data, and population data, this study realized spatial simulation of energy carbon emissions and analyzed the change characteristics of energy carbon emissions (ECE) and vegetation carbon absorption (VCA) combined with the net primary productivity (NPP)of vegetation. Besides, the relationship between energy carbon emissions, vegetation carbon absorption, and economic development was also analyzed at an urban scale. The results showed that (1) the total ECE increased from 4.34 billion tons in 2000 to 14.43 billion tons in 2019, but the growth rate of ECE decreased from 15.9% during 2000-2010 to 3.1% during 2010-2019. The VCA capacity has been increasing year by year. In 2019, it could absorb 1.56 billion tons more carbon dioxide than in 2000 with an increase of 16.1%. (2) Through the identification of the increasing and decreasing regions of ECE and VCA, it was found that the continuous rise area of ECE accounts for 0.5% of the study area; the area of fluctuating rise accounted for 6.7% of the study area. The area of continuous decline of VCA accounted for 0.2% of the study area; the area of fluctuating decline accounted for 49.6% of the study area. (3) The eastern China accounted for 42% of ECE and 17% of VCA with 11.4% of land, while the western region accounted for 26% of ECE and 55% of VCA with 66.6% of land, which indicated that there were significant differences in the characteristics of carbon budget between the eastern China and the western region. (4) The carbon pressure index (CPI) of most cities was on the rise, but the carbon efficiency index (CEI) was also on the rise, and cities were developing towards the model of low energy consumption and high output value. In a word, the growth rate of ECE is slowing down, and the VCA capacity is increasing. In the process of promoting carbon neutrality, we should be aware of the different resource endowments of different regions, realize the actual role of each region in carbon neutrality and economic development, and allocate carbon neutrality tasks differently.

A comprehensive drought index based on spatial principal component analysis and its application in northern China.

In the background of the greenhouse effect, drought events occurred more frequently. How to monitor drought events scientifically and efficiently is very urgent at present. In this study, we employed the Vegetation Water Supply Index (VSWI), Temperature Vegetation Drought Index (TVDI), and Crop Water Stress Index (CWSI) as individual variables to construct a composite drought index (CDI) using spatial principal component analysis (SPCA). The validity of CDI was assessed using gross primary productivity (GPP), soil moisture (SM), Standardized Precipitation Evapotranspiration Index (SPEI), and Vegetation Condition Index (VCI). CDI was subsequently used for drought monitoring in northern China from 2011 to 2020. The results showed that (1) at a 99% confidence level, the Pearson correlation coefficients between CDI and GPP was 0.72, while the value between CDI and SM was 0.69, which indicated the relationship between SM, GPP, and CDI was significant. (2) We compared CDI with other variables such as Standardized Precipitation Evapotranspiration Index (SPEI) and Crop Drought Index (CDI) and found that the monitoring result of CDI was more sensitive, which indicated that the proposed CDI had a better effect in local drought monitoring. (3) The results of CDI showed that the drought status in the northern region during 2011-2020 lasted from March to October, and the high severe drought period generally occurs in March-May and September-October, with low severe drought in June-August.

Mechanistic photophysics of tellurium-substituted cytosine: Electronic structure calculations and nonadiabatic dynamics simulations.

Previously, the MS-CASPT2 method was performed to study the static and qualitative photophysics of tellurium-substituted cytosine (TeC). To get quantitative information, we used our recently developed QTMF-FSSH dynamics method to simulate the excited-state decay of TeC. The CASSCF method was adopted to reduce the calculation costs, which was confirmed to provide reliable structures and energies as those of MS-CASPT2. A detailed structural analysis showed that only 5% trajectories will hop to the lower triplet or singlet state via the twisted (S2 /S1 /T2 )T intersection, while 67% trajectories will choose the planar intersections of (S2 /S1 /T3 /T2 /T1 )P and (S2 /S1 /T2 /T1 )P but subsequently become twisted in other electronic states. By contrast, ~28% trajectories will maintain in a plane throughout dynamics. Electronic population revealed that the S2 population will ultrafast transfer to the lower triplet or singlet state. Later, the TeC system will populate in the spin-mixed electronic states composed of S1 , T1 and T2 . At the end of 300 fs, most trajectories (~74%) will decay to the ground state and only 17.4% will survive in the triplet states. Our dynamics simulation verified that tellurium substitution will enhance the intersystem crossings, but the very short triplet lifetime (ca. 125 fs) will make TeC a less effective photosensitizer.

Genetic effect of metformin use on risk of cancers: evidence from Mendelian randomization analysis.

BACKGROUND: Increasing number of studies reported the positive effect of metformin on the prevention and treatment of cancers. However, the genetic causal effect of metformin utilization on the risk of common cancers was not completely demonstrated. METHODS: Two-sample Mendelian Randomization (two-sample MR) analysis was conducted to uncover the genetically predicted causal association between metformin use and 26 kinds of cancers. Besides, two-step Mendelian Randomization (two-step MR) assessment was applied to clarify the mediators which mediated the causal effect of metformin on certain cancer. We utilized five robust analytical methods, in which the inverse variance weighting (IVW) method served as the major one. Sensitivity, pleiotropy, and heterogeneity were assessed. The genetic statistics of exposure, outcomes, and mediators were downloaded from publicly available datasets, including the Open Genome-Wide Association Study (GWAS), FinnGen consortium (FinnGen), and UK Biobank (UKB). RESULTS: Among 26 kinds of common cancers, HER-positive breast cancer was presented with a significant causal relationship with metformin use [Beta: - 4.0982; OR: 0.0166 (95% CI: 0.0008, 0.3376); P value: 0.0077], which indicated metformin could prevent people from HER-positive breast cancer. Other cancers only showed modest associations with metformin use. Potential mediators were included in two-step MR, among which total testosterone levels (mediating effect: 24.52%) displayed significant mediating roles. Leave-one-out, MR-Egger, and MR-PRESSO analyses produced consistent outcomes. CONCLUSION: Metformin use exhibited a genetically protective effect on HER-positive breast cancer, which was partially mediated by total testosterone levels.

Insights into the composition and assembly mechanism of microbial communities on intertidal microsand grains.

Introduction: Marine microorganisms are essential in marine ecosystems and have always been of interest. Currently, most marine microbial communities are studied at the bulk scale (millimeters to centimeters), and the composition, function and underlying assembly mechanism of microbial communities at the microscale (sub-100 micrometers) are unclear. Methods: The microbial communities on microsand grains (40-100 µm, n = 150) from marine sediment were investigated and compared with those on macrosand grains (400-1000 µm, n = 60) and bulk sediments (n = 5) using amplicon sequencing technology. Results: The results revealed a significant difference between microsand grains and macrosand grains. Microsand grains had lower numbers of operational taxonomic units (OTUs(97%)) and predicted functional genes than macrosand grains and bulk-scale samples. Microsand grains also showed greater intersample differences in the community composition and predicted functional genes than macrosand grains, suggesting a high level of heterogeneity of microbial communities at the microscale. Analyses based on ecological models indicated that stochastic processes dominated the assembly of microbial communities on sand grains. Consistently, cooccurrence network analyses showed that most microbial cooccurrence associations on sand grains were highly unstable. Metagenomic sequencing and further genome-scale metabolic modeling revealed that only a small number (1.3%) of microbe pairs showed high cooperative potential. Discussion: This study explored the microbial community of marine sediments at the sub-100 µm scale, broadening the knowledge of the structure and assembly mechanism of marine microbial communities.

Enrichment Pretreatment Expands the Microbial Diversity Cultivated from Marine Sediments.

The majority of the microbial diversity in nature has not been recovered through cultivation. Enrichment is a classical technique widely used in the selective cultivation of specific taxa. Whether enrichment is suitable for cultivation studies that aim to recover large numbers of species remains little explored. To address this issue, we evaluated the potential of enrichment pretreatment in the cultivation of bacteria from marine sediments. Upon obtaining and classifying a total of 943 pure cultures from chitin and cellulose enrichment pretreatment systems and a control system, our results showed that species obtained using enrichment pretreatment differed greatly from those without enrichment. Multiple enrichment media and different enrichment times increased the number of cultivated species in a sample. Amplicon sequencing showed that the increased relative abundance during pretreatment contributed greatly to bacterial cultivation. The testing of degradation abilities against chitin and cellulose and the whole-genome sequencing of representative strains suggested that microorganism-microorganism interactions play roles in the expanded diversity of cultivated bacteria. This study provides new insights into the abilities of enrichment in exploring cultivable diversity and mining microbial resources.

Quantum mechanics/molecular mechanics studies on the excited-state decay mechanisms of cytidine aza-analogues: 5-azacytidine and 2'-deoxy-5-azacytidine in aqueous solution.

The excited state properties and deactivation pathways of two DNA methylation inhibitors, i.e., 5-azacytidine (5ACyd) and 2'-deoxy-5-azacytidine (5AdCyd) in aqueous solution, are comprehensively explored with the QM(CASPT2//CASSCF)/MM protocol. We systematically map the feasible decay mechanisms based on the obtained excited-state decay paths involving all the identified minimum-energy structures, conical intersections, and crossing points driving the different internal conversion (IC) and intersystem crossing (ISC) routes in and between the 1ππ*, 1nπ*, 3ππ*, 3nπ*, and S0 states. Unlike the 1nπ* state below the 1ππ* state in 5ACyd, deoxyribose group substitution at the N1 position leads to the 1ππ* state becoming the S1 state in 5AdCyd. In 5ACyd and 5AdCyd, the initially populated 1ππ* state mainly deactivates to the S0 state through the direct 1ππ* → S0 IC or mediated by the 1nπ* state. The former nearly barrierless IC channel of 1ππ* → S0 occurs ultrafast via the nearby low-lying 1ππ*/S0 conical intersection. In the latter IC channel of 1ππ* → 1nπ* → S0, the initially photoexcited 1ππ* state first approaches the nearby S2/S1 conical section 1ππ*/1nπ* and then undergoes efficient IC to the 1nπ* state, followed by the further IC to the initial S0 state via the S1/S0 conical intersection 1nπ*/S0. The 1nπ*/S0 conical intersection is estimated to be located 6.0 and 4.9 kcal mol-1 above the 1nπ* state minimum in 5ACyd and 5AdCyd, respectively, at the QM(CASPT2)/MM level. In addition to the efficient singlet-mediated IC channels, the minor ISC routes would populate 1ππ* to T1(ππ*) through 1ππ* → T1 or 1ππ* → 1nπ* → T1. Relatively, the 1ππ* → 1nπ* → T1 route benefits from the spin-orbit coupling (SOC) of 1nπ*/3ππ* of 8.7 cm-1 in 5ACyd and 10.2 cm-1 in 5AdCyd, respectively. Subsequently, the T1 system will approach the nearby T1/S0 crossing point 3ππ*/S0 driving it back to the S0 state. Given the 3ππ*/S0 crossing point located above the T1 minimum and the small T1/S0 SOC, i.e., 8.4 kcal mol-1 and 2.1 cm-1 in 5ACyd and 6.8 kcal mol-1 and 1.9 cm-1 in 5AdCyd, respectively, the slow T1 → S0 would trap the system in the T1 state for a while. The present work could contribute to understanding the mechanistic photophysics and photochemistry of similar aza-nucleosides and their derivatives.

Improved Interfacial Ion Migration and Deposition through the Chain-Liquid Synergistic Effect by a Carboxylated Hydrogel Electrolyte for Stable Zinc Metal Anodes.

The large-scale applicability of Zn-metal anodes is severely impeded by the issues such as the dendrite growth, complicated hydrogen evolution, and uncontrollable passivation reaction. Herein, a negatively charged carboxylated double-network hydrogel electrolyte (Gelatin/Sodium alginate-acetate, denoted as Gel/SA-acetate) has been developed to stabilize the interfacial electrochemistry, which restructures a type of Zn2+ ion solvent sheath optimized via a chain-liquid synergistic effect. New hydrogen bonds are reconstructed with water molecules by the zincophilic functional groups, and directional migration of hydrated Zn2+ ions is therefore induced. Concomitantly, the robust chemical bonding of such hydrogel layers to the Zn slab exhibits a desirable anti-catalytic effect, thereby greatly diminishing the water activity and eliminating side reactions. Subsequently, a symmetric cell using the Gel/SA-acetate electrolyte demonstrates a reversible plating/stripping performance for 1580 h, and an asymmetric cell reaches a state-of-the-art runtime of 5600 h with a high average Coulombic efficiency of 99.9 %. The resultant zinc ion hybrid capacitors deliver exceptional properties including the capacity retention of 98.5 % over 15000 cycles, energy density of 236.8 Wh kg-1 , and high mechanical adaptability. This work is expected to pave a new avenue for the development of novel hydrogel electrolytes towards safe and stable Zn anodes.

Optimal allocation for land in an arid inland basin in northwest China: framework and application based on CLUE-S and MCR models.

Reasonable planning of the limited land resources can promote the coordinated development of social economic and ecological protection. It is very important to optimize the rational distribution of land resources in the arid inland river basin because of the scarce land. In this paper, the GIS technologies of spatial analysis, conversion of land use, and its effects at small regional extent (CLUE-S) and minimum cumulative resistance (MCR) model were used to optimize the land allocation. The ecological security pattern (ESP) was constructed through using MCR model, which included ecological source and resistance surface. The dynamics of land use and spatial optimizing allocation of Shiyang River Basin in 2025 and 2030 was simulated under three different optimization scenarios including farmland protection scenario (FPS), free development scenario (FDS), and ecological security pattern scenario (ESPS). It was found that under ESPS, farmland was reduced, but woodland, grassland, and water body were increased significantly. Under FPS, land for construction was controlled effectively, a large part of homestead was converted into farmland, and the potential of unused land was developed vigorously. Furthermore, the current FDS and macro policy guidance should be comprehensively considered. The ESPS was more suitable for the scientific development of Shiyang River Basin on a long view. The combination of CLUE-S and MCR can effectively improve the optimization methods under ecological process and ecological resistance of landscape elements.