201 research outputs found
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λλ΄μ μ€ μλ, κ΅μ‘, κ³ μ©, ADL, IADL, λ§μ± μ§ν, κ°κ΅¬ κ΅¬μ± λ° μ¬ν νλμ΄ μ£Όκ΄μ 건κ°μΈμμ μ€μν μμμ΄λ€. λΆλͺ¨λ λ° μμλ
λκ° λ€ λλ΄ν μ¬λ μ€ μλ, IADL λ° λ§μ± μ§νμ μ£Όκ΄μ 건κ°μΈμμ μ€μν μμμ΄λ€.
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λλ΄μμμ μ°μΈμ¦ μ¦μμ΄ κ°μ₯ λ§μ΄ λνλ¬λ€. λΆλͺ¨ λλ΄μ μ€ μ±λ³, μλ, κ³ μ©, ADL, IADL, λ§μ± μ§ν λ° κ°νΈ κΈ°κ°μ΄ μκΈ° νκ° κ±΄κ°μ μ€μν μμλ‘ λ°νμ‘μ΅λλ€. μμ 보νΈμ μ€ μ±λ³, μλ, μμΉ, κ΅μ‘, ADL, IADL, λ§μ± μ§ν, μλ μ λ° μ¬νμ νλμ΄ μκΈ° νκ° κ±΄κ°μ μ€μν μμΈμΌλ‘ λ°νμ‘μ΅λλ€. λλ΄μ μ€ μ±λ³, μλ, ADL, IADL, λ§μ± μ§ν λ° κ°κ΅¬ ꡬμ±μ μκΈ° νκ° λ 건κ°μ μ€μν μμμ΄λ€.
μ΄ μ°κ΅¬λ μ€κ΅μ μμλ
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μ λμ΄ λ§μ μ‘°λΆλͺ¨ λλ¬ΈμΌ μ μμ΅λλ€. 첫째, μ€κ΅μμ λΆλͺ¨λ₯Ό λ°λΌ μΈμΆνμ§ λͺ»νκ³ μ§μ λ¨μμλ μμ΄κ° λ§μ΄ μλ€.λλ¬Έμ΄λ€. κ·Έλ° μμ΄λ€μ λ³΄ν΅ μ‘°λΆλͺ¨λμ 보μ΄νμ λ°μΌλ©° μ골μ λ¨κ²¨μ Έ μλ€. κ·Έλμ λλ΄κ°λλ λΆλͺ¨λ§μ λ보λ κ²λ³΄λ€ μμλ§μ λ보λ λ보λ μ¬λμ 2 λ°° μ΄μμ΄μλ€ (62.67λ 30.68 μκ°/μ£Ό). μμλ₯Ό λ보λ μΌμ κ±°μ μ κ·μ§κ³Ό κ°μλ€. μλ
κ° κ²°μνκ³ μμλ₯Ό λ보λ κ°λκ° λκΈ° λλ¬Έμ μμ λ보λ μ¬λμ μΌλ°μ μΌλ‘ μ§μΉ λλμ λ°μλ€. λν μμλ
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μ΄ μ°κ΅¬ κ²°κ³Όλ λλ΄ κ°λ, λλ΄ κΈ°κ° λ° μ£Όκ΄μ 건κ°μνμ ν΅κ³μ μΌλ‘ μ μν μ°κ΄μ±μ κ·λͺ
νμ§λ λͺ»νμλ€. μ΄μ μ°κ΅¬μ λΉκ΅ν λ, μ ν μ°κ΅¬μμ΄ μ°κ΅¬ κ°μ μκΈ° νκ° κ±΄κ° λ° μ°κ΅¬ μ ν μΈ‘μ μ μ°¨μ΄λ λ€λ₯Έ κ²°κ³Όλ₯Ό μ΄λνμ μ μλ€. μ£Όκ΄μ 건κ°μνμ μ°μΈ κ°μ μν₯μ λ―ΈμΉλ μμΈλ€μ λ¨λ©΄μ μΌλ‘ μ‘°μ¬ νμλ€. κ°μ‘± λλ΄ μ 곡 λ° κ±΄κ° (μ£Όκ΄μ 건κ°μν, μ°μΈκ°)μ μν₯μ λ―ΈμΉλ μμΈμ κ°μΈ νΉμ±, κ°μ‘± ꡬ쑰 λ° μ¬ν νλ μνμμ μΌκ΄λκ² λνλ¬λ€. μ΄λ κ°μ‘± λλ΄μμ λλ΄ μ 곡 λ° κ±΄κ°μ΄ μλκ³Ό κ°μ κ°μΈμ μμΈλΏλ§ μλλΌ κ°μ‘± ꡬ쑰 λ° μ¬ν νλ μνμ μν΄ μν₯μ λ°μμμ μμ¬νλ€.
μ£Όκ΄μ 건κ°μν λ° μ°μΈκ°κ³Ό κ΄λ ¨λ λ€μ°¨μμ μμΈμ κ°μ‘± λλ΄μλ₯Ό μν κ°μ
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μ μ·¨νλ ν¬κ΄μ μΈ μ κ·Ό λ°©μμ νμμ±μ λνλλ€. μλκ³Ό κ±΄κ° μ¬μ΄μ κ°λ ₯ν μ°κ΄μ±μ κ°μ‘± λλ΄μμ μ¬μ μ μ§μμ 건κ°μ κ°μ νλ ν¨κ³Όμ μΈ μ λ΅μ΄ λ μ μμμ μμ¬νλ€. μ¬ν νλκ³Ό κ±΄κ° μν κ°μ κ°ν μ°κ΄μ±μ κ°μ‘± λλ΄μ λ΄μμ μ¬νμ μ°Έμ¬λ₯Ό μ΄μ§νλ κ²μ΄ λ λμ κ±΄κ° μνλ₯Όμν ν¨κ³Όμ μΈ μ λ΅μ΄ λ μ μμμ μμ¬νλ€. λ§μ§λ§μΌλ‘, κ²°κ³Όλ λμ΄ κ±°μ£Όμκ° λμ κ±°μ£Όμλ³΄λ€ μΈλ κ° λ³΄μ΄νμ μ 곡 ν κ°λ₯μ±μ΄ λ λλ€λ κ²μ 보μ¬μ£Όμμ΅λλ€. μ€κ΅μ 곡곡 μμ€ λΆν¬κ° μ¬μ ν λμμ λμ΄μ μ°¨μ΄κ° μλ€(μ, μ μΉμ, μμμ). μ λΆλ λμ-λμ΄ κ²©μ°¨λ₯Ό μ€μ΄κΈ° μν΄ μ¬ν λ³΅μ§ ννμ±μ λ¬μ±νκ³ μ μ§νκΈ°μν ν¬κ΄μ μΈ μ κ·Ό λ°©μμ κ°λ°ν΄μΌ νλ€.China's population aged rapidly from 2010 to 2019, with life expectancy at birth increasing from 71.4 years to 77.3 years and the proportion of the population over 60 rising from 13.26% to 18.1% (NHCC, 2011-2020; NBSC, 2011-2020). Family care plays a vital role in taking the pressure of aging-related care issues. However, the maintenance of such family responsibilities can lead to negative physical and mental health consequences. Most research on the effects of caregiving focuses on Western countries. It is questionable whether Western caregivers' findings apply to Chinese society with family structures and family relationships differ from Western countries. Therefore, this study aims to investigate the relationship between family caregiving and caregivers' health among middle-aged and older adults in China by analyzing a representative sample. We compare the relationships overall and between three care-type groups: parent caregiving only, grandchild caregiving only, and both.
This study conducted a secondary analysis of the China Health and Retirement Longitudinal Study (CHARLS) wave 4 data. The CHARLS data is a national longitudinal survey of adults aged over 45 in China. A conceptual framework was drawn through a comprehensive review of the literature applied to create an analytic model, including individual characteristics, family structures, social participation status, family caregiving provision, and health outcomes. Family caregiving provision includes care type, care intensity, and care duration. Based on the review, care type includes parent caregiving only, grandchild caregiving only, and both. Health outcome is divided into self-rated health and depression. A five-point scale question measured self-rated health. Depression was measured using the CES-D-10, a 30-point scale.
This study compared the differences between non-caregivers and caregivers overall in individual characteristics, family characteristics, and social activity status using chi-square test and t-test. Next, this study also compared the differences between non-caregivers and caregivers classified by three-care types in individual characteristics, family characteristics, and social activity status using chi-square test, ANOVA analysis, and Tukey HSD test. Moreover, bivariate analysis and multivariate analysis were performed to identify the factors associated with family caregiving provision and the relationship between family caregiving provision and health. The results of this study are as follows.
Among the analytical sample of 6,871 caregivers, 74.36% were not in good self-rated health, and 36.24% presented with depressive symptoms as measured by CES-D-10.
Multivariate analysis of all caregivers results showed income, location, education, employment, ADL, IADL, chronic disease, household composition, and social activity status to be factors associated with caregivers' self-rated health. Study results also showed that age, sex, income, location, education, ADL, IADL, chronic diseases, the number of children, social activity, and care intensity are factors associated with caregivers depressive symptoms.
Multivariate analysis of the caregivers self-rated health by care type revealed that poor self-rated health was most prevalent among caregivers who only provided grandchild caregiving. For caregivers who only provided parent caregiving, gender, income, IADL, and chronic disease significantly affected self-rated health. For caregivers who only provided grandchildren caregiving, income, education, employment, ADL, IADL, chronic disease, multi-generation family, and social activity largely influence self-rated health. For caregivers who provided both parent and grandchild caregiving, income, IADL, and chronic disease were significant factors of self-rated health.
Multivariate analysis of the sample's depressive symptoms by care type revealed that depressive symptoms were also most prevalent among caregivers who only provided grandchild caregiving. For caregivers who only provided parent caregiving, gender, income, employment, ADL, IADL, chronic disease, and care duration were significant factors of depressive symptoms. For caregivers who only provided grandchild caregiving, gender, income, location, education, ADL, IADL, chronic disease, child number, and social activity were significant factors of depressive symptoms. For caregivers who provided both parent and grandchild caregiving, gender, income, ADL, IADL, chronic disease, and household composition were significant factors of depressive symptoms.
This study found that poor self-rated health and depressive symptoms were most prevalent among caregivers who cared for grandchildren. This result may be due to the millions of left-behind children and older grandparents in China. Firstly, left-behind children mean that childrens parents worked in a distant place. The children are left behind in their rural communities, cared for by their grandparents in China. The intensity was more than two times caregivers caring for grandchildren only than caring for parents only (62.67 vs 30.68 hours per week). Providing care to grandchildren was almost equivalent to a full-time job. With children absent and high intensity of care for grandchildren, grandchild caregivers commonly feel burn out. Also, caregivers who only cared for grandchildren were older than other types caregivers (60.48 vs. 53.51 and 56.52 years old). Older individuals may experience a deterioration of their health condition in older ages, limiting their capacity for social engagement and, in turn, influencing their well-being in later life.
The results of this study could not clarify a statistically significant association between care intensity, care duration and self-rated health. Compared with previous research, the difference in the measurement of self-rated health and study type between the earlier studies and this study may have resulted in different outcomes. Factors influencing self-rated health and depressive symptoms were examined cross-sectionally. The factors influencing family caregiving provision and health (self-rated health, depression) were consistently shown in individual characteristics, family structures, and social activity status. This suggests caregiving provision and health of family caregivers were influenced not only by personal factors such as income but also by family structures and social activity status.
The multidimensional factors associated with self-rated health and depressive symptoms indicated the need for a comprehensive approach to releasing intervention policy for family caregivers. The strong association between income and health suggests that promoting family caregivers' financial support could be an effective strategy to improve their health. The strong association between social activity and health advances that promoting social engagement within the family caregivers may improve their health. Finally, the results showed that rural caregivers had worse self-rated health and more depressive symptoms than urban caregivers. There is still an urban-rural disparity in social public infrastructure distribution (i.e., kindergartens, nursing homes) in China. The truth that the location influences health suggests reducing the rural-urban gap in public infrastructure distribution could be an effective health-equity strategy.Chapter 1. Introduction . 1
1.1 Background . 1
1.2 Objective . 4
Chapter 2. Literature review . 5
2.1 Theoretical background . 5
2.2 Family caregiving provision 6
2.2.1 Care type 6
2.2.2 Care intensity . 7
2.2.3 Care duration . 8
2.3 Factors associated with the family caregiving provision 10
2.3.1 Studies Abroad . 10
2.3.2 Studies in China . 12
2.4 The health of caregivers . 14
2.5 The relationship between family caregiving provision and self-rated health 16
2.5.1 Studies Abroad . 16
2.5.2 Studies in China . 17
2.6 The relationship between family caregiving provision and depressive symptom . 19
2.6.1 Studies Abroad . 19
2.6.2 Studies in China . 22
2.7 Literature review conclusion . 24
Chapter 3. Method 26
3.1 Conceptual framework 26
3.2 Study data . 27
3.3 Measurements . 29
3.3.1 Independent variable: General characteristics . 29
3.3.2 Independent variable: Care-related characteristics 31
3.3.3 Dependent variable 3
3 3.4 Statistical methods . 37
Chapter 4. Results . 38
4.1 Sample characteristics . 38
4.1.1 Descriptive statistics of the sample . 38
4.1.2 Family caregiving provision and health of the sample 42
4.2 Sample characteristics by care type . 44
4.2.1 Descriptive statistics of the sample by care type . 44
4.2.2 Caregiving provision and health of the sample by care type 49
4.3 Factors associated with care intensity 53
4.3.1 Bivariate analysis of the factors associated with care intensity. 53
4.3.2 Multivariate analysis of the factors associated with care intensity. 58
4.4 Factors associated with care duration 63
4.4.1 Bivariate analysis of the factors associated with care duration . 63
4.4.2 Multivariate analysis of the factors associated with care duration . 68
4.5 The relationship between family caregiving provision and self-rated health 73
4.5.1 Bivariate analysis of the relationship between family caregiving provision and self-rated health . 73
4.5.2 Multivariate analysis of the relationship between family caregiving provision and self-rated health . 78
4.6 The relationship between family caregiving provision and depressive symptom . 83
4.6.1 Bivariate analysis of the relationship between family caregiving provision and depressive symptom . 83
4.6.2 Multivariate analysis of the relationship between family caregiving provision and depressive symptom . 88
Chapter 5. Discussion . 93
5.1 Caregivers' characteristics, caregiving provision, and health in China . 93
5.2 Factors associated with family caregiving provision 97
5.2.1 Factors associated with family caregiving intensity 97
5.2.2 Factors associated with family caregiving duration 98
5.3 The relationship between family caregiving provision and health . 99
5.3.1 The relationship between family caregiving provision and self-rated health 99
5.3.2 The relationship between family caregiving provision and depression . 100
5.4 Policy implications 103
5.5 Significance and limitation of the study 105
Biography . 107
κ΅λ¬Έμ΄λ‘ 123Maste
An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings Learning
Unsupervised sentence embeddings learning has been recently dominated by
contrastive learning methods (e.g., SimCSE), which keep positive pairs similar
and push negative pairs apart. The contrast operation aims to keep as much
information as possible by maximizing the mutual information between positive
instances, which leads to redundant information in sentence embedding. To
address this problem, we present an information minimization based contrastive
learning (InforMin-CL) model to retain the useful information and discard the
redundant information by maximizing the mutual information and minimizing the
information entropy between positive instances meanwhile for unsupervised
sentence representation learning. Specifically, we find that information
minimization can be achieved by simple contrast and reconstruction objectives.
The reconstruction operation reconstitutes the positive instance via the other
positive instance to minimize the information entropy between positive
instances. We evaluate our model on fourteen downstream tasks, including both
supervised and unsupervised (semantic textual similarity) tasks. Extensive
experimental results show that our InforMin-CL obtains a state-of-the-art
performance.Comment: 11 pages, 3 figures, published to COLING 202
The Optimal Portfolio Model Based on Multivariate T Distribution with Fuzzy Mathematics Method
This paper proposed the optimal portfolio model maximizing returns and minimizing the risk expressed as CvaR under the assumption that the portfolio yield subject to multivariate t distribution. With Fuzzy Mathematics, we solve the multi-objectives model, and compare the model results to the case under the assumption of normal distribution yield, based on the portfolio VAR through empirical research. It is showed that our returns and risk are higher than M-V model.Key words: Multivariate t distribution; The optimal portfolio; VAR; CVAR; Multi-objectives programming; Fuzzy mathematic
Protective effect of maternal exposure to Ξ±-lipoic acid during pregnancy and lactation on susceptibility to OVAinduced neonatal asthma
Purpose: To investigate the beneficial effect of alpha-lipoic acid (ALA) during pregnancy and lactation on susceptibility to ovalbumin (OVA)-induced neonatal asthma, and the mechanism of involved.Methods: Pregnant BALB/c mice were administered ALA (1 % mixed with mouse chow) or standard mouse chow from 6th day of gestation to 21st day of lactation (postnatal). The offspring (neonatal pups) from the OVA and ALA+OVA groups were sensitized on 1st, 7th and 14th postnatal days (PNDs) via intraperitoneal (i.p.) injection of OVA (0.5 ΞΌg). Control mice pups were not exposed to OVA. On PND 21, all pubs were again exposed to 1 % OVA aerosol using a nebulizer.Results: Neonatal mice exposed to ALA showed a significant decline (p < 0.05) in the number of inflammatory cells (eosinophils), levels of inflammatory markers (IL-4, IL-13, IL-5 and TNF-Ξ±) as well as OVA-specific IgE and total IgE, when compared to neonatal mice from pregnant mice that did not receive ALA (control). Moreover, the antioxidant profiles of ALA-treated mice offspring were significantly improved (p < 0.05). Marked downregulation (p < 0.05) of the protein expressions of NF-ΞΊB p-p65 subunit and TNF-Ξ± were observed in ALA-treated mice pups.Conclusion: ALA exposure during pregnancy (maternal exposure) markedly decreases OVA-induced asthmatic airway inflammatory response in pups. Thus, ALA might be beneficial for use along with standard anti-asthmatic drugs in the management of pediatric asthmatic patient
Implications of lysyl oxidase-like protein 3 expression in the periodontium of diabetic rats
Objectives: Diabetes has been strongly associated with periodontal diseases. The periodontal ligament (PDL) has an abundant extracellular matrix (ECM). Lysyl oxidases (LOXs) are closely associated with various diseases caused by abnormal ECM functions, however, the role of LOXs in periodontal diseases induced by diabetes remains unclear. Methodology: In this study, 8-week-old Zucker diabetic fatty rats were used to establish a type 2 diabetes mellitus (T2DM) model. After 9 and 16 weeks, hematoxylin and eosin (H&E), Massonβs trichrome, and immunohistochemical staining were performed. Results:After 9 weeks, loose collagen fibers were found in the interradicular area of the diabetic group, in opposition to the control group. There were no significant differences in LOX expression between the diabetic and control groups (p>0.05). However, after 16 weeks, the diabetic group presented a disordered arrangement of the PDL, showing decreased collagen content and significantly increased lysyl oxidase-like protein 3 (LOXL3) expression when compared with the control group (p<0.05). This suggests that LOXL3 plays a significant role in periodontal histopathological changes in diabetic rats. Conclusion:Our study showed elevated LOXL3 expression in the PDL of diabetic rats after 16 weeks, suggesting that LOXL3 may be involved in the occurrence and development of periodontal histopathological changes in diabetic rats. LOXL3 could be further used as an indicator for the early diagnosis of diabetic periodontitis in T2DM patients in clinical settings
BMP4 inhibits myogenic differentiation of bone marrowβderived mesenchymal stromal cells in mdx mice
AbstractBackground aimsBone marrowβderived mesenchymal stromal cells (BMSCs) are a promising therapeutic option for treating Duchenne muscular dystrophy (DMD). Myogenic differentiation occurs in the skeletal muscle of the mdx mouse (a mouse model of DMD) after BMSC transplantation. The transcription factor bone morphogenic protein 4 (BMP4) plays a crucial role in growth regulation, differentiation and survival of many cell types, including BMSCs. We treated BMSCs with BMP4 or the BMP antagonist noggin to examine the effects of BMP signaling on the myogenic potential of BMSCs in mdx mice.MethodsWe added BMP4 or noggin to cultured BMSCs under myogenic differentiation conditions. We then injected BMP4- or noggin-treated BMSCs into the muscles of mdx mice to determine their myogenic potential.ResultsWe found that the expression levels of desmin and myosin heavy chain decreased after treating BMSCs with BMP4, whereas the expression levels of phosphorylated Smad, a downstream target of BMP4, were higher in these BMSCs than in the controls. Mdx mouse muscles injected with BMSCs pretreated with BMP4 showed decreased dystrophin expression and increased phosphorylated Smad levels compared with muscles injected with non-treated BMSCs. The opposite effects were seen after pretreatment with noggin, as expected.ConclusionsOur results identified BMP/Smad signaling as an essential negative regulator of promyogenic BMSC activity; inhibition of this pathway improved the efficiency of BMSC myogenic differentiation, which suggests that this pathway might serve as a target to regulate BMSC function for better myogenic differentiation during treatment of DMD and degenerative skeletal muscle diseases
Long-lived magmatic evolution and mineralization resulted in formation of the giant Cuonadong Sn-W-Be polymetallic deposit, southern Tibet
The Cuonadong Sn-W-Be polymetallic deposit is the first Cenozoic leucogranite-related rare-metal deposit with giant metallogenic potential in the Himalayan orogen. However, controlling factors for the supernormal enrichment of beryllium, tin and tungsten in this deposit remain vague. In this study, we carried out systematic geochronological, whole-rock geochemical, and Sr-Nd isotopic analysis for the Cuonadong leucogranites, as well as detailed ore-forming geochronological analysis. The monazite U-Th-Pb, cassiterite U-Pb and muscovite Ar-Ar dating results, together with previously reported geochronological data, indicate that the major Cuonadong leucogranites (including, from old to young, weakly-oriented two-mica, two-mica granite and muscovite) were formed during βΌ21-15 Ma, whereas the Sn-W-Be mineralization mainly occurred at βΌ18-14 Ma. The Cuonadong leucogranites show strong peraluminous (A/CNK=1.09-1.22) features, and have high SiO2 (71.62-75.97 wt.%) and Al2O3 (14.04-16.09 wt.%) and low MgO (0.07-0.33 wt.%), MnO (0.01-0.15 wt.%) and total Fe2O3 (0.36-1.01 wt.%) contents, and are enriched in large ion lithophile elements (e.g., Rb, U, K, and Pb). These geochemical features together with enriched Sr-Nd isotopes (Ξ΅Nd(t) = -15.7 to -11.7; (87Sr/86Sr)i=0.71957-0.76313) indicate that the Cuonadong leucogranites belong to S-type granite and were derived from muscovite-induced dehydration melting of metapelites of the Higher Himalayan Crystalline Sequence. Perceptible linear variations of some major elements (e.g., Na2O, K2O, MnO, Fe2O3T, TiO2 and A/CNK) with increasing Rb/Sr ratios suggest these leucogranites experienced different degrees of evolution. Quantitative simulation calculations based on the whole-rock Rb, Sr, and Ba contents imply that the Cuonadong leucogranites experienced increasingly-strong fractional crystallization of plagioclase, K-feldspar and biotite from the weakly-oriented two-mica granite to two-mica granite and muscovite granite. Importantly, intense fractional crystallization leaded to notable enrichment of Sn, W and Be, although these elements are not obviously high in the relatively primitive magma for the Cuonadong leucogranites. Significantly, evident REE tetrad effects and deviation of twin-element pair ratios (K/Rb, K/Ba, Zr/Hf, Nb/Ta, and Y/Ho) from the chondritic values demonstrate that intense interaction between melts and F-rich aqueous fluids occurred during magmatic evolution. This implies that the Cuonadong leucogranites were derived from a volatile-rich magmatic system. The abundant volatiles probably remarkably facilitated and extended the fractional crystallization though lowering the solidus and viscosity of the magma. Thus, we propose that long-lived crystal fractionation (βΌ21-15 Ma) and mineralization (βΌ18-14 Ma) collectively leaded to supernormal enrichment of Sn, W, and Be in the Cuonadong Sn-W-Be polymetallic deposit. In contrast, the enrichment of Sn, W, and Be during the partial melting was insignificant.publishedVersio
Integrative Multi-Omics Analysis of Identified NUF2 as a Candidate Oncogene Correlates With Poor Prognosis and Immune Infiltration in Non-Small Cell Lung Cancer
BackgroundLung cancer is one of the most common malignant tumors and the leading causes of cancer-related deaths worldwide. As a component of the nuclear division cycle 80 complex, NUF2 is a part of the conserved protein complex related to the centromere. Although the high expression of NUF2 has been reported in many different types of human cancers, the multi-omics analysis in non-small cell lung cancer (NSCLC) of NUF2 remains to be elucidated.MethodsIn this analysis, NUF2 expression difference analysis in non-small cell lung cancer was evaluated by Oncomine, TIMER, GEO, and TCGA database. And the prognosis analysis of NUF2 based on Kaplan-Meier was performed. R language was used to analyze the differential expression genes, functional annotation and protein-protein interaction (PPI). GSEA analysis of differential expression genes was also carried out. Mechanism analysis about exploring the characteristic of NUF2, multi-omics, and correlation analysis was carried out using UALCAN, cBioportal, GEPIA, TIMER, and TISIDB, respectively.ResultsThe expression of NUF2 in NSCLC, both lung adenocarcinoma (LUAD) and squamous lung cancer (LUSC), was significantly higher than that in normal tissues. The analysis of UALCAN database samples proved that NUF2 expression was connected with stage and smoking habits. Meanwhile, the overall survival curve also validated that high expression of NUF2 has a poorer prognosis in NSCLC. GO, KEGG, GSEA, subcellular location from COMPARTMENTS indicated that NUF2 may regulate the cell cycle. Correlation analysis also showed that NUF2 was mainly positively associated with cell cycle and tumor-related genes. NUF2 altered group had a poorer prognosis than unaltered group in NSCLC. Immune infiltration analysis showed that the NUF2 expression mainly have negatively correlation with immune cells and immune subtypes in LUAD and LUSC. Furthermore, quantitative PCR was used to validate the expression difference of NUF2 in LUAD and LUSC.ConclusionOur findings elucidated that NUF2 may play an important role in cell cycle, and significantly associated with tumor-related gene in NSCLC; we consider that NUF2 may be a prognostic biomarkers in NSCLC
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