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FOXO1-mediated argininosuccinate lyase transcription inhibits ammonia metabolism and breast cancer cell metastasis
Cultural differences in self-reported empathy in Indonesia
Abstract Empathy, comprising cognitive and affective components, is linked to numerous individual and societal benefits, including enhanced well-being and prosocial behaviours. However, empathy might also hinder societal flourishing due to biases resulting from factors like social closeness. This study explored cultural variation in empathy within Indonesia, a non-WEIRD context with diverse ethnicities, religions, and social structures. We hypothesized that cultural factors such as ethnicity, primary residence, religious beliefs, and social class would predict empathy differences. Using standardised questionnaires, we assessed helping behaviour, situational empathic concern, directed empathic concern, and personal distress in 2869 Indonesian adults. Regression analyses revealed that gender, age, ethnicity, residence, religion, and perceived social class significantly predicted empathy components. Notably, Javanese and Sundanese participants reported higher empathy levels than Minangkabau, and Muslims showed more empathy than other religious groups. Additionally, higher perceived social status correlated with increased helping behaviour and emotional empathy, but it also correlated with lower personal distress. These findings highlight the complex interplay of cultural factors in shaping empathy, with implications for understanding socioemotional dynamics across diverse societies.
Structure and loop dynamics of a chitooligosaccharide deacetylase from the marine bacterium Vibrio campbellii (harveyi)
Health risk assessment and trace element analysis in tobacco products and user blood samples from urban and rural Karachi
Abstract Cigarette smoking and use of smokeless tobacco products (STPs) such as gutka, mainpuri, and naswar are major public health concerns in Pakistan. This study assessed toxic trace elements (TTEs) Cadmium (Cd), Manganese (Mn), Lead (Pb), and Zinc (Zn) in the blood of male and female tobacco users and non-users from urban and rural Karachi, along with associated health risks. A total of 190 blood and 120 tobacco samples (30 cigarettes, 90 STPs) were analyzed. Cd, Mn, and Pb were measured using electrothermal atomic absorption spectrometry (ETAAS), and Zn by flame atomic absorption spectrometry (FAAS) after acid digestion. The study revealed significantly higher metal concentrations in urban users due to combined exposure from tobacco and environmental pollution. Cd levels in gutka (1.11 mg/kg) and cigarettes (1.035 mg/kg) exceeded WHO’s limit (0.5 mg/kg). Urban male smokers had the highest blood Pb (0.108 ± 0.01 mg/L), over tenfold above the WHO limit, while urban females showed the highest Mn (0.031 mg/L). Rural male mainpuri users had the highest Zn level (2.76 ± 0.16 mg/L). Cd in cigarette posed the highest cancer risk (CR: 9.14 × 10⁻⁴); gutka users had a CR of 6.74 × 10⁻⁴. Female gutka users had the highest Pb intake (0.513 mg/kg/day). The findings call for urgent biomonitoring, regulation, and public health interventions.
Withdrawal: p38δ regulates p53 to control p21Cip1 expression in human epidermal keratinocytes
Prenatal and maternal study of halloysite toxicity in pregnant rats
Abstract Halloysite nanoclay (HNC) is a naturally occurring tubular aluminosilicate that has various applications in nanotechnology and drug delivery. However, its toxic effects during gestation are inadequately reported. This study assessed the maternal and fetal toxic effects of intranasally and orally administered HNC. Pregnant rats were divided into three groups: vehicle control, oral HNC (75 mg/kg), and intranasal HNC at the same dose from day 0 to day 19 of gestation (day after day). Dams showed weight loss, but HNC did not cause lethality in both groups. HNC reported route-dependent tissue toxicity. Orally administered HNC leads to more pronounced oxidative intestinal damage than intranasal treatment. Intranasal administration has a much greater impact on reducing thiol content in the lungs compared to oral administration. Histopathological analysis revealed that the fetal pancreas of dams treated with HNC intranasally showed marked necrotic acini and congested blood vessels, whereas the dams treated orally exhibited foamy macrophages and lung angiopathy more frequently than the intranasally treated ones. These results highlighted that HNC, at the tested dose, caused significant pathological and oxidative damage to maternal and fetal tissues.
Structural basis of heme scavenging by the ChtA and HtaA hemophores in Corynebacterium diphtheriae
Soil moisture gradients shape microbial communities and influence cranberry yield: a case study on subirrigation
Effect of music intervention on preoperative anxiety, a randomised clinical study
Unhealthy dietary habits and sedentary behavior drive untreated dental caries among adolescents: A population-based study
Insights into Reactive Carbon Capture through Heterogeneously Catalyzed Electrochemical Reduction of an Imidazolium Carboxylate
Skin microbiome friendly topical formulations containing probiotic – loaded alginate microspheres: in vitro studies
Structural and molecular differentiation of cultured human neurons is accompanied by alterations of spontaneous and evoked calcium dynamics
Design of AI-driven microwave imaging for lung tumor monitoring
Abstract The global incidence of lung diseases, particularly lung cancer, is increasing at an alarming rate, underscoring the urgent need for early detection, robust monitoring, and timely intervention. This study presents design aspects of an artificial intelligence (AI)-integrated microwave-based diagnostic tool for the early detection of lung tumors. The proposed method assimilates the prowess of machine learning (ML) tools with microwave imaging (MWI). A microwave unit containing eight antennas in the form of a wearable belt is employed for data collection from the CST body models. The data, collected in the form of scattering parameters, are reconstructed as 2D images. Two different ML approaches have been investigated for tumor detection and prediction of the size of the detected tumor. The first approach employs XGBoost models on raw S-parameters and the second approach uses convolutional neural networks (CNN) on the reconstructed 2-D microwave images. It is found that the XGBoost-based classifier with S-parameters outperforms the CNN-based classifier on reconstructed microwave images for tumor detection. Whereas a CNN-based model on reconstructed microwave images performs much better than an XGBoost-based regression model designed on the raw S-parameters for tumor size prediction. The performances of both of these models are evaluated on other body models to examine their generalization capacity over unknown data. This work explores the feasibility of a low-cost portable AI-integrated microwave diagnostic device for lung tumor detection, which eliminates the risk of exposure to harmful ionizing radiations of X-ray and CT scans.