Associations of environmental factors with neurodegeneration: An exposome-wide Mendelian randomization investigation.

Neurodegenerative diseases (NDDs) remain a global health challenge. Previous studies have reported potential links between environmental factors and NDDs, however, findings remain controversial across studies and elusive to be interpreted as evidence of robust causal associations. In this study, we comprehensively explored the causal associations of the common environmental factors with major NDDs including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS), based on updated large-scale genome-wide association study data through two-sample Mendelian randomization (MR) approach. Our results indicated that, overall, 28 significant sets of exposure-outcome causal association evidence were detected, 12 of which were previously underestimated and newly identified, including average weekly beer plus cider intake, strenuous sports or other exercises, diastolic blood pressure, and body fat percentage with AD, alcohol intake frequency with PD, apolipoprotein B, systolic blood pressure, and forced expiratory volume in 1 s (FEV1) with ALS, and alcohol intake frequency, hip circumference, forced vital capacity, and FEV1 with MS. Moreover, the causal effects of several environmental factors on NDDs were found to overlap. From a triangulation perspective, our investigation provided insights into understanding the associations of environmental factors with NDDs, providing causality-oriented evidence to establish the risk profile of NDDs.

Artificial-intelligence-based risk prediction and mechanism discovery for atrial fibrillation using heart beat-to-beat intervals.

BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other complications. Predicting AF risk in advance can improve early diagnostic efficiency. Deep learning has been used for disease risk prediction; however, it lacks adherence to evidence-based medicine standards. Identifying the underlying mechanisms behind disease risk prediction is important and required. METHODS: We developed an explainable deep learning model called HBBI-AI to predict AF risk using only heart beat-to-beat intervals (HBBIs) during sinus rhythm. We proposed a possible AF mechanism based on the model's explainability and verified this conjecture using confirmed AF risk factors while also examining new AF risk factors. Finally, we investigated the changes in clinicians' ability to predict AF risk using only HBBIs before and after learning the model's explainability. FINDINGS: HBBI-AI consistently performed well across large in-house and external public datasets. HBBIs with large changes or extreme stability were critical predictors for increased AF risk, and the underlying cause was autonomic imbalance. We verified various AF risk factors and discovered that autonomic imbalance was associated with all these factors. Finally, cardiologists effectively understood and learned from these findings to improve their abilities in AF risk prediction. CONCLUSIONS: HBBI-AI effectively predicted AF risk using only HBBI information through evaluating autonomic imbalance. Autonomic imbalance may play an important role in many risk factors of AF rather than in a limited number of risk factors. FUNDING: This study was supported in part by the National Key R&D Program and the National Natural Science Foundation of China.

Advantages of diapause in Anastatus japonicus Ashmead mass production on eggs of the Chinese oak silkworm, Antheraea pernyi.

BACKGROUND: Anastatus japonicus Ashmead, a biological control agent utilized in China to control fruit bugs and forest caterpillars, is efficiently raised on large Chinese oak silkworm (Antheraea pernyi) eggs. Here, we investigated the biological parameters of non-diapaused and diapaused Anastatus japonicus after long-term storage within eggs of the host, Antheraea pernyi, under laboratory conditions. RESULTS: Diapaused mature larvae of Anastatus japonicus were more cold-tolerant than non-diapaused mature larvae, as reflected by a lower supercoiling point, lower freezing point, and higher survival rate at cold temperatures. Diapause induction enhanced the lifespan, fecundity and oviposition period of Anastatus japonicus than non-diapaused Anastatus japonicus when refrigerated for 6 months. However, after 12 months of refrigeration, the fecundity and oviposition period of Anastatus japonicus were significantly reduced with and without diapause. No difference in the progeny sex ratio of Anastatus japonicus was observed between diapause-induction treatment and those of non-diapaused. With the extension of refrigeration period from 6 months to 12 months, the lifespan, fecundity and oviposition period of Anastatus japonicus which were treated with diapause induction showed a sharp decrease. No significantly difference in the lifespan, fecundity and oviposition period of Anastatus japonicus was observed between diapause-induction treatment and those of non-diapaused when refrigerated for 12 months. CONCLUSION: These results suggest that the induction of diapause is an applicable technique to achieve mass production of Anastatus japonicus in long-term storage using eggs of the factitious host Antheraea pernyi, without compromising the quality of the parasitoid. The refrigeration period of diapaused Anastatus japonicus should not exceed 6 months. © 2023 Society of Chemical Industry.

Association between behavioural risks and Alzheimer's disease: Elucidated with an integrated analysis of gene expression patterns and molecular mechanisms.

Alzheimer's disease (AD) remains a global health challenge. Previous studies have reported linkages between AD and multiple behavioural risk exposures, however, the underlying biological mechanisms and crucial genes of gene expression patterns driven by behavioural risks on the onset or progression of AD remains ambiguous. In this study, we performed an integrated analysis on the influence of behavioural risks including smoking, excessive alcohol consumption, physical inactivity, and non-healthy dietary pattern on AD with a comprehensive strategy. Our results demonstrated that multiple behavioural risk exposures could independently or collectively influence diverse hierarchical levels of gene expression patterns through multiple biological mechanisms such as Wnt, mitogen-activated protein kinase (MAPK), AMP-activated protein kinase (AMPK), nuclear factor (NF)-κB, phosphatidylinositol 3-kinase (PI3K)-Akt, and insulin (INS) signalling pathways-mediated pathological processes, thereby prodromally or intermediately impacting AD. Our study provided insights into understanding the association of behavioural risk exposures with AD and informative support for further studies.

Bidirectional Semi-Supervised Dual-Branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions.

Semi-supervised learning via teacher-student network can train a model effectively on a few labeled samples. It enables a student model to distill knowledge from the teacher's predictions of extra unlabeled data. However, such knowledge flow is typically unidirectional, having the accuracy vulnerable to the quality of teacher model. In this paper, we seek to robust 3D reconstruction of stereo endoscopic images by proposing a novel fashion of bidirectional learning between two learners, each of which can play both roles of teacher and student concurrently. Specifically, we introduce two self-supervisions, i.e., Adaptive Cross Supervision (ACS) and Adaptive Parallel Supervision (APS), to learn a dual-branch convolutional neural network. The two branches predict two different disparity probability distributions for the same position, and output their expectations as disparity values. The learned knowledge flows across branches along two directions: a cross direction (disparity guides distribution in ACS) and a parallel direction (disparity guides disparity in APS). Moreover, each branch also learns confidences to dynamically refine its provided supervisions. In ACS, the predicted disparity is softened into a unimodal distribution, and the lower the confidence, the smoother the distribution. In APS, the incorrect predictions are suppressed by lowering the weights of those with low confidence. With the adaptive bidirectional learning, the two branches enjoy well-tuned mutual supervisions, and eventually converge on a consistent and more accurate disparity estimation. The experimental results on four public datasets demonstrate our superior accuracy over other state-of-the-arts with a relative decrease of averaged disparity error by at least 9.76%.

Acupuncture Therapy on Dementia: Explained with an Integrated Analysis on Therapeutic Targets and Associated Mechanisms.

BACKGROUND: Dementia, mainly Alzheimer's disease (AD) and vascular dementia (VaD), remains a global health challenge. Previous studies have demonstrated the benefits of acupuncture therapy (AT) in improving dementia. Nevertheless, the therapeutic targets and integrated biological mechanisms involved remain ambiguous. OBJECTIVE: To identify therapeutic targets and biological mechanisms of AT in treating dementia by integrated analysis strategy. METHODS: By the identification of differentially expressed genes (DEGs) of AD, VaD, and molecular targets of AT active components, the acupuncture therapeutic targets associated with the biological response to AD and VaD were extracted. Therapeutic targets-based functional enrichment analysis was conducted, and multiple networks were constructed. AT-therapeutic crucial targets were captured by weighted gene co-expression network analysis (WGCNA). The interactions between crucial targets with AT active components were verified by molecular docking. RESULTS: Our results demonstrated that 132 and 76 acupuncture therapeutic targets were associated with AD and VaD. AT-therapeutic crucial targets including 58 for AD and 24 for VaD were captured by WGCNA, with 11 in shared, including NMU, GRP, TAC1, ADRA1D, and SST. In addition, 35 and 14 signaling pathways were significantly enriched by functional enrichment analysis, with 6 mutual pathways including neuroactive ligand-receptor interaction, GABAergic synapse, calcium signaling pathway, cAMP signaling pathway, chemokine signaling pathway, and inflammatory mediator regulation of TRP channels. CONCLUSION: The improvement of AD and VaD by AT was associated with modulation of synaptic function, immunity, inflammation, and apoptosis. Our study clarified the therapeutic targets of AT on dementia, providing valuable clues for complementing and combining pharmacotherapy.

Association of time spent in outdoor light and genetic risk with the incidence of depression.

Depression is the consequence of both environment and genes working together. Genetic factors increase depression risk, but it is unclear whether this association can be offset by time spent in outdoor light. The study was undertaken to investigate the optimal time spent in outdoor light for lowering the risk of depression and the joint association of time spent in outdoor light and depression genetic risk. In UK Biobank, 380,976 depression-free individuals were included in this study. Polygenic risk score (PRS) was categorized into three groups in terms of tertiles. Time spent in outdoor light on a typical day in summer or winter originated from the questionnaire survey. Depression was defined as hospital admission. The potential dose-response relationship between time spent in outdoor light and depression risk was shown by a restricted cubic spline. Data were analyzed using Cox regressions and Laplace regression. After the median follow-up of 12.6 years, 13,636 individuals suffered from depression in the end. A nonlinear (J-shaped relationship) trend was observed between time spent in outdoor light and depression risk. On average, 1.5 h/day of outdoor light was related to the minimum risk of depression. Individuals below and above this optimal time both had elevated depression risk (below, HR = 1.09, 95% CI: 1.02-1.16; above, HR = 1.13, 95% CI: 1.07-1.20), and the time to incident depression were both shortened by 0.46 years (50th percentile differences [PD] = -0.46, 95% CI: -0.78, -0.14) and 0.63 years (50th PD = -0.63, 95% CI: -0.90, -0.35) years, respectively. In a comparison of individuals with the lowest tertile of PRS and average 1.5 h/day outdoor light, the HRs and 95% CIs of depression were 1.36 (1.21-1.53) and 1.43 (1.29-1.58) in those with the highest tertile of PRS and below/above this reference value, respectively. Significant multiplicative interactions were observed between intermediate genetic risks and longer time spent in outdoor light. We found that an average of 1.5 h/day spent in outdoor light was associated with a lower depression risk whatever the degree of depression genetic predisposition. Moderate time spent in outdoor light may contribute to a decreased depression risk even among people with a higher genetic risk of depression.

Cardiometabolic diseases, polygenic risk score, APOE genotype, and risk of incident dementia: A population-based prospective cohort study.

Objective We aimed to prospective investigate the association between cardiometabolic diseases (CMDs) with dementia, and to examine whether genetic factors and CMDs jointly contribute to the incidence of dementia. Methods We used data from the UK biobank of 204,646 adults aged 37-73 free of dementia at baseline. Genetic risk for dementia including APOE ε4 status and polygenic risk score (PRS) categorized as low, intermediate, and high. CMDs including ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D) were confirmed by touchscreen questionnaires, medical examinations, and hospital inpatient records. Results Over the follow-up (median: 12.5 years), 5,750 participants developed dementia. The HRs (95% CI) of those with APOE ε4 carriers and high PRS were 3.16 (3.00-3.33) and 1.50 (1.41-1.60), respectively. The risk of dementia was 70% higher among those with CMDs (HR: 1.70; 95% CI: 1.60-1.82). In joint effect analyses, compared to no CMDs and APOE ε4 non-carriers, the HRs (95% CIs) of dementia were 3.53 (3.31-3.76)/2.06 (1.89-2.23) in participants with only APOE ε4 carriers and CMDs, and 5.06 (4.64-5.53) for those with APOE ε4 carriers plus CMDs. Compared to no CMDs and low PRS, the HRs (95% CIs) of dementia were 1.29 (1.19-1.40)/1.60 (1.48-1.73) in participants with only intermediate and high PRS, and 2.00 (1.79-2.23)/2.63 (2.38-2.92) for those with intermediate, and high PRS plus CMDs. Moreover, there were significant additive and multiplication interactions between CMDs and APOE ε4 carriers of dementia, but only multiplication interaction was observed for PRS. Conclusions CMDs were associated with higher risk of dementia regardless of genetic risk for dementia.

Visible light sensing based on shadow features using multi-scale region convolutional neural network.

There are various production items in the industrial internet of things (IIoT) environment, such as pedestrians, robots, automated automated guided vehicles, etc. The practice industrial environment requires simultaneous communication and sensing of production items to achieve intelligent production and control. Thus, sensing methods not only require the integration of communication but also achieve sensing tasks such as recognition and positioning. Compared with traditional sensing media, visible light sensing has the advantages of high-speed communication, high sensing accuracy, and security, low energy consumption, and has become a potential sensing technology. Based on the strong directivity of visible light spatial radiation and the consistency of light intensity and position, this paper proposes a multi-scale visible light sensing-region convolutional neural network (VLS-RCNN) framework based on shadow features for multiple target sensing. The framework enables the recognition and positioning to use shared visible light shadow features to assist each other, and the multi-scale compensation strategy of the shadow region makes the framework more robust. The simulation results show that positioning results in the sensing area improve the recognition accuracy. The recognition results also reduce the positioning error without additional overhead. Therefore, this paper provides a new perspective for the sensing technology in the future IIoT, which should be considered to sense objects of interest by utilizing the inherent characteristics of visible light.

Association of impaired lung function with dementia, and brain magnetic resonance imaging indices: a large population-based longitudinal study.

OBJECTIVE: to examine the association between different patterns of impaired lung function with the incident risk of dementia and magnetic resonance imaging (MRI)-based brain structural features. METHODS: in UK Biobank, a total of 308,534 dementia-free participants with valid lung function measures (forced expiratory volume in 1 s [FEV1] and forced vital capacity [FVC]) were included. Association was assessed using Cox proportional hazards regression model. Furthermore, the association between impaired lung function and brain MRI biomarkers related to cognitive function was analysed among 30,159 participants. RESULTS: during a median follow-up of 12.6 years, 3,607 incident all-cause dementia cases were recorded. Restrictive impairment (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.27-1.60) and obstructive impairment (HR, 1.28; 95% CI, 1.15-1.42) were associated with higher risk of all-cause dementia. The restricted cubic splines indicated FEV1% predicted and FVC % predicted had reversed J-shaped associations with dementia. Participants with impaired lung function have higher risks of all-cause dementia across all apolipoprotein E (APOE) risk categories, whereas associations were stronger among those of low APOE risk (P for interaction = 0.034). In addition, restrictive and obstructive impairment were linked to lower total (ß: -0.075, SE: 0.021, Pfdr = 0.002; ß: -0.033, SE: 0.017, Pfdr = 0.069) and frontoparietal grey matter volumes, higher white matter hyperintensity, poorer white matter integrity, lower hippocampus (ß: -0.066, SE: 0.024, Pfdr = 0.017; ß: -0.051, SE: 0.019, Pfdr = 0.019) and other subcortical volumes. CONCLUSIONS: participants with restrictive and obstructive impairments had a higher risk of dementia. Brain MRI indices further supported adverse effects and provided insight into potential pathophysiology biomarkers.

Reproductive attributes and functional response of Anastatus japonicus on eggs of Antheraea pernyi, a factitious host.

BACKGROUND: Anastatus japonicus Ashmead (Hymenoptera: Eupelmidae) is a solitary egg endoparasitoid that has been studied for inundative biological control of Halyomorpha halys Stål (Hemiptera: Pentatomidae) in China. In this study, we assessed the reproductive attributes and functional response of Anastatus japonicus on a factitious host, Antheraea pernyi (Guérin-Méneville) (Lepidoptera: Anthelidae) at 25 ± 1 °C, 70 ± 5% relative humidity and 16 h:8 h light/dark photoperiod. RESULTS: The mean lifetime fecundity of Anastatus japonicus females was 404.3 progeny produced over an average oviposition period of 42.3 days. The sex ratio of adult progeny was slightly male biased (51.2%), whereas more female progeny were produced before day 20 of a female's life. Single 1-day-old mated Anastatus japonicus females exhibited a type II functional response to increasing host densities (1-50 eggs), with an inverse host density-dependent pattern of percent parasitism. The upper limit to the daily attack rate was estimated as 7.6 Antheraea pernyi eggs. Furthermore, mutual interference among Anastatus japonicus females occurred when increasing densities of parasitoids (1, 2, 4, 8, 16) were exposed to 30 host eggs. CONCLUSION: Laboratory functional response result revealed that individual Anastatus japonicus might be unable to respond effectively to increasing host density in the field, which could be compensated by releasing larger numbers of wasps. Strong mutual interference among foraging Anastatus japonicus females should be considered in any future inundative biological control programs for the sustainable management of Halyomorpha halys or other host insect pests. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Blockchain for federated learning toward secure distributed machine learning systems: a systemic survey.

Federated learning (FL) is a promising decentralized deep learning technology, which allows users to update models cooperatively without sharing their data. FL is reshaping existing industry paradigms for mathematical modeling and analysis, enabling an increasing number of industries to build privacy-preserving, secure distributed machine learning models. However, the inherent characteristics of FL have led to problems such as privacy protection, communication cost, systems heterogeneity, and unreliability model upload in actual operation. Interestingly, the integration with Blockchain technology provides an opportunity to further improve the FL security and performance, besides increasing its scope of applications. Therefore, we denote this integration of Blockchain and FL as the Blockchain-based federated learning (BCFL) framework. This paper introduces an in-depth survey of BCFL and discusses the insights of such a new paradigm. In particular, we first briefly introduce the FL technology and discuss the challenges faced by such technology. Then, we summarize the Blockchain ecosystem. Next, we highlight the structural design and platform of BCFL. Furthermore, we present the attempts ins improving FL performance with Blockchain and several combined applications of incentive mechanisms in FL. Finally, we summarize the industrial application scenarios of BCFL.

Accurate Cobb Angle Estimation on Scoliosis X-ray Images via Deeply-coupled Two-stage Network with Differentiable Cropping and Random Perturbation.

Automated Cobb angle estimation on X-ray images is crucial to scoliosis diagnosis. The existing efforts are typically two extremes, which either laboriously detect the raw vertebral landmarks or directly regress Cobb angles from the entire image. In this paper, we propose a novel two-stage end-to-end method as a balanced solution, to avoid vulnerability to false landmarks, and to preserve flexibility in clinical usages. Concretely, we cascade two stages sequentially for detecting vertebrae and then regressing their bending directions instead of raw landmarks. In the detection stage, we combine two networks called LocNet and SegNet to robustly localize vertebrae, and meanwhile to suppress the false positives by additionally segmenting the whole spine. In the subsequent stage, we introduce a regression network named RegNet to accurately regress bending directions of localized vertebrae. Furthermore, the vertebra-aligned local regions on LocNet's intermediate features are cropped via RoIAlign-pooling, and RegNet inherits the cropped regions to learn only feature residuals. By doing so, the regression difficulty can be dramatically alleviated, and the two stages are deeply coupled and mutually guided in an end-to-end training. Moreover, a random perturbation on the inherited features further enhances RegNet's robustness. We benchmark our method on both public and private datasets, and the errors are 2.92 ±2.34 degree and 6.87 ±6.26% in terms of CMAE and SMAPE on the widely-employed AASCE dataset, outperforming other state-of-the-arts by at least 16.81% and 6.15%, respectively. Also, a clinical user study verifies our promising flexibility for allowing convenient rectifications to further decrease errors by a large marge.

DLST-dependence dictates metabolic heterogeneity in TCA-cycle usage among triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is traditionally considered a glycolytic tumor with a poor prognosis while lacking targeted therapies. Here we show that high expression of dihydrolipoamide S-succinyltransferase (DLST), a tricarboxylic acid (TCA) cycle enzyme, predicts poor overall and recurrence-free survival among TNBC patients. DLST depletion suppresses growth and induces death in subsets of human TNBC cell lines, which are capable of utilizing glutamine anaplerosis. Metabolomics profiling reveals significant changes in the TCA cycle and reactive oxygen species (ROS) related pathways for sensitive but not resistant TNBC cells. Consequently, DLST depletion in sensitive TNBC cells increases ROS levels while N-acetyl-L-cysteine partially rescues cell growth. Importantly, suppression of the TCA cycle through DLST depletion or CPI-613, a drug currently in clinical trials for treating other cancers, decreases the burden and invasion of these TNBC. Together, our data demonstrate differential TCA-cycle usage in TNBC and provide therapeutic implications for the DLST-dependent subsets.

Ability of Spalangia endius (Hymenoptera: Pteromalidae) to Parasitize Bactrocera dorsalis (Diptera: Tephritidae) after Switching Hosts.

We studied the parasitism capacity of Spalangia endius as a pupal parasite of Bactocera dorsalis after switching hosts. We used pupae of B. dorsalis and M. domestica as the hosts and studied parasitism by S. endius in the laboratory. The parasitism capacities were compared at different host densities and different parasitoid ages. The two functional responses of S. endius fitted a Holling Type II equation. More M. domestica were parasitized than B. dorsalis at all the densities. The ability of S. endius to control M. domestica was α/Th (parasitism capacity) = 32.1950, which was much stronger than that of control B. dorsalis, which was α/Th = 4.7380. The parasitism rate of wasps that had parasitized B. dorsalis had decreased by the emergence time of parasitoids. These results suggest that the parasitoid-pest ratio should be 1:25 to maintain a relatively stable parasitism rate for control of B. dorsalis. The S. endius colony reared on M. domestica successfully controlled a low-density population of B. dorsalis in the lab. We provide evidence suggesting that the parasitism capacity of S. endius needs to be improved.

Behavioral response of Panonychus citri (McGregor) (Acari: Tetranychidae) to synthetic chemicals and oils.

BACKGROUND: Panonychus citri (McGregor) (Acari: Tetranychidae) population outbreaks after the citrus plantation's chemical application is a common observation. Dispersal behavior is an essential tool to understand the secondary outbreak of P. citri population. Therefore, in the current study, the dispersal activity of P. citri was observed on the leaf surfaces of Citrus reticulata (Rutaceae) treated with SYP-9625, abamectin, vegetable oil, and EnSpray 99. METHOD: Mites were released on the first (apex) leaf of the plant (adaxial surface) and data were recorded after 24 h. The treated, untreated, and half-treated data were analyzed by combining the leaf surfaces (adaxial right, adaxial left, abaxial right, and abaxial left). All experiments were performed in open-air environmental conditions. RESULTS: The maximum number of mites was captured on the un-treated or half-treated surfaces due to chemicals repellency. Chemical bioassays of the free-choice test showed that all treatments significantly increased the mortality of P. citri depending on application method and concentration. A significant number of mites repelled away from treated surfaces and within treated surfaces except adaxial left and abaxial right surfaces at LC30. In the no-choice test, SYP-9625 gave maximum mortality and dispersal by oils than others. No significant differences were observed within the adaxial and abaxial except abaxial surface at LC30. Therefore, the presence of tested acaricides interferes with P. citri dispersal within leaf surfaces of plantations depending on the mites released point and a preferred site for feeding.

Roles of Ion-Exchangeable Sodium in the Conversion Process of Tar to Soot during Rapid Pyrolysis of Two Brown Coals in a Drop-Tube Reactor.

In this work, two series of brown coals (including acid-washed coal and ion-exchangeable Na-loaded coal) were pyrolyzed in a drop-tube reactor. The experimental results revealed that soot and tar yields of Na-loaded coals were significantly lower than that of acid-washed coals. Gasified Na can reduce the formation of big soot agglomerates. During coal primary pyrolysis, ion-exchangeable Na can reduce the amount and aromaticity of primary tar. Na released with volatiles can catalyze the cracking of aliphatic and aromatic compounds, inhibit the polymerization between aromatic rings, and promote the combination of soot/tar with oxygen-containing substances, resulting in the decrease of graphite crystallite size and the increase of amorphous carbon content. Na can also reduce the organization degree of soot by forming intercalation compounds.

Gasification and catalytic reforming of corn straw in closed-loop reactor.

A closed-loop gasification and catalytic reforming apparatus was applied for producing syngas from corn straw with upgraded syngas quality. Four nickel based catalysts at 10% and that at 5-15% loadings on γ-A12O3 were synthesized and tested. Effects of reforming temperature (700-900 °C), steam to biomass ratio (S/B, 0.5-2.5), catalyst to biomass ratio (C/B, 0.2-0.6) on the syngas quality and the carbon conversion and gasification efficiency were investigated. Incorporation of reforming reaction with 10% Ni/γ-A12O3 catalyst leads to the highest CO content (50.2%) and lowest CO2 content (7.5%) amongst the four tested catalysts and amongst the Ni/γ-A12O3 catalysts at different Ni loading. The syngas was upgraded by both the decoking reaction in the pyrolytic chamber and the steam reforming and water shift reactions in the reforming chamber.

Integrated gasification and catalytic reforming syngas production from corn straw with mitigated greenhouse gas emission potential.

The syngas that is produced from waste biomass often has high levels of CH4 and CO2, which are greenhouse gases. This investigation presents an integrated gasification and catalytic reforming process with a closed gas loop that can improve quality of syngas from corn straw and mitigate CH4 and CO2 emission. The effects of the support type, reforming temperature, steam-to-biomass (S/B) ratio, and catalyst-to-biomass ratio (C/B) ratio on gas yield and composition were experimentally examined with waste corn straw as the feedstock gasified at 850 °C in the proposed closed-loop apparatus. Reformation of syngas using Ni/γ-Al2O3 at 850 °C, S/B = 1 and C/B = 0.5 yielded 1.16 m3/kg of syngas, which contained 48.5% H2, 33.9% CO, 12.2% CO2 and 5.3% CH4, corresponding to 71.0% and 81.5% enhancements of the first two and -77.8% and -58.1% reductions of the last two components.