Search Results (275)

We have used long observations of galaxy clusters obtained with the Rossi X-ray Timing Explorer to search for the 3.55 keV line from sterile neutrino decay. If a lepton-number asymmetry exists in one or more types of active neutrinos in the early Universe, sterile neutrinos can be produced via the Shi–Fuller mechanism. The data consist of 11 clusters observed for a total of 3.1 megaseconds using the Proportional Counter Array. A 2.5$\sigma$ excess of emission over a thermal model is found over the energy span of the 3.55 keV line in the combined spectra of the eight clusters that individually have an excess. These residuals are added to increase the signal to noise ratio of the excess, which is then modeled with a Gaussian to simulate the instrumental spectral response. We find a significant correlation (r = 0.76) for a line centered at 3.6 keV with a model flux of 3.07 × 10⁻⁵ ph cm⁻² s⁻¹. Mixing angle for detected clusters ranges from 2.0 to 21.6 × 10⁻¹⁰. The decay rate inferred from the line flux is strongly correlated (r = 0.87) with cluster temperature, which is due to hotter, more massive clusters having a larger amount of dark matter. Approximately half of the total flux comes from the Coma cluster. The mixing angle for Coma is calculated to be 6.2 × 10⁻¹⁰. We fit the Coma cluster spectrum with two different three-component models. The first includes a Gaussian fixed at 3.55 keV to model soft emission. The flux of the Gaussian is 5.6 × 10⁻¹² ph cm⁻² s⁻¹ or 1.3% of the total flux. The second three-component model uses a second thermal component to model soft emission. This model gives a temperature of 0–17 keV for the second thermal component and a lower temperature for the hot component. This indicates that the second thermal component is modeling high-energy residuals rather than low ones, where the Gaussian is. Though our line fluxes exceed most reported detections and upper limits, they do not overproduce the dark matter. We conclude that some fraction of the marginally detected excess could be attributed to the decay line since low-temperature thermal emission and systematics fail to model it completely. Full article

Chronic crop diseases caused by uncultured, obligate, or host-dependent pathogens challenge traditional pathogen-centric paradigms that often interpret symptoms as direct outcomes of pathogen toxins, effectors, or tissue colonization. Here, we advance a host-centric immune framework that reframes disease as an emergent consequence of dysregulated host immune network activity, including prolonged activation, signaling miscoordination, and systemic physiological disruption. Using citrus huanglongbing (HLB) as a primary exemplar and canola clubroot as a parallel system, we synthesize evidence that persistent immune stimulation can drive self-damaging outputs, including sustained reactive oxygen species accumulation, chronic vascular and transport dysfunction, hormone imbalance, and growth–defense trade-offs. While many observations derive from transcriptomic, physiological, and genetic studies conducted under controlled experimental conditions, the available evidence collectively suggests that persistent immune activation may contribute substantially to disease-associated decline in these systems. We argue that pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) operate as an integrated immune network whose feedback structure can become destabilized under chronic infection, generating immune states that are simultaneously harmful and often ineffective at pathogen clearance. We further discuss how panomic profiling, spatially resolved analyses, and network inference can diagnose host immune states at tissue and cell-type resolution, and how genome editing enables causal tests and rational immune tuning strategies that optimize defense amplitude, timing, and localization rather than indiscriminately amplifying resistance. By centering the host immune system as both a source of protection and pathology, this framework provides a conceptual and practical roadmap for understanding and engineering resilience in HLB, clubroot, and other chronic crop diseases in which pathogen biology remains experimentally opaque. Full article

People in midlife interact with several different environments during their daily life including employment, leisure, commuting, and various family responsibilities, a concept defined as activity space. However, little is known about how these activity spaces contribute to individuals’ daily health behavior choices. The Everyday Environments and Experiences (E3) study was conducted to explore these relationships. In this paper, we provide a reproducible GPS processing workflow to generate time-weighted exposure measures (activity spaces) inferred from 21 days of continuous GPS monitoring among 340 midlife adults in Cook County, Illinois (n = 340) from the E3 study. Data from waist-mounted GPS devices that recorded one-minute location epochs were aggregated after excluding time spent within an 800 m buffer around the home. For each epoch, we derived proximity and kernel density measures for eleven food and physical-activity-related location types (e.g., supermarkets, fitness facilities), along with twenty-six environmental context variables (e.g., land use, crime, population density). Time-weighted averages characterized each participant’s typical non-home environmental exposure. After adjustment for environmental context, age and gender were generally unrelated to activity-space measures. However, Black and Hispanic participants (as compared to White participants) spent less time near both food and physical-activity resources, suggesting systemic inequities in access beyond neighborhood composition. These findings highlight the need to move beyond static residential measures toward time-weighted, dynamic assessments of environmental exposure. They also indicate that racial and ethnic disparities in routine activity space may reflect structural inequities shaping daily physical activity and access to healthy food. Future research is needed to explore how these observed disparities translate into differences into disease risk, using longer exposure periods and different geographic settings to identify causal pathways and inform multi-level interventions. Full article

Purpose: Castration-resistant prostate cancer (CRPC) responds poorly to conventional chemotherapy. We evaluated a cell-based enzyme–prodrug therapy using adipose-derived stem cells (ADSCs) engineered to express cytosine deaminase (CD) or carboxylesterase 2 (CE2), paired with their respective prodrugs 5-fluorocytosine (5-FC) or irinotecan (CPT-11), to compare their antitumor efficacy. Materials and Methods: Human telomerase reverse transcriptase (hTERT)-immortalized ADSCs were transduced with CD or CE2, and transgene expression and stem cell phenotype were confirmed. CD expression was verified at the transcript level and by functional 5-FC-to-5-fluorouracil (5-FU) conversion, whereas CE2 expression was verified by transcript analysis and immunoblotting. Tumor tropism toward PC3 prostate cancer cells was tested using migration assays and analysis of chemoattractant ligand/receptor expression. Prodrug-induced self-killing and bystander tumor cell killing were assessed through viability assays and co-culture with PC3 cells. For the CE2/CPT-11 system, SN-38 was not directly quantified; functional activity was inferred from prodrug-dependent cytotoxicity and in vivo efficacy. In vivo efficacy was evaluated in nude mice with PC3 tumors treated systemically with engineered ADSCs plus prodrug. Results: CD- and CE2-expressing ADSCs were successfully established and retained mesenchymal stem cell (MSC) characteristics. Both cell types exhibited significant migration toward PC3 cells. The CE2/CPT-11 system produced stronger prodrug-mediated cytotoxicity than CD/5-FC, with CE2-modified ADSCs showing higher sensitivity to CPT-11 and inducing greater apoptosis in co-cultured PC3 cells. In vivo, both treatments suppressed tumor growth, but CE2/CPT-11 achieved greater inhibition (tumor volume ~26% of control vs. ~32% for CD/5-FC at day 14). No overt clinical toxicity was observed based on body weight and daily clinical monitoring; however, hematology/serum chemistry were not assessed. Conclusions: Engineered ADSCs home to CRPC tumors and enable local prodrug activation, producing significant antitumor effects. Within the constraints of our in vitro assays and subcutaneous xenograft model, CE2/CPT-11 demonstrated stronger efficacy outcomes than CD/5-FC. Mechanistic attribution to intratumoral SN-38 exposure should be confirmed by direct metabolite measurements in future studies. Full article

The safety-critical nature of aircraft landing gear has led to interest in Structural Health Monitoring (SHM) and Remaining Useful Life (RUL) methodologies for the fatigue substantiation of landing gear assemblies. Due to the engineering effort that can be required to implement such approaches, it is prudent to target SHM and RUL activities at specific aircraft fleets. This paper employs air traffic data in the form of Automatic Dependent Surveillance-Broadcast (ADS-B) data to characterise the occurrence and severity of ground turns performed across fleets of differing aircraft type, location and operator characteristics. From the evaluation of 3250 flights, it was observed at the fleet level that ground turn characteristics show limited sensitivity to the aircraft’s geographical location and operator characteristics, excluding cargo aircraft and those operated by Ultra-Low-Cost Carriers. However, assessment of individual aircraft highlighted that the occurrence rate of fatigue-critical pivot turns can exceed twice that of the remaining aircraft fleet, suggesting that SHM and RUL activities should be focused on aircraft that deviate significantly from the expected fleet-wide behaviour. Finally, this paper presents an initial investigation into inferring the Nose Wheel Steering angle provided from Quick Access Recorder flight data directly from ADS-B trajectories. Full article

Periodontal disease and oral squamous cell carcinoma (OSCC) are highly prevalent conditions that contribute substantially to global morbidity, as documented by recent Global Burden of Disease analyses. The growing epidemiologic and experimental literature has prompted interest in potential links between chronic periodontal dysbiosis—particularly infection with Porphyromonas gingivalis—and molecular pathways involved in oral carcinogenesis, including β-catenin signaling. This narrative review synthesizes epidemiologic, clinical, and experimental studies examining associations between periodontal disease, P. gingivalis, and OSCC, with focused evaluation of β-catenin as a context-dependent signaling component within broader inflammatory and metabolic networks. Population-based studies report heterogeneous associations between periodontitis and OSCC that are frequently confounded by tobacco use, alcohol consumption, and socioeconomic factors, supporting correlation rather than causal inference. Experimental investigations in vitro and in vivo demonstrate that P. gingivalis can influence β-catenin availability and transcriptional activity through noncanonical mechanisms, including junctional disruption, proteolytic interference with regulatory complexes, and interaction with inflammatory, immune, and metabolic pathways. However, these findings derive largely from simplified model systems and should be interpreted as biologically plausible rather than definitive for human disease. Rather than acting as a dominant oncogenic driver, β-catenin appears to function as an integrative signaling node within a complex network shaped by chronic microbial and inflammatory stress. The principal contribution of this review lies in critically integrating dispersed evidence across study types while explicitly distinguishing association, mechanistic plausibility, and causality. Future longitudinal human studies and mechanistically informed experimental models are required to clarify whether modulation of periodontal dysbiosis or associated signaling pathways has relevance for OSCC risk assessment or prevention. Full article

Ferroptosis is an iron-dependent programmed cell death (PCD) implicated in cancer therapy response, yet its transcriptional control remains unevenly characterized and often centered on a limited subset of transcription factors (TFs) rather than systematically addressing TF families. The Activating enhancer-binding Protein-2 (AP-2) family of TFs is a plausible but understudied regulatory node linking oncogenic programs to ferroptosis, with prior research limited to AP-2α and AP-2γ, suggesting anti-ferroptotic and pro-tumorigenic roles. Thus, the present study aimed to provide a family-wide analysis of the relationships between AP-2 and ferroptosis across tumors in which this PCD type is considered biologically and clinically relevant. The research integrates ferroptosis gene modules with AP-2 targetomes, tumor–normal expression comparisons, survival stratification, ferroptosis scoring, cross-cohort functional analyses, and signaling pathway projection extending canonical ferroptosis circuits with AP-2–associated non-canonical elements. Consistent associations between AP-2 expression, prognosis, and ferroptosis score were observed in five tumor cohorts: cervical squamous cell carcinoma, glioblastoma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, and thyroid carcinoma. In addition, cross-cohort clustering highlighted genes enriched in redox- and lipid-metabolism programs linked to apoptosis and autophagy-dependent death. Among the candidates emerging from these analyses, ferroptotic markers (LOX, PTGS2, and NQO1) and AP-2–linked nodes such as CD36, DUOX1, EPHA2, MUC1, PTPRC, SNAI2, and TP63 warrant targeted functional and binding validation to infer whether these associations reflect direct AP-2 regulatory mechanisms. Most importantly, AP-2–centered research appears to be a valuable area for guiding studies of tumor-specific ferroptosis vulnerability or resistance. Full article

Background: Psychosocial well-being has been increasingly recognized as a relevant factor in cardiometabolic health; however, evidence linking Purpose in Life with type 2 diabetes risk across validated prediction tools remains limited. This study examined the association between Purpose in Life and estimated diabetes risk using three established risk scores. Methods: A cross-sectional analysis was performed in 93,077 Spanish working adults aged 18–69 years participating in routine occupational health assessments. Purpose in Life was measured with the 10-item Purpose in Life scale and categorized into high, moderate, and low levels. Estimated type 2 diabetes risk was evaluated using QDScore, FINDRISC, and CANRISK. Multivariable logistic regression models were applied to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for age, sex, occupational social class, smoking status, dietary pattern, physical activity, and body mass index. Results: Lower levels of Purpose in Life were consistently associated with greater likelihood of high estimated diabetes risk across all three instruments. Compared with participants reporting high Purpose in Life, those with low Purpose in Life showed increased odds of high-risk classification for QDScore (OR 2.38; 95% CI 2.19–2.57), FINDRISC (OR 2.49; 95% CI 2.08–2.89), and CANRISK (OR 2.79; 95% CI 2.50–3.09). Clear dose–response patterns were observed across Purpose in Life categories, and associations were similar in men and women as well as across lifestyle strata. Conclusions: Reduced Purpose in Life is strongly associated with higher estimated type 2 diabetes risk across multiple validated screening tools. Although causal direction cannot be inferred from this cross-sectional design, these findings suggest that psychosocial dimensions may provide complementary information for cardiometabolic risk assessment and prevention strategies. Full article

Background/Objectives: The primary outcome of this 8-week randomized, controlled, parallel trial was to assess longitudinal shifts in gut microbiota structure and predicted metabolic potential in 45 elite football players following protein supplementation. Methods: Participants combined resistance training with daily intake (30 g) of whey protein concentrate (WPC), pea protein isolate (PPI), rice protein isolate (RPI), or a plant-protein blend (MIX). For the acquisition of prokaryotic metataxonomic data, the V3–V8 region of the 16S rRNA gene was sequenced using Oxford Nanopore Technology (ONT). Functional potential was inferred through the MACADAM database and STAMP software. Strict dietary monitoring and gravimetric adherence checks were performed to isolate the intervention effect. Results: While microbial alpha-diversity indices (Chao1, Shannon, Simpson) remained stable across all groups, significant source-specific shifts in taxonomic structure and predicted metabolic activity were identified. Whey protein concentrate (WPC) was associated with an increase in Bacteroidetes abundance and greater balance within the microbial community structure, whereas pea protein isolate (PPI) and the MIX correlated with reduced fermentative bacteria and elevated taxa potentially involved in cadaverine biosynthesis. Rice protein isolate (RPI) supplementation was associated with a higher predicted representation of taxa involved in succinate-to-butyrate fermentation pathways. These functional markers and differential responses of selected bacterial groups to particular protein types were observed. Conclusions: The data indicate complex interactions between supplement type, exposure duration, and microbiome response, underscoring the necessity for individualized dietary recommendations and supplementation strategies to optimize gut health and training adaptation in professional football players. Full article

Background: Three-finger toxins (3FTxs) are a major axis of functional diversification in advanced snake venoms, with canonical paralytic activity mediated through muscle-type nicotinic acetylcholine receptors (nAChRs) and a broader set of non-nicotinic targets. This review integrates evidence bearing on coevolution between 3FTxs and target receptors, spanning toxin origin, diversification, receptor evolution, and ecological context. Methods: The synthesis draws on comparative genomic and transcriptomic studies of 3FTx gene-family evolution, codon-model analyses of selection, structural characterisation of toxin–receptor interfaces, and functional assays (including receptor-mimicking peptide binding) that link sequence variation to binding and toxicity. Results: Across lineages, 3FTx diversification is repeatedly structured by strong constraint on the disulphide-rich scaffold with accelerated change concentrated in solvent-exposed loops, alongside birth–death dynamics and exon/segment-level innovation that expand binding specificity. On the receptor side, resistance-associated variation is most intensively characterised for the nAChR α₁ orthosteric site and includes convergent, mechanistically distinct solutions such as electrostatic repulsion and glycosylation-mediated steric interference. Within the predominantly elapid systems currently examined, integrative datasets indicate that prey-selective binding and geographically variable susceptibility can arise from modest substitutions at toxin–receptor interfaces, but they also reveal substantial taxonomic and target-specific biases. Conclusions: Current evidence supports adaptive diversification in both toxins and receptors, while broader evolutionary interpretations are limited by uneven sampling and the frequent lack of matched toxin and receptor variants analysed within a common evolutionary framework. Development of predictive models will require joint pipelines linking genomics, structure-informed evolutionary inference, scalable functional assays, and explicit ecological network context. Full article

Carotid plaque classification based on ultrasound echogenicity and quantification of plaque burden are crucial in stroke risk assessment. In this work, we propose a framework that leverages the synergy between classification and segmentation by sharing plaque location information to enhance the performance of both tasks. Our cascaded framework integrates a ResNet-based classifier (Masked-ResNet-DS) with MedSAM, a medically adapted version of the Segment Anything Model for joint classification and segmentation of carotid plaques from 2D ultrasound images. Ground truth boundaries are used to guide region-specific feature pooling in the classifier, helping it focus on plaques during training. Since ground truth boundaries are unavailable at inference, we introduce a two-iteration strategy: the first generates a class activation map (CAM), which is then used for focused pooling in the second iteration to predict plaque type. The CAM is also used as a prompt to guide MedSAM for segmentation. To ensure accurate localization, the CAM is supervised during training using a Dice loss against the segmentation ground truth. Masked-ResNet-DS achieves a mean F1-score of 96.7% in plaque classification, at least 3.2% higher than competing methods. Ablation studies confirm that ground truth-based pooling and CAM supervision both improve classification. CAM-guided MedSAM achieves a Dice similarity coefficient (DSC) of 86.6%, outperforming U-Net and nnU-Net by 5.9% and 3.6%, respectively. In addition, CAM prompts improve MedSAM’s DSC by 2.2%. By sharing plaque location between classification and segmentation, the proposed method improves both tasks and provides a more accurate tool for stroke risk stratification. Full article

Purpose: Breast cancer (BC) incidence has been increasing rapidly in North Africa, including Morocco, yet evidence regarding modifiable lifestyle factors remains limited. This study aimed to assess the associations between physical activity, sedentary behavior, daily work habits, and BC risk among Moroccan women, addressing an important gap in regional data. Methods: We conducted a case–control study between 2019 and 2023, including 1400 histologically confirmed incident BC cases and 1400 matched controls. Physical activity was assessed across the lifespan, considering type, intensity, and duration. Associations with BC risk were estimated using adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Results: Moderate physical activity was inversely associated with BC risk, showing a clear dose–response relationship. Compared with the lowest physical activity level, the highest quartile showed significantly lower odds of BC (aOR = 0.37 (95% CI: 0.29–0.47). Vigorous physical activity during young adulthood and mid-adulthood was similarly linked to reduced risk. Active daily habits, such as walking and regular stair climbing, were associated with lower odds, whereas frequent occupational fatigue and sweating were linked to increased risk. Conclusions: Our findings highlight a significant inverse association between physical activity and BC risk among Moroccan women. Notably, moderate PA and active daily habits like brisk walking are linked to lower odds of the disease. While these findings support the role of physical activity as an important factor associated with breast cancer prevention, the retrospective design of the study limits causal inference. Full article

In this study, we investigate how computationally simplified activation functions affect predictive performance, inference latency, and energy usage in long short-term memory-based temperature prediction for wind turbine generator bearings. We tested three different types of long short-term memory (LSTM) cells, along with bidirectional LSTM (biLSTM) networks, to determine their effectiveness in modeling dynamic changes in gearbox bearing temperatures. We compared several activation-function variants, focusing on variants that are either computationally simple or known to give good performance in deep recurrent networks. The results show that the best-performing architectures achieved root mean squared errors (RMSEs) between $0.0798$ and $0.0822$, corresponding to coefficients of determination in the range of $R^2=0.84$–$0.85$. When applied across five turbines, the best-performing architectures (peephole and bidirectional) achieved root mean squared errors of $0.0898$, $0.0882$, and $0.042$, respectively. The best activation function-enhanced variant (the peephole) improved accuracy by approximately $3\%$ while maintaining low model complexity. These findings provide a practical and efficient solution for embedded predictive maintenance systems, providing high accuracy without incurring the computational cost of deeper or bidirectional architectures. Full article

Objective: We examine whether a finite-range scalar–tensor modification of gravity can be simultaneously compatible with cosmological background data, galaxy rotation curves, and local/astrophysical consistency tests, while satisfying the luminal gravitational-wave propagation constraint ($c_T=1$) implied by GW170817 at low redshifts. Methods: We formulate the model at the level of an explicit covariant action and derive the corresponding field equations; for cosmological inferences, we adopt an effective background closure in which the late-time dark-energy density is modulated by a smooth activation function characterized by a length scale $\lambda$ and amplitude $ϵ$. We constrain this background model using Pantheon+, DESI Gaussian Baryon Acoustic Oscillations (BAOs), and a Planck acoustic-scale prior, including an explicit $\Lambda$CDM comparison. We then propagate the inferred characteristic length by fixing $\lambda$ in the weak-field Yukawa kernel used to model 175 SPARC galaxy rotation curves with standard baryonic components and a controlled spherical approximation for the scalar response. Results: The joint background fit yields ${\Omega }_m=0.293\pm 0.007$, $\lambda =7.{69}_{-1.71}^{+1.85}$$\mathrm{Mpc}$, and $H_0=72.33\pm 0.50$$\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$. With $\lambda$ fixed, the baryons + scalar model describes the SPARC sample with a median reduced chi-square of ${\chi }_{\nu }^2=1.07$; for a 14-galaxy subset, this model is moderately preferred over the standard baryons + NFW halo description in the finite-sample information criteria, with a mean $\Delta$AICc outcome in favor of the baryons + scalar model (≈2.8). A Vainshtein-type screening completion with $\Lambda =1.3\times {10}^{-8}$ eV satisfies Cassini, Lunar Laser Ranging, and binary pulsar bounds while keeping the kpc scales effectively unscreened. For linear growth observables, we adopt a conservative General Relativity-like baseline (${\mu }_0=0$) and show that current $f{\sigma }_8$ data are consistent with ${\mu }_0\simeq 0$ for our best-fit background; the model predicts $S_8=0.791$, consistent with representative cosmic-shear constraints. Conclusions: Within the present scope (action-level weak-field dynamics for galaxy modeling plus an explicitly stated effective closure for background inference), the results support a mutually compatible characteristic length at the Mpc scale; however, a full perturbation-level implementation of the covariant theory remains an issue for future work, and the role of cold dark matter beyond galaxy scales is not ruled out. Full article

Background and Objective: Colorectal cancer (CRC) liver metastasis (CRLM) represents a major clinical challenge, and acquired resistance to radiotherapy (RT) significantly limits therapeutic efficacy. A deep and comprehensive understanding of the cellular and molecular mechanisms driving RT resistance is urgently required to develop effective combination strategies. Here, we aimed to dissect the dynamic cellular landscape of the tumor microenvironment (TME) and identify key epigenetic regulators mediating radioresistance in CRLM by integrating cutting-edge single-cell and spatial omics technologies. Methods and Results: We performed integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) on matched pre- and post-radiotherapy tumor tissues collected from three distinct CRLM patients. Employing a robust machine-learning framework on the multi-omics data, we successfully identified MORF4L1 (Mortality Factor 4 Like 1), an epigenetic reader, as a critical epigenetic mediator of acquired radioresistance. High-resolution scRNA-seq analysis of the tumor cell compartment revealed that the MORF4L1-high subpopulation exhibited significant enrichment in DNA damage repair (DDR) pathways, heightened activity of multiple pro-survival metabolic pathways, and robust signatures of immune evasion. Pseudotime trajectory analysis further confirmed that RT exposure drives tumor cells toward a highly resistant state, marked by a distinct increase in MORF4L1 expression. Furthermore, cell–cell communication inference demonstrated a pronounced, systemic upregulation of various immunosuppressive signaling axes within the TME following RT. Crucially, high-resolution ST confirmed these molecular and cellular interactions in their native context, revealing a significant spatial co-localization of MORF4L1-expressing tumor foci with multiple immunosuppressive immune cell types, including regulatory T cells (Tregs) and tumor-associated macrophages (TAMs), thereby underscoring its role in TME-mediated resistance. Conclusions: Our comprehensive spatial and single-cell profiling establishes MORF4L1 as a pivotal epigenetic regulator underlying acquired radioresistance in CRLM. These findings provide a compelling mechanistic rationale for combining radiotherapy with the targeted inhibition of MORF4L1, presenting a promising new therapeutic avenue to overcome treatment failure and improve patient outcomes in CRLM. Full article