Carboxysomes are large self-assembled microcompartments that serve as the central machinery of a CO2-concentrating mechanism (CCM). Biogenesis of carboxysome requires the fine organization of thousands of individual proteins; however, the packaging pattern of internal RuBisCOs remains largely unknown. Here we purified the intact ß-carboxysomes from Synechococcus elongatus PCC 7942 and identified the protein components by mass spectrometry. Cryo-electron tomography combined with subtomogram averaging revealed the general organization pattern of internal RuBisCOs, in which the adjacent RuBisCOs are mainly arranged in three distinct manners: head-to-head, head-to-side, and side-by-side. The RuBisCOs in the outermost layer are regularly aligned along the shell, the majority of which directly interact with the shell. Moreover, statistical analysis enabled us to propose an ideal packaging model of RuBisCOs in the ß-carboxysome. These results provide new insights into the biogenesis of ß-carboxysomes and also advance our understanding of the efficient carbon fixation functionality of carboxysomes.
Bioretrosynthesis problem is to predict synthetic routes using substrates for given natural products (NPs). However, the huge number of metabolic reactions leads to a combinatorial explosion of searching space, which is high time-consuming and costly. Here, we propose a framework called BioRetro to predict bioretrosynthesis pathways using a one-step bioretrosynthesis network, termed HybridMLP combined with AND-OR tree heuristic search. The HybridMLP predicts precursors that will produce the target NPs, while the AND-OR tree generates the iterative multi-step biosynthetic pathways. The one-step bioretrosynthesis prediction experiments are conducted on MetaNetX dataset by using HybridMLP, which achieves 46.5%, 74.6%, 81.6% in terms of the top-1, top-5, top-10 accuracies. The great performance demonstrates the effectiveness of HybridMLP in one-step bioretrosynthesis. Besides, the evaluation of two benchmark datasets reveals that BioRetro can significantly improve the speed and success rate in predicting biosynthesis pathways. In addition, the BioRetro is further shown to find the synthetic pathway of compounds, such as ginsenoside F1 with the same substrates as reported but different enzymes, which may be the novel potential enzyme to have better catalytic performance.
Piezoceramic membranes have emerged as a prominent solution for membrane fouling control. However, the prevalent use of toxic lead and limitations of vibration-based anti-fouling mechanism impede their wider adoption in water treatment. This study introduces a Mn/BaTiO3 piezoceramic membrane, demonstrating a promising in-situ anti-fouling efficacy and mechanism insights. When applied to an Alternating Current at a resonant frequency of 20 V, 265 kHz, the membrane achieves optimal vibration, effectively mitigating various foulants such as high-concentration oil (2500 ppm, including real industrial oil wastewater), bacteria and different charged inorganic colloidal particles, showing advantages over other reported piezoceramic membranes. Importantly, our findings suggest that the built-in ultrasonic vibration of piezoceramic membranes can generate reactive oxygen species. This offers profound insights into the distinct anti-fouling processes for organic and inorganic wastewater, supplementing and unifying the traditional singular vibrational anti-fouling mechanism of piezoceramic membranes, and potentially propelling the development of piezoelectric catalytic membranes.
Purpose: This study aimed to investigate the prevalence and genetic characterization of enterococcal isolates (Enterococcus faecalis, Enterococcus faecium and Enterococcus hirae) isolated from clinical bovine mastitis cases in Ningxia, China. Patients and Methods: The enterococci were identified by 16S rRNA amplification and sequencing. Antimicrobial resistance was determined by disc diffusion method. Virulence and antimicrobial resistance genes were detected by PCR assays. Results: Overall, 198 enterococcal isolates were identified from 2897 mastitis samples, including 137 (4.7%) E. faecalis, 50 (1.7%) E. faecium and 11 (0.4%) E. hirae. E. faecalis, E. faecium and E. hirae isolates showed high resistance to tetracycline (92.7%, 68.0%, 90.9%), followed by erythromycin (86.9%, 76.0%, 72.7%). The multidrug-resistant strains of E. faecalis and E. faecium were 29 (21.2%) and 13 (26.0%), respectively. The resistance of E. faecalis, E. faecium and E. hirae isolates to tetracycline is mainly attributed to the presence of tetL (alone or combined with tetM and/or tetK), the erythromycin resistance to ermB (alone or combined with ermC and/or ermA). Moreover, cpd (94.2%), gelE (77.4%), efaAfs (93.4%), and esp (79.6%) were the most common virulence genes in E. faecalis. In E. faecium, except for the gene efaAfs (82.0%), other virulence genes are rarely found. Only two strains of E. hirae carrying asa1 gene were detected. Conclusion: The results of this study can provide a reference for the prevention and treatment of bovine mastitis caused by enterococci.
This longitudinal cohort study examined the long-term effect of statin therapy on clinical outcomes in patients undergoing percutaneous coronary intervention (PCI). A total of 1760 patients with stable coronary artery disease (CAD) were divided by receipt of statin therapy or not after index PCI. Baseline clinical characteristics, risk factors, angiographic findings, and medications after interventional procedure were assessed to compare long-term clinical outcomes between groups. Predictors for all-cause death and major adverse cardiovascular events (MACE), including myocardial infarction (MI), cardiovascular death, and repeated PCI procedures, were also analyzed. The statin therapy group had higher average serum cholesterol and more elevated low-density lipoprotein cholesterol (LDL-C) than the non-statin therapy group (189.0 ± 47.9 vs 169.3 ± 37.00 mg/dl, 117.2 ± 42.6 vs 98.7 ± 31.8 mg/dl, respectively, both P < 0.001). The non-statin group had higher rates of all-cause death and cardiovascular death compared to statin group (both P < 0.001). After adjustment for age, diabetes, and chronic kidney disease, Cox proportion hazard analysis revealed statin use significantly reduced all-cause death and repeated PCI procedure (hazard ratio: 0.53 and 0.69, respectively). Statin use seemed not reduce the hazard of cardiovascular death or MI in patients with stable CAD after PCI; however, statin therapy still was associated with reduced rates of all-cause death and repeat PCI procedure.
Coronary Artery Disease , Hydroxymethylglutaryl-CoA Reductase Inhibitors , Percutaneous Coronary Intervention , Humans , Percutaneous Coronary Intervention/adverse effects , Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use , Male , Female , Middle Aged , Aged , Coronary Artery Disease/surgery , Coronary Artery Disease/mortality , Treatment Outcome , Longitudinal Studies , Risk Factors , Myocardial Infarction , Cholesterol, LDL/blood
Background: Falls are a primary cause of injuries and hospitalization in older adults. It has been reported that cognitive impairments and dementia can increase fall risk in the older population; however, it remains unknown if fall risk differs among subgroups of dementia. This meta-analysis summarized previous studies reporting the annual fall risk of people with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and compared the fall risk between these two groups of people with dementia. Methods: Thirty-five studies enrolling 7844 older adults with AD or MCI were included. The annual fall prevalence and average number of falls of the included studies were meta-analyzed and compared by random-effects models with inverse variance weights. Results: The annual fall prevalence in people with AD (43.55%) was significantly higher than MCI (35.26%, p < 0.001). A χ2 test indicated that the pooled fall prevalence is significantly higher in people with AD than MCI χ2 = 158.403, p < 0.001). Additionally, the yearly average number of falls in AD was higher than in MCI (1.30 vs 0.77 falls/person). Conclusions: The results showed that older people with AD experience a higher annual fall prevalence with a larger number of falls than older adults with MCI. The results suggested that the fall risk measurements should be reported separately between people with AD and MCI. The findings could provide preliminary guidance for the identification of individuals with dementia who experience a high fall risk.
A convenient self-assembly method is proposed for synthesis of 3D Au/MOF-808 (Zr) composite nanostructures with a cerium metal-organic framework loaded with gold nanoparticles. We combine adsorption properties of MOF materials with surface plasmon resonance of noble metals to construct hotspot-dense 3D Au/MOF-808 (Zr) SERS substrates, by using a two-step method of solvothermal and reduction reactions. The results show that optimal SERS substrates are obtained from a volume ratio of gold nanoparticles to MOF-808 (Zr) solution of 4:1 and a self-assembly time of 2 h. Rhodamine 6G (R6G) is used as a molecular probe to characterize and analyze SERS properties of substrates of 3D Au/MOF-808 (Zr) prepared under the optimal process conditions, where the substrates are capable to detect R6G concentrations down to 10-10 M with a relative standard deviation of 8.81%. Finally, we applied the SERS substrates of 3D Au/MOF-808 (Zr) to the detection of pesticide thiram, and establish a quantitative determination method. 3D Au/MOF-808 (Zr) provides a sensitive detection of thiram in lake water by SERS with a detection limit of 1.49 × 10-9 M. Application tests show that a SERS enhancement factor of the MOF-based SERS substrates for the detection of thiram can be significantly increased to 5.91 × 105. Thus, the above results indicate that such substrate has high sensitivity, good adsorption, homogeneity, and reproducibility, which can be extended for sensitive detection of pesticide residues in food and environment.
Cytokinesis is required for faithful division of cytoplasmic components and duplicated nuclei into two daughter cells. Midbody, a protein-dense organelle that forms at the intercellular bridge, is indispensable for successful cytokinesis. However, the regulatory mechanism of cytokinesis at the midbody still remains elusive. Here, we unveil a critical role for NudC-like protein 2 (NudCL2), a co-chaperone of heat shock protein 90 (Hsp90), in cytokinesis regulation by stabilizing regulator of chromosome condensation 2 (RCC2) at the midbody in mammalian cells. NudCL2 localizes at the midbody, and its downregulation results in cytokinesis failure, multinucleation and midbody disorganization. Using iTRAQ-based quantitative proteomic analysis, we find that RCC2 levels are decreased in NudCL2 knockout (KO) cells. Moreover, Hsp90 forms a complex with NudCL2 to stabilize RCC2, which is essential for cytokinesis. RCC2 depletion mirrors phenotypes observed in NudCL2-downregulated cells. Importantly, ectopic expression of RCC2 rescues the cytokinesis defects induced by NudCL2 deletion, but not vice versa. Together, our data reveal the significance of the NudCL2/Hsp90/RCC2 pathway in cytokinesis at the midbody.
Yield prediction is the primary goal of genomic selection (GS)-assisted crop breeding. As yield is a complex quantitative trait, making predictions from genotypic data is challenging. Transfer learning can produce an effective model for a target task by leveraging knowledge from a different, but related, source domain, considered as a great potential method for improving yield prediction by integrating multi-trait data. However, it has not been applied to genotype-to-phenotype prediction before due to the lack of an efficient implementation framework. We therefore developed TrG2P, a transfer learning-based framework. TrG2P first employs convolutional neural networks (CNN) to train models using non-yield trait phenotypic and genotypic data, thus obtaining the pre-trained models. Subsequently, the convolutional layer parameters from these pre-trained models are transferred to the yield prediction task, and the fully connected layers are retrained, thus obtaining the fine-tuned models. Finally, the convolutional layer and the first fully connected layer of the fine-tuned models are fused, and the last fully connected layer is trained to enhance prediction performance. We applied TrG2P to five sets of genotypic and phenotypic data from maize (Zea mays), rice (Oryza sativa), and wheat (Triticum aestivum), and compared model precision to that of seven other popular GS tools: rrBLUP, Random Forest, Support Vector Regression, LightGBM, CNN, DeepGS, and DNNGP. TrG2P improved the accuracy of yield prediction by 39.9%, 6.8%, and 1.8% in rice, maize, and wheat, respectively, compared to predictions generated by the best performing comparison model. Our work therefore demonstrated that transfer learning is an effective strategy for improving yield prediction by integrating information from non-yield trait data. We attribute the enhanced prediction accuracy to the valuable information available from traits associated with yield and to training dataset augmentation. The Python implementation of TrG2P is available at https://github.com/lijinlong1991/TrG2P. The web-based tool is available at http://trg2p.ebreed.cn:81.
The latest discovery of high temperature superconductivity near 80 K in La3Ni2O7 under high pressure has attracted much attention. Many proposals are put forth to understand the origin of superconductivity. The determination of electronic structures is a prerequisite to establish theories to understand superconductivity in nickelates but is still lacking. Here we report our direct measurement of the electronic structures of La3Ni2O7 by high-resolution angle-resolved photoemission spectroscopy. The Fermi surface and band structures of La3Ni2O7 are observed and compared with the band structure calculations. Strong electron correlations are revealed which are orbital- and momentum-dependent. A flat band is formed from the Ni-3d z 2 orbitals around the zone corner which is ~ 50 meV below the Fermi level and exhibits the strongest electron correlation. In many theoretical proposals, this band is expected to play the dominant role in generating superconductivity in La3Ni2O7. Our observations provide key experimental information to understand the electronic structure and origin of high temperature superconductivity in La3Ni2O7.
PURPOSE: Illness cognition is an important mediator between psychological and behavioral adjustment and the quality of life for patients and their caregivers. Evidence related to illness cognition among parents of children with leukemia is limited. The purpose of this study is to explore the illness cognition status and associated factors in parents of children with leukemia. METHODS: A cross-sectional survey was conducted with the parents of 335 children with leukemia from three general children's hospitals in China from January to December 2022. A parents' version of the illness cognition questionnaire was used to collect data. This included three subscales: helplessness, acceptance, and perceived benefits. RESULTS: The mean scores of helplessness, acceptance and perceived benefits of parents regarding their children's disease were 15.56 (4.60), 16.25 (4.41), and 19.96 (3.69) respectively. The multiple regression model indicated seven factors associated with the parents' illness cognition (adjusted R [2] ranged from 0.182 to 0.134): four socio-demographic factors (parent's age, role, education level, and family income) and three clinical factors (length of time spent each day caring for the child, the child's age at diagnosis, and the duration of the disease). CONCLUSION: This study reports on different levels of illness cognition and associated factors among parents of children with leukemia. The results may help pediatric oncology medical staff identify risk factors for poor psychological adjustment to children's diseases. Parents may benefit from psychological support aimed at improving positive illness cognition.
Cognition , Leukemia , Parents , Humans , Male , Female , Parents/psychology , Cross-Sectional Studies , Child , Leukemia/psychology , Adult , China , Child, Preschool , Adolescent , Quality of Life/psychology , Middle Aged , Caregivers/psychology , Surveys and Questionnaires , Socioeconomic Factors , Adaptation, Psychological
Sample preparation, including extraction, separation, and purification, is a vital process for natural product analysis. As an attractive sample pretreatment method, magnetic solid-phase extraction (MSPE) has gained plenty of attention, mainly due to its simpler operation, less consumption of organic solvents, and shorter processing time than traditional SPE. This updated review is devoted to summarizing the applications of MSPE based on different magnetic nanomaterials in the analysis of various natural products in complex matrixes, such as biological samples, plants, and Chinese herbal preparations in the past four years (2020-2023). The preparation and fabrication of different materials are briefly introduced. Furthermore, the extraction mechanism and interaction forces between adsorbent and analytes are elaborated, and the advantages and disadvantages of different adsorbents coupled with various analytical methods for MSPE of different natural products are summarized. Moreover, the future trends and opportunities for MSPE in the natural product analysis are discussed. It is expected that this work can provide updated information for future research on the applications of MSPE in such fields.
A prior study reported that the concentric strength imbalance between hamstrings and quadriceps is associated with falls in older adults. Given that the concentric strength may not be measured as conveniently as the isometric strength, it is meaningful to test whether the isometric hamstring-quadricep strength imbalance is related to falls among older adults. This study sought to explore whether the hamstrings-quadriceps ratio could differentiate fallers from non-fallers in community-dwelling older adults. One hundred and eleven older adults were included in this cross-sectional study. Their isometric knee joint strength capacity (extensors and flexors) was measured. Based on their fall history in the past year, they were classified as fallers (at least one fall) or non-fallers (no fall). The hamstrings-quadriceps ratio was compared between the faller and non-faller groups. The receiver operating characteristic analysis was used to determine the cutoff value of the hamstrings-quadriceps ratio able to best classify fallers and non-fallers. Fallers showed a significantly lower hamstrings-quadriceps ratio than non-fallers (p = 0.008). The receiver operating characteristic analysis identified 0.733 as the best ratio to differentiate fallers from non-fallers with an accuracy of 64.0 %. A 0.1-unit reduction in the hamstrings-quadriceps ratio increases the probability of falling by a factor of 1.30. The hamstrings-quadriceps ratio could be used as an additional fall risk factor when assessing the risk of falls among older adults. A smaller than 0.733 hamstring-quadriceps ratio may indicate a high risk of falls.
Exercise training effectively relieves anxiety disorders via modulating specific brain networks. The role of post-translational modification of proteins in this process, however, has been underappreciated. Here we performed a mouse study in which chronic restraint stress-induced anxiety-like behaviors can be attenuated by 14-day persistent treadmill exercise, in association with dramatic changes of protein phosphorylation patterns in the medial prefrontal cortex (mPFC). In particular, exercise was proposed to modulate the phosphorylation of Nogo-A protein, which drives the ras homolog family member A (RhoA)/ Rho-associated coiled-coil-containing protein kinases 1(ROCK1) signaling cascade. Further mechanistic studies found that liver-derived kynurenic acid (KYNA) can affect the kynurenine metabolism within the mPFC, to modulate this RhoA/ROCK1 pathway for conferring stress resilience. In sum, we proposed that circulating KYNA might mediate stress-induced anxiety-like behaviors via protein phosphorylation modification within the mPFC, and these findings shed more insights for the liver-brain communications in responding to both stress and physical exercise.
The superconducting gap symmetry is crucial in understanding the underlying superconductivity mechanism. Angle-resolved photoemission spectroscopy (ARPES) has played a key role in determining the gap symmetry in unconventional superconductors. However, it has been considered so far that ARPES can only measure the magnitude of the superconducting gap but not its phase; the phase has to be detected by other phase-sensitive techniques. Here we propose a method to directly detect the superconducting gap sign by ARPES. This method is successfully validated in a cuprate superconductor Bi2Sr2CaCu2O8+δ with a well-known d-wave gap symmetry. When two bands have a strong interband interaction, the resulted electronic structures in the superconducting state are sensitive to the relative gap sign between the two bands. Our present work provides an approach to detect the gap sign and can be applied to various superconductors, particularly those with multiple orbitals like the iron-based superconductors.
Motorized treadmills have been extensively used in investigating reactive balance control and developing perturbation-based interventions for fall prevention. However, the relationship between perturbation intensity and its outcome has not been quantified. The primary purpose of this study was to quantitatively analyze how the treadmill belt's peak velocity affects the perturbation outcome and other metrics related to the reactive balance in young adults while the total belt displacement is controlled at 0.36 m. Thirty-one healthy young adults were randomly assigned into three groups with different peak belt speeds: low (0.9 m/s), medium (1.2 m/s), and high (1.8 m/s). Protected by a safety harness, participants were exposed to a forward support surface translation while standing at an unexpected timing on an ActiveStep treadmill. The primary (perturbation outcome: fall vs. recovery) and secondary (dynamic stability, hip descent, belt distance at liftoff, and recovery step latency) outcome measures were compared among groups. Results revealed that a higher perturbation intensity is correlated with a greater faller rate (p < 0.001). Compared to the low- and medium-intensity groups, the high-intensity group was less stable (p < 0.001) with a larger hip descent (p < 0.001) and a longer belt distance (p < 0.001) at the recovery step liftoff. The results suggest that the increased perturbation intensity raises the risk of falling with larger instability and poorer reactive performance after a support surface translation-induced perturbation in healthy young adults. The findings could furnish preliminary guidance for us to design and select the optimal perturbation intensity that can maximize the effects of perturbation-based training protocols.
Accidental Falls , Postural Balance , Humans , Postural Balance/physiology , Accidental Falls/prevention & control , Male , Female , Adult , Young Adult , Standing Position , Biomechanical Phenomena , Exercise Test/methods
BACKGROUND: The seizure prediction algorithms have demonstrated their potential in mitigating epilepsy risks by detecting the pre-ictal state using ongoing electroencephalogram (EEG) signals. However, most of them require high-density EEG, which is burdensome to the patients for daily monitoring. Moreover, prevailing seizure models require extensive training with significant labeled data which is very time-consuming and demanding for the epileptologists. METHOD: To address these challenges, here we propose an adaptive channel selection strategy and a semi-supervised deep learning model respectively to reduce the number of EEG channels and to limit the amount of labeled data required for accurate seizure prediction. Our channel selection module is centered on features from EEG power spectra parameterization that precisely characterize the epileptic activities to identify the seizure-associated channels for each patient. The semi-supervised model integrates generative adversarial networks and bidirectional long short-term memory networks to enhance seizure prediction. RESULTS: Our approach is evaluated on the CHB-MIT and Siena epilepsy datasets. With utilizing only 4 channels, the method demonstrates outstanding performance with an AUC of 93.15% on the CHB-MIT dataset and an AUC of 88.98% on the Siena dataset. Experimental results also demonstrate that our selection approach reduces the model parameters and training time. CONCLUSIONS: Adaptive channel selection coupled with semi-supervised learning can offer the possible bases for a light weight and computationally efficient seizure prediction system, making the daily monitoring practical to improve patients' quality of life.
Electroencephalography , Seizures , Humans , Electroencephalography/methods , Seizures/physiopathology , Seizures/diagnosis , Signal Processing, Computer-Assisted , Deep Learning , Algorithms , Databases, Factual , Epilepsy/physiopathology , Supervised Machine Learning
Hydrogen-bonded organic frameworks (HOFs) are versatile materials with potential applications in proton conduction. Traditional approaches involve incorporating humidity control to address grain boundary challenges for proton conduction. This study finds vitrification as an alternative strategy to eliminate grain boundary effect in HOFs by rapidly melt quenching the kinetically stable HOF-SXU-8 to glassy state HOF-g. Notably, a remarkable enhancement in proton conductivity without humidity was achieved after vitrification, from 1.31 × 10-7 S cm-1 to 5.62× 10-2 S cm-1 at 100 °C. Long term stability test showed negligible performance degradation, and even at 30 °C, the proton conductivity remained at high level of 1.2 × 10-2 S cm-1. Molecule dynamics (MD) simulations and X-ray total scattering experiments reveal the HOF-g system is consisted of three kinds of clusters, i.e., 1,5-Naphthalenedisulfonic acid (1,5-NSA) anion clusters, N,N-dimethylformamide (DMF) molecule clusters, and H+-H2O clusters. In which, the H+ plays an important role to bridge these clusters and the high conductivity is mainly related to the H+ on H3O+. These findings provide valuable insights for optimizing HOFs, enabling efficient proton conduction, and advancing energy conversion and storage devices.
Autism Spectrum Disorders (ASD) comprise a range of early age-onset neurodevelopment disorders with genetic heterogeneity. Most ASD related genes are involved in synaptic function, which is regulated by mature brain-derived neurotrophic factor (mBDNF) and its precursor proBDNF in a diametrically opposite manner: proBDNF inhibits while mBDNF potentiates synapses. Here we generated a knock-in mouse line (BDNFmet/leu) in which the conversion of proBDNF to mBDNF is attenuated. Biochemical experiments revealed residual mBDNF but excessive proBDNF in the brain. Similar to other ASD mouse models, the BDNFmet/leu mice showed reduced dendritic arborization, altered spines, and impaired synaptic transmission and plasticity in the hippocampus. They also exhibited ASD-like phenotypes, including stereotypical behaviors and deficits in social interaction. Moreover, the plasma proBDNF/mBDNF ratio was significantly increased in ASD patients compared to normal children in a case-control study. Thus, deficits in proBDNF to mBDNF conversion in the brain may contribute to ASD-like behaviors, and plasma proBDNF/mBDNF ratio may be a potential biomarker for ASD.
The Camellia tetracocca Zhang is a rare and ancient plant, exclusively found in the vicinity of Puan County, Guizhou Province, China. According to leaf color, two distinct variations have been identified: purple C. tetracocca Zhang (PCTZ) and green C. tetracocca (GCTZ). This research was conducted to investigate the antioxidant activities and chemical compositions of different edible parts of PCTZ and GCTZ. Antioxidant activity was evaluated using DPPH, ABTS, HSA, and T-AOC assays, while the content of compounds was determined by HPLC. The findings demonstrated that the antioxidant capacity of PCTZ leaves is significantly superior to that of GCTZ leaves. Notably, theacrine, a rare compound, contains up to 2.075% in PCTZ leaves, indicating potential as a novel natural antidepressant and antioxidant. In conclusion, PCTZ is a distinctive tea beverage and a valuable genetic material for tea tree breeding due to its high theacrine and low caffeine characteristics.
