Cost-utility analysis of Social Stories™ for children with autism spectrum disorder in mainstream primary schools: results from a randomised controlled trial.

BACKGROUND: One in 57 children are diagnosed with autism in the UK, and the estimated cost for supporting these children in education is substantial. Social Stories™ is a promising and widely used intervention for supporting children with autism in schools and families. It is believed that Social Stories™ can provide meaningful social information to children that can improve social understanding and may reduce anxiety. However, no economic evaluation of Social Stories has been conducted. AIMS: To assess the cost-effectiveness of Social Stories through Autism Spectrum Social Stories in Schools Trial 2, a multi-site, pragmatic, cluster-randomised controlled trial. METHOD: Children with autism who were aged 4-11 years were recruited and randomised (N = 249). Costs measured from the societal perspective and quality-adjusted life-years (QALYs) measured by the EQ-5D-Y-3L proxy were collected at baseline and at 6-month follow-up for primary analysis. The incremental cost-effectiveness ratio was calculated, and the uncertainty around incremental cost-effectiveness ratios was captured by non-parametric bootstrapping. Sensitivity analyses were performed to evaluate the robustness of the primary findings. RESULTS: Social Stories is likely to result in a small cost savings (-£191 per child, 95% CI -767.7 to 337.7) and maintain similar QALY improvements compared with usual care. The probability of Social Stories being a preferred option is 75% if society is willing to pay £20 000 per QALY gained. The sensitivity analysis results aligned with the main study outcomes. CONCLUSIONS: Compared with usual care, Social Stories did not lead to an increase in costs and maintained similar QALY improvements for primary-aged children with autism.

Duoculture diminishes social interaction costs and improves growth rates of two fish species at different temperatures.

Duoculture has been reported to increase growth rates of some fishes when reared in combination, due to "shading" effects between the species. Two experiments, one involving outdoor cage-rearing in a reservoir, and the other, indoor tank-rearing, were conducted within each of three temperatures ranges (means of ~18.0°C, ~22.0°C and ~26.5°C), to determine whether duoculture of bluegill (BG) Lepomis macrochirus and yellow perch (YP) Perca flavescens would lead to improved growth relative to when the two species were reared separately. Juvenile bluegill and yellow perch were reared in triplicated groups each involving monoculture sets of 100% BG and 100% YP, and a duoculture set of 50% BG + 50% YP. Experiments in cages (Exp. 1) ran for 150 days while those in tanks ran for 126 days (Exp. 2). In Experiment 1, bluegill exhibited significantly greater (P<0.05) mean weight (P<0.05) in duoculture than in monoculture, under the high summer-like range of temperature (~26.5°C) over most of the experiment, whereas yellow perch showed no significant difference in mean weight in duoculture versus monoculture. By the end of a 150-d experiment, bluegill in duoculture outweighed those in monoculture by 62.5%. In Experiment 2, yellow perch in duoculture grew significantly larger than in monoculture (P<0.05) under the warm thermal regime (mean of ~22°C), while no significant differences were detected in mean weight of bluegill in monoculture versus duoculture. Yellow perch in duoculture outweighed those in monoculture by 33.1% at the end of the experiment. Yellow perch performed better in duoculture than in monoculture under the low thermal regime (mean of ~18°C) in both experiments. A significantly greater reduction of CVwt was observed for both bluegill and yellow perch in duoculture than in monoculture in Experiment 1, while no differences in CVwt reduction were detected for bluegill in Experiment 2. Feed conversion ratios (FCR) of bluegill and yellow perch reared in duoculture were significantly lower than for both fishes reared in monoculture in Experiment 1, while there were no significant differences in FCR among the three groups throughout most of Experiment 2. Findings indicate that duoculture of yellow perch and bluegill holds good potential to improve growth and FCR, and to reduce size variation by diminishing social interaction costs.

Performance assessment of the effective core potentials under the fermionic neural network: First and second row elements.

The rapid development of deep learning techniques has driven the emergence of a neural network-based variational Monte Carlo (VMC) method (referred to as FermiNet), which has manifested high accuracy and strong predictive power in the electronic structure calculations of atoms, molecules, and some periodic systems. Recently, the implementation of the effective core potential (ECP) scheme has further facilitated more efficient calculations in practice. However, there is still a lack of comprehensive assessments of the ECP's performance under the FermiNet. In this work, we set sail to fill this gap by conducting extensive tests on the first two row elements regarding their atomic, spectral, and molecular properties. Our major finding is that, in general, the qualities of ECPs have been correctly reflected under FermiNet. Two recently built ECP tables, namely, correlation consistent ECP (ccECP) and energy consistent correlated electron pseudopotential (eCEPP), seem to prevail in terms of overall performance. In particular, ccECP performs slightly better on spectral precision and covers more elements, while eCEPP is more systematically built from both shape and energy consistency and better treats the core polarization. On the other hand, the high accuracy of the all-electron calculations is hindered by the absence of relativistic effects as well as the numerical instabilities in some heavier elements. Finally, with further in-depth discussions, we generate possible directions for developing and improving FermiNet in the near future.

Real-world evidence from a retrospective study on suicide during depression: clinical characteristics, treatment patterns and disease burden.

BACKGROUND: Suicide stands as both a primary symptom and the direst outcome of major depressive disorder (MDD). The scarcity of effective treatment strategies makes managing MDD patients with suicide especially challenging. Hence, it is crucial to investigate disease characteristics and efficacious therapeutic strategies for these patients, drawing insights from disease databases and real-world data. METHODS: In this retrospective study, MDD patients hospitalized between January 2013 and December 2020 were investigated using Electronic Health Records (EHR) data from Beijing Anding Hospital. The study enrolled 4138 MDD patients with suicidal ideation or behavior (MDS) and 3848 without (MDNS). Demographic data, clinical attributes, treatment approaches, disease burden, and re-hospitalization within one year of discharge were extracted and compared. RESULTS: Patients in the MDS group were predominantly younger and female, exhibiting a higher prevalence of alcohol consumption, experiencing frequent life stress events, and having an earlier onset age. Re-hospitalizations within six months post-discharge in the MDS group were significantly higher than in the MDNS group (11.36% vs. 8.91%, p < 0.001). Moreover, a more considerable fraction of MDS patients underwent combined electroconvulsive therapy treatment (56.72% vs. 43.71%, p < 0.001). Approximately 38% of patients in both groups were prescribed two or more therapeutic regimes, and over 90% used antidepressants, either alone or combined. Selective serotonin reuptake inhibitors (SSRIs) were the predominant choice in both groups. Furthermore, antidepressants were often prescribed with antipsychotics or mood stabilizers. When medication alterations were necessary, the favoured options involved combination with antipsychotics or transitioning to alternative antidepressants. Yet, in the MDS group, following these initial modifications, the addition of mood stabilizers tended to be the more prioritized alternative. CONCLUSIONS: MDD patients with suicidal ideation or behaviour displayed distinctive demographic and clinical features. They exhibited intricate treatment patterns, a pronounced burden of illness, and an increased likelihood of relapse.

Inhalation bioaccessibility of imidacloprid in particulate matter: Implications for risk assessment during spraying.

Adverse health outcomes due to the inhalation of pesticide residues in atmospheric particulate matter (PM) are gaining global attention. Quantitative health risk assessments of pesticide inhalation exposure highlight the need to understand the bioaccessibility of pesticide residues. Herein, the inhalation bioaccessibility of imidacloprid in PM was determined using three commonly used in vitro lung modeling methods (Artificial Lysosomal Fluid, Gamble Solution, and Simulated Lung Fluid). To validate its feasibility and effectiveness, we evaluated the bioavailability of imidacloprid using a mouse nasal instillation assay. The in vitro inhalation bioaccessibility of imidacloprid was extracted using Gamble Solution with a solid-liquid ratio of 1/1000, an oscillation rate of 150 r/min, and an extraction time of 24 h, showed a strong linear correlation with its in vivo liver-based bioavailability (R2 =0.8928). Moreover, the margin of exposure was incorporated into the inhalation exposure risk assessment, considering both formulations and nozzles. The inhalation unit exposure of imidacloprid for residents was 0.95-4.09 ng/m3. The margin of exposure for imidacloprid was determined to be acceptable when considering inhalation bioaccessibility. Taken together, these results indicate that the inhalation bioaccessibility of pesticides should be incorporated into assessments of human health risks posed by PM particles.

[Assessment of CO2 Co-benefits of Air Pollution Control Policies in Taiyuan's 14th Five-Year Plan].

To quantitatively evaluate the co-benefits of air pollution reduction and carbon dioxide reduction of Taiyuan's 14th Five-Year Plan air pollution prevention and control policies, this study used the Beijing-Tianjin-Hebei Greenhouse Gas-Air Pollution Interaction and Synergy Model (GAINS-JJJ) to simulate and evaluate the emission reduction potential and CO2 co-benefit of 13 air pollution control measures. The emission reductions of PM2.5, PM10, SO2, NOx, VOCs, and NH3 in 2025 were 1.8 (5%, compared with that in the baseline scenario), 2.5 (2%), 3.7 (16%), 20.0 (27%), 13.6 (15%), and 0.0 kt (0%), respectively. The reduction in CO2 emissions was 9.0 Mt (13%), whereas CH4 emissions increased by 203.3 kt (25% increase relative to that in the baseline scenario). SO2, NOx, and VOCs emission reductions derived from the power, industrial combustion, and solvent use sectors. CO2 reduction occurred mainly in the industrial combustion sector, and CH4 emission increased mainly due to the increase in coal mining activity. The highest synergistic CO2 reductions were achieved by restricting energy consumption in the high energy-consuming and high-emitting sectors; prohibiting new capacity in the steel, coke, cement, and flat glass industries; and replacing coal-fired power generation with renewable energy. Furthermore, the CO2 reduction co-benefit was highest for VOCs. In addition, this study suggests that promoting the policy of terminal electrification and simultaneously increasing the share of clean energy and the ability to consume renewable energy generation in the power sector are the keys to decreasing the emissions in Taiyuan.

Treatment response assessment to chemotherapy with bevacizumab for colorectal liver metastasis by contrast-enhanced ultrasound.

Background: Though contrast-enhanced ultrasound (CEUS) perfusion parameters have been approved to be potential indicators for response to chemotherapy in solid tumors, their ability in assessment of colorectal liver metastasis (CRLM) to chemotherapy with bevacizumab (Bev) has rarely been investigated. Methods: From March 2021 to May 2022, 115 consecutive CRLM patients with CEUS pre- and post-2 months' chemotherapy with Bev were prospectively enrolled. One target lesion per patient underwent CEUS quantitative analysis with SonoLiver software. Rise time, time-to-peak, mean transit time, maximal intensity (IMAX), and area under the time-intensity curve (AUC) were assessed with region of interest (ROI) selected on whole lesion, lesion periphery, and internal lesion, respectively. The reduction and ratio of post- to pre-treatment in parameters were investigated in development cohort (n=89) and validated in internal validation cohort (n=26) according to the chronological order. Results: With modified Response Evaluation Criteria in Solid Tumor as reference, 48, 14 responders and 41, 12 non-responders were included in development and validation cohort, respectively. Significantly smaller values of IMAX and AUC on ROIwhole, ROIperipheral, and ROIinternal, were observed post-treatment in development cohort (all P<0.05). In predicting treatment response, the influence of ROI selection was observed when using ∆IMAX and ∆AUC, while no influence was observed using ratios. Areas under the receiver operating characteristic curve (AUROCs) for ∆IMAX and ∆AUC on ROIperipheral were 0.939 (0.867-0.979), 0.951 (0.883-0.985), and 0.917 (0.740-0.988), 0.923 (0.748-0.990) in development and validation cohort, respectively. For ratios of IMAX and AUC, AUROCs were 0.976 (0.919-0.997), 0.938 (0.865-0.978), and 0.899 (0.717-0.982), 0.982 (0.836-1.000) in development and validation cohort, respectively. Conclusions: IMAX and AUC showed significant reductions in responders, and different analyses ROIs influence the performance of ∆IMAX and ∆AUC in response assessment. Parameters derived from ROI peripheral exhibited the most promising results in predicting treatment response.

MR Spectroscopy Assessment of Daily Variations of GABA Levels within the Parietal Lobe and Anterior Cingulate Gyrus Regions of Healthy Young Adults.

BACKGROUND: The changes that occur in the gamma-aminobutyric acid (GABA) levels within specific brain regions throughout the day are less clear. PURPOSE: To evaluate the daily fluctuations of GABA levels within the parietal lobe (PL) and anterior cingulate gyrus (ACC) regions and explore their association with melatonin (MT) levels, heart rate (HR), and blood pressure. STUDY TYPE: Prospective. SUBJECTS: 26 healthy young adults (15 males and 11 females aged 22-27 years). FIELD STRENGTH/SEQUENCE: 3.0T, T1-weighted imaging, Mescher-Garwood point resolved spectroscopy (MEGA-PRESS) sequence. ASSESSMENT: The acquired GABA signal contained the overlapping signals of macromolecules and homocarnosine, hence expressed as GABA+. The creatine (Cr) signal was applied as an endogenous reference. The GABA+, GABA+/Cr were measured at six different time points (1:00, 5:00, 9:00, 13:00, 17:00, and 21:00 hours) using MEGA-PRESS. The blood pressure, HR and sputum MT levels, were also acquired. STATISTICAL TESTS: The one-way repeated-measures analysis of variance (ANOVA) was used to evaluate the GABA, blood pressure, HR, and MT levels throughout the day. A general linear model was used to find the correlation between GABA and blood pressure, HR, and MT. P < 0.05 was statistically significant. RESULTS: Significant variations in GABA+/Cr and GABA+ levels were observed throughout the day within the PL region. The lowest levels were recorded at 9:00 hour (GABA+/Cr: 0.100 ± 0.003，GABA+:1.877 ± 0.051 i.u) and the highest levels were recorded at 21:00 hour (GABA+/Cr: 0.115 ± 0.003, GABA+:2.122 ± 0.052 i.u). The MT levels were positively correlated with GABA+/Cr (r = 0.301) and GABA+ (r = 0.312) within the ACC region. DATA CONCLUSION: GABA+/Cr and GABA+ in ACC are positively correlated with MT. GABA levels in the PL have diurnal differences. These findings may indicate that the body's GABA level change in response to the light-dark cycle. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

A new assessment method for water environment safety and its application.

The Three Gorges Reservoir area is recognized by its vast size, dense population, bustling economic and social activities along its banks, and by the significant volume of waterway traffic. These factors make it with a high risk of water pollution accidents, posing a serious threat to water environmental safety. Therefore, it is imperative to conduct a water environmental safety assessment in this region to ensure the safety of the water environment. In the present work, the Driving-Pressure-State-Impact-Response-Risk Water Environmental Safety model was proposed, and a comprehensive water environmental safety assessment system was established. The Water Environment Safety Index was introduced to measure the degree of water environment safety. This model synthesized multiple factors and their interrelationships, enabling a more accurate assessment of water environment safety. By adopting scientifically rigorous evaluation criteria, this assessment method enhanced the reliability and credibility of the results obtained. The water environment safety in the 22 counties and districts of the Three Gorges Reservoir area of Chongqing region from 2017 to 2021 was assessed in terms of temporal changes and spatial differentiation. In general, the overall water environment safety situation in the Three Gorges Reservoir area of Chongqing region is relatively safe, but a few counties/districts (such as Wanzhou District, Jiangjin District, etc.) are still in Warning. Spatially, the water environmental safety condition was relatively better in the northeast compared to the southwest. The main factors threatening water environment safety include: 1) the consequence of the Three Gorges Project, 2) severe soil erosion, 3) industrial, agricultural, and domestic pollution, and 4) frequent water pollution accidents. The present work provided a new method for conducting water environment safety assessments, which is expected to positively contribute to further research in this field.

In vitro inhalation bioaccessibility and health risk assessment of difenoconazole in the atmosphere.

BACKGROUND: Assessment of the risk of pesticide inhalation in populations around farmland is necessary because inhalation is one of the ways in which pesticides can risk human health. This study aimed to identify the inhalation risk of difenoconazole on humans by using dose-response and exposure assessments. RESULTS: In the field simulation application, respiratory exposure in populations around farmland ranged from 71 to 430 ng/m3 . Using response surface methodology, the maximum bioaccessibility of difenoconazole in three simulated lung fluids was 35.33% in Gamble's solution (GS), 34.12% in artificial lysosomal fluid (ALF), and 42.06% in simulated interstitial lung fluid (SLF). Taking the proliferation activity of the A549 cell model as the endpoint, the benchmark dose limit and benchmark dose of difenoconazole on A549 cells were 16.36 and 5.60 mg/kg, respectively. The margin of exposure to difenoconazole in GS, ALF and SLF were, respectively, 8.66 × 105 to 5.28 × 106 , 8.97 × 105 to 5.47 × 106 and 7.28 × 105 to 4.44 × 106 . CONCLUSION: The risk assessment results indicate that under all circumstances, applying difenoconazole is safe for populations around farmland. However, a fan-shaped nozzle, suspension concentrate and greater inhalation height increase the risk of inhalation. © 2023 Society of Chemical Industry.

Play brick therapy to aid the social skills of children and young people with autism spectrum disorder: the I-SOCIALISE cluster RCT.

Background: Social skills interventions are commonly recommended to help children and young people with autism spectrum disorder develop social skills, but some struggle to engage in these interventions. LEGO® (LEGO System A/S, Billund, Denmark) based therapy, a group social skills intervention, aims to be more interesting and engaging. Objective: To evaluate the clinical effectiveness of LEGO® based therapy on the social and emotional skills of children and young people with autism spectrum disorder in school settings compared with usual support. Secondary objectives included evaluations of cost-effectiveness, acceptability and treatment fidelity. Design: A cluster randomised controlled trial randomly allocating participating schools to either LEGO® based therapy and usual support or usual support only. Setting: Mainstream schools in the north of England. Participants: Children and young people (aged 7-15 years) with autism spectrum disorder, their parent/guardian, an associated teacher/teaching assistant and a facilitator teacher/teaching assistant (intervention schools only). Intervention: Schools randomised to the intervention arm delivered 12 weekly sessions of LEGO® based therapy, which promotes collaborative play and encourages social problem-solving in groups of three children and young people with a facilitator (trained teacher or teaching assistant). Participants received usual support from school and community services. Participants in the control arm received usual support only. Research assistants and statisticians were blind to treatment allocation. Main outcome measure: The social skills subscale of the Social Skills Improvement System (SSIS), completed by the children and young people's unblinded teacher pre randomisation and 20 weeks post randomisation. The SSIS social skills subscale measures social skills including social communication, co-operation, empathy, assertion, responsibility and self-control. Participants completed a number of other pre- and post-randomisation measures of emotional health, quality of life, loneliness, problem behaviours, academic competence, service resource utilisation and adverse events. Results: A total of 250 children and young people from 98 schools were randomised: 127 to the intervention arm and 123 to the control arm. Intention-to-treat analysis of the main outcome measure showed a modest positive difference of 3.74 points (95% confidence interval -0.16 to 7.63 points, standardised effect size 0.18; p = 0.06) in favour of the intervention arm. Statistical significance increased in per-protocol analysis, with a modest positive difference (standardised effect size 0.21; p = 0.036). Cost-effectiveness of the intervention was found in reduced service use costs and a small increase in quality-adjusted life-years. Intervention fidelity and acceptability were positive. No intervention-related adverse events or effects were reported. Conclusions: The primary and pre-planned sensitivity analysis of the primary outcome consistently showed a positive clinical difference, with modest standardised effect sizes of between 0.15 and 0.21. There were positive health economics and qualitative findings, corroborated by the difference between arms for the majority of secondary outcomes, which were not statistically significant but favoured the intervention arm. Post hoc additional analysis was exploratory and was not used in drawing this conclusion. Given the small positive change, LEGO® based therapy for children and young people with autism spectrum disorder in schools should be considered. Limitations: The primary outcome measure was completed by an unblinded teacher (rather than by the facilitator). Future work: The study team recommends future research into LEGO® based therapy, particularly in school environments. Trial registration: This trial is registered as ISRCTN64852382. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 15/49/32) and is published in full in Public Health Research; Vol. 11, No. 12. See the NIHR Funding and Awards website for further award information.

Autism spectrum disorder is characterised by difficulties with social relationships and communication, which can make it difficult to make friends. Social skills training is commonly used to help children and young people learn different social skills, but some children and young people do not enjoy these therapies. LEGO^® (LEGO System A/S, Billund, Denmark) based therapy takes a new approach by focusing on making the process interesting and fun. This research investigated the effect of LEGO^® based therapy groups in schools on the social and emotional abilities of children and young people with autism spectrum disorder. It was a randomised controlled trial, so each school that was taking part was randomly chosen to provide either usual support (from the school or NHS services) or 12 sessions of LEGO^® based therapy with a trained school staff member as well as usual support. Children and young people played one of three roles ­ the 'engineer' (gives instructions), the 'supplier' (finds the pieces) or the 'builder' (builds the model) ­ and worked together. Questionnaires completed by children and young people, their parents/guardians and teachers were used to look at the intervention's effects. The main objective was to see if there was a change in social skills measured by a teacher-completed questionnaire. Results showed that the social skills of children and young people in the LEGO^® based therapy groups did improve a little. We found that the intervention is not very costly for schools to run. Many parents/guardians and teachers thought that the intervention was beneficial and that the children and young people enjoyed it.

A Mathematical Prediction Model for Postoperative Infection Based on Logistic Multiple Regression Analysis in the Assessment of Surgical Outcome and Prediction of Infection in Elderly Spinal Fractures.

Objective: Investigating postoperative infection risk factors in elderly spinal fracture patients is crucial for optimizing surgical outcomes, improving patient safety, and guiding clinical decision-making in the management of these complex cases. To investigate the risk factors for postoperative infection in elderly patients with spinal fractures, with the goal of giving clinical care guidelines. Methods: From January 2019 to January 2022, 120 elderly patients admitted to our hospital for elective spinal fracture surgery were featured as the study subjects, and the patients were divided into infected and non-infected categories according to whether they had postoperative infection or not. A mathematical prediction model was built after using logistic multiple regression to investigate the parameters influencing postoperative infection of a spinal fracture. Results: There were 20 patients in the infected category and 100 patients in the non-infected category. Univariate analysis showed that the proportion of patients in the infected category with male, age ≥65 years, multiple fractures, use of hormones or combined diabetes was notably higher than that in the non-infected category (P < .05). Male gender, age ≥65 years, multiple fractures, and certain medical conditions are independent risk factors for postoperative infection. Conclusions: Logistic regression analysis revealed that male, age ≥65 years, multiple fractures, use of hormones, or combined diabetes was an independent risk factor for postoperative infection in elderly patients with spinal fracture. Our study provides valuable insights that can guide clinical care and decision-making for elderly patients with spinal fractures. By applying these findings in practice, clinicians can refine their treatment strategies, improve patient outcomes, and enhance the overall quality of care provided to this vulnerable population.

Assessment of nail fold capillary changes by hand-held dermoscopy in adult dermatomyositis: A single-centre prospective study.

BACKGROUND: Hand-held dermoscopy is a valuable tool for dermatologists, but it has been rarely used to assess the nail fold capillary (NFC) in patients with dermatomyositis (DM). METHODS: Patients were collected from the Department of Dermatology and Venereology from July 2020 to July 2021, and the follow-up was conducted until January 2022. Demographic features, disease activity and NFC changes were analysed using a hand-held dermoscopy. RESULTS: The most common NFC finding in our study was bushy capillary (87.0%). There was no significant improvement in scleroderma-dermatomyositis (SD)-like nail fold changes or enlarged capillaries from baseline to 12 weeks of treatment (p > 0.05) or from 12 weeks to 24 weeks of treatment (p > 0.05), but there was a significant improvement from baseline to 24 weeks of treatment (p < 0.05). The avascular area did not improve from baseline to 12 weeks of follow-up, but the changes were significant from 12 weeks to 24 weeks of treatment (p < 0.05) and baseline to 24 weeks of treatment (p < 0.05). Periungual erythema improved significantly from baseline to 12 weeks of treatment (p < 0.05) and baseline to 24 weeks of treatment (p < 0.05), but it did not improve significantly from 12 weeks to 24 weeks of treatment (p > 0.05). There was no significant difference in disease activity between patients with or without specific NFC changes. However, some NFC features improved as disease activity decreased. CONCLUSION: Dermoscopy of NFC is a cost-effective option for the preliminary diagnosis of DM. Further, long-term follow-up is necessary to study the relationship between disease activity and NFC changes.

Health Utilities of Bilateral Severe-to-Profound Hearing Loss with Assistive Devices.

Hearing loss is a common sensory disorder in newborns. Early intervention with assistive devices benefits children's auditory and speech performance. This study aimed to measure the health utilities of children with bilateral severe-to-profound hearing impairment with different assistive devices. The descriptions of four hypothetical health states were developed, and their utility values were obtained from healthcare professionals via the visual analogue scale (VAS) and time trade-off (TTO) methods. Thirty-seven healthcare professionals completed the TTO interview and were included in the analysis. The mean utility scores obtained via VAS were 0.31 for no assistive devices, 0.41 for bilateral hearing aids, 0.63 for bimodal hearing, and 0.82 for bilateral cochlear implants. As for the utility scores obtained via TTO, mean values were 0.60, 0.69, 0.81, and 0.90, respectively. None of the four groups had the same VAS- or TTO-elicited utility (p < 0.001). The post hoc test results showed that the difference was significant between any two groups (all p < 0.05). In conclusion, this study elicited health utility of bilateral hearing impairment with different assistive devices using the VAS and TTO methods. The utility values obtained provide critical data for future cost-utility analysis and health technology assessment.

Design of a Novel Compact Bandpass Filter Based on Low-Cost Through-Silicon-Via Technology.

Three-dimensional (3D) integration based on through-silicon-via (TSV) technology provides a solution to the miniaturization of electronic systems. In this paper, novel integrated passive devices (IPDs) including capacitor, inductor, and bandpass filter are designed by employing TSV structures. For lower manufacturing costs, polyimide (PI) liners are used in the TSVs. The influences of structural parameters of TSVs on the electrical performance of the TSV-based capacitor and inductor are individually evaluated. Moreover, with the topologies of capacitor and inductor elements, a compact third-order Butterworth bandpass filter with a central frequency of 2.4 GHz is developed, and the footprint is only 0.814 mm × 0.444 mm. The simulated 3-dB bandwidth of the filter is 410 MHz, and the fraction bandwidth (FBW) is 17%. Besides, the in-band insertion loss is less than 2.63 dB, and the return loss in the passband is better than 11.4 dB, showing good RF performance. Furthermore, as the filter is fully formed by identical TSVs, it not only features a simple architecture and low cost, but also provides a promising idea for facilitating the system integration and layout camouflaging of radio frequency (RF) devices.

Occurrence, seasonal variations, distribution patterns, and risk assessment of volatile monoaromatic hydrocarbons in soils of industrial parks in Yangtze River Delta, China.

Monoaromatic hydrocarbons (MACHs) are a ubiquitous category of volatile compounds found in various environmental media. Despite their prevalence, systematic studies of MACHs on a large regional scale are still lacking. Herein, a comprehensive investigation of the occurrence, seasonal variations, distribution characteristics, and health risks of MACHs was carried out by analyzing soil samples (372 surface soils and 96 soil columns) from 33 typical industrial parks in the Yangtze River Delta (YRD) region. MACHs were detected in all surface soil samples. BTEXS (benzene, toluene, ethylbenzene, xylene, and styrene) were the five predominant congeners with the highest detection frequencies (90.9 %-100 %), collectively accounting for >78.2 % of the total MACHs content. Higher residual levels of MACHs were observed in winter compared to summer (P < 0.01), with total concentrations of 24 MACHs ranging from 30.9 ng/g to 1536 ng/g (median: 135 ng/g) in winter and 16.3 ng/g to 931 ng/g (median: 87.9 ng/g) in summer. Soils collected from the northeast of Jiangsu Province and the southwest of Anhui Province exhibited relatively higher levels of MACHs. On the basis of principal component analysis, we proposed that industrial emissions and vehicle exhaust may be the main sources of MACHs contamination in the soils of YRD industrial parks. Vertically, the concentrations of total MACHs decreased with the soil depth. Soil organic matter (OM) content and the concentration of MACHs in the surface soil layer (0-15 cm) were significant factors influencing the vertical migration and distribution of MACHs (P < 0.05). It was verified that residual MACHs in the soils posed lower lifetime non-carcinogenic and carcinogenic risks to the inhabitants of the study area. The field study provides valuable evidence for the formulation of MACHs pollution control policies in the YRD region.

A comprehensive approach to quantify the source identification and human health risk assessment of toxic elements in park dust.

In this research, enrichment factor (EF) and pollution load index were utilized to explore the contamination characteristics of toxic elements (TEs) in park dust. The results exhibited that park dust in the study area was mainly moderately polluted, and the EF values of dust Cd, Zn, Pb, Cu and Sb were all > 1. The concentrations of Cr, Cu, Zn and Pb increased with the decrease of dust particle size. The investigation results of chemical speciation and bioavailability of TEs showed that Zn had the highest bioavailability. Three sources of TEs were determined by positive matrix factorization model, Pearson correlation analysis and geostatistical analysis, comprising factor 1 mixed sources of industrial and transportation activities (46.62%), factor 2 natural source (25.56%) and factor 3 mixed source of agricultural activities and the aging of park infrastructures (27.82%). Potential ecological risk (PER) and human health risk (HHR) models based on source apportionment were exploited to estimate PER and HHR of TEs from different sources. The mean PER value of TEs in the park dust was 114, indicating that ecological risk in the study area was relatively high. Factor 1 contributed the most to PER, and the pollution of Cd was the most serious. There were no significant carcinogenic and non-carcinogenic risks for children and adults in the study area. And factor 3 was the biggest source of non-carcinogenic risk, and As, Cr and Pb were the chief contributor to non-carcinogenic risk. The primary source of carcinogenic risk was factor 2, and Cr was the cardinal cancer risk element.

Incorporating Bioaccessibility into Inhalation Exposure Assessment of Emamectin Benzoate from Field Spraying.

The inhalation exposure of pesticide applicators and residents who live close to pesticide-treated fields is a worldwide concern in public health. Quantitative assessment of exposure to pesticide inhalation health risk highlights the need to accurately assess the bioaccessibility rather than the total content in ambient air. Herein, we developed an in vitro method to estimate the inhalation bioaccessibility of emamectin benzoate and validated its applicability using a rat plasma pharmacokinetic bioassay. Emamectin benzoate was extracted using the Gamble solution, with an optimized solid-to-liquid ratio (1/250), extraction time (24 h), and agitation (200 rpm), which obtained in vitro inhalation bioaccessibility consistent with its inhalation bioavailability in vivo (32.33%). The margin of exposure (MOE) was used to assess inhalation exposure risk. The inhalation unit exposures to emamectin benzoate of applicators and residents were 11.05-28.04 and 0.02-0.04 ng/m3, respectively, varying markedly according to the methods of application, e.g., formulations and nozzles. The inhalation risk assessment using present application methods appeared to be acceptable; however, the MOE of emamectin benzoate might be overestimated by 32% without considering inhalation bioaccessibility. Collectively, our findings contribute insights into the assessment of pesticide inhalation exposure based on bioaccessibility and provide guidance for the safe application of pesticides.

Secondary and Topological Structural Merge Prediction of Alpha-Helical Transmembrane Proteins Using a Hybrid Model Based on Hidden Markov and Long Short-Term Memory Neural Networks.

Alpha-helical transmembrane proteins (αTMPs) play essential roles in drug targeting and disease treatments. Due to the challenges of using experimental methods to determine their structure, αTMPs have far fewer known structures than soluble proteins. The topology of transmembrane proteins (TMPs) can determine the spatial conformation relative to the membrane, while the secondary structure helps to identify their functional domain. They are highly correlated on αTMPs sequences, and achieving a merge prediction is instructive for further understanding the structure and function of αTMPs. In this study, we implemented a hybrid model combining Deep Learning Neural Networks (DNNs) with a Class Hidden Markov Model (CHMM), namely HDNNtopss. DNNs extract rich contextual features through stacked attention-enhanced Bidirectional Long Short-Term Memory (BiLSTM) networks and Convolutional Neural Networks (CNNs), and CHMM captures state-associative temporal features. The hybrid model not only reasonably considers the probability of the state path but also has a fitting and feature-extraction capability for deep learning, which enables flexible prediction and makes the resulting sequence more biologically meaningful. It outperforms current advanced merge-prediction methods with a Q4 of 0.779 and an MCC of 0.673 on the independent test dataset, which have practical, solid significance. In comparison to advanced prediction methods for topological and secondary structures, it achieves the highest topology prediction with a Q2 of 0.884, which has a strong comprehensive performance. At the same time, we implemented a joint training method, Co-HDNNtopss, and achieved a good performance to provide an important reference for similar hybrid-model training.

Spatial correlated incidence modeling with zero inflation.

Disease mapping models have been popularly used to model disease incidence with spatial correlation. In disease mapping models, zero inflation is an important issue, which often occurs in disease incidence datasets with high proportions of zero disease count. It is originated from limited survey coverage or unadvanced testing equipment, which makes some regions have no observed patients. Then excessive zeros recorded in the disease incidence dataset would mess up the true distributions of disease incidence and lead to inaccurate estimates. To address this issue, a zero-inflated disease mapping model is developed in this work. In this model, a zero-inflated process using Bernoulli indicators is assumed to characterize whether the zero inflation occurs for each region. For regions without zero inflation, a coherent and generative disease mapping model is applied for mapping the spatially correlated disease incidence. Independent spatial random effects are incorporated in both processes to account for the spatial patterns of zero inflation and disease incidence. External covariates are also considered in both processes to better explain the disease count data. To estimate the model, a Markov chain Monte Carlo algorithm is proposed. We evaluate model performance via a variety of simulation experiments. Finally, a Lyme disease dataset of Virginia is analyzed to illustrate the application of the proposed model.