Tag: pubmed

Environ Technol. 2024 Aug 11:1-18. doi: 10.1080/09593330.2024.2388313. Online ahead of print.

ABSTRACT

High-salinity wastewater, owing to its intricate composition and challenging treatment requirements, poses a significant hurdle in water environmental governance. In this study, low-temperature evaporation technology is used to tackle wastewater containing the volatile organic compound such as N,N-dimethylacetamide (DMAC). Utilisation of comprehensive approaches involving experimental testing, mathematical modelling, and Aspen Plus software simulations, The influence of DMAC on evaporation efficiency is researched through the following factors which encompassing its effects on boiling point elevation, partial molar activation energy, and the formation of by-products. Additionally, the comparation of the impact of temperature, ionic strength, intermolecular interactions on the evaporation rate and the concentration of the volatile component DMAC in the condensate is also conducted in this study. After conducting a multiple linear regression analysis of evaporation efficiency using the Statistical Product and Service Solutions (SPSS) tool, it was discovered that temperature serves as the primary determinant influencing the evaporation rate. Additionally, ionic strength impacts solution viscosity, intermolecular interactions, and saturated vapour pressure by altering the intermolecular forces, thereby indirectly influencing both the evaporation rate and the quality of condensate water. The comparative analysis of single-effect and double-effect evaporation indicates that the optimal operating condition for double-effect evaporation yields an evaporation rate of 70%, with a remarkable 88% reduction in steam consumption compared to single one. Based on heat and mass balance principles, the mathematical model for double-effect evaporation is established to offer crucial data support for practical industrial applications.

PMID:39128844 | DOI:10.1080/09593330.2024.2388313

Glob Public Health. 2024 Jan;19(1):2386979. doi: 10.1080/17441692.2024.2386979. Epub 2024 Aug 11.

ABSTRACT

We piloted the delivery of a prototype couples-focused intervention, ‘Diabetes Together’ with 14 people living with diabetes (PLWD) and their partners, in Cape Town, South Africa in 2022. We aimed to: assess feasibility of recruiting couples in this setting; explore acceptability of intervention materials and changes needed; and investigate whether our prespecified logic model captured how the intervention may work. We used questionnaires, interviews and focus groups after each workshop and after couples completed counselling. We conducted a process evaluation to identify intervention modifications and used inductive thematic analysis to explore whether the data supported our logic model. Twelve of the 14 couples completed the second workshop and 2 couples completed two counselling sessions post-workshop. Feedback showed participants appreciated the intervention and limited improvements were made. Thematic analysis identified four main themes: (1) involving partners matters; (2) group work supports solidarity with other couples; (3) improving communication between partners is crucial; and (4) taking part helped couples to take control of diabetes. Data suggested the logic model should explicitly acknowledge the importance of group education and of equalising partners’ knowledge. This pilot suggests that ‘Diabetes Together’ increased knowledge and skills within couples and could facilitate improved, collaborative self-management of diabetes.

PMID:39128837 | DOI:10.1080/17441692.2024.2386979

Eur J Pharmacol. 2024 Aug 9:176877. doi: 10.1016/j.ejphar.2024.176877. Online ahead of print.

ABSTRACT

Breast cancer (BC) is the most common and malignant tumor diagnosed in women, with 2.9 million cases in 2023 and the fifth highest cancer-causing mortality worldwide. Recent developments in targeted therapy options for BC have demonstrated the promising potential of small interfering RNA (siRNA)-based cancer therapeutic approaches. As BC continues to be a global burden, siRNA therapy emerges as a potential treatment strategy to regulate disease-related genes in other types of cancers, including BC. siRNAs are tiny RNA molecules that, by preventing their expression, can specifically silence genes linked to the development of cancer. In order to increase the stability and effectiveness of siRNA delivery to BC cells, minimize off-target effects, and improve treatment efficacy, advanced delivery technologies such as lipid nanoparticles and nanocarriers have been created. Additionally, combination therapies, such as siRNAs that target multiple pathways are used in conjunction with conventional chemotherapy agents, have shown synergistic effects in various preclinical studies, opening up new treatment options for breast cancer that are personalized and precision medicine-oriented. Targeting important genes linked to BC growth, metastasis, and chemo-resistance has been reported in BC research using siRNA-based therapies. This study reviews recent reports on therapeutic approaches to siRNA for advanced treatment of BC. Furthermore, this review evaluates the role and mechanisms of siRNA in BC and demonstrates the potential of exploiting siRNA as a novel target for BC therapy.

PMID:39128807 | DOI:10.1016/j.ejphar.2024.176877

Hellenic J Cardiol. 2024 Aug 9:S1109-9666(24)00170-2. doi: 10.1016/j.hjc.2024.08.003. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to leverage real-world electronic medical record (EMR) data to develop interpretable machine learning models for diagnosis of Kawasaki disease, while also exploring and prioritizing the significant risk factors.

METHODS: A comprehensive study was conducted on 4,087 pediatric patients at the Children’s Hospital of Chongqing, China. The study collected demographic data, physical examination results, and laboratory findings. Statistical analyses were performed using SPSS 26.0. The optimal feature subset was employed to develop intelligent diagnostic prediction models based on the Light Gradient Boosting Machine (LGBM), Explainable Boosting Machine (EBM), Gradient Boosting Classifier (GBC), Fast Interpretable Greedy-Tree Sums (FIGS), Decision Tree (DT), AdaBoost Classifier (AdaBoost), and Logistic Regression (LR). Model performance was evaluated in three dimensions: discriminative ability via Receiver Operating Characteristic curves, calibration accuracy using calibration curves, and interpretability through Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME).

RESULTS: In this study, Kawasaki disease was diagnosed in 2,971 participants. Analysis was conducted on 31 indicators, including red blood cell distribution width and erythrocyte sedimentation rate. The EBM model demonstrated superior performance compared to other models, with an Area Under the Curve (AUC) of 0.97, second only to the GBC model. Furthermore, the EBM model exhibited the highest calibration accuracy and maintained its interpretability without relying on external analytical tools like SHAP and LIME, thus reducing interpretation biases. Platelet distribution width, total protein, and erythrocyte sedimentation rate were identified by the model as significant predictors for the diagnosis of Kawasaki disease.

CONCLUSIONS: This study employed diverse machine learning models for early diagnosis of Kawasaki disease. The findings demonstrated that interpretable models, like EBM, outperformed traditional machine learning models in terms of both interpretability and performance. Ensuring consistency between predictive models and clinical evidence is crucial for the successful integration of artificial intelligence into real-world clinical practice.

PMID:39128707 | DOI:10.1016/j.hjc.2024.08.003

Arthroscopy. 2024 Aug 9:S0749-8063(24)00551-6. doi: 10.1016/j.arthro.2024.07.023. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the change in hip distractive stability after a cam over-resection, labral tear, repair, labrectomy, or circumferential 6-mm or 10-mm labral reconstruction in a biomechanical model.

METHODS: Ten fresh-frozen matched pair human cadaveric hips were analyzed using a materials testing system to measure the force and distance required to disrupt the suction seal of the hip (1) with an intact capsule and labrum, (2) after a capsulectomy and labral repair, (3) after a capsulectomy, 5-mm cam over-resection and labral repair, (4) after a capsulectomy, 5-mm cam over-resection and labral tear, (5) after a capsulectomy, 5-mm cam over-resection and labrectomy, and (6) after a capsulectomy, 5-mm cam over-resection, and a 6- or 10-mm circumferential labral reconstruction with iliotibial band (5 hips each). Each specimen was retested at 0° flexion, 45° flexion, and 45° flexion and 15° internal rotation and analyzed using non-parametric statistical methods.

RESULTS: The Friedman test of differences was significant among structural conditions and hip positions (P = 0.001). In all positions, the resistive force that opposed the disruption of the suction seal in an intact hip was significantly greater compared to all other conditions. The resistive force for the capsulectomy, 5-mm cam over-resection and labrectomy condition was significantly less compared to almost all other conditions and hip positions. A qualitative suction seal was achieved in 20% of hip specimens with a 6-mm labral reconstruction while a seal was in achieved 60% of specimens with a 10-mm labral reconstruction.

CONCLUSIONS: After a cam over-resection, a circumferential labral reconstruction improves the distractive stability of a labral deficient hip, comparable to a labral repair or tear in a biomechanical model.

CLINICAL RELEVANCE: Circumferential labral reconstruction may be a viable treatment option for patients with ongoing symptoms after hip arthroscopy with evidence of a cam over-resection and a deficient labrum.

PMID:39128683 | DOI:10.1016/j.arthro.2024.07.023

Brain Res Bull. 2024 Aug 9:111048. doi: 10.1016/j.brainresbull.2024.111048. Online ahead of print.

ABSTRACT

BACKGROUND: Imagine if our brains could unconsciously predict future events. This study explores this concept, presenting evidence for an inherent ‘foreseeing’ ability, termed anomalous cognition (AC). We introduce a new experimentally verifiable approach to explain anomalous information anticipation (AIA), a type of AC, based on an innovative, quantum-like model of implicit learning, grounded in Nonlocal Plasticity Theory (NPT).

METHODS: Our research involved 203 participants using methods such as continuous flash suppression, random dot motion, and advanced 3D EEG neuroimaging, along with IBM quantum random event generators for precise measurements across 144 trials. These trials tested contingencies between undetectable sensory stimuli and dot movements, focusing on participants’ prediction abilities. The design conditions were strictly experimental, violating fundamental classical learning principles, particularly reflex conditioning. If these principles were immutable, their violation would prevent any systematic behavioral changes, resulting in random responses. This violation was implemented through two quantum physics concepts: the mathematical principle of nonlocality and entanglement.

RESULTS: Despite the sensory stimulus being inaccessible, our results showed a significant prediction between the contingencies and an increase in AIA accuracy, with explained variances between 25 and 48%. EEG findings supported this, showing a positive link between brain activity in specific regions and AIA success. Electrochemical activations were detected in the posterior occipital cortex, the intraparietal sulcus, and the medial temporal gyri. AIA hits exceeded the threshold value corresponding to one standard deviation above the expected mean, showing moderate effect sizes in the experimental group (Cohen’s d = 0.461). Analyzing the learning curve using the derivation technique, we identified the acceleration point of the wave function, indicating systematic implicit learning. This result showed that from repetition 63 onwards, AIA hits increased significantly.

CONCLUSIONS: The results suggest that, despite violating fundamental classical learning principles, cognitive processes produced changes in participants’ responses susceptible to neuromodulation, considering quantum physics principles of nonlocality and entanglement (both present in NPT). We discuss (a) why the priming effect does not explain the significant results; (b) the potential discovery of a new form of quantum-like implicit learning, which could scientifically resolve phenomena associated with anomalous cognitions (e.g., AIA or extraocular vision); and (c) future research directions, including potential applications and clinical impact.

PMID:39128676 | DOI:10.1016/j.brainresbull.2024.111048

Fertil Steril. 2024 Aug 9:S0015-0282(24)01938-1. doi: 10.1016/j.fertnstert.2024.08.315. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the impact of preimplantation genetic testing for aneuploidy (PGT-A) on first transfer live birth rate (LBR) and cumulative LBR (CLBR) in donor oocyte IVF cycles.

DESIGN: Retrospective cohort study of the SART CORS database.

SUBJECTS: 11,348 fresh and 7,214 frozen-thawed donor oocyte IVF cycles were analyzed.

EXPOSURE: The first reported donor stimulation cycle per patient between January 1, 2014 and December 31, 2015, and all linked embryo transfer cycles between January 1, 2014 and December 31, 2016, were included in the study.

MAIN OUTCOME MEASURES: LBR was compared for patients using fresh and frozen-thawed donor oocytes, with or without PGT-A. Logistic regression models were adjusted for age, body mass index, gravidity, infertility etiology, and prior IVF cycles.

RESULTS: Among patients who had blastocysts available for transfer or PGT-A, use of PGT-A was associated with a decreased first transfer LBR (46.9 vs 53.2%, p <0.001) and CLBR (58.4 vs 66.6%, p <0.001) in fresh oocyte donor cycles compared with no PGT-A. LBR in frozen-thawed oocyte donor cycles with PGT-A were nominally higher than those without PGTA (48.3% vs. 40.5%) but were not statistically significant in multivariable logistic regression models (p=0.14). Early pregnancy loss was not significantly different with and without PGT-A. Multiple gestation, preterm birth, and low birthweight infants were all reduced with addition of PGT-A in fresh donor oocyte cycles, though these outcomes were not significantly different when comparing single embryo transfers in fresh oocyte cycles and also not significantly different among frozen-thawed donor oocyte cycles.

CONCLUSION: PGT-A in fresh oocyte donor cycles was associated with decreased LBR and CLBR, while effects on frozen-thawed oocyte donor cycles were clinically negligible. Obstetrical benefits associated with PGT-A in fresh donor cycles appear linked to increased single embryo transfer.

PMID:39128672 | DOI:10.1016/j.fertnstert.2024.08.315

Fertil Steril. 2024 Aug 9:S0015-0282(24)01953-8. doi: 10.1016/j.fertnstert.2024.08.322. Online ahead of print.

ABSTRACT

IMPORTANCE: Findings from several high-profile meta-analyses have raised concerns about an ongoing global decline in sperm concentration and male fertility. However, these studies exhibit considerable heterogeneity in key variables including study population, methodology, fertility status, and geographic region.

OBJECTIVE: To perform a systematic review and meta-analysis exploring temporal trends in sperm concentration among fertile men and men unselected for fertility status in the United States.

DATA SOURCES: A literature search performed in Scopus and PubMed databases for studies published between 1970-2023. Additional studies were included from citations of prior global meta-analyses and reviews evaluating temporal trends in sperm count. Study selection and synthesis: Studies were included if they presented original data on sperm concentration in U.S. men without known infertility from 1970 to 2023. Aggregate data were assessed across all study populations, with additional subgroup analyses stratified by fertility status and U.S. region.

MAIN OUTCOMES: Weighted generalized linear models were generated to evaluate the association between mean sperm concentration and sample collection year.

RESULTS: A total of 874 articles were screened, with 58 meeting the inclusion criteria. These represented 75 unique study populations totaling 11,787 men in the U.S. Across all study populations, no change in sperm concentration was observed between 1970-2018 in unadjusted models (β=0.14million/mL/year, p=0.42). When adjusting for U.S. region, no statistically significant decline in sperm concentration was seen. When adjusting for both region and fertility status, a modest annual decline was observed to meet statistical significance (β=-0.35million/ml/year, p=0.04). Of the 49 study populations reporting adequate data to determine mean total sperm count, there was a significant increase in total sperm count of 2.9 million/year between 1970 and 2018 (p=0.03). Subgroup analysis found no statistically significant change in mean sperm concentration among any U.S. census region or fertility status cohort.

CONCLUSION AND RELEVANCE: In contrast to prior global studies, this analysis suggests no clinically significant decline in sperm concentration among confirmed fertile men and the general male U.S. population without known infertility. While these findings provide some reassurance against a widespread rapid decline, further studies are necessary to better understand this important topic.

PMID:39128669 | DOI:10.1016/j.fertnstert.2024.08.322

Environ Res. 2024 Aug 9:119747. doi: 10.1016/j.envres.2024.119747. Online ahead of print.

ABSTRACT

Policy synergies effectively contribute to the integrated management of air pollution and carbon emissions, which is crucial for safeguarding ecosystem stability and public health. This study uses the causal network model of Gaussian process regression to analyze the combined impacts of dynamic and static carbon emission reduction and air quality policies on carbon emissions and air quality. The causal effects of policy measures and their synergistic effects are also examined. The study results indicate: (1) There is significant geographical heterogeneity in the implementation of environmental policies and regional economic development, with the economically developed eastern coastal regions adopting more stringent carbon emission and air pollution control measures, while the western provinces adopt relatively lax environmental policies. (2) The synergistic effect of carbon emission reduction policies and air quality policies exists, and the two types of static policies are substitutable for managing carbon dioxide emissions and air pollution. (3) Policies’ forced effect exists, where the exacerbation of environmental problems leads to the formation and implementation of policies. (4) The value added by the secondary industry is a key motivation for forming carbon emission reduction policies and air quality control policies. Additionally, the value added by the secondary industry directly impacts the incidence of respiratory diseases (e.g., tuberculosis). Finally, dynamic and synergistic policy recommendations are proposed based on the study’s findings.

PMID:39128666 | DOI:10.1016/j.envres.2024.119747

Am Heart J. 2024 Aug 9:S0002-8703(24)00198-4. doi: 10.1016/j.ahj.2024.08.004. Online ahead of print.

ABSTRACT

BACKGROUND: Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that its accessibility in rural areas may be limited, leading to delayed management decisions and potential missed diagnoses. Artificial intelligence-guided (AI)-TTE offers a solution by permitting non-expert image acquisition. The impact of AI-TTE on the timing of diagnosis and early initiation of cardioprotection is undefined.

METHODS: AGILE-Echo (use of Artificial intelligence-Guided echocardiography to assIst cardiovascuLar patient managEment) is a randomized-controlled trial conducted in 5 rural and remote areas around Australia. Adults with CV risk factors and exercise intolerance, or concerns regarding HVD are randomized into AI-TTE or usual care (UC). AI-TTE participants may have a cardiovascular problem excluded, identified (leading to AI-guided interventions) or unresolved (leading to conventional TTE). UC participants undergo usual management, including referral for standard TTE. The primary endpoint is a composite of HVD or HF diagnosis at 12-months. Subgroup analysis, stratified based on age range and sex, will be conducted. All statistical analyses will be conducted using R.

RESULTS: Of the first 157 participants, 78 have been randomized into AI-TTE (median age 68 [IQR 17]) and 79 to UC (median age 65 [IQR 17], p=0.034). HVD was the primary concern in 37 participants (23.6%) while 84.7% (n=133) experienced exercise intolerance. The overall 10-year HF incidence risk was 13.4% and 20.0% (p=0.089) for UC and AI-TTE arm respectively. Atrial remodeling, left ventricular remodeling and valvular regurgitation were the most common findings. Thirty-three patients (42.3%) showed no abnormalities.

CONCLUSIONS: This randomized-controlled trial of AI-TTE will provide proof-of-concept for the role of AI-TTE in identifying pre-symptomatic HF or HVD when access to TTE is limited. Additionally, this could promote the usage of AI-TTE in rural or remote areas, ultimately improving health and quality of life of community dwelling adults with risks, signs or symptoms of cardiac dysfunction.

PMID:39128659 | DOI:10.1016/j.ahj.2024.08.004