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Acute lung injury (ALI) is caused by a variety of intrapulmonary and extrapulmonary factors and is associated with high morbidity and mortality. Oxidative stress is an important part of the pathological mechanism of ALI. Ferroptosis is a mode of programmed cell death distinguished from others and characterized by iron-dependent lipid peroxidation. This article reviews the metabolic regulation of ferroptosis, its role in the pathogenesis of ALI, and the use of ferroptosis as a therapeutic target regarding the pharmacological treatment of ALI.
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BACKGROUND: Periodontal tissue loss is the main reason for tooth mobility and loss caused by periodontal disease. Dental follicle stem cells (DFSCs) have significant therapeutic potential in periodontal regeneration, which maybe mainly depends on their potent immunomodulatory capacity. Consequently, this study aims to elucidate the impact of implanted xenogenous DFSCs on innate immune responses during early and late stages in the periodontal defect repair period. METHODS: To trace and investigate the immunomodulation mechanisms of DFSCs in vivo, DFSCs were engineered (E-DFSCs) using lentiviral vectors expressing CD63-enhanced green fluorescent protein (CD63-EGFP) and ß-Actin-mCherry protein (ACTB-mCherry) to exhibit green and red fluorescence. The biological characteristics and functions of E-DFSCs were verified by proliferation, differentiation, and co-culture experiments in vitro. In vivo, the periodontal regeneration capacity of E-DFSCs was detected by implantation of murine periodontal defect model, and the response of innate immune cells was detected at the 1st, 3rd, and 5th days (early stage) and 4th week (late stage) after implantation. RESULTS: In vitro assessments showed that E-DFSCs retain similar properties to their non-engineered counterparts but exhibit enhanced macrophage immunomodulation capability. In mice models, four-week micro-CT and histological evaluations indicated that E-DFSCs have equivalent efficiency to DFSCs in periodontal defect regeneration. At the early stage of repair in mice periodontal defect, fluorescence tracking showed that implanted E-DFSCs might primarily activate endogenous cells through direct contact and indirect actions, and most of these cells are myeloperoxidase-positive neutrophils. Additionally, compared with the control group, the neutrophilic infiltration and conversion of N2-type were significantly increased in the E-DFSC group. At the late stage of defect regeneration, more M2-type macrophages, fewer TRAP + osteoclasts, and an upregulated OPG/RANKL ratio were detected in the E-DFSC group compared to the control group, which indicated that immune balance tilts towards healing and bone formation. CONCLUSION: The xenogenous implanted DFSCs can induce the N2 phenotype of neutrophils in the early stage, which can activate the innate immune mechanism of the host to promote periodontal tissue regeneration.
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Saco Dental , Neutrófilos , Células Madre , Animales , Saco Dental/citología , Saco Dental/metabolismo , Ratones , Neutrófilos/metabolismo , Células Madre/metabolismo , Células Madre/citología , Regeneración , Diferenciación Celular , Periodoncio , Fenotipo , Trasplante de Células Madre/métodos , HumanosRESUMEN
Increasing evidence underscores the pivotal role of ferroptosis in Parkinson's Disease (PD) pathogenesis. Acteoside (ACT) has been reported to possess neuroprotective properties. However, the effects of ACT on ferroptosis and its molecular mechanisms remain unknown. This study aimed to explore whether ACT can regulate ferroptosis in dopaminergic (DA) neurons within both in vitro and in vivo PD models and to elucidate the underlying regulatory mechanisms. PD models were established and treated with various concentrations of ACT. Cell viability assays, Western blot, lipid peroxidation assessments, immunohistochemistry, and transmission electron microscopy were employed to confirm ACT's inhibition of ferroptosis and its protective effect on DA neurons across PD models. Immunofluorescence staining, MitoSOX staining, and confocal laser scanning microscopy further validated ACT's regulation regulatory effects on ferroptosis via the Nrf2-mitophagy pathway. Four animal behavioral tests were used to assess behavioral improvements in PD animals. ACT inhibited ferroptosis in PD models in vitro, as evidenced by increased cell viability, the upregulation of GPX4 and SLC7A11, reduced lipid peroxides, and attenuation of mitochondrial morphological alterations typical of ferroptosis. By activating the Nrf2-mitophagy axis, ACT enhanced mitochondrial integrity and reduced lipid peroxidation, mitigating ferroptosis. These in vitro results were consistent with in vivo findings, where ACT treatment significantly preserved DA neurons, curbed ferroptosis in these cells, and alleviated cognitive and behavioral deficits. This study is the first demonstration of ACT's capability to inhibit neuronal ferroptosis and protect DA neurons, thus alleviating behavioral and cognitive impairments in both in vitro and in vivo PD models. Furthermore, The suppression of ferroptosis by ACT is achieved through the activation of the Nrf2-mitophagy signaling pathway. Our results show that ACT is beneficial for both treating and preventing PD. They also offer novel therapeutic options for treating PD and molecular targets for regulating ferroptosis.
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Peripheral sensory neurons widely innervate various tissues to continuously monitor and respond to environmental stimuli. Whether peripheral sensory neurons innervate the spleen and modulate splenic immune response remains poorly defined. Here, we demonstrate that nociceptive sensory nerve fibers extensively innervate the spleen along blood vessels and reach B cell zones. The spleen-innervating nociceptors predominantly originate from left T8-T13 dorsal root ganglia (DRGs), promoting the splenic germinal center (GC) response and humoral immunity. Nociceptors can be activated by antigen-induced accumulation of splenic prostaglandin E2 (PGE2) and then release calcitonin gene-related peptide (CGRP), which further promotes the splenic GC response at the early stage. Mechanistically, CGRP directly acts on B cells through its receptor CALCRL-RAMP1 via the cyclic AMP (cAMP) signaling pathway. Activating nociceptors by ingesting capsaicin enhances the splenic GC response and anti-influenza immunity. Collectively, our study establishes a specific DRG-spleen sensory neural connection that promotes humoral immunity, suggesting a promising approach for improving host defense by targeting the nociceptive nervous system.
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Péptido Relacionado con Gen de Calcitonina , Centro Germinal , Inmunidad Humoral , Bazo , Animales , Masculino , Ratones , Linfocitos B/inmunología , Linfocitos B/metabolismo , Péptido Relacionado con Gen de Calcitonina/metabolismo , Capsaicina/farmacología , AMP Cíclico/metabolismo , Dinoprostona/metabolismo , Ganglios Espinales/metabolismo , Centro Germinal/inmunología , Ratones Endogámicos C57BL , Nociceptores/metabolismo , Proteína 1 Modificadora de la Actividad de Receptores/metabolismo , Células Receptoras Sensoriales/metabolismo , Células Receptoras Sensoriales/efectos de los fármacos , Transducción de Señal , Bazo/inervación , Bazo/inmunología , FemeninoRESUMEN
Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases.
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COVID-19 , Enfermedades Transmisibles , Adulto , Humanos , Persona de Mediana Edad , COVID-19/epidemiología , Brotes de Enfermedades , Cuarentena , SARS-CoV-2 , Adolescente , Adulto JovenRESUMEN
BACKGROUND: ALI/ARDS is a syndrome of acute onset characterized by progressive hypoxemia and noncardiogenic pulmonary edema as the primary clinical manifestations. Necroptosis is a form of programmed cell necrosis that is precisely regulated by molecular signals. This process is characterized by organelle swelling and membrane rupture, is highly immunogenic, involves extensive crosstalk with various cellular stress mechanisms, and is significantly implicated in the onset and progression of ALI/ARDS. METHODS: The current body of literature on necroptosis and ALI/ARDS was thoroughly reviewed. Initially, an overview of the molecular mechanism of necroptosis was provided, followed by an examination of its interactions with apoptosis, pyroptosis, autophagy, ferroptosis, PANOptosis, and NETosis. Subsequently, the involvement of necroptosis in various stages of ALI/ARDS progression was delineated. Lastly, drugs targeting necroptosis, biomarkers, and current obstacles were presented. CONCLUSION: Necroptosis plays an important role in the progression of ALI/ARDS. However, since ALI/ARDS is a clinical syndrome caused by a variety of mechanisms, we emphasize that while focusing on necroptosis, it may be more beneficial to treat ALI/ARDS by collaborating with other mechanisms.
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Lesión Pulmonar Aguda , Necroptosis , Humanos , Lesión Pulmonar Aguda/patología , Lesión Pulmonar Aguda/inmunología , Animales , Síndrome de Dificultad Respiratoria/patología , Autofagia , ApoptosisRESUMEN
The pathogenesis of glioma has remained unclear. In this study, it was found that high expression of the outer dense fibers of sperm tail 3B (ODF3B) in gliomas was positively correlated with the grade of glioma. The higher the grade, the worse the prognosis. ODF3B is closely related to the growth and apoptosis of glioma. In terms of mechanism, ODF3B was found to affect the proliferation and apoptosis of glioma through the JAK1 and JAK2/STAT3 pathways. ODF3B was also found to affect the growth and apoptosis of glioma in vivo. We conclude that ODF3B affects glioma proliferation and apoptosis via the JAK/STAT pathway and is a potential therapeutic target.
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OBJECTIVES: To understand the growth and development status and differences between small for gestational age (SGA) and appropriate for gestational age (AGA) preterm infants during corrected ages 0-24 months, and to provide a basis for early health interventions for preterm infants. METHODS: A retrospective study was conducted, selecting 824 preterm infants who received regular health care at the Guangzhou Women and Children's Medical Center from July 2019 to July 2022, including 144 SGA and 680 AGA infants. The growth data of SGA and AGA groups at birth and corrected ages 0-24 months were analyzed and compared. RESULTS: The SGA group had significantly lower weight and length than the AGA group at corrected ages 0-18 months (P<0.05), while there were no significant differences between the two groups at corrected age 24 months (P>0.05). At corrected age 24 months, 85% (34/40) of SGA and 79% (74/94) of AGA preterm infants achieved catch-up growth. Stratified analysis by gestational age showed that there were significant differences in weight and length at corrected ages 0-9 months between the SGA subgroup with gestational age <34 weeks and the AGA subgroups with gestational age <34 weeks and 34 weeks (P<0.05). In addition, the weight and length of the SGA subgroup with gestational age 34 weeks showed significant differences compared to the AGA subgroups with gestational age <34 weeks and 34 weeks at corrected ages 0-18 months and corrected ages 0-12 months, respectively (P<0.05). Catch-up growth for SGA infants with gestational age <34 weeks and 34 weeks mainly occurred at corrected ages 0-12 months and corrected ages 0-18 months, respectively. CONCLUSIONS: SGA infants exhibit delayed early-life physical growth compared to AGA infants, but can achieve a higher proportion of catch-up growth by corrected age 24 months than AGA infants. Catch-up growth can be achieved earlier in SGA infants with a gestational age of <34 weeks compared to those with 34 weeks.
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Recien Nacido Prematuro , Recién Nacido Pequeño para la Edad Gestacional , Recién Nacido , Niño , Lactante , Femenino , Humanos , Preescolar , Edad Gestacional , Estudios Longitudinales , Estudios RetrospectivosRESUMEN
The embryonic mesoderm comprises heterogeneous cell subpopulations with distinct lineage biases. It is unclear whether a bias for the human hematopoietic lineage emerges at this early developmental stage. In this study, we integrated single-cell transcriptomic analyses of human mesoderm cells from embryonic stem cells and embryos, enabling us to identify and define the molecular features of human hematopoietic mesoderm (HM) cells biased towards hematopoietic lineages. We discovered that BMP4 plays an essential role in HM specification and can serve as a marker for HM cells. Mechanistically, BMP4 acts as a downstream target of HDAC1, which modulates the expression of BMP4 by deacetylating its enhancer. Inhibition of HDAC significantly enhances HM specification and promotes subsequent hematopoietic cell differentiation. In conclusion, our study identifies human HM cells and describes new mechanisms for human hematopoietic development.
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Células Madre Embrionarias , Mesodermo , Humanos , Diferenciación Celular/genética , Mesodermo/metabolismo , Linaje de la Célula/genéticaRESUMEN
INTRODUCTION: Synthetic lethality (SL) provides an opportunity to leverage different genetic interactions when designing synergistic combination therapies. To further explore SL-based combination therapies for cancer treatment, it is important to identify and mechanistically characterize more SL interactions. Artificial intelligence (AI) methods have recently been proposed for SL prediction, but the results of these models are often not interpretable such that deriving the underlying mechanism can be challenging. OBJECTIVES: This study aims to develop an interpretable AI framework for SL prediction and subsequently utilize it to design SL-based synergistic combination therapies. METHODS: We propose a knowledge and data dual-driven AI framework for SL prediction (KDDSL). Specifically, we use gene knowledge related to the SL mechanism to guide the construction of the model and develop a method to identify the most relevant gene knowledge for the predicted results. RESULTS: Experimental and literature-based validation confirmed a good balance between predictive and interpretable ability when using KDDSL. Moreover, we demonstrated that KDDSL could help to discover promising drug combinations and clarify associated biological processes, such as the combination of MDM2 and CDK9 inhibitors, which exhibited significant anti-cancer effects in vitro and in vivo. CONCLUSION: These data underscore the potential of KDDSL to guide SL-based combination therapy design. There is a need for biomedicine-focused AI strategies to combine rational biological knowledge with developed models.
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Most mammals tolerate exposure to hypobaric hypoxia poorly as it may affect multiple regulatory mechanisms and inhibit cell proliferation, promote apoptosis, limit tissue vascularization, and disrupt the acid-base equilibrium. Here, we quantified the functional state of germ cell development and demonstrated the interaction between the germ and somatic cells via single-cell RNA sequencing (scRNA-seq). The present study elucidated the regulatory effects of hypobaric hypoxia exposure on germ cell formation and sperm differentiation by applying enrichment analysis to genomic regions. Hypobaric hypoxia downregulates the genes controlling granule secretion and organic matter biosynthesis, upregulates tektin 1 (TEKT1) and kinesin family member 2C (KIF2C), and downregulates 60S ribosomal protein 11 (RPL11) and cilia- and flagella-associated protein 206 (CFAP206). Our research indicated that prosaposin-G protein-coupled receptor 37 (PSAP-GPR37) ligands mediate the damage to supporting cells caused by hypobaric hypoxic exposure. The present work revealed that hypoxia injures peritubular myoid (PTM) cells and spermatocytes in the S phase. It also showed that elongating spermatids promote maturation toward the G2 phase and increase their functional reserve for sperm-egg binding. The results of this study provide a theoretical basis for future investigations on prophylactic and therapeutic approaches toward protecting the reproductive system against the harmful effects of hypobaric hypoxic exposure.
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Purpose: Xiang-Sha-Liu-Jun-Zi-Tang(XSLJZT) is a common formula for the treatment of Gastric Cancer(GC) and is widely used in clinical practice, however, there is a lack of investigation into its mechanism. Methods: We collected and organized drug and disease targets, constructed the "XSLJZT-Active Ingredient-Target" visualization network, and performed GO and KEGG functional enrichment analysis of crossover genes, followed by molecular docking of active ingredients and core targets. The best docked monomers were combined with weighted gene co-expression network analysis(WGCNA) and macroscopically analyzed by GO and KEGG enrichment techniques. The results of cluster gene difference analysis, ROC evaluation, and CIBERSORT immune infiltration analysis were evaluated and finally supported by cellular experiments. Results: The main components of XSLJZT are quercetin, stigmasterol, and naringenin, effectively treat GC by targeting STAT3, TP53 and MAPK3, which are involved in IL-17, TNF and HIF-1 signaling pathways. The results of molecular docking showed that quercetin bound better to the core targets. We performed an in-depth analysis of this monomer and found that quercetin acts on the core targets of TP53, MMP9, TIMP1 and MYC, and is involved in two key signaling pathways, TNF and IL-17, thus effectively treating GC. The experimental results are consistent with our analysis that quercetin inhibits the proliferation of GC cells and promotes apoptosis, and TP53, MYC and TIMP1 are the quercetin targets for the treatment of GC. Conclusion: The present study tentatively suggests that quercetin, the main active ingredient in XSLJZT, can exert a therapeutic effect on GC by targeting TIMP1.
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Sepsis is an uncontrolled host response to infection, resulting in a clinical syndrome involving multiple organ dysfunctions. Cardiac damage is the most common organ damage in sepsis. Uncontrolled inflammatory response is an important mechanism in the pathogenesis of septic cardiomyopathy (SCM). NLRP3 inflammasome promotes inflammatory response by controlling the activation of caspase-1 and the release of pro-inflammatory cytokines interleukin IL-1ß and IL-18. The role of NLRP3 inflammasome has received increasing attention, but its activation mechanism and regulation of inflammation in SCM remain to be investigated.
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Cardiomiopatías , Sepsis , Humanos , Inflamasomas , Proteína con Dominio Pirina 3 de la Familia NLR/genética , Caspasa 1RESUMEN
Cancer is an extremely complex disease and each type of cancer usually has several different subtypes. Multi-omics data can provide more comprehensive biological information for identifying and discovering cancer subtypes. However, existing unsupervised cancer subtyping methods cannot effectively learn comprehensive shared and specific information of multi-omics data. Therefore, a novel method is proposed based on shared and specific representation learning. For each omics data, two autoencoders are applied to extract shared and specific information, respectively. To reduce redundancy and mutual interference, orthogonality constraint is introduced to separate shared and specific information. In addition, contrastive learning is applied to align the shared information and strengthen their consistency. Finally, the obtained shared and specific information for all samples are used for clustering tasks to achieve cancer subtyping. Experimental results demonstrate that the proposed method can effectively capture shared and specific information of multi-omics data and outperform other state-of-the-art methods on cancer subtyping.
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Combination therapy is a promising clinical treatment strategy for cancer and other complex diseases. Multiple drugs can target multiple proteins and pathways, greatly improving the therapeutic effect and slowing down drug resistance. To narrow the search space of synergistic drug combinations, many prediction models have been developed. However, drug combination datasets always have the characteristics of class imbalance. Synergistic drug combinations receive the most attention in clinical application but are in small numbers. To predict synergistic drug combinations in different cancer cell lines, in this study, we propose a genetic algorithm-based ensemble learning framework, GA-DRUG, to address the problems of class imbalance and high dimensionality of input data. The cell-line-specific gene expression profiles under drug perturbations are used to train GA-DRUG, which contains imbalanced data processing and the search of global optimal solutions. Compared to 11 state-of-the-art algorithms, GA-DRUG achieves the best performance and significantly improves the prediction performance in the minority class (Synergy). The ensemble framework can effectively correct the classification results of a single classifier. In addition, the cellular proliferation experiment performed on several previously unexplored drug combinations further confirms the predictive ability of GA-DRUG.
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Algoritmos , Neoplasias , Humanos , Combinación de Medicamentos , Neoplasias/tratamiento farmacológico , Proteínas , Aprendizaje AutomáticoRESUMEN
Background: Polycystic ovary syndrome (PCOS) is one of the most common gynecological endocrine diseases for women of puberty and reproductive age. PCOS can affect women's health for the rest of their lives since the incidence of coronary heart disease (CHD) may increase in the perimenopausal and senile periods among PCOS women compared with non-PCOS women. Method: A literature retrieval based on the Science Citation Index Expanded (SCI-E) database. All obtained records results were downloaded in plain text format for subsequent analysis. VOSviewer v1.6.10, Citespace and Microsoft Excel 2010 software were utilized for analyzing the following terms: countries, institutions, authors, journals, references and keywords. Results: There were 312 articles retrieved from January 1, 2000 to February 8, 2023, and the frequency of citations was 23,587. The United States, England, and Italy contributed the majority of the records. Harvard University, the University of Athens, and Monash University were the top 3 most productive institutions with publications on the relationship between PCOS and CHD. Journal of clinical endocrinology & metabolism ranked first with the highest publications (24 records), followed by Fertility and sterility (18 records). The keywords were divided into six clusters in the overlay keywords network: (1) the correlation between CHD risk factors and PCOS women; (2) the relationship between cardiovascular disease and female reproductive system hormone secretion; (3) the interaction between CHD and metabolic syndrome; (4) the relationship between c-reactive protein and endothelial function and oxidative stress in PCOS patients; (5) the potential positive effect of metformin on reducing CHD risk factors in PCOS patients; (6) the study of serum cholesterol and body-fat distribution in patients with CHD in PCOS. Oxidative stress, genome-wide association, obesity, primary prevention, and sex difference were main hotspots in this field in recent five years according to the keyword citation burst analysis. Conclusion: The article obtained the hotspots and trends and provided a reference for subsequent research on the association between PCOS and CHD. Moreover, it is hypothesized that oxidative stress and genome-wide association were frontier hotspots in studies that explore the relationship between PCOS and CHD, and prevention research may be valued in the future.
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Enfermedad Coronaria , Síndrome del Ovario Poliquístico , Humanos , Femenino , Masculino , Síndrome del Ovario Poliquístico/complicaciones , Síndrome del Ovario Poliquístico/epidemiología , Estudio de Asociación del Genoma Completo , Bibliometría , FertilidadRESUMEN
RATIONALE: Cerebral venous sinus thrombosis (CVST) represents 0.5% to 1% of all strokes. CVST can cause headaches, epilepsy, and subarachnoid hemorrhage (SAH). CVST is easily misdiagnosed because of the variety and non-specificity of symptoms. Herein, we report a case of infectious thrombosis of the superior sagittal sinus with SAH. PATIENT CONCERNS: A 34-year-old man presented to our hospital with a 4-hour history of sudden and persistent headache and dizziness with tonic convulsions of the limbs. Computed tomography revealed SAH with edema. Enhanced magnetic resonance imaging showed an irregular filling defect in the superior sagittal sinus. DIAGNOSES: The final diagnosis was hemorrhagic superior sagittal sinus thrombosis and secondary epilepsy. INTERVENTIONS: He was treated with antibiotic, antiepileptic, fluids to rehydrate, and intravenous dehydration. OUTCOMES: After treatment, the seizures did not recur and the symptoms were relieved. One month after the antibiotic treatment, the muscle strength of the patient's right extremity was restored to level 5, and there was no recurrence of his neurological symptoms. LESSONS: We describe a case of infectious thrombosis of the superior sagittal sinus manifested as SAH, which is easily misdiagnosed, especially when patients present with an infection. Clinicians must therefore take care during the diagnosis and selection of the treatment strategy.
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Trombosis del Seno Sagital , Trombosis de los Senos Intracraneales , Hemorragia Subaracnoidea , Trombosis , Masculino , Humanos , Adulto , Hemorragia Subaracnoidea/etiología , Seno Sagital Superior , Imagen por Resonancia Magnética/efectos adversos , Convulsiones/complicaciones , Cefalea/diagnóstico , Trombosis/complicaciones , Trombosis de los Senos Intracraneales/complicacionesRESUMEN
Combination therapy is a promising approach in treating multiple complex diseases. However, the large search space of available drug combinations exacerbates challenge for experimental screening. To predict synergistic drug combinations in different cancer cell lines, we propose an improved deep forest-based method, ForSyn, and design two forest types embedded in ForSyn. ForSyn handles imbalanced and high-dimensional data in medium-/small-scale datasets, which are inherent characteristics of drug combination datasets. Compared with 12 state-of-the-art methods, ForSyn ranks first on four metrics for eight datasets with different feature combinations. We conduct a systematic analysis to identify the most appropriate configuration parameters. We validate the predictive value of ForSyn with cell-based experiments on several previously unexplored drug combinations. Finally, a systematic analysis of feature importance is performed on the top contributing features extracted by ForSyn. The resulting key genes may play key roles on corresponding cancers.
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Biología Computacional , Neoplasias , Humanos , Biología Computacional/métodos , Neoplasias/tratamiento farmacológico , Combinación de Medicamentos , Línea CelularRESUMEN
Established taxonomy system based on disease symptom and tissue characteristics have provided an important basis for physicians to correctly identify diseases and treat them successfully. However, these classifications tend to be based on phenotypic observations, lacking a molecular biological foundation. Therefore, there is an urgent to integrate multi-dimensional molecular biological information or multi-omics data to redefine disease classification in order to provide a powerful perspective for understanding the molecular structure of diseases. Therefore, we offer a flexible disease classification that integrates the biological process, gene expression, and symptom phenotype of diseases, and propose a disease-disease association network based on multi-view fusion. We applied the fusion approach to 223 diseases and divided them into 24 disease clusters. The contribution of internal and external edges of disease clusters were analyzed. The results of the fusion model were compared with Medical Subject Headings, a traditional and commonly used disease taxonomy. Then, experimental results of model performance comparison show that our approach performs better than other integration methods. As it was observed, the obtained clusters provided more interesting and novel disease-disease associations. This multi-view human disease association network describes relationships between diseases based on multiple molecular levels, thus breaking through the limitation of the disease classification system based on tissues and organs. This approach which motivates clinicians and researchers to reposition the understanding of diseases and explore diagnosis and therapy strategies, extends the existing disease taxonomy. Availability of data and materials: The preprocessed dataset and source code supporting the conclusions of this article are available at GitHub repository https://github.com/yangxiaoxi89/mvHDN.
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Synergistic drug combinations have demonstrated effective therapeutic effects in cancer treatment. Deep learning methods accelerate identification of novel drug combinations by reducing the search space. However, potential adverse drug-drug interactions (DDIs), which may increase the risks for combination therapy, cannot be detected by existing computational synergy prediction methods. We propose DEML, an ensemble-based multi-task neural network, for the simultaneous optimization of five synergy regression prediction tasks, synergy classification, and DDI classification tasks. DEML uses chemical and transcriptomics information as inputs. DEML adapts the novel hybrid ensemble layer structure to construct higher order representation using different perspectives. The task-specific fusion layer of DEML joins representations for each task using a gating mechanism. For the Loewe synergy prediction task, DEML overperforms the state-of-the-art synergy prediction method with an improvement of 7.8% and 13.2% for the root mean squared error and the R2 correlation coefficient. Owing to soft parameter sharing and ensemble learning, DEML alleviates the multi-task learning 'seesaw effect' problem and shows no performance loss on other tasks. DEML has a superior ability to predict drug pairs with high confidence and less adverse DDIs. DEML provides a promising way to guideline novel combination therapy strategies for cancer treatment.