Browse Articles

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.

Comparative transcriptomics reveals a mixed basal, club, and hillock epithelial cell identity in castration-resistant prostate cancer

Inhibiting the androgen receptor (AR) is effective for treatment of advanced prostate cancers because of their AR-dependent luminal epithelial cell identity. Tumors progress during therapy to castration-resistant prostate cancer (CRPC) by restoring AR signaling and maintaining luminal identity or by converting through lineage plasticity to a neuroendocrine (NE) identity or double-negative CRPC (DNPC) lacking luminal or NE identities. Here, we show that DNPC cells express genes defining basal, club, and hillock epithelial cells from benign prostate. We identified KLF5 as a regulator of genes defining this mixed basal, club, and hillock cell identity in DNPC models. KLF5-mediated upregulation of RARG uncovered a DNPC sensitivity to growth inhibition by retinoic acid receptor agonists, which down-regulated KLF5 and up-regulated AR. These findings offer CRPC classifications based on prostate epithelial cell identities and nominate KLF5 and RARG as therapeutic targets for CRPC displaying a mixed basal, club, and hillock identity.

Artificial neural network controlled DSTATCOM for mitigating power quality concerns in solar PV and wind system

HflX-mediated drug resistance through ribosome splitting and rRNA disordering in mycobacteria

HflX is a highly conserved ribosome-associated GTPase implicated in rescuing stalled ribosomes and mediating antibiotic resistance in several bacteria, including macrolide-lincosamide antibiotic resistance in mycobacteria. Mycobacterial HflXs carry a distinct N-terminal extension (NTE) and a small insertion, as compared to their eubacterial homologs. Here, we present several high-resolution cryo-EM structures of mycobacterial HflX in complex with the 70S ribosome and its 50S subunit, with and without antibiotics. These structures reveal a distinct mechanism for HflX-mediated ribosome splitting and antibiotic resistance in mycobacteria. Our findings indicate that the NTE of mycobacterial HflX induces persistent disordering of multiple 23S rRNA helices, facilitating the dissociation of the 70S ribosome and generating an inactive pool of 50S subunits. During this process, HflX undergoes a large conformational change that stabilizes its NTE. Mycobacterial HflX also acts as an anti-association factor by binding to predissociated 50S subunits. Our structures show that a mycobacteria-specific insertion in HflX reaches far into the peptidyl transferase center (PTC), such that it would overlap with the ribosome-bound macrolide antibiotics. However, in the presence of antibiotics, this insertion retracts, adjusts around, and interacts with the antibiotic molecules. These results suggest that mycobacterial HflX is agnostic to antibiotic presence in the PTC. It mediates antibiotic resistance by splitting antibiotic-stalled 70S ribosomes and inactivating the resulting 50S subunits.

Research on the controller of an active vibration isolation unit for underwater crushing operations

Mec1-mediated Atg9 phosphorylation regulates the PAS recruitment of Atg9 vesicles upon energy stress

Mec1 plays an essential role in both the DNA damage response and glucose starvation–induced autophagy. We recently reported that Mec1 regulates glucose starvation–induced autophagy through its direct binding to Atg13. However, the role of Mec1’s kinase activity in autophagy remains unclear. In this study, we demonstrate that the kinase activity of Mec1 is required for glucose starvation–induced autophagy by regulating the phagophore assembly site (PAS) recruitment of Atg9 vesicles. Mechanistic and functional analyses identified Atg9 as a direct phosphorylation substrate of Mec1, with phosphorylation occurring at the S35, T203, and T243 sites. Mutations at these sites reduce the association of Atg9 with Atg17, Atg23, and Atg27, thereby impairing the PAS recruitment of Atg9 vesicles. Notably, we found that the Mec1–Atg13 binding is a prerequisite for the phosphorylation of Atg9 by Mec1. Furthermore, Mec1-mediated phosphorylation of Atg9 is also crucial for the PAS recruitment of Atg9 vesicles in response to DNA damage. We thus propose that Mec1’s kinase activity regulates the PAS recruitment of Atg9 vesicles by phosphorylating Atg9 in response to energy stress and DNA damage.

Publisher Correction: A meta-analysis of bulk RNA-seq datasets identifies potential biomarkers and repurposable therapeutics against Alzheimer’s disease

An ear for an ear, but only if you are a deomyinid

Bioinformatics analysis of coronary microvascular dysfunction in rats based on single-cell RNA sequencing

Abscisic acid signaling gates salt-induced responses of plant roots

Soil salinity presents a dual challenge for plants, involving both osmotic and ionic stress. In response, plants deploy distinct yet interconnected mechanisms to cope with these facets of salinity stress. In this investigation, we observed a substantial overlap in the salt (NaCl)-induced transcriptional responses of Arabidopsis roots with those triggered by osmotic stress or the plant stress hormone abscisic acid (ABA), as anticipated. Notably, a specific cluster of genes responded uniquely to sodium (Na + ) ions and are not regulated by the known monovalent cation sensing mechanism MOCA1 . Surprisingly, expression of sodium-induced genes exhibited a negative correlation with the ABA response and preceded the activation of genes induced by the osmotic stress component of salt. Elevated exogenous ABA levels resulted in the complete abolition of sodium-induced responses. Consistently, the ABA insensitive snrk2.2/2.3 double mutant displayed prolonged sodium-induced gene expression, coupled with increased root cell damage and root swelling under high salinity conditions. Moreover, ABA biosynthesis and signaling mutants were unable to redirect root growth to avoid high sodium concentrations and had increased sodium accumulation in the shoot. In summary, our findings unveil an unexpected and pivotal role for ABA signaling in mitigating cellular damage induced by salinity stress and modulating sodium-induced responses in plant roots.

Assessment of heavy metals and microbial loads in Nile tilapia (Oreochromis niloticus) from different farms and rivers

Synergistic anion–π interactions in peptidomimetic polyethers

Anion–π interactions are crucial in various biological processes, such as enzyme catalysis and ion transport. Despite their significance, the exploitation of anion–π interactions in synthetic polymer systems remains underexplored. This study investigates anion–π interactions using chemically well-defined peptidomimetics guided by the composition of mussel foot proteins. Specifically, polyether-based polymers were designed utilizing two functional epoxide monomers—catechol acetonide glycidyl ether and 4,4-dimethyl-2-oxazoline glycidyl ether—to mimic the key amino acids 3,4-dihydroxyphenylalanine and aspartic acid, respectively. A surface forces apparatus was employed to study the anion–π interaction between the polymers, considering the effects of relative monomer composition and pH conditions. The maximum cohesion energy of 15.0 mJ/m 2 was observed at an equimolar monomer composition at pH 7. Incorporating a phenyl group instead of the catechol group and introducing competing anions confirmed the dominant role of anion–π interactions. This study highlights the significance of anion–π interactions, posing a high potential in the design and synthesis of functional materials.