CircBRIP1: a plasma diagnostic marker for non-small-cell lung cancer.

BACKGROUND: Circular RNA (circRNA), which has been demonstrated in studies to be abundantly prevalent in tumor cells and bodily fluids and to play a significant role in tumors, has the potential for biological markers to be used to assist tumor diagnosis. This study mainly discusses the potential of circBRIP1 as a biomarker for diagnosing non-small-cell lung cancer (NSCLC). METHODS: First, high-throughput sequencing screened the differentially expressed circBRIP1, and real-time fluorescence quantitative PCR (qRT-PCR) verified its expression in NSCLC. Next, sanger sequencing, agarose gel electrophoresis, RNase R assay, and fluorescence in situ hybridization (FISH) were used to verify its molecular characteristics. The diagnostic value was analyzed by the subject operating characteristic curve (ROC), and the cardinality test was analyzed for correlation with clinicopathological parameters. Finally, we tentatively predicted the downstream miRNA- or RNA-binding protein that may bind to circBRIP1. RESULTS: CircBRIP1 is highly expressed in NSCLC tissues, cells and plasma with good specificity and stability. CircBRIP1 not only can well-distinguish NSCLC patients from benign pulmonary diseases (BPD) patients, healthy individuals and small cell lung cancer (SCLC) patients, but it also has some potential for dynamic monitoring. Combined with the analysis of clinicopathological data, the high level of circRNA expression was related to the degree of tumor differentiation, TNM stage, T stage, lymph node metastasis and distal metastasis in NSCLC patients. In addition, circBRIP1 has a high diagnostic value. CONCLUSIONS: Plasma circBRIP1 is significantly overexpressed in NSCLC patients. It can be used as a sensitive biomarker with unique value for early diagnosis, tumor development and prognosis detection.

Decoding Optical Responses of Contact-Printed Arrays of Thermotropic Liquid Crystals Using Machine Learning: Detection and Reporting of Aqueous Amphiphiles with Enhanced Sensitivity and Selectivity.

Surfactants and other amphiphilic molecules are used extensively in household products, industrial processes, and biological applications and are also common environmental contaminants; as such, methods that can detect, sense, or quantify them are of great practical relevance. Aqueous emulsions of thermotropic liquid crystals (LCs) can exhibit distinctive optical responses in the presence of surfactants and have thus emerged as sensitive, rapid, and inexpensive sensors or reporters of environmental amphiphiles. However, many existing LC-in-water emulsions require the use of complicated or expensive instrumentation for quantitative characterization owing to variations in optical responses among individual LC droplets. In many cases, the responses of LC droplets are also analyzed by human inspection, which can miss subtle color or topological changes encoded in LC birefringence patterns. Here, we report an LC-based surfactant sensing platform that takes a step toward addressing several of these issues and can reliably predict concentrations and types of surfactants in aqueous solutions. Our approach uses surface-immobilized, microcontact-printed arrays of micrometer-scale droplets of thermotropic LCs and hierarchical convolutional neural networks (CNNs) to automatically extract and decode rich information about topological defects and color patterns available in optical micrographs of LC droplets to classify and quantify adsorbed surfactants. In addition, we report computational capabilities to determine relevant optical features extracted by the CNN from LC micrographs, which can provide insights into surfactant adsorption phenomena at LC-water interfaces. Overall, the combination of microcontact-printed LC arrays and machine learning provides a convenient and robust platform that could prove useful for developing high-throughput sensors for on-site testing of environmentally or biologically relevant amphiphiles.

Construction of amidoxime-functionalized magnetic hydroxyapatite with enhanced uranium extraction performance from aqueous solution and seawater.

A novel amidoxime-functionalized magnetic hydroxyapatite (AFNH) was successfuly fabricated to extract uranium from aqueous solution and seawater. The introduction of amidoxime group not only increased the number of active site of AFNH to speed up the adsorption rate and increase the extraction capacity, but also adjusted the optimal extraction pH from 4 to 8, which was beneficial for capturing uranium from seawater. The maximum adsorption capacity and adsorption efficiency at pH 8 were 945.2 mg g-1 and 99.2%, respectively. AFNH still had good removal efficiency (above 90%) after five cycles, indicating the good regeneration of AFNH. After uranium adsorption, AFNH could be easily recycled by magnetic separation due to its magnetism. In simulated seawater, AFNH also showed excellent uranium removal performance with high adsorption efficiency (84.9%) and adsorption capacity (1.70 mg g-1). Furthermore, the 14-day uranium extraction capacity of AFNH in natural seawater could reach 5.93 mg g-1. The SEM, FTIR, XRD and XPS analyses showed that the enhanced uranium extraction performance of AFNH was mainly attributed to electrostatic interaction, complexation and co-precipitation. In conclusion, AFNH was expected to be a candidate as adsorbent with great potential in extracting uranium from seawater.

Efficient separation of uranium(VI) from aqueous solution using magnetic Co/Al layered double oxides coated with carbon dots.

Herein, magnetic layered double oxides coated with carbon dots (MLCs) were synthesized through introducing sodium dodecylbenzene sulfonate and FeCl2 into Co/Al LDH for capturing uranium from aqueous solution. When the molar ratio of Co to Al was 4 : 1, the MLC composite possessed the strongest affinity to uranium(VI) in solution with short equilibrium time (<160 min), high adsorption efficiency (94.31%) and large removal capacity (513.85 mg g-1). The adsorption behavior of MLCs for uranium(VI) was well fitted with Langmuir and pseudo-second-order models, suggesting that the monolayer chemical adsorption was the rate-limiting step. Besides, MLC-3 could be reused by using 0.15 mol L-1 ethylene diamine tetraacetic acid as an eluent and the removal percentage still remained at a high level (>83.3%) after 5 adsorption/desorption cycles. Redox reaction, chemical complexation and electrostatic attraction were proved to play significant roles in uranium(VI) separation. Therefore, MLC-3 could be used as a potential adsorbent in uranium(VI)-containing wastewater treatment due to its excellent adsorption performance for uranium(VI).

Fabrication of phosphoric-crosslinked chitosan@g-C3N4 gel beads for uranium(VI) separation from aqueous solution.

In this work, a novel g-C3N4 filled, phosphoric-crosslinked chitosan gel bead (P-CS@CN) was successfully prepared to adsorb U(VI) from water. The separation performance of chitosan was improved by introducing more functional groups. At pH 5 and 298 K, the adsorption efficiency and adsorption capacity could reach 98.0 % and 416.7 mg g-1, respectively. After adsorption, the morphological structure of P-CS@CN did not change and adsorption efficiency remained above 90 % after 5 cycles. P-CS@CN exhibited an excellent applicability in water environment based on dynamic adsorption experiments. Thermodynamic analyses demonstrated the value of ΔG, manifesting the spontaneity of U(VI) adsorption process on P-CS@CN. The positive values of ΔH and ΔS showed that the U(VI) removal behavior of P-CS@CN was an endothermic reaction, indicating that the increase of temperature was great benefit to the removal. The adsorption mechanism of P-CS@CN gel bead could be summarized as the complexation reaction with the surface functional groups. This study not only developed an efficient adsorbent for the treatment of radioactive pollutants, but also provided a simple and feasible strategy for the modification of chitosan-based adsorption materials.

Circulating circular RNA hsa_circ_0023179 acts as a diagnostic biomarker for non-small-cell lung cancer detection.

BACKGROUND: Lung cancer, the most prevalent cancer-related death worldwide, still lacks the means for early diagnosis. Because of the unique properties of the loop that make it stable in body fluids, circular RNAs (circRNAs) as a biomarker becomes a possibility. This research purposed to explore whether hsa_circ_0023179 can be applied as a possible biomarker for the early diagnosis and prognosis of non-small cell lung cancer (NSCLC). METHODS: hsa_circ_0023179 was screened by high-throughput sequencing of three pairs of NSCLC tissues and their surrounding tissues. Agarose gel electrophoresis (AGE), Sanger sequencing, exonuclease digestion assay, and actinomycin D were used to affirm the molecular properties of circRNA. Precision determination was performed by placement at room temperature and multiple freeze-thawing test for methodological evaluation. The expression of hsa_circ_0023179 in tissues, serum, and cells was determined by quantitative real-time polymerase chain reaction (qRT-PCR) to establish the receiver operating characteristic (ROC) curve to assess the diagnostic efficacy of hsa_circ_0023179. RESULTS: hsa_circ_0023179 conforms to the basic properties of circRNA, and the detection method of hsa_circ_0023179 has good stability and repeatability. Its expression was connected to histological type, TNM stage, lymph node metastasis, and distal metastasis in NSCLC tissues, serum, and cells. Compared with traditional tumor markers with higher sensitivity and specificity. A combined diagnosis can significantly improve the diagnostic value. The decrease in postoperative expression level suggests some potential for dynamic monitoring. CONCLUSION: hsa_circ_0023179 might be a promising novel serum marker for the detection and prediction of NSCLC.

Hsa_circ_0000437 promotes pathogenesis of gastric cancer and lymph node metastasis.

Cellular communication between gastric cancer (GC) cells with different metastatic potentials and microenvironments and resultant cancer progression is not fully understood. Circular RNAs (circRNAs) and exosomal circRNAs are known to play extremely important regulatory roles in GC occurrence and progression. Here, we revealed significant differences in coronin-like actin-binding protein 1C (CORO1C) derived circRNA hsa_circ_0000437 between GC and para-cancer tissues. Hsa_circ_0000437 regulated GC cell proliferation, invasion, migration and apoptosis by targeting Ser/Arg-rich splicing factor 3 (SRSF3) and inhibiting programmed cell death 4 (PDCD4). The ectopic expression of hsa_circ_0000437 dramatically promoted tumor growth in nude mice in vivo. Furthermore, both gain-of-function and loss-of-function experiments demonstrated that hsa_circ_0000437 promoted human lymphatic endothelial cells (HLECs) invasion, migration, and tube formation in vitro and also promoted lymphangiogenesis and lymph node metastasis (LNM) in popliteal LNM model in vivo, when it was enriched in GC-secreted exosomes and transferred into HLECs. Mechanistically, exosomal hsa_circ_0000437 induced LNM via HSPA2-ERK signaling pathway independent of VEGF-C. Clinical data showed that exosomal hsa_circ_0000437 was enriched in the serum of GC patients, which was associated with LNM. In summary, these findings highlight the potential role of hsa_circ_0000437 as an outcome biomarker in GC patients with LNM, which may provide a novel target for GC therapy.

m6A-modified circRNAs: detections, mechanisms, and prospects in cancers.

Circular RNAs (circRNAs) have become a research hotspot in recent years with their universality, diversity, stability, conservativeness, and spatiotemporal specificity. N6-methyladenosine (m6A), the most abundant modification in the eukaryotic cells, is engaged in the pathophysiological processes of various diseases. An increasing amount of evidence has suggested that m6A modification is common in circRNAs and is associated with their biological functions. This review summarizes the effects of m6A modification on circRNAs and their regulation mechanisms in cancers, providing some suggestions of m6A-modified circRNAs in cancer therapy.

Natural Rubber Blend Optimization via Data-Driven Modeling: The Implementation for Reverse Engineering.

Natural rubber formulation methodologies implemented within industry primarily implicate a high dependence on the formulator's experience as it involves an educated guess-and-check process. The formulator must leverage their experience to ensure that the number of iterations to the final blend composition is minimized. The study presented in this paper includes the implementation of blend formulation methodology that targets material properties relevant to the application in which the product will be used by incorporating predictive models, including linear regression, response surface method (RSM), artificial neural networks (ANNs), and Gaussian process regression (GPR). Training of such models requires data, which is equal to financial resources in industry. To ensure minimum experimental effort, the dataset is kept small, and the model complexity is kept simple, and as a proof of concept, the predictive models are used to reverse engineer a current material used in the footwear industry based on target viscoelastic properties (relaxation behavior, tanδ, and hardness), which all depend on the amount of crosslinker, plasticizer, and the quantity of voids used to create the lightweight high-performance material. RSM, ANN, and GPR result in prediction accuracy of 90%, 97%, and 100%, respectively. It is evident that the testing accuracy increases with algorithm complexity; therefore, these methodologies provide a wide range of tools capable of predicting compound formulation based on specified target properties, and with a wide range of complexity.

Design of Multifunctional Nanopore Using Polyampholyte Brush with Composition Gradient.

Molecular organizations and charge patterns inside biological nanopores are optimized by evolution to enhance ionic and molecular transport. Inspired by the nuclear pore complex that employs asymmetrically arranged disordered proteins for its gating, we here design an artificial nanopore coated by an asymmetric polyampholyte brush as a model system to study the asymmetric mass transport under nanoconfinement. A nonequilibrium steady-state molecular theory is developed to account for the intricate charge regulation effect of the weak polyampholyte and to address the coupling between the polymer conformation and the external electric field. On the basis of this state-of-the-art theoretical method, we present a comprehensive theoretical description of the stimuli-responsive structural behaviors and transport properties inside the nanopore with all molecular details considered. Our model demonstrates that by incorporating a gradient of pH sensitivity into the polymer coatings of the nanopore, a variety of asymmetric charge patterns and functional structures can be achieved, in a pH-responsive manner that allows for multiple functions to be implemented into the designed system. The asymmetric charge pattern inside the nanopore leads to an electrostatic trap for major current carriers, which turns the nanopore into an ionic rectifier with a rectification factor above 1000 at optimized pH and salt concentration. Our theory further predicts that the nanopore design behaves like a double-gated nanofluidic device with pH-triggered opening of the gates, which can serve as an ion pump and pH-responsive molecular filter. These results deepen our understanding of asymmetric transport in nanoconfined systems and provide guidelines for designing polymer-coated smart nanopores.

Elucidating the Role of Serum tRF-31-U5YKFN8DYDZDD as a Novel Diagnostic Biomarker in Gastric Cancer (GC).

BACKGROUND: Gastric cancer (GC) is one of the malignant tumors with the highest morbidity and mortality in the world. Early diagnosis combined with surgical treatment can significantly improve the prognosis of patients. Therefore, it is urgent to seek higher sensitivity and specificity biomarkers in GC. tRNA-derived small RNAs are a new non-coding small RNA that widely exists in tumor cells and body fluids. In this study, we explore the expression and biological significance of tRNA-derived small RNAs in GC. MATERIALS AND METHODS: First of all, we screened the differentially expressed tRNA-derived small RNAs in tumor tissues by high-throughput sequencing. Agarose gel electrophoresis (AGE), Sanger sequencing, and Nuclear and Cytoplasmic RNA Separation Assay were used to screen tRF-31-U5YKFN8DYDZDD as a potential tumor biomarker for the diagnosis of GC. Then, we detected the different expressions of tRF-31-U5YKFN8DYDZDD in 24 pairs of GC and paracancerous tissues, the serum of 111 GC patients at first diagnosis, 89 normal subjects, 48 superficial gastritis patients, and 28 postoperative GC patients by quantitative real-time PCR (qRT-PCR). Finally, we used the receiver operating characteristic (ROC) curve to analyze its diagnostic efficacy. RESULTS: The expression of tRF-31-U5YKFN8DYDZDD has good stability and easy detection. tRF-31-U5YKFN8DYDZDD was highly expressed in tumor tissue, serum, and cell lines of GC, and the expression was significantly related to TNM stage, depth of tumor invasion, lymph node metastasis, and vascular invasion. The expression of serum tRF-31-U5YKFN8DYDZDD in the GC patients decreased after the operation (P = 0.0003). Combined with ROC curve analysis, tRF-31-U5YKFN8DYDZDD has better detection efficiency than conventional markers. CONCLUSIONS: The expressions of tRF-31-U5YKFN8DYDZDD in the tumor and paracancerous tissues, the serum of GC patients and healthy people, and the serum of GC patients before and after operation were different. tRF-31-U5YKFN8DYDZDD is not only a diagnostic biomarker of GC but also a predictor of poor prognosis.

Predicting Critical Micelle Concentrations for Surfactants Using Graph Convolutional Neural Networks.

Surfactants are amphiphilic molecules that are widely used in consumer products, industrial processes, and biological applications. A critical property of a surfactant is the critical micelle concentration (CMC), which is the concentration at which surfactant molecules undergo cooperative self-assembly in solution. Notably, the primary method to obtain CMCs experimentally-tensiometry-is laborious and expensive. In this study, we show that graph convolutional neural networks (GCNs) can predict CMCs directly from the surfactant molecular structure. In particular, we developed a GCN architecture that encodes the surfactant structure in the form of a molecular graph and trained it using experimental CMC data. We found that the GCN can predict CMCs with higher accuracy on a more inclusive data set than previously proposed methods and that it can generalize to anionic, cationic, zwitterionic, and nonionic surfactants using a single model. Molecular saliency maps revealed how atom types and surfactant molecular substructures contribute to CMCs and found this behavior to be in agreement with physical rules that correlate constitutional and topological information to CMCs. Following such rules, we proposed a small set of new surfactants for which experimental CMCs are not available; for these molecules, CMCs predicted with our GCN exhibited similar trends to those obtained from molecular simulations. These results provide evidence that GCNs can enable high-throughput screening of surfactants with desired self-assembly characteristics.

Evaluation of cornstalk as bulking agent on greenhouse gases emission and bacterial community during further composting.

The aim of current work was to explore the impact of Cornstalk (CS) on greenhouse gaseous emission and maturation during further composting and analyzed its impact on bacterial diversity. Three kinds of immature fertilizers were collected from chicken, pig and dairy manure namely T1, T2 and T3 as control, T4, T5 and T6 were added CS into T1 to T3 and adjusted C/N to 25 namely treatment. The results illustrated that gases (N2O, CH4 and NH3) emission of CS added treatments decreased by 6.39%-24.68%, 10.60%-23.23% and 13.00%-19.58%, respectively. But the CS amendment increased CO2 emission by 15.53%-30.81%. The mineralization of carbon and nitrogen was mainly correlated to Firmicutes, Actinobacteria, Proteobacteria and Bacteroidota, CS amendment increased abundance by 22.28%, 17.79%, 1.48% and 35.90%, respectively. The strategy of employing CS would be the most feasible approach for recycling of immature manure, considering its compost quality and environmental from farm.

LncRNA HCP5 : A Potential Biomarker for Diagnosing Gastric Cancer.

BACKGROUND: It has been reported that long non-coding RNAs (lncRNAs) can be regarded as a biomarker and had particular clinical significance for early screening and gastric cancer (GC) diagnosis. Therefore, this study aimed to investigate whether serum HCP5 could be a new diagnostic biomarker. METHODS: Filtered out the HCP5 from the GEO database. The specificity of HCP5 was verified by real-time fluorescence quantitative PCR (qRT-PCR), and then the stability of HCP5 was verified by room temperature storage and repeated freeze-thaw experiments. Meanwhile, the accuracy of HCP5 was verified by agarose gel electrophoresis (AGE) and Sanger sequencing. Simultaneously, the expression level of serum HCP5 was detected by qRT-PCR in 98 patients with primary gastric cancer, 21 gastritis patients, 82 healthy donors, and multiple cancer types. Then, the methodology analysis was carried on. Moreover, receiver operating characteristic (ROC) was used to evaluate its diagnostic efficiency. RESULTS: qRT-PCR method had good repeatability and stability in detecting HCP5. The expression level of HCP5 in the serum of gastric cancer patients was remarkably higher than that of healthy controls, and it could distinguish gastritis patients from healthy donors. Besides, the expression of HCP5 was increased dramatically in MKN-45 and MGC-803. The FISH assay showed that HCP5 was mainly distributed in the cytoplasm of MKN-45 and BGC-823 cells. When HCP5 was combined with existing tumor markers, the diagnostic efficiency of HCP5 was the best, and the combined diagnosis of carcinoembryonic antigen (CEA), carbohydrate antigen199 (CA199), and HCP5 can significantly improve the diagnostic sensitivity. Besides, compared with the expression levels of thyroid cancer (THCA), colorectal cancer (CRC), and breast cancer (BRCA), serum HCP5 in gastric cancer was the most specific. Moreover, the high expression of serum HCP5 was related to differentiation, lymph node metastasis, and nerve invasion. The term of serum HCP5 after the operation was significantly lower than that of patients with primary gastric cancer. CONCLUSION: Serum HCP5 can be used as a potential biomarker of non-invasive fluid biopsy, which had a unique value in the early diagnosis, development, and prognosis of gastric cancer.

CAM-DR: Mechanisms, Roles and Clinical Application in Tumors.

Despite the continuous improvement of various therapeutic techniques, the overall prognosis of tumors has been significantly improved, but malignant tumors in the middle and advanced stages still cannot be completely cured. It is now evident that cell adhesion-mediated resistance (CAM-DR) limits the success of cancer therapies and is a great obstacle to overcome in the clinic. The interactions between tumor cells and extracellular matrix (ECM) molecules or adjacent cells may play a significant role in initiating the intracellular signaling pathways that are associated with cell proliferation, survival upon binding to their ligands. Recent studies illustrate that these adhesion-related factors may contribute to the survival of cancer cells after chemotherapeutic therapy, advantageous to resistant cells to proliferate and develop multiple mechanisms of drug resistance. In this review, we focus on the molecular basis of these interactions and the main signal transduction pathways that are involved in the enhancement of the cancer cells' survival. Furthermore, therapies targeting interactions between cancer cells and their environment to enhance drug response or prevent the emergence of drug resistance will also be discussed.

Production and beneficial impact of biochar for environmental application: A comprehensive review.

This review focuses on a holistic view of biochar, production from feedstock's, engineering production strategies, its applications and future prospects. This article reveals a systematic emphasis on the continuation and development of biochar and its production methods such as Physical engineering, chemical and bio-engineering techniques. In addition, biochar alternatives such as nutrient formations and surface area made it a promising cheap source of carbon-based products such as anaerobic digestion, gasification, and pyrolysis, commercially available wastewater treatment, carbons, energy storage, microbial fuel cell electrodes, and super-capacitors repair have been reviewed. This paper also covers the knowledge blanks of strategies and ideas for the future in the field of engineering biochar production techniques and application as well as expand the technology used in the circular bio-economy.

Fungal dynamics during anaerobic digestion of sewage sludge combined with food waste at high organic loading rates in immersed membrane bioreactors.

In this study, the influence of distinct hydraulic retention times (HRT) and organic loading rates (OLRs) on fungal dynamics during food waste anaerobic digestion in immersed membrane-based bio-reactors (iMBR) were investigated. The organic loading rate 4-8 g VS/L/d (R1) and 6-10 g VS/L/d (R2) were set in two iMBR. T1 (1d), T2 (15d) and T3 (34d) samples collected from each bioreactor were analyzed fungal community by using 18s rDNA. In R2, T2 had the most abundant Ascomycota, Basidiomycota, Chytridiomycota and Mucoromycota. As for R1, T3 also had the richest Cryptomycota except above four kinds of fungi. Subsequently, the Principal Component Analysis (PCA) and Non-Metric Multi-Dimensional Scaling (NMDS) indicated that fungal diversity was varied among the all three phases (T1, T2, and T3) and each treatment (R1 and R2). Finally, the results showed that different OLRs and HRT have significantly influenced the fungal community.

Distribution of heavy metal resistant bacterial community succession in cow manure biochar amended sheep manure compost.

The aim of this investigation was to study the effects of cow manure biochar (CMB) on the distribution of heavy metal resistant bacterial (HMRB) community succession during sheep manure (SM) composting. The experiments were conducted with six different ratio of CMB (0%(T1), 2.5%(T2), 5%(T3),7.5%(T4),10%(T5) and 12%(T6)onadryweightbasis) and 0% is used as control. The results showed that the most dominant phylum were Proteobacteria (40.89%-5.65%) and Firmicutes (0.16%-93.18%), and 7.5% CMB mixed with sheep manure for best results. Thus, significant correlation was noticed among the analyzed physicochemical factors, gaseous emission and bacterial phylum in used 7.5-10% CMB applied for SM composting. Overall, the application of biochar increased the diversity of the bacterial community and promoted the degradation of organic matter. In addition, 7.5-10% CMB applied treatments showed greater immobilization of HMRB community succession during SM composting.

Sustainable blueberry waste recycling towards biorefinery strategy and circular bioeconomy: A review.

Waste valorization using biological methods for value addition as well as environmental management is becoming popular approach for sustainable development. The present review addresses the availability of blueberry crop residues (BCR), applications of this feedstock in bioprocess for obtaining range of value-added products, to offer economic viability, business development and market potential, challenges and future perspectives. To the best of our knowledge, this is the first article addressing the blueberry waste valorization for a sustainable circular bioeconomy. Furthermore, it covers the information on the alternative BCR valorization methods and production of biochar for environmental management through removal or mitigation of organic and inorganic pollutants from contaminated sites. The review also discusses the ample opportunities of strategic utilization of BCR to offer solutions for environmental sustenance, covers the emerging trends to produce multi-products and techno-economic prospective for sustainable agronomy.

Conversion food waste and sawdust into compost employing black soldier fly larvae (diptera: Stratiomyidae) under the optimized condition.

The increasing number of food waste (FW) had led to an urgent methods to recycle, black soldier fly larvae (BSFL) was a potential quick waste manager. To assess the impact of BSFL on conversion FW and sawdust into compost via the parameters of maturity, nutrient transformation and volatile fatty acids (VFAs). Meanwhile, the artificial of FW contained noodles, cabbages, rice and pork. FW and sawdust were employed by BSFL (6.5:0.5:1.2 ratio on fresh weight basis) as T1 and without BSFL called control (T2), while moisture content for FW and sawdust was 86.57% and 5.98%. Results illustrated that BSFL declined the composting time and only 9 d. Compared with initial mixture materials, T1 decreased organic matter, total kjeldahl nitrogen and VFAs from 97.41 to 85.96%, 23.01 to 17.77 g kg-1 and 3.25 to 1.69 g kg-1, respectively. However, T1 increased the total phosphorous and total potassium in 3.8 folds and 5 folds. The value of pH and EC reached at 4.27 and 1100 µS cm-1, and the germination index attained to 70.69%. In addition, redundancy analysis was used to analysis the correlation between factors under composting employed with different additive ratio of BSFL. Therefore, BSFL played a vital role in FW and sawdust recycling, especially reduced composting time and made the final separation of larvae and substrate easily, saving labor costs.