Anxiety and depression in nasopharyngeal carcinoma patients and network analysis to identify central symptoms: A cross-sectional study from a high-incidence area.

PURPOSE: To determine the prevalence of anxiety and depression in patients with nasopharyngeal carcinoma (NPC) and to identify central symptoms and bridge symptoms among psychiatric disorders. METHODS: This cross-sectional study recruited patients with NPC in Guangzhou, China from May 2022, to October 2022. The General Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) were used for screening anxiety and depression, respectively. Network analysis was conducted to evaluate the centrality and connectivity of the symptoms of anxiety, depression, quality of life (QoL) and insomnia. RESULTS: A total of 2806 respondents with complete GAD-7 and PHQ-9 scores out of 3828 were enrolled. The incidence of anxiety in the whole population was 26.5% (depression, 28.5%; either anxiety or depression, 34.8%). Anxiety was highest at caner diagnosis (34.2%), while depression reached a peak at late-stage radiotherapy (48.5%). Both moderate and severe anxiety and depression were exacerbated during radiotherapy. Coexisting anxiety and depression occurred in 58.3% of those with either anxiety or depression. The generated network showed that anxiety and depression symptoms were closely connected; insomnia was strongly connected with QoL. "Sad mood", "Lack of energy", and "Trouble relaxing" were the most important items in the network. Insomnia was the most significant bridge item that connected symptom groups. CONCLUSION: Patients with NPC are facing alarming disturbances of psychiatric disorders; tailored strategies should be implemented for high-risk patients. Besides, central symptoms (sad mood, lack of energy, and trouble relaxing) and bridge symptoms (insomnia) may be potential interventional targets in future clinical practice.

Relationships among anxiety, depression, and health-related quality of life in adult epilepsy: A network analysis.

OBJECTIVE: Comorbid depression and anxiety in patients with epilepsy (PWE) are common and frequently under-treated, thus, causing poor health-related quality of life (HRQoL). However, little is known regarding the interconnections between anxious/depressive symptoms and the dimensions of HRQoL. Therefore, we conducted a network analysis to explore these relationships in detail among Chinese adult PWE. METHODS: A cohort of adult PWE was consecutively recruited from the First Affiliated Hospital of Chongqing Medical University. HRQoL, depression, and anxiety were measured with Quality of Life in Epilepsy Inventory-31, Neurological Disorders Depression Inventory for Epilepsy, and Generalized Anxiety Disorder 7-Item Scale, respectively. A regularized partial correlation network was constructed to investigate the interconnections between symptoms of anxiety/depression and the dimensions of HRQoL. We calculated expected influence (EI) and bridge expected influence (BEI) values to identify the most influential nodes. RESULTS: A total of 396 PWE were enrolled in this study, 78.1% of whom had focal onset epilepsy. The prevalence of anxiety and depression was 30.3% and 28.8%, respectively. The symptoms "frustrated" and "uncontrollable worry" had the highest EI values, whereas "emotional well-being", "seizure worry", "difficulty finding pleasure", and "nervousness or anxiety" had the highest BEI values. CONCLUSION: This study provides new insights into the relationships among anxiety, depression, and HRQoL. Critical central symptoms and bridge symptoms identified in the network might help to quickly identify PWE comorbid anxiety and depression in busy outpatient settings, thereby enabling early intervention and enhancing quality of life.

Immune persistence after different polio sequential immunization schedules in Chinese infants.

Trivalent oral poliovirus vaccine (tOPV) has been withdrawn and instead an inactivated poliovirus vaccine (IPV) and bivalent type 1 and type 3 OPV (bOPV) sequential immunization schedule has been implemented since 2016, but no immune persistence data are available for this polio vaccination strategy. This study aimed to assess immune persistence following different polio sequential immunization schedules. Venous blood was collected at 24, 36, and 48 months of age from participants who had completed sequential schedules of combined IPV and OPV in phase III clinical trials. The serum neutralizing antibody titers against poliovirus were determined, and the poliovirus-specific antibody-positive rates were evaluated. A total of 1104 participants were enrolled in this study. The positive rates of poliovirus type 1- and type 3-specific antibodies among the sequential immunization groups showed no significant difference at 24, 36, or 48 months of age. The positive rates of poliovirus type 2-specific antibody in the IPV-IPV-tOPV group at all time points were nearly 100%, which was significantly higher than the corresponding rates in other immunization groups (IPV-bOPV-bOPV and IPV-IPV-bOPV). Immunization schedules involving one or two doses of IPV followed by bOPV failed to maintain a high positive rate for poliovirus type 2-specific antibody.

Targeted arginine metabolomics combined with metagenomics revealed the potential mechanism of Pueraria lobata extract in treating myocardial infarction.

The extraction methods for traditional Chinese medicine (TCM) may have varying therapeutic effects on diseases. Currently, Pueraria lobata (PL) is mostly extracted with ethanol, but decoction, as a TCM extraction method, is not widely adopted. In this study, we present a strategy that integrates targeted metabolomics, 16 s rDNA sequencing technology and metagenomics for exploring the potential mechanism of the water extract of PL (PLE) in treating myocardial infarction (MI). Using advanced analytical techniques like ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), we comprehensively characterized PLE's chemical composition. Further, we tested its efficacy in a rat model of MI induced by ligation of the left anterior descending branch of the coronary artery (LAD). We assessed cardiac enzyme levels and conducted echocardiograms. UPLC-MS/MS was used to compare amino acid differences in serum. Furthermore, we investigated fecal samples using 16S rDNA sequencing and metagenomic sequencing to study intestinal flora diversity and function. This study demonstrated PLE's effectiveness in reducing cardiac injury in LAD-ligated rats. Amino acid metabolomics revealed significant improvements in serum levels of arginine, citrulline, proline, ornithine, creatine, creatinine, and sarcosine in MI rats, which are key compounds in the arginine metabolism pathway. Enzyme-linked immunosorbent assay (ELISA) results showed that PLE significantly improved arginase (Arg), nitric oxide synthase (NOS), and creatine kinase (CK) contents in the liver tissue of MI rats. 16 s rDNA and metagenome sequencing revealed that PLE significantly improved intestinal flora imbalance in MI rats, particularly in taxa such as Tuzzerella, Desulfovibrio, Fournierella, Oscillibater, Harryflintia, and Holdemania. PLE also improved the arginine metabolic pathway in the intestinal microorganisms of MI rats. The findings indicate that PLE effectively modulates MI-induced arginine levels and restores intestinal flora balance. This study, the first to explore the mechanism of action of PLE in MI treatment considering amino acid metabolism and intestinal flora, expands our understanding of the potential of PL in MI treatment. It offers fresh insights into the mechanisms of PL, guiding further research and development of PL-based medicines.

Clinical evaluation of photodynamic therapy for oral leukoplakia: a retrospective study of 50 patients.

BACKGROUND: Topical photodynamic therapy (PDT) has demonstrated encouraging results in the treatment of oral leukoplakia (OLK). However, data on the clinical efficacy of PDT in Chinese patients with OLK are still limited. METHODS: Fifty patients diagnosed with OLK were enrolled, including patients with various dysplastic tissues. All patients received topical PDT with 5-aminolevulinic acid (5-ALA) as a photosensitizer. Clinical efficacy was evaluated 4 weeks after treatment. Follow-up was performed every 3 months during the first year and every 6 months during the second year. RESULTS: The overall response rate was 68% (34/50): 12% (n = 6) complete and 56% (n = 28) partial responses. Aneuploidy was reduced in the patients with dysplastic lesions. Oral pain and local ulcers developed in 52% of the patients (n = 26). Patients with a long history of OLK including hyperplasia and dysplastic lesions, as well as those with non-homogenous lesions, were more likely to develop pain and ulcer. During follow-up, the recurrence rate of hyperplasia and dysplastic lesions was 32% (n = 16) and the malignant transformation rate of dysplastic lesions was 4% (n = 2). Lesions on the buccal mucosa were associated with recurrence (P = 0.044; OR: 0.108, 95% CI: 0.013-0.915). CONCLUSION: Topical 5-ALA-mediated PDT is an effective treatment for OLK, particularly for homogenous leukoplakia, with few side effects. The buccal mucosa may be a protective factor that can reduce recurrence.

Transcriptomic analysis approach towards an improved tolerance of Escherichia coli to gallic acid stress.

As a natural green additive, gallic acid has been widely used in food production. However, it can inhibit the physiological metabolism of Escherichia coli, which severely limits the ability and efficiency of gallic acid production. To explore the adaptation mechanism of E. coli under gallic acid stress and further explore the target of genetic modification, the effects of gallic acid stress on the fermentation characteristics of E. coli W3110 ATCC (82057) were investigated by cell biomass and cell morphometry. Moreover, transcriptome analysis was used to analyze the gene transcription level of E. coli W3110 ATCC (82057) to explore effects of gallic acid stress on important essential physiological processes. The results showed that under high concentration of gallic acid, the biomass of E. coli W3110 ATCC (82057) decreased significantly and the cells showed irregular morphology. Transcriptome analysis showed that E. coli W3110 ATCC (82057) improved its adaptive capacity through three strategies. First, genes of bamD, ompC, and ompF encoding outer membrane protein BamD, OmpC, and OmpC were decreased 5-, 31.1- and 8.1-fold, respectively, under gallic acid stress compared to the control, leading to the reduction of gallic acid absorption. Moreover, genes (mdtA, mdtB, mdtC, mdtD, mdtE, and mdtF) related to MdtABC multidrug efflux system and multidrug efflux pump MdtEF were up-regulated by1.0-53.0 folds, respectively, and genes (aaeA, aaeB, and aaeX) related to AaeAB efflux system were up-regulated by 8.0-13.3 folds, respectively, which contributed to the excretion of gallic acid. In addition, genes of acid fitness island also were up-regulated by different degrees under the stress of an acidic environment to maintain the stability of the intracellular environment. In conclusion, E. coli W3110 ATCC (82057) would enhance its tolerance to gallic acid by reducing absorption, increasing excretion, and maintaining intracellular environment stability. This study provides research ideas for the construction of engineered strains with high gallic acid yield.

The Identification of Fritillaria Species Using Hyperspectral Imaging with Enhanced One-Dimensional Convolutional Neural Networks via Attention Mechanism.

Combining deep learning and hyperspectral imaging (HSI) has proven to be an effective approach in the quality control of medicinal and edible plants. Nonetheless, hyperspectral data contains redundant information and highly correlated characteristic bands, which can adversely impact sample identification. To address this issue, we proposed an enhanced one-dimensional convolutional neural network (1DCNN) with an attention mechanism. Given an intermediate feature map, two attention modules are constructed along two separate dimensions, channel and spectral, and then combined to enhance relevant features and to suppress irrelevant ones. Validated by Fritillaria datasets, the results demonstrate that an attention-enhanced 1DCNN model outperforms several machine learning algorithms and shows consistent improvements over a vanilla 1DCNN. Notably under VNIR and SWIR lenses, the model obtained 98.97% and 99.35% for binary classification between Fritillariae Cirrhosae Bulbus (FCB) and other non-FCB species, respectively. Additionally, it still achieved an extraordinary accuracy of 97.64% and 98.39% for eight-category classification among Fritillaria species. This study demonstrated the application of HSI with artificial intelligence can serve as a reliable, efficient, and non-destructive quality control method for authenticating Fritillaria species. Moreover, our findings also illustrated the great potential of the attention mechanism in enhancing the performance of the vanilla 1DCNN method, providing reference for other HSI-related quality controls of plants with medicinal and edible uses.

Slow-digestive yeast protein concentrate: An investigation of its in vitro digestibility and digestion behavior.

Yeast protein concentrate, a by-product of the fermentation industry waste, is a potential alternative protein source with high nutritional quality, environmental sustainability, and functional properties. However, its digestibility and digestion behavior are poorly understood. In this study, we compared the in vitro digestion behavior of yeast protein concentrate and whey protein concentrate using simulated gastrointestinal conditions. We found that yeast protein concentrate had lower digestibility than whey protein concentrate (31.25% vs. 86.23% at 120 min of pepsin digestion and 75.12% vs. 95.2% at 120 min of pancreatin digestion). Yeast protein concentrate differed from whey protein concentrate in microstructure, secondary structure, and amino acid composition, which may affect its digestion behavior. Compared to whey protein concentrate, a higher level of ß-sheets and a lower zeta potential explain the slow-digesting property of yeast protein concentrate. Yeast protein concentrate also underwent depolymerization and Plastein reaction during digestion. These results provided valuable information for developing and applying yeast protein concentrate as an alternative to conventional animal protein.

[Hyperspectral imaging technology distinguishes between Puerariae Lobatae Radix and Puerariae Lobatae Caulis].

Puerariae Lobatae Radix, the dried root of Pueraria lobata, is a traditional Chinese medicine with a long history. Puerariae Lobatae Caulis as an adulterant is always mixed into Puerariae Lobatae Radix for sales in the market. This study employed hyperspectral imaging(HSI) to distinguish between the two products. VNIR lens(spectral scope of 410-990 nm) and SWIR lens(spectral scope of 950-2 500 nm) were used for image acquiring. Multi-layer perceptron(MLP), partial least squares discriminant analysis(PLS-DA), and support vector machine(SVM) were employed to establish the full-waveband models and select the effective wavelengths for the distinguishing between Puerariae Lobatae Caulis and Puerariae Lobatae Radix, which provided technical and data support for the development of quick inspection equipment based on HSI. The results showed that MLP model outperformed PLS-DA and SVM models in the accuracy of discrimination with full wavebands in VNIR, SWIR, and VNIR+SWIR lens, which were 95.26%, 99.11%, and 99.05%, respectively. The discriminative band selection(DBS) algorithm was employed to select the effective wavelengths, and the discrimination accuracy was 93.05%, 98.05%, and 98.74% in the three different spectral scopes, respectively. On this basis, the MLP model combined with the effective wavelengths within the range of 2 100-2 400 nm can achieve the accuracy of 97.74%, which was close to that obtained with the full waveband. This waveband can be used to develop quick inspection devices based on HSI for the rapid and non-destructive distinguishing between Puerariae Lobatae Radix and Puerariae Lobatae Caulis.

Synthesis of Imidazole-Based Deep Eutectic Solvents as Solid Lubricants: Lubricated State Transition.

The controllable character of the melting point of deep eutectic solvents (DESs) makes it easy to realize lubricated state transitions and produce excellent lubricating properties during friction. In this work, a series of novel imidazole-based DESs were synthesized to present a room-temperature solid state by shifting its eutectic point. Tribological test results show that the wear volume of these DESs decreases as the alkyl chains of the hydrogen bond donors increase. A proper deviation of the eutectic point in DESs produces stable lubricating properties. The present work provides a novel and simple method to prepare solid lubricants and enriches the use of DESs as lubricants. Simultaneously, the method expected to replace the use of conventional cutting fluids.

Identification of Turtle-Shell Growth Year Using Hyperspectral Imaging Combined with an Enhanced Spatial-Spectral Attention 3DCNN and a Transformer.

Turtle shell (Chinemys reecesii) is a prized traditional Chinese dietary therapy, and the growth year of turtle shell has a significant impact on its quality attributes. In this study, a hyperspectral imaging (HSI) technique combined with a proposed deep learning (DL) network algorithm was investigated for the objective determination of the growth year of turtle shells. The acquisition of hyperspectral images was carried out in the near-infrared range (948.72-2512.97 nm) from samples spanning five different growth years. To fully exploit the spatial and spectral information while reducing redundancy in hyperspectral data simultaneously, three modules were developed. First, the spectral-spatial attention (SSA) module was developed to better protect the spectral correlation among spectral bands and capture fine-grained spatial information of hyperspectral images. Second, the 3D convolutional neural network (CNN), more suitable for the extracted 3D feature map, was employed to facilitate the joint spatial-spectral feature representation. Thirdly, to overcome the constraints of convolution kernels as well as better capture long-range correlation between spectral bands, the transformer encoder (TE) module was further designed. These modules were harmoniously orchestrated, driven by the need to effectively leverage both spatial and spectral information within hyperspectral data. They collectively enhance the model's capacity to extract joint spatial and spectral features to discern growth years accurately. Experimental studies demonstrated that the proposed model (named SSA-3DTE) achieved superior classification accuracy, with 98.94% on average for five-category classification, outperforming traditional machine learning methods using only spectral information and representative deep learning methods. Also, ablation experiments confirmed the effectiveness of each module to improve performance. The encouraging results of this study revealed the potentiality of HSI combined with the DL algorithm as an efficient and non-destructive method for the quality control of turtle shells.

A nomogram model for predicting lower extremity deep vein thrombosis after gynecologic laparoscopic surgery: a retrospective cohort study.

Objective: To investigate the risk factors associated with lower extremity deep vein thrombosis (LEDVT) and to establish a predictive model for patients who undergo gynecologic laparoscopic surgery. Methods: A review of clinical data was conducted on patients who underwent gynecologic laparoscopic surgery between November 1, 2020, and January 31, 2022. Patients who developed LEDVT after surgery were included as the observation group, while the control group comprised patients who did not experience complications. Multivariate forward stepwise logistic regression models were used to identify independent risk factors associated with LEDVT. A nomogram model was then developed based on these risk factors. Results: A total of 659 patients underwent gynecologic laparoscopic surgery during the study period, and 52 (7.89%) of these patients developed postoperative LEDVT. Multivariate logistic regression analysis showed that older age (adjusted OR, 1.085; 95% CI [1.034-1.138]; P < 0.05), longer operation duration (adjusted OR, 1.014; 95% CI [1.009-1.020]; P < 0.05), shorter activated partial thromboplastin time (APTT) (adjusted OR, 0.749; 95% CI [0.635-0.884]; P < 0.05), higher D-dimer (adjusted OR, 4.929; 95% CI [2.369-10.255]; P < 0.05), higher Human Epididymis Protein 4 (HE4) (adjusted OR, 1.007; 95% CI [1.001-1.012]; P < 0.05), and history of hypertension (adjusted OR, 3.732; 95% CI [1.405-9.915]; P < 0.05) were all independent risk factors for LEDVT in patients who underwent gynecologic laparoscopic surgery. A nomogram model was then created, which had an area under the curve of 0.927 (95% CI [0.893-0.961]; P < 0.05), a sensitivity of 96.1%, and a specificity of 79.5%. Conclusions: A nomogram model that incorporates information on age, operation duration, APTT, D-dimer, history of hypertension, and HE4 could effectively predict the risk of LEDVT in patients undergoing gynecologic laparoscopic surgery, potentially helping to prevent the development of this complication.

Identification of growth years for Puerariae Thomsonii Radix based on hyperspectral imaging technology and deep learning algorithm.

Puerariae Thomsonii Radix (PTR) is not only widely used in disease prevention and treatment but is also an important raw material as a source of starch and other food. The growth years of PTR are closely related to its quality. The rapid and nondestructive identification of growth year is essential for the quality control of PTR and other traditional Chinese medicines. In this study, we proposed a convolutional neural network (CNN)-based classification framework in conjunction with hyperspectral imaging (HSI) technology for the rapid identification of the growth years of PTRs. Traditional treatment methods (i.e., multiplicative scatter correction, standard normal variate, and Savitzky-Golay smoothing) combined with machine learning algorithms (i.e., random forest, logistic regression, naive Bayes, and eXtreme gradient boost) were used as baseline models. Among them, the F1-score of CNN-based models based on PTRs' outer surfaces was over 90%, outperforming all the other baseline models. These results showed that it was feasible to use a deep learning algorithm in conjunction with HSI technology to identify the growth years of PTR. This method provides a fast, nondestructive, and simple method of identifying the growth years of PTR. It can be easily applied to other scenarios, such as for the identification of the locality or years of growth for other traditional Chinese herbs.

Preparing and Wear-Resisting Property of Al2O3/Cu Composite Material Enhanced Using Novel In Situ Generated Al2O3 Nanoparticles.

Al2O3/Cu composite material (ACCM) are highly suitable for various advanced applications owing to its excellent properties. In the present work, a combination of the solution combustion synthesis and hydrogen reduction method was first employed to prepare Al2O3/Cu composite powder (ACCP), and subsequently ACCM was prepared by employing spark plasma sintering (SPS) technique. The effect of Al2O3 contents and SPS temperatures on the properties (relative density, hardness, friction coefficient, and electrical conductivity, et al.) of ACCM were investigated in detail. The results indicated that ACCM was very dense, and microstructure was consisted of fine Al2O3 particles evenly distributed in the Cu matrix. With the increase of SPS temperature, the relative density and hardness of ACCM had first increased and then decreased. At 775 °C, the relative density and hardness had attained the maximum values of 98.19% and 121.4 HV, respectively. With the increase of Al2O3 content, although the relative density of ACCM had gradually decreased, nevertheless, its friction coefficient had increased. Moreover, with the increase of Al2O3 contents, the hardness of ACCM first increased and then decreased, and reached the maximum value (121.4 HV) with 3 wt.% addition. On the contrary, the wear rate of ACCM had first decreased and then increased with the increase of Al2O3 contents, and attained the minimum (2.32 × 10-5 mm3/(N.m)) with 3 wt.% addition.

Non-enzymatic browning of wine induced by monomeric flavan-3-ols: A review.

Non-enzymatic browning occurs widely in both white and red wines, and it has a huge impact on the color evolution and aging potential. Previous studies have proved that phenolic compounds, especially those with catechol groups, are the most important substrates involved in browning reactions of wine. This review focus on the current knowledge of non-enzymatic browning in wine resulting from monomeric flavan-3-ols. First, some relevant aspects of monomeric flavan-3-ols are introduced, including their structures, origins, chemical reactivities, as well as potential impacts on the organoleptic properties of wine. Second, the mechanism for non-enzymatic browning induced by monomeric flavan-3-ols is discussed, with an emphasis on the formation of yellow xanthylium derivatives, followed by their spectral properties and effects on the color change of wine. Finally, attentions are also be given to the factors that influence non-enzymatic browning, such as metal ions, light exposure, additives in winemaking, etc.

Pueraria montana Population Structure and Genetic Diversity Based on Chloroplast Genome Data.

Despite having a generally conserved structure, chloroplast genome data have been helpful for plant population genetics and evolution research. To mine Pueraria montana chloroplast genome variation architecture and phylogeny, we investigated the chloroplast variation architecture of 104 P. montana accessions from across China. P. montana's chloroplast genome showed high diversity levels, with 1674 variations, including 1118 single nucleotide polymorphisms and 556 indels. The intergenic spacers, psbZ-trnS and ccsA-ndhD, are the two mutation hotspot regions in the P. montana chloroplast genome. Phylogenetic analysis based on the chloroplast genome dataset supported four P. montana clades. P. montana variations were conserved among and within clades, which showed high gene flow levels. Most P. montana clades were estimated to have diverged at 3.82-5.17 million years ago. Moreover, the East Asian summer monsoon and South Asian summer monsoon may have accelerated population divergence. Our results show that chloroplast genome sequences were highly variable and can be used as molecular markers to assess genetic variation and relationships in P. montana.

Improving the Sustainability of Processing By-Products: Extraction and Recent Biological Activities of Collagen Peptides.

Society and consumers are increasingly concerned about food safety and the sustainability of food production systems. A significant amount of by-products and discards are generated during the processing of aquatic animals, which still needs to be fully utilized by the food industry. The management and sustainable use of these resources are essential to avoiding environmental pollution and resource waste. These by-products are rich in biologically active proteins, which can be converted into peptides by enzymatic hydrolysis or fermentation treatment. Therefore, exploring the extraction of collagen peptides from these by-products using an enzymatic hydrolysis technology has attracted a wide range of attention from numerous researchers. Collagen peptides have been found to possess multiple biological activities, including antioxidant, anticancer, antitumor, hypotensive, hypoglycemic, and anti-inflammatory properties. These properties can enhance the physiological functions of organisms and make collagen peptides useful as ingredients in food, pharmaceuticals, or cosmetics. This paper reviews the general methods for extracting collagen peptides from various processing by-products of aquatic animals, including fish skin, scales, bones, and offal. It also summarizes the functional activities of collagen peptides as well as their applications.

Isolation of a potential probiotic strain Bacillus amyloliquefaciensLPB-18 and identification of antimicrobial compounds responsible for inhibition of food-borne pathogens.

This study was carried out to screen a potential probiotic microbe with broad-spectrum antagonistic activity against food-borne pathogens and identify the antimicrobial compounds. Based on morphological and molecular analysis, a new Bacillus strain with the ability to produce effective antimicrobial agents was isolated from the breeding soil of earthworms and identified as having a close evolutionary footprint to Bacillus amyloliquefaciens. The antimicrobial substances produced by B. amyloliquefaciens show effective inhibition of Aspergillus flavus and Fusarium oxysporum in an agar diffusion assay. Antimicrobial agents were identified as a series of fengycin and its isoforms (fengycin A and fengycin B) after being submitted to RT-HPLC and MALDI-TOF MS analyses. To evaluate the probiotic activity of the B. amyloliquefaciens, antibiotic safety and viability of the isolated strain in a simulated gastrointestinal environment were carried out. The safety test result revealed that strain LPB-18 is susceptible to multiple common antibiotics. Moreover, acidic condition and bile salts assay were carried out, and the results revealed that it couble be a potential probiotic microbe B. amyloliquefaciens LPB-18 is good choice for biological strains in agricultural commodities and animal feedstuffs.

Identification and functional analysis of non-coding regulatory small RNA FenSr3 in Bacillus amyloliquefaciens LPB-18.

Bacillus amyloliquefaciens is an interesting microbe in the food processing and manufacturing industries. Non-coding small RNAs (sRNAs) have been shown to play a crucial role in the physiology and metabolism of bacteria by post-transcriptionally regulating gene expression. This study investigated the function of novel sRNA FenSr3 by constructing fenSr3 deficient strain and complementary strains in B. amyloliquefaciens LPB-18 , which were named LPN-18N and LPB-18P, respectively. The result showed significant differences in fengycin yield between strain LPB -18N and LPB-18P. The production of fengycin was significantly enhanced in B. amyloliquefaciens LPB-18N, compared with that of the strain LPB-18 from 190.908 mg/L to 327.598 mg/L. Moreover, the production of fengycin decreased from 190.464 mg/L to 38.6 mg/L in B . amyloliquefaciens LPB-18P. A comparative transcriptome sequencing was carried out to better understand the complex regulatory mechanism. Transcription analysis revealed that 1037 genes were differentially expressed between B. amyloliquefaciens LPB-18 and B. amyloliquefaciens LPB-18N, including the key regulatory genes in fatty acid, amino acid biosynthesis, and central carbon metabolism, which could provide sufficient quantities of building precursors for fengycin biosynthesis. The biofilm formation and sporulation was also enhanced in the strain LPB-18N, which indicates that FenSr3 could play a vital role in stress resistance and promotes survival in B. amyloliquefaciens. Some sRNAs involved in stress response have been identified in the literature, but their regulatory roles in fengycin production remain unclear. The study will contribute a novel perspective to the regulation mechanism of biosynthesis and the optimization of key metabolites of B. amyloliquefaciens.

Clinical relevance of serum lipids in the carcinogenesis of oral squamous cell carcinoma.

BACKGROUND: Dyslipidaemia is associated with cancers. However, the specific expression of serum lipids in oral potentially malignant disorders (OPMD) and oral squamous cell carcinoma (OSCC) remains unclear, and it remains unknown whether serum lipids are associated with the development of OPMD and OSCC. This study investigated the serum lipid profiles of OPMD and OSCC patients, and the association of serum lipids with the occurrence of OPMD and OSCC. METHODS: A total of 532 patients were recruited from the Affiliated Hospital of Stomatology, Nanjing Medical University. Serum lipid parameters including total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A (Apo-A), apolipoprotein B (Apo-B), and lipoprotein (a) (Lpa) were analysed, and clinicopathological data were collected for further analysis. Furthermore, a regression model was used to evaluate the relationship between serum lipids and the occurrence of OSCC and OPMD. RESULTS: After adjusting for age and sex, no significant differences were observed in serum lipid or body mass index (BMI) between OSCC patients and controls (P > 0.05). HDL-C, Apo-A, and Apo-B levels were lower in OSCC patients than in OPMD patients (P < 0.05); HDL-C and Apo-A levels were higher in OPMD patients than in controls (P < 0.05). Furthermore, female OSCC patients had higher Apo-A and BMI values than males. The HDL-C level was lower in patients under 60 years of age than in elders (P < 0.05); and age was related to a higher risk of developing OSCC. Female patients with OPMD had higher TC, HDL-C, and Apo-A levels than males (P < 0.05); OPMD patients over 60 years of age had higher HDL-C than youngers (P < 0.05), whereas the LDL-C level was lower in elders (P < 0.05). The HDL-C and BMI values of the patients with oral leukoplakia (OLK) with dysplasia were more elevated than those of the oral lichen planus group, and the LDL-C, and Apo-A levels in patients with OLK with dysplasia were decreased (P < 0.05). Sex, high HDL-C and Apo-A values were associated with the development of OPMD. CONCLUSION: Serum lipids exhibited certain differences according to the occurrence and development of OSCC; high levels of HDL-C and Apo-A might be markers for predicting OPMD.