Small proteins can no longer be ignored.

Small proteins, here defined as proteins of 50 amino acids or fewer in the absence of processing, have traditionally been overlooked due to challenges in their annotation and biochemical detection. In the past several years, however, increasing numbers of small proteins have been identified either through the realization that mutations in intergenic regions are actually within unannotated small protein genes or through the discovery that some small, regulatory RNAs encode small proteins. These insights, together with comparative sequence analysis, indicate that tens if not hundreds of small proteins are synthesized in a given organism. This review summarizes what has been learned about the functions of several of these bacterial small proteins, most of which act at the membrane, illustrating the astonishing range of processes in which these small proteins act and suggesting several general conclusions. Important questions for future studies of these overlooked proteins are also discussed.

Cell division machinery drives cell-specific gene activation during differentiation in Bacillus subtilis.

When faced with starvation, the bacterium Bacillus subtilis transforms itself into a dormant cell type called a "spore". Sporulation initiates with an asymmetric division event, which requires the relocation of the core divisome components FtsA and FtsZ, after which the sigma factor σF is exclusively activated in the smaller daughter cell. Compartment-specific activation of σF requires the SpoIIE phosphatase, which displays a biased localization on one side of the asymmetric division septum and associates with the structural protein DivIVA, but the mechanism by which this preferential localization is achieved is unclear. Here, we isolated a variant of DivIVA that indiscriminately activates σF in both daughter cells due to promiscuous localization of SpoIIE, which was corrected by overproduction of FtsA and FtsZ. We propose that the core components of the redeployed cell division machinery drive the asymmetric localization of DivIVA and SpoIIE to trigger the initiation of the sporulation program.

Integration of graph network with kernel SVM and logistic regression for identification of biomarkers in SCA12 and its diagnosis.

Spinocerebellar ataxia type 12 is a hereditary and neurodegenerative illness commonly found in India. However, there is no established noninvasive automatic diagnostic system for its diagnosis and identification of imaging biomarkers. This work proposes a novel four-phase machine learning-based diagnostic framework to find spinocerebellar ataxia type 12 disease-specific atrophic-brain regions and distinguish spinocerebellar ataxia type 12 from healthy using a real structural magnetic resonance imaging dataset. Firstly, each brain region is represented in terms of statistics of coefficients obtained using 3D-discrete wavelet transform. Secondly, a set of relevant regions are selected using a graph network-based method. Thirdly, a kernel support vector machine is used to capture nonlinear relationships among the voxels of a brain region. Finally, the linear relationship among the brain regions is captured to build a decision model to distinguish spinocerebellar ataxia type 12 from healthy by using the regularized logistic regression method. A classification accuracy of 95% and a harmonic mean of precision and recall, i.e. F1-score of 94.92%, is achieved. The proposed framework provides relevant regions responsible for the atrophy. The importance of each region is captured using Shapley Additive exPlanations values. We also performed a statistical analysis to find volumetric changes in spinocerebellar ataxia type 12 group compared to healthy. The promising result of the proposed framework shows that clinicians can use it for early and timely diagnosis of spinocerebellar ataxia type 12.

Folate Receptor Targeting Mn(II) Complex Encapsulated Porous Silica Nanoparticle as an MRI Contrast Agent for Early-State Detection of Cancer.

Cancer is recognized as one of the major causes of mortality, however, early-stage detection can increase the survival chance greatly. It is recognized that folate receptors are gradually overexpressed in the cellular membrane with the progress of cancer from stage 1 to stage 4. Utilizing the fact, herein, developed a porous silica nanoparticle system C1@SiO2-FA-NP; A) impregnated with thermodynamically stable Mn(II) complex (1) molecules within the core of the nanoparticle, and B) surface functionalized with folate units. It exhibited a high longitudinal relaxivity value r1 = 21.45 mM-1s-1 that substantially increased to r1 = 40.97 mM-1s-1 in the presence of 0.67 mM concentration of BSA under the physiological condition. The in vitro fluorescent images after surface conjugation of C1@SiO2-FA-NP with FITC (fluorescein isothiocyanate) buttressed the inclusion of the nanoparticle exclusively within the cancerous HeLa cells than that of healthy HEK293 cells. The importance of the surface-bound folate unit in the nanoparticle is further established by comparing the fluorescent images of HeLa cells in the absence of the group. Finally, the applicability of C1@SiO2-FA-NP as the T1-weighted MRI contrast agent for early-stage cancer diagnosis is established within C57BL/6 mice after infecting the mice with HeLa cells.

A dimeric proteomimetic prevents SARS-CoV-2 infection by dimerizing the spike protein.

Protein tertiary structure mimetics are valuable tools to target large protein-protein interaction interfaces. Here, we demonstrate a strategy for designing dimeric helix-hairpin motifs from a previously reported three-helix-bundle miniprotein that targets the receptor-binding domain (RBD) of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Through truncation of the third helix and optimization of the interhelical loop residues of the miniprotein, we developed a thermostable dimeric helix-hairpin. The dimeric four-helix bundle competes with the human angiotensin-converting enzyme 2 (ACE2) in binding to RBD with 2:2 stoichiometry. Cryogenic-electron microscopy revealed the formation of dimeric spike ectodomain trimer by the four-helix bundle, where all the three RBDs from either spike protein are attached head-to-head in an open conformation, revealing a novel mechanism for virus neutralization. The proteomimetic protects hamsters from high dose viral challenge with replicative SARS-CoV-2 viruses, demonstrating the promise of this class of peptides that inhibit protein-protein interaction through target dimerization.

Explainable lung cancer classification with ensemble transfer learning of VGG16, Resnet50 and InceptionV3 using grad-cam.

Medical imaging stands as a critical component in diagnosing various diseases, where traditional methods often rely on manual interpretation and conventional machine learning techniques. These approaches, while effective, come with inherent limitations such as subjectivity in interpretation and constraints in handling complex image features. This research paper proposes an integrated deep learning approach utilizing pre-trained models-VGG16, ResNet50, and InceptionV3-combined within a unified framework to improve diagnostic accuracy in medical imaging. The method focuses on lung cancer detection using images resized and converted to a uniform format to optimize performance and ensure consistency across datasets. Our proposed model leverages the strengths of each pre-trained network, achieving a high degree of feature extraction and robustness by freezing the early convolutional layers and fine-tuning the deeper layers. Additionally, techniques like SMOTE and Gaussian Blur are applied to address class imbalance, enhancing model training on underrepresented classes. The model's performance was validated on the IQ-OTH/NCCD lung cancer dataset, which was collected from the Iraq-Oncology Teaching Hospital/National Center for Cancer Diseases over a period of three months in fall 2019. The proposed model achieved an accuracy of 98.18%, with precision and recall rates notably high across all classes. This improvement highlights the potential of integrated deep learning systems in medical diagnostics, providing a more accurate, reliable, and efficient means of disease detection.

Advanced AI-driven approach for enhanced brain tumor detection from MRI images utilizing EfficientNetB2 with equalization and homomorphic filtering.

Brain tumors pose a significant medical challenge necessitating precise detection and diagnosis, especially in Magnetic resonance imaging(MRI). Current methodologies reliant on traditional image processing and conventional machine learning encounter hurdles in accurately discerning tumor regions within intricate MRI scans, often susceptible to noise and varying image quality. The advent of artificial intelligence (AI) has revolutionized various aspects of healthcare, providing innovative solutions for diagnostics and treatment strategies. This paper introduces a novel AI-driven methodology for brain tumor detection from MRI images, leveraging the EfficientNetB2 deep learning architecture. Our approach incorporates advanced image preprocessing techniques, including image cropping, equalization, and the application of homomorphic filters, to enhance the quality of MRI data for more accurate tumor detection. The proposed model exhibits substantial performance enhancement by demonstrating validation accuracies of 99.83%, 99.75%, and 99.2% on BD-BrainTumor, Brain-tumor-detection, and Brain-MRI-images-for-brain-tumor-detection datasets respectively, this research holds promise for refined clinical diagnostics and patient care, fostering more accurate and reliable brain tumor identification from MRI images. All data is available on Github: https://github.com/muskan258/Brain-Tumor-Detection-from-MRI-Images-Utilizing-EfficientNetB2 ).

Grasping at origins.

Chromosome segregation in the bacterium Caulobacter crescentus involves propulsion of the replication origin and its capture at one pole of the cell. Bowman et al. (2008) and Ebersbach et al. (2008) now report the discovery of a protein called PopZ that mediates this chromosome capture.

Melanocortin-4 receptor and proopiomelanocortin: Candidate genes for obesity in domestic shorthair cats.

Obesity is an escalating global health problem affecting both humans and companion animals. In cats it is associated with increased mortality and multiple diseases, including diabetes mellitus. Two genes coding for proteins known to play a critical role in energy homeostasis across species are the proopiomelanocortin (POMC) gene and the melanocortin-4 receptor (MC4R) gene. A missense variant in the coding sequence of the feline MC4R (MC4R:c.92C>T) has been reported to be associated with diabetes and overweight in domestic shorthair cats, and while variants in the POMC gene are known to cause obesity in humans and dogs, variants in POMC and their association with feline obesity and diabetes mellitus have not been investigated to date. The current study aimed to assess the association between the previously described MC4R variant and body condition score (BCS), as well as body fat content (%BF) in 89 non-diabetic domestic shorthair cats. Furthermore, we investigated the feline POMC gene as a potential candidate gene for obesity. Our results indicate that the MC4R:c.92C>T polymorphism is not associated with BCS or %BF in non-diabetic domestic shorthair cats. The mutation analysis of all POMC exons identified two missense variants, with a variant in exon 1 (c.28G>C; p.G10R) predicted to be damaging. The variant was subsequently assessed in all 89 cats, and cats heterozygous for the variant had a significantly increased body condition score (p = 0.03) compared with cats homozygous for the wild-type allele. Results from our study provide additional evidence that the previously described variant in MC4R is not associated with obesity in domestic shorthair cats. More importantly, we have identified a novel variant in the POMC gene, which might play a role in increased body condition score and body fat content in domestic shorthair cats.

How bacteria block their own biofilms.

Bacterial biofilms are surface-associated multicellular communities that are highly resistant to removal. Scheffler et al. discovered that Pseudomonas aeruginosa secretes a small molecule that inhibits other P. aeruginosa cells from adsorbing to surfaces by interfering with type IV pili dynamics. The inhibition of cell adsorption could present a method to prevent biofilm formation on sensitive surfaces in hospitals and industry.

Molecular mechanism of selective substrate engagement and inhibitor disengagement of cysteine synthase.

O-acetyl serine sulfhydrylase (OASS), referred to as cysteine synthase (CS), synthesizes cysteine from O-acetyl serine (OAS) and sulfur in bacteria and plants. The inherent challenge for CS is to overcome 4 to 6 log-folds stronger affinity for its natural inhibitor, serine acetyltransferase (SAT), as compared with its affinity for substrate, OAS. Our recent study showed that CS employs a novel competitive-allosteric mechanism to selectively recruit its substrate in the presence of natural inhibitor. In this study, we trace the molecular features that control selective substrate recruitment. To generalize our findings, we used CS from three different bacteria (Haemophilus, Salmonella, and Mycobacterium) as our model systems and analyzed structural and substrate-binding features of wild-type CS and its ∼13 mutants. Results show that CS uses a noncatalytic residue, M120, located 20 Šaway from the reaction center, to discriminate in favor of substrate. M120A and background mutants display significantly reduced substrate binding, catalytic efficiency, and inhibitor binding. Results shows that M120 favors the substrate binding by selectively enhancing the affinity for the substrate and disengaging the inhibitor by 20 to 286 and 5- to 3-folds, respectively. Together, M120 confers a net discriminative force in favor of substrate by 100- to 858-folds.

Cytoskeletal proteins: lessons learned from bacteria.

Cytoskeletal proteins are classified as a group that is defined functionally, whose members are capable of polymerizing into higher order structures, either dynamically or statically, to perform structural roles during a variety of cellular processes. In eukaryotes, the most well-studied cytoskeletal proteins are actin, tubulin, and intermediate filaments, and are essential for cell shape and movement, chromosome segregation, and intracellular cargo transport. Prokaryotes often harbor homologs of these proteins, but in bacterial cells, these homologs are usually not employed in roles that can be strictly defined as 'cytoskeletal'. However, several bacteria encode other proteins capable of polymerizing which, although they do not appear to have a eukaryotic counterpart, nonetheless appear to perform a more traditional 'cytoskeletal' function. In this review, we discuss recent reports that cover the structures and functions of prokaryotic proteins that are broadly termed as cytoskeletal, either by sequence homology or by function, to highlight how the enzymatic properties of traditionally studied cytoskeletal proteins may be used for other types of cellular functions; and to demonstrate how truly 'cytoskeletal' functions may be performed by uniquely bacterial proteins that do not display homology to eukaryotic proteins.

Bacterial Cell Division: Nonmodels Poised to Take the Spotlight.

The last three decades have witnessed an explosion of discoveries about the mechanistic details of binary fission in model bacteria such as Escherichia coli, Bacillus subtilis, and Caulobacter crescentus. This was made possible not only by advances in microscopy that helped answer questions about cell biology but also by clever genetic manipulations that directly and easily tested specific hypotheses. More recently, research using understudied organisms, or nonmodel systems, has revealed several alternate mechanistic strategies that bacteria use to divide and propagate. In this review, we highlight new findings and compare these strategies to cell division mechanisms elucidated in model organisms.

Improved Measurement of Solar Neutrinos from the Carbon-Nitrogen-Oxygen Cycle by Borexino and Its Implications for the Standard Solar Model.

We present an improved measurement of the carbon-nitrogen-oxygen (CNO) solar neutrino interaction rate at Earth obtained with the complete Borexino Phase-III dataset. The measured rate, R_{CNO}=6.7_{-0.8}^{+2.0} counts/(day×100 tonnes), allows us to exclude the absence of the CNO signal with about 7σ C.L. The correspondent CNO neutrino flux is 6.6_{-0.9}^{+2.0}×10^{8} cm^{-2} s^{-1}, taking into account the neutrino flavor conversion. We use the new CNO measurement to evaluate the C and N abundances in the Sun with respect to the H abundance for the first time with solar neutrinos. Our result of N_{CN}=(5.78_{-1.00}^{+1.86})×10^{-4} displays a ∼2σ tension with the "low-metallicity" spectroscopic photospheric measurements. Furthermore, our result used together with the ^{7}Be and ^{8}B solar neutrino fluxes, also measured by Borexino, permits us to disfavor at 3.1σ C.L. the "low-metallicity" standard solar model B16-AGSS09met as an alternative to the "high-metallicity" standard solar model B16-GS98.

First Directional Measurement of Sub-MeV Solar Neutrinos with Borexino.

We report the measurement of sub-MeV solar neutrinos through the use of their associated Cherenkov radiation, performed with the Borexino detector at the Laboratori Nazionali del Gran Sasso. The measurement is achieved using a novel technique that correlates individual photon hits of events to the known position of the Sun. In an energy window between 0.54 to 0.74 MeV, selected using the dominant scintillation light, we have measured 10 887_{-2103}^{+2386}(stat)±947(syst) (68% confidence interval) solar neutrinos out of 19 904 total events. This corresponds to a ^{7}Be neutrino interaction rate of 51.6_{-12.5}^{+13.9} counts/(day·100 ton), which is in agreement with the standard solar model predictions and the previous spectroscopic results of Borexino. The no-neutrino hypothesis can be excluded with >5σ confidence level. For the first time, we have demonstrated the possibility of utilizing the directional Cherenkov information for sub-MeV solar neutrinos, in a large-scale, high light yield liquid scintillator detector. This measurement provides an experimental proof of principle for future hybrid event reconstruction using both Cherenkov and scintillation signatures simultaneously.

Surface treated Phoenix sylvestris for bioadsorption of oil from aqueous solution: Isotherms and kinetic studies.

Biosorption is a versatile technique of removing the oil spill - one of the major toxicants that causes water pollution, which threatens the ecological balance of the aquatic ecosystem. The proposed research aims in developing a viable adsorbent from discarded agricultural waste, Phoenix sylvestris, which was surface altered, assessed and utilised as a biosorbent for the effective removal of diesel from aqueous solution in batch adsorption trials. Waste palm leaves, Phoenix sylvestris (RPS)was physically (PMPS) and chemically modified (CMPS) to adsorb diesel in the emulsion. The synthesised materials were characterised by FTIR, SEM, and EDS, confirming a well-defined microporous structure consisting of ionisable groups. The studies indicated optimised conditions of 10 g, 4.5 g and 2 g of RPS, PMPS and CMPS respectively at 303K for an optimised adsorption time of 60 min. Freundlich isotherm agreed well with experimental data, and the kinetic mechanism claimed better results with RPS, PMPS and CMPS for Pseudo first-order model. The adsorbents could be reused five times without much loss of efficiency. From the performed studies, it can be inferred that good adsorption capacities at optimised conditions followed the order of CMPS > PMPS > RPS. Thermodynamic analysis proved the feasibility of such biosorption with exothermic nature predicting spontaneous attraction of oil components to the surface of PMPS and CMPS. Moreover, the density of the CMPS layer rendered proven results for such biosorption displaying a hyperbolic dependency assuring its efficacy. Hence, it can be concluded that the prepared adsorbent from Phoenix sylvestris, an agricultural waste, possess good adsorptive properties.

A 2-dimensional ratchet model describes assembly initiation of a specialized bacterial cell surface.

Bacterial spores are dormant cells that are encased in a thick protein shell, the "coat," which participates in protecting the organism's DNA from environmental insults. The coat is composed of dozens of proteins that assemble in an orchestrated fashion during sporulation. In Bacillus subtilis, 2 proteins initiate coat assembly: SpoVM, which preferentially binds to micron-scale convex membranes and marks the surface of the developing spore as the site for coat assembly; and SpoIVA, a structural protein recruited by SpoVM that uses ATP hydrolysis to drive its irreversible polymerization around the developing spore. Here, we describe the initiation of coat assembly by SpoVM and SpoIVA. Using single-molecule fluorescence microscopy in vivo in sporulating cells and in vitro on synthetic spores, we report that SpoVM's localization is primarily driven by a lower off-rate on membranes of preferred curvature in the absence of other coat proteins. Recruitment and polymerization of SpoIVA results in the entrapment of SpoVM on the forespore surface. Using experimentally derived reaction parameters, we show that a 2-dimensional ratchet model can describe the interdependent localization dynamics of SpoVM and SpoIVA, wherein SpoVM displays a longer residence time on the forespore surface, which favors recruitment of SpoIVA to that location. Localized SpoIVA polymerization in turn prevents further sampling of other membranes by prelocalized SpoVM molecules. Our model therefore describes the dynamics of structural proteins as they localize and assemble at the correct place and time within a cell to form a supramolecular complex.

Structural and white matter changes associated with duration of Braille education in early and late blind children.

In early (EB) and late blind (LB) children, vision deprivation produces cross-modal plasticity in the visual cortex. The progression of structural- and tract-based spatial statistics changes in the visual cortex in EB and LB, as well as their impact on global cognition, have yet to be investigated. The purpose of this study was to determine the cortical thickness (CT), gyrification index (GI), and white matter (WM) integrity in EB and LB children, as well as their association to the duration of blindness and education. Structural and diffusion tensor imaging data were acquired in a 3T magnetic resonance imaging in EB and LB children (n = 40 each) and 30 sighted controls (SCs) and processed using CAT12 toolbox and FSL software. Two sample t-test was used for group analyses with P < 0.05 (false discovery rate-corrected). Increased CT in visual, sensory-motor, and auditory areas, and GI in bilateral visual cortex was observed in EB children. In LB children, the right visual cortex, anterior-cingulate, sensorimotor, and auditory areas showed increased GI. Structural- and tract-based spatial statistics changes were observed in anterior visual pathway, thalamo-cortical, and corticospinal tracts, and were correlated with education onset and global cognition in EB children. Reduced impairment in WM, increased CT and GI and its correlation with global cognitive functions in visually impaired children suggests cross-modal plasticity due to adaptive compensatory mechanism (as compared to SCs). Reduced CT and increased FA in thalamo-cortical areas in EB suggest synaptic pruning and alteration in WM integrity. In the visual cortical pathway, higher education and the development of blindness modify the morphology of brain areas and influence the probabilistic tractography in EB rather than LB.

Frontal lobe metabolic alterations characterizing Parkinson's disease cognitive impairment.

BACKGROUND AND PURPOSE: Diagnosis of Parkinson's disease (PD) cognitive impairment at early stages is challenging compared to the stage of PD dementia where functional impairment is apparent and easily diagnosed. Hence, to evaluate potential early stage cognitive biomarkers, we assessed frontal lobe metabolic alterations using in vivo multi-voxel proton magnetic resonance spectroscopic imaging (1H-MRSI). METHOD: Frontal metabolism was studied in patients with PD with normal cognition (PD-CN) (n = 26), with cognitive impairment (PD-CI) (n = 27), and healthy controls (HC) (n = 30) using a single slice (two-dimensional) 1H-MRSI at 3 T. The acquired spectra were post-processed distinctly for voxels corresponding to the bilateral middle/superior frontal gray matter (GM) and frontal white matter (WM) regions (delineated employing neuromorphometrics atlas) using the LC-Model software. RESULT: Significant (post hoc p < 0.016) reduction in the concentration of N-acetyl aspartate (NAA) in the middle and superior frontal GMs and total choline (tCho) and total creatine (tCr) in the frontal WM was observed in PD-CI compared to PD-CN and HC, while that in HC and PD-CN groups were comparable. The NAA and tCr/tCho metabolite concentrations showed significant (p < 0.05) positive correlations with cognitive test scores in the frontal GM and WM, respectively. The receiver operating curve (ROC) analysis revealed significant (p < 0.05) "area under curve" for NAA/tNAA in the frontal GM and tCho in the frontal WM. CONCLUSION: The frontal metabolic profile is altered in cognitively impaired PD compared with cognitively normal PD. Neuronal function loss (NAA), altered energy metabolism (Cr), and cholinergic (Cho) neural transmission are implicated in PD cognitive pathology. Frontal neuro-metabolism may promisingly serve as PD cognitive biomarker.

Visual Cortex Alterations in Early and Late Blind Subjects During Tactile Perception.

Involvement of visual cortex varies during tactile perception tasks in early blind (EB) and late blind (LB) human subjects. This study explored differences in sensory motor networks associated with tactile task in EB and LB subjects and between children and adolescents. A total of 40 EB subjects, 40 LB subjects, and 30 sighted controls were recruited in two subgroups: children (6-12 years) and adolescents (13-19 years). Data were acquired using a 3T MR scanner. Analyses of blood oxygen level dependent (BOLD), functional connectivity (FC), correlation, and post hoc test for multiple comparisons were carried out. Difference in BOLD activity was observed in EB and LB groups in visual cortex during tactile perception, with increased FC of visual with dorsal attention and sensory motor networks in EB. EB adolescents exhibited increased connectivity with default mode and salience networks when compared with LB. Functional results correlated with duration of training, suggestive of better performance in EB. Alteration in sensory and visual networks in EB and LB correlated with duration of tactile training. Age of onset of blindness has an effect in cross-modal reorganization of visual cortex in EB and multimodal in LB in children and adolescents.