Nevin Manimala

Environ Sci Technol. 2026 Mar 23. doi: 10.1021/acs.est.6c01728. Online ahead of print.

ABSTRACT

Alkylated polycyclic aromatic hydrocarbons (APAHs) often possess higher toxicity than their parent compounds, yet global inventories largely overlook their direct volatilization from crude oil spills. To quantify this missing pathway, we developed a Monte Carlo framework that estimates this non-combustion source by coupling empirical spill statistics, APAH composition from 18 crude oils, and marine/terrestrial volatilization efficiencies. Across eight validated volatile species (C1-C4 naphthalenes, C1 phenanthrenes, C1-C3 fluorenes), global emissions span 3.4-73.4 kt/year (95% confidence interval), with a median of ∼17.5 kt/year. Notably, methylnaphthalenes (MeNAPs) alone account for ∼5.9% of their known global atmospheric emissions. Although global inventories for other homologues are unavailable, absolute fluxes of C2-C4 naphthalenes are comparable to or exceed MeNAPs, underscoring oil spills as a substantial, previously unquantified source of light APAHs. Sensitivity analyses highlight key uncertainties in spill volumes, crude compositions, and volatilization ratios; assumptions of parameter independence may understate extreme events. It is important to note that, due to the exclusion of dynamic meteorological suppression factors (e.g., low temperature and calm winds), these estimates represent a potential source strength. Incorporating this non-combustion pathway into inventories is therefore critical for accurate environmental risk assessments and regulatory policies.

PMID:41870409 | DOI:10.1021/acs.est.6c01728

J Nurs Manag. 2026;2026(1):e5604987. doi: 10.1155/jonm/5604987.

ABSTRACT

BACKGROUND: Occupational burnout poses a persistent threat to nurses’ mental health and the quality of patient care. Emerging evidence indicates that burnout is not a uniform phenomenon but manifests in distinct psychological patterns. Yet, how these diverse burnout experiences interact with safety-related factors is insufficiently understood. Network analysis offers a systems-level perspective to uncover interconnections among psychological and safety variables and to pinpoint potential bridge nodes for targeted interventions.

AIM: This study sought to map the network architecture linking psychological and safety-related factors among nurses across different burnout profiles, to identify profile-specific central and bridge nodes, and to examine their associations with safety behaviors.

METHODS: A total of 2092 nurses were included. This study was a secondary analysis based on a previously established dataset in which three distinct burnout profiles were identified using latent profile analysis: the High Achievement Stable Group (Class 1, 70.3%), the High Efficiency Contradictory Group (Class 2, 6.6%), and the High Pressure Adaptive Group (Class 3, 23.1%). Psychological-safety networks were estimated for both the overall sample and each subgroup using the EBICglasso model. Centrality and bridging indices were computed via expected influence and bridge expected influence, followed by network comparison tests to evaluate structural variations across profiles.

RESULTS: In the overall network, “skills” (B4) exhibited the greatest centrality, whereas “personal accomplishment” (A3) and “knowledge” (B1) consistently functioned as pivotal bridge nodes across profiles. Although bridge configurations differed slightly among classes, A3 and B1 remained the principal connectors integrating psychological and safety communities. Significant structural differences were detected between Classes 2 and 1 (M test, p < 0.001) and between Classes 3 and 1 (M test, p < 0.001; S test, p = 0.002), with pronounced discrepancies in the edge patterns surrounding A3 and B1.

CONCLUSIONS: The burnout-safety networks revealed distinct structural configurations across nurse subgroups. Identifying profile-specific bridge nodes offers practical guidance for precision interventions that enhance safety behaviors and foster occupational resilience.

PMID:41870377 | DOI:10.1155/jonm/5604987

J Exp Psychol Gen. 2026 Mar 23. doi: 10.1037/xge0001911. Online ahead of print.

ABSTRACT

According to the theory of efficient coding, sensory processing is optimized for representing the information content of natural scenes. This implies that perceptual systems are adapted to the statistical regularities of the environments they are immersed in. In color vision, relatively low sensitivity for discriminating color along blue and yellow axes has been linked to the dominance of blue-yellow color variation in natural scenes. It has been suggested that higher order visual processes, such as aesthetic preferences, could also be adapted to natural environments. Here, we manipulate the chromatic contrast of natural scenes to test whether low-, medium-, and high-level aspects of color perception can be calibrated to the color statistics of visual environments. In three experiments, we measured color discrimination, chromatic balance perception, and aesthetic judgments of colorful Mondrian patterns after adaptation to scenes with natural colors or scenes with manipulated colors. After viewing naturally colored scenes, color discrimination, perception of chromatic balance, and color preferences are biased along the blue-yellow color axis, along which there is most chromatic variance in natural scenes. Blue-yellow biases were reduced or partially inverted following adaptation to color-manipulated scenes, though the extent of the reversal in bias we observed following short-term adaptation appears to have been limited by long-term adaptation to the color statistics of natural environments. Our findings support the efficient coding theory and provide experimental support for the hypothesis that multiple attributes of human color perception adapt to the color statistics of visual environments. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:41870374 | DOI:10.1037/xge0001911

J Couns Psychol. 2026 Mar 23. doi: 10.1037/cou0000867. Online ahead of print.

ABSTRACT

The working alliance is hypothesized to be crucial for facilitating change during psychodynamic therapy. However, few studies have examined the session-by-session effects of the alliance on outcomes within this therapeutic approach. We aimed to test the effect of the client- and therapist-reported alliance on next-session problems/functioning in short-term psychodynamic therapy conducted in a university training clinic. A secondary aim was to test whether baseline personality functioning and adverse childhood experiences moderate the association between alliance and outcome. A total of 152 clients, receiving short-term psychodynamic psychotherapy from novice therapists, completed the Clinical Outcomes in Routine Evaluation-10 before each session. After each session, clients and therapists completed the Working Alliance Inventory-Short. Data were analyzed using continuous time structural equation modeling, which allows for relatively strong causal inferences despite the nonexperimental design. Improvement in the client-reported alliance significantly predicted a reduction of problems/dysfunction in the following session with a small effect size that increased to a large effect size after 7-8 sessions. The effect of problems/functioning on the client-reported alliance was also statistically significant. No associations were found between the therapist-reported alliance and outcome. The alliance effect varied considerably between therapist-client dyads and was stronger for clients reporting more adverse childhood experiences. In conclusion, the client-reported alliance was a predictor of outcome in the following session. Its effect on outcome peaked after 7-8 sessions. While this long-term effect aligns with the principles of psychodynamic therapy, it may also stem from the statistical model used. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:41870354 | DOI:10.1037/cou0000867

Cancer Biol Med. 2026 Mar 20:j.issn.2095-3941.2025.0625. doi: 10.20892/j.issn.2095-3941.2025.0625. Online ahead of print.

ABSTRACT

OBJECTIVE: This study was aimed at analyzing temporal trends in lung cancer mortality from 2013 to 2021, and projecting future trends until 2030.

METHODS: Mortality data were extracted from the China Causes of Death Surveillance Dataset, which covers 2.37 billion person-years. Age-standardized mortality rates (ASMRs) were calculated with Segi’s world standard population. Joinpoint regression was used to analyze temporal trends, and linear regression was applied to assess changes in mean age at death. A Bayesian age-period-cohort model was used to project mortality trends through 2030. Contributions of risk factors and demographic changes (population size and age structure) to mortality trends were decomposed with the population split method.

RESULTS: From 2013 to 2021, the crude lung cancer mortality rate increased by 2.3% annually, whereas the ASMR remained stable overall but showed significant 2.9% annual declines during 2015 and 2021. The ASMRs in urban areas (-2.9% per year) and eastern regions (-1.5% per year) showed significant decreasing trends throughout the entire period. The mean age at death increased across all areas, and the largest increases were observed in rural areas. Deaths among people ≥65 years of age rose by 1.6%-5.6% during the entire period. Decomposition analysis indicated that the increased death counts were driven primarily by population aging (32%-43%) and population growth (8%-31%), whereas risk factors contributed negatively (-3% to -29%). Projections suggested that the number of lung cancer deaths will reach approximately 760,200 by 2030, with continued increases in the crude mortality rate but slight declines in the ASMR.

CONCLUSIONS: The lung cancer burden in China shows marked regional disparities and challenges due to population aging. To further decrease lung cancer deaths, optimized allocation of medical resources, strengthened prevention and control of lung cancer risk factors, and integration of effective policies will be required.

PMID:41870348 | DOI:10.20892/j.issn.2095-3941.2025.0625

Anesthesiology. 2026 Mar 23. doi: 10.1097/ALN.0000000000006059. Online ahead of print.

ABSTRACT

BACKGROUND: Cryoneurolysis provides analgesia by reversibly ablating peripheral nerves using gas-induced exceptionally low temperature. The desired therapeutic temperature is between approximately -20°C and -100°C. Warmer temperatures can induce a neuropraxia that may itself induce pain; and colder temperatures can result in permanent nerve injury. Therefore, it is imperative that the target nerve reach but not exceed the therapeutic window.

METHODS: A convenience sample of participants undergoing mastectomy (n=3) received a high-thoracic paravertebral nerve block, while subjects being treated for traumatic rib fractures (n=3) did not. All participants had ultrasound-guided cryoneurolysis of multiple intercostal nerves with a percutaneous thermocouple inserted approximately 3 mm adjacent to the cryoprobe shaft. The returning argon gas and tissue temperatures were correlated. Due to the limited sample size, the data are presented and not statistically analyzed.

RESULTS: Although in all cases (31 nerves) the returning gas was ultimately colder than -80°C, the tissue adjacent to the probe did not reach -20°C after 3 and 5 min in 71% (n=5) and 42% (n=10) of treatments, respectively. The coldest mean temperature in adjacent tissue was 60 degrees warmer than the returning gas without a nerve block, and 95 degrees warmer with a concurrent nerve block. When treating adjacent intercostal nerves, the gas temperature remained unchanged while the tissue became colder with each consecutive treatment.

CONCLUSIONS: During percutaneous cryoneurolysis, the temperature of tissue is frequently deceptively warm relative to the returning gas and tissue frequently does not reach an adequately cold temperature; prolonging gas treatment from 3 to 5 min improves the success of reaching therapeutic temperatures; the presence of a peripheral nerve block appears to lessen the chance of reaching therapeutic temperatures; and caution is warranted when treating consecutive intercostal nerves as tissue temperature may decrease with each level.

PMID:41870345 | DOI:10.1097/ALN.0000000000006059

J Pregnancy. 2026;2026(1):e2785076. doi: 10.1155/jp/2785076.

ABSTRACT

INTRODUCTION: In sub-Saharan African region, high-maternal mortality is high due to complications of labor, delivery as well as low patronage of antenatal care and skilled birth attendants (SBAs), poverty and poor health-seeking behavior. Although considerable studies exist on drivers of choice of birth locations, there is a paucity of current, nationally representative samples from various SSA countries examining factors influencing birthplace choices. This study addresses this gap by employing a recent dataset to assess the determinants of changing birth locations in SSA.

METHODS: This cross-sectional study used the most recent Demographic and Health Survey (DHS) data from 30 sub-Saharan African countries collected between 2014 and 2024, comprising 61,240 women aged 15-49. Two outcomes were examined: (i) any change in childbirth location between the two most recent births, and (ii) a shift from home to health-facility delivery. Two binary logistic regression models were fitted to identify factors associated with each outcome, with checks for multicollinearity conducted using variance inflation factors and tolerance indices. Survey design was accounted for in our regression analyses (sampling weights and clustering).

RESULTS: Overall, 13.59% (n = 8320) of women changed their childbirth location between their two most recent births, and more than half of these women (54.35%) shifted from home to a healthcare facility. The highest change is observed in Uganda where 20.36% (95% CI; 19.07-21.66) changed their location of childbirth, and the lowest is observed in Burkina Faso where only 5.24% (95% CI; 2.99-7.48) changed their location of childbirth. The probability of changing birth location from home to a healthcare facility increased with the level of education, with those with higher education having a higher likelihood of changing from home to a facility (AOR = 2.76, 95% CI: 1.53-4.97) compared with those with no education. The odds of changing birth location from home to a healthcare facility increase with wealth status, particularly for women in the richest category (AOR = 2.31, 95% CI: 1.79-2.97) relative to those in the poorest category. Women in rural areas are 34% less likely to change from home to a facility compared with those in urban areas (AOR = 0.66, 95% CI: 0.57-0.76).

CONCLUSION: Our study highlights significant disparities in changes in childbirth locations across SSA countries, driven primarily by education, wealth, and rural-urban residence. Although countries like Malawi and Zimbabwe demonstrate successful strategies for promoting facility-based deliveries, others like Chad and Burkina Faso face persistent barriers. Addressing these disparities requires targeted interventions, including expanding rural healthcare infrastructure and implementing pro-poor healthcare policies. Future research and program designs should prioritize longitudinal assessments of these determinants to tailor interventions for specific country contexts.

PMID:41870343 | DOI:10.1155/jp/2785076

Int J Nanomedicine. 2026 Mar 16;21:588259. doi: 10.2147/IJN.S588259. eCollection 2026.

ABSTRACT

INTRODUCTION: To address the poor water solubility and low bioavailability of the curcumin derivative CU1, this study constructed a long-circulating pH-sensitive nanoliposome (CU1-LCpHL) as its delivery system.

METHODS: The physicochemical properties, stability, and anti-lung cancer efficacy of CU1-LCpHL were systematically evaluated, including in vitro cellular assays (cellular uptake, apoptosis, proliferation, and migration), in vivo pharmacokinetics and pharmacodynamics, mechanistic studies, and immunohistochemical analysis.

RESULTS: CU1-LCpHL presented a spherical morphology with uniform particle size. Its lyophilized powder remained stable for at least three months at 25°C and exhibited sustained-release characteristics. In vitro experiments demonstrated that, compared to free curcumin (CU), free CU1, and long-circulating stable nanoliposomes (CU1-LSLN), CU1-LCpHL promoted more efficient cellular uptake, induced apoptosis, and significantly inhibited the proliferation and migration of lung cancer cells. Pharmacokinetic studies revealed that the area under the curve (AUC_0-t) of CU1-LCpHL was 9.52-fold and 9.47-fold higher than that of CU and CU1, respectively, while its mean residence time (MRT_0-t) was 3.37-fold and 7.69-fold longer, respectively. In vivo pharmacodynamic results indicated that the tumor-inhibition rate of CU1-LCpHL was 2.42-, 2.17-, and 1.37-fold higher than those of CU, CU1, and CU1-LSLN, respectively, with no significant organ toxicity or hemolysis observed. Mechanistic studies showed that CU1-LCpHL significantly upregulated Caspase-3, Caspase-9, and Bax, while downregulating the p-AKT/AKT ratio and Bcl-2 levels. Immunohistochemical analysis further confirmed that CU1-LCpHL markedly reduced the positive expression of Ki67, CD34, and VEGFR2, outperforming all other treatment groups.

CONCLUSION: CU1-LCpHL significantly enhances the delivery efficiency and antitumor efficacy of CU1, representing a promising nano-drug delivery system for lung cancer therapy.

PMID:41869398 | PMC:PMC13004129 | DOI:10.2147/IJN.S588259

Front Surg. 2026 Mar 5;13:1730726. doi: 10.3389/fsurg.2026.1730726. eCollection 2026.

ABSTRACT

BACKGROUND: Superior labrum anterior and posterior (SLAP) lesions are a common cause of shoulder pain and instability. Developing accurate, non-invasive diagnostic tools is essential to support clinical decision-making for SLAP lesions. This study aimed to establish an automated diagnostic model for SLAP lesions using a 2.5D deep learning framework combined with ensemble learning and to evaluate its clinical utility.

METHODS: In this retrospective study, 185 patients who underwent shoulder arthroscopy between January 2019 and September 2025 were included (91 SLAP lesions, 94 controls). Preoperative shoulder magnetic resonance imaging (MRI) data were analysed. Images from three consecutive slices, centred on the maximal region of interest (ROI), were processed using a Wide_ResNet101_2 network pre-trained on ImageNet for deep feature extraction and probability prediction. A decision-level fusion strategy integrated the predicted probabilities from all three layers as input features for three ensemble classifiers: AdaBoost, Random Forest, and XGBoost. Model performance was assessed with accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, specificity, precision, and F1-score. The DeLong test and integrated discrimination improvement (IDI) were used to compare models.

RESULTS: All ensemble models exhibited robust diagnostic performance. On the test set, the XGBoost model achieved the highest AUC (0.754) and sensitivity (0.933), though specificity was moderate (0.538). The Random Forest model yielded an AUC of 0.745, while the AdaBoost model achieved an AUC of 0.731. F1-scores ranged from 0.75 to 0.80. There were no statistically significant differences in AUC among the models. Feature importance analysis highlighted the central MRI slice as most contributory. Model interpretability assessments showed that the network focused predominantly on the biceps-labral complex, which is anatomically consistent with SLAP pathology.

CONCLUSIONS: The proposed automated diagnostic model, utilising a 2.5D deep learning and ensemble approach, demonstrated favourable diagnostic performance and clinical applicability for SLAP lesion detection on shoulder MRI. Among the ensemble strategies, the XGBoost model provided the highest sensitivity, rendering it particularly suitable as a clinical decision-support tool. The multi-slice information fusion framework substantially improved diagnostic accuracy, supporting its potential as a novel artificial intelligence solution to assist radiologists in diagnosing shoulder labral injuries.

PMID:41869384 | PMC:PMC12999963 | DOI:10.3389/fsurg.2026.1730726

Front Surg. 2026 Mar 5;13:1737152. doi: 10.3389/fsurg.2026.1737152. eCollection 2026.

ABSTRACT

STUDY DESIGN: Systematic review and update meta-analysis.

PURPOSE: This systematic review and meta-analysis was conducted to determine the effect of preoperative (neoadjuvant) chemotherapy with 5-fluorouracil (intraperitoneal) on the integrity of colorectal anastomoses in an experimental rat model.

OVERVIEW OF LITERATURE: Emergency surgery in cancer patients undergoing chemotherapy is associated with an increased risk of complications, including anastomotic leakage, and worse survival outcomes. 5FU is widely used in the treatment of GI tumors. The effect of 5FU on anastomotic integrity has been demonstrated previously; this meta-analysis provides a quantitative assessment of this effect.

METHODS: A literature search was conducted using PubMed and Google Scholar in MEDLINE up to May 2025. Only experimental studies on rat models were selected, which compared a Control group (no chemotherapy) and a group receiving intraperitoneal 5FU. The following outcomes were extracted: anastomotic bursting pressure, severity of adhesion formation, and hydroxyproline levels.

RESULTS: Six studies were included in the meta-analysis. Statistically significant results demonstrated the superiority of the Control group over the 5FU group in terms of hydroxyproline levels (p < 0.00001). The severity of adhesion formation was higher in the group treated with 5FU (p = 0.59). The anastomotic bursting pressure was higher in the Control group (p = 0.36).

CONCLUSIONS: 5FU had a negative impact on the integrity of the anastomotic suture line, as evidenced by lower hydroxyproline levels. Lower bursting pressure and a higher degree of adhesions were found in the 5FU group; however, these results were not statistically significant.

PMID:41869383 | PMC:PMC12999958 | DOI:10.3389/fsurg.2026.1737152