Abstract: Water hyacinth (Eichhornia crassipes) is an invasive aquatic plant with high lignocellulosic content, offering potential as a natural fiber resource for craft-based industries. However, its extremely high initial moisture content (≈95%) presents a major challenge in fiber processing, particularly for small-scale industries that rely on traditional sun-drying methods. These methods are highly dependent on weather conditions, prone to contamination, and produce inconsistent fiber quality. This study adopts a research and development (R&D) approach to design and evaluate an innovative dryer machine specifically for water hyacinth fiber processing. The proposed system utilizes LPG-based heating and controlled airflow to achieve stable drying conditions. Experimental results show that the dryer machine can process 10 kg of wet water hyacinth within 280 minutes, significantly shorter than approximately four days required for manual drying. The system reduces the moisture content to below 10%, resulting in improved fiber cleanliness, uniformity, and usability. Although the dried mass produced by the machine is slightly lower compared to manual drying, this is attributed to more effective moisture removal, leading to lower residual water content in the final product. Productivity analysis indicates improved operational consistency and higher processing capacity over extended periods (30–180 days), particularly under varying weather conditions. These findings demonstrate that controlled drying technology provides a reliable and efficient solution for lignocellulosic fiber processing in small-scale industries, contributing to improved material utilization and sustainable biomass management.

Abstract: Soil health and irrigation water quality are fundamental to sustainable agricultural productivity, particularly in semi-arid environments. This study evaluated the influence of irrigation water quality on soil physical and chemical properties within the Kagitumba Irrigation Scheme in Eastern Rwanda. An observational analytical design integrated field sampling, laboratory analysis, and statistical evaluation. Soil samples (n = 20) were col-lected at depths of 0–30 cm and 30–60 cm, alongside irrigation water samples (n = 5) from intake and distribution points. Soil parameters analyzed included texture, bulk density, pH, electrical conductivity (EC), organic matter, and nutrient content, while water quality assessment focused on pH, EC, turbidity, dissolved oxygen (DO), and oxidation–reduction potential (ORP). Data were subjected to descriptive statistics, Pearson correlation, and ANOVA at a 95% confidence level. Findings revealed predominantly sandy loam soils with low bulk density, moderate water-holding capacity, and near-neutral pH. Soil salin-ity remained low, indicating limited risk of degradation. Irrigation water was generally suitable for agricultural use in terms of pH and salinity; however, elevated turbidity showed a strong negative correlation with infiltration rate (r = −0.73). Additionally, low soil nitrogen levels were significantly associated with water quality, suggesting nutrient leaching. These results underscore the critical role of irrigation water quality in shaping soil health and emphasize the need for improved water filtration and integrated nutrient management to enhance long-term sustainability.

Abstract: The complete blood count (CBC) is a diagnostic test to analyze abnormalities of blood cells. Currently, automated hematology analyzers and artificial intelligence technology are being used with automated blood analyzers to ensure accuracy and reliability. This study aimed to evaluate the performance of artificial intelligence (AI) based automated blood cell analyzer, Awalife AI-100Vet Multifunctional Morphological Analyzer, in dog and cat blood samples by comparison with the CBC manual method. In dogs, PCV, hemoglobin, RBC, MCH, WBC, % Neutrophil, %Lymphocyte, %Monocyte, %Eosinophil and %Reticulocyte were all significantly correlated. While in cats, PCV, Hemoglobin RBC, WBC, % Neutrophil, % Lymphocyte, and % Eosinophil were all also significantly correlated. AUC values obtained by the Awalife AI-100Vet analyzer for Hematology testing in dogs and cats were 0.72 and 0.92 respectively. These findings suggest that the Awalife AI-100Vet analyzer demonstrated good accuracy using dog blood for hematology testing as well as excellent accuracy when using cat blood. The AI-based automated blood analyzer has the potential to analyze hematological data and is close to the reference method. However, there are still differences in some parameters. Further optimization of the AI algorithm, which will involve increasing the accuracy of identifying unusual cell shapes, improving stability against various samples, such as stains, and achieving good results when working with unique pathologies, should be carried out.

Abstract: In vitro-transcribed modified mRNA is a promising platform for transient protein replacement in regenerative medicine, including cardiomyocyte regeneration, but repeated dosing is limited by variable innate immune activation and ISR-mediated translation shutdown across individuals. We propose a Human-specific PRR/ISR Immunogenicity Atlas: a focused, genotype-aware computational framework linking patient genetic variation in pattern recognition receptors and ISR components to predict immune and translation responses for IVT modRNA. The Atlas generates individualized “genetic passports” that stratify responder risk, estimate cytokine and PKR/eIF2α activation, and prioritize clinically feasible temporary knockdown strategies (LNP-siRNA/ASO or small molecules). We outline a six-stage roadmap covering data integration, feature engineering, multi-modal modeling, uncertainty quantification, a knockdown prioritization module, and open deployment. Ethical, privacy, ancestry-representation, and regulatory considerations are discussed, along with a staged validation strategy. This Atlas provides a conceptual and practical framework to support safer, more consistent protein replacement in regenerative medicine by moving from one-size-fits-all to genotype-guided approaches.

Abstract:

Dixit et al. proposed an asymptotic drag scaling for zero-pressure-gradient flat-plate turbulent boundary layers based on the approximation $M\sim U_{\tau}^2\delta$, where $M$ is the kinematic momentum rate through the boundary layer, $U_{\tau}$ is the friction velocity, and $\delta$ is the boundary-layer thickness. In the present paper, an explicit Reynolds-number-dependent correction to this approximation is derived from the logarithmic mean-velocity profile. Integration of the log law across the layer yields $M\sim U_{\tau}^2\delta\,f(Re_{\tau})$, where $Re_{\tau}=\delta U_{\tau}/\nu$ is the friction Reynolds number and $f(Re_{\tau})$ is given analytically. Application of the correction to the dataset compiled by Dixit et al. shows that the corrected scaling gives an exponent consistent with the asymptotic value $-1/2$ within bootstrap confidence intervals, whereas the uncorrected formulation does not. The correction should be viewed as a leading-order amendment, since the derivation uses the logarithmic law outside its strict range of validity.

Abstract:

Background: Streptococcus agalactiae (group B Streptococcus, GBS) remains a leading cause of invasive infections in pregnant women, fetuses, and neonates. Universal screening at 36-37 weeks of gestation followed by intrapartum antibiotic prophylaxis is essential to prevent adverse outcomes. However, data on GBS serotype distribution are limited in several regions, including Greece. This study aimed to determine the prevalence, serotype distribution, and antimicrobial susceptibility of GBS isolates among pregnant women in Greece. Methods: Vaginal and rectal swabs were collected from pregnant women undergoing routine GBS screening between January 2021 and December 2025. Samples were processed using selective enrichment broth and cultured on blood agar and chromogenic media. Identification was based on standard microbiological methods, CAMP test, and VITEK2 system. Antimicrobial susceptibility testing and macrolide-lincosamide-streptogramin B (MLS_B) phenotyping were performed. Serotyping was conducted using a commercial latex agglutination assay. Results: Among 941 women screened, 118 (12.5%) were colonized with GBS. The most prevalent serotypes were III (29.7%), V (18.6%), Ib (14.4%), IX (10.2%), Ia (9.3%), and II (9.3%). All isolates were susceptible to penicillin. Resistance to erythromycin and clindamycin was observed in 29.7% and 22.9% of isolates, respectively. The predominant MLSB phenotype was constitutive (cMLSB, 78.4%), followed by inducible (iMLSB, 13.5%), L (5.4%), and M (2.7%) phenotypes. Conclusions: GBS colonization was detected in 12.5% of pregnant women, with serotype III predominating, underscoring its clinical relevance due to its association with invasive neonatal disease. Although penicillin remains fully effective, the observed resistance to macrolides and lincosamides, primarily mediated by the cMLS_B phenotype, raises concerns regarding alternative therapies.

Abstract: Federal post-quantum cryptography migration is scoped around three categories of cryptographic assets: libraries, protocols, and key stores. We argue that this scoping is incomplete. Cryptographic functions and key material can be realized in the parameters of machine learning models, and current open-source serialization-focused scanners we evaluated do not detect them. We provide an existence proof: a 30-layer feed-forward ReLU network that realizes AES-128 exactly, with the master key and all eleven round keys resident directly in layer bias vectors and recoverable by parsing. The construction validates bit-exactly against FIPS 197 and the NIST CAVP AESAVS known-answer subsets across 10⁴ random plaintext-key pairs, including under float32 quantization. We then argue analytically that ML-KEM and ML-DSA private keys hide more comfortably in modern weight tensors than AES keys do, not less, by virtue of their larger size and lower internal rigidity. The consequence under the harvest-now-decrypt-later threat model is that any long-lived cryptographic key embedded in an open-weights model artifact distributed today is recoverable by any future party with knowledge of the embedding scheme, without any quantum capability required. We propose a parameter-space cryptographic recognizer operating on structural, parametric, and functional signatures, integrated with cryptographic bill-of-materials tooling as a parameter_resident_cryptographic_content emission class extending the MBOM-PQC schema. The audit primitive is defense-in-depth: it closes the gap for known constructions and architectural fingerprints without claiming completeness against adaptive adversaries. We make no claim that any deployed model contains such an embedding; the contribution is the existence of the capability, the absence of detection, and the migration-scope consequence.

Abstract: A robust evaluation of predictive uncertainty is essential for deploying machine learning models in high-risk sectors. While various techniques such as Gaussian Processes and Bayesian Neural Networks have been developed to address model uncertainty, the measurement uncertainty associated with input data, particularly regarding heteroscedasticity and autocorrelation, is often overlooked. This work introduces the Generalized Least Squares Support Vector Machines (GLS-SVM), a kernel-based regression model designed to integrate the full variance-covariance matrix of the response variable into the training process. A GUM-consistent methodology is then developed for evaluating prediction uncertainty including a correction for model bias. The performance of the proposed model is validated using two case studies: a simulated regression problem with heteroscedastic, autocorrelated noise and the calibration of a mass flow controller. Results demonstrate that GLS-SVM significantly outperforms other kernel-based models when dealing with correlated data, providing accurate estimations and physically consistent standard uncertainties. This approach offers a versatile, metrologically-informed framework for data-driven regression tasks where measurement covariance information is available and rigorous uncertainty quantification is required.

Abstract: Background: Type 2 diabetes mellitus (T2DM) and periodontitis are chronic inflammatory conditions. Periodontitis may amplify low-grade systemic inflammation in people with T2DM. High-sensitivity C-reactive protein (hsCRP) reflects this inflammatory burden, but the effect of non-surgical periodontal therapy (NSPT) on hsCRP in T2DM remains uncertain. Objective: To evaluate whether NSPT changes hsCRP at 3 and 6 months compared with oral hygiene instructions alone in patients with T2DM and periodontitis. Methods: Predefined secondary analysis of a 1:1 parallel-group randomized trial with assessments at baseline, 3 months, and 6 months. Participants received scaling and root planing plus oral hygiene instructions (intervention) or oral hygiene instructions only (control). Fasting hsCRP (mg/L) was analyzed on the log scale using mixed-effects models; effects are presented as exponentiated ratios with 95% confidence intervals. Sensitivity analyses included baseline-adjusted analysis of covariance (ANCOVA) and covariate-adjusted mixed models. An exploratory group-adjusted regression examined associations between periodontal changes and hsCRP change. Results: Eighty-nine participants were randomized (45 control, 44 intervention), with hsCRP available for most participants through 6 months. There was no between-group difference at 3 months (ratio 0.958; 95% CI 0.875–1.049; p=0.358). At 6 months, hsCRP was lower in the NSPT group than in controls (ratio 0.809; 95% CI 0.738–0.887; p<0.001), corresponding to ~19% lower hsCRP; the model-based geometric mean hsCRP at 6 months was 2.66 mg/L versus 3.26 mg/L. Periodontal measures improved more with NSPT, but changes in periodontal measures were not independently associated with hsCRP change after group adjustment. Conclusions: In patients with T2DM and periodontitis, NSPT was associated with lower hsCRP at 6 months, suggesting a potential systemic anti-inflammatory benefit. These findings support periodontal care as part of integrated management in T2DM.

Abstract: Swelling soil landslides pose severe challenges in geotechnical engineering due to non-linear deformation and strength degradation. Accurate characterisation of pore structure parameters remains the core difficulty. This study proposes a Physics-Informed Neural Network (PINNs) framework that utilises Mercury Intrusion Porosimetry (MIP) data to simultaneously invert three key physical parameters: pore fractal dimension (Ds), surface tension (γ), and contact angle (θ). By embedding the Washburn equation and fractal pore theory into the neural network loss function, the framework achieves high-precision inversion without requiring complete prior information. Validated on three expansive soil samples, the inverted Ds values were 2.47, 2.53, and 2.58, showing excellent agreement with classical models (R² > 0.99) and an average relative error below 2.3%. The inverted γ ranged from 0.476 to 0.480 N/m and θ from 142.3° to 144.2°, both satisfying physical plausibility requirements. Five-fold cross-validation confirmed the absence of overfitting (ΔR² < 0.001). Sensitivity analysis identified Ds as the dominant parameter controlling pore volume distribution; Ds exceeding 2.55 indicates elevated landslide susceptibility. This framework provides a rapid, automated approach for extracting pore structure parameters, offering parametric support for preliminary risk assessment of expansive soil slopes.

Abstract: This work explores how graph theory concepts and neural networks can assist in strategic planning of metro network expansions using publicly available city data with the São Paulo Metropolitan Region. The methodology consolidated information from multiple public sources, developed a formula to estimate passenger demand based on catchment areas, applied Random Forest to identify the most relevant demographic features, and implemented a GraphSAGE model for demand prediction, extracting predictive capability from the topology of the system as well as socioeconomic features and Origin-Destination trips. The model achieved an R² of 0.874 ± 0.042 with minimal overfitting, outperforming the Random Forest approach. It can be applied to predict demand for future projects in a way that is accurate, inexpensive and computationally efficient, while also not requiring any rail system specific information besides topology. In this project, it was used to analyze multiple real projects and proposals for the São Paulo Metropolitan Region. Analysis revealed that employment, residences, and destinations where people go to eat represent 65% of the predictive capacity in the city.

Abstract: This study aimed to identify the volatile organic compounds (VOCs) present in the es-sential oil (EO) of Schinus lentiscifolia and to evaluate the effect of chitosan coatings (1%) enriched with EO of S. lentiscifolia (1000, 2000, and 4000 mg L⁻¹) on the control of Penicillium sp. and on the quality of ‘Fuji’ apples. The EO was extracted from S. lentiscifolia collected in the municipality of Lages, Santa Catarina State, Brazil, in March, May, and November 2022. The antifungal activity of S. lentiscifolia EO against Penicil-lium sp. was evaluated in vitro. Apples were stored under refrigerated conditions (0 ± 0.5 °C; 90 ± 5% RH) for 30 days and subsequently under ambient conditions (23 ± 3 °C; 70 ± 5% RH) for 6 days. A total of 14 VOCs were identified in the EO of S. lentiscifolia, with the monoterpenes β-pinene (34.68%) and α-pinene (30.61%) as the major com-pounds, followed by β-terpinene (10.13%), camphene (9.66%), and o-cymene (7.14%). The application of chitosan coating with S. lentiscifolia EO (2000 mg L⁻¹) reduced the severity of blue mold in ‘Fuji’ apples by 88.1% during refrigerated storage and by 69.2% under ambient conditions. Ethylene production by the apples was also reduced when treated with chitosan and EO. No influence of the treatments was observed on fruit quality attributes. The postharvest application of chitosan coatings combined with S. lentiscifolia EO reduces disease caused by Penicillium sp. in ‘Fuji’ apples without affect-ing fruit quality.

Abstract: Discoidin domain receptor 1 (DDR1) has been implicated in fibrotic progression in multiple organs, including the kidney; however, its role in regulating cytoskeletal organization and matrix remodeling in renal fibroblasts remains unclear. Here, we investigated how DDR1 expression is regulated by profibrotic stimulation and extracellular matrix stiffness, and how DDR1 influences cytoskeletal organization and collagen remodeling. Single-cell RNA sequencing of murine kidneys subjected to unilateral ureteral obstruction (UUO) revealed enrichment of Ddr1 expression in transitional fibroblast populations during early activation. In vitro, transforming growth factor-β1 (TGF-β1) increased DDR1 expression, but DDR1 depletion did not affect canonical myofibroblast marker expression. Instead, DDR1 depletion suppressed stress fiber assembly while promoting actin-rich podosome formation associated with matrix degradation. Functionally, DDR1-deficient cells exhibited impaired focal adhesion maturation, enhanced collagen degradation, reduced gel contraction, and decreased collagen matrix stiffness as measured by atomic force microscopy. Furthermore, extracellular matrix stiffness dynamically regulated DDR1 expression, suggesting a bidirectional relationship between DDR1 expression and matrix mechanics. Together, these findings identify DDR1 as a modulator of cytoskeletal remodeling that governs the balance between matrix-degradative and contractile remodeling programs in renal fibroblasts.

Abstract: A four-dimensional anisotropic metric branch is defined for traceless gauge-side stress tensors of non-null Rainich type. The construction is motivated by the Alena Tensor correspondence between flat force-density and curvilinear geometric descriptions, but the branch data are fixed locally. The branch has a 2+2 form with one anisotropy field. This field is obtained both from the gauge stress and from a normalized vorticity-flux closure, while the remaining tensor-force term is represented by the Levi-Civita geometry only when a trace-adjusted branch tensor satisfies the Codazzi condition. Under these restrictions, the closed branch gives a common geometric language for elementary-mode data. Mass is read as scalar curvature response, electric charge as transverse-frame holonomy, and color as a three-dimensional multiplicity space of equivalent self-dual branch modes. After a two-dimensional weak space is adjoined, preservation of the top form gives S(U(3) \times U(2)), and the even exterior algebra gives the anomaly-free representation content of one Standard Model generation, including \nu_L^c. The same branch normalization fixes a primitive coupling $g_B$; with G_F and one intermediate scale E_B=2.64\times10^{14}\,\mathrm{GeV} as inputs, the resulting branch-level one-loop evaluation gives a consistency check for m_W, m_Z, m_h, and \alpha_s(m_Z). The numerical Yukawa matrices, confinement energy, and global family spectrum are left as dynamical problems.

Abstract: Background: Invasive pulmonary aspergillosis (IPA) is a major cause of morbidity and mortality in patients with hematological malignancies. Serum galactomannan (GM) is widely used for diagnosis, but the prognostic value of the initial GM level is not well established. Objective: To assess the association between the initial serum GM level at IPA diagnosis and the radiological and clinical outcomes at 42 and 90 days. Methods: We retrospectively reviewed adult patients with hematological malignancies, including hematopoietic stem cell transplant (HSCT) recipients, diagnosed with proven or probable IPA at Sultan Qaboos University Hospital between 2014 and 2017, according to the EORTC/MSG criteria. Demographic, microbiological, radiological, and clinical data were collected. Outcomes were assessed using three GM cut-off categories. Results: Seventy-eight patients were included. The median age was 44.5 years (range 18–76); 53.8% were male. Lymphoma (30.7%) and acute leukemia (25.6%) were the leading underlying diseases. Voriconazole was the most frequently used antifungal agent (74.3%). Prolonged neutropenia was present in 61.9%, and 30.7% had received HSCT. The mean serum GM at diagnosis was 1.95 (range 0.5–7.89). At 90 days, 30% had a complete radiological response, 51.4% partial, and 32.8% no response. Overall, 90-day mortality was 35.9%. There was no statistically significant association between initial GM level and 90-day mortality across categories (GM 0.5–3.0: 34.2% mortality; GM > 3.0: 60%; p = 0.243). Within the GM 0.5–3.0 group, complete radiological response was strongly associated with survival (95.2% alive at 90 days; p < 0.001). Conclusions: The initial serum GM level was not significantly associated with clinical or radiological outcomes at 42 or 90 days in patients with hematological malignancies and IPA. However, an early complete radiological response was strongly associated with improved survival, supporting the use of follow-up CT chest imaging to guide management.

Abstract: Sugarcane harvester performance varies substantially with field geometry, crop, and operator factors, yet separating these sources from telematics data while preserving engineering interpretability remains a methodological gap. This study models field efficiency (Eff) and harvesting capacity (Ca) separately from JDLink telematics, aligning model structure with each target's response behavior. Operational data covered 105 plots across four seasons (2019/20–2022/23) from three John Deere chopper harvesters in eastern Thailand. Six engineering-relevant predictors were retained after multicollinearity screening, and linear (MLR), additive nonlinear (GAM), and tree-based models were compared under 5-fold grouped cross-validation by BaseField (87 groups). Eff was assigned to GAM (R²CV = 0.621 ± 0.114) on the basis of its threshold-like response to turning frequency; Ca was retained for MLR (R²CV = 0.681 ± 0.121), with GAM essentially tied. Train–validation gaps were substantially smaller for additive models (0.096–0.118) than for tuned tree-based candidates (GBR 0.210–0.302, RF 0.322–0.358). Turning frequency (TF) and perimeter-to-area ratio (PAR) were the strongest predictors, and a constant-turn-time partial-out test indicated that TF's univariate effect on Eff is largely mediated by the time-budget identity. Tactical interventions (path planning, operator training, machine–field allocation) are immediately feasible, although strategic field-layout change remains constrained by smallholder land tenure.

Abstract: Bitter taste receptors (T2Rs), specifically T2R38, are present in the respiratory epithelium and react with bacterial quorum-sensing molecules to induce an innate immunity response. Although T2R38 polymorphisms have been correlated with susceptibility to chronic rhinosinusitis (CRS), they have not yet been explored in odontogenic rhinosinusitis (ORS), a distinct form of CRS with particular microbial and inflammatory features. Objectives: We aim to establish a proof-of-concept methodology for investigating T2R38 genetic variants in ORS using direct maxillary sinus tissue analysis and demonstrate the feasibility of this translational approach. Methods: We conducted a prospective case-control study of 36 ORS patients and 37 controls undergoing septoplasty without sinonasal disease. Maxillary sinus mucosal biopsies were obtained intraoperatively with informed consent. Genomic DNA was extracted using the PureLink Genomic DNA Mini Kit and quantified via NanoDrop spectrophotometry. T2R38 haplotypes were determined and classified as taster (PAV/PAV), non-taster (AVI/AVI), or intermediate (PAV/AVI) phenotype. Results: T2R38 phenotype distributions between ORS patients and controls were: tasters 11.1% vs 18.9%, non-tasters 27.8% vs 18.9%, and intermediate phenotypes 50.0% vs 37.8%, respectively. Statistical analysis revealed no significant association between T2R38 phenotypes and ORS susceptibility (Pearson χ² = 0.372, df = 1, p = 0.542; Fisher's exact test p = 0.595). The effect size was minimal (φ = 0.07). Non-taster phenotype showed a non-significant trend toward higher prevalence in ORS patients (OR = 1.4, 95% CI: 0.5–3.9, p > 0.5), though this finding lacks statistical power given the sample size. Conclusion: This proof-of-concept study successfully demonstrates the feasibility of T2R38 genotyping from maxillary sinus mucosa in ORS patients, establishing a novel methodological framework for investigating genetic factors in odontogenic sinonasal disease. While preliminary findings suggest potential phenotype differences (non-taster prevalence: 27.8% vs 18.9%), the study's primary value lies in validating the translational approach and informing power calculations for definitive multicenter investigations. This methodology provides the foundation for future studies to elucidate the role of taste receptor genetics in ORS pathogenesis and potentially guide personalized therapeutic strategies.

Abstract: Objectives: Paramedics are at elevated risk for adverse mental health outcomes due to occupational exposures including trauma, workplace violence, and chronic operational stress. Community Paramedicine (CP) represents an evolving model of care in which paramedics provide scheduled, non-urgent clinical and psychosocial support, potentially altering exposure profiles and the associated mental health risks. Our objective was to estimate the prevalence of mental health concerns among community paramedics and compare their risk of adverse mental health outcomes with paramedics working in 9-1-1 emergency response roles. Methods: We conducted a cross-sectional survey of paramedics from two Ontario services during compulsory in-person continuing medical education sessions from September to December 2024. Participants completed validated self-report screening tools for posttraumatic stress disorder, major depressive disorder, generalized anxiety disorder, insomnia, alcohol use, and burnout. We used logistic regression models adjusted for demographic variables to assess the association between CP role and mental health outcomes. Results: A total of 995 paramedics participated (96% of eligible), including 63 (6%) assigned to CP roles. Overall, 12% screened positive for PTSD, 25% for major depressive disorder, 23% for generalized anxiety disorder, 30% for insomnia, and 36% for at least moderate burnout. CPs had significantly lower adjusted risk of major depressive disorder compared to paramedics in 9-1-1 response roles (adjusted odds ratio [aOR] 0.45, 95% confidence interval [CI] 0.20-0.98). For other outcomes, our point estimates favored lower risk among CPs but did not reach statistical significance, including a composite outcome of PTSD, major depressive disorder, or generalized anxiety disorder (aOR 0.81, 95% CI 0.46-1.45). Conclusions: Community paramedics demonstrated a lower adjusted risk of major depressive disorder and a consistent, though non-significant, pattern toward lower risk across multiple mental health outcomes compared to paramedics in 9-1-1 response roles. These findings suggest a potentially different occupational risk profile associated with CP practice environments. Further longitudinal and mixed-methods research is warranted.

Abstract: Background/Objectives: Sellar solitary fibrous tumors (SFTs) are exceptionally rare mesenchymal neoplasms that frequently mimic non-functioning pituitary adenomas both clinically and radiologically. Because of their nonspecific imaging characteristics, accurate preoperative diagnosis remains challenging and often requires histopathological and immunohistochemical confirmation. Nuclear STAT6 expression has become a key diagnostic marker for this entity. Methods: We present a case-based diagnostic analysis of a high-grade (WHO grade 3) sellar SFT initially misdiagnosed as a pituitary adenoma. Clinical, radiological, intraoperative, and histopathological findings were systematically evaluated and correlated. In addition, previously reported sellar SFT cases were reviewed to identify recurring diagnostic patterns and pitfalls. Results: A 65-year-old male presented with headache, progressive visual impairment, and hypopituitarism. Magnetic resonance imaging demonstrated a heterogeneously enhancing sellar mass with suprasellar extension and cavernous sinus involvement, leading to a presumptive diagnosis of pituitary adenoma. Intraoperatively, the lesion was markedly hypervascular and fibrous, raising suspicion for an alternative diagnosis. Histopathological examination revealed a spindle-cell neoplasm with a hemangiopericytoma-like vascular pattern, increased mitotic activity, and strong nuclear STAT6 positivity, confirming a WHO grade 3 SFT. Literature analysis showed that most reported sellar SFTs share overlapping MRI features with pituitary adenomas and are frequently misdiagnosed preoperatively. Conclusions: Sellar SFT should be considered in the differential diagnosis of atypical sellar lesions, particularly when imaging findings are inconclusive and intraoperative features suggest a hypervascular and fibrous tumor. Radiological–pathological correlation, including STAT6 immunohistochemistry, is critical for accurate diagnosis. Increased awareness of these diagnostic pitfalls may improve recognition of this rare entity and guide surgical and pathological decision-making.

Abstract: Consolidated bioprocessing (CBP), where enzyme production, substrate hydrolysis, and fermentation occur in a single bioreactor, provides a promising pathway for lignocellulosic ethanol production. Nevertheless, CBP operation involves trade-offs among ethanol titer, productivity, substrate conversion, soluble sugar accumulation, batch cycle time, and the operating severity associated with temperature and pH profiles. This study introduces a feasibility-aware multi-objective dynamic optimization approach for identifying Pareto-optimal operating policies for batch CBP processes. A simplified, mechanistically driven dynamic model is developed to represent biomass growth, enzyme activity, insoluble substrate hydrolysis, soluble sugar formation and consumption, ethanol production, and inhibition under time-varying temperature and pH profiles. The multi-objective optimization simultaneously maximizes ethanol titer, productivity, and substrate conversion while minimizing sugar accumulation, operating severity, control effort, and batch time. In the main simulation run, 120,000 dynamic policies were evaluated, resulting in 5,017 feasible policies and 328 feasible Pareto-optimal policies under a minimum conversion threshold of 0.42. The optimized dynamic policy achieved an ethanol titer of 1.265 g L−1, a maximum productivity of 0.017 g L−1 h−1, and a maximum conversion of 0.440. Compared with the best static policies, the dynamic Pareto policies improved ethanol titer, productivity, and conversion by 10.6%, 8.3%, and 14.3%, respectively. The feasibility analysis showed that a conversion threshold of 0.42 is stringent but achievable, whereas thresholds of 0.44 and 0.55 were not attainable under the current dynamic model and operating range. Independent-seed repetition confirmed the existence of a consistent high-performing region across different stochastic searches. The resulting Pareto front and operating-policy charts provide a useful basis for selecting temperature and pH profiles for CBP process operation.