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Trajectories of quality of life during hematopoietic stem cell transplantation: longitudinal cohort study

Dynamic response and damage mechanism of reinforced concrete beam bridges under rockfall impacts

Microwave resonance detection method for hidden crack depth in rock and cementitious mortar

Top-performing girls are more impactful peer role models than boys, teachers say

We examine teachers’ perceptions toward top-performing students and their role model influence on others in an online survey-based experiment. We randomly expose teachers to profiles of top-performing students and inquire whether they consider the profiled top performers to be influential role models. These profiles varied by gender and field of study (STEM or Non-STEM). Our findings show that teachers perceive top-performing girls as more influential peer role models compared to top-performing boys ( β ̂ = 0.289 ; P < 0.001 ). We also investigate the qualities teachers perceive top performers who are successful role models to have. We show that teachers associate a greater sense of learning autonomy and sense of being an example with top-performing girls compared to top-performing boys. Estimated effects are more pronounced among teachers with children and teachers in urban areas. Administrative data from a representative sample show limited observed differences between top-performing boys’ and girls’ educational outcomes that could justify the differences in teachers’ gender perceptions. These findings carry significant implications for education, as teachers play a crucial role in the cultivation of positive externalities between students.

Enhancing Intelligent HVAC optimization with graph attention networks and stacking ensemble learning, a recommender system approach in Shenzhen Qianhai Smart Community

Facile fabrication of novel magnetic chitosan@Ag-MWCN nanocomposite for the adsorptive removal of ciprofloxacin from aqueous solutions

Author Correction: Lignan enriched fraction (LRF) of Phyllanthus amarus promotes apoptotic cell death in human cervical cancer cells in vitro

The ER–PM interaction is essential for cytokinesis and recruits the actin cytoskeleton through the SCAR/WAVE complex

Plant cytokinesis requires coordination between the actin cytoskeleton, microtubules, and membranes to guide division plane formation and cell plate expansion; how these regulatory factors are coordinated remains unknown. The actin cytoskeleton assembly is controlled by several actin nucleation factors, such as the SCAR/WAVE complex, which regulates actin nucleation and branching through the activation of the ARP2/3 complex. The activity of these actin regulatory proteins is likely influenced by interactions with specific membranes; however, the molecular basis and the biological relevance of SCAR–membrane interactions are also unclear. In this study, we demonstrate that the ER–PM tethering protein VAP27-1 directly interacts with SCAR2 at the ER membrane and that they colocalize to guide cell plate orientation during cell division. In the root meristem, both VAP27-1 and SCAR2 exhibit polarized localization at the cell plates, where the interaction between ER and PM is abundant. VAP27-1 recruits SCAR2 to the cell division plane, where there is a high concentration of actin filaments. In the vap27-1346 mutant, the densities of cortical ER, SCAR2, and consequently actin filaments are significantly reduced at the cell division plane, affecting cell plate orientation, cell division, and root development. A similar phenomenon is also observed in the scar1234 mutant, suggesting that VAP27 and SCAR proteins regulate cell division through a similar pathway. In conclusion, our data reveal a plant-specific function of VAP27-regulated ER–PM interaction and advance our understanding of plant ER–PM contact site and its role in cell division.

Combining plant extracts and hot water treatments for the management of postharvest mango anthracnose (Colletotrichum gloeosporioides)

The structure of full-length AFPK supports the ACP linker in a role that regulates iterative polyketide and fatty acid assembly

The polyketide synthases (PKSs) in microbes and the cytoplasmic fatty acid synthases in humans (FASs) are related enzymes that have been well studied. As a result, there is a paradigm explaining in general terms how FASs repeatedly use a set of enzymatic domains to produce simple fats, while PKSs use the domains in a much more complex manner to produce pharmaceuticals and other elaborate molecules. However, most animals also have PKSs that do not conform to the rules described in microbes, including a large family of enzymes that bridge fatty acid and polyketide metabolism, the animal FAS-like PKSs (AFPKs). Here, we present the cryoelectron microscopy structures of two AFPKs from sea slugs. While the AFPK resemble mammalian FASs, their chemical products mimic those of PKSs in complexity. How then does the architecture of AFPKs facilitate this structural complexity? Unexpectedly, chemical complexity is controlled not solely by the enzymatic domains but is aided by the dynamics of the acyl carrier protein (ACP), a shuttle that moves intermediates between these domains. We observed interactions between enzyme domains and the linker-ACP domain, which, when manipulated, altered the kinetic properties of the enzyme to change the resulting chemical products. This unveils elaborate mechanisms and enzyme motions underlying lipid and polyketide biochemistry across the domains of life.

Effect of pH and buffer on substrate binding and catalysis by cis-aconitate decarboxylase

Abstract cis-Aconitate decarboxylase (ACOD1, CAD, IRG1) catalyses the synthesis of itaconic acid in activated myeloid cells such as macrophages. Several histidine residues in the active site bind the substrate and enable the decarboxylation reaction. The in vitro activity of ACOD1 enzymes is commonly determined by incubation with substrate, followed by HPLC measurement of itaconic acid production. Phosphate buffers have often been used for this assay. However, the influence of buffer type on enzyme activity has not been investigated. Here, the effect of buffer and pH on enzyme kinetics of human and mouse ACOD1 and Aspergillus terreus CAD was investigated. It was found that high concentrations of phosphate inhibit the three enzymes. An alternative buffer was selected and the assay was adapted to the 96-well microtitre plate format for increased throughput. Enzyme kinetics were determined in the pH range of 5.5–8.25. A strong increase of K M values was observed between the physiologically relevant pH values 7.5 and 8.25. The data indicate that more than one histidine residue needs to be protonated in the active site for binding the substrate.

Microlevel structural poverty estimates for southern and eastern Africa

For many countries in the Global South traditional poverty estimates are available only infrequently and at coarse spatial resolutions, if at all. This limits decision-makers’ and analysts’ ability to target humanitarian and development interventions and makes it difficult to study relationships between poverty and other natural and human phenomena at finer spatial scales. Advances in Earth observation and machine learning-based methods have proven capable of generating more granular estimates of relative asset wealth indices. They have been less successful in predicting the consumption-based poverty measures most commonly used by decision-makers, those tied to national and international poverty lines. For a study area including four countries in southern and eastern Africa, we pilot a two-step approach that combines Earth observation, accessible machine learning methods, and asset-based structural poverty measurement to address this gap. This structural poverty approach to machine learning-based poverty estimation preserves the interpretability and policy-relevance of consumption-based poverty measures, while allowing us to explain 72 to 78% of cluster-level variation in a pooled model and 40 to 54% even when predicting out-of-country.

Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization

Deep learning–driven bacterial cytological profiling to determine antimicrobial mechanisms in <i>Mycobacterium tuberculosis</i>

Tuberculosis (TB), caused by Mycobacterium tuberculosis , remains a significant global health threat, affecting an estimated 10.6 million people in 2022. The emergence of multidrug resistant and extensively drug resistant strains necessitates the development of novel and effective drugs. Accelerating the determination of mechanisms of action (MOAs) for these drugs is crucial for advancing TB treatment. This study introduces MycoBCP, a unique adaptation of bacterial cytological profiling (BCP) tailored to M. tuberculosis , utilizing the application of convolutional neural networks (CNNs) within BCP to overcome challenges posed by traditional image analysis techniques. Using MycoBCP, we analyzed the morphological effects of various antimicrobial compounds on M. tuberculosis , capturing broad patterns rather than relying on precise cell segmentation. This approach circumvented issues such as cell clumping and uneven staining, which are prevalent in M. tuberculosis . In a blind test, MycoBCP accurately identified the MOA for 96% of the compounds, with a single misclassification of rifabutin, which was incorrectly categorized as affecting translation rather than transcription. The similar morphologies resulting from transcription and translation inhibition indicate a need for further refinement to distinguish them more effectively. Application of MycoBCP to a series of antitubercular agents successfully identified known MOAs and revealed unique effects, demonstrating its utility in early drug discovery and development. Our findings underscore the potential of CNN-based BCP to enhance the accuracy and efficiency of MOA determination, particularly for challenging pathogens like M. tuberculosis . MycoBCP represents a significant advancement in TB drug development, offering a robust and adaptable method for high-throughput screening of antimicrobial compounds.

The interplay among energy utilisation efficiency and industrial agglomeration through spatial heterogeneity insights

A reduced order pseudochannel model accounting for flow maldistribution in automotive catalysis

Abstract Exhaust aftertreatment systems (EATS) play a critical role in reducing emissions and ensuring compliance with stringent emission regulations. Catalytic converters, as part of EATS, involve complex physico-chemical processes. To accurately predict their behavior in realistic geometries, transient 3D models are necessary. However, the computational cost associated with simulations based on such models prevents their application to long-time behaviors as well as in real-time control and diagnostics. While single-channel models (SCMs) are computationally efficient, they struggle to provide accurate predictions during real-time operations with flow maldistribution. In this study, we propose a pseudochannel model derived using steady-state reactive 3D simulations and a nonlinear least squares optimization technique. We show that the performance of this pseudochannel model is superior to a conventional SCM in both transient and steady state test cases. At the same time, the computational cost of the pseudochannel model is equivalent to that of the SCM. These results imply that flow maldistribution effects can be well incorporated in SCMs via a pseudochannel approach that relies on relatively inexpensive steady-state system data.

G-quadruplexes catalyze protein folding by reshaping the energetic landscape

Many proteins have slow folding times in vitro that are physiologically untenable. To combat this challenge, ATP-dependent chaperonins are thought to possess the unique ability to catalyze protein folding. Performing quantitative model selection using protein folding and unfolding data, we here show that short nucleic acids containing G-quadruplex (G4) structure can also catalyze protein folding. Performing the experiments as a function of temperature demonstrates that the G4 reshapes the underlying driving forces of protein folding. As short nucleic acids can catalyze protein folding without the input of ATP, the ability of the cell to fold proteins is far higher than previously anticipated.

Bone anchoring annular suture technique for repairing annular defects at vertebral body edge following lumbar discectomy

Extrinsic induction of apoptosis and tumor suppression via the p53–Reprimo–Hippo–YAP/TAZ–p73 pathway

Tumor progression is suppressed by inherent cellular mechanisms such as apoptosis. The p53 tumor suppressor gene is the most commonly mutated gene in human cancer and plays a pivotal role in tumor suppression. RPRM is a target gene of p53 known to be involved in tumor suppression, but its molecular function has remained elusive. Here, we report that Reprimo (the protein product of RPRM ) is secreted and extrinsically induces apoptosis in recipient cells. We identified FAT1, FAT4, CELSR1, CELSR2, and CELSR3, members of the protocadherin family, as receptors for Reprimo. Subsequent analyses revealed that Reprimo acts upstream of the Hippo–YAP/TAZ–p73 axis and induces apoptosis by transactivating various proapoptotic genes. In vivo analyses further support the tumor-suppressive effects of secreted Reprimo. These findings identify the p53–Reprimo–Hippo–YAP/TAZ–p73 axis as an extrinsic apoptosis pathway that plays a crucial role in tumor suppression. Our finding of the innate tumor eliminator Reprimo and the downstream pathway offers a promising avenue for the pharmacological treatment of cancer.

Innovative application of ceftriaxone as a quorum sensing inhibitor in Pseudomonas aeruginosa

Abstract Pseudomonas aeruginosa is a Gram-negative bacterium that has the potential to induce various healthcare-related infections through its array of virulence factors. The control of virulence factor expression is mainly regulated by a communication process among cells called quorum sensing (QS). Blocking QS could be a viable tactic to suppress virulence factors and reduce pathogenicity without impacting bacterial growth. This approach has the potential to significantly decrease the multiple drug resistance emergence. In this study, we explored the impact of ceftriaxone (CRO), which is a commonly used β-lactam antibiotic, and its metal derivatives on the QS system and virulence factors of both standard strains and clinical isolates of P. aeruginosa. The quorum sensing inhibitory (QSI) activity of CRO and ceftriaxone Nickel complex (CRON) was evaluated. The minimum inhibitory concentration (MIC) was determined and the effect of sub-MICs of CRO and CRON was assessed on P. aeruginosa strains virulence factors. CRO and CRON effectively suppressed the virulence factors of P. aeruginosa strains at sub-MICs, without altering bacterial viability. Additionally, a molecular docking investigation was carried out to identify potential mechanisms of QSI. CRO and CRON exhibited high ICM scores, potentially displacing natural ligands when interacting with LasR, LasI, and PqsR receptors.