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Small target detection algorithm based on the fusion attention mechanism and multi-layer convolution
In the realm of unmanned aerial vehicles, we proposed an enhanced small target detection algorithm, MGAC-YOLO, to address the challenges of missed detections and low accuracy associated with small target identification. Initially, we designed the MConv (Multi-layer Convolution) module to replace the conventional Conv module within the backbone network, thereby augmenting the dimensionality of information capture and enhancing the detection performance for small targets. Subsequently, we harnessed the advantages of both attention mechanisms—GAM (Global Attention Mechanism) and CloAttention (Contextualized Local and Global Attention)—to create a GACAttention module that extracts small target features from both global and local perspectives, thereby enriching the network’s focus on small target feature information and further enhancing its feature processing capabilities. Finally, we incorporated an additional small target detection layer to capture feature information at a shallower level, thereby reducing the likelihood of missed detections and bolstering the detection capabilities for small targets. Experimental results on the VisDrone2019 dataset demonstrate that the Precision, mAP50, and mAP50-95 of the MGAC-YOLO algorithm have improved by 5.3%, 6.3%, and 4.4%, respectively, in comparison to the baseline model YOLOv8s. Furthermore, when compared to other leading algorithms, the MGAC-YOLO algorithm has exhibited notable superiority.
A framework for complex signal processing via synthetic biological operational amplifiers
Exploration of short-term predictions and long-term projections of Barents Sea cod biomass using statistical methods on data from dynamical models
This study aims to explore how well simple statistical modeling can generate short-term predictions and long-term projections of the total biomass of the Northeast Arctic stock of Atlantic cod (Gadus Morhua) inhabiting the Barents Sea. We examine the predictability of statistical models only based on hydrographic and lower trophic level biological variables from dynamical modeling. Simple and multiple linear regression models are developed based on gridded variables from the regional ocean model NEMO-NAA10km and the ecosystem model NORWECOM.E2E. This includes the essential environmental variables temperature, salinity, sea ice concentration, primary production and secondary production. The regression models are statistically evaluated to find variables that can capture variability in Barents Sea cod biomass. Finally, future total cod stock biomass is projected by applying the best found regression models to the range of downscaled IPCC climate scenarios from the coupled Intercomparison Project Phase 6 (CMIP6 Shared Socioeconomic Pathways; SSP1–2.6, SSP2–4.5, SSP5–8.5). Our prediction models are based on variables that affect cod both directly and indirectly. We find that several regression models have high prediction skill and capture the variations in total stock biomass of the Northeast Arctic cod well. Our results suggest that increased ocean temperature and abundant zooplankton may lead to a large cod stock. However, even if total stock biomass has a positive trend with an increase in copepods in the highest warming scenario SSP5–8.5, we found that it has a negative trend in the low emission scenario SSP1–2.6 when the regional ocean and ecosystem models show weak cooling and reduced zooplankton. We show that variability in essential environmental variables can provide a remarkably good first approximation to cod dynamics. However, to resolve the full picture other factors like fishing and natural mortality also need to be addressed explicitly.
Local structural distortions drive magnetic molecular field in compositionally complex spinel oxide
Reassessment of public awareness and prevention strategies for HIV and COVID-19 co-infections through epidemic modeling
A co–infection model between HIV and COVID-19 that takes into account COVID-19 vaccination and public awareness is discussed in this article. Rigorous analysis of the model is conducted to establish the existence and local stability conditions of the single-infection models. We discover that when the corresponding reproduction number for COVID-19 and HIV exceeds one, the disease continues to exist in both single-infection models. Furthermore, HIV will always be eradicated if its reproduction number is less than one. Nevertheless, this does not apply to the single-infection COVID-19 model. Even when the fundamental reproduction number is less than one, an endemic equilibrium point may exist due to the potential for a backward bifurcation phenomenon. Consequently, in the single-infection COVID-19 model, bistability between the endemic and disease-free equilibrium may arise when the basic reproduction number is less than one. From the co–infection model, we find that the reproduction number of the co–infection model is the maximum value between the reproduction number of HIV and COVID-19. Our numerical continuation experiments on the co–infection model reveal a threshold indicating that both HIV and COVID-19 may coexist within the population. The disease-free equilibrium for both HIV and COVID-19 is stable only if the reproduction numbers are less than one. Additionally, our two-parameter continuation analysis of the bifurcation diagram shows that the condition where both reproduction numbers equal one serves as an organizing center for the dynamic behavior of the co-infection model. An extended version of our model incorporates four different interventions: face mask usage, vaccination, and public awareness for COVID-19, as well as condom use for HIV, formulated as an optimal control problem. The Pontryagin’s Maximum Principle is employed to characterize the optimal control problem, which is solved using a forward-backward iterative method. Numerical investigations of the optimal control model highlight the critical role of a well-designed combination of interventions to achieve optimal reductions in the spread of both HIV and COVID-19.
Cholesterol modulates membrane elasticity via unified biophysical laws
Factors influencing the adoption of the BYOD policy in teaching hospitals: A cross-sectional study from Southeastern Iran
Introduction Clinicians are increasingly using their devices for work at hospitals, a practice known as Bring-your-own-device (BYOD), to enhance productivity and mobility. This study aimed to determine the affecting factors of intention to adoption of BYOD policy in public hospitals from the healthcare staff’s perspective. Methods A cross-sectional analytical study was done in 2024. The study population comprised 1130 healthcare workers from five teaching hospitals. A researcher-made and validated questionnaire was distributed among 620 samples. Data were analyzed by SPSS software using descriptive (mean and standard deviation) and analytical (Pearson and Spearman correlation test) statistics. Results The mean score of facilitating conditions, perceived cost-effectiveness, perceived trust, perceived usefulness, perceived ease of use, and intention to adoption BYOD was 3.90 ± 0.87, 3.87 ± 0.97, 3.83 ± 0.93, 3.76 ± 1.01, 3.07 ± 0.48 and 3.62 ± 1.16, respectively. There was a positive significant correlation between factors of perceived usefulness, perceived ease of use, perceived cost effectiveness, perceived trust, and facilitating conditions with an intention to adoption the BYOD policy (P < 0.05). Conclusion Healthcare workers have partially intended to adopt the BYOD policy. Ensuring the security of access to healthcare information, provision, support and maintenance of devices used by staff in the workplace for job-related activities can play a significant role in promoting the intention to adoption the BYOD. The results of the present study can be useful for planning and policy-making to increase the adoption and acceptance of the BYOD method in hospitals.
mRNA trafficking directs cell-size-scaling of mitochondria distribution and function
Abstract The subcellular positioning of organelles is critical to their function and is dynamically adapted to changes in cell morphology. Yet, how cells sense shifts in their dimensions and redistribute organelles accordingly remains unclear. Here we reveal that cell-size-scaling of mitochondria distribution and function is directed by polarised trafficking of mRNAs. We identify a 29 bp 3’UTR motif in mRNA encoding TRAK2, a key determinant of mitochondria retrograde transport, that promotes cell-size-dependent targeting of TRAK2 mRNA to distal sites of cell protrusions. Cell-size-scaled mRNA polarisation in turn scales mitochondria distribution by defining the precise site of TRAK2-MIRO1 retrograde transport complex assembly. Consequently, 3’UTR motif excision perturbs size-regulated transport and eradicates scaling of mitochondria positioning, triggering distal accumulation of mitochondria and progressive hypermotility as cells increase size. Together, our results reveal an RNA-driven mechanistic basis for the cell-size-scaling of organelle distribution and function that is critical to homeostatic control of motile cell behaviour.
A multi-biomarker approach to risk stratification and detection of early cardiac disease in systemic sclerosis
Objective We sought to investigate the relationship between serum biomarkers of cardiac dysfunction, longitudinal strain on echocardiography, and all-cause mortality in patients with systemic sclerosis. Methods This was an observational study using a biorepository of serum samples of patients with systemic sclerosis who underwent echocardiography. We investigated 3 biomarkers: periostin, galectin-3, and N-terminal prohormone brain natriuretic peptide and applied a K-means clustering resulting in 3 patient clusters. We subsequently measured left ventricular and right ventricular free wall longitudinal strain in each cluster. We then determined the association between each cluster and time to all-cause mortality compared to N-terminal prohormone brain natriuretic peptide, alone. Results The 125 patients with systemic sclerosis included in the study were divided into 3 clusters based on biomarker levels (Cluster 1: N = 75; Cluster 2: N = 39; Cluster 3: N = 11). Compared to Cluster 1, Cluster 2 had only elevated periostin levels whereas Cluster 3 had elevated levels of all 3 serum biomarkers and was characterized by reduced left ventricular and right ventricular free wall longitudinal strain, regionally and globally. When adjusted for age, sex, systemic sclerosis disease duration, and forced vital capacity, patients in Cluster 3 had a HR of 14.42 (95% CI: 4.82, 43.18) for all-cause mortality compared to those in Cluster 1. Conclusion In conclusion, combining N-terminal prohormone brain natriuretic peptide, periostin, and galectin-3 as serum biomarkers enhances risk stratification and sensitivity in detection of cardiac disease in patients with systemic sclerosis. However, before implementation in routine care, further prospective studies must refine biomarker sensitivity, specificity, and accuracy together with optimizing detection strategies and establishing clinical protocols for integration.
Differential impacts of social isolation and enriched environment on multi-sensory brain-wide functionality and network segregation
Correction: Identification of a disulfide bridge important for transport function of SNAT4 neutral amino acid transporter
PCSK9 drives sterol-dependent metastatic organ choice in pancreatic cancer
Non-equilibrium anti-Stokes Raman spectroscopy for investigating Higgs modes in superconductors
Abstract Even before its role in electroweak symmetry breaking, the Anderson-Higgs mechanism was introduced to explain the Meissner effect in superconductors. Spontaneous symmetry-breaking yields massless phase modes representing the low-energy excitations of the Mexican-Hat potential. Only in superconductors the phase mode is shifted towards higher energies owing to the gauge field of the charged condensate. This results in a low-energy excitation spectrum governed by the Higgs mode. Consequently, the Bardeen-Cooper-Schrieffer-like Meissner effect signifies a macroscopic quantum condensate in which a photon acquires mass, representing a one-to-one analogy to high-energy physics. We report on an innovative spectroscopic technique to study symmetries and energies of the Higgs modes in the high-temperature superconductor Bi2Sr2CaCu2O8 after a soft quench of the Mexican-Hat potential. Population inversion induced by an initial laser pulse leads to an additional anti-Stokes Raman-scattering signal, which is consistent with polarization-dependent Higgs modes. Within Ginzburg-Landau theory, the Higgs-mode energy is connected to the Cooper-pair coherence length. Within a Bardeen-Cooper-Schrieffer weak-coupling model we develop a quantitative and coherent description of single-particle and two-particle channels. This opens the avenue for Higgs Spectroscopy in quantum condensates and provides a unique pathway to control and explore Higgs physics.
Criterion-related validity of self-screening using the KOJI AWARENESS™ test for range of motion and strength in healthy participants
Objective This study aimed to establish the validity of the KOJI AWARENESS™ sub-components by determining whether there is a connection between the sub-component scores and joint range of motion, muscle strength, and balance. Methods Fifty healthy adults (17 females and 33 males) participated in the study, completing the KOJI AWARENESS™ assessments and measurements of joint range of motion, muscle strength, and balance. The range of motion of the upper and lower extremities and trunk was measured using either a goniometer or an inclinometer. A handheld dynamometer was used to measure muscle strength. Balance ability was assessed using a modified balance error scoring system. Using the Mann–Whitney U test or the Jonckheere–Terpstra test, we compared KOJI AWARENESS™ scores with the corresponding body segments at a significance level of P ≤ 0.05. Results Our results indicated associations between external references and many items; however, no associations were found for flexion, extension, and rotation of neck mobility, extension and external rotation of hip mobility, and mid-section stability strength in KOJI AWARENESS™. Conclusion Overall, the KOJI AWARENESS™ sub-component scores demonstrated good validity, except for the items related to neck and hip flexibility and trunk muscle strength. Future analyses should include a wider range of age groups, such as middle-aged and older adults.
A broad-spectrum antibiotic targets multiple-drug-resistant bacteria with dual binding targets and no detectable resistance
Unmasking the rising global burden of depression: A 32-year GBD analysis of gender disparities and regional hotspots in Sub-Saharan Africa
Aims Depression, a leading contributor to the global disease burden, exhibits alarming increases in incidence and prevalence, with pronounced disparities across regions and genders. This study provides the first comprehensive analysis of depression burden from 1990 to 2021, integrating the latest Global Burden of Disease (GBD) 2021 data to identify critical hotspots and policy-relevant trends. Methods Estimated global, regional, and national burden of disease for depression from 1990–2021 by extracting incidence, prevalence, and DALYS from the Global Burden of Disease(GBD) database 2021. Results From 1990 to 2021, the global incidence of depression surged by 15.6% (3,749–4,334 per 100,000), with Sub-Saharan Africa emerging as an unexpected epicenter. Uganda and The Gambia recorded the highest incidence rates globally (9,644 and 7,624 per 100,000, respectively), likely linked to civil instability and healthcare deficits. Women bore a disproportionate burden, with adolescent females (15–19 years) showing 64% higher incidence than males (5,584 vs. 3,401 per 100,000). High-income regions paradoxically exhibited steeper annual percentage increases (EAPC: 1.0 in North America), suggesting improved detection or escalating stressors. Conclusions This study highlights urgent priorities: (1) integrating mental health services into primary care in conflict-affected African nations. (2) gender-sensitive interventions targeting adolescent females. (3) global equity in mental health resource allocation.
RIFINs displayed on malaria-infected erythrocytes bind KIR2DL1 and KIR2DS1
Abstract Natural killer (NK) cells use inhibitory and activating immune receptors to differentiate between human cells and pathogens. Signalling by these receptors determines whether an NK cell becomes activated and destroys a target cell. In some cases, such as killer immunoglobulin-like receptors, immune receptors are found in pairs, with inhibitory and activating receptors containing nearly identical extracellular ligand-binding domains coupled to different intracellular signalling domains 1 . Previous studies showed that repetitive interspersed family (RIFIN) proteins, displayed on the surfaces of Plasmodium falciparum -infected erythrocytes, can bind to inhibitory immune receptors and dampen NK cell activation 2,3 , reducing parasite killing. However, no pathogen-derived ligand has been identified for any human activating receptor. Here we identified a clade of RIFINs that bind to inhibitory immune receptor KIR2DL1 more strongly than KIR2DL1 binds to the human ligand (MHC class I). This interaction mediates inhibitory signalling and suppresses the activation of KIR2DL1-expressing NK cells. We show that KIR2DL1-binding RIFINs are abundant in field-isolated strains from both Africa and Asia and reveal how the two RIFINs bind to KIR2DL1. The RIFIN binding surface of KIR2DL1 is conserved in the cognate activating immune receptor KIR2DS1. We find that KIR2DL1-binding RIFINs can also bind to KIR2DS1, resulting in the activation of KIR2DS1-expressing NK cells. This study demonstrates that activating killer immunoglobulin-like receptors can recruit NK cells to target a pathogen and reveals a potential role for activating immune receptors in controlling malaria infection.
RSGPT: a generative transformer model for retrosynthesis planning pre-trained on ten billion datapoints
Cryo-EM reveals an extrahelical allosteric binding site at the M5 mAChR
Abstract The M5 muscarinic acetylcholine receptor (M5 mAChR) represents a promising therapeutic target for neurological disorders. However, the high conservation of its orthosteric binding site poses significant challenges for drug development. While selective positive allosteric modulators (PAMs) offer a potential solution, a structural understanding of the M5 mAChR and its allosteric binding sites remains limited. Here, we present a 2.8 Å cryo-electron microscopy structure of the M5 mAChR complexed with heterotrimeric Gq protein and the agonist iperoxo, completing the active-state structural characterization of the mAChR family. To identify the binding site of M5-selective PAMs, we implement an integrated approach combining mutagenesis, pharmacological assays, structural biology, and molecular dynamics simulations. Our mutagenesis studies reveal that selective M5 PAMs bind outside previously characterized M5 mAChR allosteric sites. Subsequently, we obtain a 2.1 Å structure of M5 mAChR co-bound with acetylcholine and the selective PAM VU6007678, revealing an allosteric pocket at the extrahelical interface between transmembrane domains 3 and 4 that is confirmed through mutagenesis and simulations. These findings demonstrate the diverse mechanisms of allosteric regulation in mAChRs and highlight the value of integrating pharmacological and structural approaches to identify allosteric binding sites.