Enhancing nutritional composition and aroma characteristics of kiwifruit wines through indigenous non-Saccharomyces yeast extracellular extract treatment.

To unlock the potential of strains for further enhancing the aromatic complexity of kiwifruit wines while avoiding undesirable flavors, indigenous non-Saccharomyces yeast extracellular extract treatment for fermentation was established. The extracellular extract from Zygosaccharomyces rouxii, Pichia kudriavzevii, and Meyerozyma guilliermondii were prepared and supplemented individually or in pairs to the kiwifruit wine fermentation system. Subsequently, the changes in physicochemical properties, antioxidants, and volatile characteristics of kiwifruit wines produced by different protocols were comprehensively evaluated, and the major aroma descriptors affecting sensory acceptability were analyzed by sensory evaluation and partial least squares regression. The results showed that extracellular extract treatment significantly improved the organic acids and monomeric phenols content, antioxidant capacity, and volatiles of kiwifruit wines. Compared to Sc, the increase in esters and alcohols, along with the decrease in aldehydes and acids in Pk-Zr and Mg-Zr, enhanced the aromatic complexity while reduce grassy and fungal flavors, resulting in higher sensory acceptability.

Improvement of water quality through coordinated multi-trophic level biomanipulations: Application to a subtropical emergency water supply lake.

Artificial emergency water source lakes have been built in most cities in the middle and lower reaches of the Yangtze River, China, to ensure water safety for residents. However, these new ecosystems are prone to algal blooms or other degraded water quality conditions. A newly built water supply lake in the lower reaches of the Yangtze River was selected as a model system to test whether the coordinated manipulation of fish and submerged macrophyte communities could enhance ecosystem function and quality. The coordinated manipulations spanned a five-year period, aiming to enhance both top-down and bottom-up control of phytoplankton. As a result of these manipulations, the catch per unit effort of small-bodied zooplanktivorous fishes decreased by >95 % from year two and remained low. The coverage and biomass of submerged macrophytes increased year by year. Water transparency increased from 1.07 to 3.33 m. Total phosphorus and total nitrogen showed a decreasing trend (not significant though). The annual mean biomass of Cyanophyta, Chlorophyta and Bacillariophyta decreased from 2.99 to 0.03 mg/L, 3.90 to 0.16 mg/L, and 3.50 to 0.3 mg/L, respectively. The biomass of phytoplankton in different groups decreased in all four seasons. The annual mean biomass of Cladocera and Copepoda remained low. The biomass of Cladocera and Copepoda decreased in summer, fall, and winter. The Ecosystem Health Index - increased from 15.9 to 32.0. The pros and cons of the various top-down and bottom-up control measures employed are discussed. This research presents a valuable case study on the enhancement of ecosystem structure and function in newly constructed emergency water supply lakes and offers insights into the restoration of other subtropical shallow lakes.

Learned liquid crystal microlens array for joint optimized deep optical architecture in identifying metameric materials.

Multispectral imaging holds great promise for the detection of metameric materials. However, traditional multispectral imaging systems are characterized by their large volume, complex structure, and high computational requirements, limiting their practical application. We propose a jointly optimized deep optical architecture that combines the liquid crystal (LC) microlens array (MLA) characteristics and a multi-level perceptual spectral reconstruction network (MLP-SRN). The core of the architecture is to integrate the physical properties of the LC-MLA into the MLP-SRN using point spread function (PSF) optical convolution kernels, decoupling the light-field characteristic information collected by the LC-MLA at different voltages. Experimental results demonstrate that the incorporation of the physical properties of the LC-MLA not only reduces the system size and computational complexity but demonstrates excellent performance in identifying a metameric material.

Endoscopic Cartilage Myringoplasty with Anterior Margin Preservation for Repairing Large Anterior Perforations.

Objective: This study compared the graft outcomes and complications of endoscopic cartilage inlay myringoplasty with preservation of anterior margins (IPAM) and the cartilage underlay technique with raising the tympanomeatal flap (CUTF) for repairing large anterior perforations. Materials and Methods: In total, 55 patients with large anterior perforations were recruited and allocated to the IPAM (n = 28) or the CUTF (n = 27) group. The graft success rate, hearing gain, operation time, and postoperative complications were compared between the groups at 12 months. Results: The mean operation times were 29.3 ± 2.7 minutes and 46.4 ± 3.9 minutes in the IPAM and CUTF groups, respectively (P < .001). The residual perforation rate was 0.0% in the IPAM group and 11.1% in the CUTF group (P = .222). All patients completed the 12-month follow-up. The overall graft success rate was 96.4% in the IPAM group and 88.9% in the CUTF group (P = .577). No significant differences were observed between the groups in terms of postoperative pure-tone averages for air conduction and bone conduction, air-bone gaps (ABGs), or ABG changes. In the CUTF group, 22.2% of the patients reported altered taste perception, 3.7% experienced bony external auditory canal (EAC) stenosis, and 3.7% developed EAC cholesteatoma. By contrast, the IPAM group did not have any cases of altered taste perception, EAC stenosis, or cholesteatoma. Conclusions: Endoscopic cartilage myringoplasty with IPAM and anterior perichondrium folding is a simple, effective, and minimally invasive technique for repairing large anterior perforations. It offers a high graft success rate and better hearing improvement compared to CUTF.

Comparison of volatile compounds and sensory profiles of low-alcohol pear beverages fermented with Saccharomyces cerevisiae and different non-Saccharomyces cerevisiae.

This study aimed to assess the impact of Saccharomyces cerevisiae and different non-Saccharomyces cerevisiae (Zygosaccharomyces bailii, Hanseniaspora opuntiae and Zygosaccharomyces rouxii) on the volatile compounds and sensory properties of low-alcohol pear beverages fermented from three varieties of pear juices (Korla, Laiyang and Binzhou). Results showed that all three pear juices were favorable matrices for yeasts growth. Non-Saccharomyces cerevisiae exhibited a higher capacity for acetate ester production compared to Saccharomyces cerevisiae, resulting in a significant enhancement in sensory complexity of the beverages. PCA and sensory analysis demonstrated that pear varieties exerted a stronger influence on the crucial volatile components and aroma characteristics of the fermented beverages compared to the yeast species. CA results showed different yeast strains exhibited suitability for the fermentation of specific pear juice varieties.

PhIP-Seq: methods, applications and challenges.

Phage-immunoprecipitation sequencing (PhIP-Seq) technology is an innovative, high-throughput antibody detection method. It enables comprehensive analysis of individual antibody profiles. This technology shows great potential, particularly in exploring disease mechanisms and immune responses. Currently, PhIP-Seq has been successfully applied in various fields, such as the exploration of biomarkers for autoimmune diseases, vaccine development, and allergen detection. A variety of bioinformatics tools have facilitated the development of this process. However, PhIP-Seq technology still faces many challenges and has room for improvement. Here, we review the methods, applications, and challenges of PhIP-Seq and discuss its future directions in immunological research and clinical applications. With continuous progress and optimization, PhIP-Seq is expected to play an even more important role in future biomedical research, providing new ideas and methods for disease prevention, diagnosis, and treatment.

Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers linked to immunogenic cell death (ICD) in DUs by utilizing RNA-sequencing data of Gene Expression Omnibus (GEO) analysis combined with a comprehensive database interrogation. Employing a random forest algorithm, we have developed a diagnostic model that demonstrates improved accuracy in distinguishing DUs from normal tissue, with satisfactory results from ROC analysis. Beyond mere diagnosis, our model categorizes DUs into novel molecular classifications, which may enhance our comprehension of their underlying pathophysiology. This study bridges the gap between molecular insights and clinical practice. It sets the stage for transformative strategies in DUs management, marking a significant step forward in personalized medicine for diabetic patients.

Integration of proteomics and transcriptomics to construct a prognostic signature of renal clear cell carcinoma.

Background: Protein information is often replaced by RNA data in studies to understand cancer-related biological processes or molecular functions, and proteins of prognostic significance in Kidney clear cell carcinoma (KIRC) remain to be mined. Methods: The cancer genome atlas program (TCGA) data was utilized to screen for proteins that are prognostically significant in KIRC. Machine learning algorithms were employed to develop protein prognostic models. Additionally, immune infiltration abundance, somatic mutation differences, and immunotherapeutic responses were analyzed in various protein risk subgroups. Ultimately, the validation of protein-coding genes was confirmed by utilizing an online database and implementing quantitative real-time PCR (qRT-PCR). Results: The patients were divided into two risk categories based on prognostic proteins, and notable disparities in both overall survival (OS) and progression free interval (PFI) were observed between the two groups. The OS was more unfavorable in the high-risk group, and there was a noteworthy disparity in the level of immune infiltration observed between the two groups. In addition, the nomogram showed high accuracy in predicting survival in KIRC patients. Conclusion: In this research, we elucidated the core proteins associated with prognosis in terms of survival prediction, immunotherapeutic response, somatic mutation, and immune microenvironment. Additionally, we have developed a reliable prognostic model with excellent predictive capabilities.

Piecewise Linear Strength Models for Analyzing Multiple Failure Mechanisms in Rocks Materials.

Rock materials failures are accompanied by the co-existence of various failure mechanisms, including rock fracturing, shearing, and compaction yield. These mechanisms manifest macroscopically as multiple failure modes and nonlinear strength characteristics related to stress levels. Considering the limitations of current rock mechanics strength theories, which are primarily derived from single failure mechanisms, this study evaluates the applicability of alternative strength theories. Based on the extensional-strain criterion and the PMC (Paul-Mohr-Coulomb) model, a piecewise linear strength model was proposed that is suitable for analyzing multiple failure mechanisms in rocks, revealing the intrinsic mechanisms of multi-mechanism rock material failure. A multiple failure mechanism strength model in the form of inequalities was proposed, using the generalized shear stress, mean stress, and stress Lode angle as parameters. Strength tests conducted on sandstone and granite rock material samples under different stress conditions revealed distinct piecewise linear strength characteristics for both rock types, validating the rationality and applicability of the multiple failure mechanism model. The findings construct a multi-mechanism failure model for rocks, providing enhanced predictive capabilities and aiding in the prevention of rock structural failures.

Polyhedral oligomeric silsesquioxane (POSS)-silicon/carbon quantum dots nanocomposites for cell imaging.

Silicon quantum dots (SiQDs) and carbon quantum dots (CQDs) are renowned for their outstanding applications in fluorescence imaging and biosensing. However, their small size poses significant challenges in terms of preparation, collection, and purification. Polyhedral oligomeric silsesquioxanes (POSS), an organic-inorganic nanohybrid with a cage-like structure, has recently attracted considerable attention due to its excellent biocompatibility. In this research, we utilize the encapsulating properties of POSS to improve the optical property of SiQDs/CQDs through an in situ synthesis strategy, resulting in the production of blue-emitting POSS-SiQDs, green-emitting POSS-G-CNDs, and red-emitting POSS-R-CNDs. By examining their structural and optical characteristics, it is found that these hybrid materials exhibit excellent luminescent properties, biocompatibility and cell membrane permeability. This facilitates multicolor intracellular imaging and underscores their successful application in biological imaging. Our study presents a novel approach to synthesize POSS-QDs composite nanomaterials with new perspectives in biological imaging and medical diagnostics.

Therapeutic effects of tetrahedral framework nucleic acids and tFNAs-miR22 on retinal ischemia/reperfusion injury.

Retinal ischemia/reperfusion injury (RI/R) is a common pathological process in ophthalmic diseases, which can cause severe visual impairment. The mechanisms underlying RI/R damage and repair are still unclear. Scholars are actively exploring effective intervention strategies to restore impaired visual function. With the development of nucleic acid nanomaterials, tetrahedral framework nucleic acids (tFNAs) have shown promising therapeutic potential in various fields such as stem cells, biosensors, and tumour treatment due to their excellent biological properties. Besides, miRNA-22-3p (miR-22), as an important regulatory factor in neural tissue, has been proven to have positive effects in various neurodegenerative diseases. By stably constructing a complex of tetrahedral framework nucleic acids miR22 (tFNAs-miR22), we observed that tFNAs-miR22 had a positive effect on the repair of RI/R injury in retinal neural tissue. Previous studies have shown that tFNAs can effectively deliver miR-22 into damaged retinal neurons, subsequently exerting neuroprotective effects. Interestingly, we found that there was a certain synergistic effect between tFNAs and miR-22. tFNAs-miR22 can selectively activated the ERK1/2 signalling pathway to reduce neuronal apoptosis, accelerate cell proliferation, and restore synaptic functional activity. In this study, we established a simple yet effective small molecule drug for RI/R treatment which may become a promising neuroprotectant for treating this type of vision impairment disease in the future.

Effect of sequential fermentation with indigenous non-Saccharomyces cerevisiae combinations and Saccharomyces cerevisiae on the chemical composition and aroma compounds evolution of kiwifruit wine.

To unlock the potential of indigenous non-Saccharomyces cerevisiae and develop novel starters to enhance the aromatic complexity of kiwifruit wine, Zygosaccharomyces rouxii, Pichia kudriavzevii and Meyerozyma guilliermondii were pairwise combined and then used in sequential fermentation with Saccharomyces cerevisiae. The impact of different starter cultures on the chemical composition and flavor profile of the kiwifruit wines was comprehensively analyzed, and the aroma evolution during alcoholic fermentation was investigated by examining the changes in key volatiles and their loss rates. Compared with Saccharomyces cerevisiae, mixed starter cultures not only improve antioxidant capacity but also increase esters and alcohols yields, presenting intense floral and fruity aromas with high sensory acceptability. The results indicated that sequential inoculation of non-Saccharomyces cerevisiae combination and Saccharomyces cerevisiae promoted the development of volatiles while maintaining the stability of key aroma compounds in the winemaking environment and reducing the aroma loss rates during alcoholic fermentation.

Characterization and subcellular localization of selenium in Limosilactobacillus fermentum Ln-9 obtained by intense pulsed light-ultraviolet combined mutagenesis.

Lactic acid bacteria (LAB) can convert inorganic selenium (Se) to organic Se and elemental forms with low toxicity and high bioavailability, but a comprehensive Se analysis of Se-enriched LAB is lacking. In this study, Limosilactobacillus fermentum Ln-9 was obtained by intense pulsed light-ultraviolet combined mutagenesis, and its characteristics and subcellular localization of Se were analyzed. The results displayed that Ln-9 accumulated 3.03 times Se that of the original strain. Under optimal fermentation conditions, the total Se content of Se-enriched Ln-9 (SeLn-9) reached 12.16 mg/g with 96.34% contained in Se nanoparticles (SeNPs), which was much higher than that of organic macromolecules. Furthermore, SeNPs were mainly localized outside the cell, Se-proteins were in the membrane and cytoplasmic fractions, and Se-polysaccharides were in the membrane fraction. Besides, SeLn-9 maintained a good morphology and gastrointestinal tolerance and had an enhanced antioxidant capacity. These findings make Ln-9 promising for applications in the food industry.

Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023.

BACKGROUND: Recently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aimed to explore the research status and hotspots of the application of DL in cancer. METHODS: We retrieved all articles on the application of DL in cancer from the Web of Science database Core Collection database. Biblioshiny, VOSviewer and CiteSpace were used to perform the bibliometric analysis through analyzing the numbers, citations, countries, institutions, authors, journals, references, and keywords. RESULTS: We found 6,016 original articles on the application of DL in cancer. The number of annual publications and total citations were uptrend in general. China published the greatest number of articles, USA had the highest total citations, and Saudi Arabia had the highest centrality. Chinese Academy of Sciences was the most productive institution. Tian, Jie published the greatest number of articles, while He Kaiming was the most co-cited author. IEEE Access was the most popular journal. The analysis of references and keywords showed that DL was mainly used for the prediction, detection, classification and diagnosis of breast cancer, lung cancer, and skin cancer. CONCLUSIONS: Overall, the number of articles on the application of DL in cancer is gradually increasing. In the future, further expanding and improving the application scope and accuracy of DL applications, and integrating DL with protein prediction, genomics and cancer research may be the research trends.

Simultaneous inoculation of non-Saccharomyces yeast and lactic acid bacteria for aromatic kiwifruit wine production.

To further explore strain potential and develop an aromatic kiwifruit wine fermentation technique, the feasibility of simultaneous inoculation by non-Saccharomyces yeast and lactic acid bacteria was investigated. Lacticaseibacillus paracasei, Lactiplantibacillus plantarum, and Limosilactobacillus fermentum, which have robust ß-glucosidase activity as well as good acid and ethanol tolerance, were inoculated for simultaneous fermentation with Zygosaccharomyces rouxii and Meyerozyma guilliermondii, respectively. Subsequently, the chemical compositions and sensory characteristics of the wines were comprehensively evaluated. The results showed that the majority of the simultaneous protocols effectively improved the quality of kiwifruit wines, increasing the content of polyphenols and volatile compounds, thereby enhancing sensory acceptability compared to the fermentation protocols inoculated with non-Saccharomyces yeast individually. Particularly, the collaboration between Lacp. plantarum and Z. rouxii significantly increased the diversity and content of esters, alcohols, and ketones, intensifying floral and seeded fruit odors, and achieving the highest overall acceptability. This study highlights the potential significance of simultaneous inoculation in kiwifruit wine production.

Monocyte distribution width as a promising biomarker for differential diagnosis of chronic hepatitis, cirrhosis, and hepatocellular carcinoma.

Objective: We aimed to investigate the association and diagnostic value of monocyte distribution width (MDW) for chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Methods: MDW levels were measured in 483 individuals (103 CHB, 77 LC, 153 HCC, and 150 controls). MDW was detected using UniCel Dx900 for specific cell volume parameters and the distribution of cell volumes. Results: Our findings revealed a dynamic upward change in MDW levels across different stages of chronic liver disease, from CHB to LC and HCC. In CHB, MDW levels were highest among HBeAg-positive CHB patients and exhibited a negative correlation with HBV markers while positively correlating with ALT levels. In LC, MDW showed a positive association with the pathological progression of LC, demonstrating consistency with CP scores. MDW proved to be equally effective as traditional detection for diagnosing LC. In HCC, MDW was positively correlated with HCC occurrence and development, with higher levels observed in the high MDW group, which also exhibited elevated AFP levels, MELD scores, and 90-day mortality rates. MDW surpassed predictive models in its effectiveness for diagnosing HCC, as well as CHB and LC, with respective areas under the curve of 0.882, 0.978, and 0.973. Furthermore, MDW emerged as an independent predictor of HCC. Conclusion: MDW holds significant diagnostic efficacy in identifying CHB, LC, and HCC. These findings suggest that MDW could serve as a promising biomarker for predicting the severity of liver diseases and aid in rational clinical treatment strategies.

Enhancement of vitamin B stability with the protection of whey protein and their interaction mechanisms.

Vitamin B is easily degraded by light and heat during storage, which results in nutritional loss of food. Whey protein is expected to protect vitamin B by forming complexes through secondary bonds. The properties of the complexes and protective effects of whey protein on vitamins B1, B2, B3 and B6 were characterized. The percentage losses of vitamin B were decreased by more than 60% with the protection of whey protein. FTIR, fluorescence spectroscopy, thermodynamic analysis and molecular docking were used to investigate the binding interaction between vitamin B and whey protein. Vitamin B quenched the intrinsic fluorescence of whey protein, mainly with a static nature (Kq > 2.0 × 1010 L/(mol·s)). The interactions between whey protein and vitamin B were mostly mediated by hydrogen bonds and van der Waals forces, as demonstrated by the thermodynamic parameters and molecular docking.

Bisphenol S exposure induces intestinal inflammation via altering gut microbiome.

Bisphenol S (BPS), a substitute for bisphenol A, is widely used in the manufacture of food packaging materials, raising concern over its toxicity. However, evidence is still lacking on whether gut microbiota involved in BPS induced intestinal inflammation in mammals, as well as its underlying mechanism. Using mouse BPS exposure model, we found intestinal inflammation characterized by shortened colon length, crypt distortion, macrophage accumulation and increased apoptosis. As for gut microbiota, 16s rRNA gene amplicon sequencing showed BPS exposure induced gut dysbiosis, including increased pro-inflammatory microbes such as Ileibacterium, and decreased anti-inflammatory genera such as Lactobacillus, Blautia and Romboutsia. Besides, LC-MS/MS-based untargeted metabolomic analysis indicated BPS impaired both bacteria and host metabolism. Additionally, transcriptome analysis of the intestine revealed abnormal gene expression in intestinal mucosal barrier and inflammation. More importantly, treating mice with antibiotics significantly attenuated BPS-induced gut inflammation via the regulation of both bacterial and host metabolites, indicating the role of gut microbiota. Collectively, BPS exposure induces intestinal inflammation via altering gut microbiota in mouse. This study provides the possibility of madecassic acid, an anti-inflammatory metabolite, to prevent BPS-induced intestinal inflammation and also new insights in understanding host-microbiota interaction in BPS toxicity.