Hypolipidemic Effect of Rice Bran Oil Extract Tocotrienol in High-Fat Diet-Induced Hyperlipidemia Zebrafish (Danio Rerio) Induced by High-Fat Diet.

In recent years, the potent influence of tocotrienol (T3) on diminishing blood glucose and lipid concentrations in both Mus musculus (rats) and Homo sapiens (humans) has been established. However, the comprehensive exploration of tocotrienol's hypolipidemic impact and the corresponding mechanisms in aquatic species remains inadequate. In this study, we established a zebrafish model of a type 2 diabetes mellitus (T2DM) model through high-fat diet administration to zebrafish. In the T2DM zebrafish, the thickness of ocular vascular walls significantly increased compared to the control group, which was mitigated after treatment with T3. Additionally, our findings demonstrate the regulatory effect of T3 on lipid metabolism, leading to the reduced synthesis and storage of adipose tissue in zebrafish. We validated the expression patterns of genes relevant to these processes using RT-qPCR. In the T2DM model, there was an almost two-fold upregulation in pparγ and cyp7a1 mRNA levels, coupled with a significant downregulation in cpt1a mRNA (p < 0.01) compared to the control group. The ELISA revealed that the protein expression levels of Pparγ and Rxrα exhibited a two-fold elevation in the T2DM group relative to the control. In the T3-treated group, Pparγ and Rxrα protein expression levels consistently exhibited a two-fold decrease compared to the model group. Lipid metabolomics showed that T3 could affect the metabolic pathways of zebrafish lipid regulation, including lipid synthesis and decomposition. We provided experimental evidence that T3 could mitigate lipid accumulation in our zebrafish T2DM model. Elucidating the lipid-lowering effects of T3 could help to minimize the detrimental impacts of overfeeding in aquaculture.

Computer Vision-Based Biomass Estimation for Invasive Plants.

We report on the detailed steps of a method to estimate the biomass of invasive plants based on UAV remote sensing and computer vision. To collect samples from the study area, we prepared a sample square assembly to randomize the sampling points. An unmanned aerial camera system was constructed using a drone and camera to acquire continuous RGB images of the study area through automated navigation. After completing the shooting, the aboveground biomass in the sample frame was collected, and all correspondences were labeled and packaged. The sample data was processed, and the aerial images were segmented into small images of 280 x 280 pixels to create an image dataset. A deep convolutional neural network was used to map the distribution of Mikania micrantha in the study area, and its vegetation index was obtained. The organisms collected were dried, and the dry weight was recorded as the ground truth biomass. The invasive plant biomass regression model was constructed using the K-nearest neighbor regression (KNNR) by extracting the vegetation index from the sample images as an independent variable and integrating it with the ground truth biomass as a dependent variable. The results showed that it was possible to predict the biomass of invasive plants accurately. An accurate spatial distribution map of invasive plant biomass was generated by image traversal, allowing precise identification of high-risk areas affected by invasive plants. In summary, this study demonstrates the potential of combining unmanned aerial vehicle remote sensing with machine learning techniques to estimate invasive plant biomass. It contributes significantly to the research of new technologies and methods for real-time monitoring of invasive plants and provides technical support for intelligent monitoring and hazard assessment at the regional scale.

Responses of multi-faceted benthic macroinvertebrates alpha and beta diversity to flooding in a highland floodplain.

Flooding is an important process in natural fluvial floodplains. How the flood shapes aquatic community diversity in highland floodplains is still poorly understood. The aim of this study was to unravel the multi-faceted responses of benthic macroinvertebrate diversity to flooding and habitat environments in the Baihe River Basin from a taxonomic, phylogenetic, and functional perspective. We examined the alpha and beta diversity patterns of benthic macroinvertebrate communities in the mainstream, tributaries, and oxbow lakes during the normal water and flood periods. The results showed that the traditional alpha taxonomic diversity (TD) varied across habitats, despite minor changes after flood pulse. Alpha phylogenetic diversity (PD) decreased and alpha functional diversity (FD) markedly increased after flooding, with functional traits transiting toward risk avoidance. While all the three facets of beta diversity significantly responded to habitat differences, beta TD and PD shifted in response to flooding. Species turnover prominently increased in beta TD and PD after flood pulse, which contrasted with a weaker response of this process in FD. The explanatory power of significant environmental factors on both alpha and beta diversity was reduced by flooding. Compared with traditional TD, cooperating multi-faceted diversity could better depict the responses of benthic macroinvertebrate communities to flooding. The assessment and conservation of aquatic biodiversity in highland floodplains should take into account the three facets of alpha and beta diversity.

SUMOylation of TEAD1 Modulates the Mechanism of Pathological Cardiac Hypertrophy.

Pathological cardiac hypertrophy is the leading cause of heart failure and has an extremely complicated pathogenesis. TEA domain transcription factor 1 (TEAD1) is recognized as an important transcription factor that plays a key regulatory role in cardiovascular disease. This study aimed to explore the role of TEAD1 in cardiac hypertrophy and to clarify the regulatory role of small ubiquitin-like modifier (SUMO)-mediated modifications. First, the expression level of TEAD1 in patients with heart failure, mice, and cardiomyocytes is investigated. It is discovered that TEAD1 is modified by SUMO1 during cardiac hypertrophy and that the process of deSUMOylation is regulated by SUMO-specific protease 1 (SENP1). Lysine 173 is an essential site for TEAD1 SUMOylation, which affects the protein stability, nuclear localization, and DNA-binding ability of TEAD1 and enhances the interaction between TEAD1 and its transcriptional co-activator yes-associated protein 1 in the Hippo pathway. Finally, adeno-associated virus serotype 9 is used to construct TEAD1 wild-type and KR mutant mice and demonstrated that the deSUMOylation of TEAD1 markedly exacerbated cardiomyocyte enlargement in vitro and in a mouse model of cardiac hypertrophy. The results provide novel evidence that the SUMOylation of TEAD1 is a promising therapeutic strategy for hypertrophy-related heart failure.

A few-shot link prediction framework to drug repurposing using multi-level attention network.

Drug repurposing is a strategy aiming at uncovering novel medical indications of approved drugs. This process of discovery can be effectively represented as a link prediction task within a medical knowledge graph by predicting the missing relation between the disease entity and the drug entity. Typically, the links to be predicted pertain to rare types, thereby necessitating the task of few-shot link prediction. However, the sparsity of neighborhood information and weak triplet interactions result in less effective representations, which brings great challenges to the few-shot link prediction. Therefore, in this paper, we proposed a meta-learning framework based on a multi-level attention network (MLAN) to capture valuable information in the few-shot scenario for drug repurposing. First, the proposed method utilized a gating mechanism and a graph attention network to effectively filter noise information and highlight the valuable neighborhood information, respectively. Second, the proposed commonality relation learner, employing a set transformer, effectively captured triplet-level interactions while remaining insensitive to the size of the support set. Finally, a model-agnostic meta-learning training strategy was employed to optimize the model quickly on each meta task. We conducted validation of the proposed method on two datasets specifically designed for few-shot link prediction in medical field: COVID19-One and BIOKG-One. Experimental results showed that the proposed model had significant advantages over state-of-the-art few-shot link prediction methods. Results also highlighted the valuable insights of the proposed method, which successfully integrated the components within a unified meta-learning framework for drug repurposing.

Low serum apolipoprotein A1 level predicts poor prognosis of patients with diffuse large B-cell lymphoma in the real world: a retrospective study.

BACKGROUND: Apolipoprotein A1 (ApoA1) is a member of the apolipoprotein family with diverse functions. It is associated with the pathogenesis and prognosis of several types of tumors. However, the role of serum apolipoprotein A1 (ApoA1) in the prognosis of patients with diffuse large B-cell lymphoma (DLBCL) remains unclear. This study aimed to elucidate its influence on clinical outcomes in patients with DLBCL. METHODS: We retrospectively analyzed a cohort of 1583 consecutive DLBCL patients admitted to the Fujian Medical University Union Hospital between January 2011 and December 2021. 949 newly diagnosed DLBCL patients who met the inclusion criteria were enrolled for statistical analysis. Receiver operating characteristic curve analysis was performed to determine the optimal cut-off value for serum ApoA1 levels for prognostic prediction among patients with DLBCL. The correlations between serum ApoA1 levels and clinical and laboratory parameters were analyzed. Prognostic significance was analyzed using univariate and multivariate Cox proportional hazards models. RESULTS: Newly diagnosed patients with DLBCL demonstrated low serum ApoA1 levels (< 0.925 g/L), had more B symptoms, higher levels of serum lactate dehydrogenase (LDH) (>upper limit of normal), poorer performance status (Eastern Cooperative Oncology Group score of 2-4), higher percentage of advanced stage and non-germinal center B-cell (non-GCB) subtype, more cases of > 1 extranodal site, higher International Prognostic Index (IPI) score (3-5), and higher incidence of relapse or refractory diseases compared with those with high serum ApoA1 levels (≥ 0.925 g/L). Low serum ApoA1 levels were an independent adverse prognostic factor for overall survival (OS) but not progression-free survival (PFS). CONCLUSIONS: Low serum ApoA1 levels were associated with poor treatment response and inferior survival in newly diagnosed patients with DLBCL.

LAMB3 Promotes Intestinal Inflammation Through SERPINA3 and Is Directly Transcriptionally Regulated by P65 in Inflammatory Bowel Disease.

BACKGROUND: Various extracellular matrix (ECM) reshaping events are involved in inflammatory bowel disease (IBD). LAMB3 is a vital subunit of laminin-332, an important ECM component. Data on the biological function of LAMB3 in intestinal inflammation are lacking. Our aim is to discuss the effect of LAMB3 in IBD. METHODS: LAMB3 expression was assessed in cultured intestinal epithelial cells, inflamed mucosal tissues of patients and mouse colitis models. RNA sequencing, quantitative real-time polymerase chain reaction and Western blotting were used to detect the LAMB3 expression distribution and potential downstream target genes. Dual-luciferase assays and chromatin immunoprecipitation-quantitative polymerase chain reaction were used to determine whether P65 could transcriptionally activate LAMB3 under tumor necrosis factor α stimulation. RESULTS: LAMB3 expression was increased in inflammatory states in intestinal epithelial cells and colonoids and was associated with adverse clinical outcomes in Crohn's disease. Knockdown of LAMB3 inhibited the expression of proinflammatory cytokines. Mechanistically, LAMB3 expression was directly transcriptionally activated by P65 and was inhibited by nuclear factor kappa B inhibitors under tumor necrosis factor α stimulation. Furthermore, RNA sequencing and replenishment experiments revealed that LAMB3 upregulated SERPINA3 to promote intestinal inflammation via the integrin α3ß1/FAK pathway. CONCLUSION: We propose that LAMB3 could serve as a potential therapeutic target of IBD and a predictor of intestinal stenosis of Crohn's disease. Our findings demonstrate the important role of ECM in the progression of IBD and offer an experimental basis for the treatment and prognosis of IBD.

[Expression and Clinical Significance of Exosome Component 4 in Newly Diagnosed Patients with Diffuse Large B-Cell Lymphoma].

OBJECTIVE: To explore the expression of Exosome Component 4（EXOSC4） in the tissues of newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) and its clinical significance. METHODS: The expression of EXOSC4 protein in the tissues of 181 newly diagnosed DLBCL patients was analyzed by immunohistochemical staining. Clinical data were collected. The correlation between EXOSC4 protein expression in the tissues of newly diagnosed DLBCL patients and clinical features were analyzed and its prognostic significance. RESULTS: The positive rate of EXOSC4 protein expression was 68.51% in the tissues of 181 newly diagnosed DLBCL patients. These patients were divided into two groups, with 44 cases in high expression group and 137 cases in low expression group. There were no significant differences in age, gender, B symptoms, serum lactate dehydrogenase (LDH) level, Eastern Cooperative Oncology Group (ECOG) score, Ann Arbor stage, extranodal disease, International Prognostic Index (IPI) score, National Comprehensive Cancer Network IPI (NCCN-IPI) score, and cell origin between the two groups (P>0.05). Cox multivariate regression analysis showed that high EXOSC4 protein expression in tissues was an independent poor prognostic factor for OS and PFS in newly diagnosed DLBCL patients (all P<0.05). K-M survival analysis showed that newly diagnosed DLBCL patients with high EXOSC4 protein expression had significantly shorter overall survival (OS) and progression free survival (PFS) than those patients with low EXOSC4 protein expression (all P<0.05). CONCLUSION: High EXOSC4 protein expression in tissues of newly diagnosed DLBCL patients is an independent poor prognostic factor for survival.

Mucosal immunity and microbiota change in the rainbow trout (Oncorhynchus mykiss) gills after being challenged with infectious hematopoietic necrosis virus.

Respiratory structures are crucial for vertebrate survival, as they serve not only to perform gas-exchange processes but also as entry points for opportunistic pathogens. Previous studies have demonstrated that fish contain gill mucosal-associated lymphoid tissue, and harbor a large number of commensal bacteria on their surface and contribute to maintaining fish health. However, by far, very limited information is known regarding the effects of viral infection on gill mucosal immunity and microbiota homeostasis. In this study, we conducted an infection model by bath with infectious hematopoietic necrosis virus (IHNV) and revealed a 27 % mortality rate among rainbow trout in the first two weeks after infection. Moreover, we found that diseased fish with the highest IHNV loads in gills exhibiting severe damage, as well as increased goblet cell counts in both primary lamellae (PL) and secondary lamellae (SL). Additionally, RT-qPCR and RNA-seq analyses revealed that IHNV infection induced a strong innate and adaptive antiviral immune responses. Interestingly, an antibacterial immune response was also observed, suggesting that a secondary bacterial infection occurred in trout gills after viral infection. Furthermore, 16S rRNA analysis of trout gills revealed a profound dysbiosis marked by a loss of beneficial taxa and expansion of pathobionts following IHNV infection. Overall, our finding demonstrates that IHNV infection induces significant changes of the microbial community in the fish respiratory surface, thus triggering local antiviral and bacterial mucosal immunity.

ELK4 Promotes Colorectal Cancer Progression by Activating the Neoangiogenic Factor LRG1 in a Noncanonical SP1/3-Dependent Manner.

Although the MAPK/MEK/ERK pathway is prevalently activated in colorectal cancer (CRC), MEK/ERK inhibitors show limited efficiency in clinic. As a downstream target of MAPK, ELK4 is thought to work primarily by forming a complex with SRF. Whether ELK4 can serve as a potential therapeutic target is unclear and the transcriptional regulatory mechanism has not been systemically analyzed. Here, it is shown that ELK4 promotes CRC tumorigenesis. Integrated genomics- and proteomics-based approaches identified SP1 and SP3, instead of SRF, as cooperative functional partners of ELK4 at genome-wide level in CRC. Serum-induced phosphorylation of ELK4 by MAPKs facilitated its interaction with SP1/SP3. The pathological neoangiogenic factor LRG1 is identified as a direct target of the ELK4-SP1/SP3 complex. Furthermore, targeting the ELK4-SP1/SP3 complex by combination treatment with MEK/ERK inhibitor and the relatively specific SP1 inhibitor mithramycin A (MMA) elicited a synergistic antitumor effect on CRC. Clinically, ELK4 is a marker of poor prognosis in CRC. A 9-gene prognostic model based on the ELK4-SP1/3 complex-regulated gene set showed robust prognostic accuracy. The results demonstrate that ELK4 cooperates with SP1 and SP3 to transcriptionally regulate LRG1 to promote CRC tumorigenesis in an SRF-independent manner, identifying the ELK4-SP1/SP3 complex as a potential target for rational combination therapy.

Noncovalent composites of meso-substituted A2B2-porphyrins and carbon nanotubes for enhanced electrocatalytic oxygen reduction.

Exploring highly active oxygen reduction electrocatalysts with low precious metals content is imperative but remains a considerable challenge. Herein, a series of heterobimetallic multi-walled carbon nanotubes (MWCNTs) electrocatalysts based on metal complexes are presented. These electrocatalysts feature diverse transition metals (M=Mn, Fe, Co, Ni) 5,15-bromophenyl-10, 20-methoxyphenyl porphyrin (MBMP) and tetrakis(triphenylphosphine)palladium (0) (Pd[P(Ph3)4]) anchored non-covalently on its surface. The resulting NiBMP-based MWCNTs with Pd[P(Ph3)4] (PdNiN4/MWCNTs) display outstanding electrocatalytic oxygen reduction activity (onset potential, 0.941 V; half wave potential, 0.830 V) and robust long-term durability in alkaline electrolyte. While in neutral condition, the MnBMP-based MWCNTs with Pd[P(Ph3)4] (PdMnN4/MWCNTs) are the most active heterobimetallic ORR catalyst and produce ultra-low concentration hydrogen peroxide (H2O2yield, 1.2%-1.3%). Synergistically tuning the ORR electrocatalytic activity and electron transfer pathway is achieved by the formation of NiBMP/MnBMP-Pd[P(Ph3)4] active sites. This work indicates such metalloporphyrin-Pd[P(Ph3)4] active sites on MWCNTs have significantly positive influence on electrocatalytic ORR systems and provides facile and mild strategy for designing highly efficient ORR electrocatalysts with ultra-low loading precious metal.

Induced Abortion and the Risk of Rh Sensitization.

Importance: While population-level data suggest Rh immunoglobulin is unnecessary before 12 weeks' gestation, clinical evidence is limited. Thus, guidelines vary, creating confusion surrounding risks and benefits of Rh testing and treatment. As abortion care in traditional clinical settings becomes harder to access, many people are choosing to self-manage and need to know if ancillary blood type testing is necessary. Objective: To determine how frequently maternal exposure to fetal red blood cells (fRBCs) exceeds the most conservative published threshold for Rh sensitization in induced first-trimester abortion. Design, Setting, and Participants: Multicenter, observational, prospective cohort study using high-throughput flow cytometry to detect circulating fRBCs in paired maternal blood samples before and after induced first-trimester abortion (medication or procedural). Individuals undergoing induced first-trimester abortion before 12 weeks 0 days' gestation were included. Paired blood samples were available from 506 participants who underwent either medical (n = 319 [63.0%]) or procedural (n = 187 [37.0%]) abortion. Exposure: Induced first-trimester abortion. Main Outcomes and Measures: The primary outcome was the proportion of participants with fRBC counts above the sensitization threshold (125 fRBCs/5 million total RBCs) after induced first-trimester abortion. Results: Among the 506 participants, the mean (SD) age was 27.4 (5.5) years, 313 (61.9%) were Black, and 123 (24.3%) were White. Three of the 506 participants had elevated fRBC counts at baseline; 1 of these patients had an elevated fRBC count following the abortion (0.2% [95% CI, 0%-0.93%]). No other participants had elevated fRBC counts above the sensitization threshold after induced first-trimester abortion. The median change from baseline was 0 fRBCs, with upper 95th and 99th percentiles of 24 and 35.6 fRBCs, respectively. Although there was a strong association between the preabortion and postabortion fRBC counts, no other baseline characteristic was significantly associated with postabortion fRBC count. Conclusions and Relevance: Induced first-trimester abortion is not a risk factor for Rh sensitization, indicating that Rh testing and treatment are unnecessary before 12 weeks' gestation. This evidence may be used to inform international guidelines for Rh immunoglobulin administration following first-trimester induced abortion.

Hydrological disturbances enhance stochastic assembly processes and decrease network stability of algae communities in a highland floodplain system.

Floodplains are hotspots for biodiversity research and conservation worldwide. Hydrological disturbances can profoundly influence the ecological processes and functions of floodplain systems by altering key biological groups such as algae communities. However, the impacts of flood disturbance on the assembly processes and co-occurrence patterns of algae communities in floodplain ecosystems are still unclear. To ascertain the response patterns of algae communities to flood disturbance, we characterized planktonic and benthic algae communities in 144 water and sediment samples collected from the Tibetan floodplain during non-flood and flood periods based on 23S ribosomal RNA gene sequencing. Results showed that planktonic algae exhibited higher diversity and greater compositional variations compared with benthic communities after flood disturbance. Flooding promoted algae community homogenization at horizontal (rivers vs. oxbow lakes) and vertical levels (water vs. sediment). Stochastic processes governed the assembly of distinct algae communities, and their ecological impacts were enhanced in response to flooding. In the non-flood period, dispersal limitation (81.78 %) was the primary ecological process driving algae community assembly. In the flood period, the relative contribution of ecological drift (72.91 %) to algae community assembly markedly increased, with dispersal limitation (22.61 %) being less important. Flooding reduced the interactions among algae taxa, resulting in lower network complexity and stability. Compared with the planktonic algae subnetworks, the benthic subnetworks showed greater stability in the face of flooding. Findings of this study broaden our understanding of how algae communities respond to hydrological disturbances from an ecological perspective and could be useful for the management of highland floodplain ecosystems.

Spatial differences of specialty agriculture development in the mountainous areas of China -- "one village, one product" as an example.

With the rapid development of urbanization, the rate of abandonment of arable land in China's mountainous areas has accelerated. Solving the phenomenon of abandonment of arable land has become an important issue in managing the use of China's arable land, the key to which lies in the development of specialty agriculture using the unique natural environment of mountainous areas. This paper scrutinizes both the horizontal and vertical distribution of specialty agriculture in these areas, drawing upon the "One Village, One Product" dataset provided by the Chinese Ministry of Agriculture and Rural Development. The findings reveal that the horizontal distribution pattern of specialty agriculture exhibits the formation of eight primary clusters. It is intriguing to observe that a majority of these clusters are situated at the intersection of two or three provincial administrative units, with the largest cluster occurring at the border of Chengdu and Chongqing. In terms of the vertical distribution pattern, the specialty agriculture in China's mountainous areas are mainly distributed at low altitudes, i.e., below 500 m, and at gentle slopes of 4°-8°, and with increases in altitude or slope, the overall amount of specialty agriculture declines rapidly.

Analysis of the microbiota composition in the genital tract of infertile patients with chronic endometritis or endometrial polyps.

Background: The previous researches show that infertile patients have a higher incidence of endometritis and endometrial polyps, and the occurrence of these two diseases is related to changes in the microbiota of the genital tract. We aim to determine the composition and changing characteristics of the microbiota in the genital tract (especially the endometrium) of infertile patients with chronic endometritis or endometrial polyps, and find the correlation between it and the occurrence of diseases. Methods: This is a prospective study. We collected genital tract biopsy samples from 134 asymptomatic infertile patients receiving assisted reproductive therapy before embryo transfer. Through pathological examination and 16S ribosomal RNA(16S rRNA) sequencing, we determined the distribution of chronic endometritis and endometrial polyps in these patients, as well as their distribution of reproductive tract microorganisms. Results: Compared with the normal control group, the microbial group of reproductive tract in patients with chronic endometritis and endometrial polyps is changed, and there are significant species differences and relative abundance differences in the vagina, cervix and uterine cavity. Lactobacillus, the dominant flora of female genital tract, showed a change in abundance in patients with endometrial diseases. Endometrial microbiota composed of Staphylococcus, Gardnerella, Atopobium, Streptococcus, Peptostreptococcus, Chlamydia, Fusobacterium, Acinetobacter, etc. are related to chronic endometritis and endometrial polyps. Conclusion: The results showed that, compared with the normal control group, the endometrial microbiota of infertile patients with chronic endometritis or endometrial polyps did have significant changes in the relative abundance distribution of species, suggesting that changes in local microecology may be an important factor in the occurrence of disease, or even adverse pregnancy outcomes. The further study of endometrial microecology may provide a new opportunity to further improve the diagnosis and treatment strategy of chronic endometritis.

KISL: knowledge-injected semi-supervised learning for biological co-expression network modules.

The exploration of important biomarkers associated with cancer development is crucial for diagnosing cancer, designing therapeutic interventions, and predicting prognoses. The analysis of gene co-expression provides a systemic perspective on gene networks and can be a valuable tool for mining biomarkers. The main objective of co-expression network analysis is to discover highly synergistic sets of genes, and the most widely used method is weighted gene co-expression network analysis (WGCNA). With the Pearson correlation coefficient, WGCNA measures gene correlation, and uses hierarchical clustering to identify gene modules. The Pearson correlation coefficient reflects only the linear dependence between variables, and the main drawback of hierarchical clustering is that once two objects are clustered together, the process cannot be reversed. Hence, readjusting inappropriate cluster divisions is not possible. Existing co-expression network analysis methods rely on unsupervised methods that do not utilize prior biological knowledge for module delineation. Here we present a method for identification of outstanding modules in a co-expression network using a knowledge-injected semi-supervised learning approach (KISL), which utilizes apriori biological knowledge and a semi-supervised clustering method to address the issue existing in the current GCN-based clustering methods. To measure the linear and non-linear dependence between genes, we introduce a distance correlation due to the complexity of the gene-gene relationship. Eight RNA-seq datasets of cancer samples are used to validate its effectiveness. In all eight datasets, the KISL algorithm outperformed WGCNA when comparing the silhouette coefficient, Calinski-Harabasz index and Davies-Bouldin index evaluation metrics. According to the results, KISL clusters had better cluster evaluation values and better gene module aggregation. Enrichment analysis of the recognition modules demonstrated their effectiveness in discovering modular structures in biological co-expression networks. In addition, as a general method, KISL can be applied to various co-expression network analyses based on similarity metrics. Source codes for the KISL and the related scripts are available online at https://github.com/Mowonhoo/KISL.git.

Cross-Modal Retrieval With Partially Mismatched Pairs.

In this paper, we study a challenging but less-touched problem in cross-modal retrieval, i.e., partially mismatched pairs (PMPs). Specifically, in real-world scenarios, a huge number of multimedia data (e.g., the Conceptual Captions dataset) are collected from the Internet, and thus it is inevitable to wrongly treat some irrelevant cross-modal pairs as matched. Undoubtedly, such a PMP problem will remarkably degrade the cross-modal retrieval performance. To tackle this problem, we derive a unified theoretical Robust Cross-modal Learning framework (RCL) with an unbiased estimator of the cross-modal retrieval risk, which aims to endow the cross-modal retrieval methods with robustness against PMPs. In detail, our RCL adopts a novel complementary contrastive learning paradigm to address the following two challenges, i.e., the overfitting and underfitting issues. On the one hand, our method only utilizes the negative information which is much less likely false compared with the positive information, thus avoiding the overfitting issue to PMPs. However, these robust strategies could induce underfitting issues, thus making training models more difficult. On the other hand, to address the underfitting issue brought by weak supervision, we present to leverage of all available negative pairs to enhance the supervision contained in the negative information. Moreover, to further improve the performance, we propose to minimize the upper bounds of the risk to pay more attention to hard samples. To verify the effectiveness and robustness of the proposed method, we carry out comprehensive experiments on five widely-used benchmark datasets compared with nine state-of-the-art approaches w.r.t. the image-text and video-text retrieval tasks. The code is available at https://github.com/penghu-cs/RCL.

Highly sensitive liquid chromatographic method combined with online ion suppression to remove interfering anions and mass spectrometry for impurity profiling of paromomycin sulfate.

A previously developed high-performance liquid chromatography method combined with pulsed amperometric detection allowed to separate many impurities of paromomycin. However, due to the presence of ion pairing agents and sodium hydroxide in the mobile phase, direct coupling to mass spectrometry for the identification of the chemical structures of the impurities was not an option. Indeed, ion suppression was encountered by trifluoroacetic acid and pentafluoroproponic acid in the mobile phase. A cation self-regenerating suppressor, which was originally designed for increasing analyte conductivity of ammonia and amines analysis in ion chromatography, was coupled between the liquid chromatography and ion trap-time of flight-mass spectrometry and almost all trifluoroacetic acid and pentafluoroproponic acid in the mobile phase was removed. The limit of detection of paromomycin in this integrated system improved significantly to 20 ng/ml (0.4 ng). The chemical structures of 19 impurities were elucidated and seven impurities were reported for the first time.

Neural functions in cancer: Data analyses and database construction.

Recent studies have revealed that neural functions are involved in possibly every aspect of a cancer development, serving as bridges connecting microenvironmental stressors, activities of intracellular subsystems, and cell survival. Elucidation of the functional roles played by the neural system could provide the missing links in developing a systems-level understanding of cancer biology. However, the existing information is highly fragmented and scattered across the literature and internet databases, making it difficult for cancer researchers to use. We have conducted computational analyses of transcriptomic data of cancer tissues in TCGA and tissues of healthy organs in GTEx, aiming to demonstrate how the functional roles by the neural genes could be derived and what non-neural functions they are associated with, across different stages of 26 cancer types. Several novel discoveries are made, including i) the expressions of certain neural genes can predict the prognosis of a cancer patient; ii) cancer metastasis tends to involve specific neural functions; iii) cancers of low survival rates involve more neural interactions than those with high survival rates; iv) more malignant cancers involve more complex neural functions; and v) neural functions are probably induced to alleviate stresses and help the associated cancer cells to survive. A database, called NGC, is developed for organizing such derived neural functions and associations, along with gene expressions and functional annotations collected from public databases, aiming to provide an integrated and publicly available information resource to enable cancer researchers to take full advantage of the relevant information in their research, facilitated by tools provided by NGC.

Seasonal variation of phytoplankton community assembly processes in Tibetan Plateau floodplain.

Uncovering the mechanisms underlying phytoplankton community assembly remains a major challenge in freshwater ecology. The roles of environmental filtering and spatial processes in shaping phytoplankton metacommunity in Tibetan floodplain ecosystems under various hydrological conditions are still unclear. Here, multivariate statistics and a null model approach were used to compare the spatiotemporal patterns and assembly processes of phytoplankton communities in the river-oxbow lake system of Tibetan Plateau floodplain between non-flood and flood periods. The results showed that phytoplankton communities had significant seasonal and habitat variations, with the seasonal variations being more remarkable. Phytoplankton density, biomass, and alpha diversity were distinctly lower in the flood than non-flood period. The habitat differences (rivers vs. oxbow lakes) in phytoplankton community were less pronounced during the flood than non-flood period, most likely due to the increased hydrological connectivity. There was a significant distance-decay relationship only in lotic phytoplankton communities, and such relationship was stronger in the non-flood than flood period. Variation partitioning and PER-SIMPER analysis showed that the relative role of environmental filtering and spatial processes affecting phytoplankton assemblages varied across hydrological periods, with environmental filtering dominating in the non-flood period and spatial processes in the flood period. These results suggest that the flow regime plays a key role in balancing environmental and spatial factors in shaping phytoplankton communities. This study contributes to a deeper understanding of ecological phenomena in highland floodplains and provides a theoretical basis for floodplain ecosystem maintenance and ecological health management.