Arsenic (As) accumulation in different genotypes of indica rice (Oryza sativa L.) and health risk assessment based on inorganic As.

To reveal differences in arsenic (As) accumulation among indica rice cultivars and assess the human health risks arising from inorganic arsenic (iAs) intake via rice consumption, a total of 320 field indica rice samples and corresponding soil samples were collected from Fujian Province in China. The results showed that available soil As (0.03 to 3.83 mg/kg) showed a statistically significant positive correlation with total soil As (0.10 to 19.45 mg/kg). The inorganic As content in brown rice was between 0.001 and 0.316 mg/kg. Among the cultivars, ten brown rice samples (3.13%) exceeded the maximum contaminant level (MCL) of iAs in food of 0.2 mg/kg in China. The estimated daily intake (EDI) and calculated individual incremental lifetime cancer risk (ILCR) ranged from 0.337 µg/day to 106.60 µg/day and from 8.18 × 10-6 to 2.59 × 10-3, respectively. Surprisingly, the average EDI and the EDIs of 258 (80.63%) brown rice samples were higher than the maximum daily intake (MDI) of 10 µg/day in drinking water as set by the National Research Council. The mean ILCR associated with iAs was 54.3 per 100,000, which exceeds the acceptable upper limit (AUL) of 10 per 100,000 set by the USEPA. Notably, the cultivars Y-Liang-You 1 and Shi-Ji 137 exhibited significantly higher mean ILCRs compared to the AUL and other cultivars, indicating that they pose more serious cancer risks to the local population. Finally, this study demonstrated that the cultivars Yi-Xiang 2292 and Quan-Zhen 10 were the optimal cultivars to mitigate risks associated with iAs to human health from rice consumption.

Assessment of Effective Antimicrobial Regimens and Mortality-Related Risk Factors for Bloodstream Infections Caused by Carbapenem-Resistant Acinetobacter baumannii.

Objective: This study aimed to determine the clinical features, risk factors, and effective antimicrobial therapy for Carbapenem-resistant Acinetobacter baumannii (CRAB) bloodstream infection (BSI). Methods: This was a retrospective analysis of data from patients with CRAB bacteremia in a Chinese tertiary hospital between January 2012 and October 2021. Risk factors, predictors of 30-day mortality, and effective antimicrobial therapy for CRAB BSI were identified using logistic and cox regression analyses. Results: Data from 276 patients with Acinetobacter baumannii (AB) BSI were included, of whom 157 (56.9%) had CRAB BSI. The risk factors that were significantly associated with CRAB BSI included previous intensive care unit (ICU) stay (P < 0.001), immunocompromised status (P < 0.001), cephalosporin use (P = 0.014), and fluoroquinolone use (P = 0.007). The 30-day mortality of the CRAB BSI group was 49.7% (78/157). ICU stay after BSI (P = 0.047), sequential organ failure assessment (SOFA) score ≥10 (P < 0.001), and multiple organ failure (MOF) (P = 0.037) were independent predictors of 30-day mortality. Among antibiotic strategies for the treatment of patients with CRAB BSI, we found that definitive regimens containing cefoperazone/sulbactam were superior to those without cefoperazone/sulbactam in reducing the 30-day mortality rate (25.4% vs 53.4%, P = 0.005). After propensity score matching, we observed a significant increase in the 30-day mortality (77.8%vs 33.3%, P = 0.036) in patients receiving tigecycline monotherapy compared to those receiving cefoperazone/sulbactam monotherapy. The mortality rate of patients receiving tigecycline with cefoperazone/sulbactam was also higher than that of patients receiving cefoperazone-sulbactam monotherapy; however, the difference was not significant (28.6%vs 19.0%, P = 0.375). Conclusion: The severity of patient conditions was significantly associated with mortality in patients with CRAB BSI. Those Patients treated with cefoperazone/sulbactam had better clinical prognoses, and tigecycline should be used with caution.

Assessment of macular structures and vascular characteristics in highly myopic anisometropia using swept-source optical coherence tomography angiography.

Purpose: This study aimed to explore the macular structures and vascular characteristics of more myopic (MM) and contralateral eyes with highly myopic anisometropia. Methods: Comprehensive ophthalmic examinations were performed for 33 patients with highly myopic anisometropia. Macular structures (total retinal layer [TRL], ganglion cell and inner plexiform layer [GCIPL], inner nuclear layer [INL], outer retinal layer [ORL], nerve fiber layer [NFL], choroidal layer [CHL]) and vascular characteristics (superficial vascular complex density [SVD], deep vascular complex density [DVD], choriocapillaris perfusion area [CCPA]) were assessed using swept-source optical coherence tomography (SS-OCT) and OCT angiography (OCTA). Macular structures and vascular characteristics of each subregion were compared to those of the Early Treatment of Diabetic Retinopathy Study (ETDRS). Results: With highly myopic anisometropia, the thicknesses of the TRL, GCIPL, INL, and ORL in MM eyes were smaller than those in contralateral eyes in at least one quadrant of the perifoveal and parafoveal circles (all p < 0.05), with no changes in the foveal and temporal quadrants of perifoveal regions (all p > 0.05). A thicker NFL (p = 0.018) was found in MM eyes than in contralateral eyes in the superior perifoveal quadrant. The CHL (all p < 0.05) in MM eyes was thinner in all regions than in the contralateral eyes according to the ETDRS. There were no statistical differences in the SVD, DVD, and CCPA of MM and contralateral eyes (all p > 0.05). Conclusion: All retinal layers, except the NFL, tended to be thinner in all subregions, except the temporal perifoveal and foveal quadrants in MM eyes, and choroidal thickness was thinned in all areas.

Systematic review and cost-effectiveness of bosentan and sildenafil as therapeutic drugs for pediatric pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a rare disease in children, with significant mortality. Because of the limited research on pediatric PAH, first, systematic review of related drugs is conducted, and then economic evaluation of PAH drug treatment programs is conducted, which to provide a reference for the choice of more cost-effective treatment options. METHODS: The search includes electronic databases such as Pubmed, ScienceDirect, and Embase. Through inclusion and exclusion criteria, screen high-quality randomized controlled trials. We used TreeAge Pro 2011 software to construct the markov model, that to simulate the total medical cost and quality-adjusted life years (QALYs), and to calculate the incremental cost-effectiveness ratio. Sensitivity analysis of transfer probability, utility, and cost was carried out. RESULTS: Incorporate two studies that meet the criteria, one compared the therapeutic effects of bosentan and placebo on pediatric PAH, the other compared therapeutic effects of sildenafil and placebo on pediatric PAH, both articles were of good quality. Compared with the sildenafil group (3.38QALYs and $161,120.14), the QALY of the bosentan treatment group (3.33QALYs and $257,411.29) was reduced by 0.05, and the cost increased by $96,291.15. The estimated improvement to quality of life and reduced costs result in an estimate of economic dominance for sildenafil over bosentan. This dominant result persisted probabilistic analyses. CONCLUSIONS: Based on this model, a more cost-effective treatment drug for PAH in children is sildenafil.

Patients' Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment.

BACKGROUND: Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19. OBJECTIVE: This study aims to visualize and measure patients' heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future. METHODS: A DCE approach was the main analysis method applied in this paper. Attributes from different dimensions were hypothesized: diagnostic method, outpatient waiting time, diagnosis time, accuracy, follow-up after diagnosis, and diagnostic expense. After that, a questionnaire is formed. With collected data from the DCE questionnaire, we apply Sawtooth software to construct a generalized multinomial logit (GMNL) model, mixed logit model, and latent class model with the data sets. Moreover, we calculate the variables' coefficients, standard error, P value, and odds ratio (OR) and form a utility report to present the importance and weighted percentage of attributes. RESULTS: A total of 55.8% of the respondents (428 out of 767) opted for AI diagnosis regardless of the description of the clinicians. In the GMNL model, we found that people prefer the 100% accuracy level the most (OR 4.548, 95% CI 4.048-5.110, P<.001). For the latent class model, the most acceptable model consists of 3 latent classes of respondents. The attributes with the most substantial effects and highest percentage weights are the accuracy (39.29% in general) and expense of diagnosis (21.69% in general), especially the preferences for the diagnosis "accuracy" attribute, which is constant across classes. For class 1 and class 3, people prefer the AI + clinicians method (class 1: OR 1.247, 95% CI 1.036-1.463, P<.001; class 3: OR 1.958, 95% CI 1.769-2.167, P<.001). For class 2, people prefer the AI method (OR 1.546, 95% CI 0.883-2.707, P=.37). The OR of levels of attributes increases with the increase of accuracy across all classes. CONCLUSIONS: Latent class analysis was prominent and useful in quantifying preferences for attributes of diagnosis choice. People's preferences for the "accuracy" and "diagnostic expenses" attributes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.

A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China.

Investor sentiment is a research focus in behavior finance. This paper chooses five proxy variables according to China's reality and uses a two-step principal component analysis to construct an investor sentiment index. The five proxy variables are the number of new stock accounts, turnover ratio, margin balance, net active purchasing amount, and investor attention. In the final part of this study, using the price data from the Shanghai and Shenzhen Security Exchange, this paper investigates the dynamic relationship between investor sentiment and stock market realized volatility based on the thermal optimal path. The empirical results show that when the market fluctuates severely, investor sentiment leads stock market realized volatility over one or two steps. The prediction power is also checked. The results indicate that investor sentiment indeed forecasts the realized volatility. This research supports regulators and financial institutions in taking advanced measures.

A Facile, Low-Cost Plasma Etching Method for Achieving Size Controlled Non-Close-Packed Monolayer Arrays of Polystyrene Nano-Spheres.

Monolayer nano-sphere arrays attract great research interest as they can be used as templates to fabricate various nano-structures. Plasma etching, and in particular high-frequency plasma etching, is the most commonly used method to obtain non-close-packed monolayer arrays. However, the method is still limited in terms of cost and efficiency. In this study, we demonstrate that a low frequency (40 kHz) plasma etching system can be used to fabricate non-close-packed monolayer arrays of polystyrene (PS) nano-spheres with smooth surfaces and that the etching rate is nearly doubled compared to that of the high-frequency systems. The study reveals that the low-frequency plasma etching process is dominated by a thermal evaporation etching mechanism, which is different from the atom-scale dissociation mechanism that underlines the high-frequency plasma etching. It is found that the polystyrene nano-sphere size can be precisely controlled by either adjusting the etching time or power. Through introducing oxygen as the assisting gas in the low frequency plasma etching system, we achieved a coalesced polystyrene nano-sphere array and used it as a template for metal-assisted chemical etching. We demonstrate that the method can significantly improve the aspect ratio of the silicon nanowires to over 200 due to the improved flexure rigidity.