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ABSTRACTThe occurrence and progression of tumors are often accompanied by disruptions in the gut microbiota. Inversely, the impact of the gut microbiota on the initiation and progression of cancer is becoming increasingly evident, influencing the tumor microenvironment (TME) for both local and distant tumors. Moreover, it is even suggested to play a significant role in the process of tumor immunotherapy, contributing to high specificity in therapeutic outcomes and long-term effectiveness across various cancer types. Probiotics, with their generally positive influence on the gut microbiota, may serve as effective agents in synergizing cancer immunotherapy. They play a crucial role in activating the immune system to inhibit tumor growth. In summary, this comprehensive review aims to provide valuable insights into the dynamic interactions between probiotics, gut microbiota, and cancer. Furthermore, we highlight recent advances and mechanisms in using probiotics to improve the effectiveness of cancer immunotherapy. By understanding these complex relationships, we may unlock innovative approaches for cancer diagnosis and treatment while optimizing the effects of immunotherapy.

AbstractThis paper proposes a new testing method, phased array ultrasonic testing, for the internal defects of gear teeth, which can be used to inspect the teeth of final products, breaking the limitations of incomplete volume coverage of conventional ultrasonic testing. This paper mainly discusses the inspection process of phased array ultrasonic testing, and verifies the feasibility of phased array ultrasonic testing for gear teeth defects of finished products by using physical and chemical inspection technology. The practical application results show that the phased array ultrasonic testing technology uses sector scanning mode to scan the area comprehensively between the pitch circle and the base circle, and the inspection image displayed by the equipment is intuitive, which can clearly identify defects. The number of defects inspected by phased array ultrasonic testing is consistent with the results of the physical and chemical inspection technology. The above summary shows that phased array ultrasonic testing is feasible, and the test results are reliable.

Heat stress severely affects the yield and quality of maize. Melatonin (N-acetyl-5-methoxy-tryptamin, MT) plays an important role in various types of stress resistance in plants, including heat tolerance. Enolase (ENO, 2-phospho-D-glycerate hydrolyase) contributes to plant growth, development, and stress response. As of now, the molecular mechanisms by which MT and ENO1 affect heat tolerance are unknown. In our research, we have revealed that heat stress (H) and heat stress + MT (MH) treatment upregulate ZmENO1 expression levels by 15 and 20 times, respectively. ZmENO1 overexpression and mutant maize lines were created by transgenic and genome editing. These results illustrate that heat stress has a significant impact on the growth of maize at the seedling stage. However, ZmENO1-OE lines showed a lower degree of susceptibility to heat stress, whereas the mutant exhibited the most severe effects. Under heat stress, exogenous application of MT improves heat resistance in maize. The ZmENO1-OE lines exhibited the best growth and highest survival rate, while the zmeno1 mutants showed the least desirable results. Following treatment with H and MH, the level of MT in ZmENO1-OE lines exhibited the greatest increase and reached the maximum value, whereas the level of MT in the zmeno1 mutant was the lowest. Heat stress decreased the maize’s relative water content and fresh weight, although ZmENO1-OE lines had the highest and zmeno1 mutants had the lowest. Heat stress led to an increase in the levels of MDA, hydrogen peroxide, and superoxide in all plants. Additionally, the ionic permeability and osmotic potential of the plants were significantly increased. However, the levels of MT were decreased in all plants, with the greatest decrease observed in the ZmENO1-OE lines. Interestingly, the zmeno1 mutant plants had the highest expression levels of MT. Heat stress-induced upregulation of ZmSOD, ZmPOD, ZmAPX, ZmCAT, ZmP5CS, and ZmProDH in all plants. However, the ZmENO1-OE lines exhibited the greatest increase in expression levels, while the zmeno1 mutants showed the lowest increase following MT spraying. The patterns of SOD, POD, APX, and CAT enzyme activity, as well as proline and soluble protein content, aligned with the variations in the expression levels of these genes. Our findings indicate that MT can upregulate the expression of the ZmENO1 gene. Upregulating the ZmENO1 gene resulted in elevated expression levels of ZmSOD, ZmPOD, ZmAPX, ZmCAT, ZmP5CS, and ZmProDH. This led to increased activity of antioxidant enzymes and higher levels of osmoregulatory substances. Consequently, it mitigated the cell membrane damage caused by heat stress and ultimately improved the heat resistance of maize. The results of this study provide genetic resources for molecular design breeding and lay a solid foundation for further exploring the molecular mechanism of MT regulation of heat stress tolerance in maize.

Abstract Background The existence of the gut microbiota produces an “individual drug reaction.” As members of the intestinal microbiota, probiotics, although they have prebiotic functions, may accelerate the degradation of drugs, thereby affecting drug efficacy. Lovastatin is one of the well-recognized lipid-lowering drugs. Its main action site is the liver. Therefore, if it is degraded in advance by gastrointestinal probiotics, its efficacy may be reduced. Results Here, we designed a two-stage experiment in vitro and in vivo to explore the degradation of lovastatin by probiotics. In vitro, the degradation of lovastatin by 83 strains of Lactiplantibacillus plantarum and the “star strain” Lacticaseibacillus paracasei strain Shirota was investigated by high-performance liquid chromatography (HPLC). The results showed that probiotics could degrade lovastatin to varying degrees. Subsequently, we selected Lactiplantibacillus plantarum A5 (16.87%) with the strongest ability to degrade lovastatin, Lactiplantibacillus plantarum C3 (4.61%) with the weakest ability to degrade lovastatin and Lacticaseibacillus paracasei strain Shirota (17.6%) as representative probiotics for in vivo experiments. In vivo, the therapeutic effect of lovastatin combined with probiotics on golden hamsters with mixed hyperlipidemia was evaluated by measuring blood indicators, intestinal microbiota metagenomic sequencing, and the liver transcriptome. The results showed that the intake of probiotics did not affect the efficacy of lovastatin and could slow the inflammatory reaction of the liver. Conclusions The supplementation of probiotics produced beneficial metabolites in the intestine by promoting beneficial microbes. Intestinal metabolites affected the expression of the liver genes through the gut-liver axis, increased the relative content of the essential amino acids, and finally improved the liver inflammatory response of the host. This study aims to reveal the impact of probiotics on the human body from a unique perspective, suggesting the impact of taking probiotics while taking drugs. Video Abstract

ABSTRACT Adaptive evolutionary changes can precede the ecological changes in the gut microbial communities under constant host selection pressure, yet their association with host diseased status was underexplored. Explore shared disease-associated single-nucleotide variants (SNVs) in gut microbes spanning diverse human diseases. We performed a meta-analysis of 1,711 gut metagenomic samples from 16 case-control studies spanning 12 human diseases and included an additional 446-member cohort for validation. Overall, healthy individuals carried more mutated resident gut microbes, and more SNVs, mainly involving the short-chain fatty acids (SCFAs) producing bacteria. Furthermore, the widespread differences in base variant bias of gut microbes were observed between healthy and nonhealthy subjects suggesting divergent gut microbial evolutionary directions under different host medical conditions. We further found that nonsynonymous SNVs can lead to the loss of function of four SCFA-production genes in nonhealthy populations, among which two genes (i.e., ack and scpC) from Faecalibacterium prausnitzii C and Bacteroides stercoris, respectively, were externally validated. Subsequently, we developed a novel gut microbiome health index based on the SNV rate of all mutated strains, classifying host health states with 74.23% accuracy, and validated with high accuracy (AUROC = 69.28%). Our study highlights the importance of employing the genetic variability in gut microbiome to characterize the gut microbial adaptation that can also predict human chronic diseases.IMPORTANCEMost studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

An increasing number of studies have widely recognized that the gut mycobiota and bacteriophages are closely related to human health and disease, although little is known about the responses of fungi and phages that are induced by probiotics. In this study, based on published longitudinal cohorts, a meta-analysis of intestinal fungi and bacteriophages after probiotic consumption was performed. On the fungi, our results showed that probiotics had an effect size on the composition of intestinal fungi, and the strain specificity of probiotics were the most important influencing factors. In terms of phage, probiotics regulated the gut microbiome, which led to elevation and diminishment of multiple phages in the gut, although dramatic changes did not occur in the diversity and structure of intestinal bacteriophages after intervention with probiotics. Our study extended the understanding of the effects of probiotics on intestinal fungi and bacteriophages.

The protein phosphatase PP2C plays an important role in plant responses to stress. Therefore, the identification of maize PP2C genes that respond to drought stress is particularly important for the improvement and creation of new drought-resistant assortments of maize. In this study, we identified 102 ZmPP2C genes in maize at the genome-wide level. We analyzed the physicochemical properties of 102 ZmPP2Cs and constructed a phylogenetic tree with Arabidopsis. By analyzing the gene structure, conserved protein motifs, and synteny, the ZmPP2Cs were found to be strongly conserved during evolution. Sixteen core genes involved in drought stress and rewatering were screened using gene co-expression network mapping and expression profiling. The qRT-PCR results showed 16 genes were induced by abscisic acid (ABA), drought, and NaCl treatments. Notably, ZmPP2C15 exhibited a substantial expression difference. Through genetic transformation, we overexpressed ZmPP2C15 and generated the CRISPR/Cas9 knockout maize mutant zmpp2c15. Overexpressing ZmPP2C15 in Arabidopsis under drought stress enhanced growth and survival compared with WT plants. The leaves exhibited heightened superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX), and catalase (CAT) activities, elevated proline (Pro) content, and reduced malondialdehyde (MDA) content. Conversely, zmpp2c15 mutant plants displayed severe leaf dryness, curling, and wilting under drought stress. Their leaf activities of SOD, POD, APX, and CAT were lower than those in B104, while MDA was higher. This suggests that ZmPP2C15 positively regulates drought tolerance in maize by affecting the antioxidant enzyme activity and osmoregulatory substance content. Subcellular localization revealed that ZmPP2C15 was localized in the nucleus and cytoplasm. Yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) experiments demonstrated ZmPP2C15’s interaction with ZmWIN1, ZmADT2, ZmsodC, Zmcab, and ZmLHC2. These findings establish a foundation for understanding maize PP2C gene functions, offering genetic resources and insights for molecular design breeding for drought tolerance.

Nuclear factor Y (NF-Y) genes play important roles in many biological processes, such as leaf growth, nitrogen nutrition, and drought resistance. However, the biological functions of these transcription factor family members have not been systematically analyzed in maize. In the present study, a total of 52 ZmNF-Y genes were identified and classified into three groups in the maize genome. An analysis of the evolutionary relationship, gene structure, and conserved motifs of these genes supports the evolutionary conservation of NF-Y family genes in maize. The tissue expression profiles based on RNA-seq data showed that all genes apart from ZmNF-Y16, ZmNF-YC15, and ZmNF-YC17 were expressed in different maize tissues. A weighted correlation network analysis was conducted and a gene co expression network method was used to analyze the transcriptome sequencing results; six core genes responding to drought and rewatering were identified. A real time fluorescence quantitative analysis showed that these six genes responded to high temperature, drought, high salt, and abscisic acid (ABA) treatments, and subsequent restoration to normal levels. ZmNF-YC12 was highly induced by drought and rewatering treatments. The ZmNF-YC12 protein was localized in the nucleus, and the Gal4-LexA/UAS system and a transactivation analysis demonstrated that ZmNF-YC12 in maize (Zea mays L.) is a transcriptional activator that regulates drought resistance and recovery ability. Silencing ZmNF-YC12 reduced net photosynthesis, chlorophyll content, antioxidant (superoxide dismutase, catalase, peroxidase and ascorbate peroxidase) system activation, and soluble protein and proline contents; it increased the malondialdehyde content, the relative water content, and the water loss rate, which weakened drought resistance and the recoverability of maize. These results provide insights into understanding the evolution of ZmNF-Y family genes in maize and their potential roles in genetic improvement. Our work provides a foundation for subsequent functional studies of the NF-Y gene family and provides deep insights into the role of the ZmNF-YC12 regulatory network in controlling drought resistance and the recoverability of maize.

Chenchen Ma, Chengcheng Zhang, and Denghui Chen et al. examine how probiotic consumption impacts gut microbiota composition in human and mice through a global, cross-cohort metagenomic analysis. Their results suggest that probiotic consumption may result in widespread variation among the native microbiota in both the human and mouse gut.

Hepatocellular carcinoma (HCC) is one of the most malignant tumors with persistently high morbidity and mortality. However, the expression, prognostic and clinical significance of FAM189 family genes in HCC remain largely unknown. In this study, the expression levels of FAM189 family genes in HCC were analyzed through TCGA-LIHC and ICGC-LIRI-JP cohorts, and further validated in multiple independent GEO datasets. It was found that the expression of FAM189B was significantly upregulated in HCC tumor tissues, while the expression of FAM189A1 and FAM189A2 was not significantly changed between tumor and adjacent tissues. Further analysis revealed that upregulated copy number variation contributed to increased expression of FAM189B in HCC. Survival analysis showed that highly expressed FAM189B was significantly correlated with unfavorable prognosis, including overall survival, disease-specific survival, and progression-free interval. Univariate and multivariate Cox regression analysis showed that FAM189B was a potential novel prognosis factor for HCC patients. In addition, the association between FAM189B expression and clinical and molecular characteristics was analyzed. High expression of FAM189B was associated with high AFP level, high predicted risk metastasis signature, and TP53 mutation, while there was no significant association between FAM189B expression and cancer stage or tumor grade of HCC. Gene set enrichment analysis revealed that highly expressed FAM189B was closely related with signal pathways and biological processes associated with cell proliferation and cell cycle in HCC. In conclusion, this study suggested that FAM189B was highly expressed in HCC and highly expressed FAM189B may serve as an effective prognostic indicator and a potential therapeutic target for HCC patients.

Early adversity can cause malfunction of the visual system in adulthood. Adult female but not male mice undergoing early chronic mild stress (ECMS) maintain ocular dominance (OD) plasticity after the critical period. How early stressful experiences have a long-term impact on it is largely unknown. Here, we observed a wide distribution of corticotropin-releasing factor (CRF)-positive neurons, which mainly colocalized with a subpopulation of GABAergic interneurons in the mouse primary visual cortex (V1). Optogenetic activation of CRF-positive neurons transfected with AAV-ChR2 evoked inhibitory currents in nearby pyramidal cells. ECMS induced a reduction in the expression of CRF mRNA in adult mouse V1. Chemogenetic activation of V1 CRF neurons impaired OD plasticity in adult ECMS females. We further showed that local administration of the corticotropin releasing factor receptor 1 (CRFR1) antagonist via an osmotic minipump into the visual cortex mimicked OD plasticity in adult ECMS females. Whole-cell recording in layer 2/3 pyramidal neurons revealed that the CRFR1 antagonist reduced the short-term depression (STD) of evoked inhibitory postsynaptic current (IPSC) in females but not in males. Likewise, CRF agonists have the opposite effect. In summary, our findings indicate that the local CRF-CRFR1 system within V1 may mediate the long-term and sex-dependent effect of early stress experiences on visual plasticity and provide a target for the prevention of visual deficits in adults with a history of early-life adversity.

Abstract The intestinal microbiota is a crucial environmental factor in the development of inflammatory bowel disease (IBD). The abundance of Faecalibacterium prausnitzii is significantly decreased in IBD patients, which is used as a biomarker for IBD diagnosis. However, this can be observed in both IBD and colorectal cancer, which would confound the diagnostic results. Thus, we first established a new model for predicting Crohn's disease (CD) with high precision according to gene characteristics based on single nucleotide variants (SNVs). Next, five gene markers belonging to two species, F. prausnitzii and Eubacterium rectale, that were enriched in the CD group were obtained to build a CD prediction model, and high accuracy in distinguishing the CD and control groups was observed in the discovery (area under curve [AUC] = 91.13%) and validation cohorts (AUC = 79.55%). The model still maintained high accuracy after expanding the healthy cohort (AUC = 89.75%). High disease specificity in distinguishing CD and CRC groups (AUC = 95.74%) was also proven. This study establishes a novel diagnostic method for predicting IBD that also provides unprecedented insight for the early, painless diagnosis of other non‐communicable diseases.

Abstract Background Improving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods. Results We combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10–70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice. Conclusions Collectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans. Video abstract

Both hemispheres connect with each other by excitatory callosal projections, and whether inhibitory interneurons, usually believed to have local innervation, engage in transcallosal activity modulation is unknown. Here, we used optogenetics in combination with cell-type-specific channelrhodopsin-2 expression to activate different inhibitory neuron subpopulations in the visual cortex and recorded the response of the entire visual cortex using intrinsic signal optical imaging. We found that optogenetic stimulation of inhibitory neurons reduced spontaneous activity (increase in the reflection of illumination) in the binocular area of the contralateral hemisphere, although these stimulations had different local effects ipsilaterally. The activation of contralateral interneurons differentially affected both eye responses to visual stimuli and, thus, changed ocular dominance. Optogenetic silencing of excitatory neurons affects the ipsilateral eye response and ocular dominance in the contralateral cortex to a lesser extent. Our results revealed a transcallosal effect of interneuron activation in the mouse visual cortex.

Abstract Background Maize (Zea mays) ear length, which is an important yield component, exhibits strong heterosis. Understanding the potential molecular mechanisms of ear-length heterosis is critical for efficient yield-related breeding. Results Here, a joint netted pattern, including six parent-hybrid triplets, was designed on the basis of two maize lines harboring long (T121 line) and short (T126 line) ears. Global transcriptional profiling of young ears (containing meristem) was performed. Multiple comparative analyses revealed that 874 differentially expressed genes are mainly responsible for the ear-length variation between T121 and T126 lines. Among them, four key genes, Zm00001d049958, Zm00001d027359, Zm00001d048502 and Zm00001d052138, were identified as being related to meristem development, which corroborated their roles in the superior additive genetic effects on ear length in T121 line. Non-additive expression patterns were used to identify candidate genes related to ear-length heterosis. A non-additively expressed gene (Zm00001d050649) was associated with the timing of meristematic phase transition and was determined to be the homolog of tomato SELF PRUNING, which assists SINGLE FLOWER TRUSS in driving yield-related heterosis, indicating that Zm00001d050649 is a potential contributor to drive heterotic effect on ear length. Conclusion Our results suggest that inbred parents provide genetic and heterotic effects on the ear lengths of their corresponding F1 hybrids through two independent pathways. These findings provide comprehensive insights into the transcriptional regulation of ear length and improve the understanding of ear-length heterosis in maize.

Abstract Background Numerous studies have reported the health-promoting effects of exopolysaccharides (EPSs) in in vitro models; however, a functional evaluation of EPSs will provide additional knowledge of EPS-microbe interactions by in vivo intestinal microbial model. In the present study, high-throughput amplicon sequencing, short-chain fatty acid (SCFAs) and intestinal inflammation evaluation were performed to explore the potential benefits of exopolysaccharides (EPSs) and EPS-producing Lactobacillus (HNUB20 group) using the healthy zebrafish (Danio rerio) model. Results The results based on microbial taxonomic analysis revealed that the abundance of four genera, Ochrobactrum, Sediminibacterium, Sphingomonas and Sphingobium, were increased in the control group in comparison to HNUB20 group. Pelomonas spp. levels were significantly higher and that of the genera Lactobacillus and Brachybacterium were significantly decreased in EPS group compared with control group. PICRUSt based functional prediction of gut microbiota metabolic pathways indicated that significantly lower abundance was found for transcription, and membrane transport, whereas folding, sorting and degradation and energy metabolism had significantly higher abundance after HNUB20 treatment. Two metabolic pathways, including metabolism and endocrine functions, were more abundant in the EPS group than control group. Similar to the HNUB20 group, transcription was also decreased in the EPS group compared with the control group. However, SCFAs and immune indexes indicated EPS and HNUB20 performed limited efficacy in the healthy zebrafish. Conclusions The present intestinal microbial model-based study indicated that EPSs and high-yield EPS-producing Lactobacillus can shake the structure of intestinal microbiota, but cannot change SCFAs presence and intestinal inflammation.

ABSTRACT With the increasing prevalence of colorectal cancer (CRC), extending the present biomarkers for the diagnosis of colorectal cancer is crucial. Previous studies have highlighted the importance of bacteriophages in gastrointestinal diseases, suggesting the potential value of gut phageome in early CRC diagnostic. Here, based on 317 metagenomic samples of three discovery cohorts collected from China (Hong Kong), Austria, and Japan, five intestinal bacteriophages, including Fusobacterium nucleatum, Peptacetobacter hiranonis, and Parvimonas micra phages were identified as potential CRC biomarkers. The five CRC enriched bacteriophagic markers classified patients from controls with an area under the receiver-operating characteristics curve (AUC) of 0.8616 across different populations. Subsequently, we used a total of 80 samples from China (Hainan) and Italy for validation. The AUC of the validation cohort is 0.8197. Moreover, to further explore the specificity of the five intestinal bacteriophage biomarkers in a broader background, we performed a confirmatory meta-analysis using two inflammatory bowel disease cohorts, ulcerative colitis (UC) and Crohn's disease (CD). Excitingly, we observed that the five CRC-enriched phage markers also exhibited high discrimination in UC (AUC = 78.02%). Unfortunately, the five CRC-rich phage markers did not show high resolution in CD (AUC = 48.00%). The present research expands the potential of microbial biomarkers in CRC diagnosis by building a more accurate classification model based on the human gut phageome, providing a new perspective for CRC gut phagotherapy. IMPORTANCE Worldwide, by 2020, colorectal cancer has become the third most common cancer after lung and breast cancer. Phages are strictly host-specific, and this specificity makes them more accurate as biomarkers, but phage biomarkers for colorectal cancer have not been thoroughly explored. Therefore, it is crucial to extend the existing phage biomarkers for the diagnosis of colorectal cancer. Here, we innovatively constructed a relatively accurate prediction model, including: three discovery cohorts, two additional validation cohorts and two cross-disease cohorts. A total of five possible biomarkers of intestinal bacteriophages were obtained. They are Peptacetobacter hiranonis Phage, Fusobacterium nucleatum animalis 7_1 Phage, Fusobacterium nucleatum polymorphum Phage, Fusobacterium nucleatum animalis 4_8 Phage, and Parvimonas micra Phage. This study aims at identifying fine-scale species-strain level phage biomarkers for colorectal cancer diseases, so as to expand the existing CRC biomarkers and provide a new perspective for intestinal phagocytosis therapy of colorectal cancer.

Preoperative, non-invasive, and accurate identification of the pathological subtypes of pulmonary ground glass nodules (GGNs) play an important role in the precise selection of clinical surgical operations and individualized treatment plans. Efforts have been made for the classification of pathological subtypes of GGNs, but most existing methods focus on benign or malignant diagnosis of GGNs by means of a one-time computed tomography image (CTI), which fails to capture the nodule development based on follow-up CTI. In this paper, a novel method for subtype classification based on follow-up CTIs is presented as a viable option to the existing one-time CTI-based approach. A total of 383 follow-up CTIs with GGNs from 146 patients was collected and retrospectively labeled via posterior surgical pathology. Feature extraction is performed individually to the follow-up CTIs. The extracted feature differences were represented as a vector, which was then used to construct a set of vectors for all the patients. Finally, a subspace K-nearest neighbor classifier was built to predict the pathological subtypes of GGNs. Experimental validation confirmed the efficacy of the new method over the existing method. Results showed that the accuracy of the new method could reach 72.5%, while the existing methods had an upper bound of 67.5% accuracy. Subsequent three-category comparison experiments were also performed to demonstrate that the new method could increase the accuracy up to 21.33% compared to the existing methods that use one-time CTI.

The apolipoprotein B mRNA editing enzyme catalytic subunit 3G (APOBEC3G) converts cytosine to uracil in DNA/RNA. Its role in resisting viral invasion has been well documented. However, its expression pattern and potential function in AML remain unclear. In this study, we carried out a bioinformatics analysis and revealed that the expression of APOBEC3G was significantly upregulated in AML, and high expression of APOBEC3G was significantly associated with short overall survival (OS). APOBEC3G expression was especially increased in non-M3AML, and correlated with the unfavorable cytogenetic risks. Additionally, Cox regression analyses indicated APOBEC3G is a hazard factor that cannot be ignored for OS of AML patients. In molecular docking simulations, the natural product crotonoside was found to interact well with APOBEC3G. The expression of APOBEC3G is the highest in KG-1 cells, and the treatment with crotonoside can reduce the expression of APOBEC3G. Crotonoside can inhibit the viability of different AML cells in vitro, arrest KG-1 and MV-4-11 cells in the S phase of the cell cycle and affect the expression of cycle-related proteins, and induce cell apoptosis. Therefore, APOBEC3G could be a potential drug target of crotonoside, and crotonoside can be considered as a lead compound for APOBEC3G inhibition in non-M3 AML.

Statistical Learning Theory (SLT) plays an important role in prediction estimation and machine learning when only limited samples are available. At present, determining how many samples are necessary under given circumstances for prediction accuracy is still an unknown. In this paper, the medical diagnosis on lung cancer is taken as an example to solve the problem. Invasive adenocarcinoma (IA) is a main type of lung cancer, often presented as ground glass nodules (GGNs) in patient’s CT images. Accurately discriminating IA from non-IA based on GGNs has important implications for taking the right approach to treatment and cure. Support Vector Machine (SVM) is an SLT application and is used to classify GGNs, wherein the interrelation between the generalization and the lower bound of necessary sampling numbers can be effectively recovered. In this research, to validate the interrelation, 436 GGNs were collected and labeled using surgical pathology. Then, a feature vector was constructed for each GGN sample through the fully connected layer of AlexNet. A 10-dimensional feature subset was then selected with the p-value calculated using Analysis of Variance (ANOVA). Finally, four sets with different sample sizes were used to construct an SVM classifier. Experiments show that a theoretical estimate of minimum sample size is consistent with actual values, and the lower bound on sample size can be solved under various generalization requirements.

A kind of terpyridine derivative (NH2-Tpy) in which the amino was incorporated by a short alkyl chain was synthesized. Through grafting of terpyridine units into the hydrophilic copolymers of maleic anhydride and acrylic acid PAAMa via the reaction of the amino groups in NH2-Tpy and the maleic anhydride units, a series of gelator polymers—P1, P2, and P3—containing different contents of terpyridine units was synthesized. Under coordination of Ni2+ and terpyridine ligands in linear polymers, the supramolecular hydrogels H1, H2, and H3 with different cross-linking degrees were prepared. The linear polymers P1–P3 had a strong absorption peak at about 290 nm in the UV-vis spectra which was attributed to π–π* transition, and there was a new peak at about 335 nm led by the metal-to-ligands charge transfer (MLCT) when coordinated with Ni2+ ions. According to the rheological behaviors, the storage modulus (G′) was larger than the loss modulus (G′′). These hydrogels showed typical gel-like characteristics when the terpyridine content of the hydrogels exceeded 10%, and the hydrogels showed liquid-like characteristics when the terpyridine content of the hydrogels was less than 7%. The results of the micromorphological investigation of the xerogels from SEM illustrated the metal–terpyridine coordination cross-linking could have an important influence on the microstructures of the resulting hydrogels. Furthermore, these hydrogels based on supramolecular cross-links exhibited reversible solution–gel transition at different environmental temperatures. At the same time, the equilibrium swelling of the supramolecular hydrogels was 8.0–12.3 g/g, which increased with the decrease in the content of the terpyridine units in the resulting hydrogels.

Melatonin has been widely used as a “probiotic agent” capable of producing strong neurotransmitter secretion regulatory effects, and the microbiota-gut-brain axis-related studies have also highlighted the role of the gut microbiota in neuromodulation. In the present study, a zebrafish neural hyperactivity model was established using caffeine induction to explore the regulatory effects of melatonin and probiotic on neurotransmitter secretion disorder in zebrafish. Disorders of brain neurotransmitter secretion (dopamine, γ-aminobutyric acid, and 5-hydroxytryptamine) caused by caffeine were improved after interference treatment with melatonin or probiotic. Shotgun metagenomic sequencing demonstrated that the melatonin-treated zebrafish gradually restored their normal intestinal microbiota and metabolic pathways. Germ-free (GF) zebrafish were used to verify the essential role of intestinal microbes in the regulation of neurotransmitter secretion. The results of the neurotransmitter and short-chain fatty acid determination revealed that the effect on the zebrafish in the GF group could not achieve that on the zebrafish in the melatonin group after adding the same dose of melatonin. The present research revealed the potential mode of action of melatonin through the microbiota-gut-brain axis to regulate the disruption of neurotransmitter secretion, supporting the future development of psychotropic drugs targeting the intestinal microbiota.

A simple route to the preparation of benzodipyrrolidone (BDP) based monomeric building blocks containing 2,2′:6′,2″-terpyridines is reported from a common precursor 4′-(4-pinacolatoboronphenyl)-2,2′:6′,2″-terpyridine via Suzuki coupling reaction. Self-assembly polymerization with ruthenium (II) ions under mild conditions yielded a series of novel metallo-supramolecular polymers with weak donor-acceptor (D-A) structures based on benzodipyrrolidone. The structure of the bridge connected BDP with terpyridine have a significant impact on the wavelength and intensity of the intramolecular charge transfer (ICT) absorption peak. The resulting metallo-polymers exhibited strong double absorption bands around 315 nm and 510 nm involved in π-π* transitions and ICT or metal to ligand charge transfer (MLCT) absorption bands. The forming of D-A structure and coordination with ruthenium (II) ions is favorable to narrow the energy gap and the energy gaps of the resulting metallo-supramolecular polymers are 2.01 and 1.62 eV, respectively.

In this work, chemical localization, structural changes, and antioxidant properties of tuna colloidal particles (TCPs) in boiling tuna head soup were examined. The results demonstrated that TCPs might be core–shell colloidal spherical structures. The hydrophobic core consisted of triglycerides and chloride ions. The hydrophilic shell layer consisted of chloride ions, sodium ions, phospholipids, protein, and glycosyl molecules. Coalescence of TCPs occurred during the boiling process, and water may enter the hydrophobic core of TCPs after the boiling time of 60 min. TCPs had excellent antioxidant properties against H2O2-induced human umbilical vein endothelial cell injury. It might be resulted from that TCPs could decrease cell apoptosis proportion and downregulate mRNA levels of endoplasmic reticulum-bounded chaperone protein glucose-related protein (GRP78), C/EBP homologous protein (CHOP), and activating transcription factor-4 (ATF4). This work can provide useful basic information to understand the colloidal system in foods, especially in soup. In addition, it may also promote the potential high-value-added utilization of aquatic by-products.

Current metagenomic species-based colorectal cancer (CRC) microbial biomarkers may confuse diagnosis because the genetic content of different microbial strains, even those belonging to the same species, may differ from 5% to 30%. Here, a total of 7549 non-redundant single nucleotide variants (SNVs) were annotated in 25 species from 3 CRC cohorts (n = 249). Then, 22 microbial SNV markers that contributed to distinguishing subjects with CRC from healthy subjects were identified by the random forest algorithm to construct a novel CRC predictive model. Excitingly, the predictive model showed high accuracy both in the training (AUC = 75.35%) and validation cohorts (AUC = 73.08%-88.02%). We further explored the specificity of these SNV markers in a broader background by performing a meta-analysis across 4 metabolic disease cohorts. Among these SNV markers, 3 SNVs that were enriched in CRC patients and located in the genomes of Eubacterium rectale and Faecalibacterium prausnitzii were CRC specific (AUC = 72.51%-94.07%).

Environmental exposure during earlier life stages can govern the assembly and development of gut microbiota, yet it is insufficiently understood. In this study, ex-germ-free mice were cohoused with distinct soil-microbiota (from desert, steppe, and forest) beddings within 60 days after birth and subsequently transferred to new soil beddings from 60 to 90th day. Using metagenomic shotgun sequencing, firstly, we found soil microbes from natural environments (birthplace) greatly influenced the gut community assembly in the housing experiment. About 27% microbial species and 12% functional components that associated with birthplaces at Day 60 were still discriminatory of birthplaces after transferring mice to new environments. Moreover, prior soil-exposure types are associated with the magnitude of temporal microbiome change due to environmental shifts. The appropriate soil-exposure (e.g., steppe) might help mice gut microbiome adapt to changing environments or host development. Our study demonstrated the continuous soil-exposure history earlier is associated with the gut microbiome individuality and development later.

The stable gut microbiome plays a key role in sustaining host health, while the instability of gut microbiome also has been found to be a risk factor of various metabolic diseases. At the ecological and evolutionary scales, the inevitable competition between the ingested probiotic and indigenous gut microbiome can lead to an increase in the instability. It remains largely unclear if and how exogenous prebiotic can improve the overall gut microbiome stability in probiotic consumption. In this study, we used Lactobacillus plantarum HNU082 (Lp082) as a model probiotic to examine the impact of the continuous or pulsed supplementation of galactooligosaccharide (GOS) on the gut microbiome stability in mice using shotgun metagenomic sequencing. Only continuous GOS supplement promoted the growth of probiotic and decreased its single-nucleotide polymorphisms (SNPs) mutation under competitive conditions. Besides, persistent GOS supplementation increased the overall stability, reshaped the probiotic competitive interactions with Bacteroides species in the indigenous microbiome, which was also evident by over-abundance of carbohydrate-active enzymes (CAZymes) accordingly. Also, we identified a total of 793 SNPs arisen in probiotic administration in the indigenous microbiome. Over 90% of them derived from Bacteroides species, which involved genes encoding transposase, CAZymes, and membrane proteins. However, neither GOS supplementation here de-escalated the overall adaptive mutations within the indigenous microbes during probiotic intake. Collectively, our study demonstrated the beneficial effect of continuous prebiotic supplementation on the ecological and genetic stability of gut microbiomes.

Accumulating evidence indicated that gut microbiota-targeted therapy is a promising strategy to treat Cardiovascular Disease (CVD). Traditional Chinese Medicine (TCM) has been used in CVD treatments for over 2,000 years which is believed to result from the modulation of gut microbiota, yet the underlying mechanism remains elusive. According to the theoretical system of TCM, we developed an innovative formula of TCM named “TongMai ZhuYu (TMZY)” on top of one classic Chinese herbal formula [“XueFu ZhuYu (XFZY)”], which can more effectively alleviate CVD in the clinical practice. Here, we first systematically assessed the pharmacological effects of TMZY, XFZY, and atorvastatin on atherosclerosis (AS) induced by high-fat diet (HFD) in rats. TMZY typically outperformed others in alleviating AS rats by characterization of pathological morphology, immunohistochemistry, inflammatory cytokines. Remarkably, combining this modified TCM formula (TMZY) with atorvastatin can further help the alleviation of AS in rats by suppressing immune and inflammatory responses. Furthermore, to test whether TMZY alleviated AS symptoms by altering gut microbial compositions (dysbiosis), we employed 16S amplicon sequencing to investigate gut microbiota changes in the AS mice induced by high choline diet (HCD) using both TMZY and XFZY under antibiotic-treated and untreated conditions. TCM formulas induced consistent and remarkable changes in the phenotypes and microbiota in the HCD mice. TMZY modulated more changes in the gut microbiota to improve diseased phenotypes than XFZY. Notably, the TMZY-intervention effect on CVD in mice attenuated after the suppression of gut microbial activity by antibiotics. Collectively, we demonstrated that TCM herbals could effectively modulate the gut microbiota as a mechanism for altering the pathogenesis of cardiovascular disorders in mice/rats.

Intravenous thrombolysis (IVT) improves functional outcome after acute ischemic stroke (AIS) and is the standard first-line treatment; however, it is associated with many complications, including cerebral hemorrhage. Cancer patients are susceptible to thrombotic events – collectively referred to as Trousseau syndrome (TS) – owing to their hypercoagulable state. Here, we describe the case of a 55-year-old male with a history of hypertension for over 10 years who underwent surgery for removal of a cancer of lower esophagus, with no subsequent treatment. Three months later, he was admitted to the emergency department of our hospital with sudden dizziness and incoherent speech. Brain computed tomography revealed multiple cerebral infarctions. The patient was treated by IVT with tissue plasminogen activator (rtPA) after the onset of symptoms, which improved by the end of the treatment. However, a few months later, he experienced a recurrence of cerebral infarction and hemorrhage, which has rarely been reported. The clinical course of this case suggests that the suitability of thrombolysis with rtPA in the acute phase of cerebral infarction complicated with TS should be carefully considered.

Intestinal microbiota performed numerous important functions during digestion. The first filial generation (F1) hybrids of Hainan black goats and Saanen goats had different traits, black goats (BG) and white goats (WG), which also brought different production performance. We explored the difference of gut microbiota between black goats and white goats that both belonged to the first filial generation (F1) hybrids. In general, the alpha diversity of the black goat group was significantly higher than the white goat group. The species richness had no significant difference, while the species evenness of BG was higher than WG. Bacteroides, Oscillospira, Alistipes, Ruminococcus, Clostridium and Oscillibacter, as the core gut microbial genera, all had high abundance in BG and WG group. Only the Bacteroides and Bacteroidaceae 5-7N15 were the different genera between the BG and WG group, of which Bacteroides overlapped with the core genera and enriched in the WG group. Besides, PICRUSt analysis showed that there was a high abundance in the secondary metabolic pathways including membrane transport, replication and repair, carbohydrate metabolism and amino acid metabolism. We found the intestinal microbial species of black goats and white goats were very similar for living in the identical growing environment and feeding conditions, but there was still a slight difference in the content. On the one hand, it was proved that the small effect of genotype and the great effect of diet affected the intestinal microbiota together. On the other hand, it was also proved that these different traits of first filial generation (F1) hybrids may not related to gut microbiota and only because of different genotype. Moreover, characterization of the gut microbiota in BG and WG will be useful in goats gut microbiota research.

The pros and cons of monosodium glutamate (MSG), a common food additive, have been long disputed, whereas the effects of MSG consumption on human intestinal microbiome have not been fully understood. In the present study, metagenomics sequencing was performed to evaluate the effects of MSG on human intestinal microbiota (n = 12) during a four-week experiment. It was observed that MSG consumption did not significantly alter the intestinal microbial community structure and functional features of the subjects. Although some bacteria including Faecalibacterium, Megamonas, Blautia and Collinsella tended to change, there was no significant difference in the alteration of all genera. At the functional level, the microbial functions were rich, mainly distributed in membrane transport, amino acid metabolism and carbohydrate metabolism, but there was no significant difference between samples obtained at different times. Additionally, it was discovered that the impact of the individuals on intestinal microbiota was greater than that of MSG.

Abstract Background Using next-generation sequencing technology to measure gene expression, an empirically intriguing question concerns the identification of differentially expressed genes across treatment groups. Existing methods aim to identify genes whose mean expressions differ among treatment groups by assuming equal dispersion across all groups. For syndromes, however, various combinations of gene expression alterations can result in the same disease, leading to greater heteroscedasticity in the biological replicates in the disease group compared to the normal group. Traditional methods that only consider changes in the mean will fail to fully analyze gene expression in such a scenario. In addition, sequencing technology is relatively expensive; most labs can only afford a few replicates per treatment group, which poses further challenges to reliably estimating the mean and dispersion under each treatment condition. Results We designed an empirical Bayes method and a pooled permutation test to simultaneously consider the change in mean and dispersion across treatment groups. We further computed confidence intervals based on Bayes estimates to identify differentially expressed genes that are unique to each disease sample as well as those that are common across all disease samples. We illustrated our method by applying it to gene expression data from a large offspring syndrome experiment, which motivated this study. We compared our method to competing approaches through simulation studies that mimicked the real datasets to demonstrate the effectiveness of our proposed method. Conclusions We will show that, compared to popular methods that only aim to find the difference in the mean, our method can capture greater variation in the disease group to effectively identify differentially expressed genes for syndromes.

Cyclin-dependent kinase 5 (Cdk5) has been shown to play a critical role in brain development, learning, memory and neural processing in general. Cdk5 is widely distributed in many neuron types in the central nervous system, while its cell-specific role is largely unknown. Our previous study showed that Cdk5 inhibition restored ocular dominance (OD) plasticity in adulthood. In this study, we specifically knocked down Cdk5 in different types of neurons in the visual cortex and examined OD plasticity by optical imaging of intrinsic signals. Downregulation of Cdk5 in parvalbumin-expressing (PV) inhibitory neurons, but not other neurons, reactivated adult mouse visual cortical plasticity. Cdk5 knockdown in PV neurons reduced the evoked firing rate, which was accompanied by an increment in the threshold current for the generation of a single action potential (AP) and hyperpolarization of the resting membrane potential. Moreover, chemogenetic activation of PV neurons in the visual cortex can attenuate the restoration of OD plasticity by Cdk5 inhibition. Taken together, our results suggest that Cdk5 in PV interneurons may play a role in modulating the excitation and inhibition balance to control the plasticity of the visual cortex.

Approximately 17 million people suffer from cardiovascular diseases caused by hyperlipidemia, making it a serious global health concern. Among others, resistant starch (RS) has been widely used as a prebiotic in managing hyperlipidemia conditions. However, some studies have reported limited effects of RS on body weight and blood lipid profile of the host, suggesting further investigation on the synergistic effects of RS in combination with probiotics as gut microbes plays a role in lipid metabolism. This study evaluated the effects of jackfruit seed sourced resistant starch (JSRS) as a novel RS on mice gut microbes and hyperlipidemia by performing 16s rRNA and shotgun metagenomic sequencing. The results showed that 10% JSRS had a limited preventive effect on bodyweight and serum lipid levels. However, the JSRS promoted the growth of Bifidobacterium pseudolongum, which indicated the ability of B. pseudolongum for JSRS utilization. In the validation experiment, B. pseudolongum interacted with JSRS to significantly reduce bodyweight and serum lipid levels and had a therapeutic effect on hepatic steatosis in mice. Collectively, this study revealed the improvements of hyperlipidemia in mice by the synergistic effects of JSRS and B. pseudolongum, which will help in the development of “synbiotics” for the treatment of hyperlipidemia in the future.

ABSTRACT Although a few studies have investigated the intestinal microbiota of women with polycystic ovary syndrome (PCOS), the functional and metabolic mechanisms of the microbes associated with PCOS, as well as potential microbial biomarkers, have not yet been identified. To address this gap, we designed a two-phase experiment in which we performed shotgun metagenomic sequencing and monitored the metabolic parameters, gut-brain mediators, and sex hormones of PCOS patients. In the first stage, we identified an imbalance in the intestinal microbiota of the PCOS patients, observing that Faecalibacterium, Bifidobacterium, and Blautia were significantly more abundant in the control group, whereas Parabacteroides and Clostridium were enriched in the PCOS group. In the second stage, we monitored the impact of the probiotic Bifidobacterium lactis V9 on the intestinal microbiome, gut-brain mediators, and sex hormones of 14 PCOS patients. Notably, we observed that the levels of luteinizing hormone (LH) and LH/follicle-stimulating hormone (LH/FSH) decreased significantly in 9 volunteers, whereas the levels of sex hormones and intestinal short-chain fatty acids (SCFAs) increased markedly. In contrast, the changes in the indices mentioned above were indistinct in the remaining 5 volunteers. The results of an analysis of the number of viable Bifidobacterium lactis V9 cells in the two groups were highly consistent with the clinical and SCFA results. Therefore, effective host gut colonization of the probiotic Bifidobacterium lactis V9 was crucial for its ability to function as a probiotic. Finally, we propose a potential mechanism describing how probiotics regulate the levels of sex hormones by manipulating the intestinal microbiome in PCOS patients. IMPORTANCE Polycystic ovary syndrome (PCOS) is a common metabolic disorder among women of reproductive age worldwide. Through a two-phase clinical experiment, we first revealed an imbalance in the intestinal microbiome of PCOS patients. By binning and annotating shotgun metagenomic sequences into metagenomic species (MGS), 61 MGSs were identified as potential PCOS-related microbial biomarkers. In the second stage, we monitored the impact of the probiotic Bifidobacterium lactis V9 on the intestinal microbiota, metabolic parameters, gut-brain mediators, and sex hormones of PCOS patients. Notably, we observed that the PCOS-related clinical indices and the intestinal microbiotas of the participating patients exhibited an inconsistent response to the intake of the B. lactis V9 probiotic. Therefore, effective host gut colonization of the probiotic was crucial for its ability to function as a probiotic. Finally, we propose a potential mechanism by which B. lactis V9 regulates the levels of sex hormones by manipulating the intestinal microbiome in PCOS patients.

Fermented fish, fermented shrimp and fermented crab are traditionally prepared seafoods that are commonly consumed in the Hainan area in China. We studied the microbial diversity and metabolic pathways in traditional fermented seafoods using high-throughput sequencing technology, and based on our previous research, we also compared the differences between fermented seafood and fermented vegetables. The alpha diversity of fermented seafood was higher than that of fermented vegetables and attained the highest level in fermented shrimp. The dominant genera in fermented seafood were different from those of fermented vegetables. Furthermore, we analyzed the 16S rDNA gene polymorphisms (SNPs) of the same dominant species (Lactobacillus plantarum and Lactobacillus fermentum) in two fermented environments, which showed that most of the mutations occurred in fermented vegetables and that fermenting environment might be the major factor for these mutations. This research provides us with new insights into beneficial microbial resources in regard to microbial diversity and genetic polymorphisms and lays a foundation for the subsequent development and utilization of beneficial microorganisms.

Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models that are widely used in educational and psychological measurement. A key component of CDMs is the Q-matrix characterizing the dependence structure between the items and the latent attributes. Additionally, researchers also assume in many applications certain hierarchical structures among the latent attributes to characterize their dependence. In most CDM applications, the attribute--attribute hierarchical structures, the item-attribute Q-matrix, the item-level diagnostic models, as well as the number of latent attributes, need to be fully or partially pre-specified, which however may be subjective and misspecified as noted by many recent studies. This paper considers the problem of jointly learning these latent and hierarchical structures in CDMs from observed data with minimal model assumptions. Specifically, a penalized likelihood approach is proposed to select the number of attributes and estimate the latent and hierarchical structures simultaneously. An expectation-maximization (EM) algorithm is developed for efficient computation, and statistical consistency theory is also established under mild conditions. The good performance of the proposed method is illustrated by simulation studies and real data applications in educational assessment.

Fermented vegetables are typically traditional foods made of fresh vegetables and their juices, which are fermented by beneficial microorganisms. Herein, we applied high-throughput sequencing and culture-dependent technology to describe the diversities of microbiota and identify core microbiota in fermented vegetables from different areas of Hainan Province, and abundant metabolic pathways in the fermented vegetables were simultaneously predicted. At the genus level, Lactobacillus bacteria were the most abundant. Lactobacillus plantarum was the most abundant species, followed by Lactobacillus fermentum, Lactobacillus pentosaceus, and Weissella cibaria. These species were present in each sample with average absolute content values greater than 1% and were thus defined as core microbiota. Analysis results based on the alpha and beta diversities of the microbial communities showed that the microbial profiles of the fermented vegetables differed significantly based on the regions and raw materials used, and the species of the vegetables had a greater effect on the microbial community structure than the region from where they were harvested. Regarding microbial functional metabolism, we observed an enrichment of metabolic pathways, including membrane transport, replication and repair and translation, which implied that the microbial metabolism in the fermented vegetables tended to be vigorous. In addition, Lactobacillus plantarum and Lactobacillus fermentum were calculated to be major metabolic pathway contributors. Finally, we constructed a network to better explain correlations among the core microbiota and metabolic pathways. This study facilitates an understanding of the differences in microbial profiles and fermentation pathways involved in the production of fermented vegetables, establishes a basis for optimally selecting microorganisms to manufacture high-quality fermented vegetable products, and lays the foundation for better utilizing tropical microbial resources.

Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models widely used in educational, psychological and social sciences. In many applications of CDMs, certain hierarchical structures among the latent attributes are assumed by researchers to characterize their dependence structure. Specifically, a directed acyclic graph is used to specify hierarchical constraints on the allowable configurations of the discrete latent attributes. In this paper, we consider the important yet unaddressed problem of testing the existence of latent hierarchical structures in CDMs. We first introduce the concept of testability of hierarchical structures in CDMs and present sufficient conditions. Then we study the asymptotic behaviors of the likelihood ratio test (LRT) statistic, which is widely used for testing nested models. Due to the irregularity of the problem, the asymptotic distribution of LRT becomes nonstandard and tends to provide unsatisfactory finite sample performance under practical conditions. We provide statistical insights on such failures, and propose to use parametric bootstrap to perform the testing. We also demonstrate the effectiveness and superiority of parametric bootstrap for testing the latent hierarchies over non-parametric bootstrap and the naïve Chi-squared test through comprehensive simulations and an educational assessment dataset.

In this paper, the runoff of Huayuankou and Lijin Hydrologic Stations of the downstream areas of the Yellow River from 1951 to 2012 were calculated and analyzed in order to explore the runoff variable characteristics and their response to climatic factors. The following conclusions can be drawn:(1)Annual runoff of the river shows a clear downward trend as a whole, especially in the 1990s, but shifted to increase in the early 21st century.(2)Runoff can be affected by climate change; climatic factors and runoff change in the same time or precedes the latter.(3)The response of runoff to climatic factors is not stable, in other words, changing with time; (4)the response of runoff to precipitation is more sensitive than that of temperature.(5)Precipitation and temperature both contribute to the change of runoff, but the former is a positive contribution and the latter is opposite.

Accurate short-term electrical load forecasting plays a pivotal role in the national economy and people’s livelihood through providing effective future plans and ensuring a reliable supply of sustainable electricity. Although considerable work has been done to select suitable models and optimize the model parameters to forecast the short-term electrical load, few models are built based on the characteristics of time series, which will have a great impact on the forecasting accuracy. For that reason, this paper proposes a hybrid model based on data decomposition considering periodicity, trend and randomness of the original electrical load time series data. Through preprocessing and analyzing the original time series, the generalized regression neural network optimized by genetic algorithm is used to forecast the short-term electrical load. The experimental results demonstrate that the proposed hybrid model can not only achieve a good fitting ability, but it can also approximate the actual values when dealing with non-linear time series data with periodicity, trend and randomness.