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Abstract Background Anaesthetic methods and drugs with rapid onset, rapid recovery and better postoperative analgesia are more suitable for rapid recovery in obstetric anaesthesia. We formulated the following hypothesis: a combination of mepivacaine and ropivacaine could provide a longer analgesic effect and have more advantages in terms of rapid-recovery indicators. Methods A total of 180 pregnant women scheduled to undergo elective caesarean sections were randomly assigned to three surgical groups, which received 2% mepivacaine (Group M), 2% mepivacaine + 0.75% ropivacaine (Group MR) (Volume 1:1) or 0.75% ropivacaine (Group R) through an epidural catheter. The situation of postoperative analgesia and other indicators of rapid recovery were recorded. Results One hundred and fifty patients were included in the final analysis. Their demographic data were similar. The visual analogue scale (VAS) scores of Group MR and Group R were lower than Group M at 1 and 2 h after surgery both at rest and with movement (P

Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD). Methods: We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature. Results: A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group. Conclusion: Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

Abstract GEnome-scale Metabolic models (GEMs) are powerful tools to predict cellular metabolism and physiological states in living organisms. However, due to our imperfect knowledge of metabolic processes, even highly curated GEMs have knowledge gaps (e.g., missing reactions). Existing gap-filling methods typically require phenotypic data as input to tease out missing reactions. We still lack a computational method for rapid and accurate gap-filling of metabolic networks before experimental data is available. Here we present a deep learning-based method — CHEbyshev Spectral HyperlInk pREdictor (CHESHIRE) — to predict missing reactions in GEMs purely from metabolic network topology. We demonstrate that CHESHIRE outperforms other topology-based methods in predicting artificially removed reactions over 926 high- and intermediate-quality GEMs. Furthermore, CHESHIRE is able to improve the phenotypic predictions of 49 draft GEMs for fermentation products and amino acids secretions. Both types of validation suggest that CHESHIRE is a powerful tool for GEM curation to reveal unknown links between reactions and observed metabolic phenotypes.

Abstract Background Previous studies have demonstrated an association between male sperm quality and assisted reproduction outcomes, focusing on the effects of individual parameters and reaching controversial conclusions. The WHO 6th edition manual highlights a new semen assay, the sperm DNA fragmentation index, for use after routine semen examination. However, the combined effect of the sperm DNA fragmentation index (DFI) and routine semen parameters remains largely unknown. Methods We assessed the combined effect of the sperm DFI and conventional semen parameters on single fresh conventional IVF outcomes for infertile couples from January 1, 2017, to December 31, 2020. IVF outcomes were obtained from the cohort database follow-up records of the Clinical Reproductive Medicine Management System of the Third Affiliated Hospital of Guangzhou Medical University. An unsupervised K-means clustering method was applied to classify participants into several coexposure pattern groups. A multivariate logistic regression model was used for statistical analysis. Results A total of 549 live births among 1258 couples occurred during the follow-up period. A linear exposure–response relationship was observed among the sperm DFI, sperm motility, and IVF outcomes. In multivariable adjustment, increased sperm DFI values and decreased sperm motility and semen concentration levels were associated with reduced odds of favourable IVF outcomes. Four coexposure patterns were generated based on the sperm DFI and the studied semen parameters, as follows: Cluster 1 (low sperm DFI values and high sperm motility and semen concentration levels), Cluster 2 (low sperm DFI values and moderate sperm motility and semen concentration levels), Cluster 3 (low sperm DFI values and low sperm motility and semen concentration levels) and Cluster 4 (high sperm DFI values and low sperm motility and semen concentration levels). Compared with those in Cluster 1, participants in Cluster 3 and Cluster 4 had lower odds of a live birth outcome, with odds ratios (95% confidence intervals [CIs]) of 0.733 (0.537, 0.998) and 0.620 (0.394, 0.967), respectively. Conclusions When combined with low sperm DFI values, there was no significant difference between high or moderate sperm concentration and motility levels, and both were associated with favourable IVF outcomes. Low sperm parameter levels, even when DFI values remain low, may still lead to poor IVF outcomes. Participants with high sperm DFI values and low sperm motility and semen concentration levels had the worst outcomes. Our findings offer a novel perspective for exploring the joint effects of sperm DFI and routine semen parameter values.

Constructing a Z-scheme heterostructure is of great significance to achieve efficient photocatalytic CO2 conversion without sacrificial reagents. However, the fabrication of a well-suited Z-scheme remains a challenge. In this work, we constructed a Z-scheme system with a suitable band structure by in-situ hydrothermal growth of In2S3 nanosheets on electrospun Fe3C/Carbon fibers with 3D structure. The Z-scheme electron transport path is verified by the calculation of the energy band structure calculation and the method of photodeposition, indicating that In2S3 and Fe3C are reduction reaction sites and oxidation reaction sites respectively. Carbon fibers serve as both the skeleton of the 3D structure and the electron mediator from Fe3C to In2S3. Moreover, the DFT calculation demonstrates that the introduction of Fe3C can reduce the energy barrier of *CO and *COH coupling on In2S3, and weaken the bonding of In-S, thereby enhancing the product selectivity towards acetate. Owing to the efficient charge transfer of the Z-scheme system, the photocorrosion in In2S3 is also greatly reduced, showing a relatively stable chemical composition after several hours of reaction. Compared with In2S3 and Fe3C/C, In2S3-C/Fe3C composites showed a significantly increased acetate evolution rate of 11.33 μmol/h/g without any sacrificial reagents. This work provides important insights into the design and research of the photocatalyst system that combines a monolithic 3D structure and a Z-scheme charge flow for efficient CO2 conversion.

Colloidal semiconductor nanocrystals have attracted widespread attention due to their tremendous electrical and optical properties. Nanoparticles exhibit a strong tendency to aggregate and sinter in a short period of time during processing or use due to their large surface area-to-volume ratio, which may lead to significant changes in their required performance. Therefore, it is of great significance to conduct in-depth research on the sintering process and mechanism of nanoparticles to maintain their stability. Here, the sintering process of CdSe/CdS core/shell nanocrystals under continuous electron beam irradiation was studied using in situ transmission electron microscopy (TEM). In the early stages of sintering, CdSe/CdS nanocrystals approached each other at a distance of approximately 1–2 nm. As the exposure time to the electron beam increased, the movement of surface atoms on the nanocrystals led to contact between them. Subsequently, the atoms on the contact surfaces underwent rapid motion, resulting in the rapid formation of the neck between the particles. The neck formation between adjacent particles provides strong evidence of a sintering mechanism dominated by surface atom diffusion rather than Ostwald ripening. Further research in this area could lead to the development of improved methods to prevent sintering and enhance the stability of nanocrystals, ultimately contributing to the advancement of nanomaterial-based devices and materials with long-lasting performance.

Measurement(s) Metagenomics Technology Type(s) next generation DNA sequencing Sample Characteristic - Organism Bacteria Sample Characteristic - Environment gut microbiome Sample Characteristic - Location New York City

Abstract Background Microdissection testicular sperm extraction (micro-TESE) in combination with ICSI can make paternity possible for non-obstructive azoospermia (NOA) patients. Testicular sperm can be successfully retrieved in nearly half of NOA patients. Nevertheless, not many convincing protocols are established to improve sperm retrieval rate (SRR). The goal of this study was to evaluate whether gonadotropins therapy before micro-TESE could improve sperm retrieval rate and affect the ICSI outcomes in non-obstructive azoospermia patients with hypergonadotropic hypogonadism. Methods This retrospective cohort study included a total of 569 non-obstructive azoospermia men who underwent micro-TESE with or without 3-month of preoperative hCG / hCG plus highly purified urinary FSH (uFSH) between January 2016 and December 2019. The primary outcome was the sperm retrieval rate of micro-TESE. Results Sperm was found in 27 patients among 395 NOA men who accepted preoperative gonadotropins treatment (6.8%, 27/395) in post-treatment semen analysis for ICSI. One hundred forty nine out of 542 patients could successfully obtain enough sperm for ICSI through the micro-TESE (overall SRR = 27.5%). There was a statistically significant difference in the SRR between the preoperative gonadotropins treatment and non-gonadotropins treatment groups (31.2%, 115/368 vs. 19.5%, 34/174, P = 0.006). In the multivariable analysis with IPTW according to the propensity score, there was a significant association between preoperative gonadotropins treatment and the SRR (OR, 1.59; 95% CI: 1.02–2.52; P = 0.042). No differences in the clinical pregnancy rate, live birth delivery rate, or miscarriage rate were observed between the two groups. Conclusion Preoperative gonadotropins therapy seems to have a role in improving SRR in NOA patients with hypergonadotropic hypogonadism. We found that gonadotropins therapy had no effect on ICSI clinical outcomes and live birth.

Regarding the interpretable techniques in the field of image recognition, Grad-CAM is widely used for feature localization in images to reflect the logical decision-making information behind the neural network due to its high applicability. However, extensive experimentation on a customized dataset revealed that the deep convolutional neural network (CNN) model based on Gradient-weighted Class Activation Mapping (Grad-CAM) technology cannot effectively resist the interference of large-scale noise. In this article, an optimization of the deep CNN model was proposed by incorporating the Dropkey and Dropout (as a comparison) algorithm. Compared with Grad-CAM, the improved Grad-CAM based on Dropkey applies an attention mechanism to the feature map before calculating the gradient, which can introduce randomness and eliminate some areas by applying a mask to the attention score. Experimental results show that the optimized Grad-CAM deep CNN model based on the Dropkey algorithm can effectively resist large-scale noise interference and achieve accurate localization of image features. For instance, under the interference of a noise variance of 0.6, the Dropkey-enhanced ResNet50 model achieves a confidence level of 0.878 in predicting results, while the other two models exhibit confidence levels of 0.766 and 0.481, respectively. Moreover, it exhibits excellent performance in visualizing tasks related to image features such as distortion, low contrast, and small object characteristics. Furthermore, it has promising prospects in practical computer vision applications. For instance, in the field of autonomous driving, it can assist in verifying whether deep learning models accurately understand and process crucial objects, road signs, pedestrians, or other elements in the environment.

The aldose reductase inhibitor Fidarestat has been noted to have efficacy in treating a variety of tumors. To define its role in hepatocellular carcinoma (HCC), we induced a HCC xenograft model in mice, which were treated with different doses of Fidarestat. The amounts of natural killer (NK) cells and related inflammatory factors were detected in the serum of the mice. Fidarestat inhibited HCC tumor growth and lung metastasis in vivo and increased NK cell number as well as levels of NK cell-related inflammatory factors in mouse serum. NK cells were then co-cultured with the HCC cell line in vitro to detect effects on HCC cell progression after Fidarestat administration. The glycolysis activity of the NK cells was evaluated by extracellular acidification rate, while aldo-keto reductase family 1 member B10 (AKR1B10) expression was detected by western blot analysis. Administration of Fidarestat downregulated the expression of AKR1B10 in NK cells and promoted NK cell glycolysis to enhance their killing activity against HCC cells. However, depletion of NK cells or upregulation of AKR1B10 attenuated the anticancer activity of Fidarestat. Taken together, Fidarestat downregulated AKR1B10 expression in NK cells to promote NK cell glycolysis, thereby alleviating HCC progression.

ObjectiveMirror movements (MMs) are common abnormal motor performance in patients with poststroke hemiparesis. The study aimed to utilize the Electromyography (EMG) characterization of MMs in stroke patients and explore the relationship between MMs and the motor function of affected limbs.MethodsSixty patients with stroke who had used to undergo clinical assessment and surface Electromyography (sEMG) were selected in this study. We investigated the standardized net excitation (SNE) and overflow percentage (OF) as a measure of mirror activities on bilateral muscles of stroke patients.ResultsIn stroke patients, mirror activities occurred in both affected and unaffected muscles during maximal contractions. We found that OF at unilateral contraction on the affected side (UCA) was significantly greater than that at unilateral contraction on the unaffected side (UCU). Additionally, a negative correlation between OF at UCA and Brunnstrom stages on admission and discharge. However, there were no significant correlations between OF and disease duration, Barthel Index, or the degree of improvement in all clinical evaluations. We still found a positive correlation between SNE at UCA and the improvement of the Brunnstrom stage of the hand. But we could not find any significant correlation between SNE and other clinical evaluation scores.ConclusionIn conclusion, the study found mirror activities in both affected and unaffected muscles, confirming an asymmetry between them. Although the mechanisms are still unclear, we confirmed a significant correlation between MMs at UCA and the motor function of the affected upper extremity, which might provide further evidences for understanding MMs in stroke patients and a new research direction on evaluation for motor function and outcomes of stroke patients.

Microbes have disproportionate impacts on the macroscopic world. This is in part due to their ability to grow to large populations that collectively secrete massive amounts of secondary metabolites and alter their environment. Yet, the conditions favoring secondary metabolism despite the potential costs for primary metabolism remain unclear. Here we investigated the biosurfactants that the bacterium Pseudomonas aeruginosa makes and secretes to decrease the surface tension of surrounding liquid. Using a combination of genomics, metabolomics, transcriptomics, and mathematical modeling we show that the ability to make surfactants from glycerol varies inconsistently across the phylogenetic tree; instead, lineages that lost this ability are also worse at reducing the oxidative stress of primary metabolism on glycerol. Experiments with different carbon sources support a link with oxidative stress that explains the inconsistent distribution across the P. aeruginosa phylogeny and suggests a general principle: P. aeruginosa lineages produce surfactants if they can reduce the oxidative stress produced by primary metabolism and have excess resources, beyond their primary needs, to afford secondary metabolism. These results add a new layer to the regulation of a secondary metabolite unessential for primary metabolism but important to change physical properties of the environments surrounding bacterial populations.

Teacher education students, as an important reserve in the field of education, their growth and development are related to the future of science, economy, sustainable development of education. Through participation in the educational practice of STEAM, which integrates science, technology, engineering, art, and mathematics is more beneficial for them to acquire 21st century skills like communication, collaboration, learning innovation and critical thinking. However, little has been seen about the use and effectiveness of short videos in STEAM education activities and how they can be used to support and promote teacher education students STEAM learning performance and sustainable inquiry behaviors. Therefore, this study combines the framework of triadic reciprocity determinism theory and technology acceptance theory to propose six research hypotheses and develop a research model to explore the relationship between collaborative self-efficacy (CS-E), perceived usefulness (PU) of short videos, perceived ease of use (PEOU), STEAM learning performance and teacher education students’ sustainable inquiry behavior. To achieve the purpose of this study, this study used purposive sampling and invited teacher education students from five classes of preschool education at a university in Guangxi Zhuang Autonomous Region (GZAR), China, to participate in this study. A total of 8 h of instructional guidance was provided over a four-week period, in which participants used short videos for collaborative group learning and independent inquiry and applied STEAM concepts to kindergarten science activities. Participants’ STEAM performance was measured and surveyed during the fourth week. The results of the study validation showed that (1) teacher education students CS-E had a positive effect on the PU and PEOU of short videos; (2) Teacher’s education students PEOU of short videos had a positive effect on usefulness; (3) Teacher’s education students PU and PEOU of short videos had a positive effect on STEAM learning performance; (4) Teacher’s education students’ STEAM learning performance had a positive effect on sustainable inquiry behavior.

In our initial study on the high-voltage 5 V cobalt-free spinel LiNi0.5Mn1.5O4 (LNMO) cathode, we discovered a severe delamination issue in the laminates when cycled at a high upper cut-off voltage (UCV) of 4.95 V, especially when a large cell format was used. This delamination problem prompted us to investigate further by studying the transition metal (TM) dissolution mechanism of cobalt-free LNMO cathodes, and as a comparison, some cobalt-containing lithium nickel manganese cobalt oxides (NMC) cathodes, as the leachates from the soaking experiment might be the culprit for the delamination. Unlike other previous reports, we are interested in the intrinsic stability of the cathode in the presence of a baseline Gen2 electrolyte consisting of 1.2 M of LiPF6 in ethylene carbonate/ethyl methyl carbonate (EC/EMC), similar to a storage condition. The electrode laminates (transition metal oxides, transition metal oxides, TMOs, coated on an Al current collector with a loading level of around 2.5 mAh/cm2) or the TMO powders (pure commercial quality spinel LNMO, NMC, etc.) were stored in the baseline solution, and the transition metal dissolution was studied through nuclear magnetic resonance, such as 1H NMR, 19F NMR, scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS) and inductively coupled plasma mass spectrometry (ICP-MS). Significant electrolyte decomposition was observed and could be the cause that leads to the TM dissolution of LNMO. To address this TM dissolution, additives were introduced into the baseline electrolyte, effectively alleviating the issue of TM dissolution. The results suggest that the observed delamination is caused by electrolyte decompositions that lead to etching, and additives such as lithium difluorooxalato borate and p-toluenesulfonyl isocyanate can alleviate this issue by forming a firm cathode electrolyte interface. This study provides a new perspective on cell degradation induced by electrode/electrolyte interactions under storage conditions.

Reversible electrochemical magnesium plating/stripping processes are important for the development of high-energy-density Mg batteries based on Mg anodes. Ether glyme solutions such as monoglyme (G1), diglyme (G2), and triglyme (G3) with the MgTFSI2 salt are one of the conventional and commonly used electrolytes that can obtain the reversible behavior of Mg electrodes. However, the electrolyte cathodic efficiency is argued to be limited due to the enormous parasitic reductive decomposition and passivation, which is governed by impurities. In this work, a systematic identification of the impurities in these systems and their effect on the Mg deposition–dissolution processes is reported. The mitigation methods generally used for eliminating impurities are evaluated, and their beneficial effects on the improved reactivity are also discussed. By comparing the performances, we proposed a necessary conditioning protocol that can be easy to handle and much safer toward the practical application of MgTFSI2/glyme electrolytes containing impurities.

The preschool education profession often faces many challenges and preschool teachers, as important members of the preschool education profession must respond to a variety of emergencies with young children, which also leads to high levels of job stress and can have a negative impact on their ongoing well-being. Past research has pointed out that a healthy lifestyle is one of the key factors in enhancing sustainable well-being in high-stress work situations and many studies have found that good leisure activity engagement as a healthy lifestyle is associated with higher levels of well-being. However, the relationship between preschool teachers’ leisure engagement and sustainable well-being has been less explored. Therefore, this study proposed seven research hypotheses based on the engagement theory proposed by Fredricks et al. (2004) and developed a research model to explore the relationship between three types of leisure engagement, including behavioral, affective and cognitive, and preschool teachers’ job stress and sustainable well-being, using age as a control variable. This study used a cross-sectional web-based questionnaire with a convenience sample of 500 preschool teachers in China. The collected data were analyzed for reliability and validity, model fit testing and structural equation modeling for model validation after removing invalid data and incomplete responses. The results of the study showed that (a) behavioral engagement was not related with either the job stress or sustainable well-being of preschool teachers; (b) Emotional and cognitive engagement were negatively related to job stress but positively related to the sustainable well-being of preschool teachers; and (c) Job stress was negatively related to the sustainable well-being of preschool teachers; (d) Age is an effective control variable. From the above results, it is clear that not all three types of leisure engagement are effective in terms of reducing the work stress of preschool teachers. As well as being related to the sustainable well-being of preschool teachers emotional and cognitive engagement contributed more to sustainable well-being acquisition.

BackgroundMost of data available in the literature reported the sperm retrieval rate and limited intracytoplasmic sperm injection (ICSI) results of microdissection testicular sperm extraction (micro-TESE) in non-obstructive azoospermia (NOA) patients with different etiologies. Unfortunately, there is currently a lack of comprehensive data to guide clinicians in conducting comprehensive consultations with NOA patients.ObjectivesTo obtain more comprehensive evidence-based data and clinical outcomes for better consultation of NOA patients who opted to undergo micro-TESE combined with ICSI-IVFMethodsIt was a retrospective study involved 968 NOA patients underwent micro-TESE during January 2015 to December 2019. Embryological, clinical, and live birth outcomes were demonstrated comprehensively and three kinds of stratification analyses were performed based on ICSI-IVF cycles using frozen and fresh sperm, different etiologies of NOA and various amounts of sperm retrieved.ResultsThe sperm retrieval rate was 44.6%, and ICSI was performed in 299 couples leading to 150 clinical pregnancies and 140 live-birth deliveries. The clinical pregnancy rate (CPR) was 50.17%, and the cumulative live birth rate (LBR) was 46.82%, and the low birth defects rate was 1.43%. No significant difference was observed about cumulative LBR in frozen sperm group and fresh sperm group (47.5% vs 42.9%, P>0.05). NOA patients with AZFc microdeletions had the lowest rate of a high-score embryo on day 3 (4.4%, P

Measurement(s) gut microbiome measurement • Cell Density • Clinical Data Technology Type(s) DNA sequencing • quantitative PCR • clinical laboratory measurement • 16s ribosomal gene sequencing assay Factor Type(s) relative abundance of bacteria • timepoint of hematopoietic cell transplantation • type of hematologic malignancy • time and route of drug administration • type of bacterial infection Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13584986

The lithium-ion cathode material olivine LiFePO4 (LFP) has been synthesized for the first time from natural paleozoic iron carbonate (FeCO3). The ferrous carbonate starting material consists of the mineral siderite at about 92 wt. % purity. Because FeCO3 has divalent iron, the reaction with lithium dihydrogen phosphate (LiH2PO4) provides a unique method to develop iron-(II) containing LFP in an inert atmosphere. Since siderite FeCO3 is a common mineral that can be directly mined, it may, therefore, provide an inexpensive route for the production of LFP. After carbon-coating, the LFP yields a capacity in the range of 80–110 mAh g−1LFP (in one chosen specimen sample), which is lower than commercially available LiFePO4 (150–160 mAh g−1LFP). However, the tap density of LFP derived from siderite is noticeably high at 1.65 g cm−3. The material is likely to be improved with powder purification, nanosized processing, and more complete carbon-coating coverage with increased optimization.

Summary: Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.

Abstract Background Accurate network models of species interaction could be used to predict population dynamics and be applied to manage real world ecosystems. Most relevant models are nonlinear, however, and data available from real world ecosystems are too noisy and sparsely sampled for common inference approaches. Here we improved the inference of generalized Lotka–Volterra (gLV) ecological networks by using a new optimization algorithm to constrain parameter signs with prior knowledge and a perturbation-based ensemble method. Results We applied the new inference to long-term species abundance data from the freshwater fish community in the Illinois River, United States. We constructed an ensemble of 668 gLV models that explained 79% of the data on average. The models indicated (at a 70% level of confidence) a strong positive interaction from emerald shiner (Notropis atherinoides) to channel catfish (Ictalurus punctatus), which we could validate using data from a nearby observation site, and predicted that the relative abundances of most fish species will continue to fluctuate temporally and concordantly in the near future. The network shows that the invasive silver carp (Hypophthalmichthys molitrix) has much stronger impacts on native predators than on prey, supporting the notion that the invader perturbs the native food chain by replacing the diets of predators. Conclusions Ensemble approaches constrained by prior knowledge can improve inference and produce networks from noisy and sparsely sampled time series data to fill knowledge gaps on real world ecosystems. Such network models could aid efforts to conserve ecosystems such as the Illinois River, which is threatened by the invasion of the silver carp.

Rechargeable multivalent ion batteries are promising tools to complement current lithium-ion batteries for a future of diverse energy storage needs. Divalent Mg and Ca are attractive candidates for their high crustal abundance, high volumetric anode capacity, and infrequent dendrite formation during electrochemical cycling. Electrolyte research is central to these efforts and continually improves coulombic efficiencies towards the ideal 100%. This mini-review discusses recent work towards fundamental understandings that push these chemistries towards practical use. Piecing together compatible cathode and electrolytes for a complete practical multivalent ion battery lacks a cohesive method for further development and refinement. Understanding liquid solvation, utilizing rational design, and probing interfacial interactions are focal points that govern electrolyte performance. The combination of these areas will be critical for meaningful development.

Metal nanoparticles have attracted a great deal of interest due to their unique properties of surface plasmon resonance. Metal nanoparticles can enhance the fluorescence emission intensity of quantum dots (QDs) through the local surface plasmon resonance effect, which is mainly determined by the distance between them. Therefore, it is very important to achieve controllable distance between metal and QDs, and study fluorescence enhancement. In this work, the controllable adjustment of the distance between metal nanoparticles and QDs was successfully realized by controlling the thickness of the SiO2 shell of Ag@SiO2 nanoparticles. Firstly, Ag nanoparticles with uniform size distribution and relatively high concentration were prepared, and then the thickness of the SiO2 shell was controlled by controlling the amount of tetra-ethyl orthosilicate (TEOS) in the hydrolysis of TEOS reaction. (3-aminopropyl) triethoxysilane (APS) was used to connect CdS/ZnS QDs with Ag@SiO2 nanoparticles to form Ag@SiO2@CdS/ZnS QD composite nanoparticles. The fluorescence spectra shows that the fluorescence intensity of the Ag@SiO2@CdS/ZnS QD composite nanoparticles is significantly enhanced. Photoexcitation spectra and fluorescence spectra of CdS/ZnS QD and Ag@SiO2@CdS/ZnS QD composite nanoparticles, measured under different energy excitation conditions, indicate that the existence of Ag nanoparticles can enhance the fluorescence intensity of CdS/ZnS QDs. Finally, a further physical mechanism of fluorescence enhancement is revealed.

Temperature sensors are widely used in important fields such as daily home, medical care, and aerospace as a commonly used device for measuring temperature. Traditional temperature sensors such as thermocouples, thermal resistances, and infrared sensors are technically mature; however, they have limitations in the application environment, temperature measurement range, and temperature measurement accuracy. An eye-resolvable surface plasmon-enhanced fluorescence temperature sensor based on dual-emission Ag@SiO2@CdS/ZnS composite nanoparticle film with multiple-parameter detectable signals and high response sensitivity was proposed in this work. The temperature sensor’s x-chromaticity coordinate varied from 0.299 to 0.358 in the range of 77–297 K, while the y-chromaticity coordinate varied from 0.288 to 0.440, displaying eye-resolvable surface plasmon-enhanced fluorescence. The ratiometric response of two isolated photoluminescence (PL) peak-integrated areas located around 446 and 592 nm was found to be significantly temperature dependent, with a thermal sensitivity of 1.4% K−1, which can be used as an additional parameter to measure the precise temperature. Furthermore, the surface state emission peak intensity was linearly related to temperature, with a correlation index Adj. R-Square of 99.8%. Multiple independent temperature estimates can help with self-calibration and improve the measurement accuracy. Our findings show that the designed sensors can detect low temperatures while maintaining stability and reproducibility.

Exploring the temperature-dependent photoluminescence (PL) properties of quantum dots (QDs) is not only important for understanding the carrier recombination processes in QD-based devices but also critical for expanding their special applications at different temperatures. However, there is still no clear understanding of the optical properties of CdS/ZnS core/shell QDs as a function of temperature. Herein, the temperature-dependent PL spectra of CdS/ZnS core/shell QDs were studied in the temperature range of 77–297 K. It was found that the band-edge emission (BEE) intensity decreases continuously with increasing temperature, while the surface-state emission (SSE) intensity first increases and then decreases. For BEE intensity, in the low temperature range, a small activation energy (29.5 meV) in the nonradiative recombination process led to the decrease of PL intensity of CdS/ZnS core/shell QDs; and at high temperature the PL intensity attenuation was caused by the thermal escape process. On the other hand, the temperature-dependent variation trend of the SSE intensity was determined by the competition of the trapping process of the surface trap states and the effect of thermally activated non-radiative defects. As the temperature increased, the PL spectra showed a certain degree of redshift in the peak energies of both band-edge and surface states and the PL spectrum full width at half-maximum (FWHM) increases, which was mainly due to the coupling of exciton and acoustic phonon. Furthermore, the CIE chromaticity coordinates turned from (0.190, 0.102) to (0.302, 0.194), which changed dramatically with temperature. The results indicated that the CdS/ZnS core/shell QDs are expected to be applied in temperature sensors.

Background and Aims: Aspirin leads to substantial benefits for the secondary prevention of cardiovascular disease (CVD). We aimed to cast more light on aspirin’s role for the primary prevention of CVD.Methods: Databases were searched for clinical trials comparing aspirin vs. no aspirin use in this meta-analysis. Efficacy and safety profiles were rigorously investigated. Trial sequential analysis (TSA) was used to determine the robustness of the results.Results: Fourteen studies with 163,840 participants were eligible (mean follow-up 6.2 y). Aspirin intake was found to be associated with 9, 13, and 12% reductions in the risk of cardiovascular events (CV events) (relative risk [RR]: 0.91, 95% confidence intervals [CI]: 0.87–0.96; risk difference (RD): 0.29%; absolute risk percentage (AR%): 7.61%; number needed to treat (NNT): 345), myocardial infarction (RR: 0.87, 95% CI: 0.77–0.97; RD: 0.21%; AR%: 11.11%; NNT: 488) and ischemic stroke (RR: 0.88, 95% CI: 0.80–0.96; RD: 0.21%; AR%: 16.14%; NNT: 476), respectively; aspirin intake was also associated with 40%, 30%, and 57% increases in the risk of major bleeding (RR: 1.40, 95% CI: 1.29–1.53; RD: 0.47%; AR%: 27.85; NNT: 214), intracranial bleeding (RR: 1.30, 95% CI: 1.11–1.52; RD: 0.10%; AR%: 22.99%; NNT: 1,000) and major gastrointestinal bleeding (RR: 1.57, 95% CI: 1.38–1.78; RD: 0.32%; AR%: 36.70%; NNT: 315), respectively. Further, populations with low doses of aspirin intake (≤100 mg), populations

Social interaction between microbes can be described at many levels of details: from the biochemistry of cell-cell interactions to the ecological dynamics of populations. Choosing an appropriate level to model microbial communities without losing generality remains a challenge. Here we show that modeling cross-feeding interactions at an intermediate level between genome-scale metabolic models of individual species and consumer-resource models of ecosystems is suitable to experimental data. We applied our modeling framework to three published examples of multi-strain Escherichia coli communities with increasing complexity: uni-, bi-, and multi-directional cross-feeding of either substitutable metabolic byproducts or essential nutrients. The intermediate-scale model accurately fit empirical data and quantified metabolic exchange rates that are hard to measure experimentally, even for a complex community of 14 amino acid auxotrophies. By studying the conditions of species coexistence, the ecological outcomes of cross-feeding interactions, and each community's robustness to perturbations, we extracted new quantitative insights from these three published experimental datasets. Our analysis provides a foundation to quantify cross-feeding interactions from experimental data, and highlights the importance of metabolic exchanges in the dynamics and stability of microbial communities.

Pseudomonas aeruginosa, a main cause of human infection, can gain resistance to the antibiotic aztreonam through a mutation in NalD, a transcriptional repressor of cellular efflux. Here we combine computational analysis of clinical isolates, transcriptomics, metabolic modeling and experimental validation to find a strong association between NalD mutations and resistance to aztreonam-as well as resistance to other antibiotics-across P. aeruginosa isolated from different patients. A detailed analysis of one patient's timeline shows how this mutation can emerge in vivo and drive rapid evolution of resistance while the patient received cancer treatment, a bone marrow transplantation, and antibiotics up to the point of causing the patient's death. Transcriptomics analysis confirmed the primary mechanism of NalD action-a loss-of-function mutation that caused constitutive overexpression of the MexAB-OprM efflux system-which lead to aztreonam resistance but, surprisingly, had no fitness cost in the absence of the antibiotic. We constrained a genome-scale metabolic model using the transcriptomics data to investigate changes beyond the primary mechanism of resistance, including adaptations in major metabolic pathways and membrane transport concurrent with aztreonam resistance, which may explain the lack of a fitness cost. We propose that metabolic adaptations may allow resistance mutations to endure in the absence of antibiotics and could be targeted by future therapies against antibiotic resistant pathogens.

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00903-0.