Application of Urethral Contrast Computed Tomography Three-Dimensional Imaging in the Postoperative Assessment of Prostate Hyperplasia.

This study assesses the morphological effectiveness of benign prostatic hyperplasia (BPH) surgery using multislice spiral computed tomography three-dimensional imaging (CT3D) with urethral contrast. Twenty-five male patients with BPH and bladder outlet obstruction (BOO) who underwent bipolar transurethral resection of the prostate were selected. Preoperative and postoperative CT3D indicators of retrograde and voiding cystourethrography, including bladder neck diameter, length of the posterior urethra, and degree of prostate protrusion into the bladder and upper and lower diameter of the prostate were used to assess bladder neck and posterior urethra morphology and BOO severity. In addition, preoperative and postoperative International Prostate Symptom Scores and maximum urine flow rates were compared. Postoperative CT3D was used to evaluate changes following obstruction relief postsurgery. Preoperative CT3D indicated significant BOO, whereas postoperative imaging showed improved patency but with irregular posterior urethral lumens and varying degrees of residual glandular tissue. Comparative analysis of preoperative and postoperative bladder outlet metrics revealed significant changes (p < .05). Urethral contrast CT3D effectively visualizes the prostate, bladder neck, and prostatic urethra. It quantifies changes in the urethral lumen postsurgery, correlating the extent of posterior urethral lumen spaciousness with urinary flow rates.

Prognostic Assessment of Histopathologic Lesions in Patients with Community-Acquired Acute Kidney Injury with Biopsy-Proven Acute Tubular Necrosis.

BACKGROUND: Community-acquired acute kidney injury (CA-AKI) was more likely to be comorbid with underlying kidney histopathological lesions in addition to acute tubular necrosis (ATN). Thus, we tried to clarify the histological determinants that could influence the prognosis and recovery of CA-AKI patients with biopsy-proven ATN. METHODS: Adult patients with CA-AKI with biopsy-proven ATN who underwent renal biopsy at Shanghai Changzheng Hospital from January 1, 2010, to December 31, 2018, were included and followed up for 5 years. The impacts of histopathological lesions on short-term and long-term renal dysfunction were also analysed. RESULTS: Multivariate analysis revealed that ATNs, crescents, and decrease of arteriole lumens increased short-term dialysis requirements. The severity of ATN was closely associated with renal survival. According to the Kaplan-Meier analysis, the severity of ATN was significantly associated with short-term dialysis needs and long-term development of end-stage kidney disease (ESKD) during follow-up. Crescent and decrease of arteriole lumens are significantly associated with progression to ESKD and exert synergistic effects with ATN. For patients who did not progress to dialysis, tubular atrophic/interstitial fibrosis and endocapillary lesions were more relevant to partial recovery of renal function after CA-AKI at the three-month follow-up and increased the risk of chronic kidney disease (CKD) stage 3-5 at the five-year follow-up. According to our correlation analysis, endocapillary lesions and crescents were positively correlated with ATN. CONCLUSIONS: Histopathologic lesions, apart from tubular necrosis, contributed to the detrimental short-term and long-term renal prognosis of CA-AKI patients with ATN; concomitant histopathologic lesions exerted a combined impact on renal survival together with ATN in CA-AKI patients.

PresRecST: a novel herbal prescription recommendation algorithm for real-world patients with integration of syndrome differentiation and treatment planning.

OBJECTIVES: Herbal prescription recommendation (HPR) is a hot topic and challenging issue in field of clinical decision support of traditional Chinese medicine (TCM). However, almost all previous HPR methods have not adhered to the clinical principles of syndrome differentiation and treatment planning of TCM, which has resulted in suboptimal performance and difficulties in application to real-world clinical scenarios. MATERIALS AND METHODS: We emphasize the synergy among diagnosis and treatment procedure in real-world TCM clinical settings to propose the PresRecST model, which effectively combines the key components of symptom collection, syndrome differentiation, treatment method determination, and herb recommendation. This model integrates a self-curated TCM knowledge graph to learn the high-quality representations of TCM biomedical entities and performs 3 stages of clinical predictions to meet the principle of systematic sequential procedure of TCM decision making. RESULTS: To address the limitations of previous datasets, we constructed the TCM-Lung dataset, which is suitable for the simultaneous training of the syndrome differentiation, treatment method determination, and herb recommendation. Overall experimental results on 2 datasets demonstrate that the proposed PresRecST outperforms the state-of-the-art algorithm by significant improvements (eg, improvements of P@5 by 4.70%, P@10 by 5.37%, P@20 by 3.08% compared with the best baseline). DISCUSSION: The workflow of PresRecST effectively integrates the embedding vectors of the knowledge graph for progressive recommendation tasks, and it closely aligns with the actual diagnostic and treatment procedures followed by TCM doctors. A series of ablation experiments and case study show the availability and interpretability of PresRecST, indicating the proposed PresRecST can be beneficial for assisting the diagnosis and treatment in real-world TCM clinical settings. CONCLUSION: Our technology can be applied in a progressive recommendation scenario, providing recommendations for related items in a progressive manner, which can assist in providing more reliable diagnoses and herbal therapies for TCM clinical task.

Prevalence, characteristics, evaluation, and management of carotid body tumors: Systematic analysis based on available evidence.

OBJECTIVE: Although carotid body tumors (CBTs) are rare, they attract particular attention because of their propensity for malignant transformation and the high surgical risk. Because data are scarce and as it is difficult to achieve a large sample size, no study has yet comprehensively analyzed the characteristics, management, or operative complications of CBTs. Therefore, we collected and analyzed all currently available information on CBTs and used the pooled data to derive quantitative information on disease characteristics and management. METHODS: We systematically searched PubMed, Embase, the Cochrane Library, and the Web of Science up to December 1, 2022, for studies that investigated the characteristics and management of CBTs. The primary objective was to identify the prevalence of the various characteristics and the incidence of complications. The secondary objective was to compare patients who underwent preoperative embolization (PE) and those who did not (non-PE), as well as to compare patients with different Shamblin grades and those with and without succinate dehydrogenase (SDH) mutations in terms of CBT characteristics and complications. Two reviewers selected studies for inclusion and independently extracted data. All statistical analyses were performed using the standard statistical procedures of Review Manager 5.2 and Stata 12.0. RESULTS: A total of 155 studies with 9291 patients and 9862 tumors were identified. The pooled results indicated that the median age of patients with CBT was 45.72 years, and 65% were female. The proportion of patients with bilateral lesions was 13%. In addition, 16% of patients had relevant family histories, and the proportion of those with SDH gene mutations was 36%. Sixteen percent of patients experienced multiple paragangliomas, and 12% of CBTs had catecholamine function. The incidence of cranial nerve injury (CNI) was 27%, and 14% of patients suffered from permanent CNI. The incidence rates of operative mortality and stroke were both 1%, and 4% of patients developed transient ischemic attacks. Of all CBTs, 6% were malignant or associated with metastases or recurrences. The most common metastatic locations were the lymph nodes (3%) and bone (3%), followed by the lungs (2%). Compared with non-PE, PE reduced the estimated blood loss (standardized mean difference, -0.95; 95% confidence interval [CI], -1.70 to -0.20) and the operation time (standardized mean difference, -0.56; 95% CI, -1.03 to -0.09), but it increased the incidence of stroke (odds ratio, 2.44; 95% CI, 1.04-5.73). Higher Shamblin grade tumors were associated with more operative complications. Patients who were SDH gene mutation-positive were more likely to have a relevant family history and had more symptoms. CONCLUSIONS: CBT was most common in middle-aged females, and early surgical resection was feasible; there was a low incidence of serious operative complications. Routine PE is not recommended because this may increase the incidence of stroke, although PE somewhat reduced the estimated blood loss and operation time. Higher Shamblin grade tumors increased the incidence of operative complications. Patients who were SDH gene mutation-positive had the most relevant family histories and symptoms.

Ultrasound-Based Deep Learning Radiomics Nomogram for the Assessment of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: The aim of this study was to develop a deep learning radiomics nomogram (DLRN) based on B-mode ultrasound (BMUS) and color doppler flow imaging (CDFI) images for preoperative assessment of lymphovascular invasion (LVI) status in invasive breast cancer (IBC). MATERIALS AND METHODS: In this multicenter, retrospective study, 832 pathologically confirmed IBC patients were recruited from eight hospitals. The samples were divided into training, internal test, and external test sets. Deep learning and handcrafted radiomics features reflecting tumor phenotypes on BMUS and CDFI images were extracted. The BMUS score and CDFI score were calculated after radiomics feature selection. Subsequently, a DLRN was developed based on the scores and independent clinic-ultrasonic risk variables. The performance of the DLRN was evaluated for calibration, discrimination, and clinical usefulness. RESULTS: The DLRN predicted the LVI with accuracy, achieving an area under the receiver operating characteristic curve of 0.93 (95% CI 0.90-0.95), 0.91 (95% CI 0.87-0.95), and 0.91 (95% CI 0.86-0.94) in the training, internal test, and external test sets, respectively, with good calibration. The DLRN demonstrated superior performance compared to the clinical model and single scores across all three sets (p < 0.05). Decision curve analysis and clinical impact curve confirmed the clinical utility of the model. Furthermore, significant enhancements in net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indicated that the two scores could serve as highly valuable biomarkers for assessing LVI. CONCLUSION: The DLRN exhibited strong predictive value for LVI in IBC, providing valuable information for individualized treatment decisions.

Mechanism and ecological environmental risk assessment of peroxymonosulfate for the treatment of heavy metals in soil.

Oxidation technologies based on peroxymonosulfate (PMS) have been effectively used for the remediation of soil organic pollutants due to their high efficiency. However, the effects of advanced PMS-based oxidation technologies on other soil pollutants, such as heavy metals, remain unknown. In this study, changes in the form of heavy metals in soil after using PMS and the risk of pollution to the ecological environment were investigated. Furthermore, two risk assessment methods, the mung bean germination toxicity test and groundwater leaching soil column test, were employed to evaluate the soil before and after PMS treatment. The results showed that PMS has a strong ability to degrade complex compounds, enabling the transformation of heavy metals, such as Cd, Pb, and Zn, from stable to active states in the soil. The risk assessments showed that PMS treatment activated heavy metals in the soil, which delayed the growth of plants, increased heavy metal content in plant tissues and the risk of groundwater pollution. These findings provide a new perspective for understanding the effects of PMS on soil, thus facilitating the sustained and reliable development of future research in the field of advanced oxidation applied to soil treatment.

A decision tree model to help treatment decision-making for severe spontaneous intracerebral hemorrhage.

BACKGROUND: Surgical treatment demonstrated a reduction in mortality among patients suffering from severe spontaneous intracerebral hemorrhage (SSICH). However, which SSICH patients could benefit from surgical treatment was unclear. This study aimed to establish and validate a decision tree (DT) model to help determine which SSICH patients could benefit from surgical treatment. MATERIALS AND METHODS: SSICH patients from a prospective, multicenter cohort study were analyzed retrospectively. The primary outcome was the incidence of neurological poor outcome (modified Rankin scale as 4-6) on the 180th day posthemorrhage. Then, surgically-treated SSICH patients were set as the derivation cohort (from a referring hospital) and validation cohort (from multiple hospitals). A DT model to evaluate the risk of 180-day poor outcome was developed within the derivation cohort and validated within the validation cohort. The performance of clinicians in identifying patients with poor outcome before and after the help of the DT model was compared using the area under curve (AUC). RESULTS: One thousand two hundred sixty SSICH patients were included in this study (middle age as 56, and 984 male patients). Surgically-treated patients had a lower incidence of 180-day poor outcome compared to conservatively-treated patients (147/794 vs. 128/466, P <0.001). Based on 794 surgically-treated patients, multivariate logistic analysis revealed the ischemic cerebro-cardiovascular disease history, renal dysfunction, dual antiplatelet therapy, hematoma volume, and Glasgow coma score at admission as poor outcome factors. The DT model, incorporating these above factors, was highly predictive of 180-day poor outcome within the derivation cohort (AUC, 0.94) and validation cohort (AUC, 0.92). Within 794 surgically-treated patients, the DT improved junior clinicians' performance to identify patients at risk for poor outcomes (AUC from 0.81 to 0.89, P <0.001). CONCLUSIONS: This study provided a DT model for predicting the poor outcome of SSICH patients postsurgically, which may serve as a useful tool assisting clinicians in treatment decision-making for SSICH.

Mapping wild vascular plant species diversity in urban areas in California using crowdsourcing data by regression kriging: Examining socioeconomic disparities.

Biodiversity is crucial for human health, but previous methods of measuring biodiversity require intensive resources and have other limitations. Crowdsourced datasets from citizen scientists offer a cost-effective solution for characterizing biodiversity on a large spatial scale. This study has two aims: 1) to generate fine-resolution plant species diversity maps in California urban areas using crowdsourced data and extrapolation methods; and 2) to examine their associations with sociodemographic factors and identify subpopulations with low biodiversity exposure. We used iNaturalist observations from 2019 to 2022 to calculate species diversity metrics by exploring the sampling completeness in a 5 × 5-km2 grid and then computing species diversity metrics for grid cells with at least 80 % sample completeness (841 out of 4755 grid cells). A generalized additive model with ordinary kriging (GAM OK) provided moderately reliable estimates, with correlations of 0.64-0.66 between observed and extrapolated metrics, relative mean absolute errors of 21 %-23 %, and relative root mean squared errors of 27 %-30 % for grid cells with ≥80 % sample completeness from 10-fold cross-validation. GAM OK was further applied to extrapolate species diversity metrics from saturated grid cells (N = 841) to the remaining grid cells with <80 % sample completeness (N = 3914) and generate diversity maps that cover the grid. Further, generalized linear mixed models were used to examine the associations between species diversity and sociodemographic indicators at census tract level. The wild vascular plant species diversity metrics were inversely associated with neighborhood socioeconomic status (i.e., unemployment, linguistic isolation, educational attainment, and poverty rate). Minority populations (i.e., African American, Asian American, and Hispanic) and children had significantly lower diversity exposure in their neighborhoods. Crowdsourcing data offers a cost-effective solution for characterizing large-scale biodiversity in urban areas.

Accumulation degree and risk assessment of metals in street dust from a developing city in Central Taiwan.

Due to the numerous industrial parks and high traffic density in Miaoli, Taiwan, large amounts of metals may be released into the atmosphere, accumulating in street dust. Therefore, this study aimed to collect street dust in Miaoli to quantify the metals and assess the accumulation degree, sources, and potential risks. The enrichment factor (EF), geological accumulation index (Igeo), ecological risk, and non-carcinogenic and lifetime carcinogenic risk were estimated to assess the accumulation degree and the potential environmental and health risks. Pearson correlation analysis, principal component analysis, and positive matrix factor model were used to clarify the relationship between levels of metals and identify possible sources. The levels of metals in street dust in order were Fe > Zn > Mn > Cu > Cr > Ni > Pb > Sr > Co > Sb. According to Igeo, the level of Ni indicated moderately polluted. The levels of Zn, Cu, and Pb showed moderate to strong pollution, strong pollution, and very strong pollution, respectively. Results of average ecological risk analysis pointed out that Pb and Cu represent a very high risk, while other metals posed low-to moderate-level ecological risks. Excluding the Steel Enterprise area, based on the EF value and source identification, it might be concluded that Co, Sr, Fe, Mn, and Sb were mainly from natural sources, while Cu, Pb, and Zn come from anthropogenic pollution sources. Based on the results of the risk assessments, most metals pose no serious adverse health risk to humans. But, in comparison to Miaoli townships, the health risks of residents living in the Steel Enterprise area were higher. However, given that children and adolescents exposure to Co, Cr, Pb, and Ni together constitute a relatively higher carcinogenic risk (CR > 10-6), more attention needs to be paid to the populations most susceptible.

Cost-benefits analysis of ultra-low emissions standard on air quality and health impact in thermal power plants in China.

As China's largest energy infrastructure, thermal power plant consumed approximately half of China's coal over the past decade and threatened air quality, human health and socioeconomic development. Thus, a series of control policies have been implemented to alleviate those impacts in China. Particularly, China has witnessed unprecedented declines in air pollutant emissions from thermal power plants since the ultra-low emissions (ULE) standards were implemented. In contrast, the effect of the ULE policy on air quality, health and cost benefits remains poorly understood. Therefore, this study estimates the improved air quality and associated health and economic benefits under the ULE standards in the thermal power sector by using a measure-specific approach, combining a bottom-up emission inventory, an atmospheric model, a health assessment model and a cost analysis model. The results show that all the control measures lead to reduced air pollution, and renovating pre-existing units (RPU) is the most effective. Compared to without implementing the ULE policy, the population-weighted average PM2.5 and O3 concentrations decreased by 1.50 µg/m3 and 0.87 ppm, and 67,831 premature deaths could be avoided nationally. Furthermore, the results also show the net economic benefits of combining health benefits and costs due to control measures are 109.92 billion Yuan (in 2015 value) in China. The comprehensive results reveal that the health benefits outweigh the direct policy. Based on these empirical findings and the specific circumstances of China, we suggest that RPU should be further promoted to the entire of China, and if necessary, establish a long-term compensation mechanism for inter-provincial interests and institute and enforce comprehensive policies that carefully consider the health impacts of policies. This study provides strong arguments for China's policy-making and considering tightening emission standards for thermal power plants worldwide.

Imaging feature-based clustering of financial time series.

Timeseries representation underpin our ability to understand and predict the change of natural system. Series are often predicated on our choice of highly redundant factors, and in fact, the system is driven by a much smaller set of latent intrinsic keys. It means that a better representation of data makes points in phase space clearly for researchers. Specially, a 2D structure of timeseries could combine the trend and correlation characters of different periods in timeseries together, which provides more clear information for top tasks. In this work, the effectiveness of 2D structure of timeseries is investigated in clustering tasks. There are 4 kinds of methods that the Recurrent Plot (RP), the Gramian Angular Summation Field (GASF), the Gramian Angular Differential Field (GADF) and the Markov Transition Field (MTF) have been adopted in the analysis. By classifying the CSI300 and S&P500 indexes, we found that the RP imaging series are valid in recognizing abnormal fluctuations of financial timeseries, as the silhouette values of clusters are over 0.6 to 1. Compared with segment methods, the 2D models have the lowest instability value of 0. It verifies that the SIFT features of RP images take advantage of the volatility of financial series for clustering tasks.

Association of Neighborhood Socioeconomic Disadvantage and Postpartum Readmission.

We assessed whether neighborhood socioeconomic disadvantage, as measured by the Area Deprivation Index (ADI), was associated with an increased risk of postpartum readmission. This is a secondary analysis from nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be), a prospective cohort of nulliparous pregnant individuals from 2010 to 2013. The exposure was the ADI in quartiles, and the outcome was postpartum readmission; Poisson regression was used. Among 9,061 assessed individuals, 154 (1.7%) were readmitted postpartum within 2 weeks of delivery. Individuals living with the most neighborhood deprivation (ADI quartile 4) were at increased risk of postpartum readmission compared with those living with the lowest neighborhood deprivation (ADI quartile 1) (adjusted risk ratio 1.80, 95% CI 1.11-2.93). Measures of community-level adverse social determinants of health, such as the ADI, may inform postpartum care after delivery discharge.

Focused liquid ultrasonography in dropsy protocol for quantitative assessment of subcutaneous edema.

BACKGROUND: Although subcutaneous edema is a common symptom of critically ill patients, it is still underreported due to the lack of a systematic method for evaluating it. The present study aims to describe the occurrence and distribution of subcutaneous edema, as well as the risk factors associated with it, in critically ill patients using the focused liquid ultrasonography in dropsy (FLUID) protocol, and to assess their impact on ICU mortality. METHODS: The FLUID protocol and the pitting test were performed on general ICU patients in China. Cohen's Kappa coefficient and Bland-Altman plots were used to evaluate the agreement between the two methods at each measurement site and between the whole-body subcutaneous edema scores, respectively, while a repeated measures ANOVA was performed to compare the differences between the two methods in whole-body and body-part measurements. A generalized linear model was used to evaluate the risk factors for subcutaneous edema development and the relationship between subcutaneous edema severity and ICU mortality. RESULTS: A total of 145 critically ill patients were evaluated using both approaches, of whom 40 (27.6%) experienced subcutaneous edema. Over 1440 measurements, it was found that ultrasound discovered more subcutaneous edema than the pitting test (ultrasound: 522[36.3%], pitting test: 444[30.8%], χ2 = 9.477, p = 0.002). The FLUID protocol scored edema severity significantly higher than the pitting test in the whole body and specific body parts, including the abdominal wall, thighs, chest wall, and hands. Subcutaneous edema exhibited gravity-dependent distribution patterns, particularly in the abdominal wall. The APACHE II, NT-proBNP, serum creatinine, and sepsis were independent risk factors for subcutaneous edema development. The score of ultrasonic subcutaneous edema was related to ICU mortality. CONCLUSIONS: The FLUID protocol provides a comprehensive strategy for the semi-quantitative assessment of subcutaneous edema in critically ill patients. In detecting the onset and severity of edema, ultrasound was found to outperform the pitting test. Subcutaneous edema showed a gravity-dependent distribution pattern, and its severity was associated with mortality.

Tomato based gelatin methacryloyl hydrogel as an effective natural and low-cost scaffold for accelerative wound healing.

Oxidative stress and infection are the main reasons for postponement of wound healing rate. They can potentially lead to serious inflammation and eventually lead to a longer and more painful recovery phase. Although wound dressings based on synthetic materials with antioxidative property have been proved to exhibit remarkable effect in controlling ROS level and improving wound healing, issues, such as high cost in raw materials, complicated procedures, usage of various toxic additives, and potential allergies, have significantly confined further clinical applications. In this study, a novel type of tissue engineering scaffold, based on tomatoes (Solanum lycopersicon) and gelatin methacryloyl (GelMA), was prepared via facile lyophilization and photo cross-link method (SL/GelMA). By taking advantages of various antioxidative components, such as carotenoids, flavonoids, phenolic acids, vitamin E, and vitamin C in tomatoes, SL/GelMA can effectively regulate ROS level, relieve the oxidative stress in wound bed, promote cell migration and angiogenesis, contribute to collagen deposition, and thus accelerate the rate of wound enclosure. Along with its high biocompatibility and low allergic potential, we believe that the food-derived wound dressing with facile preparation method, easy accessibility, and high cost-effectiveness can be translated for clinical treatments of various chronic wounds.

Community-Engaged Use of Low-Cost Sensors to Assess the Spatial Distribution of PM2.5 Concentrations across Disadvantaged Communities: Results from a Pilot Study in Santa Ana, CA.

PM2.5 is an air pollutant that is widely associated with adverse health effects, and which tends to be disproportionately located near low-income communities and communities of color. We applied a community-engaged research approach to assess the distribution of PM2.5 concentrations in the context of community concerns and urban features within and around the city of Santa Ana, CA. Approximately 183 h of one-minute average PM2.5 measurements, along with high-resolution geographic coordinate measurements, were collected by volunteer community participants using roughly two dozen low-cost AtmoTube Pro air pollution sensors paired with real-time GPS tracking devices. PM2.5 varied by region, time of day, and month. In general, concentrations were higher near the city's industrial corridor, which is an area of concern to local community members. While the freeway systems were shown to correlate with some degree of elevated air pollution, two of four sampling days demonstrated little to no visible association with freeway traffic. Concentrations tended to be higher within socioeconomically disadvantaged communities compared to other areas. This pilot study demonstrates the utility of using low-cost air pollution sensors for the application of community-engaged study designs that leverage community knowledge, enable high-density air monitoring, and facilitate greater health-related awareness, education, and empowerment among communities. The mobile air-monitoring approach used in this study, and its application to characterize the ambient air quality within a defined geographic region, is in contrast to other community-engaged studies, which employ fixed-site monitoring and/or focus on personal exposure. The findings from this study underscore the existence of environmental health inequities that persist in urban areas today, which can help to inform policy decisions related to health equity, future urban planning, and community access to resources.

The challenge of healthcare big data to China's commercial health insurance industry: evaluation and recommendations.

BACKGROUND: China's social medical insurance system faces challenges in financing, product coverage, patient health responsibility sharing and data security, which commercial health insurance companies can help address. Confronting accelerated population aging, the rapid increase of patients with chronic diseases and the maternal and child healthcare needs created by the three-child policy, the Chinese government has encouraged the development of commercial health insurance. But China's commercial health insurance companies face financial sustainability problems, limited product ranges and high operating costs. At the same time, the informatization level of China's healthcare industry, and the value of healthcare big data, is increasing. We analyze and describe the potential application of healthcare big data in the life cycle of China's commercial health insurance system and provide specific action plans for Chinese commercial health insurance companies; identify the challenges to commercial health insurers; and make recommendations for the application of big health data by commercial health insurers. Our recommendations inform healthcare policy makers on the development of commercial health insurance and the improvement of the healthcare financing system. We not only verify the value of healthcare big data, but also identify specific ways that healthcare big data plays in the development of commercial health insurance. Based on the research results, we recommend new policies for government and new uses of healthcare big data for commercial health insurance institutions. The benign development of commercial health insurance will improve the level of health services in China. METHODS: By interviewing health insurance managers (including actuaries, product managers, business executives, information technology medical workers, and commercial health insurance personnel) and by accessing research papers, industry reports, news reports and public information disclosure documents about commercial health insurance, we describe the impact of healthcare big data on the life cycle of commercial health insurance products and processes. RESULTS: We identify the issues and challenges of commercial health insurers in the use of healthcare big data, and advance specific strategies to expand the use of healthcare big data. In the life cycle of commercial health insurance products, healthcare big data can improve premium income, control medical costs and increase operational efficiency. First, healthcare big data can increase premiums, products and services by attenuating moral hazard and adverse selection problems, where high quality clients over-pay and high-risk clients underpay for health insurance. Second, healthcare big data can reduce medical expenses compensation pay-outs by promoting the establishment of a management medical system. Finally, the use of healthcare big data improves operational efficiency by increasing payment speeds, identifying fraud and increasing claim verification processes through automating payments and reducing offline processes. We discuss the obstacles to obtain healthcare big data confronting commercial health insurance companies. The sharing and data mining of healthcare big data brings privacy risks to the insured and there are significant differences in data standards and quality of healthcare big data that limit the application of healthcare big data in commercial health insurance. We recommend that national, regional and local government departments coordinate policies to facilitate the cooperation between commercial health insurance companies and regional healthcare big data platforms. In terms of technology, we recommend the establishment of data sharing platforms and data exchange mechanism across institutions and regions according to nation-wide standards and specifications. Government management departments should establish healthcare big data standards and specification system, promote the construction of healthcare big data and ensure the integrity, authenticity and reliability of health data. We recommend data quality continuous improvement and management mechanisms that combine technology and management. Government regulation should oversee commercial health insurance institutions and establish data security management systems to monitor and supervise the privacy of personal data. CONCLUSIONS: Healthcare big data can play an important role in the development of China's commercial health insurance industry. Healthcare big data can increase commercial health insurers' financial viability while providing improved, and cost-effective, products and services. By providing more and better information to insurers, healthcare big data attenuates the asymmetric information problem, addressing moral hazard and adverse selection problems. By combining hospital and medical organization management information systems with insurers' data management, healthcare big data can help insurers set sustainable premiums, control medical costs and promote operational efficiency. At present, the informatization degree of China's healthcare industry remains limited. To improve the performances, products and services of commercial health insurers, we recommend government reforms in healthcare big data, such as expanding medical industry cooperation; further developing the processes of applying healthcare big data; augmenting data sharing; addressing privacy risks; setting data standards; and improving data quality.

[Spatiotemporal Distribution and Risk Assessment of Pharmaceuticals in Typical Drinking Water Sources in the Middle Reaches of the Yangtze River].

The seasonal variation and spatial distribution of pharmaceuticals in typical drinking water sources in the middle reaches of the Yangtze River were analyzed using the solid-phase extraction and high-performance liquid chromatography-tandem mass spectrometry methods. Combined with the risk entropy method, the corresponding ecological risks for aquatic organisms were evaluated. The results showed that 80% of the target pharmaceuticals were detected in the drinking water sources, with average concentrations of 0.07-13.00 ng·L-1. The concentrations of the target pharmaceuticals were lower than or comparable with those in other drinking water sources reported in China. The spatiotemporal distribution of different pharmaceuticals varied. Generally, the detection level in winter was higher than that in summer, and there was no significant difference between that upstream and that downstream. This might be mainly attributed to seasonal/regional use and emissions of the pharmaceuticals, the impact of flow rate on dilution, and the impact of temperature on biodegradation. Compared with those before the COVID-19 epidemic, the detection concentrations of the target pharmaceuticals were relatively low. The reason for this might be that the prevention and control of the epidemic reduced the use and emission of the pharmaceuticals to a certain extent, and the high rainfall and runoff strengthened the dilution of water flow. The target pharmaceuticals, especially antibiotics, posed medium or low risks to aquatic organisms (especially algae). Considering the ecological risks and genotoxicity of pharmaceuticals and the potential risks of antibiotic-resistant genes, it is suggested to strengthen the investigation, evaluation, treatment, and control of pharmaceuticals in the water environment.

Water quality evaluation and ecological-health risk assessment on trace elements in surface water of the northeastern Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau is a unique area with water sources for approximately 40 % of the population in the world. Water resources and water quality are closely associated with ecological security and human health. Fifty-one trace elements in surface water samples (n = 40) were measured, and water quality, health and ecological risks were assessed. Trace elements showed significant variations in different surface water bodies in the study area. Concentrations of minor elements were relatively high in saline and salt lakes while those of REEs varied from 0.05 to 33.62 µg/L with an average value of 3.80 µg/L. The Nemerow pollution index (NP) values of trace elements ranged from 0.08 to 3.48, with an average value of 0.36 in rivers, fresh lakes and reservoir water samples; The heavy metal pollution index (HPI) values ranged from 3.70 to 21.18, indicating that most samples were within the critical limit; The heavy metal evaluation index (HEI) values and degree of contamination (DC) values indicated a free pollution status. The water quality index (WQI) values showed that 96 % of the samples belonged to excellent status in rivers, fresh lakes and reservoir water samples. More attention should be given to the Cr, Zn and Hg in the study area according to potential ecological risk assessment. Hazard quotients for residential children in 30 sites exceed 1.0 with maximal value of 10.97, suggesting the high non-carcinogenic risks for children in the study area. U, Zr and Cr for the ingestion pathway, Cr and U for the dermal pathway were primary contributors to the total health risk. Carcinogenic risk values of trace elements for residential and recreational receptors were in the range of 3.20 × 10-5-7.38 × 10-3 and 8.62 × 10-6-3.63 × 10-3, respectively. The carcinogenic risk values of Cr in surface water were higher than the target risk of 1 × 10-4, while the carcinogenic risk values of As were below the target risk. The results of this study provided information on trace elements for human health protection and water management in the northeastern Qinghai-Tibet Plateau.

Polystyrene microplastic particles: In vivo and in vitro ocular surface toxicity assessment.

Microplastics (MPs) have become a global concern as a key environmental pollutant. MPs are widely found in oceans, rivers, bottled water, plastic-packaged foods, and toiletries. The ocular surface is the exposed mucosal tissue, which comes in contact with MP particles contained in toiletries, tap water, cosmetics, and air. However, the effects of MPs on ocular surface health are still unclear. In this study, the toxic effects of polystyrene MPs (PS-MPs) on the ocular surface in vivo and in vitro were explored. The results demonstrated that 50 nm or 2 µm PS-MPs, following exposure for 48 h appeared in the cytoplasm of two kinds of eye cells in vitro and caused a concentration dependent reduction in cell viability, further causing oxidative stress and cell apoptosis. In addition, after treatment for 2 or 4 weeks, 50 nm and 2 µm PS-MPs were deposited in the conjunctival sac of mice. After 2 and 4 weeks of PS-MP treatment, the number of goblet cells in the lower eyelid conjunctival sac decreased to 65% and 40% of that in the control group, respectively. Moreover, dry eye like ocular surface damage and inflammation of conjunctiva and lacrimal gland in mice were observed. In conclusion, this study revealed that PS-MPs could cause ocular surface dysfunctions in mice, thus providing a new perspective for the toxic effects of MPs on ocular surface.

Socioeconomic Disparities of Low-Cost Air Quality Sensors in California, 2017-2020.

Objectives. To (1) examine the disparity in availability of PurpleAir low-cost air quality sensors in California based on neighborhood socioeconomic status (SES) and exposure to fine particulate matter smaller than 2.5 micrometers (PM2.5), (2) investigate the temporal trend of sensor distribution and operation, and (3) identify priority communities for future sensor distribution. Methods. We obtained census tract-level SES variables and PM2.5 concentrations from the CalEnviroScreen4.0 data set. We obtained real-time PurpleAir sensor data (July 2017-September 2020) to examine sensor distribution and operation. We conducted spatial and temporal analyses at the census tract level to investigate neighborhood SES and PM2.5 concentrations in relation to sensor distribution and operation. Results. The spatial coverage and the number of PurpleAir sensors increased significantly in California. Fewer sensors were distributed in census tracts with lower SES, higher PM2.5, and higher proportions of racial/ethnic minority populations. Furthermore, a large proportion of existing sensors were not in operation at a given time, especially in disadvantaged communities. Conclusions. Disadvantaged communities should be given access to low-cost sensors to fill in spatial gaps of air quality monitoring and address environmental justice concerns. Sensor purchasing and deployment must be paired with regular maintenance to ensure their reliable performance. (Am J Public Health. 2022;112(3):434-442. https://doi.org/10.2105/AJPH.2021.306603).