Category: Nevin Manimala

Rep Pract Oncol Radiother. 2025 Dec 31;30(6):796-803. doi: 10.5603/rpor.108577. eCollection 2025.

ABSTRACT

BACKGROUND: Rhabdomyosarcoma (RMS) of the extremities has a particularly poor prognosis compared to other primary sites due to an increased rate of alveolar histology, higher rate of metastasis, and the extent of regional lymph node involvement. To date there are few assessments comparing upper extremity (UE) to lower extremity (LE) RMS of the extremities using population-based registry, so we sought to compare survival between UE and LE RMS.

MATERIALS AND METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) database, cases of RMS of the UE and LE diagnosed between 2000-2020 were collected. Descriptive statistics and chi-square analyses were completed for one-and five-year survival. Log-rank and Cox regression analyses were completed to compare UE versus LE survival.

RESULTS: A total of 641 cases were included, of which 221 (34.5%) were UE and 420 (65.5%) were LE. On log-rank tests, UE survival was longer than LE survival (p = 0.021). The one-year survival rate was greater for the UE (88.7%) compared to the LE (81.4%) (p = 0.020) but similar at five-years. Cox regression analysis showed no difference in survival between UE and LE primary site (hazard ratio = 1.172, p = 0.322).

CONCLUSIONS: In comparing UE and LE RMS survival, UE survival was greater at one-year, but not on adjusted analyses. These findings contribute to the few prior assessments of outcomes between UE and LE RMS, though direct comparisons between UE and LE should be included in future prospective studies.

PMID:41498078 | PMC:PMC12767979 | DOI:10.5603/rpor.108577

J Pediatr Clin Pract. 2025 Oct 16;18:200190. doi: 10.1016/j.jpedcp.2025.200190. eCollection 2025 Dec.

ABSTRACT

OBJECTIVE: The incidence of neonatal opioid withdrawal syndrome (NOWS) has dramatically increased, and illegally manufactured fentanyl may be a significant contributor. The optimal treatment approach for an infant experiencing severe withdrawal from fentanyl is unknown. Our aim was to decrease the mean length of stay (LOS) by 20% over 19 months for infants with NOWS by implementing a transitional phase before establishing our modified Eat, Sleep, Console (ESC) model of care.

STUDY DESIGN: A multidisciplinary team used quality improvement methodology to improve treatment of NOWS in 2 phases, each adapted to fentanyl’s complex pharmacology. Beginning May 2023, a hybrid Finnegan/ESC protocol was implemented to address hospital barriers for a year before initiating full ESC management. Data were collected on infants >35 weeks of gestational age admitted to a level III neonatal intensive care unit. Primary metrics included LOS and total days/doses of morphine. Rates of apnea and naloxone were used as balancing measures. The LOS was plotted on a statistical process control chart and the data were summarized with descriptive statistics.

RESULTS: Outcomes were analyzed for 217 infants. The aim was exceeded with a mean LOS reduction of 29% (hybrid) and 49% (ESC). On average, decreased morphine days (22.5, 11.2, 6.9, P < .001) and doses (162, 63, 14, P < .001) also were observed. No significant apnea occurred, nor was naloxone used.

CONCLUSIONS: This quality improvement project provides a successful fentanyl-adapted ESC model that may be adopted to decrease postnatal morphine usage and LOS.

PMID:41498060 | PMC:PMC12766099 | DOI:10.1016/j.jpedcp.2025.200190

J Biomed Opt. 2026 Jan;31(1):018001. doi: 10.1117/1.JBO.31.1.018001. Epub 2026 Jan 5.

ABSTRACT

SIGNIFICANCE: Pleural photodynamic therapy (PDT) faces significant dosimetry challenges due to complex light distribution patterns within the pleural cavity, where integrating sphere effects dominate light propagation. Accurate prediction of light fluence rate distributions is essential for optimizing treatment protocols and improving therapeutic outcomes in this emerging clinical application.

AIM: The aim is to quantitatively analyze light fluence rate distributions in pleural PDT using Monte Carlo (MC) simulations in various cavity geometries and tissue optical properties, providing essential data for treatment planning.

APPROACH: Graphics processing unit-accelerated MC simulations ( ${10}^8\text{photons}$ ) using MCmatlab analyzed light distribution in spherical cavities (radii 0.2 to 10 cm) and anatomically realistic lung cavity models (volume = 2 L) with point sources. Simulations include a range of tissue optical properties ( ${\mu }_a$ : 0.1 to $1.0{\mathrm{cm}}^{–1}$ ; ${\mu }_s^{‘}$ : 5 to $40{\mathrm{cm}}^{–1}$ ) for a flat-cut fiber source inside a realistic three-dimensional (3D) lung geometry, including realistic thoracotomy access openings and different fill media (air versus saline). Experimental validation is made using isotropic detectors in the same 3D-printed lung phantom with varying optical properties.

RESULTS: MC statistical uncertainties averaged 1.9% across all voxels. Spherical cavities ( $r=4\mathrm{cm}$ ) demonstrated highly uniform scattered light distribution along cavity-tissue boundaries (distribution uniformity 4.9%), whereas anatomically realistic lung phantoms showed greater heterogeneity (49.9%). Scattered light fluence rate per source power ( ${\varphi }_s/S$ ) strongly correlated with tissue optical properties, particularly scattering coefficients. Source position minimally affected scattered light patterns, though direct components remained position-dependent. Side openings reduced scatter fluence near access points, with saline-filled cavities showing slightly higher fluence rates than air-filled cavities.

CONCLUSIONS: We demonstrate that patient-specific factors including cavity geometry, tissue optical properties, and surgical access considerations significantly influence light distribution in pleural PDT. The quantitative relationships established between these parameters and fluence patterns provide essential data for developing personalized treatment planning protocols to optimize therapeutic light delivery.

PMID:41498054 | PMC:PMC12768299 | DOI:10.1117/1.JBO.31.1.018001

Occup Ther Int. 2026 Jan 4;2026:4450215. doi: 10.1155/oti/4450215. eCollection 2026.

ABSTRACT

INTRODUCTION: The prospective, historically controlled study evaluated whether a collaborative practice (CP) model between nurses and occupational therapists improves activities of daily living (ADLs) and reduces the use of disposable absorbent products and physical restraints in hospitalized older patients.

METHODS: Data from the historical control group (n = 72), who received usual care, were collected from medical records, and the intervention group (n = 46), who participated in the CP-based intervention, was recruited in a community-based care ward in a regional hospital. The CP model was designed to facilitate collaborative planning for improving ADLs between nurses and occupational therapists. Outcome measures included disposable absorbent product use, physical restraint use, and the functional independence measure (FIM). Assessments were conducted at admission and discharge. Propensity score matching was applied to balance baseline characteristics between groups and to reduce potential confounding factors.

RESULTS: Propensity score matching generated 45 pairs (“historical controls,” n = 45, and “interventions,” n = 45). Although physical restraint use was reduced in both groups (p ≤ 0.007), the use of disposable absorbent products in the intervention group was significantly reduced compared to the historical control group (p = 0.020). Additionally, significant interaction effects were observed between time and group for all FIM scores, indicating greater improvements in ADLs in the intervention group, with moderate to large effect sizes (p ≤ 0.013, partial η ² ≥ 0.068).

CONCLUSIONS: This study demonstrated the positive impact of a CP model between nurses and occupational therapists in improving ADLs and reducing disposable absorbent product use in older patients. These findings suggest that this model of CP enhances the quality of geriatric care. Trial Registration: UMIN Clinical Trials Registry number: UMIN000047072.

PMID:41498052 | PMC:PMC12765810 | DOI:10.1155/oti/4450215

N Am Spine Soc J. 2025 Aug 10;24:100782. doi: 10.1016/j.xnsj.2025.100782. eCollection 2025 Dec.

ABSTRACT

BACKGROUND: Hypertrophy of the ligamentum flavum (LF) contributes significantly to the development of lumbar spinal stenosis (LSS), a serious and often disabling disease predominantly affecting the aging population. Histologic changes in the ligament and the tissue mediators that drive these alterations have been described, but their spatial distribution within the ligament remains unclear. Understanding these changes may enable future interventions to slow ligament degeneration and disease progression. To date, no study has comprehensively described the distribution of pathological changes within individual ligaments.

METHODS: This study combined histopathobiochemical analysis and micromechanical mapping of healthy and degenerated human LF specimens obtained perioperatively from 57 patients undergoing lumbar spine surgery (38 with LSS and 19 controls). Ligament samples were analyzed histologically for vascular density, presence of inflammatory infiltrates, and chondroid metaplasia using morphometric software and immunohistochemical staining. Mechanical properties, including stiffness (Young’s modulus) and contact pressure, were measured via nanoindentation using the Hysitron BioSoft In-Situ Indenter system. Samples were spatially mapped across 9 anatomical zones of the LF to investigate regional variation. Statistical analyses compared these parameters between spinal segments (L3/4, L4/5, L5/S1), between LSS and control groups, and evaluated age-related trends.

RESULTS: The central region of the LF exhibited significantly higher vascularity and stiffness compared to peripheral regions. Areas showing chondroid metaplasia and inflammation demonstrated increased vascularization, characteristic of LSS pathology. Although vascular density and mechanical stiffness were elevated in LSS patients versus controls, these differences did not reach statistical significance. Age-related trends differed between groups: stiffness increased with age in controls but decreased in LSS patients.

CONCLUSIONS: The greatest changes in vascularization and stiffness occur in the central region of ligamentum flavum. Understanding these localized alterations may support future development of targeted therapies to slow or prevent disease progression.

PMID:41498049 | PMC:PMC12766084 | DOI:10.1016/j.xnsj.2025.100782

Ann Appl Stat. 2024 Mar;18(1):683-703. doi: 10.1214/23-aoas1807. Epub 2024 Jan 31.

ABSTRACT

Respondent-driven sampling (RDS) is used throughout the world to estimate prevalence and population size for hidden populations. Although RDS is an effective method for enrolling people from key populations in studies, it relies on a partially unknown sampling mechanism, and thus each individual’s inclusion probability is unknown. Current estimators for population prevalence, population size, and other outcomes rely on a participant’s network size (degree) to approximate their inclusion probability in the sample from the networked population. However, in most RDS studies, a participant’s network size is attained via a self-report and is subject to many types of misreporting and bias. Because design-based inclusion probabilities cannot be exactly computed, we instead use the term visibility to describe how likely a person is to be selected to participate in the study. The commonly used successive sampling population size estimation (SS-PSE) framework to estimate population sizes from RDS data relies on self-reported network sizes in the model for the sampling mechanism. We propose an enhancement of the SS-PSE framework that adds a measurement error model for visibility used in place of the self-reported network size and a model for the number of recruits an individual can enroll. Inferred visibilities are a way to smooth the degree distribution and bring in outliers as well as a mechanism to deal with missing and invalid network sizes. We demonstrate the performance of visibility SS-PSE on three populations from Kosovo sampled in 2014 using RDS. We also discuss how the visibility modeling framework could be extended to prevalence estimation.

PMID:41498046 | PMC:PMC12768521 | DOI:10.1214/23-aoas1807

Mediators Inflamm. 2025 Dec 10;2025:5588098. doi: 10.1155/mi/5588098. eCollection 2025.

ABSTRACT

BACKGROUND: Previous studies have found that some indices derived from preoperative complete blood count (CBC) are closely related to the prognosis of glioma, but the results are inconsistent. This study comprehensively discussed the prognostic significance of the preoperative CBC index in patients with glioblastoma (GBM) through a multicenter study.

METHODS: In this multicenter study, we retrospectively analyzed clinical data from 143 GBM patients to evaluate the prognostic value of 12 preoperative CBC-derived indicators: Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), red cell distribution width (RDW), platelet distribution width (PDW), RDW-to-PDW (RPR), systemic inflammation index (SII), systemic inflammation response index (SIRI), hemoglobin-to-red cell distribution width ratio (HRR), platelet-to-basophil ratio (PBR), lymphocyte-to-basophil ratio (LBR), and eosinophil-to-lymphocyte ratio (ELR). Optimal cut-off values for each indicator were determined using maximally selected rank statistics (MSRS). Survival outcomes were assessed by Kaplan-Meier analysis, and univariate and multivariate Cox regression were employed to identify independent prognostic factors. Furthermore, a nomogram was developed by integrating significant prognostic indicators to facilitate individualized prediction of survival in GBM patients.

RESULTS: The results showed that higher levels of NLR, PLR, MLR, RDW, PDW, and RPR were associated with shorter survival in GBM patients. In contrast, lower levels of ELR were associated with shorter survival in GBM patients. Among these, RDW (HR 1.905, 95% CI 1.114-3.258, p = 0.019), MLR (HR 1.603, 95% CI 1.029-2.496, p = 0.037), and ELR (HR 0.380, 95% CI 0.193-0.747, p = 0.005) emerged as an independent prognostic factors. The prognostic nomogram was constructed according to the three independent factors, which improved the accuracy of prognosis prediction (AUC = 0.702).

CONCLUSION: Routine preoperative CBC parameters, particularly RDW, MLR, and ELR, serve as valuable complementary prognostic indicators for GBM patients. These accessible biomarkers warrant further validation through large-sample, multicenter studies to solidify their clinical utility.

PMID:41498042 | PMC:PMC12767395 | DOI:10.1155/mi/5588098

Mediators Inflamm. 2025 Dec 25;2025:5592084. doi: 10.1155/mi/5592084. eCollection 2025.

ABSTRACT

BACKGROUND: Diabetic kidney disease (DKD) is a multifactorial complication of diabetes involving mitochondrial dysfunction and immune cell infiltration. However, the causal relationships remain unclear.

METHODS: We applied Mendelian randomization (MR) and single-cell RNA sequencing (scRNA-seq) to investigate the roles of mitochondrial gene expression and immune cells in DKD. Additionally, peripheral blood mononuclear cells (PBMCs) from DKD patients were analyzed for differential gene expression.

RESULTS: Higher expression of mitochondrial genes PCCB, ACADM, ADHFE1, OCIAD1, and FIS1 increased DKD risk, while genes like NT5DC2, ATP5MC3, and GLYCTK decreased risk. Immune traits, including human leukocyte antigen (HLA)-DR + plasmacytoid dendritic cells (pDCs), mediated the effects of mitochondrial dysfunction on DKD. scRNA-seq revealed significant downregulation of ATP5MC3, GLYCTK, and NT5DC2 in podocytes (PODOs) and tubular cells in DKD kidneys, alongside increased infiltration of helper T cells, B cells, dendritic cells (DCs), and plasma cells. PBMC analysis highlighted the upregulation of proinflammatory genes (CXCL2, CXCL3, and others) in DKD patients.

CONCLUSION: This study highlights the complex interplay between mitochondrial dysfunction and immune cell infiltration in DKD pathogenesis. Key mitochondrial genes and immune traits identified here offer novel therapeutic targets such as ATP5MC3, GLYCTK, and DC pathways.

PMID:41498039 | PMC:PMC12767380 | DOI:10.1155/mi/5592084

Mediators Inflamm. 2025 Dec 8;2025:8804923. doi: 10.1155/mi/8804923. eCollection 2025.

ABSTRACT

BACKGROUND: Inflammatory cytokines have been implicated in monoclonal gammopathy of undetermined significance (MGUS), but their causal mechanisms remain unclear. Metabolites play pivotal roles in plasma cell dysregulation, however, their potential mediation effects between cytokines and MGUS are unexplored. We aimed to elucidate causal relationships between inflammatory cytokines and MGUS and identify metabolite-mediated pathways.

METHODS: Using genome-wide association study (GWAS) summary statistics, we performed bidirectional two-sample Mendelian randomization (MR) to assess causality between 91 inflammatory cytokines and MGUS. A two-step MR approach was employed to investigate metabolite mediation using data from 1400 blood metabolites. Sensitivity analyses addressed pleiotropy and reverse causality (IVs: p < 1 × 10^-5, F-statistic > 10).

RESULTS: MR analysis identified CXCL10 (OR = 2.12, 95% CI: 1.06-4.23, p = 0.034) and IL-6 (OR = 3.61, 95% CI: 1.22-10.65, p = 0.020) as causal risk factors for MGUS. We also found Threonate (OR = 2.24, 95% CI: 1.06-4.75, p = 0.035), X-22776 (OR = 3.45, 95% CI: 1.37-8.67, p = 0.009) and glucose to sucrose ratio (OR = 2.89, 95% CI: 1.18-7.07, p = 0.020) were associated with increased MGUS risk, while N-acetylputrescine to (N(1) + N(8))-acetylspermidine ratio (OR = 0.65, 95% CI: 0.43-0.98, p = 0.039) showed protective effects. Mediation analysis revealed 2 metabolites Threonate and X-22776 mediating CXCL10’s effect on MGUS. Threonate mediated 11.2% (β = 0.08, p = 0.014) and X-22776 mediated 17.7% (β = 0.13, p = 0.028) of CXCL10’s total effect. Sensitivity analyses confirmed robustness (no pleiotropy: MR-Egger intercept p > 0.05; Cochran’s Q p > 0.05).

CONCLUSION: This study deeply reveals the mechanism by which inflammatory cytokines affect the pathogenesis of MGUS through metabolite-mediated pathways, providing new potential targets for the early diagnosis and treatment of MGUS. In the future, other inflammatory cytokines and metabolites that may be related to the pathogenesis of MGUS can be further explored, and the interactions and potential mechanisms between them can be further studied to provide a more comprehensive theoretical basis and practical guidance for the prevention and treatment of MGUS.

PMID:41498034 | PMC:PMC12767486 | DOI:10.1155/mi/8804923

Mediators Inflamm. 2025 Dec 28;2025:4342537. doi: 10.1155/mi/4342537. eCollection 2025.

ABSTRACT

BACKGROUND: Cancer-associated fibroblasts (CAFs), as a key component of the tumor microenvironment, have not been systematically elucidated in glioblastoma (GBM). Our study aims to develop a prognostic model integrating CAFs-related features, with the goal of providing new insights for precise stratification and optimized treatment strategies for GBM patients.

METHODS: Utilizing GBM-related data from reputable public databases, we utilized the Seurat package in R to analyze single-cell RNA sequencing (scRNA-seq) data for the characterization of CAFs in GBM. We identified CAFs phenotypes and screened for key CAFs-related genes significantly associated with patient prognosis. Using regression analysis, we constructed a CAFs-based risk score, which was subsequently validated in multiple independent cohorts. A nomogram integrating the risk score and clinicopathological features was also developed. Furthermore, we systematically evaluated the prognostic and therapeutic relevance of the model in GBM patients through multi-dimensional analyses, including gene mutation profiling, pathway enrichment analysis, immune infiltration, immunotherapy response, and drug sensitivity analysis.

RESULTS: A total of six CAFs-related genes (FAM241B, LSM2, IGFBP2, LOXL1, OSMR, and STOX1) were identified as significantly associated with GBM prognosis. We used it to construct the CAFs-based risk score model, which demonstrated robust prognostic performance across multiple cohorts and served as an independent predictor of overall survival in GBM patients, efficiently categorizing groups into high and low risk. By integrating clinical features, the nomogram model significantly increased predictive accuracy and reliability. Analytical results indicated a statistically significant association between the computed risk score and the level of immune cell infiltration. Furthermore, the established prognostic model exhibited robust efficacy in predicting patient outcomes following conventional targeted treatments as well as immunotherapeutic interventions.

CONCLUSIONS: This study introduces a GBM risk profiling framework and accompanying nomogram, offering exceptional accuracy in prognostic prediction for GBM. The framework and nomogram provide valuable insights into the roles of CAFs and key genes in GBM progression and immunity, and extend beyond classification by offering promising avenues for deciphering tumor mutations, mapping immune landscapes, refining drug predictions, and forecasting the efficacy of immunotherapeutic interventions. These findings have the potential to significantly improve personalized treatment strategies and patient outcomes.

PMID:41498024 | PMC:PMC12767406 | DOI:10.1155/mi/4342537