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Influence of the COVID-19 pandemic on the prevalence of depression in U.S. adults: evidence from NHANES

Exploring real estate blockchain adoption: An empirical study based on an integrated task-technology fit and technology acceptance model

Although many organizations have adopted blockchain technology (BCT) for efficiency and automation and users’ adoption of BCT is becoming crucial for the companies, few studies have focused on the factors affecting the adoption of BCT in real estate sector. This study aims to assess the factors affecting the adoption of BCT in real estate by the lens of an extended Technology Acceptance Model (TAM) and Task-technology fit (TTF). This current study uses quantitative survey approach. Data were collected from 311 real sector buyers and sellers in China. Partial least square structural equation modeling (PLS-SEM) was used for data analysis. The study’s findings indicate that attitude, perceived usefulness (PU) and data privacy and security (DPS) exerts highest influence in the proposed theoretical model. In addition, the findings also confirmed the significant impact of perceived ease of use (PEOU) on attitude, and TTF impact on PU and PEOU in adoption of BCT. Furthermore, the moderating impact of perceived compatibility (PC) on the relationship between TTF and PEOU was also confirmed. The study has useful practical implications for the real estate buyers and sellers that adoption of BCT improves efficiency, reduce transaction cost incur due to intermediaries, and enhance security system. Furthermore, the study suggests that automation achieved through BCT will facilitate customized agreements and improve process of title transfer.

Decreased PD-L1 contributes to preeclampsia by suppressing GM-CSF via the JAK2/STAT5 signal pathway

AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study

To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings for rib fractures (RFs) detection on CT images. This study included 243 consecutive chest trauma patients (mean age, 58.1 years; female, 166) with rib CT scans. All CT scans were interpreted by two radiologists. The CT images were re-evaluated by primary readers with AI assistance in a blinded manner. Reference standards were established by two musculoskeletal radiologists. The re-evaluation results were then compared with those from the initial double-reading. The primary analysis focused on demonstrate superiority of AI-assisted sensitivity and the noninferiority of specificity at patient level, compared to standard double-reading. Secondary endpoints were at the rib and lesion levels. Stand-alone AI performance was also assessed. The influence of patient characteristics, report time, and RF features on the performance of AI and radiologists was investigated. At patient level, AI-assisted radiologists significantly improved sensitivity by 25.0% (95% CI: 10.5, 39.5; P < 0.001 for superiority), compared to double-reading, from 69.2% to 94.2%. And, the specificity of AI-assisted diagnosis (100%) was noninferior to double-reading (98.2%) with a difference of 1.8% (95% CI: -3.8, 7.4; P = 0.999 for noninferiority). The diagnostic accuracy of both radiologists and AI was influenced by patient gender, rib number, fracture location, and fracture type. Radiologist performance was affected by report time, whereas AI’s diagnostic accuracy was influenced by patient age and the side of the rib involved. AI-assisted additional-reader workflow might be a feasible strategy to instead of traditional double-reading, potentially offering higher sensitivity and specificity compared to standard double-reading in real-word clinical practice.

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma

Efficacy of different routes of triamcinolone acetonide administration on macular edema: A systematic review and network meta-analysis

There is different administration routes of triamcinolone acetonide (TA) administration for macular edema, but the efficacy ranking remains unclear. The purpose of this study is to assess the efficacy of different administration routes of TA employed in macular edema. PubMed, Medline, Embase, and Cochrane Central Register of Controlled Trials were systematically searched for published articles comparing macular edema in patients with triamcinolone acetonide in different administration. The sparse network was evaluated using a random-effects model and consistency model within the Bayesian framework, utilizing the multinma package in R. The evidence was assessed based on the Grading of Recommendations. Assessment, Development, and Evaluation (GRADE) criteria. A total of 1138 citations were identified by our search, of which 20 RCTs enrolled 892 eyes. The network showed that intravitreal triamcinolone acetonide (IVTA) was associated with a statistically significant better best corrected visual acuity (BCVA) at the 12th week compared to placebo (MD: − 0.15, 95% CI: − 0.30 to − 0.01, P < 0.05), which was moderate-quality evidence. IVTA and suprachoroidal triamcinolone acetonide (SCTA) were both associated with a statistically significant reduction in central macular thickness (CMT) at the 12th week, which was moderate evidence. The probabilities of rankings and SUCRA demonstrated that sub-Tenon’s infusion of triamcinolone acetonide (STiTA) might be the worst. SCTA and IVTA were proven to be the best administration routes for improving BCVA and reducing CMT. In addition, STiTA was less advisable than other administration routes of triamcinolone acetonide according to the rankings and SUCRA.

Primary tumor resection might improve outcomes in metastatic thoracic esophageal cancer

Examining hurricane–related social media topics longitudinally and at scale: A transformer-based approach

Instead of turning to emergency phone systems, social media platforms, such as Twitter, have emerged as alternative and sometimes preferred venues for members of the public in the US to communicate during hurricanes and other natural disasters. However, relevant posts are likely to be missed by responders given the volume of content on platforms. Previous work successfully identified relevant posts through machine-learned methods, but depended on human annotators. Our study indicates that a GPU-accelerated version of BERTopic, a transformer-based topic model, can be used without human training to successfully discern topics during multiple hurricanes. We use 1.7 million tweets from four US hurricanes over seven years and categorize identified topics as temporal constructs. Some of the more prominent topics related to disaster relief, user concerns, and weather conditions. Disaster managers can use our model, data, and constructs to be aware of the types of themes social media users are producing and consuming during hurricanes.

Connecting electronic health records to a biomedical knowledge graph to link clinical phenotypes and molecular endotypes in atopic dermatitis

A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution

Petroleum hydrocarbon pollution causes significant damage to soil, so accurate prediction and early intervention are crucial for sustainable soil management. However, traditional soil analysis methods often rely on statistical methods, which means they always rely on specific assumptions and are sensitive to outliers. Existing machine learning based methods convert features containing spatial information into one-dimensional vectors, resulting in the loss of some spatial features of the data. This study explores the application of Three-Dimensional Convolutional Neural Networks (3DCNN) in spatial interpolation to evaluate soil pollution. By introducing Channel Attention Mechanism (CAM), the model assigns different weights to auxiliary variables, improving the prediction accuracy of soil hydrocarbon content. We collected soil pollution data and validated the spatial distribution map generated using this method based on the drilling dataset. The results indicate that compared with traditional Kriging3D methods (R2 = 0.318) and other machine learning methods such as support vector regression (R2 = 0.582), the proposed 3DCNN based method can achieve better accuracy (R2 = 0.954). This approach provides a sustainable tool for soil pollution management, supports decision-makers in developing effective remediation strategies, and promotes the sustainable development of spatial interpolation techniques in environmental science.

Advancing neutron imaging techniques to highest resolution with fluorescent nuclear track detectors

Analysis of seroprevalence and risk factors for syphilis and HIV among female sex workers and transgender individuals in different cities of Sindh, Pakistan

Introduction Co-infections of syphilis and HIV have been found to exacerbate the impact on sexual and reproductive health, especially among key population groups such as Female Sex Workers (FSWs) and Transgender Individuals (TGs). The data on the prevalence and determinants of syphilis and HIV in Pakistan, particularly in Sindh province, is limited. This prospective cross-sectional study aimed to determine the seroprevalence and risk factors for HIV and syphilis infections among FSWs and TGs in different cities of Sindh, Pakistan. Methods A total of 1120 participants (531 FSWs and 589 TGs) were recruited from Karachi, Sukkur, Hyderabad, and Larkana. Community-based serological testing for HIV and syphilis was performed using Abbot Bioline HIV/syphilis Duo test kits, and sociodemographic and risk factor data were collected through questionnaires. Chi-square and logic regression were applied to determine variables associated significantly with syphilis in TGs and FSWs. Results TGs exhibited higher rates of syphilis (16.29%) and syphilis-HIV (6.79%) as compared to FSWs (syphilis: 15.63%; syphilis-HIV: 0.75%). Inconsistent condom use was more common among FSWs (75.32%), and over half reported STI symptoms. Regression analysis showed that for TGs, having five years (adjusted OR: 0.52, p = 0.04) and graduate-level education (adjusted OR: 0.40, p = 0.04) was associated with a lower risk of syphilis, while an income between 30,000 and 50,000 Pakistani rupees (OR: 1.93, p = 0.028) and more than three years in profession (adjusted OR: 2.20, p = 0.04) was associated with a higher risk. For FSWs, five (OR: 0.34, p = 0.03) and ten (OR: 0.02, p = 0.02) years of education were associated with a lower risk of syphilis, whereas an income between 30,000 and 50,000 PKR (OR: 3.05, p < 0.01) and self-reported HIV-negative status (OR: 3.08, p = 0.01) were associated with a higher risk of syphilis mono-infection. Conclusion In conclusion, the results of the study show higher rates of syphilis and HIV co-infection among TG compared to FSW from Sind. The study findings provide valuable insights for national health agencies and policymakers to devise data-driven strategies for preventing and controlling syphilis and HIV infections among FSW and TG populations in Sind.

In situ forming gels as subcutaneous delivery systems of curcumin and piperine

Environmental judicature and firm productivity: Evidence from a quasi-natural experiment

The impact of environmental governance on firm productivity has been widely discussed, but few studies have examined the function of environmental judicature. Using the establishment of environmental courts as a quasi-natural experiment, this paper examines the relationship between environmental judicature and firm productivity. Our findings show that environmental courts will reduce firm productivity in the short term, chiefly owing to the increased environmental violation costs, environmental reputation costs and environmental compliance costs. The conclusion remains robust after mitigation of heterogeneous treatment effects, PSM-DID estimation, placebo tests and IV estimation. This negative effect is more pronounced for firms located in regions with high legal scores and low government intervention, for firms located in the eastern region, for firms with weak market power, and for firms with high pollution intensity. In addition, our further analysis suggests that environmental courts would improve the long-term firm productivity and regional green productivity, indicating that strengthening environmental judicature are conducive to firms’ sustainable growth and regions’ green transformation in the long run.

Clinical evaluation of corneal ulcer with a portable and smartphone-attachable slit lamp device: Smart Eye Camera

Prediction of mortality and prioritisation to tertiary care using the ‘OUR-ARCad’ risk score gleaned from the second wave of COVID-19 pandemic—A retrospective cohort study from South India

Background Judicious utilisation of tertiary care facilities through appropriate risk stratification assumes priority, in a raging pandemic, of the nature of delta variant-predominated second wave of COVID-19 pandemic in India. Prioritisation of tertiary care, through a scientifically validated risk score, would maximise recovery without compromising individual safety, but importantly without straining the health system. Methods De-identified data of COVID-19 confirmed patients admitted to a tertiary care hospital in South India, between April 1, 2021 and July 31, 2021, corresponding to the peak of COVID-19 second wave, were analysed after segregating into ‘survivors’ or ‘non-survivors’ to evaluate the risk factors for COVID-19 mortality at admission and formulate a risk score with easily obtainable but clinically relevant parameters for accurate patient triaging. The predictive ability was ascertained by the area under the receiver operator characteristics (AUROC) and the goodness of fit by the Hosmer-Lemeshow test and validated using the bootstrap method. Results Of 617 COVID-19 patients (325 survivors, 292 non-survivors), treated as per prevailing national guidelines, with a slight male predilection (358/617 [58.0%]), fatalities in the age group above and below 50 years were (217/380 [57.1%]) and (75/237 [31.6%]), p<0.001. The relative distribution of the various parameters among survivors and non-survivors including self-reported comorbidities helped to derive the individual risk scores from parameters significant in the multivariable logistic regression. The ‘OUR-ARCad’ risk score components were—Oxygen saturation SaO2<94%-23, Urea > 40mg/dL-15, Neutrophil/Lymphocytic ratio >3–23, Age > 50 years-8, Pulse Rate >100–8 and Coronary Artery disease-15. A summated score above 50, mandated tertiary care management (sensitivity-90%, specificity-75%; AUC-0.89), validated in 2000 bootstrap dataset. Conclusions The OUR-ARCad risk score, could potentially maximize recovery in a raging COVID-19 pandemic, through prioritisation of tertiary care services, neither straining the health system nor compromising patient’s safety, delivering and diverting care to those who needed the most.

Subsistence hunting impacts wildlife assemblages and functional ecology in tropical forests

Abstract Unsustainable wild meat hunting poses a significant threat to wildlife and tropical forest ecosystems. While high levels of extraction linked to commercial trade have received significant attention, the sustainability of subsistence hunting by Indigenous Peoples in Africa has been less studied. Understanding how changing lifestyles, particularly the sedentarisation of former hunter-gatherers, have affected the use of forest resources is crucial for wildlife conservation and livelihoods. The spatial management of hunting through the establishment of no-take zones, which act as sources for adjacent hunting areas, offers promise for the sustainability of Indigenous livelihoods. We conducted an extensive camera trap study in hunting areas subject to source-sink dynamics used by 10 sedentarised Baka communities. We compared species richness, occupancy, abundance, and community composition to a relatively non-hunted reference area in the adjacent Dja Faunal Reserve. Subsistence hunting by the Baka had a limited impact on species richness but significantly altered community composition and the abundance of carnivores, seed dispersers and granivores. These changes highlight that even the spatial management of hunting may have consequences for the sustainability of hunting systems and the functional ecology of tropical forests.

Asymptotic BLSCP models in uncertain and asymmetric environments—Take the charging station location problem

The rapid development of the field of vehicles exposes many problems of charging station, the most common is the uncertainty and asymmetry of its task volume, so the flexibility of location and scale design is crucial. This paper proposes the asymptotic BLSCP model, suitable for uncertain and asymmetric environments, which balances facility workload and minimizes cost through the forward or backward asymptotic methods of candidate center locations and flexible allocation of jurisdictions. Additionally, the findings suggest these methods possess considerable potential for application and generalization.

Companion dogs show signs of jealous behaviour toward non-living agents

Abstract Dogs engage in social interactions with robots, yet whether they perceive them as social agents remains uncertain. In jealousy-evoking contexts, specific behaviours were observed exclusively when dogs’ owners interacted with social, rather than non-social rivals. Here, we investigated whether a robot elicits jealous behaviour in dogs based on its level of animateness. First, dogs observed a robot either moving mechanistically, or showing animate motions in a non-interactive, or interactive manner towards a human. Then, in consecutive trials the owner interacted with a rival dog, the robot, and read a magazine, while ignoring the subject. Dogs displayed more owner-oriented behaviours, interaction interruption, vocalization and snapping when the owner attended the rival dog compared to reading. Dogs showed intermediate interest toward the robot but snapped more toward the robot than the magazine. Thus, dogs adjust their jealous behaviour to the actual rival, and indirect, brief experience is sufficient to consider the robot as distinct from typical inanimate objects.

Decoding the aroma of Rosa canina L.: Chemical composition and gene expression

Objective The aromatic profile of Rosa canina L. petals hold immense potential for the fragrance and pharmaceutical industries. This study aims to investigate the chemical composition and gene expression patterns across different floral development stages to uncover the biosynthetic pathways of floral scent. Methods Essential oils (EOs) were extracted from petals at five developmental stages (S1-S5) and analyzed using Gas Chromatography-Mass Spectrometry (GC-MS), identifying 20 distinct compounds. RNA isolation and quantitative real-time PCR (qRT-PCR) analysis were performed to assess gene expression. Results Stage S3, notable for its enhanced aromatic profile, was dominated by terpenoid compounds such as β-Citronellol (1.18%), Caryophyllene (8.59%), β-Selinene (1.50%), and Caryophyllene oxide (0.50%), indicating significant upregulation of terpenoid biosynthesis genes. qRT-PCR analysis revealed that CCD1 had the highest expression in S4 (9.51-fold), while DXR and DXS peaked at S3 with fold changes of 29058.38 and 73.35, respectively. Other genes like AAT1, LIS, and GPS also showed peak expressions at S3 with fold changes of 1.33, 10.70, and 1.18, respectively. PAR exhibited the highest expression in S1, while GGPPS peaked in S4 (2.01-fold). Clustering analysis indicated distinct groupings of developmental stages and gene expression patterns, with strong correlations between specific genes and compounds, such as CCD1 with GGPPS (0.78) and β-Citronellol with Caryophyllene (0.92). Principal Component Analysis (PCA) highlighted significant contributions of AAT1, GPS, and nonadecane compounds to the overall variance. Conclusion These findings provide a comprehensive understanding of the chemical and genetic factors shaping the aromatic profile of R. canina, with promising applications for both the fragrance and pharmaceutical sectors. The study’s innovation lies in the detailed correlation between EO composition and gene expression, presenting new insights into the biosynthetic pathways of floral scent.