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1.
Diabetes Res Clin Pract ; 204: 110917, 2023 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-37748711

RESUMO

AIM: To explore the influencing factors of Type 2 diabetes mellitus (T2DM) in the rural population of Henan Province and evaluate the predictive ability of non-invasive factors to T2DM. METHODS: A total of 30,020 participants from the Henan Rural Cohort Study in China were included in this study. The dataset was randomly divided into a training set and a testing set with a 50:50 split for validation purposes. We used logistic regression analysis to investigate the association between 56 factors and T2DM in the training set (false discovery rate < 5 %) and significant factors were further validated in the testing set (P < 0.05). Gradient Boosting Machine (GBM) model was used to determine the ability of the non-invasive variables to classify T2DM individuals accurately and the importance ranking of these variables. RESULTS: The overall population prevalence of T2DM was 9.10 %. After adjusting for age, sex, educational level, marital status, and body measure index (BMI), we identified 13 non-invasive variables and 6 blood biochemical indexes associated with T2DM in the training and testing dataset. The top three factors according to the GBM importance ranking were pulse pressure (PP), urine glucose (UGLU), and waist-to-hip ratio (WHR). The GBM model achieved a receiver operating characteristic (AUC) curve of 0.837 with non-invasive variables and 0.847 for the full model. CONCLUSIONS: Our findings demonstrate that non-invasive variables that can be easily measured and quickly obtained may be used to predict T2DM risk in rural populations in Henan Province.


Assuntos
Diabetes Mellitus Tipo 2 , Humanos , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Estudos de Coortes , Fatores de Risco , População Rural , Índice de Massa Corporal , Circunferência da Cintura , China/epidemiologia
2.
JMIR Public Health Surveill ; 9: e43381, 2023 05 22.
Artigo em Inglês | MEDLINE | ID: mdl-37213192

RESUMO

BACKGROUND: Multimorbidity causes substantial disease and economic burdens on individuals and the health care system. OBJECTIVE: This study aimed to explore the disease burden of multimorbidity and the potential correlations among chronic noncommunicable diseases (NCDs) in a rural population in Henan, China. METHODS: A cross-sectional analysis was performed using the baseline survey of the Henan Rural Cohort Study. Multimorbidity was defined as the simultaneous occurrence of at least two NCDs in a participant. This study examined the multimorbidity pattern of 6 NCDs, including hypertension, dyslipidemia, type 2 diabetes mellitus, coronary heart disease, stroke, and hyperuricemia. RESULTS: From July 2015 to September 2017, a total of 38,807 participants (aged 18-79 years; 15,354 men and 23,453 women) were included in this study. The overall population prevalence of multimorbidity was 28.1% (10,899/38,807), and the multimorbidity of hypertension and dyslipidemia was the most common (8.1%, 3153/38,807). Aging, higher BMI, and unfavorable lifestyles were significantly associated with a higher risk of multimorbidity (multinomial logistic regression, all P<.05). The analysis of the mean age at diagnosis suggested a cascade of interrelated NCDs and their accumulation over time. Compared with participants without 2 conditional NCDs, participants with 1 conditional NCD would have higher odds of another NCD (1.2-2.5; all P<.05), and those with 2 conditional NCDs would elevate the odds of the third NCD to 1.4-3.5 (binary logistic regression, all P<.05). CONCLUSIONS: Our findings indicate a plausible tendency for the coexistence and accumulation of NCDs in a rural population in Henan, China. Early prevention of multimorbidity is essential to reduce the NCD burden in the rural population.


Assuntos
Diabetes Mellitus Tipo 2 , Hipertensão , Doenças não Transmissíveis , Masculino , Humanos , Feminino , Estudos Transversais , Multimorbidade , Doenças não Transmissíveis/epidemiologia , Estudos de Coortes , Diabetes Mellitus Tipo 2/epidemiologia , População Rural , Doença Crônica , Hipertensão/epidemiologia , Efeitos Psicossociais da Doença
3.
Nature ; 606(7912): 146-152, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-35614219

RESUMO

Real-world memories are formed in a particular context and are often not acquired or recalled in isolation1-5. Time is a key variable in the organization of memories, as events that are experienced close in time are more likely to be meaningfully associated, whereas those that are experienced with a longer interval are not1-4. How the brain segregates events that are temporally distinct is unclear. Here we show that a delayed (12-24 h) increase in the expression of C-C chemokine receptor type 5 (CCR5)-an immune receptor that is well known as a co-receptor for HIV infection6,7-after the formation of a contextual memory determines the duration of the temporal window for associating or linking that memory with subsequent memories. This delayed expression of CCR5 in mouse dorsal CA1 neurons results in a decrease in neuronal excitability, which in turn negatively regulates neuronal memory allocation, thus reducing the overlap between dorsal CA1 memory ensembles. Lowering this overlap affects the ability of one memory to trigger the recall of the other, and therefore closes the temporal window for memory linking. Our findings also show that an age-related increase in the neuronal expression of CCR5 and its ligand CCL5 leads to impairments in memory linking in aged mice, which could be reversed with a Ccr5 knockout and a drug approved by the US Food and Drug Administration (FDA) that inhibits this receptor, a result with clinical implications. Altogether, the findings reported here provide insights into the molecular and cellular mechanisms that shape the temporal window for memory linking.


Assuntos
Região CA1 Hipocampal , Memória , Neurônios , Receptores CCR5 , Animais , Região CA1 Hipocampal/citologia , Região CA1 Hipocampal/fisiologia , Memória/fisiologia , Rememoração Mental/fisiologia , Camundongos , Neurônios/metabolismo , Receptores CCR5/deficiência , Receptores CCR5/genética , Receptores CCR5/metabolismo , Fatores de Tempo
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