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Imaging-based single-cell physiological profiling holds great potential for uncovering fundamental bacterial cold shock response (CSR) mechanisms, but its application is impeded by severe focus drift during rapid temperature downshifts required for CSR induction. Here, we introduce LUNA (Locking Under Nanoscale Accuracy), an innovative autofocusing method that leverages the coma pattern of detection light to characterize focus drift. LUNA improves the focusing precision down to 3 nm and extends the focusing range to at least 40 times the objective depth of focus. These advancements enable us to investigate the complete dynamics of bacterial single-cell CSR, revealing continuous cellular growth and division. We resolve a three-phase adaptation process characterized by distinct growth deceleration dynamics, and show that bacterial cells maintain robust size regulation and coordinate uniform adaptation to cold shock through synchronized growth and elapsed cycles. Notably, a model based on scattering theory reconciles the paradox between the growth lag of batch culture and continuous single-cell growth. These findings fundamentally transform our understanding of bacterial CSR and highlight LUNA's excellent potential for expanding state-of-the-art research in biology.

A globally prevalent human cytomegalovirus (HCMV), capable of establishing a lifelong infection in the host, exists in a latent state and can reactivate. Viral transmission can occur through contact with the bodily fluids of infected individuals, such as saliva, semen, urine, and breast milk. The infection is usually asymptomatic. However, immunocompromised individuals are more prone to experience severe complications, including pneumonia, organ damage, and retinitis. Because of high levels of HCMV in breast milk, breastfeeding by seropositive mothers may lead to viral transmission, which is most hazardous in low-birth-weight and very preterm infants. During infection, thrombocytopenia and inflammation of the lungs, liver, retina, and meninges may occur. To date, risk mitigation strategies have included pasteurization of breast milk. HCMV latency is defined as the presence of the viral genome in the infected cell without the production of infectious viral particles. This state is regulated by viral proteins, such as LUNA, UL138, and US28, as well as viral miRNAs, which silence transcription of immediate-early genes. The virus also avoids eliciting an immune response by suppressing the MHC class II presentation, utilizing viral IL-10 homologs, and impairing T-cell recognition. The reactivation of HCMV can be triggered by cellular differentiation or by the release of inflammatory cytokines, leading to the re-expression of viral IE genes and subsequent viral replication. This review summarizes the current knowledge of HCMV's molecular biology and pathogenesis, emphasizing the interplay between viral and host factors during latency and reactivation. It also highlights the importance of milk-mediated infection and its implications for neonatal health.

This study evaluated the avocado varieties 'Hass', 'GEM', 'Luna UCR', 'Eugenin', 'Flavia', I27EG, I55B, I49LB, I54J, and I73WL to determine seasonal dry matter (DM) patterns and assess how harvest timing, storage duration, and variety influenced stem-end rot, body rot, vascular streaking, and fruit susceptibility. Fungal pathogens associated with postharvest decay were identified using morphological characterization and multilocus phylogenetic analyses based on ITS, tub2, tef1-α, GAPDH, and MAT1-2 regions. Four Neofusicoccum species (N. australe, N. luteum, N. nonquaesitum, and N. parvum), one Colletotrichum species (C. perseae), and two Diaporthe species (D. baccae and D. foeniculina) were identified from decayed avocado fruits. Susceptibility tests confirmed that N. nonquaesitum was the most aggressive pathogen on avocado fruit, followed by C. perseae and D. foeniculina. The diversity of pathogens causing postharvest rot highlighted the complexity involved in managing stem-end rot and body rot in avocado fruits. Seasonal patterns of dry matter (DM) accumulation were identified for new varieties, aiding in establishing these standards. The study explored the seasonal variation in DM percentages across different avocado varieties and their correlation with disease severity. Results showed that this parameter can help prevent fungal disorders in some varieties. This finding emphasized the importance of adhering to both minimum and potentially maximum maturity standards to minimize fruit diseases and disorders and optimize postharvest performance. Additionally, the seasonality of stem-end and body rots in California avocados appears to be more associated with the inherent susceptibility of the fruits at harvest time than with environmental factors. Overall, general seasonal patterns were difficult to determine, as final postharvest disease intensity depended on the variety and the disease.

Accurate identification of phytoplankton communities is essential for understanding the ecological dynamics of aquatic ecosystems. Conventional optical microscopy, while widely used, is labor-intensive and limited in its ability to resolve small-sized taxa or organisms present at low cell densities. Here, we present a rapid, one-step chemotaxonomic approach based on ultrahigh-resolution Matrix-Assisted Laser Desorption/Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (MALDI FT-ICR MS) performed on a 21 T instrument for the molecular characterization of phytoplankton assemblages. Phytoplankton samples were collected from two contrasting sites in the Ciénaga Grande de Santa Marta (CGSM)Ciénaga La Luna and Boca de La Barraduring the dry (June) and rainy (August) seasons of 2022. The 21 T MALDI FT-ICR MS platform enabled the simultaneous detection of chlorophylls, carotenoids, and cyanobacterial secondary metabolites directly from crude solvent extracts, generating reproducible molecular fingerprints without prior chromatographic separation. Clear spatial and seasonal differences in molecular composition were observed between sampling sites and seasons, as evidenced by distinct pigment and metabolite profiles and supported by a multivariate analysis. Specific biomarkers, including chlorophyll derivatives, diagnostic carotenoids (e.g., fucoxanthin- and zeaxanthin-related compounds), and cyanobacterial metabolites, showed qualitative agreement with phytoplankton taxa identified by optical microscopy. These results demonstrate that 21 T MALDI FT-ICR MS provides a robust and time-efficient platform for resolving chemically driven differences among phytoplankton communities and for complementing traditional taxonomic identification in complex estuarine systems.

Growing pressure on UK land, driven by demands for food production, renewable energy, biodiversity recovery and climate mitigation, is intensifying competition for limited land. Vertical farming (VF) offers a land-sparing strategy: by relocating crop production indoors and achieving extremely high yields per unit area, VF can free agricultural land for other uses. However, VF has high greenhouse gas (GHG) emissions compared to traditional field farming due to intensive electricity demand, so its environmental value depends on whether land-sparing outcomes can offset production-stage impacts. This study provides the first UK-wide, full-system assessment of lettuce production, comparing business-as-usual field farming with national-scale VF and alternative uses of spared land. A primary-data life cycle assessment (LCA) quantifies the impacts of VF; a separate primary-data LCA of field farming incorporates DNDC-modelled national soil emissions; and the Land Use Net-Zero Advisor (LUNA) evaluates the GHG, land-carbon and energy implications of repurposing spared land for solar, wind, afforestation, agroforestry and bioenergy. VF reduces land demand by 93% but has higher GHG emissions per-kg than field systems. System-level outcomes depend on how spared land is used. Solar energy provides the strongest mitigation, fully offsetting VF's operational emissions and reducing total system impacts below the field baseline. Forestry and agroforestry generate positive land-carbon outcomes but more modest GHG reductions. Across all scenarios, peat soils dominate land-carbon losses, underscoring the need to avoid land-use change on peat and prioritise restoration. Overall, VF's environmental value arises from the land-use transitions it enables. When incorporated into multifunctional land-use planning, VF can support domestic food production while facilitating renewable-energy deployment and ecosystem restoration within a highly constrained UK land system.

For translational impact, both accurate drug response prediction and biological plausibility of predictive features are needed. We present drGT, a heterogeneous graph deep learning model over drugs, genes, and cell lines that couples prediction with mechanism-oriented interpretability via attention coefficients (ACs). We assess both predictive generalization (random, unseen-drug, unseen-cell, and zero-shot splits) and biological plausibility (use of text-mined PubMed gene-drug co-mentions and comparison to a structure-based DTI predictor) on GDSC, NCI60, and CTRP datasets. Across benchmarks, drGT consistently delivers top regression performance while maintaining competitive classification accuracy for drug sensitivity. Under random 5-fold cross-validation, drGT attains an AUROC of up to 0.945 (3rd overall) and an [Formula: see text] up to 0.690, outperforming all baselines on regression. In leave-one-out tests for unseen cell lines and drugs, drGT achieves AUROCs of 0.706 and 0.844, and [Formula: see text] values of 0.692 and 0.022, the only model yielding positive [Formula: see text] for unseen drugs. In zero-shot prediction, drGT achieves an AUROC of 0.786 and a regression [Formula: see text] of 0.334, both representing the highest scores among all models. For interpretability, AC-derived drug-gene links recover known biology: among 976 drugs with known DTIs, 36.9% of predicted links match established DTIs, and 63.7% are supported by either PubMed abstracts or a structure-based predictive model. Enrichment analyses of AC-prioritized genes reveal drug-perturbed biological processes, providing pathway-level explanations. drGT advances predictive generalization and mechanism-centered interpretability, offering state-of-the-art regression accuracy and literature-supported biological hypotheses that demonstrate the use of graph learning from heterogeneous input data for biological discovery. Code: https://github.com/sciluna/drGT.

Lung cancer remains the most significant cause of cancer-related death worldwide due to the critical challenges in diagnosis. Despite the promising efforts, the existing models faced challenges in capturing the complex patterns in medical imaging data while minimizing the computational complexity. In this research, the lung cancer detection using Computed Tomography (CT) images is performed using the Reverse Task attention-enabled Distributed Elman convolutional neural Network (RTsDEN) model that helps in mitigating the challenges in existing methods and improving the detection performance for real-time applications. The proposed model, combining the Reverse Task attention-(RTsAt) module and the distributed Elman concept, significantly contributes to capturing the intricate disease patterns from the complex backgrounds and varying environmental conditions. In addition, the proposed method exploits the adaptive lobe and multigranular nodule segmentation stage to facilitate better understanding and interpretation for accurate diagnosis. Experimental results reveal that the proposed RTsDEN outperforms other existing models by attaining 97.12% accuracy, 98.03% precision 96.22% recall using LUNA 16 dataset and 97.72% accuracy, 98.31% precision, 97.14% recall using the LIDC-IDRI dataset. The research introduces an efficient DL model with an ensemble approach, which significantly influences effective lung cancer detection.

This study evaluated a multidomain 6-month intervention combining training in memory strategies (e.g., goal setting, to-do lists, calendar scheduling) and lifestyle modifications (physical exercise, cognitive/social engagement, well-being exercises) supported by a digital application. The target intervention group is compared to an education only group. Participants were 270 older adults with subjective cognitive decline. Primary outcomes included global cognition and everyday function. Secondary outcomes included engagement in health behaviors, compensation strategy use, and other measures of health and well-being. We also examined baseline participant characteristics that predicted treatment response based on components of Self-Determination Theory (competence, relatedness, autonomous motivation), health literacy, demographics, and baseline dementia risk. Using an intent-to-treat framework, multiple linear regression models evaluated intervention effectiveness. At 6 months, no intervention group differences in cognition or everyday function were detected. However, the intervention group demonstrated significantly better well-being outcomes (i.e., gratitude) (p&#x202f;=&#x202f;.04). Lower baseline competence and autonomous motivation were associated with greater intervention effects on global cognition (ps <.04) and self-perceived stress (ps <.05), while higher autonomous motivation was associated with greater effects on everyday functioning (p&#x202f;=&#x202f;.026). Less education was associated with greater intervention benefits on social activity engagement (p&#x202f;=&#x202f;.03). Lower baseline dementia risk was associated with greater intervention benefits on moderate physical activity (p&#x202f;=&#x202f;.01). Combined training in healthy lifestyles and cognitive compensation may enhance aspects of emotional well-being. Further, particular participant characteristics may help determine who most benefits from this type of dementia risk reduction intervention.

Wearable and textile-based technologies are transforming health monitoring by enabling continuous, non-invasive, and context-aware assessment of physiological and biochemical signals in daily life. Advances in flexible electronics, conductive fibers, smart materials, and artificial intelligence have driven a shift from rigid, device-centric wearables toward textile-integrated and garment-based systems capable of distributed sensing, actuation, energy harvesting, storage, and communication. This roadmap provides a textile-centric overview of the current state and future trajectory of wearable technologies for healthcare, with electronic textiles positioned as a distinct and strategically important class within the broader wearable ecosystem. We synthesize progress across textile-integrated sensing, therapeutic and protective garments, textile body-area networks, energy-autonomous systems, and embedded computing, while critically examining challenges related to signal reliability, manufacturability, scalability, data governance, regulation, and equity. Market trends and adoption patterns are discussed to contextualize translational pathways from laboratory prototypes to clinically deployable and scalable textile systems. By identifying key scientific, technological, and societal priorities, this roadmap outlines actionable directions to accelerate the integration of textile-based wearable technologies into preventive, personalized, and decentralized healthcare.

In matrix acid stimulation of carbonate rocks, understanding acid-rock interaction is essential to optimize wormhole formation and overall treatment efficiency, since heterogeneity can lead to distinct dissolution patterns. Mineralogical heterogeneity significantly affects this process due to the different dissolution kinetics of calcite and dolomite; however, it remains unclear how grain size, crystal defects, and mineral distribution influence this interaction. To investigate these factors, five highly dolomitized carbonate samples from the Piau&#xed; Formation (Parna&#xed;ba Basin) were characterized by petrography, X-ray diffraction, X-ray fluorescence, scanning electron microscopy, and porosity measurements, and subjected to static dissolution in 1 M HCl with evaluation of mass loss and quantification of calcium and magnesium ions. The results showed that texture and mineralogical composition play a fundamental role in dissolution: larger crystals generated wider cavities due to detachment during acid attack; samples with higher Ca and Mg contents relative to Si exhibited higher dissolution rates, whereas increasing quartz content reduced reactivity. Most samples showed an early predominance of Ca2+ release followed by increasing Mg2+ concentrations, reflecting preferential calcite dissolution and progressive dolomite contribution. Well-developed crystals with fewer structural defects exhibited lower reactivity. Postdissolution peak broadening in XRD patterns suggests structural modification of the minerals. Overall, mineralogical heterogeneity controls acid-rock reactivity across multiple scales, highlighting the importance of integrated mineralogical and textural characterization to improve prediction and optimization of acid stimulation in heterogeneous carbonate reservoirs.

Snakebites represent a significant public health concern in tropical and subtropical countries. In 2025, approximately 21,000 incidents of snakebites were reported in Brazil, with 1.7% attributed to coral snakes. Although the incidence of coral snake envenomation in Brazil is lower compared to accidents caused by pit vipers, its venom is highly toxic and always considered a severe medical emergency requiring immediate intervention, a need that highlights the importance of maintaining Micrurus for antivenom production. Maintaining and feeding M. corallinus ex situ presents a significant challenge due to the lack of regular availability of their natural prey, snakes and amphisbaenians. This study developed an artisanal sausage for this species kept ex situ. The artisanal sausage was tested as a supplemental diet alongside traditional prey, focusing on acceptance rates, weight gain, and nutritional adequacy. For the sausage filling we used beef protein mixed with chicken liver, supplemented with essential and non-essential amino acids and calcium carbonate. Our findings revealed no significant difference in acceptance between sausages and snake prey, with 77% acceptance rate for sausages. Weight gain was comparable across diet types, suggesting that the sausages may provide nutritional support to maintain growth under the conditions evaluated. However, because the bromatological analysis was limited to lipids, protein, calcium, and phosphorus, the nutritional adequacy of the sausage diet could not be fully assessed, as other important dietary components were not evaluated. Despite this, the alternative diet should be considered a promising supplemental feeding strategy for Micrurus in captivity, rather than a fully validated substitute for natural prey. Further research is recommended to investigate the long-term health effects of this diet and to refine its formulation for optimal nutritional balance.

Pantoea ananatis has recently emerged as a causal agent of Pantoea leaf blight (PLB) and Pantoea panicle blight (PPB) of rice in the United States, raising concerns about its potential impact on rice production. Despite increasing reports of the disease, mechanisms underlying host specialization and virulence within this pathosystem remain poorly understood. Here, we combined comparative genomics and in-planta assays to investigate population structure and virulence determinants among rice-associated P. ananatis strains. Average nucleotide identity analysis of P. ananatis genomes resolved two lineages with contrasting host associations. One lineage, composed of strains recovered almost exclusively from rice, lacked the HiVir operon responsible for synthesis of the phosphonate toxin pantaphos. A second, broadly distributed lineage included P. ananatis isolated from diverse hosts, including rice, and many contained the HiVir operon. HiVir-mediated pantaphos production induced necrotic symptom development, but was not required for bacterial replication within rice tissue. Accordingly, strains lacking HiVir, including those from the rice-associated lineage and targeted mutants, exhibited reduced necrosis while achieving bacterial population sizes comparable to wild-type generalist strains during infection of rice. Conversely, host-range experiments showed that rice-associated strains colonized onion tissue less than generalist strains, consistent with evolutionary specialization for rice. Comparative pangenome analysis supported the separation of lineages and identified hundreds of lineage-specific genes that may underpin host associations. These findings demonstrate that P. ananatis populations associated with rice comprise distinct evolutionary lineages with differing genomic features and virulence strategies and reveal a decoupling between symptom development and bacterial proliferation during infection of rice.

BackgroundWhile Alzheimer's disease (AD) is a known risk factor for falls, the association between falls and incident AD is a growing area of study.ObjectiveThe primary aim of this analysis was to examine associations between new-onset falls in older adults and neuroimaging and plasma biomarkers of AD. A secondary aim was to evaluate associations between new-onset falls and neuroimaging markers of motor dysfunction.MethodsData from the UK Biobank study was utilized. Participants were 70 years of age or older at the date of neuroimaging and had no reported history of falls at study enrollment. To determine falls status, participants self-reported data on falls history within the last year prior to neuroimaging.Results15,447 individuals were included in our analysis (No falls, N&#x2009;=&#x2009;12,522; One fall, N&#x2009;=&#x2009;2,199, Multiple falls, N&#x2009;=&#x2009;726). Compared to individuals in the No falls group, individuals in the One fall and Multiple falls group had significantly higher volumes of white matter hyperintensities, while individuals in the Multiple falls group had significantly lower left and right hippocampal volumes. One or more fall was associated with higher plasma levels of pTau181, which did not remain significant after adjusting for multiple comparisons. Plasma amyloid-&#x3b2; 42/amyloid-&#x3b2; 40 ratio did not differ significantly between groups.ConclusionsIn a sample of older adults without history of falls at study enrollment, new-onset falls were associated with decreased hippocampal volumes, which is associated with prodromal AD, as well as an increased volume of white matter hyperintensities, which may also emerge secondary to AD pathology.

In the sentence beginning with "High-frequency ventilation (HFV) maintains functional residual capacity and minimizes ventilator-induced lung injury by delivering subdead-space tidal volumes at supraphysiologic frequencies. Its performance depends on airway size and lung mechanics, making it effective in preterm infants with low compliance. HFV modalities include high-frequency jet ventilation, delivering rapid gas pulses with passive exhalation to improve gas exchange and support lung stabilization, especially in air-leak syndromes; high-frequency oscillatory ventilation, providing bidirectional oscillations at constant mean airway pressure, enabling alveolar recruitment while limiting volutrauma and atelectrauma, with volume-guarantee strategies enhancing stability and protection; and less common percussive or flow-interruption ventilation with limited neonatal evidence&#x2026;" please link the citations to the references as appropriate.

Accurate differentiation between major depressive disorder (MDD) and schizophrenia (SZ) remains a clinical challenge due to overlapping symptoms and limitations of traditional diagnostic methods. Integrating neurobiological markers, especially functional magnetic resonance imaging (fMRI), with clinical assessments holds promise for improving diagnostic specificity. Recently, a translational cross-validation paradigm integrated the von Zerssen Paranoid-Depression Scale (a clinical self-assessment scale) with simultaneous fMRI data acquisition to cross-validate evaluations of psychopathology using neuroimaging techniques, allowing direct comparison of subjective symptom-related processing with corresponding neural activation patterns. Hence, we sought to replicate this method in an independent Chinese cohort. A sample of 62 participants, comprising 32 MDD and 30 SZ patients, underwent task-based fMRI scanning using a paradigm with statements of diagnostically neutral (DN), depressive-specific (DS), and paranoid-specific (PS) content. After preprocessing, the number was reduced to 57 (30 MDD and 27 SZ). Neural responses were analyzed using the PS versus DS contrast to isolate paranoia- versus depression-related processing. Brain activation patterns were compared across the two patient groups. Mixed-effects Analysis of Variance (ANOVA) was used to test main effects and interactions. In SZ relative to MDD, processing paranoia-relevant content (PS > DS) was associated with greater activation in the bilateral supplementary motor area (SMA), left middle cingulate cortex (MCC), right precentral gyrus, and right superior frontal gyrus, indicating differential neural engagement during paranoia-specific processing. The second-level mixed-effects ANOVA revealed a significant main effect of condition (PS versus DS) across both groups in the precuneus/calcarine cortex, left frontal cortex, and hippocampal regions, indicating task-related modulation of neural activity. Importantly, a significant group &#xd7; condition interaction was identified in fronto-cingulate, motor, temporal, and prefrontal regions, suggesting differential neural responses to paranoia-related processing between SZ and MDD. Integrating task-based fMRI with clinical self-assessment scales offers a robust approach to delineate neurofunctional differences between SZ and MDD. Combining self-report scales with fMRI data contributes to the development of objective neurobiological markers, enhances the reliability of the differential diagnosis, and provides a neurobiological basis for more precise clinical assessments.

Three decades after the approval of the first cancer nanomedicine, low (<1%) tumor delivery remains the central unsolved challenge in nanoparticle (NP)-based therapy. This barrier has prompted a research shift toward biologically derived delivery systems able to reduce immune clearance while preserving tumor-homing capabilities. In particular, extracellular vesicles (EVs) seem obvious candidates on account of their intrinsic biocompatibility, cell-specific tropism, and biological functionality. In this mini-review, we critically analyze EVs as nanoparticle delivery vectors in cancer therapy. We describe current EV engineering approaches, including loading methodologies, surface modification strategies, and the development of artificial or biomimetic EVs, highlighting technical, scalability, and characterization challenges. We also summarize key in vitro and in vivo results, addressing encapsulation strategy, biodistribution, and therapeutic outcomes. From this discussion, we outline research needs that must be addressed to develop EV-NP hybrids as tools to overcome the delivery challenge in cancer.

As a cyclical parthenogen, Brachionus plicatilis possesses two divergent reproductive modes regulated by habitat cues. Since 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) and its UV-B irradiated photodegradation product 2,4,4'-tribromodiphenyl ether (BDE-28) can be transferred intergenerationally during parthenogenesis and affect the fitness of the F1 generation, is it possible that a similar effect could be observed during sexual reproduction? This study examined the intergenerational transmission and toxicity of these compounds between maternal rotifers and their resting eggs. The results demonstrated that both BDE-47 and BDE-28 accumulated and transferred in a concentration-dependent manner, with BDE-28 notably enhancing the accumulation and toxicity of BDE-47. Maternal exposure for 24&#x202f;h adversely affected the quantity and quality of resting eggs, and subsequently impaired the survival and reproductive performance of the hatched F1 individuals. Concurrently, the expression of key sexual reproduction genes, cell division cycle 20 (CDC20) and trehalose-6-phosphate synthase (TPS), increased with exposure level, suggesting a potential mechanism underlying the altered resting eggs production and viability. Furthermore, the nutrient composition transferred to resting eggs was altered: glycogen and protein content increased with exposure, whereas lipid content decreased, accompanied by changes in associated enzyme activities. Correlation analysis identified that lipids and lipase activity were the key factors linked to the poor fitness observed in the F1, highlighting a potential metabolic basis for the observed intergenerational toxicity. These findings reveal the intergenerational transfer of contaminants and their degradation products through sexual reproduction, providing crucial insights for ecological risk assessment.

The ever-increasing trend of antibiotic resistance necessitates new therapeutic strategies for fighting infection. Standing on decades of extensive research and development, monoclonal antibodies have great promise for treating antibiotic-resistant bacterial infections. In this comprehensive review of the field, we summarize the rapidly emerging field of monoclonal therapeutics that offer alternative approaches to target bacterial pathogens that pose critical concern to human health. Organizing the findings by species and by molecular target, we discuss antibodies that have demonstrated therapeutic potential as well as those that did not provide efficacy, highlighting new insights for the design and discovery of highly effective therapeutics for the future. Furthermore, we discuss the latest advances in molecular biology that have revolutionized the implementation, efficacy, and utility of monoclonal antibodies as therapeutics, and that continues to drive what will be an exciting era for antibacterial monoclonal antibodies.

Small renal masses are increasingly detected incidentally, but up to 25% prove to be benign. Imaging alone often cannot distinguish malignant tumors from inflammatory or ischemic lesions, posing a risk of overtreatment. This case highlights a renal mass initially concerning for malignancy that resolved entirely following treatment for acute pyelonephritis A 51-year-old woman presented with bilateral flank pain, fever, and myalgias. Laboratory findings were consistent with a urinary tract infection, and cultures grew Escherichia coli. Imaging revealed a 4.4 cm right renal mass with features concerning for renal cell carcinoma. However, biopsy demonstrated arterionephrosclerosis without malignancy. Follow-up MRI at 3 months showed complete resolution of the lesion, suggesting a transient inflammatory pseudotumor related to acute pyelonephritis and chronic ischemia. This case illustrates the diagnostic overlap between renal cell carcinoma and benign renal lesions such as focal pyelonephritis, arterionephrosclerosis, or inflammatory pseudotumors. Despite radiologic features mimicking malignancy, clinical context and histology supported a non-neoplastic process. Renal mass biopsy, when combined with follow-up imaging, proved essential to avoid unnecessary intervention. Awareness of inflammatory mimics and their clinical course is critical in managing indeterminate renal lesions, particularly in patients with risk factors for infection or vascular disease. This case underscores the importance of integrating clinical, radiologic, and histologic data in evaluating renal masses. Biopsy and imaging surveillance can help differentiate benign mimics from malignancy, minimizing overtreatment and preserving renal function.