Membrane-based inverse-transition purification facilitates a rapid isolation of various spider-silk elastin-like polypeptide fusion proteins from extracts of transgenic tobacco.

Plants can produce complex pharmaceutical and technical proteins. Spider silk proteins are one example of the latter and can be used, for example, as compounds for high-performance textiles or wound dressings. If genetically fused to elastin-like polypeptides (ELPs), the silk proteins can be reversibly precipitated from clarified plant extracts at moderate temperatures of ~ 30 °C together with salt concentrations > 1.5 M, which simplifies purification and thus reduces costs. However, the technologies developed around this mechanism rely on a repeated cycling between soluble and aggregated state to remove plant host cell impurities, which increase process time and buffer consumption. Additionally, ELPs are difficult to detect using conventional staining methods, which hinders the analysis of unit operation performance and process development. Here, we have first developed a surface plasmon resonance (SPR) spectroscopy-based assay to quantity ELP fusion proteins. Then we tested different filters to prepare clarified plant extract with > 50% recovery of spider silk ELP fusion proteins. Finally, we established a membrane-based purification method that does not require cycling between soluble and aggregated ELP state but operates similar to an ultrafiltration/diafiltration device. Using a data-driven design of experiments (DoE) approach to characterize the system of reversible ELP precipitation we found that membranes with pore sizes up to 1.2 µm and concentrations of 2-3 M sodium chloride facilitate step a recovery close to 100% and purities of > 90%. The system can thus be useful for the purification of ELP-tagged proteins produced in plants and other hosts.

Application of multiple strategies to enhance oleanolic acid biosynthesis by engineered Saccharomyces cerevisiae.

Oleanolic acid and its derivatives are widely used in the pharmaceutical, agricultural, cosmetic and food industries. Previous studies have shown that oleanolic acid production levels in engineered cell factories are low, which is why oleanolic acid is still widely extracted from traditional medicinal plants. To construct a highly efficient oleanolic acid production strain, rate-limiting steps were regulated by inducible promoters and the expression of key genes in the oleanolic acid synthetic pathway was enhanced. Subsequently, precursor pool expansion, pathway refactoring and diploid construction were considered to harmonize cell growth and oleanolic acid production. The multi-strategy combination promoted oleanolic acid production of up to 4.07 g/L in a 100 L bioreactor, which was the highest level reported.

The application of the propensity score matching method in stock prediction among stocks within the same industry.

Stock price prediction is crucial in stock market research, yet existing models often overlook interdependencies among stocks in the same industry, treating them as independent entities. Recognizing and accounting for these interdependencies is essential for precise predictions. Propensity score matching (PSM), a statistical method for balancing individuals between groups and improving causal inferences, has not been extensively applied in stock interdependence investigations. Our study addresses this gap by introducing PSM to examine interdependence among pharmaceutical industry stocks for stock price prediction. Additionally, our research integrates Improved particle swarm optimization (IPSO) with long short-term memory (LSTM) networks to enhance parameter selection, improving overall predictive accuracy. The dataset includes price data for all pharmaceutical industry stocks in 2022, categorized into chemical pharmaceuticals, biopharmaceuticals, and traditional Chinese medicine. Using Stata, we identify significantly correlated stocks within each sub-industry through average treatment effect on the treated (ATT) values. Incorporating PSM, we match five target stocks per sub-industry with all stocks in their respective categories, merging target stock data with weighted data from non-target stocks for validation in the IPSO-LSTM model. Our findings demonstrate that including non-target stock data from the same sub-industry through PSM significantly improves predictive accuracy, highlighting its positive impact on stock price prediction. This study pioneers PSM's use in studying stock interdependence, conducts an in-depth exploration of effects within the pharmaceutical industry, and applies the IPSO optimization algorithm to enhance LSTM network performance, providing a fresh perspective on stock price prediction research.

Land-use simulation for synergistic pollution and carbon reduction: Scenario analysis and policy implications.

Simulations of sustainable land use and management are required to achieve targets to reduce pollution and carbon emissions. Limited research has been conducted on synergistic pollution and carbon reduction (SPCR) in land-use simulations. This study proposed a framework for land-use simulation focused on SPCR. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) and the entropy weight-based technique for order of preference by similarity to an ideal solution (TOPSIS) were used to optimize the land-use structure according to minimum net carbon, nitrogen, and phosphorus emissions. The cellular automata (CA) Markov model was then utilized to simulate the land-use spatial pattern according to the optimal conditions. The proposed framework was applied to the Dongjiang River Basin, South China, and three other scenarios (natural development (ND), carbon minimization (CM), and pollution minimization (PM)) were designed to validate the effectiveness of pollution and carbon emissions reduction under the SPCR scenario. The land-use structure and the pollution and carbon emissions in the scenarios were compared. The results showed the following. (1) The proportions of cultivated land, woodland, grassland, water, and construction land In the SPCR scenario accounted for 14%, 72%, 4%, 3%, and 7% of the total area, respectively. The carbon, nitrogen, and phosphorus emissions were 42.4%, 6.6%, and 7.8% lower, respectively, in the SPCR scenario than in the ND scenario, demonstrating the advantages of simultaneous pollution and carbon reduction. (2) The kappa coefficient of the CA-Markov model was 0.8729, indicating high simulation accuracy. (3) The simulated land-use spatial patterns exhibited low spatial heterogeneity under the CM, PM, and SPCR scenarios. However, there were significant disparities between the ND and SPCR scenarios. The cultivated and construction land areas were significantly smaller in the SPCR scenario than in the ND scenario. In contrast, the woodland and grassland areas were larger, with most differences in the central and southwestern regions of the Dongjiang River Basin. The results of the current study can be used to formulate effective land use policies and strategies in the Dongjiang Basin and similar areas to achieve the Coupling coordination between pollution reduction and carbon reduction. Policy recommendations include increasing the proportion of woodland and grassland, implementing reasonable constraints on expanding cultivated and construction lands, and establishing farmland red lines to promote synergistic pollution and carbon reduction.

Partitioning and Mobility of Chromium in Iron-Rich Laterites from an Optimized Sequential Extraction Procedure.

Chromium (Cr) leached from iron (Fe) (oxyhydr)oxide-rich tropical laterites can substantially impact downstream groundwater, ecosystems, and human health. However, its partitioning into mineral hosts, its binding, oxidation state, and potential release are poorly defined. This is in part due to the current lack of well-designed and validated Cr-specific sequential extraction procedures (SEPs) for laterites. To fill this gap, we have (i) first optimized a Cr SEP for Fe (oxyhydr)oxide-rich laterites using synthetic and natural Cr-bearing minerals and laterite references, (ii) used a complementary suite of techniques and critically evaluated existing non-laterite and non-Cr-optimized SEPs, compared to our optimized SEP, and (iii) confirmed the efficiency of our new SEP through analyses of laterites from the Philippines. Our results show that other SEPs inadequately leach Cr host phases and underestimate the Cr fractions. Our SEP recovered up to seven times higher Cr contents because it (a) more efficiently dissolves metal-substituted Fe phases, (b) quantitatively extracts adsorbed Cr, and (c) prevents overestimation of organic Cr in laterites. With this new SEP, we can estimate the mineral-specific Cr fractionation in Fe-rich tropical soils more quantitatively and thus improve our knowledge of the potential environmental impacts of Cr from lateritic areas.

Tailored microbial consortium producing hydrolytic enzyme cocktail for maximum saccharification of wheat straw.

The potential of hydrolytic enzyme cocktail obtained from designed bacterial consortium WSh-1 comprising Bacillus subtilis CRN 16, Paenibacillus dendritiformis CRN 18, Niallia circulans CRN 24, Serratia marscens CRN 29, and Streptomyces sp. CRN 30, was investigated for maximum saccharification. Activity was further enhanced to 1.01 U/ml from 0.82 U/ml by supplementing growth medium with biotin and cellobiose as a cofactor and inducer. Through kinetic analysis, the enzyme cocktail showed a high wheat straw affinity with Michaelis-Menten constant (Km) of 0.68 µmol/L and a deconstruction rate (Vmax) of 4.5 U/ml/min. The statistical optimization of critical parameters increased saccharification to 89 %. The optimized process in a 5-L lab-scale bioreactor yielded 501 mg/g of reducing sugar from NaOH-pretreated wheat straw. Lastly, genomic insights revealed unique abundant oligosaccharide deconstruction enzymes with the most diverse CAZyme profile. The consortium-mediated enzyme cocktails offer broader versatility with efficiency for the economical and sustainable valorization of lignocellulosic waste.

Optimization of newly isolated Bacillus cereus α-amylase production using orange peels and crab shells and application in wastewater treatment.

A newly isolated amylolytic strain was identified as Bacillus cereus spH1 based on 16S and 16-23S gene sequencing (Accession numbers OP811441.1 and OP819558, respectively), optimization strategies, using one variable at time (OVAT) and Plackett-Burman design, were employed to improve the alpha-amylase (α-amylase) production. Condition inferred revealed that the optimal physical parameters for maximum enzyme production were 30 °C, pH 7.5, and 12 h of incubation, using tryptone, malt extract, orange (Citrus sinensis) peels, crab (Portunus segnis) shells, calcium, and sodium chloride (NaCl) as culture medium. The full factorial design (FFD) model was observed to possess a predicted R2 and adjusted R2 values of 0.9788 and 0.9862, respectively, and it can effectively predict the response variables (p = 0). Following such efforts, α-amylase activity was increased 141.6-folds, ranging from 0.06 to 8.5 U/mL. The ideal temperature and pH for the crude enzyme activity were 65 °C and 7.5, respectively. The enzyme exhibited significant stability, with residual activity over 90% at 55 °C. The maltose was the only product generated during the starch hydrolysis. Moreover, the Bacillus cereus spH1 strain and its α-amylase were used in the treatment of effluents from the pasta industry. Germination index percentages of 143% and 139% were achieved when using the treated effluent with α-amylase and the strain, respectively. This work proposes the valorization of agro-industrial residues to improve enzyme production and to develop a green and sustainable approach that holds great promise for environmental and economic challenges.

Agave angustifolia Haw. Leaves as a Potential Source of Bioactive Compounds: Extraction Optimization and Extract Characterization.

The leaves of Agave angustifolia Haw. are the main agro-waste generated by the mezcal industry and are becoming an important source of bioactive compounds, such as phenolic compounds, that could be used in the food and pharmaceutical industries. Therefore, the extraction and identification of these phytochemicals would revalorize these leaf by-products. Herein, maceration and supercritical carbon dioxide (scCO2) extractions were optimized to maximize the phenolic and flavonoid contents and the antioxidant capacity of vegetal extracts of A. angustifolia Haw. In the maceration process, the optimal extraction condition was a water-ethanol mixture (63:37% v/v), which yielded a total phenolic and flavonoid content of 27.92 ± 0.90 mg EAG/g DL and 12.85 ± 0.53 µg QE/g DL, respectively, and an antioxidant capacity of 32.67 ± 0.91 (ABTS assay), 17.30 ± 0.36 (DPPH assay), and 13.92 ± 0.78 (FRAP assay) µM TE/g DL. Using supercritical extraction, the optimal conditions for polyphenol recovery were 60 °C, 320 bar, and 10% v/v. It was also observed that lower proportions of cosolvent decreased the polyphenol extraction more than pressure and temperature. In both optimized extracts, a total of 29 glycosylated flavonoid derivatives were identified using LC-ESI-QTof/MS. In addition, another eight novel compounds were identified in the supercritical extracts, showing the efficiency of the cosolvent for recovering new flavonoid derivatives.

Exome-Based Amino Acid Optimization: A Dietary Strategy to Satisfy Human Nutritional Demands and Enhance Muscle Strength in Breast Tumor Mice Undergoing Chemotherapy.

Breast cancer patients undergoing chemotherapy often experience muscle wasting and weakness, which impact their quality of life. A potential solution lies in customizing amino acid compositions based on exome-derived formulations (ExAAs). The study hypothesized that tailoring dietary amino acids using ExAAs could enhance muscle health. Theoretical amino acid requirements were calculated from the genome's exome region, and a breast cancer mouse model undergoing paclitaxel treatment was established. The mice were supplemented with a cancer-specific nutritional formula (QJS), and the effects of QJS and amino acid-adjusted QJS (adjQJS) were compared. Both formulations improved the nutritional status without compromising tumor growth. Notably, adjQJS significantly enhanced muscle strength compared to QJS (1.51 ± 0.25 vs. 1.30 ± 0.08 fold change, p < 0.05). Transcriptome analysis revealed alterations in complement and coagulation cascades, with an observed upregulation of C3 gene expression in adjQJS. Immune regulation also changed, showing a decrease in B cells and an increase in monocytes in skeletal muscle with adjQJS. Importantly, adjQJS resulted in a notable increase in Alistipes abundance compared to QJS (10.19 ± 0.04% vs. 5.03 ± 1.75%). This study highlights the potential of ExAAs as valuable guide for optimizing amino acid composition in diets for breast cancer patients undergoing chemotherapy.

Optimization of bacterial cellulose production by Komagataeibacter sucrofermentans in synthetic media and agrifood side streams supplemented with organic acids and vitamins.

The effect of thiamine (TA), ascorbic acid (AA), citric acid, and gallic acid (GA) on bacterial cellulose (BC) production by Komagataeibacter sucrofermentans, in synthetic (Hestrin and Schramm, HS) and natural substrates (industrial raisins finishing side stream extract, FSSE; orange juice, OJ; green tea extract, GTE), was investigated. The Response Surface Methodology was found reliable for BC yield prediction and optimization. Higher yields were achieved in the FSSE substrates, especially those supplemented with AA, TA, and GA (up to 19.4 g BC/L). The yield in the non-fortified substrates was 1.1-5.4 and 11.6-15.7 g/L, in HS and FSSE, respectively. The best yield in the natural non-fortified substrate FSSE-OJ-GTE (50-20-30 %), was 5.9 g/L. The porosity, crystallinity, and antioxidant properties of the produced BC films were affected by both the substrate and the drying method (freeze- or oven-drying). The natural substrates and the process wastewaters can be further exploited towards added value and sustainability. Take Home Message Sentence: Raisin and citrus side-streams can be efficiently combined for bacterial cellulose production, enhanced by other vitamin- and phenolic-rich substrates such as green tea.

Two-Dimensional Semiconductors and Transistors for Future Integrated Circuits.

Silicon transistors are approaching their physical limit, calling for the emergence of a technological revolution. As the acknowledged ultimate version of transistor channels, 2D semiconductors are of interest for the development of post-Moore electronics due to their useful properties and all-in-one potentials. Here, the promise and current status of 2D semiconductors and transistors are reviewed, from materials and devices to integrated applications. First, we outline the evolution and challenges of silicon-based integrated circuits, followed by a detailed discussion on the properties and preparation strategies of 2D semiconductors and van der Waals heterostructures. Subsequently, the significant progress of 2D transistors, including device optimization, large-scale integration, and unconventional devices, are presented. We also examine 2D semiconductors for advanced heterogeneous and multifunctional integration beyond CMOS. Finally, the key technical challenges and potential strategies for 2D transistors and integrated circuits are also discussed. We envision that the field of 2D semiconductors and transistors could yield substantial progress in the upcoming years and hope this review will trigger the interest of scientists planning their next experiment.

Cyanobacterial blooms control with CaO2 in different stages: Inhibition efficiency, water quality optimization and microbial community changes.

This study explored the feasibility of calcium peroxide (CaO2) to inhibit cyanobacterial blooms of the outbreak and dormancy stages. Our previous studies have found that CaO2 has a high inhibitory effect on cyanobacteria. In order to explore the application effect of CaO2 in actual cyanobacteria lake water, we conducted this study to clarify the effect of CaO2 on inhibiting cyanobacteria in outbreak and dormancy stages. The results showed that CaO2 inhibited the growth of cyanobacteria in the outbreak and dormancy stages by 98.7% and 97.6%, respectively. The main inhibitory mechanism is: (1) destroy the cell structure and make the cells undergo programmed cell death by stimulating the oxidation balance of cyanobacteria cells; (2) EPS released by cyanobacteria resist stimulation and combine calcium to form colonies, and accelerate cell settlement. In addition to causing direct damage to cyanobacteria, CaO2 can also improve water quality and sediment microbial diversity, and reduce the release of sediment to phosphorus, so as to further contribute to cyanobacterial inhibition. Finally, the results of qRT-PCR analysis confirmed the promoting effect of CaO2 on the downregulation of photosynthesis-related genes (rbcL and psaB), microcystn (mcyA and mcyD) and peroxiredoxin (prx), and verified the mechanism of CaO2 inhibition of cyanobacteria. In conclusion, this study provides new findings for the future suppression of cyanobacterial bloom, by combining water quality, cyanobacterial inhibition mechanisms, and sediment microbial diversity.

Production of biodiesel from waste fish fat through ultrasound-assisted transesterification using petro-diesel as cosolvent and optimization of process parameters using response surface methodology.

Biodiesel is a highly promising and viable alternative to fossil-based diesel that also addresses the urgent need for effective waste management. It can be synthesized by the chemical modification of triglycerides sourced from vegetable origin, animal fat, or algal oil. The transesterification reaction is the preferred method of producing biodiesel. However, the non-miscibility of alcohol and oil layer causes excessive utilization of alcohol, catalyst, and a substantial reacting time and temperature. In the current investigation, transesterification of waste fish oil was performed with petro-diesel as cosolvent, under the influence of ultrasound energy. The combination of both techniques is a unique and efficient way to minimize the mass transfer limitations considerably and hence reduces the parameters of the reaction. It is also a sincere effort to comply with the principles of green chemistry. The optimum reaction conditions were obtained using response surface methodology (RSM) that were as follows: molar ratio of methanol to oil 9.09:1, catalyst concentration of 0.97 wt%, cosolvent concentration of 29.1 wt%, temperature 60.1℃, and a reacting time 30 min. Under these listed conditions, 98.1% biodiesel was achievable, which was in close agreement with the expected result. In addition, the cosolvent removal step from the crude biodiesel was also eliminated as it could be employed as a blended fuel in CI engines.

Bio-fabrication of silver nanoparticles using Commelina erecta, L.: a mechanistic approach on synthesis, optimization, antibacterial, and antioxidant potential.

The ongoing exploration of economical, sustainable, and environment-friendly methods for synthesizing monodisperse colloidal metal nanoparticles is growing day by day due to their potential application in various fields. The use of plant derivatives in nanoparticle synthesis and their suitability as sustainable catalysts have emerged as significant areas of research. In this study, silver nanoparticles were synthesized using an aqueous extract obtained from the commonly found weed Commelina erecta, L. Extensive study is conducted to optimize various synthesis parameters such as pH, reducing agent concentration, silver nitrate concentration, and temperature. The plant extract utilized in the synthesis process contained variety of antioxidants, including malic acid, phenol, benzoic acid, and catechol, which played a crucial role in both reduction and capping during the synthesis process, thereby making them suitable for biomedical applications. The optimized synthesis process yielded silver nanoparticles with a particle size of 16.2 ± 3.1 nm. These nanoparticles exhibited excellent stability and demonstrated remarkable antibacterial activity compared to the standard antibacterial agent, streptomycin. In addition, the silver nanoparticles displayed promising antioxidant activity attributed to the presence of antioxidant functional groups on their surface. This study reports, for the first time, the synthesis of silver nanoparticles using antioxidant compounds present in C. erecta, L. plant extract. The antioxidant compounds identified through GC-MS belong to phenols, phenolic acids, and carboxylic acid groups. Furthermore, the exceptional antimicrobial and antioxidant properties exhibited by the synthesized silver nanoparticles offer new possibilities for their potential applications.

Impact of bariatric surgery on oral anticancer drugs: an analysis of real-world data.

PURPOSE: The number of patients with bariatric surgery who receive oral anticancer drugs is rising. Bariatric surgery may affect the absorption of oral anticancer drugs. Strikingly, no specific drug dosing recommendations are available. We aim to provide practical recommendations on the application of oral anticancer drugs in patients who underwent bariatric surgery. METHODS: Patients with any kind of bariatric surgery were extracted retrospectively in a comprehensive cancer center. In addition, a flowchart was proposed to assess the risk of inadequate exposure to oral anticancer drugs in patients who underwent bariatric surgery. Subsequently, the flowchart was evaluated retrospectively using routine Therapeutic drug monitoring (TDM) samples. RESULTS: In our analysis, 571 cancer patients (0.4% of 140.000 treated or referred patients) had previous bariatric surgery. Of these patients, 78 unique patients received 152 oral anticancer drugs equaling an overall number of 30 unique drugs. The 30 different prescribed oral anticancer drugs were categorized as low risk (13%), medium risk (67%), and high risk (20%) of underdosing. TDM plasma samples of 25 patients (82 samples) were available, of which 21 samples post-bariatric surgery (25%) were below the target value. CONCLUSIONS: The proposed flowchart can support optimizing the treatment with orally administered anticancer drugs in patients who underwent bariatric surgery. We recommend performing TDM in drugs that belong to BCS classes II, III, or IV. If more risk factors are present in BCS classes II or IV, a priori switches to other drugs may be advised. In specific cases, higher dosages can be provided from the start (e.g., tamoxifen).

Optimization, In Vitro and Ex Vivo Assessment of Nanotransferosome Gels Infused with a Methanolic Extract of Solanum xanthocarpum for the Topical Treatment of Psoriasis.

The goal of this investigation is to improve the topical delivery of medicine by preparing and maximizing the potential of a nanotransferosome gel infused with Solanum xanthocarpum methanolic extract (SXE) to provide localized and regulated distribution. Thin-film hydration was used to create SXE-infused nanotransferosomes (SXE-NTFs), and a Box-Behnken design was used to improve them. Phospholipon 90G (X1), cholesterol (X2) and sodium cholate (X3) were chosen as the independent variables, and their effects on vesicle size (Y1), polydispersity index (PDI) (Y2) and the percentage of entrapment efficiency (EE) (Y3) were observed both individually and in combination. For the SXE-NTFs, the vesicle size was 146.3 nm, the PDI was 0.2594, the EE was 82.24 ± 2.64%, the drug-loading capacity was 8.367 ± 0.07% and the drug release rate was 78.86 ± 5.24%. Comparing the antioxidant activity to conventional ascorbic acid, it was determined to be 83.51 ± 3.27%. Ex vivo permeation tests revealed that the SXE-NTF gel (82.86 ± 2.38%) considerably outperformed the SXE gel (35.28 ± 1.62%) in terms of permeation. In addition, it seemed from the confocal laser scanning microscopy (CLSM) picture of the Wistar rat's skin that the rhodamine-B-loaded SXE-NTF gel had a higher penetration capability than the control. Dermatokinetic studies showed that the SXE-NTF gel had a better retention capability than the SXE gel. According to the experimental results, the SXE-NTF gel is a promising and successful topical delivery formulation.

Optimization of fungal chitosan production from Cunninghamella echinulata using statistical designs.

Fungal chitosan (FCH) is superior to crustacean chitosan (CH) sources and is of immense interest to the scientific community while having a high demand at the global market. Industrial scale fermentation technologies of FCH production are associated with considerable challenges that frequently restrict their economic production and feasibility. The production of high quality FCH using an underexplored fungal strain Cunninghamella echinulata NCIM 691 that is hoped to mitigate potential future large-scale production was investigated. The one-factor-at-a-time (OFAT) method was implemented to examine the effect of the medium components (i.e. carbon and nitrogen) on the FCH yield. Among these variables, the optimal condition for increased FCH yield was carbon (glucose) and nitrogen (yeast extract) source. A total of 11 factors affected FCH yield among which, the best factors were screened by Plackett-Burman design (PBD). The optimization process was carried out using the response surface methodology (RSM) via Box-Behnken design (BBD). The three-level Box- Behnken factorial design facilitated optimum values for 3 parameters-glucose (2% w/v), yeast extract (1.5% w/v) and magnesium sulphate (0.1% w/v) at 30˚C and pH of 4.5. The optimization resulted in a 2.2-fold higher FCH yield. The produced FCH was confirmed using XRD, 1H NMR, TGA and DSC techniques. The degree of deacetylation (DDA) of the extracted FCH was 88.3%. This optimization process provided a significant improvement of FCH yields and product quality for future potential scale-up processes. This research represents the first report on achieving high FCH yield using a reasonably unfamiliar fungus C. echinulata NCIM 691 through optimised submerged fermentation conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-03919-6.

[Application strategy of artificial intelligence technology in feed-based development of medicinal and edible homologous traditional Chinese medicine(TCM)resources in era of the "antibiotic ban"].

In the context of the "antibiotic ban" era, the feed conversion of medicinal and edible traditional Chinese medicine(TCM) resources is a research hotspot in the field of antibiotic alternatives development. How to develop feed products that are beneficial to agriculture and livestock while ensuring nutrient balance and precision using medicinal and edible TCM resources as raw materials has become a challenge. Artificial intelligence(AI) technology has unique advantages in feed production and improving the efficiency of intelligent breeding. If AI technology is applied to the feed development of medicinal and edible TCM resources, it is possible to realize feeding and antibiotic-replacement value while ensuring precise nutrition. In order to better apply AI technology in the field of feed development of medicinal and edible TCM resources, this article used CiteSpace software to carry out literature visualization analysis and found that AI technology had a good application in the field of feed formulation optimization in recent years. However, there is still a gap in the research on the intelligent utilization of medicinal and edible TCM resources. Nonetheless, it is feasible for AI technology to be applied to the feed conversion of medicinal and edible TCM resources. Therefore, this article proposed for the first time an intelligent formulation system framework for feed materials derived from medicinal and edible TCM resources to provide new ideas for research in the field of feed development of medicinal and edible TCM resources and the research on the development of antibiotic alternatives. At the same time, it can pave the way for a new green industry chain for contemporary animal husbandry and the TCM industry.

GrMoNAS: A granularity-based multi-objective NAS framework for efficient medical diagnosis.

Neural Architecture Search (NAS) has been widely applied to automate medical image diagnostics. However, traditional NAS methods require significant computational resources and time for performance evaluation. To address this, we introduce the GrMoNAS framework, designed to balance diagnostic accuracy and efficiency using proxy datasets for granularity transformation and multi-objective optimization algorithms. The approach initiates with a coarse granularity phase, wherein diverse candidate neural architectures undergo evaluation utilizing a reduced proxy dataset. This initial phase facilitates the swift and effective identification of architectures exhibiting promise. Subsequently, in the fine granularity phase, a comprehensive validation and optimization process is undertaken for these identified architectures. Concurrently, employing multi-objective optimization and Pareto frontier sorting aims to enhance both accuracy and computational efficiency simultaneously. Importantly, the GrMoNAS framework is particularly suitable for hospitals with limited computational resources. We evaluated GrMoNAS in a range of medical scenarios, such as COVID-19, Skin cancer, Lung, Colon, and Acute Lymphoblastic Leukemia diseases, comparing it against traditional models like VGG16, VGG19, and recent NAS approaches including GA-CNN, EBNAS, NEXception, and CovNAS. The results show that GrMoNAS achieves comparable or superior diagnostic precision, significantly enhancing diagnostic efficiency. Moreover, GrMoNAS effectively avoids local optima, indicating its significant potential for precision medical diagnosis.

Green Synthesis of Selenium Nanoparticles using Green Coffee Beans: An Optimization Study.

In this study, ultrasonication extraction of some bioactive compounds from green coffee beans was optimized with the response surface method using Box-Behnken experimental design. The best condition was selected as 90.90 W ultrasonic power, 33.63 min sonication time and 30 % solid concentration. The responses obtained under optimum conditions had TPC, DPPH and CUPRAC values identified as 6603.33±2025.94 ppm GAE, 9638.31±372.17 ppm TE and 98.83 mmol, respectively. Microwave-assisted selenium nanoparticle production was carried out using the extract obtained under optimized conditions. The produced selenium nanoparticles showed absorbance between 350-400 nm. The surface morphology and size of the nanoparticles were determined by transmission electron microscopy (TEM) and spherical nanoparticles of about 100 nm were produced. Functional groups affecting the reduction were determined by FTIR analysis. In addition, the produced selenium nanoparticles had amorphous (non-uniform) structure and could maintain their stability at high temperatures.