Queer youth in Egypt navigate a carceral ecosystem characterized by systematic state surveillance, medical pathologization, and societal exclusion. Despite the severity of these conditions, empirical data on their lived experiences remains scarce. This study addresses this gap through a web-based, cross-sectional quantitative survey (N = 165) designed specifically to bypass Western clinical pathologization. The findings reveal a catastrophic mental health crisis: 70.3% of respondents reported self-harm, and 56.4% reported at least one suicide attempt. A three-step hierarchical multiple regression model demonstrated that perceived public safety (B = 0.281, p < .001) eclipses family acceptance as the primary driver of psychological deterioration. Furthermore, a Chi-Square analysis empirically validated the lethality of the visibility trap, revealing that suicide attempts surge from 39% to 66% (p = .001) among youth who experience public discrimination. While psychological distress is pervasive across the cohort, transgender women face distinct, statistically significant intersections of structural violence. We conclude that these elevated rates of suicidality represent rational responses to conditional citizenship-a framework where survival is predicated on identity erasure or migration. This challenges Western applications of the Minority Stress model by highlighting state-level spatial violence, rather than interpersonal rejection, as the primary catalyst of psychosocial collapse.
To explore how algorithmic recommendation experiences shape media consumption intentions across different cultures based on the Stimulus-Organism-Response (S-O-R) framework and Self-Determination Theory (SDT). Survey data collected from social media users in China and South Korea were analyzed using partial least squares structural equation modeling and multi-group analysis (MGA). Perceived autonomy significantly mediates the relationship between algorithmic stimuli (personalized perception and forced exposure) and viewing intentions in both nations. However, forced exposure exhibits a distinct cultural polarity reversal. It enhances perceived autonomy among Chinese users due to platform-led convenience. Conversely, it directly threatens autonomy among South Korean users who prioritize decision-making independence. Electronic word of mouth (eWOM) shows a non-significant moderating effect in both groups. In highly automated media environments, direct machine-user cognitive processing eclipses traditional external social signaling. The psychological impacts of algorithmic interventions are heavily bound by national culture rather than being universal.
Our understanding of the impact of solar eclipse events on animal behaviors is mostly based on anecdotal reports, and rigorous scientific studies are scarce. On April 8, 2024, a significant portion of North America witnessed a rare total solar eclipse. This was a unique chance to study how animals in zoological institutions react to unpredictable and sudden environmental changes. Although based on a short-duration event (approximately 3 h in total and 1-4 min of total eclipse), such an event is an opportunity to carry out comparative studies on animal behavior and cognition. We compared the behavior and space use of animals during the eclipse to the same time period on days before and after the eclipse (baseline). While most species showed little response, Japanese macaques showed a significant and noticeable response by reducing their activity level and moving up higher on branches in their habitat. They returned to their normal behavior when the light intensity came back to normal. Zebras reacted with increased activity level and some signs of stress that lasted beyond totality. Incidentally, we found that the observers' subjective appraisal of behavioral responses does not fully match the data collected, emphasizing the importance of standardized protocols and training in animal behavior studies. As the zoo was closed to visitors during the observations, our study allows for a better understanding of animal behavioral reactions to total eclipse events, without the confusing effect of surrounding humans' reactions.
To provide a detailed and reproducible description of the development and clinical implementation of a RapidPlan knowledge‑based planning (KBP) model for lung stereotactic body radiotherapy (SBRT) in Eclipse v15.6, including training dataset composition, model analytics, objective template design, and prospective validation. A RapidPlan model was constructed using 161 coplanar VMAT SBRT plans calculated with Acuros XB (2.0 mm grid) and 6 MV FFF beams. Structure matching, outlier identification, and DVH prediction behavior were assessed using Varian Model Analytics report. A unified optimization template was assembled with explicit target priorities, a PTV gEUD objective, and gradient‑focused constraints addressing near‑target fall‑off and chest‑wall interfaces. The model was prospectively validated on 21 patients by comparing KBP plans with previously approved clinical plans. Model Analytics indicated stable DVH prediction bands after refinement; 4 plans were removed for atypical geometric or dosimetric behavior. The finalized template produced clinically acceptable plans for both peripheral and central tumors across the prescription range represented in the training set. In validation, most plans met target and OAR criteria on first optimization; where needed, minor adjustments (typically <10 minutes) resolved remaining issues. This technical note provides a complete, practical workflow for constructing a lung SBRT RapidPlan model in Eclipse v15.6. The reported training selection, analytics‑based refinement, and optimization template parameters enable other centers to reproduce or adapt the model for standardized SBRT planning without outcome comparisons.
To identify characteristics of patients with geographic atrophy (GA) who received pegcetacoplan or avacincaptad pegol and discontinued treatment. Two complementary retrospective cohort studies of a large, geographically and demographically diverse, deidentified database were performed. One analysis assessed baseline characteristics. Eyes with 12 months of data were included in a subsequent analysis of follow-up changes/characteristics. Univariate and multivariate mixed-effects Cox proportional hazard and logistic regression models, respectively, were used to estimate the hazard ratio (HR) and odds ratio (OR) of attrition. A total of 21 914 eyes were identified for the baseline analysis, 14 690 (67%) of which received pegcetacoplan and 7224 (33%) avacincaptad pegol. Mean (±SD) patient age was 82.1 ± 7.85 years. Treatment retention declined between 0 and 12 months. Baseline predictors of attrition were age older than 90 years (HR, 1.26; 95% CI, 1.03-1.55; P = .028), pegcetacoplan treatment (HR, 3.32; 95% CI, 2.92-3.76; P < .001), treated (HR, 1.56; 95% CI, 1.40-1.75; P < .001) and untreated (HR, 1.41; 95% CI, 1.21-1.64; P < .001) neovascular age-related macular degeneration (nAMD), visual acuity of less than 35 Early Treatment Diabetic Retinopathy Study (ETDRS) letters (HR, 1.45; 95% CI, 1.25-1.67; P < .001), and subfoveal GA (HR, 1.15; 95% CI, 1.04-1.27; P = .007). Poor baseline visual acuity remained significant in the adjusted 12-month analysis. Significant predictors included new nAMD (OR, 3.02; 95% CI, 2.35-3.89; P < .001) and a loss of more than 5 ETDRS letters (OR, 1.36; 95% CI, 1.17-1.58; P < .001). nAMD treatment intervals of more than 6 weeks (OR, 0.59; 95% CI, 0.39-0.90; P = .014) and GA treatment intervals of 6 to 8 weeks (OR, 0.56; 95% CI, 0.43-0.74; P < .001) contributed to decreased odds of attrition. Poor baseline vision and development of new nAMD are associated with patient attrition, and the combination of nAMD and GA and treatment burden challenges patient retention.
A sensitive and robust SPE-HPLC-MS/MS method was developed and validated for the simultaneous quantification of five steroid hormones in H295R cell culture medium. Chromatographic separation of the target steroids and selected potential endocrine‑disrupting chemicals (EDCs) was achieved using a ZORBAX Eclipse Plus C18 column (1.8 µm, 95 Å, 50 × 2.1 mm). Sample preparation was performed by solid‑phase extraction employing hydrophilic-lipophilic balanced polymeric reversed‑phase sorbent cartridges. Extraction recovery was evaluated at three concentration levels, tailored to each steroid, and exceeded 80% for all analytes. Intra‑ and inter‑day precision, expressed as relative standard deviation (RSD), ranged from 1 to 12%. Method limits of quantification were in the range of 8 and 73 pg mL⁻1, enabling reliable detection of steroids present at low endogenous levels. In addition to method validation, the ESI response of steroids was systematically evaluated in the presence of the selected compounds. Under the reference chromatographic gradient, signal variations were generally limited, indicating stable and robust ionization performance during LC-ESI-MS/MS analysis. The validated method was successfully applied to the high-throughput analysis of 285 H295R cell culture medium samples, generating a dataset of 1425 individual hormone measurements obtained within a broader framework investigating steroidogenic responses to individual potential EDCs. The results confirmed the capability of the analytical method to reliably monitor hormone fluctuations across a broad concentration range, demonstrating its suitability for routine, large-scale sample analysis in complex in vitro systems.
This study aims to develop an automatic beam arrangement algorithm based on deep reinforcement learning (DRL) to explore DRL's clinical potential in radiotherapy. The Soft Actor-Critic (SAC) algorithm was used with planning data from brain tumor patients at our institution. A three-dimensional dose distribution incorporating target areas and isocenters was used as input. Data interaction with the ECLIPSE planning system was facilitated through ESAPI scripts. To enhance sampling efficiency, multi-agent parallel sampling was employed to generate beam distribution plans. A total of 236 brain tumor patients were included. In the validation set, the model achieved a score of 73.48±23.17, compared to an initial plan score of 66.16±26.76. A random selection of 48 cases from the training set revealed that the best beam arrangement plans generated during training scored 83.33±25.18, while the initial plans scored 64.43±24.37. Furthermore, 14 cases not conforming to clinical beam arrangement practices were manually arranged, with the DRL group scoring 87.25±16.67 and the manual group scoring 79.94±20.02. All P-values were less than 0.05, indicating statistical significance. In this investigated cohort of brain tumor cases and under the evaluated technical configuration, the proposed DRL framework generated beam arrangement plans with improved plan scores, supporting its feasibility and potential value for beam angle optimization.
We develop and apply a dual experimental and computational framework to predict antigen specificity of TCR sequences in serial clinical samples. Our model integrates TCR primary sequences with previously reported and in silico-derived TCR-pMHC structural data. We apply this approach in the setting of hematopoietic stem cell transplant, focusing on a collection of HLA-A*02-restricted epitopes, including the Melan-A tumor associated antigen (ELAGIGILTV), Influenza A virus M158-66-derived peptide (GILGFVFTL), and human cytomegalovirus pp65-derived peptide (NLVPMVATV). We demonstrate accurate prediction of specificity for previously uncharacterized donor- and patient-derived TCRs, wherein model performance is enhanced through sequence-based clustering and incorporation of structurally diverse templates. Our results demonstrate that structure-guided learning enables robust specificity prediction from limited training data and can generalize across sequentially obtained patient samples. This framework provides a scalable strategy for TCR specificity prediction with potential applications in immunotherapy, vaccine design, and immune monitoring.
Linear accelerator-based stereotactic radiosurgery and stereotactic radiotherapy (SRS/SRT) are commonly used in the treatment of ocular malignancies. However, a substantial portion of the treatment planning process relies on manual plan optimization to achieve acceptable plan quality, leading to increased planning time and variability among planners. In this work, we demonstrate the feasibility of adapting a single-fraction model to a multifraction-capable knowledge-based planning model for ocular malignancies using noncoplanar treatment geometries. This approach has the potential to significantly improve planning efficiency for ocular SRS/SRT treatments. A previously validated HyperArc-based RapidPlan model for single-fraction (25 Gy) ocular SRS was adapted and further trained to handle 3- and 5-fraction prescriptions (42 Gy/3 Fx and 50 Gy/5 Fx). The knowledge-based planning (KBP) model was trained on 86 synthetic HyperArc plans and retrospectively tested on 24 datasets. Treatment planning was performed in the Varian Eclipse treatment planning system with the Acuros XB dose algorithm. Metrics included the Radiation Therapy Oncology Group conformity index, Paddick conformity index, gradient index, heterogeneity index, organ-at-risk (OAR) doses, and delivery accuracy via portal dosimetry patient-specific quality assurance (QA) and an in-house Monte Carlo second check. Across 1-, 3-, and 5-fraction ocular SRS/SRT regimens, the KBP model-based plans produced comparable target conformity, gradient, homogeneity, and coverage metrics, with no clinically meaningful differences between fractionation schemes. Differences in mean target dose (∼1%) were negligible. Most OAR constraints were met; optic nerve and lacrimal gland sparing were consistently achievable except when the OARs were included within the planning target volume, while lens and skin constraints were more challenging. Plan optimization was efficient (median ∼14 minutes), delivery times decreased with increased fractionation, and all KBP plans met patient-specific QA criteria with high pass rates during end-to-end testing and validation. These results demonstrate that a single RapidPlan model can generate high-quality ocular SRS plans across 1-, 3-, and 5-fraction schemes. The rapid generation of these KBP plans allows multiple fractionation schemes to be explored on a per-patient basis in a timely manner that would otherwise be clinically impractical with conventional manual planning.
Background/purpose Breast cancer is among the most prevalent malignancies treated at the Liga Nacional Contra el Cáncer (LNCC) in Guatemala, representing a significant proportion of annual radiotherapy cases. Access to high-quality, standardized treatment planning in resource-constrained settings remains a critical challenge. This study evaluates the dosimetric performance of knowledge-based planning (KBP) models adapted from Washington University (WashU) in St. Louis for breast and chest wall radiotherapy at LNCC, validated against a retrospective 2025 clinical cohort, and benchmarked against the ASTRO 2026 Practical Radiation Oncology guidelines. Materials and methods A retrospective analysis of 84 treatment plans (40 left, 44 right) for whole-breast or chest-wall treatment with regional nodal involvement was performed. All patients were treated using volumetric modulated arc therapy (VMAT) under a moderate hypofractionation scheme (40.05 Gy in 15 fractions). KBP models were developed during 2022-2024 using Eclipse V18.0 (Varian Medical Systems, Palo Alto, CA) RapidPlanTM, originally built at Washington University, and augmented with 194 left-breast and 103 right-breast cases from LNCC. Model validity was confirmed with Varian's model analytics tool. Dosimetric metrics for the planning target volume (PTV) and organs at risk (OARs) were extracted using a custom ESAPI (the OWASP enterprise security application programming interface) application and compared against ASTRO 2026 Table 3 benchmarks, categorized as recommended (green), acceptable (yellow), or unacceptable (red). Results PTV coverage was adequate, with an average V95% of 97.3% ± 1.8%; V90% of 99.7% ± 0.4 (right), and average V95% of 96.6%±3.8%; V90% of 99.0%, ± 2.8% (left). Most plans met ASTRO's recommended range. The heart mean dose was well-controlled, with median values of 2.4 Gy (right) and 4.2 Gy (left). Ipsilateral lung V18Gy showed a median of 18.6% (right) and 17.7% (left), and V10Gy of 33.3% (right) and 31.6% (left), both within acceptable ranges. Spinal cord D0.035cc had a median of 8.3 Gy (right) and 10.1 Gy (left), well below neurological tolerance thresholds. Contralateral breast D10% had median doses of 2.6 Gy (right) and 2.9 Gy (left), with ranges of 1.7-3.1 Gy and 2.2-5.4 Gy, respectively. KBP model analytics validation confirmed institutional model statistics fell within acceptable quality benchmarks across all evaluated structures. Conclusion KBP models developed at a high-income institution and iteratively refined with local data can be successfully deployed for breast and chest wall radiotherapy in a resource-constrained low- and middle-income country (LMIC) setting, achieving dosimetric outcomes consistent with ASTRO 2026 guidelines. The temporal separation between model training (2022-2024) and retrospective validation (2025) further confirms the models' robustness and generalizability. This approach supports standardized, high-quality treatment planning at scale, contributing to more equitable access to radiotherapy for breast cancer patients.
The purpose of this study is to investigate the influence of practice location on the type of tibial endovascular arterial intervention performed in the Medicare population. Furthermore, stratification of the frequency of the performance of each type of intervention between the primary subspecialty stakeholders in endovascular lower extremity care is investigated. A retrospective analysis of claims data from the Centers for Medicare and Medicaid Service's (CMS) Physician/Supplier Procedure Summary files for each year between 2011 and 2022 was conducted. Physicians were grouped into 1 of 4 categories: radiologists, cardiologists, vascular surgeons, or other. Claims data were tabulated for all Current Procedural Terminology (CPT) codes corresponding to endovascular therapy in the tibial arterial segment. These CPT codes encompass the interventions of angioplasty alone (CPT 37228), atherectomy with or without angioplasty (CPT 37229), stent placement with or without angioplasty (CPT 37230), and atherectomy in combination with stent placement (CPT 37231). Chi-squared testing was utilized for univariable comparisons. Atherectomy procedures were performed at a nearly two-fold higher rate in outpatient-based laboratories (OBLs) relative to hospital-based facilities (59.1% of procedures vs. 31.3%, odds ratio (OR): 1.87, P < 0.0001). After 2011 atherectomy rapidly accelerated with a per annum increase from 18,000 cases to over 45,000 per year. In 2011, balloon angioplasty was performed twice as frequently as atherectomy. By the year 2016 atherectomy with angioplasty eclipsed angioplasty. When analyzing location of service, the escalation in atherectomy occurred entirely in the OBL setting as the total number of atherectomies remained stable year over year between 2011 and 2022. Vascular surgeons performed tibial atherectomy at the lowest rate, but within an absolute rate of 1% relative to other disciplines for atherectomy without stent placement and within an absolute rate of 3% relative to other disciplines for tibial atherectomy with stent placement. Among all OBL cases, vascular surgery (41.5%) and cardiology (31.9%) performed the highest proportion of procedures relative to interventional radiology (22.0%) and other subdisciplines (4.5%), P < 0.001. There was a rapid acceleration in the performance of tibial atherectomy between 2011 and 2022. This was driven entirely by OBL based atherectomy performed at essentially equal rates across subdisciplines. Patients treated in the OBL setting were nearly twice as likely to be treated with atherectomy relative to those in hospital settings. Future reimbursement models for infrainguinal endovascular arterial interventions should carefully identify to-facility cost of devices utilized and create an equivalent reimbursement to cost margin across clinically equivalent methods of treatment.
The primary aim was to evaluate the accuracy of the generated Mid-Ventilation (MidV) Gross Tumour Volume (GTV) and Planning Target Volume (PTV) using three Deformable Image Registration (DIR) algorithms (Eclipse DIR, MIM DIR, Velocity DIR) and two starting phases for contour propagation (0% vs. 20%), compared with inter-observer variation (IOV). 27 stereotactic ablative radiotherapy (SABR) lung datasets were analysed. For each patient, three contours and a consensus reference contour was created. This reference contour was used to generate six DIR-based 4D contours (three algorithms with two starting phases). Performance was assessed using contour agreement metrics (mean distance to agreement [MDA)], Dice similarity coefficient [DSC], Hausdorff distance [HD], and volume ratio). Non-inferiority tests (one-sided, Dunnett-adjusted) evaluated DIR performance relative to IOV. DIR with a 20% starting phase outperformed 0% predominantly. Eclipse and Velocity DIR-20% met all published tolerances (MDA within 2 mm, DSC more than 0.8, and volume ratio within 10%) and were non-inferior to IOV. Secondary analyses showed improved consistency in MidV phase determination, MidV to Mid-position (MidP) centroid deviation (within 1 mm), 4D motion estimation (<1 mm), and PTV margin calculation (<1 mm difference). DIR algorithms using a 20% starting phase demonstrated superior performance compared with a 0% starting phase. Commercial DIR algorithms can support MidV contouring for lung SABR when initiated from the 20% starting phase. DIR-20% produced contour accuracy comparable to IOV with robust performance across MidV subprocesses.
Reporting cumulative equivalent dose in 2 Gy fractions (EQD2) for combined external beam radiotherapy (EBRT) and gynecologic high-dose-rate brachytherapy (HDR-BT) typically requires manual transcription of dose-volume histogram (DVH) parameters from treatment planning system (TPS) into worksheets. This process is time-consuming and prone to transcription errors. This study aimed to develop and validate a standalone application for automated DVH-based EQD2 reporting in cervical cancer HDR-BT, eliminating manual transcription, improving efficiency, and supporting standardized reporting. A standalone application (Gy+) was developed in C# using Varian's Eclipse Scripting API (ESAPI v15.5). The application retrieved treatment plan's metadata and DVH data, calculated biologically effective dose (BED) and EQD2 using linear-quadratic model, and performed parameter-wise EQD2 summation across EBRT and HDR-BT plans. The output included a standardized PDF report, aligned with ICRU Report 89 (Level 2) and EMBRACE II objectives. Technical verification was performed against an ESAPI reference script, and clinical validation was conducted against the existing manual workflow for 40 patients (154 HDR-BT plans). Technical verification confirmed identical DVH parameter extraction at ±0.1 Gy, ±0.01 Gy, and ±0.001 Gy, and EQD2 calculations matched worksheet outputs at the clinical reporting resolution. Clinical validation at the patient level showed median differences of -0.061 Gy for bladder and -0.066 Gy for rectum, with 52.5% and 47.5% agreeing within ±0.1 Gy, respectively. Plan-level analysis showed median differences of -0.013 Gy for bladder and -0.012 Gy for rectum, with 87.0% and 89.6% agreeing within ±0.1 Gy. Reporting time was reduced from approximately 6 minutes to 35 seconds. Gy+ application provides accurate, efficient, and reproducible automated EQD2 reporting for cervical cancer brachytherapy, reducing manual transcription and operator-dependent variability, with reporting consistent with ICRU 89 and EMBRACE II guidelines.
Pelitinib's (PTB) strong, irreversible inhibition of EGFR continues to pique scientific curiosity and warrants investigation of potential therapeutic uses, necessitating reliable analytical methods for its pharmacokinetic and metabolic assessment. Here, we have developed and validated a single, sensitive, and reliable LC-MS/MS (liquid chromatography-tandem mass spectrometry) method in accordance with USFDA guidelines for the quantification of PTB in plasma, human, and rat liver microsomes, where greenness assessment by (Analytical GREEnness metric approach and software) AGREE and (Methodological Overall Green Analytical Procedure Index) MoGAPI tools exhibited a good to moderate environmental performance. Chromatographic separation was achieved on an Agilent Eclipse Plus C18 column using a gradient mobile phase consisting of 0.1% formic acid in water and acetonitrile. Pelitinib exhibited dose-dependent systemic exposure and slow systemic elimination in vivo, along with low intrinsic clearance in microsomal incubations. Hepatic clearance was underestimated relative to the observed pharmacokinetic clearance, according to in vitro-in vivo extrapolation (IVIVE). Further, SwissADME (Swiss Absorption, Distribution, Metabolism, and Excretion) provided additional insights regarding the pharmacokinetic characteristics using in silico predictions.
Adaptive immune responses to primary Kaposi sarcoma-associated herpesvirus (KSHV) infection are poorly defined. To develop better small-animal models for understanding KSHV pathogenesis and immunity, we previously generated a chimeric virus in which the KSHV latency-associated nuclear antigen (kLANA), a conserved multifunctional protein critical for viral latency, was exchanged for the LANA homolog in murine gammaherpesvirus 68 (MHV68). Despite supporting comparable levels of latent infection between wild-type (WT) and KLKI MHV68, kLANA directly repressed MHV68 lytic replication and reactivation. We therefore hypothesized that suppression of lytic replication by kLANA dampens adaptive immune responses. To test this, mice were infected with equivalent doses of either WT or KLKI MHV68, and adaptive immune responses were evaluated over time. Compared to the WT virus, polyclonal B and T cell activation was starkly reduced following KLKI MHV68 infection, which correlated with reduced virus-specific humoral immunity and effector CD4+ and CD8+ T cell activation. Immune activation phenotypes were independent of the inoculating dose, as a high-dose infection with KLKI MHV68 still resulted in comparatively reduced adaptive immune activation. In contrast, infection of Ifnar1-/- mice, which support enhanced KLKI MHV68 lytic replication, led to potent adaptive cellular and humoral immune activation by both WT and KLKI viruses, suggesting that a lytic replication threshold must be passed for viral antigen-driven adaptive immune engagement. Collectively, these data support the hypothesis that kLANA-mediated suppression of lytic replication limits polyclonal lymphocyte activation and facilitates adaptive immune evasion by holding viral replication below an antigenic activation threshold.IMPORTANCEKSHV is a gammaherpesvirus that establishes lifelong, chronic infections in humans and increases the risk of virus-associated cancers. Currently, there is little information on how primary KSHV infection influences adaptive immune development in healthy individuals. Rodent models, such as murine gammaherpesvirus 68 (MHV68), provide a valuable laboratory system for studying gammaherpesvirus pathogenesis in vivo. In this study, we report that infection with a previously characterized chimeric KSHV-MHV68 virus expressing KSHV LANA represses lytic viral replication and elicits weak adaptive immune responses following primary infection, despite efficient latency establishment. By enhancing KLKI MHV68 replication in vivo, we restore adaptive immune activation, providing evidence that a viral replication threshold must be eclipsed for potent adaptive immune engagement. We propose that KSHV, through LANA, evades detection by repressing lytic viral replication to remain "below the radar" of adaptive immune defenses during host colonization.
Fluoroquinolone (FQ) antibiotics persist in the environment, posing risks to ecosystems and public health through antimicrobial resistance and bioaccumulation. Effective analytical methods are essential for monitoring these residues and enforcing regulations to limit antibiotic pollution. This study developed validated reversed-phase high-performance liquid chromatography (RP-HPLC) approaches for the simultaneous detection of five FQs: norfloxacin (NFX), levofloxacin (LFX), enrofloxacin (ENR), ofloxacin (OFX), and ciprofloxacin (CFX). Two chromatographic methods were required due to structural similarities between LFX and OFX. Method I, using an Eclipse Plus phenyl hexyl column, produced retention times of 5.2 min for NFX, 5.7 min for LFX, and 7.9 min for ENR. Method II, utilizing a YMC C18 column, yielded retention times of 8.9 min for OFX and 10.7 min for CFX. Both methods demonstrated high selectivity, specificity, linearity (R2 > 0.998), and precision (relative standard deviation (RSD) < 2 %), with Photodiode Array (PDA) detection at 280 nm. Validation followed International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2R2 guidelines. Environmental samples from West Bengal, including water, soil, chicken muscle, and fish skin, were processed using solid-phase extraction. Residues of all five FQs were detected, ranging from 0.1 to 1.4 μg g-1. Ofloxacin and CFX were more frequently found in animal-derived samples, whereas NFX and ENR were predominant in water and soil. The validated RP-HPLC methods provide robust tools for monitoring FQ residues in diverse matrices. The widespread contamination observed highlights the urgent need for stronger surveillance, stricter regulatory enforcement, and comprehensive risk assessment to mitigate antimicrobial resistance and protect public health. © 2026 Society of Chemical Industry.
Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-generation sequencing, multi-omics analysis, and emerging computational frontiers such as quantum-inspired feature selection. This review outlines how contemporary AI tools can automate labor-intensive quantitation, flag diagnostically salient patterns, and standardize interpretation, while the pathologist or hematologist retains authority over validation, context-specific integration, and clinical decision-making. We present an illustrative "human-in-the-loop" workflow that embeds AI modules within current laboratory information systems, emphasizing points where expert oversight mitigates algorithmic bias and resolves discordant findings. We further map the validator-integrator role across morphology, flow cytometry, and genomic/multi-omic interpretation and provide practical training competencies and use cases for AI-assisted hematopathology. Beyond technical deployment, the article addresses the educational transformation required for sustainable adoption. Drawing on international competency frameworks, including the Digital Health Competencies in Medical Education Framework and recently proposed AI-specific Entrustable Professional Activities, we map core skills that future hematopathologists must master: data-science literacy, critical appraisal of AI outputs, and ethical governance. We highlight evaluated training models such as the Pathology Informatics Essentials for Residents curriculum, Stanford Artificial Intelligence in Machine and Imaging workshops, and College of American Pathologists bootcamps and propose integration strategies adaptable across resource settings. By pairing rigorous validation with targeted education, AI can elevate rather than eclipse the diagnostic role of the leukemia specialist, enabling more timely, reproducible, and personalized patient care.
MicroRNA (miRNA) silencing is classically ascribed to RNA-sequence rules that guide Argonaute 2 (AGO2) targeting. Using chimeric eCLIP and complementary analyses in CRISPR-edited human lung epithelial cells, we show that efficient miRNA targeting also depends on the AGO2 adaptor-scaffold LIMD1. In LIMD1-deficient cells, AGO2 binds more miRNAs, but each AGO2-miRNA engages fewer transcripts and sites, reducing occupancy and halving both the breadth and depth of targeting. LIMD1 dependence is most pronounced for poorly conserved, weakly seed-paired sites that nonetheless form stable duplexes. LIMD1 deficiency alters AGO2 footprints and derepresses oncogenic targets inversely correlated with LIMD1 expression in lung adenocarcinoma. Thus, LIMD1 modifies the outcome of sequence-defined interactions that would otherwise be infrequent, unstable, or unproductive, revealing an adaptor-governed layer of posttranscriptional regulation beyond RNA-sequence rules.
Stereotactic ablative radiotherapy (SABR) with dose escalation is increasingly used for pancreatic cancer; however, the dosimetric impact of metallic biliary stents remains poorly characterized. Self-expanding metal stents (SEMS), commonly placed for obstructive jaundice, contain high-density nitinol that produces computed tomography (CT) artifacts, including beam hardening, potentially compromising treatment planning system (TPS) dose accuracy. Precise dose estimation is critical given the proximity of the duodenum and other organs at risk (OARs). This study evaluated dose distribution in pancreatic SABR in the presence of a metallic biliary stent using Monte Carlo (MC) simulation with refined stent contouring and material correction. Two patients with SEMS (Cook Evolution, nitinol alloy) treated with SABR (50 Gy in 5 fractions) using volumetric modulated arc therapy (VMAT) were retrospectively analyzed. Plans were generated in Eclipse TPS (v.13.7) using the analytical anisotropic algorithm. MC simulations were performed in PRIMO (PENELOPE-based) with ≤2% uncertainty. A novel contouring technique separated the hollow lumen from the metallic stent wall to correct CT beam hardening artifacts. Nitinol (density 6.45 g/cm3) was incorporated into MC calibration. Comparisons between standard MC, modified MC, and TPS were assessed using percentage agreement (PA), gamma passing rate (GPR; 3%/3 mm), and dose-volume histogram metrics. Refined contouring reduced modeled stent volumes from 26.1 to 22.8 cm3 and from 19.87 to 18.23 cm3. The standard MC model overestimated planning target volume (PTV) dose by 14.9% and 15.7%, with PTV GPRs of 55.29% and 79.78%, respectively. Approximately 2% dose enhancement was observed at the stent-tissue interface. Compared with the modified MC model, TPS underestimated dose lateral to the stent by up to 12.3% (worst case, Patient B, Plan 2) and overestimated it elsewhere by up to 12.2%. The duodenum showed the largest OAR discrepancies, with TPS up to 9.7% underestimation adjacent to the stent, whereas distant structures demonstrated high agreement. Conventional TPS algorithms exhibit clinically relevant inaccuracies in the presence of metallic biliary stents. Incorporating refined stent contouring and material correction within an MC framework improves dosimetric accuracy and may support safer dose escalation in pancreatic SABR.
Spatially fractionated radiation therapy (SFRT) offers a method to treat bulky, radioresistant tumors while sparing normal tissues. Modern volumetric modulated arc therapy (VMAT) delivery enables conformal lattice SFRT plans, but practical guidance for implementation across different linear accelerators is limited. This study presents a structured clinical workflow for implementing lattice SFRT across Edge and Halcyon linacs, with emphasis on quality assurance (QA) and motion management. A systematic workflow was developed using Eclipse TPS (Acuros v16) with 6 MV flattening filter-free (FFF) beams and applied to Edge and Halcyon linacs. The implementation progressed from 28 preliminary phantom and test plans to 12 representative clinical test plans across head and neck, pelvis, and extremity sites, and 6 lung plans evaluating respiratory motion effects with and without the SDX breath-hold system. Two prescription strategies were investigated: (a) a single-fraction lattice regimen delivering 18 Gy to vertices with valley doses < 6 Gy, and (b) a simultaneous integrated boost (SIB) approach delivering 66.7 Gy to vertices with 20 Gy in 5 fractions to the entire target. Dosimetric accuracy and deliverability were evaluated using Delta4, Electronic Portal Imaging Device (EPID), and film measurements. VMAT-based lattice SFRT plans were successfully delivered on both linacs with consistent dosimetric performance. Point-based peak-to-valley dose ratios (PVDRs) ranged from 2.8 to 3.4 across the two platforms for both dose prescriptions. Delta4 and EPID gamma pass rates exceeded 90% (3%/1 mm), and film dosimetry agreed within ∼5% uncertainty. Comparable outcomes between Edge and Halcyon support cross-platform reproducibility. In the evaluated lung cases, motion on the order of 5 mm was associated with changes in organ-at-risk (OAR) doses, highlighting the need for motion management. This structured framework demonstrates that lattice SFRT can be safely implemented across different linac platforms. While dosimetric outcomes are institution-dependent, the method provides practical guidance for clinical adoption.