Browse Articles

Unconventional secretion of PARK7 requires lysosomal delivery via chaperone-mediated autophagy and specialized SNARE complex

PARK7/DJ-1, a redox-sensitive protein implicated in neurodegeneration, cancer, and inflammation, exhibits increased secretion under stress. We previously demonstrated that, as a leaderless protein, PARK7 relies on an unconventional autophagy pathway for stress-induced secretion. The current study delves deeper into the mechanisms governing PARK7 secretion under oxidative stress triggered by the neurotoxin 6-hydroxydopamine (6-OHDA). Here, we revealed that 6-OHDA-induced autophagic flux is critical for PARK7 secretion. Downregulation of syntaxin 17 (STX17), a SNARE protein crucial for autophagosome-lysosome fusion and cargo degradation, hindered PARK7 secretion. Likewise, impairing lysosomal function with bafilomycin A1 (BafA1) or chloroquine (CQ) diminished PARK7 release, highlighting the importance of functional lysosomes, potentially in the form of secretory autolysosomes, in PARK7 release. We also found that 6-OHDA appeared to promote the unfolding of PARK7, allowing its selective recognition by the chaperone HSPA8 via KFERQ-like motifs, leading to PARK7 translocation to the lysosomal membrane through LAMP2 via chaperone-mediated autophagy (CMA). Additionally, a dedicated SNARE complex comprising Qabc-SNAREs (STX3/4, VTI1B, and STX8) and R-SNARE SEC22B mediates the fusion of PARK7-containing autolysosomes with the plasma membrane, facilitating the extracellular release of PARK7. Hence, this study uncovers a mechanism where 6-OHDA-induced autophagic flux drives the unconventional secretion of PARK7, involving CMA for PARK7 translocation to lysosomes and specialized SNARE complexes for membrane fusion events.

Multicenter, prospective clinical trial for balloon-occluded alternative infusion of cisplatin solution and fragmented gelatin particles of transarterial chemoembolization for hepatocellular carcinoma beyond up-to-seven criteria

Conversion of social organization in fire ants induced by few colony members: Unmasking indirect genetic effects

Genes and the environment jointly shape individual traits, but the influence of indirect genetic effects (IGEs), arising from the genetic composition of interacting conspecific individuals, is often ignored or underemphasized. Moreover, because of practical challenges in characterizing IGEs, empirical research has fallen behind theoretical advancement. The fire ant Solenopsis invicta offers a uniquely suitable study system due to its distinct colony-level phenotypic variation (monogyne and polygyne social forms) attributed to IGEs of a social-supergene variant ( b allele). A minority of b -carrying workers ( Bb genotype) can trigger colony-level conversion from monogyne (single queen per colony) to polygyne (multiple queens per colony) behavior. This study investigated the mechanisms underlying this process via 400-ant microcolonies. We first showed that assimilated Bb workers reduce aggression by host BB workers toward Bb queens, thus inducing polygyny, at rates observed earlier in experiments that used full-size (>20,000 ants) colonies. We then demonstrated that social conversion is facilitated by cuticular contact between the worker types, and verified the presence of nonvolatile cuticular pheromones that are necessary but not sufficient components underpinning this process. Follow-up experiments suggested that a second, polygyne worker-produced pheromone that is only released once such workers detect a Bb queen is also necessary but again insufficient, for full expression of the conversion phenomenon. Thus, multiple pheromonal components linked to presence of the b supergene allele in colony workers appear to be involved in shaping social environments and thereby inducing, via IGEs, the transformation from monogyne to polygyne fire ant societies.

Author Correction: Response of soil organic carbon and soil aggregate stability to changes in land use patterns on the Loess Plateau

Combining live fluorescence imaging with in situ cryoelectron tomography sheds light on the septation process in <i>Deinococcus radiodurans</i>

Cell division is a fundamental biological process that allows a single mother cell to produce two daughter cells. In walled bacteria, different modes of cell division have been reported that are notably associated with distinctive cell shapes. In all cases, division involves a step of septation, corresponding to the growth of a new dividing cell wall, followed by splitting of the two daughter cells. The radiation-resistant Deinococcus radiodurans is a spherical bacterium protected by a thick and unusual cell envelope. It has been reported to divide using a distinctive mode of septation in which two septa originating from opposite sides of the cell progress with a flat leading edge until meeting and fusing at mid-cell. In the present study, we have combined conventional and superresolution fluorescence microscopy of live bacteria with in situ cryogenic electron tomography of bacterial lamellae to investigate the septation process in D. radiodurans . This work provides important insight into i) the complex architecture and multilayered composition of the cell envelope of this bacterium, ii) the unusual “sliding doors” septation process and iii) the sequence of events and molecular mechanisms underlying septal closure, including the synthesis of a FtsZ-dependent peptidoglycan layer that rigidifies and straightens the growing septa.

Identification of the histologic transformation of follicular lymphoma using super-resolution microcirculation imaging

Paving the way for social touch at a distance: Sonifying tactile interactions and their underlying emotions

Social touch is crucial for human well-being, as a lack of tactile interactions increases anxiety, loneliness, and need for social support. To address the detrimental effects of social isolation, we build on cutting-edge research on social touch and movement sonification to investigate whether social tactile gestures could be recognized through sounds, a sensory channel giving access to remote information. Four online experiments investigated participants’ perception of auditory stimuli that were recorded with our “audio-touch” sonification technique, which captures the sounds of touch. In the first experiment, participants correctly categorized sonified skin-on-skin tactile gestures (i.e., stroking, rubbing, tapping, hitting). In the second experiment, the audio-touch sample consisted of the sonification of six socio-emotional intentions conveyed through touch (i.e., anger, attention, fear, joy, love, sympathy). Participants categorized above chance the socio-emotional intentions of skin-on-skin touches converted into sounds and coherently rated their valence. In two additional experiments, the surface involved in the touches (either skin or plastic) was shown to influence participants’ recognition of sonified gestures and socio-emotional intentions. Thus, our research unveils that specific information about social touch (i.e., gesture, emotions, and surface) can be recognized through sounds, when they are obtained with our specific sonifying methodology. This shows significant promise for providing remote access, through the auditory channel, to meaningful social touch interactions.

GC-MS based nutritional and aroma profiling of date palm seeds collected from different Egyptian cultivars for valorization purposes

Abstract Date palm (Phoenix dactylifera L.) is a globally edible fruit and a traditional dietary component in various cultures. The fruit’s fleshy part is consumed for its nutritional value, while the seeds are discarded or valorized for oil production and as a coffee substitute. The current study aimed to investigate date seeds’ metabolome, in addition to macro- and micro-elements composition within12 major Egyptian cultivars (cvs.) for the first time using gas chromatography coupled with mass spectrometry (GC-MS). Post-silylation GC-MS analysis and headspace coupled with solid-phase microextraction (HS-SPME) were used for nutrients and aroma profiling in roasted seeds, respectively. Furthermore, multivariate data analyses were employed for samples classification and markers identification via principal component analysis (PCA) and orthogonal projection to least square discriminant analysis (OPLS-DA). Models are further validated by permutation test. Moreover, absolute quantification of potential markers was attempted based on reference standards A total of 101 and 65 nutrient and aroma metabolites were annotated, respectively. Fatty acids/esters (38 peaks), sugars (18), organic acids (17), sugar alcohols (7), steroids/triterpenoids (5), alcohols and aldehydes (6), in addition to flavonoids (1) and phenolic acids (3) were identified as major components in GC-MS post-silylation platform. ‘’Khalas’’ cv. seed appeared the most nutritive being enriched in sugars and fatty acids/esters. Moreover, date seed volatiles from different cvs. were dominated by fatty acids/esters (19 peaks), esters (6), and phenols/ethers (9). Anethole (peak 47) was the most abundant at 9.1–23.3% of seeds contributing to their unique aroma, especially ‘’Barhi’’ a premium date cv. PCA score plot of primary metabolites’ dataset revealed for 1-monopalmitin and monostearin as potential markers for ‘’Aref’’ and ‘’Khalas’’. Furthermore, ‘’Barhi’’, ‘’Omeldehn’’, and ‘’Lolo’’ cvs. showed comparable aroma profile and in partial agreement with nutrient results. OPLS-DA model revealed that anethole, estragole, methyl esters of dodecanoic acid and octanoic acid were characteristic in case of ‘’Barhi’’ cv. which are likely to impart a fine aroma and flavor. With regards to minerals, ‘’Zamli’’, ‘’Barhi’’, and ‘’Hasawi’’ cvs. were most rich in calcium, copper, and selenium, respectively. This study offers new perspectives for the phytochemical makeup and valorization potentials of date palm seeds. Fatty acids/esters and sugars were the major components in date palm seeds found enriched in ‘’Khalas’’ cv, while anethole, estragole, methyl esters of dodecanoic acid and octanoic acid were potential markers of ‘’Barhi’’ cultivar. Such extensive profiling identified premium cvs. to be considered for food applications.

Proviral insights of glycolytic enolase in <i>Bamboo mosaic virus</i> replication associated with chloroplasts and mitochondria

Diverse single-stranded RNA viruses employ different host cellular organelles or membrane systems to compartmentalize their replication intermediates and proviral factors, ensuring robust replication. Replication of Bamboo mosaic virus (BaMV), an Alphaflexiviridae family, is tightly associated with chloroplasts and dynamic cytosolic viral replication complex (VRC) clusters. BaMV VRC clusters comprise double-stranded viral RNA, BaMV replicase (Rep BaMV ), and mitochondrial outer membrane protein, voltage-dependent anion channel (VDAC). In this study, we demonstrate that host glycolytic enolase (ENO) binds to untranslated regions of BaMV RNA independently of ENO hydrolytic activity. However, the structural integrity of ENO is essential for its direct interaction with Rep BaMV , and its positive regulating role in BaMV replication and the size of BaMV VRC clusters. Additionally, ENO, pyruvate kinase (PYK), and VDAC colocalize within cytosolic BaMV VRC clusters embedded in the convoluted endomembrane reticulum (ER) along with ER-targeted viral movement proteins under BaMV infection. This association suggests that the ENO-PYK-VDAC metabolon, with ENO serving as a scaffold to link chloroplasts and mitochondria, may play a pivotal role in BaMV robust replication. Collectively, our findings offer significant insights into how glycolytic ENO acts in BaMV replication.

Cobalt, nickel and zinc spinel ferrites with high transmittance and UV-blocking for advanced optical applications

Abstract This study successfully synthesized and characterized CoFe2O4, NiFe2O4, and ZnFe2O4 ferrite nanoparticles. The results showed that CoFe2O4 and NiFe2O4 exhibited ferrimagnetic behavior, while ZnFe2O4 demonstrated antiferromagnetic properties. These magnetic characteristics influence the material’s response to electromagnetic radiation, such as visible and infrared light. Optical studies revealed that CoFe2O4 had the highest radiation absorption, while ZnFe2O4 showed superior reflection and transmission. The ferrites’ band gap energies, ranging from 3.3 to 3.6 eV, played a key role in their optical properties, with higher energy absorption and lower energy reflection. The refractive index varied with photon energy, reaching its peak at lower energy levels due to oxygen vacancies. Additionally, the optical conductivity increased with higher photon energy, peaking at 4.3 eV. These findings suggest promising applications in light transmission and sensing, with ferrites offering versatile optical properties that can be tailored for various uses.

Interspecies interactions in dual, fibrous gels enable control of gel structure and rheology

Natural and synthetic multicomponent gels display emergent properties, which implies that they are more than just the sum of their components. This warrants the investigation of the role played by interspecies interactions in shaping gel architecture and rheology. Here, using computer simulations, we investigate the effect of changing the strength of the interactions between two species forming a fibrous double network. Simply changing the strength of interspecies lateral association, we generate two types of gels: one in which the two components demix and another one in which the two species wrap around each other. We show that demixed gels have structure and rheology that are largely unaffected by the strength of attraction between the components. In contrast, architecture and material properties of intertwined gels strongly depend on interspecies “stickiness” and volume exclusion. These results can be used as the basis of a design principle for double networks which are made to emphasize either stability to perturbations or responsiveness to stimuli. Similar ideas could be used to interpret naturally occurring multicomponent gels.

Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays

Cross-feeding creates tipping points in microbiome diversity

A key unresolved question in microbial ecology is how the extraordinary diversity of microbiomes emerges from the interactions among their many functionally distinct populations. This process is driven in part by the cross-feeding networks that help to structure these systems, in which consumers use resources to fuel their metabolism, creating by-products which can be used by others in the community. Understanding the effects of cross-feeding presents a major challenge, as it creates complex interdependencies between populations which can be hard to untangle. We address this problem using the tools of network science to develop a structural microbial community model. Using methods from percolation theory, we identify feasible community states for cross-feeding network structures in which the needs of consumers are met by metabolite production across the community. We identify tipping points at which small changes in structure can cause the catastrophic collapse of cross-feeding networks and abrupt declines in microbial community diversity. Our results are an example of a well-defined tipping point in a complex ecological system and provide insight into the fundamental processes shaping microbiomes and their robustness. We further demonstrate this by considering how network attacks affect community diversity and apply our results to show how the apparent difficulty in culturing the microbial diversity emerges as an inherent property of their cross-feeding networks.

Impact of temperature shocks on household water poverty in India

Population imaging of enterochromaffin cell activity reveals regulation by somatostatin

Sensory enteroendocrine cells in the intestinal epithelium detect and relay information about the luminal environment to other cells within and outside the gut. Serotonergic enterochromaffin (EC) cells are a subset of enteroendocrine cells that detect noxious stimuli within the gut lumen, such as chemical irritants and microbial byproducts, and transduce this information to sensory nerve fibers to elicit defensive responses such as nausea and visceral pain. While much has recently been learned about the pharmacological and biophysical characteristics of EC cells, a more broadscale investigation of their properties has been hindered by their relatively low prevalence and sparse anatomical distribution within the gut epithelium. Here, we introduce a method for large-scale parallel analysis of individual EC cell activity within a physiologically relevant epithelial context. Using this approach, we identify somatostatin-28 as a potent inhibitor of both basal and stimulus-evoked serotonin release from EC cells and delineate the signaling pathway that underlies this modulatory response. Our analysis suggests that targeting this inhibitory signaling pathway may offer therapeutic avenues for treating gastrointestinal disorders associated with EC cell function and dysregulated serotonin signaling. Together with the ongoing development of specific biosensors, this platform provides a template for the efficient characterization of other rare sensory cell types and their pharmacological modulators.

Study on digging form of mechanized harvesting of Cyperus esculentus and optimization test of device parameters

De novo DUOX2 expression in neutrophil subsets shapes the pathogenesis of intestinal disease

Infiltrating neutrophils are key effector cells in inflammatory bowel disease (IBD) while providing antimicrobial defense and tissue restitution in the intestine. The complexity of neutrophil functions in local environments underscores our limited understanding of how their adaptation in tissues influences disease progression. Here, we demonstrate that neutrophils recruited in murine colitis and infection models, idiopathic IBD, and chronic granulomatous disease-associated IBD undergo extensive transcriptional reprogramming, resulting in the emergence of neutrophil populations that feature unique DUOX2 NADPH oxidase expression. Functional studies utilizing mice with myeloid and neutrophil specific DUOX2 inactivation reveal a vital and dichotomous role for this NADPH oxidase in both colitis and intestinal infection. Niche-directed reprogramming promoted a DUOX2-dependent chemokine and cytokine-rich intestinal environment that amplified and prolonged inflammatory responses, suggesting that selectively suppressing DUOX2 may constitute an anti-inflammatory strategy for IBD treatment. Altering spatiotemporal redox signaling by de novo expression of a ROS-generating enzyme represents an important feature for functional neutrophil diversification in disease, with implications for other neutrophil-driven diseases in specialized niches.

AI-IoT based smart agriculture pivot for plant diseases detection and treatment

Abstract There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) toward developing the agriculture use cases and transforming the agriculture industry into robustness and ecologically conscious. Various IoT smart agriculture techniques are escalated in this field to solve these challenges such as drop irrigation, plant diseases detection, and pest detection. Several agriculture devices were installed to perform these techniques on the agriculture field such as drones and robotics but in expense of their limitations. This paper proposes an AI-IoT smart agriculture pivot as a good candidate for the plant diseases detection and treatment without the limitations of both drones and robotics. Thus, it presents a new IoT system architecture and a hardware pilot based on the existing central pivot to develop deep learning (DL) models for plant diseases detection across multiple crops and controlling their actuators for the plant diseases treatment. For the plant diseases detection, the paper augments a dataset of 25,940 images to classify 11-classes of plant leaves using a pre-trained ResNet50 model, which scores the testing accuracy of 99.8%, compared to other traditional works. Experimentally, the F1-score, Recall, and Precision, for ResNet50 model were 99.91%, 99.92%, and 100%, respectively.

METTL3 mediates atheroprone flow–induced glycolysis in endothelial cells

Atheroprone flow–increased glycolysis in vascular endothelial cells (ECs) is pivotal in EC dysfunction and the initiation of atherosclerosis. Methyltransferase 3 (METTL3) is a major m 6 A methyltransferase for RNA N6-mehtyladenosine (m 6 A) modifications to regulate epitranscriptome and cellular functions. With the atheroprone flow upregulating METTL3 and m 6 A RNA hypermethylation, we investigate the role of METTL3 in atheroprone flow–induced glycolysis in ECs in vitro and in vivo. Compared to pulsatile shear stress (PS, atheroprotective flow), oscillatory shear stress (OS, atheroprone flow) increases METTL3 expression to enhance the m 6 A modifications of mRNAs encoding HK1, PFKFB3, and GCKR, which are rate-limiting enzymes of glycolysis. These augmented m 6 A modifications increase the expressions of HK1 and PFKFB3 while decreasing GCKR, resulting in elevated EC glycolysis, as revealed by seahorse analysis. Moreover, a stimulated Raman scattering (SRS) imaging study demonstrates the elevation of glucose incorporation into de novo synthesized lipids in ECs under atheroprone flow in vitro and in vivo. Empagliflozin, a sodium-glucose cotransporter-2 inhibitor (SGLT2i) drug, represses METTL3 expression, thereby mitigating OS-induced glycolysis in ECs. These data suggest mechanisms by which METTL3 links EC mechanotransduction with metabolic reprogramming under atherogenic conditions.

Early detection of mental health disorders using machine learning models using behavioral and voice data analysis

Abstract People of all demographics are impacted by mental illness, which has become a widespread and international health problem. Effective treatment and support for mental illnesses depend on early discovery and precise diagnosis. Notably, delayed diagnosis may lead to suicidal thoughts, destructive behaviour, and death. Manual diagnosis is time-consuming and laborious. With the advent of AI, this research aims to develop a novel mental health disorder detection network with the objective of maximum accuracy and early discovery. For this reason, this study presents a novel framework for the early detection of mental illness disorders using a multi-modal approach combining speech and behavioral data. This framework preprocesses and analyzes two distinct datasets to handle missing values, normalize data, and eliminate outliers. The proposed NeuroVibeNet combines Improved Random Forest (IRF) and Light Gradient-Boosting Machine (LightGBM) for behavioral data and Hybrid Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) for voice data. Finally, a weighted voting mechanism is applied to consolidate predictions. The proposed model achieves robust performance and a competitive accuracy of 99.06% in distinguishing normal and pathological conditions. This framework validates the feasibility of multi-modal data integration for reliable and early mental illness detection.