Advancing Open Science

Background/Objectives: Chronic medical conditions may contribute to psychological burden among individuals with cancer. This study examined associations between chronic medical conditions and posttraumatic stress, depressive symptoms, anxiety, and perceived stress among Puerto Rican adults with a self-reported cancer diagnosis. Methods: This quantitative secondary analysis used baseline data from a longitudinal study (N = 402) conducted in Puerto Rico following Hurricane Maria. The analytic sample included 108 adults with a self-reported cancer diagnosis. Psychological outcomes were assessed using the PCL-5, PHQ-8, GAD-7, and PSS. Mann–Whitney U and chi-square tests were conducted, followed by multivariable logistic and linear regression models adjusting for co-occurring conditions, age, and gender. Results: Asthma was associated with higher posttraumatic stress, depressive symptoms, and perceived stress scores; arthritis with higher depressive symptoms, anxiety, and perceived stress; and thyroid disorders with higher anxiety symptoms. Unadjusted analyses showed associations between asthma and clinically significant posttraumatic stress symptoms (OR = 3.13) and thyroid disorders and anxiety symptoms (OR = 2.90). After adjustment, thyroid disorders remained associated with clinically significant anxiety (aOR = 2.70, p = 0.041), whereas asthma was no longer significantly associated with posttraumatic stress (aOR = 2.45, p = 0.116). Self-reported depression was associated with all psychological outcomes in adjusted models. Conclusions: Specific chronic medical conditions were associated with psychological burden among adults with cancer, supporting psychological screening and coordinated care.

Background/Objectives: Primary airway epithelia grown at air–liquid interface (ALI) are widely used to model respiratory endophenotypes and to enable individualized functional testing. However, culture conditions used to establish ALI vary considerably and may introduce selection biases. We aimed to adapt our lung explant-based ALI protocol to nasal basal cells obtained by minimally invasive brushing and to identify expansion conditions that optimize the number of primary epithelia that can be generated from nasal brushing while preserving donor-specific features. Methods: Primary nasal basal cells from nine healthy adult donors were expanded using different protocol variations in a paired design. We systematically varied two factors during the expansion phase: (a) supplementation with Rho-associated kinase (ROCK) and SMAD pathway inhibitors and (b) a single passage prior to ALI differentiation. Outcomes included the likelihood of obtaining a well-formed, differentiated ALI epithelium and functional readouts relevant to respiratory phenotyping. Results: The probability of establishing a well-differentiated ALI epithelium in a single attempt was highest when expansion was performed without ROCK/SMAD inhibitors and without passaging. Among successfully established ALI cultures, replicate inserts from the same donor showed comparable CFTR expression and ciliary beat frequency; however, functional chloride secretion could only be robustly detected in a subset of epithelia and was associated with low epithelial apoptosis. Conclusions: Avoiding strong selection pressures during the expansion phase—by omitting ROCK/SMAD inhibitors and minimizing passaging—improves the success rate of obtaining well-differentiating primary nasal ALI cultures and likely preserves cellular diversity among founder cells of the epithelium. These findings support the use of patient-derived nasal ALI cultures as robust, reproducible platforms for individualized respiratory phenotyping and functional assessment in personalized medicine.

Bank-funded supply chain finance can support retailers’ inventory purchases, but compensating core suppliers for hidden monitoring effort can reduce lending profits. This study examines how banks should design monitoring incentives for core suppliers that sell inventory to cash-constrained retailers. The contribution of the three-party principal–agent model is to link supplier trading earnings, the retailer’s order and borrowing response, and the bank’s default recovery. Least-cost supplier contracts are derived under participation, incentive and payment-floor constraints, and illustrative financing offers are compared on nested grids. The illustrative results show that baseline financing supports larger retailer orders and higher retailer profits than self-financing, while low monitoring effort is preferred because the additional recovery from high effort is outweighed by its incentive cost. Lower effort costs and more informative signals can make high effort preferable without increasing retailer orders. A common minimum supplier payment reduces bank profitability and, when sufficiently high in the tested scenarios, leads to no financing. These illustrative grid findings support assessing monitoring’s recovery gains against incentive costs and retailer responses; they do not establish a continuous-offer equilibrium.

To reveal the relative effects and interaction mechanism of soil acidification and nitrogen regulation on the growth of Chinese fir (Cunninghamia lanceolata) and to provide a scientific basis for the prevention and control of Chinese fir plantation decline, we conducted an 18-month greenhouse pot experiment using 1-year-old Chinese fir saplings. The experiment combined three acid solution spraying gradients to simulate soil acidification (control S0, distilled water; low acidification LS, acid solution pH 4.5; high acidification HS, acid solution pH 3.5; the initial soil pH was 6.3; acidification was simulated by spraying a mixed acid solution of H₂SO₄ and HNO₃ at a molar ratio of 5:1) with three nitrogen application levels (no nitrogen N0, 0; low nitrogen LN, 50 mg N·kg⁻¹ dry soil; high nitrogen HN, 200 mg N·kg⁻¹ dry soil), forming nine treatment groups in total. Correlation analysis and a structural equation model (SEM) were used to analyze the influencing pathways. Soil acidification significantly reduced soil pH and nitrate nitrogen content, inhibited sapling growth, impaired the function of the photosynthetic system, and excessively activated superoxide dismutase (SOD) activity, which showed an extremely significant negative correlation with growth rate (−0.83). The total inhibitory effect of soil acidification on sapling growth reached 0.792, operating through direct growth inhibition, impaired nutrient supply, and enhanced antioxidant defense responses. Nitrogen application significantly increased soil available nitrogen content and alleviated stress under low acidification conditions by improving chlorophyll synthesis and photosynthetic efficiency; however, it had no significant direct effect on growth rate (0.15) and slightly exacerbated soil acidification (−0.45). The alleviating effect of nitrogen was completely lost under high acidification treatment with acid solution pH 3.5. The structural equation model showed a good fit (p = 0.379, GFI = 0.940, RMSEA = 0.051), confirming that soil acidification was the core dominant factor restricting Chinese fir growth. These results provide theoretical support and technical reference for precise nutrient management and decline control of Chinese fir plantations in southern China.

This study evaluated whether short-term extraction of Thymus vulgaris L. with solvents of different polarity selectively modifies the essential-oil (EO) fingerprint of post-extraction biomass. The initial material contained 1.85% v/w EO, dominated by thymol (53.65%), p-cymene (21.53%), and γ-terpinene (5.28%). Water, 65% glycerol–water, rapeseed oil, and 50% ethanol–water were compared under different time and temperature conditions. Selective retention of six markers was assessed using an apparent marker retention index (AMRI), combining residual EO content with relative GC-FID composition, together with SEF, thymol-profile ratios, and CLR-PCA. Under solvent-specific reference conditions, thymol AMRI was 59.2% for water, 39.3% for glycerol, 18.4% for oil, and 27.2% for ethanol. The strongest relative enrichment occurred for (E)-caryophyllene after glycerol extraction (AMRI 149.8%; SEF 3.26). CLR-PCA explained 90.2% of compositional variability in the first two components and revealed solvent-dependent reorganization of the marker profile. Water and nanowater produced the highest integrated polar-functional response based on TPC, TFC, and DPPH. These results show that extraction can selectively modify the chemical fingerprint of the residual volatile fraction without implying a change in the biologically determined chemotype, supporting targeted fractionation and sequential use of post-extraction thyme biomass.

Multifunctional hybrid spheres were developed via ionic gelation, using sodium alginate as an encapsulating matrix to integrate TiO₂, Fe₃O₄, activated carbon, hypochlorite-impregnated clinoptilolite zeolite, and metallic copper, followed by chitosan coating and glutaraldehyde cross-linking to enhance mechanical stability. The material combines photocatalytic, adsorbent, antimicrobial, and magnetic functions in a single system, expected to support partial treatment of contaminated water. X-ray diffraction confirmed the expected crystalline phases with no impurities. Physicochemical evaluation showed reductions in turbidity (1.8 to 0.7 NTU), total hardness (306 to 150 mg/L), iron (0.4 to 0.01 mg/L), and lead (<0.001 mg/L), while free residual chlorine remained within permissible limits. Microbiologically, fecal coliforms decreased from 83 to <1.5 CFU/100 mL and total coliforms from 839 to 19 CFU/100 mL. Photocatalytic activity, evaluated using methylene blue, showed an absorbance decrease from 0.38 to 0.17 A.U. over 4 h, corresponding to a blank-corrected removal of 95.5% relative to clean water, fitted to a pseudo-first-order kinetic model (R² = 0.8868). These results demonstrate a synergistic effect among adsorption, photocatalysis, disinfection, and magnetic recovery, positioning the hybrid spheres as a promising alternative for sustainable water treatment technologies.

Maritime chokepoint exposure can be quantified, but supply-chain risk management still requires an ex ante decision about which alternatives to keep ready. The objective is to identify and evaluate an ex ante corridor-readiness portfolio before the disruption state is known, while accounting for shared regional capacity, distributional ambiguity, and tail risk. This study models the Eastern Mediterranean as an interconnected maritime-logistics system comprising five countries, five sectors, five corridors, and six empirically calibrated disruption states. A two-stage distributionally robust decision model couples pre-disruption corridor readiness with post-disruption flow recourse under shared regional capacities, Wasserstein ambiguity, and CVaR tail-risk pricing. Relative to the inferred status quo, the optimized portfolio reduces the composite USD-equivalent objective by USD 241.623 billion, equivalent to 22.6% of the model’s average annual trade-account base under the maintained normalization. This is a calibrated benchmark-distance-to-base ratio, not a realized saving. The optimized portfolio concentrates readiness and improves aggregate performance, yet it performs USD 14.465 billion worse in the Turkish Straits disruption state. Doubling and renormalizing that state’s policy weight shifts the portfolio away from the Turkish Straits and reverses the state-specific loss. The contribution is a transparent decision-analytics framework that places system boundaries, infrastructure interdependencies, advance preparedness, recourse, and residual vulnerability in one auditable supply-chain risk model.

The International Roughness Index (IRI) is a crucial indicator of rigid pavement performance and distress, and artificial neural networks (ANNs) have made pavement management system (PMS) forecasting more cost-effective. However, purely data-driven ANN models are not constrained to follow known physical trends and can behave unpredictably outside their training range. This study developed a physics-informed neural network (PINN) for predicting IRI in jointed plain concrete pavements (JPCPs) by incorporating an empirical equation from the Mechanistic-Empirical Pavement Design Guide (MEPDG) into the training loss, intended to bias predictions toward physically consistent trends. A total of 2705 observations from 394 U.S. and 6 Canadian pavement sections were used to train the model and compare it against a conventional ANN, standard regression, and the standalone MEPDG equation. The PINN achieved a coefficient of determination (R²) of 0.695 and a root mean square error (RMSE) of 11.79 in./mi. Its performance was comparable to the ANN (R² = 0.698, RMSE = 11.71 in./mi), and both outperformed the MEPDG equation and conventional regression. A closed-form equation was extracted from the trained ANN weights and biases. While the physics constraint did not improve predictive accuracy in this study, it offers a transparent, interpretable tool that agencies can apply directly to prioritize JPCP maintenance and rehabilitation without proprietary model files.