[An ensemble model for assisting early Alzheimer's disease diagnosis based on structural magnetic resonance imaging with dual-time-point fusion].

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder. Due to the subtlety of symptoms in the early stages of AD, rapid and accurate clinical diagnosis is challenging, leading to a high rate of misdiagnosis. Current research on early diagnosis of AD has not sufficiently focused on tracking the progression of the disease over an extended period in subjects. To address this issue, this paper proposes an ensemble model for assisting early diagnosis of AD that combines structural magnetic resonance imaging (sMRI) data from two time points with clinical information. The model employs a three-dimensional convolutional neural network (3DCNN) and twin neural network modules to extract features from the sMRI data of subjects at two time points, while a multi-layer perceptron (MLP) is used to model the clinical information of the subjects. The objective is to extract AD-related features from the multi-modal data of the subjects as much as possible, thereby enhancing the diagnostic performance of the ensemble model. Experimental results show that based on this model, the classification accuracy rate is 89% for differentiating AD patients from normal controls (NC), 88% for differentiating mild cognitive impairment converting to AD (MCIc) from NC, and 69% for distinguishing non-converting mild cognitive impairment (MCInc) from MCIc, confirming the effectiveness and efficiency of the proposed method for early diagnosis of AD, as well as its potential to play a supportive role in the clinical diagnosis of early Alzheimer's disease.

Ecofriendly Solution Processing of Perovskite Solar Cells Using Water.

Perovskite solar cells (PSCs) represent a promising avenue for producing cost-effective solar energy by harnessing sunlight, but challenges persist in their solution processing, which uses a large amount of organic solvent for existing PSC technology. The use of water as a solvent offers an environmentally friendly alternative to traditional solvents, aligning with the global drive for sustainable renewable energy technologies. This Perspective provides an overview of research in the area of PSC fabrication using water as a solvent, highlighting key advancements in the synthesis process. We delve into the kinetics of crystallization and the physical-chemical transformations of perovskite materials in water-based solution processing. Key challenges of the scalability of water-based solution processing for PSC fabrication are discussed. The Perspective sheds light on the broader potential for enhancing the ecofriendliness of perovskite solar cell technologies.

Advanced Materials for NH3 Capture: Interaction Sites and Transport Pathways.

Ammonia (NH3) is a carbon-free, hydrogen-rich chemical related to global food safety, clean energy, and environmental protection. As an essential technology for meeting the requirements raised by such issues, NH3 capture has been intensively explored by researchers in both fundamental and applied fields. The four typical methods used are (1) solvent absorption by ionic liquids and their derivatives, (2) adsorption by porous solids, (3) ab-adsorption by porous liquids, and (4) membrane separation. Rooted in the development of advanced materials for NH3 capture, we conducted a coherent review of the design of different materials, mainly in the past 5 years, their interactions with NH3 molecules and construction of transport pathways, as well as the structure-property relationship, with specific examples discussed. Finally, the challenges in current research and future worthwhile directions for NH3 capture materials are proposed.

Boosting the degradation of antibiotics via peroxymonosulfate activation with a Cu-based metal-organic framework.

Highly efficient degradation of antibiotics is a huge challenge due to the extremely stable molecules and the potential for biological resistance. However, conventional degradation methods are limited to lower degradation rate, higher energy consumption and secondary pollution. Herein, we report a new Cu-based metal-organic framework (MOF), featuring classical planar trinuclear [Cu3(µ3-O)]4+ clusters within the pores. The presence of the rich open metal sites and the large pore ratio, as well as the high catalytic activity of Cu2+ ions, are conducive to boosting the degradation of various antibiotics (>95%) under the activation of peroxymonosulfate. Remarkably, this is the first MOF to achieve such exceptional catalytic performance under neutral and even alkaline conditions, which exceeds those of most reported materials. Mechanism investigation demonstrates that multiple active species were produced and promoted the degradation synergistically during the advanced oxidation processes.

A novel nanobody broadly neutralizes SARS-CoV-2 via induction of spike trimer dimers conformation.

The ongoing mutations of the SARS-CoV-2 pose serious challenges to the efficacy of the available antiviral drugs, and new drugs with fantastic efficacy are always deserved investigation. Here, a nanobody called IBT-CoV144 is reported, which exhibits broad neutralizing activity against SARS-CoV-2 by inducing the conformation of spike trimer dimers. IBT-CoV144 was isolated from an immunized alpaca using the RBD of wild-type SARS-CoV-2, and it showed strong cross-reactive binding and neutralizing potency against diverse SARS-CoV-2 variants, including Omicron subvariants. Moreover, the prophylactically and therapeutically intranasal administration of IBT-CoV144 confers fantastic protective efficacy against the challenge of Omicron BA.1 variant in BALB/c mice model. The structure analysis of the complex between spike (S) protein, conducted using Cryo-EM, revealed a special conformation known as the trimer dimers. This conformation is formed by two trimers, with six RBDs in the "up" state and bound by six VHHs. IBT-CoV144 binds to the lateral region of the RBD on the S protein, facilitating the aggregation of S proteins. This aggregation results in steric hindrance, which disrupts the recognition of the virus by ACE2 on host cells. The discovery of IBT-CoV144 will provide valuable insights for the development of advanced therapeutics and the design of next-generation vaccines.

REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data.

MOTIVATION: Profiling of gene expression and chromatin accessibility by single-cell multi-omics approaches can help to systematically decipher how transcription factors (TFs) regulate target gene expression via cis-region interactions. However, integrating information from different modalities to discover regulatory associations is challenging, in part because motif scanning approaches miss many likely TF binding sites. RESULTS: We develop REUNION, a framework for predicting genome-wide TF binding and cis-region-TF-gene "triplet" regulatory associations using single-cell multi-omics data. The first component of REUNION, Unify, utilizes information theory-inspired complementary score functions that incorporate TF expression, chromatin accessibility, and target gene expression to identify regulatory associations. The second component, Rediscover, takes Unify estimates as input for pseudo semi-supervised learning to predict TF binding in accessible genomic regions that may or may not include detected TF motifs. Rediscover leverages latent chromatin accessibility and sequence feature spaces of the genomic regions, without requiring chromatin immunoprecipitation data for model training. Applied to peripheral blood mononuclear cell data, REUNION outperforms alternative methods in TF binding prediction on average performance. In particular, it recovers missing region-TF associations from regions lacking detected motifs, which circumvents the reliance on motif scanning and facilitates discovery of novel associations involving potential co-binding transcriptional regulators. Newly identified region-TF associations, even in regions lacking a detected motif, improve the prediction of target gene expression in regulatory triplets, and are thus likely to genuinely participate in the regulation. AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/yangymargaret/REUNION.

Unraveling the Mechanistic Origin of High N2 Selectivity in Ammonia Selective Catalytic Oxidation on CuO-Based Catalyst.

NH3 emissions from industrial sources and possibly future energy production constitute a threat to human health because of their toxicity and participation in PM2.5 formation. Ammonia selective catalytic oxidation to N2 (NH3-SCO) is a promising route for NH3 emission control, but the mechanistic origin of achieving high N2 selectivity remains elusive. Here we constructed a highly N2-selective CuO/TiO2 catalyst and proposed a CuOx dimer active site based on the observation of a quadratic dependence of NH3-SCO reaction rate on CuOx loading, ac-STEM, and ab initio thermodynamic analysis. Combining this with the identification of a critical N2H4 intermediate by in situ DRIFTS characterization, a comprehensive N2H4-mediated reaction pathway was proposed by DFT calculations. The high N2 selectivity originated from the preference for NH2 coupling to generate N2H4 over NH2 dehydrogenation on the CuOx dimer active site. This work could pave the way for the rational design of efficient NH3-SCO catalysts.

Are there any differences in the quality of high-mountain green tea before and after the first new leaves unfold? A comprehensive study based on E-sensors, whole metabolomics and sensory evaluation.

High-mountain green tea, where the first new leaf hasn't yet unfurled, is prized for perceived superior quality, but this hasn't yet been verified by experimentation. Electronic sensors, whole metabolomics and sensory evaluation were employed to assess the quality of yymj (tea buds with a newly unfurled leaf) and qymj (tea buds without new leaves). The qymj proved to have significant advantages in aroma, color and shape, but still had some shortcomings in umami, bitterness and sourness. Differences in the content of volatile organic compounds (including alcohols, hydrocarbons and lipids) and nonvolatile organic compounds (flavonoids, amino acids, sugars, and phenolic acids) quality of high-mountain green teas with different maturity levels and provides well explained these quality differences. This study establishes a systematic approach to study the quality of high-mountain green tea at different maturity levels, and provides important reference information for consumers, governments and tea farmers.

Near-Infrared Light-Activatable DNA Tentacles for Efficient Inhibition of Tumor Metastasis by Bio-Orthogonal Cell Assembly.

Tumor metastasis remains a major challenge in cancer management. Among various treatment strategies, immune cell-based cancer therapy holds a great potential for inhibiting metastasis. However, its wide application in cancer therapy is restricted by complex preparations, as well as inadequate homing and controllability. Herein, we present a groundbreaking approach for bioorthogonally manipulating tumor-NK (natural killer) cell assembly to inhibit tumor metastasis. Multiple dibenzocyclootyne (DBCO) groups decorated long single-stranded DNA were tail-modified on core-shell upconversion nanoparticles (CSUCNPs) and condensed by photosensitive chemical linker (PC-Linker) DNA to shield most of the DBCO groups. On the one hand, the light-triggered DNA scaffolds formed a cross-linked network by click chemistry, effectively impeding tumor cell migration. On the other hand, the efficient cellular assembly facilitated the effective communication between tumor cells and NK-92 cells, leading to enhanced immune response against tumors and further suppression of tumor metastasis. These features make our strategy highly applicable to a wide range of metastatic cancers.

Data imbalance in cardiac health diagnostics using CECG-GAN.

Heart disease is the world's leading cause of death. Diagnostic models based on electrocardiograms (ECGs) are often limited by the scarcity of high-quality data and issues of data imbalance. To address these challenges, we propose a conditional generative adversarial network (CECG-GAN). This strategy enables the generation of samples that closely approximate the distribution of ECG data. Additionally, CECG-GAN addresses waveform jitter, slow processing speeds, and dataset imbalance issues through the integration of a transformer architecture. We evaluated this approach using two datasets: MIT-BIH and CSPC2020. The experimental results demonstrate that CECG-GAN achieves outstanding performance metrics. Notably, the percentage root mean square difference (PRD) reached 55.048, indicating a high degree of similarity between generated and actual ECG waveforms. Additionally, the Fréchet distance (FD) was approximately 1.139, the root mean square error (RMSE) registered at 0.232, and the mean absolute error (MAE) was recorded at 0.166.

Prognostic implication and immunotherapy response prediction of a novel ubiquitination-related gene signature in liver cancer.

HCC, also known as hepatocellular carcinoma, is a frequently occurring form of cancer with an unfavorable prognosis. This research constructed a prognostic signature related to ubiquitination and investigated its correlation with the response to immunotherapy in HCC. The Molecular Signatures Database provided a compilation of genes associated with ubiquitination. A gene signature related to ubiquitination was obtained through Cox regression using the Least Absolute Shrinkage and Selection Operator method. The genetic factors CPY26B1, MCM10, SPINK4, and TRIM54 notably impacted the outcomes of HCC. The patients were divided into two groups: one group had a high risk of poor survival while the other had a low risk but a greater chance of controlling HCC progression. Both univariate and multivariate analyses using Cox regression found the risk score to be an independent predictor of HCC prognosis. Gene set enrichment analysis (GSEA) indicated enrichment in cell cycle and cancer-related microRNAs in high-risk groups. The tumor microenvironment (TME), response to immunotherapy, and effectiveness of chemotherapy medications positively correlated with the risk score. In the high-risk group, erlotinib showed higher IC50 values compared to the low-risk group which exhibited higher IC50 values for VX-11e, AKT inhibitor VIII, AT-7519, BMS345541, Bortezomib, CP466722, FMK, and JNK-9L. The results of RT-qPCR revealed that the expression of four UEGs was higher in tumor tissue as compared to normal tissue. Based on the genes that were expressed differently and associated with ubiquitination-related tumor categorization, we have developed a pattern of four genes and a strong nomogram that can predict the prognosis of HCC, which could be useful in identifying and managing HCC.

Repeated Omicron infection dampens immune imprinting from previous vaccination and induces broad neutralizing antibodies against Omicron sub-variants.

OBJECTIVE: Similar with influenza virus, antigenic drift is highly relevant to SARS-CoV-2 evolution, and immune imprinting has been found to limit the performance of updated vaccines based on the emerging variants of SARS-CoV-2. We aimed to investigate whether repeated exposure to Omicron variant could reduce the immune imprinting from previous vaccination. METHODS: A total of 194 participants with different status of vaccination (unvaccinated, regular vaccination and booster vaccination) confirmed for first infection and re-infection with BA.5, BF.7 and XBB variants were enrolled, and the neutralizing profiles against wild type (WT) SARS-CoV-2 and Omicron sub-variants were analyzed. RESULTS: Neutralizing potency against the corresponding infected variant is significantly hampered along with the doses of vaccination during first infection. However, for the participants with first infection of BA.5/BF.7 variants and re-infection of XBB variant, immune imprinting was obviously alleviated, indicated as significantly increased ratio of the corresponding infected variant/WT ID50 titers and higher percentage of samples with high neutralizing activities (ID50 > 500) against BA.5, BF.7 and XBB variants. Moreover, repeated Omicron infection could induce strong neutralizing potency with broad neutralizing profiles against a series of other Omicron sub-variants, both in the vaccine naive and vaccine experienced individuals. CONCLUSIONS: Our results demonstrate that repeated Omicron infection dampens immune imprinting from vaccination with WT SARS-CoV-2 and induces broad neutralizing profiles against Omicron sub-variants.

Identified γ-glutamyl cyclotransferase (GGCT) as a novel regulator in the progression and immunotherapy of pancreatic ductal adenocarcinoma through multi-omics analysis and experiments.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its challenging early diagnosis, high malignancy, and resistance to chemotherapy drugs, the treatment of pancreatic cancer has long been exceedingly difficult in the realm of oncology. γ-Glutamyl cyclotransferase (GGCT), a vital enzyme in glutathione metabolism, has been implicated in the proliferation and progression of several tumor types, while the biological function of GGCT in pancreatic ductal adenocarcinoma remains unknown. METHODS: The expression profile of GGCT was validated through western blotting, immunohistochemistry, and RT-qPCR in both pancreatic cancer tissue samples and cell lines. Functional enrichment analyses including GSVA, ssGSEA, GO, and KEGG were conducted to explore the biological role of GGCT. Additionally, CCK8, Edu, colony formation, migration, and invasion assays were employed to evaluate the impact of GGCT on the proliferation and migration abilities of pancreatic cancer cells. Furthermore, the LASSO machine learning algorithm was utilized to develop a prognostic model associated with GGCT. RESULTS: Our study revealed heightened expression of GGCT in pancreatic cancer tissues and cells, suggesting an association with poorer patient prognosis. Additionally, we explored the immunomodulatory effects of GGCT in both pan-cancer and pancreatic cancer contexts, found that GGCT may be associated with immunosuppressive regulation in various types of tumors. Specifically, in patients with high expression of GGCT in pancreatic cancer, there is a reduction in the infiltration of various immune cells, leading to poorer responsiveness to immunotherapy and worse survival rates. In vivo and in vitro assays indicate that downregulation of GGCT markedly suppresses the proliferation and metastasis of pancreatic cancer cells. Moreover, this inhibitory effect appears to be linked to the regulation of GGCT on c-Myc. A prognostic model was constructed based on genes derived from GGCT, demonstrating robust predictive ability for favorable survival prognosis and response to immunotherapy.

The realization logic of rural revitalization: Coupled coordination analysis of development and governance.

BACKGROUND: Socialism with Chinese characteristics has entered a new stage. The principal social contradiction is the uneven development of urban and rural areas. The rural revitalization strategy has emerged as time has required. The realization of rural revitalization not only requires development to lay the foundation of the countryside but also requires governance to lead the development of the countryside. Development and governance are two indispensable aspects of rural revitalization. However, China's rural areas have long been in a state of development without governance, and this situation must change. Therefore, systematically exploring the relationship between development and governance is the key to solving the current shortcomings in rural areas. METHODS: Based on the data from the statistical yearbook, the study constructed a set of evaluation indicators for rural development governance and revitalization and verified the model's effectiveness.The entropy method and the assessment model were used to calculate the comprehensive score of rural development, governance, and revitalization. The relationship between rural development and governance was analyzed using a coupled coordination model. The regression analysis model was used to explore the relationship between the coupling results of rural development, governance, and rural revitalization. RESULTS: From the comprehensive results, both development and governance show an upward trend, but the upward trend of development is better. From the analysis of coupling coordination between development and governance, the C value is in good condition, the T value fluctuates wildly, and the D fluctuates with the fluctuation of T. Judging from the comprehensive score of rural revitalization, it also shows an upward trend year by year. Judging from the regression analysis results of coupling coordination degree and rural revitalization comprehensive score, coupling coordination degree will significantly impact the rural revitalization evaluation value. CONCLUSIONS: The study found that current rural development and governance present a spiral coupling coordination relationship, and the degree of coupling coordination significantly correlates with rural revitalization. Based on the research conclusions, the study further proposes three paths to promote the coupling and coordination of development and governance. The first is an organizational isomorphism, which builds a coupled coordination system for rural development and governance. The second is to tilt resources and improve the supply of connected and coordinated factors for rural development and governance. The third is the operating mechanism to optimize rural development and governance's coupling and coordination path.

Pan-cancer analysis of PSCA that is associated with immune infiltration and affects patient prognosis.

Prostate stem cell antigen (PSCA) is associated with disease progression, promotion of angiogenesis, invasion, metastasis and immune evasion in cancer. However, its expression pattern and diagnostic and prognostic potential have not been thoroughly analysed from a pan-cancer perspective. This study aimed to examine the effects of PSCA on the prognosis and inflammatory cell infiltration patterns of various cancer types. We analysed the relationship between PSCA expression and immunological subtypes in tumor microenvironment (TME) and the role of molecular subtypes, potentially promising immune biomarkers and tumour-infiltrating lymphocytes (TILs) in various cancer types, especially lung adenocarcinoma (LUAD). In addition, we investigated the prognostic significance of PSCA expression in LUAD. The co-expression network of PSCA was found to be mainly involved in the regulation of immune responses and antigen processing and expression and was significantly enriched in pathological and substance metabolism-related pathways in cancer. Altogether, this study reveals that PSCA is a promising target for immunotherapy in patients with cancer.

The efficacy of repetitive transcranial magnetic stimulation in postherpetic neuralgia: a meta-analysis of randomized controlled trials.

Purpose: This systematic review and meta-analysis aimed to evaluate the efficacy of repetitive transcranial magnetic stimulation (rTMS) in postherpetic neuralgia (PHN). Methods: Through an extensive search in four databases until October 2023, we selected five randomized controlled trials adhering to our specific criteria, involving 257 patients in total. For continuous outcomes, the standardized mean difference (SMD) was calculated. Heterogeneity among the studies was assessed using Cochran's I 2 and Q statistics, adopting a random-effects model for I 2 values over 50%. For assessing potential publication bias, we utilized both funnel plot and Egger's test. Results: Our analysis found that rTMS reduced the overall visual analogue scale (VAS) (SMD: -1.52, 95% CI: -2.81 to -0.23, p = 0.02), VAS at 1 month post-treatment (SMD: -2.21, 95% CI: -4.31 to -0.10, p = 0.04), VAS at 3 months post-treatment (SMD: -1.51, 95% CI: -2.81 to -0.22, p = 0.02), as well as patients' global impression of change scale (PGIC) (SMD: -1.48, 95% CI: -2.87 to -0.09, p = 0.04) and short-form McGill pain questionnaire (SF-MPQ) (SMD: -1.25, 95% CI: -2.41 to -0.09, p = 0.03) compared to the sham-rTMS group. Conclusion: Our study suggests that rTMS might have a potential alleviating effect on PHN symptoms. However, due to the limited number of studies and variations in rTMS parameters, larger sample studies involving more diverse populations, as well as further clarification of the most appropriate stimulation protocol, are still needed. Systematic review registration: https://www.crd.york.ac.uk/prospero/, Identifier ID: CRD42023488420.

Potential COVID-19 remedies from repurposed drugs and herbal small RNAs.

To date, SARS-CoV-2 has caused millions of deaths, but the choice of treatment is limited. We previously established a platform for identifying Food and Drug Administration (FDA)-approved repurposed drugs for avian influenza A virus infections that could be used for coronavirus disease 2019 (COVID-19) treatment. In this study, we analyzed blood samples from two cohorts of 63 COVID-19 patients, including 19 patients with severe disease. Among the 39 FDA-approved drugs we identified for COVID-19 therapy in both cohorts, 23 drugs were confirmed by literature mining data, including 14 drugs already under COVID-19 clinical trials and 9 drugs reported for COVID-19 treatments, suggesting the remaining 16 FDA-approved drugs may be candidates for COVID-19 therapy. Additionally, we previously reported that herbal small RNAs (sRNAs) could be effective components in traditional Chinese medicine (TCM) for treating COVID-19. Based on the abundance of sRNAs, we screened the 245 TCMs in the Bencao (herbal) sRNA Atlas that we had previously established, and we found that the top 12 TCMs for COVID-19 treatment was consistent across both cohorts. We validated the efficiency of the top 30 sRNAs from each of the top 3 TCMs for COVID-19 treatment in poly(I:C)-stimulated human non-small cell lung cancer cells (A549 cells). In conclusion, our study recommends potential COVID-19 remedies using FDA-approved repurposed drugs and herbal sRNAs from TCMs.

Continuous Strain Regulation of Palladium-Gold at the Atomic Level.

Revealing the effect of surface structure changes on the electrocatalytic performance is beneficial to the development of highly efficient catalysts. However, precise regulation of the catalyst surface at the atomic level remains challenging. Here, we present a continuous strain regulation of palladium (Pd) on gold (Au) via a mechanically controllable surface strain (MCSS) setup. It is found that the structural changes induced by the strain setup can accelerate electron transfer at the solid-liquid interface, thus achieving a significantly improved performance toward hydrogen evolution reaction (HER). In situ X-ray diffraction (XRD) experiments further confirm that the enhanced activity is attributed to the increased interplanar spacing resulting from the applied strain. Theoretical calculations reveal that the tensile strain modulates the electronic structure of the Pd active sites and facilitates the desorption of the hydrogen intermediates. This work provides an effective approach for revealing the relationships between the electrocatalyst surface structure and catalytic activity.

Highly Efficient Separation of Ethanol Amines and Cyanides via Ionic Magnetic Mesoporous Nanomaterials.

Simple and efficient sample pretreatment methods are important for analysis and detection of chemical warfare agents (CWAs) in environmental and biological samples. Despite many commercial materials or reagents that have been already applied in sample preparation, such as SPE columns, few materials with specificity have been utilized for purification or enrichment. In this study, ionic magnetic mesoporous nanomaterials such as poly(4-VB)@M-MSNs (magnetic mesoporous silicon nanoparticles modified by 4-vinyl benzene sulfonic acid) and Co2+@M-MSNs (magnetic mesoporous silicon nanoparticles modified by cobalt ions) with high absorptivity for ethanol amines (EAs, nitrogen mustard degradation products) and cyanide were successfully synthesized. The special nanomaterials were obtained by modification of magnetic mesoporous particles prepared based on co-precipitation using -SO3H and Co2+. The materials were fully characterized in terms of their composition and structure. The results indicated that poly(4-VB)@M-MSNs or Co2+@M-MSNs had an unambiguous core-shell structure with a BET of 341.7 m2·g-1 and a saturation magnetization intensity of 60.66 emu·g-1 which indicated the good thermal stability. Poly(4-VB)@M-MSNs showed selective adsorption for EAs while the Co2+@M-MSNs were for cyanide, respectively. The adsorption capacity quickly reached the adsorption equilibrium within the 90 s. The saturated adsorption amounts were MDEA = 35.83 mg·g-1, EDEA = 35.00 mg·g-1, TEA = 17.90 mg·g-1 and CN-= 31.48 mg·g-1, respectively. Meanwhile, the adsorption capacities could be maintained at 50-70% after three adsorption-desorption cycles. The adsorption isotherms were confirmed as the Langmuir equation and the Freundlich equation, respectively, and the adsorption mechanism was determined by DFT calculation. The adsorbents were applied for enrichment of targets in actual samples, which showed great potential for the verification of chemical weapons and the destruction of toxic chemicals.