The long-term spatio-temporal trends in burden and attributable risk factors of major depressive disorder at global, regional and national levels during 1990-2019: a systematic analysis for GBD 2019.

AIMS: Caused by multiple risk factors, heavy burden of major depressive disorder (MDD) poses serious challenges to public health worldwide over the past 30 years. Yet the burden and attributable risk factors of MDD were not systematically known. We aimed to reveal the long-term spatio-temporal trends in the burden and attributable risk factors of MDD at global, regional and national levels during 1990-2019. METHODS: We obtained MDD and attributable risk factors data from Global Burden of Disease Study 2019. We used joinpoint regression model to assess the temporal trend in MDD burden, and age-period-cohort model to measure the effects of age, period and birth cohort on MDD incidence rate. We utilized population attributable fractions (PAFs) to estimate the specific proportions of MDD burden attributed to given risk factors. RESULTS: During 1990-2019, the global number of MDD incident cases, prevalent cases and disability-adjusted life years (DALYs) increased by 59.10%, 59.57% and 58.57%, respectively. Whereas the global age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized DALYs rate (ASDR) of MDD decreased during 1990-2019. The ASIR, ASPR and ASDR in women were 1.62, 1.62 and 1.60 times as that in men in 2019, respectively. The highest age-specific incidence, prevalence and DALYs rate occurred at the age of 60-64 in women, and at the age of 75-84 in men, but the maximum increasing trends in these age-specific rates occurred at the age of 5-9. Population living during 2000-2004 had higher risk of MDD. MDD burden varied by socio-demographic index (SDI), regions and nations. In 2019, low-SDI region, Central sub-Saharan Africa and Uganda had the highest ASIR, ASPR and ASDR. The global PAFs of intimate partner violence (IPV), childhood sexual abuse (CSA) and bullying victimization (BV) were 8.43%, 5.46% and 4.86% in 2019, respectively. CONCLUSIONS: Over the past 30 years, the global ASIR, ASPR and ASDR of MDD had decreased trends, while the burden of MDD was still serious, and multiple disparities in MDD burden remarkably existed. Women, elderly and populations living during 2000-2004 and in low-SDI regions, had more severe burden of MDD. Children were more susceptible to MDD. Up to 18.75% of global MDD burden would be eliminated through early preventing against IPV, CSA and BV. Tailored strategies-and-measures in different regions and demographic groups based on findings in this studywould be urgently needed to eliminate the impacts of modifiable risk factors on MDD, and then mitigate the burden of MDD.

Biopsy-free AI-aided precision MRI assessment in prediction of prostate cancer biochemical recurrence.

BACKGROUND: To investigate the predictive ability of high-throughput MRI with deep survival networks for biochemical recurrence (BCR) of prostate cancer (PCa) after prostatectomy. METHODS: Clinical-MRI and histopathologic data of 579 (train/test, 463/116) PCa patients were retrospectively collected. The deep survival network (iBCR-Net) is based on stepwise processing operations, which first built an MRI radiomics signature (RadS) for BCR, and predicted the T3 stage and lymph node metastasis (LN+) of tumour using two predefined AI models. Subsequently, clinical, imaging and histopathological variables were integrated into iBCR-Net for BCR prediction. RESULTS: RadS, derived from 2554 MRI features, was identified as an independent predictor of BCR. Two predefined AI models achieved an accuracy of 82.6% and 78.4% in staging T3 and LN+. The iBCR-Net, when expressed as a presurgical model by integrating RadS, AI-diagnosed T3 stage and PSA, can match a state-of-the-art histopathological model (C-index, 0.81 to 0.83 vs 0.79 to 0.81, p > 0.05); and has maximally 5.16-fold, 12.8-fold, and 2.09-fold (p < 0.05) benefit to conventional D'Amico score, the Cancer of the Prostate Risk Assessment (CAPRA) score and the CAPRA Postsurgical score. CONCLUSIONS: AI-aided iBCR-Net using high-throughput MRI can predict PCa BCR accurately and thus may provide an alternative to the conventional method for PCa risk stratification.

Self-reported critical gaps in the essential knowledge and capacity of spatial epidemiology between the current university education and competency-oriented professional demands in preparing for a future pandemic among public health postgraduates in China: a nationwide cross-sectional survey.

BACKGROUND: Spatial epidemiology plays an important role in public health. Yet, it is unclear whether the current university education in spatial epidemiology in China could meet the competency-oriented professional demands. This study aimed to understand the current situation of education and training, practical application, and potential demands in spatial epidemiology among public health postgraduates in China, and to assess the critical gaps in a future emerging infectious diseases (EID) pandemic preparedness and response. METHODS: This study was divided into three parts. The first part was a comparative study on spatial epidemiology education in international public health postgraduate training. The second part was a cross-sectional survey conducted among public health professionals. The third part was a nationwide cross-sectional survey conducted among public health postgraduates at Chinese universities from October 2020 to February 2021. Data was collected by the WeChat-based questionnaire star survey system and analyzed using the SPSS software. RESULTS: International education institutions had required public health postgraduates to master the essential knowledge and capacity of spatial epidemiology. A total of 198 public health professionals were surveyed, and they had a median of 4.00 (IQR 3.13-4.53) in demand degree of spatial epidemiology. A total of 1354 public health postgraduates were surveyed from 51 universities. Only 29.41% (15/51) of universities offered spatial epidemiology course. Around 8.05% (109/1354) of postgraduates had learned spatial epidemiology, and had a median of 1.05 (IQR 1.00-1.29) in learning degree and a median of 1.91 (IQR 1.05-2.78) in practical application degree of spatial epidemiology. To enhance professional capacity, 65.95% (893/1354) of postgraduates hoped that universities would deliver a credit-course of spatial epidemiology. CONCLUSIONS: A huge unmet education and training demand in spatial epidemiology existed in the current education system of public health postgraduates in China. To enhance the competency-oriented professional capacity in preparedness and response to a future pandemic, it is urgent to incorporate the teaching and training of spatial epidemiology into the compulsory curriculum system of public health postgraduates in China.

Evaluation and development strategy of urban-rural integration under ecological protection in the Yellow River Basin, China.

The problem of imbalanced urban-rural development in China is becoming increasingly serious. Urban-rural integration (URI) is an inevitable way to narrow the urban-rural gap and promote rural development. The Yellow River Basin (YRB) is an important barrier to China's ecological security and plays a crucial role in promoting ecological protection and in high-quality development strategies. Therefore, this article constructs an evaluation index system for URI from five dimensions: economic integration, social integration, ecological integration, element integration, and spatial integration. The simulated annealing-projection pursuit model and time degree are used to analyze the dynamic urban-rural integration level (URIL) of 373 counties from 2000 to 2019. Building upon this foundation, this study classifies four types of URI zones and proposes development strategies tailored to each zone. The results indicate (1) that the URIL in the YRB continues to increase, and that there has been a significant increase in high-level integration areas since 2010. (2) The URIL exhibits a distinct spatial clustering pattern, characterized by lower levels in the upper reaches, and higher levels in the middle and lower reaches. (3) There exists a spatial disparity between economic development and the ecological environment, and it is particularly noticeable in the lower reaches regions. These results contribute to a better understanding of URI in the YRB and provide a reference for the sustainable development of URI in various regions.

Occurrence, source, and risk assessment of neonicotinoid insecticides in the Huai River, China.

Neonicotinoids (NEOs) are the most widely used insecticides in the world. Nevertheless, the occurrence and distribution of NEOs in agricultural areas are not well understood. This study investigated the concentration, sources, ecological risks, and health risks of eight NEOs in the water of the Huai River, which flows through a typical agricultural area in China. The total concentration of NEOs in the river water ranged from 1.02 to 191.2 ng L-1, with an average of 64.1 ng L-1. Thiamethoxam was the dominant compound, with an average relative contribution of 42.5%. The average concentration of the total NEOs in downstream was significantly higher than that in upstream (p < 0.05). This may be related to the intensity of agricultural activities. The riverine NEO fluxes increased by approximately 12 times from the upper site to the lower site. More than 1.3 tons of NEOs in 2022 were transferred into Lake Hongze, the largest regulative lake on the Eastern Route of the South-to-North Water Diversion Project. Nonpoint sources were the major contributor to the total NEO inputs, and water use was the main output pathway. The risk assessment indicated that the individual NEOs in the river water presented low ecological risks. The NEO mixtures would produce chronic risks to aquatic invertebrates in 50% of the sampling sites, which were mostly distributed in downstream. Thus, more attention should be given to the downstream. Based on the Monte Carlo simulation, the health risks of NEOs via water consumption were estimated. The maximum chronic daily intakes were 8.4 × 10-4, 2.25 × 10-4, 1.27 × 10-4, 1.88 × 10-4 mg kg-1 day-1 for boys, girls, men, and women, respectively, which were approximately 2 orders of magnitude lower than the acceptable daily intake. Therefore, river water consumption would not be a concern for the public health.

Green, General and Low-cost Synthesis of Porous Organic Polymers in Sub-kilogram Scale for Catalysis and CO2 Capture.

Porous organic polymers (POPs) with high porosity and tunable functionalities have been widely studied for use in gas separation, catalysis, energy conversion and energy storage. However, the high cost of organic monomers, and the use of toxic solvents and high temperatures during synthesis pose obstacles for large-scale production. Herein, we report the synthesis of imine and aminal-linked POPs using inexpensive diamine and dialdehyde monomers in green solvents. Theoretical calculations and control experiments show that using meta-diamines is crucial for forming aminal linkages and branching porous networks from [2+2] polycondensation reactions. The method demonstrates good generality in that 6 POPs were successfully synthesized from different monomers. Additionally, we scaled up the synthesis in ethanol at room temperature, resulting in the production of POPs in sub-kilogram quantities at a relatively low cost. Proof-of-concept studies demonstrate that the POPs can be used as high-performance sorbents for CO2 separation and as porous substrates for efficient heterogeneous catalysis. This method provides an environmentally friendly and cost-effective approach for large-scale synthesis of various POPs.

A NEW DOSE DETERMINATION METHOD FOR HP(3) AND DP LENS FOR BETA REFERENCE RADIATION QUALITIES.

For the purpose of obtaining the smaller uncertainties for Hp(3) and Dp lens in 90Sr/90Y beta reference fields, a new dose determination method based on the Monte-Carlo simulation was proposed. The conversion coefficients from the absorbed dose in air, at the reference point of the extrapolation ionisation chamber, Dair, det to Hp(3; α) and the conversion factors from Dair, det to Dp lens(α) were calculated with EGSnrc, respectively, for the irradiation angles from 0° to 60°. Compared with the dose determination method in International Organization for Standardization (ISO) 6980 standard, the uncertainty reductions of 7.7-52.8% for Hp(3; α) and 7.9-55.0% for Dp lens(α) were achieved, respectively. In addition, for the conversion coefficients from the reference absorbed dose DR to Hp(3; α), the calculations were performed for more irradiation conditions, which are not included in the current ISO 6980 standard. For the calculations of the conversion factors from DR to Dp lens(α), the eye and head phantoms with Chinese characteristics were utilised, which makes the conversion factors more suitable for use in China.

Optimizing the Synthetic Conditions of "Green" Colloidal AgBiS2 Nanocrystals Using a Low-Cost Sulfur Source.

Colloidal AgBiS2 nanocrystals (NCs) have attracted increasing attention as a near-infrared absorbent materials with non-toxic elements and a high absorption coefficient. In recent years, colloidal AgBiS2 NCs have typically been synthesized via the hot injection method using hexamethyldisilathiane (TMS) as the sulfur source. However, the cost of TMS is one of the biggest obstacles to large-scale synthesis of colloidal AgBiS2 NCs. Herein, we synthesized colloidal AgBiS2 NCs using oleylamine@sulfur (OLA-S) solution as the sulfur source instead of TMS and optimized the synthesis conditions of colloidal AgBiS2 NCs. By controlling the reaction injection temperature and the dosage of OLA-S, colloidal AgBiS2 NCs with adjustable size can be synthesized. Compared with TMS-based colloidal AgBiS2 NCs, the colloidal AgBiS2 NCs based on OLA-S has good crystallinity and fewer defects.

Highly digestible nitrogen-enriched straw upgraded by ozone-urea pretreatment: Digestibility metrics and energy-economic analysis.

Ozone is a powerful oxidative gas widely used as a green pretreatment to enhance the delignification of cereal straws. Urea pretreatment can enrich straws with nitrogen to make them more accessible to anaerobic microorganisms. This study aimed to evaluate the effect of ozone-urea pretreatment on the digestibility of wheat straw (i.e., physicochemical, nitrogen enrichment, gas production, nutritional value, and surface chemistry). The results of ozone-urea pretreatment were compared with non-pretreated, ozone-pretreated, and urea-pretreated samples. This pretreatment method outperformed the other methods in terms of digestibility metrics. The ozone-urea pretreatment resulted in a 50% reduction in lignin, a 4.2 times increase in crude protein, a 22.5% increase in bonded organic-N, a 2 times increase in 24 h-gas production, and a 43.67% increase in total digestible nutrients compared to the non-pretreated sample. Based on the total digestible nutrients index, one-tonne ozone-urea-pretreated straw would be 70.6 USD cheaper than the non-pretreated one.

The severity of portal hypertension by a non-invasive assessment: acoustic structure quantification analysis of liver parenchyma.

BACKGROUND: Acoustic structure quantification (ASQ) has been applied to evaluate liver histologic changes by analyzing the speckle pattern seen on B-mode ultrasound. We aimed to assess the severity of portal hypertension (PHT) through hepatic ultrasonography. METHODS: Sixty patients diagnosed with PHT and underwent surgical treatment with portosystemic shunts were enrolled. Portal pressure (PP) was measured intraoperatively. Patients were divided into subgroups according to the severity of gastroesophageal varices and Child-Pugh class. Three difference ratio (Cm2) values on ASQ histogram mode were analyzed for their relationships with PP, degree of gastroesophageal varices and Child-Pugh liver function. Thirty healthy volunteers matched with the patients for gender and age were enrolled as controls. Comparisons among groups and correlation of the parameters with PP were analyzed. Area under the receive operating characteristic curve was used to evaluate the predicting value of ASQ parameters. RESULTS: In the patients, the ASQ parameters peak Cm2 (Cm2max), mean Cm2 (Cm2mean) and the highest occurred Cm2 value of the obtained red curve (RmaxCm2) were all greatly increased (P < 0.0001, P < 0.0001, P = 0.027). Multiple comparisons indicated that, regardless of Child-Pugh class and degree of gastroesophageal varices, the patients had significantly increased Cm2max and Cm2mean compared with the controls (all P < 0.0001). No differences among subgroups were observed. Cm2max was significantly statistically correlated with PP (r = 0.3505, P < 0.01), degree of varices (r = 0.4998, P < 0.0001). Youden's index for Cm2max with a cut-off value of 140.3 for predicting the presence of PHT, gastroesophageal varices and liver function equal to or worse than Child-Pugh class B were 0.8, 0.91 and 0.84, respectively. CONCLUSIONS: ASQ analysis of ultrasonographic images may have a role in the evaluation of the severity of PHT by detecting liver histologic changes in the speckle pattern caused by cirrhosis.

Deep Data Analysis-Based Agricultural Products Management for Smart Public Healthcare.

Agricultural is an indispensably public healthcare industry for human beings at any time and smart management of it is of great significance. Since substantial technical advance relies on long-term efforts and continuous progress, reasonably scheduling the distribution of agricultural products acts as a key aspect of smart public healthcare. The most intuitive factor affecting the distribution of agricultural products is its dynamic price. Forecasting price fluctuations in advance can optimize the distribution of agricultural products and pave the way to smart public healthcare. Most researchers study the prices of various agricultural products separately, without considering the interaction of different agricultural products in the time dimension. This study introduces a typical deep learning model named graph neural network (GNN) for this purpose and proposes deep data analysis-based agricultural products management for smart public healthcare (named GNN-APM for short). The highlight of GNN-APM is to take latent correlations among multiple types of agricultural products into consideration when modeling evolving rules of price sequences. A case study is set up with the use of real-world data of the agricultural products market. Simulative results reveal that the designed GNN-APM functions well.

Accelerating Monte Carlo Bayesian Prediction via Approximating Predictive Uncertainty Over the Simplex.

Estimating the predictive uncertainty of a Bayesian learning model is critical in various decision-making problems, e.g., reinforcement learning, detecting the adversarial attack, self-driving car. As the model posterior is almost always intractable, most efforts were made on finding an accurate approximation to the true posterior. Even though a decent estimation of the model posterior is obtained, another approximation is required to compute the predictive distribution over the desired output. A common accurate solution is to use Monte Carlo (MC) integration. However, it needs to maintain a large number of samples, and evaluate the model repeatedly, and average multiple model outputs. In many real-world cases, this is computationally prohibitive. In this work, assuming that the exact posterior or a decent approximation is obtained, we propose a generic framework to approximate the output probability distribution induced by the model posterior with a parameterized model and in an amortized fashion. The aim is to approximate the predictive uncertainty of a specific Bayesian model, meanwhile alleviating the heavy workload of MC integration at testing time. The proposed method is universally applicable to Bayesian classification models that allow for posterior sampling. Theoretically, we show that the idea of amortization incurs no additional costs on approximation performance. Empirical results validate the strong practical performance of our approach.

Spatial Threshold Effect of Industrial Land Use Efficiency on Industrial Carbon Emissions: A Case Study in China.

China's industry is still in the middle of industrialization. Land use activities are crucial to the growth of carbon emissions. However, few scholars focus on the influence mechanism between industrial land use efficiency (ILUE) and industrial carbon emissions. In this paper, the threshold model and the spatial Durbin model are used to investigate the spatial threshold effect of industrial land use efficiency on industrial carbon emission from 2003 to 2018. The results show that ILUE of China's provinces basically shows an improvement trend, with little difference in spatial distribution, showing a pattern of high in the eastern region and low in the western region. When economic development level (A) and technical level (T) are taken as the threshold variable, ILUE has a single threshold effect on industrial carbon emissions in the eastern region. In the central region, with a as the threshold variable, ILUE shows a double threshold effect on industrial carbon emission. Under the 0-1 geographical proximity weight matrix, the indirect spillover effect of ILUE on reducing regional carbon emissions is significant, and the indirect effect is even greater than that on regional carbon emissions. The spatial spillover effect is not significant in the eastern region. These findings have important practical significance for promoting regional industrial transformation and upgrading, optimizing land space and realizing high-quality economic development.

A systematic approach to the scale separation problem in the development of multiscale models.

Throughout engineering there are problems where it is required to predict a quantity based on the measurement of another, but where the two quantities possess characteristic variations over vastly different ranges of time and space. Among the many challenges posed by such 'multiscale' problems, that of defining a 'scale' remains poorly addressed. This fundamental problem has led to much confusion in the field of biomedical engineering in particular. The present study proposes a definition of scale based on measurement limitations of existing instruments, available computational power, and on the ranges of time and space over which quantities of interest vary characteristically. The definition is used to construct a multiscale modelling methodology from start to finish, beginning with a description of the system (portion of reality of interest) and ending with an algorithmic orchestration of mathematical models at different scales within the system. The methodology is illustrated for a specific but well-researched problem. The concept of scale and the multiscale modelling approach introduced are shown to be easily adaptable to other closely related problems. Although out of the scope of this paper, we believe that the proposed methodology can be applied widely throughout engineering.

[Clinical effectiveness of Subjective Global Nutritional Assessment in hospitalized children with cerebral palsy].

OBJECTIVE: To investigate the nutritional status of children with cerebral palsy (CP) and the clinical effectiveness of Subjective Global Nutritional Assessment (SGNA) in nutritional assessment of hospitalized children with CP. METHODS: A total of 208 children with CP, aged 1-5 years, who were hospitalized from April to October 2019 were enrolled as subjects. SGNA was used to investigate nutritional status, and the Z-score method recommended by the World Health Organization was used as a reference standard to validate the clinical effectiveness of SGNA. RESULTS: The detection rate of malnutrition in children with CP was 42.3% by SGNA and 39.4% by the Z-score method (P>0.05). The application of SGNA showed high consistency between different evaluators (κ=0.621, P<0.001). With the Z-score method as the reference standard, SGNA had a sensitivity of 80.5%, a specificity of 82.5%, a positive predictive value of 75.0%, and a negative predictive value of 86.7%, and high consistency was observed between the two evaluation methods (κ=0.622, P<0.001). SGNA was moderately consistent with weight-for-age Z-score and height-for-age Z-score (κ=0.495 and 0.478 respectively, P<0.001) and was poorly consistent with weight-for-height Z-score (κ=0.197, P<0.05). CONCLUSIONS: There is a relatively high incidence rate of malnutrition in children with CP. SGNA can be used as a tool to assess the nutritional status of children with CP.

Vancomycin population pharmacokinetics and dosing recommendations in haematologic malignancy with augmented renal clearance children.

WHAT IS KNOWN AND OBJECTIVES: Augmented renal clearance (ARC) is characterized by enhanced renal clearance, which leads to insufficient vancomycin exposure and treatment failure. In haematologic malignancy patients, determination of optimal vancomycin dosage is essential because of high stake of life-threatening bacterial infection and increased clearance. The aim of this study was to describe vancomycin pharmacokinetic parameters in haematologic malignancy with augmented renal clearance children and define the appropriate dosing regimen to achieve an AUC0-24h /MIC ≥400. METHODS: Hematologic malignancy with ARC children was enrolled in this retrospective study. The vancomycin PPK model was established by non-linear mixed-effects modelling programme. Goodness-of-fit (GOF) plots, non-parametric bootstrap, normalized prediction distribution error (NPDE) and visual predictive checks (VPCs) were carried out for internal evaluation of the final model. Monte Carlo simulation method was used to stimulate the optimal dosage regimens. RESULTS: Fifty-three patients with 106 samples were included. A one-compartment model with first-order elimination was developed, and the final model was as follows: CL (L/h) = 6.32×（WT/70）0.75  × e0.0467 ; V(L) = 39.6×(WT/70), where WT denotes weight (kg). The internal validation of the model showed a good prediction performance. Monte Carlo simulation results showed that when MIC was 0.5 mg/L or 1 mg/L, the recommended doses to achieve a target of AUC0-24h /MIC ≥400 were 25 to 40 and 50 to 75 mg/kg/d, respectively. With decreasing weight, the recommended dosage to achieve an AUC0-24h /MIC ≥400 increased. WHAT IS NEW AND CONCLUSION: A one-compartment vancomycin PPK model was established in haematologic malignancy with augmented renal clearance children with weight with allometric scaling as a significant covariate. When MIC was 1 mg/L, current recommended paediatric dosages were insufficient in haematologic malignancy with augmented renal clearance children and should be increased.

Noninvasive stiffness assessment of the human lens nucleus in patients with anisometropia using an ultrasound elastography system.

AIM: To investigate the significance of ultrasound elastography for evaluating stiffness of the human lens nucleus in patients with anisometropia. METHODS: A total of 14 patients (28 eyes) with anisometropia were enrolled. The difference in refractive status between two eyes ≥-4.0 diopters (D) and the difference in axial length (AL) of the eyes was ≥3 mm. There were 5 males and 9 females with an average age of 62±3.3y. The test data of the long AL eye of each patient was included in group A (14 eyes), and test data of the eye with relative short AL was included in group B. Lens nuclear stiffness was measured with free-hand qualitative elastography by independent operators. Strain gray scale and color-coded elastography maps were recorded. In each case, three consecutive measurements were performed and strain ratio was used for statistical analysis. Photograph and sectional view of the lens were analyzed and archived by anterior segment image. RESULTS: In the long AL group, the strain rate in the nucleus of the lens was 0.16%±0.08%; in the short AL group, the strain rate in the nucleus of the lens was 0.54%±0.16%. Independent sample t-test analyses showed that the long AL group lens had a significantly smaller nuclear strain rate than the relatively short AL group, P<0.05. CONCLUSION: The relationship between human lens stiffness and different AL is demonstrated by ultrasound elastography. The long AL is associated with lower strain ratio and less resilience of the lens.

Low-cost multi-core inertial microfluidic centrifuge for high-throughput cell concentration.

We developed a low-cost multi-core inertial microfluidic centrifuge (IM-centrifuge) to achieve a continuous-flow cell/particle concentration at a throughput of up to 20 mL/min. To lower the cost of our IM-centrifuge, we clamped a disposable multilayer film-based inertial microfluidic (MFIM) chip with two reusable plastic housings. The key MFIM chip was fabricated in low-cost materials by stacking different polymer-film channel layers and double-sided tape. To increase processing throughput, multiplexing spiral inertial microfluidic channels were integrated within an all-in-one MFIM chip, and a novel sample distribution strategy was employed to equally distribute the sample into each channel layer. Then, we characterized the focusing performance in the MFIM chip over a wide flow-rate range. The experimental results showed that our IM-centrifuge was able to focus various-sized particles/cells to achieve volume reduction. The sample distribution strategy also effectively ensured identical focusing and concentration performances in different cores. Finally, our IM-centrifuge was successfully applied to concentrate microalgae cells with irregular shapes and highly polydisperse sizes. Thus, our IM-centrifuge holds the potential to be employed as a low-cost, high-throughput centrifuge for disposable use in low-resource settings.

A new low-cost hydroxyapatite for efficient immobilization of lead.

Distiller waste (DW), a common by-product of soda ash plants, was used as the unique calcium source to produce low-cost hydroxyapatites (HAPs) for the first time. The DW-derived HAPs were characterized by SEM, TEM, XRD and BET methods and investigated as amendments for soil Pb immobilization. The DW-derived HAPs displayed relatively smaller particle size (30-80 nm) and larger BET specific surface areas (60.00-64.06 m2/g) compared with two selected commercial HAPs (technical grade HAP and biological reagent HAP designated as HAP-TG and HAP-BR, respectively). The maximum sorption capacity of Pb on the DW-derived HAPs predicted from Langmuir sorption isotherm model was 726-734 mg/g higher than the commercial HAPs and even other well-designed sorbents. TCLP leaching experiments and BCR sequential extraction experiments were conducted to determine the effectiveness of HAP additions on Pb immobilization in soil. A lower addition ratio is required for the DW-derived HAPs than commercial HAPs to reduce Pb leachability to below the harmless level. Meanwhile, the DW-derived HAPs were found to be superior to commercial HAPs in transformation of readily bioavailable forms of Pb to stable speciation in soil, with residual fraction of Pb increased from 6.7% in non-amended soil to 60.7-61.4% in DW-derived HAPs amended soils, 58.3% in HAP-TG amended soil and 42.6% in HAP-BR amended soil, respectively. This study strongly demonstrated the feasibility and low-cost of HAPs derived from the distiller waste for reducing the environmental risks and bioavailability of Pb in soil.

Assessment of diets containing curcumin, epigallocatechin-3-gallate, docosahexaenoic acid and α-lipoic acid on amyloid load and inflammation in a male transgenic mouse model of Alzheimer's disease: Are combinations more effective?

Increasingly, evidence is accumulating pointing at a protective role of a healthy diet at decreasing the risk of Alzheimer's disease. To test the effectiveness of nutritional components, the following food-derived compounds: curcumin alone (curcumin), curcumin combined with (-)epigallocatechin-3-gallate (EGCG), docosahexaenoic acid (DHA) and α-lipoic acid (ALA) (curcumin + EDA), or a combination of EGCG, DHA and ALA (EDA) were assessed in male Tg2576 transgenic mice on amyloid plaque load, amyloid levels (Aß40/Aß42, but not oligomers due to tissue limitations), microglial activation and memory using the contextual and cued fear conditioning test. The combination diet EDA, resulted in the strongest reduction of amyloid plaque load in both the cortical (p < .0001) and hippocampal (p < .0001) areas of the Tg2576 mouse brain, along with lower Aß40/Aß42 levels in the frontal cortex (p = .000129 and p = .000039, respectively) and Aß42 levels in the temporal lobe (p = .000082). A curcumin only diet was shown to lower amyloid plaque load (p = .028), but when combined with EGCG, DHA and ALA did not result in further decreases in amyloid plaque load. The EDA combination group showed the most prominent decrease in microglial activation (number of microglia around plaques: p < .05 and p < .0001, respectively, for the cortex and hippocampus). Analysing the hippocampal associated contextual fear conditioning revealed that both the curcumin+EDA (p < .0001) and EDA groups (p = .001) spent increased time on freezing compared to the control group. In addition, the curcumin+EDA group showed a significant increase in time spent freezing compared with the curcumin only group. In the amygdala associated cued test, all mice demonstrated the ability to associate the conditioned stimulus with the unconditioned stimulus as evidenced by a significant increase in freezing behaviour in response to the presentation of the cue (p < .0001). Post-hoc analysis showed that only curcumin+EDA (p < .0001) and EDA groups (p < .0001) developed a significant increase in freezing during the cue presentation. The results from this study show that the combination of EGCG, DHA and ALA (EDA) appeared to have the most potent anti-inflammatory and neuroprotective effect. Our results also demonstrate that interactions between nutraceutical products might result in counterproductive outcomes, highlighting the fact that manufacturers of nutraceuticals containing multiple compounds should be careful not to claim additive or synergistic effects of their combination products in vivo without having tested it in animal models and/or human clinical trials.