A machine learning-based data mining in medical examination data: a biological features-based biological age prediction model.

BACKGROUND: Biological age (BA) has been recognized as a more accurate indicator of aging than chronological age (CA). However, the current limitations include: insufficient attention to the incompleteness of medical data for constructing BA; Lack of machine learning-based BA (ML-BA) on the Chinese population; Neglect of the influence of model overfitting degree on the stability of the association results. METHODS AND RESULTS: Based on the medical examination data of the Chinese population (45-90 years), we first evaluated the most suitable missing interpolation method, then constructed 14 ML-BAs based on biomarkers, and finally explored the associations between ML-BAs and health statuses (healthy risk indicators and disease). We found that round-robin linear regression interpolation performed best, while AutoEncoder showed the highest interpolation stability. We further illustrated the potential overfitting problem in ML-BAs, which affected the stability of ML-Bas' associations with health statuses. We then proposed a composite ML-BA based on the Stacking method with a simple meta-model (STK-BA), which overcame the overfitting problem, and associated more strongly with CA (r = 0.66, P < 0.001), healthy risk indicators, disease counts, and six types of disease. CONCLUSION: We provided an improved aging measurement method for middle-aged and elderly groups in China, which can more stably capture aging characteristics other than CA, supporting the emerging application potential of machine learning in aging research.

The tomato CONSTANS-LIKE protein SlCOL1 regulates fruit yield by repressing SFT gene expression.

BACKGROUND: CONSTANS (CO) and CONSTANS-LIKE (COL) transcription factors have been known to regulate a series of cellular processes including the transition from the vegetative growth to flower development in plants. However, their role in regulating fruit yield in tomato is poorly understood. RESULT: In this study, the tomato ortholog of Arabidopsis CONSTANS, SlCOL1, was shown to play key roles in the control of flower development and fruit yield. Suppression of SlCOL1 expression in tomato was found to lead to promotion of flower and fruit development, resulting in increased tomato fruit yield. On the contrary, overexpression of SlCOL1 disturbed flower and fruit development, and significantly reduced tomato fruit yield. Genetic and biochemical evidence indicated that SlCOL1 controls inflorescence development by directly binding to the promoter region of tomato inflorescence-associated gene SINGLE-FLOWER TRUSS (SFT) and negatively regulating its expression. Additionally, we found that SlCOL1 can also negatively regulate fruit size in tomato. CONCLUSIONS: Tomato SlCOL1 binds to the promoter of the SFT gene, down-regulates its expression, and plays a key role in reducing the fruit size.

A Fresh Perspective on Examining Population Emotional Well-Being Trends by Internet Search Engine: An Emerging Composite Anxiety and Depression Index.

Traditional assessments of anxiety and depression face challenges and difficulties when it comes to understanding trends in-group psychological characteristics. As people become more accustomed to expressing their opinions online, location-based online media and cutting-edge algorithms offer new opportunities to identify associations between group sentiment and economic- or healthcare-related variables. Our research provides a novel approach to analyzing emotional well-being trends in a population by focusing on retrieving online information. We used emotionally enriched texts on social media to build the Public Opinion Dictionary (POD). Then, combining POD with the word vector model and search trend, we developed the Composite Anxiety and Depression Index (CADI), which can reflect the mental health level of a region during a specific time period. We utilized the representative external data by CHARLS to validate the effectiveness of CADI, indicating that CADI can serve as a representative indicator of the prevalence of mental disorders. Regression and subgroup analysis are employed to further elucidate the association between public mental health (measured by CADI) with economic development and medical burden. The results of comprehensive regression analysis show that the Import-Export index (-16.272, p < 0.001) and average cost of patients (4.412, p < 0.001) were significantly negatively associated with the CADI, and the sub-models stratificated by GDP showed the same situation. Disposable income (-28.389, p < 0.001) became significant in the subgroup with lower GDP, while the rate of unemployment (2.399, p < 0.001) became significant in the higher subgroup. Our findings suggest that an unfavorable economic development or unbearable medical burden will increase the negative mental health of the public, which was consistent across both the full and subgroup models.

Effects of accelerated biological age on depressive symptoms in a causal reasoning framework.

BACKGROUND: Depression in middle-aged and elderly individuals is multifaceted and heterogeneous, linked to biological age (BA) based on aging-related biomarkers. However, due to confounding with chronological age and the absence of subgroup analysis and causal reasoning, the association between BA and depressive symptoms (DS) might be unstable and requires further investigation. METHODS: We utilized data from the China Health and Retirement Longitudinal Study (N = 9478) to perform association analysis, causal inference, and subgroup analysis. BA acceleration (BAA) was derived using machine learning and adjusted for chronological age. A generalized linear mixed-effects model (GLMM) tree algorithm was employed to identify subgroups. The causal reasoning frame included propensity score matching and fast large-scale almost matching exactly. RESULTS: In the longitudinal analysis, BAA exhibited a consistent and significant positive association with DS, even after controlling for demographic characteristics, lifestyle factors, health status, and physical functions. This association remained unchanged within the causal framework. GLMM tree analysis identified three partitioning variables (sex, satisfaction, and BMI) and five subgroups. Further subgroup analysis revealed that BAA exerted the strongest effect on DS among women with less satisfying lives. LIMITATIONS: Depressive symptoms were evaluated through scale measurements rather than clinical diagnosis. The sample was derived from the general population, not the clinically depressed population. CONCLUSIONS: This study provided the first longitudinal evidence that biological age acceleration increases depressive symptoms under causal reasoning and subgroup analysis, particularly among less satisfied women. And the association between BAA and DS was independent of known risk factors.

Peripheral and cerebral inflammation induced by repeated anesthesia and surgery do not cause impairment of learning and memory in middle­aged mice.

Postoperative cognitive dysfunction is a postoperative complication of the central nervous system that reduces quality of life and increases mortality in perioperative patients, especially among elderly patients. Many studies have shown that the incidence of postoperative cognitive impairment in adults induced by one­time anesthesia and surgery is very low, while multiple experiences of anesthesia and surgery can induce cognitive impairment in the developing brain. However, the effect of multiple experiences of anesthesia and surgery on cognitive function over a short period in middle­aged mice, i.e., 6 to 8 months old, remains unclear. In this study, we explored whether the cognitive function of mice aged 6-8 months is impaired after multiple operations. Middle­aged mice (6 to 8 months old) healthy male C57BL/6 mice underwent exploratory laparotomy under isoflurane anesthesia. Morris water maze testing was performed after the operations. Blood and brain samples were collected at 6 h, 24 h, and 48 h after the operations. Serum IL­6, IL­1, and S­100ß concentrations were detected by ELISA. The expressions of ChAT, AChE, and Aß in the hippocampus were measured by western blot. Up­regulation of Iba1 and GFAP, respectively, indicated activation of microglia and astrocytes in the hippocampus. Expression of Iba1 and GFAP was examined by immunofluorescence. The present results revealed that serum IL­6, IL­1ß, and S­100ß concentrations were enhanced after multiple instances of anesthesia and surgery, and microglia and astrocytes in the hippocampus were activated. However, learning and memory were not impaired in the middle­aged mice by multiple experiences of anesthesia and surgery. There were no changes in ChAT, AChE, and Aß in the hippocampus after multiple experiences of anesthesia/surgery. Taken together, we suggest that although multiple anesthesia/surgery procedures can induce peripheral inflammation, neuroinflammation, and transient cerebral injury, it is insufficient to impair learning and memory in middle­aged mice.

Reconstructing hepatic metabolic profile and glutathione-mediated metabolic fate of acrylamide.

The toxicity of acrylamide (AA) has continuously attracted wide concerns as its extensive presence from both environmental and dietary sources. However, its hepatic metabolic transformation and metabolic fate still remain unclear. This study aims to unravel the metabolic profile and glutathione (GSH) mediated metabolic fate of AA in liver of rats under the dose-dependent exposure. We found that exposure to AA dose-dependently alters the binding of AA and GSH and the generation of mercapturic acid adducts, while liver as a target tissue bears the metabolic transformation of AA via regulating GSH synthesis and consumption pathways, in which glutamine synthase (GSS), cytochrome P450 2E1 (CYP2E1), and glutathione S-transferase P1 (GSTP1) play a key role. In response to high- and low-dose exposures to AA, there were significant differences in liver of rats, including the changes in GSH and cysteine (CYS) activities and the conversion ratio of AA to glycidamide (GA), and liver can affect the transformation of AA by regulating the GSH-mediated metabolic pathway. Low-dose exposure to AA activates GSH synthesis pathway in liver and upregulates GSS activity and CYS content with no change in γ-glutamyl transpeptidase 1 (GGT1) activity. High-dose exposure to AA activates the detoxification pathway of GSH and increases GSH consumption by upregulating GSTP1 activity. In addition, molecular docking results showed that most of the metabolic molecules transformed by AA and GA other than themselves can closely bind to GSTP1, GSS, GGT1, N-acetyltransferase 8, and dimethyl sulfide dehydrogenase 1. The binding of AA-GSH and GA-GSH to GSTP1 and CYP2E1 enzymes determine the tendentiousness between toxicity and detoxification of AA, which exerts a prospective avenue for targeting protective role of hepatic enzymes against in vivo toxicity of AA.

The Role of Gut Microbiota-Gut-Brain Axis in Perioperative Neurocognitive Dysfunction.

With the aging of the world population and advances in medical and health technology, more and more elderly patients are undergoing anesthesia and surgery, and perioperative neurocognitive dysfunction (PND) is receiving increasing attention. The latest definition of PND, published simultaneously in November 2018 in 6 leading journals in the field of anesthesiology, clarifies that PND includes preoperatively cognitive impairment, postoperative delirium, delayed neurocognitive recovery, and postoperative cognitive dysfunction and meets the diagnostic criteria for neurocognitive impairment in the Diagnostic and Statistical Manual of Mental Disorders -fifth edition (DSM-5). The time frame for PND includes preoperatively and within 12 months postoperatively. Recent studies have shown that gut microbiota regulates central nervous function and behavior through the gut microbiota - gut - brain axis, but the role of the axis in the pathogenesis of PND remains unclear. Therefore, this article reviews the mechanism of the role of gut microbiota-gut-brain axis in PND, so as to help explore reasonable early treatment strategies.

Machine learning prediction of exposure to acrylamide based on modelling of association between dietary exposure and internal biomarkers.

The ubiquitous occurrence of acrylamide in various thermal processing food products poses a potential health risk for the public. An accurate exposure assessment is crucial to the risk evaluation of acrylamide. Machine learning emerging as a powerful computational tool for prediction was employed to establish the association between internal exposure and dietary exposure to acrylamide among a Chinese cohort of middle-aged and elderly population (n = 1,272). Five machine learning regression models were constructed and compared to predict the daily dietary acrylamide exposure based on urinary biomarkers including N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA), N-acetyl-S-(2-carbamoylethyl)-L-cysteine-sulfoxide (AAMA-sul), N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA), and N-acetyl-S-(1-carbamoyl-2-hydroxyethyl)-L-cysteine (iso-GAMA). Other important covariates such as age, gender, physical activities, and total energy intake were also considered as predictors in the models. Average dietary intake of acrylamide among Chinese elderly participants was 8.9 µg/day, while average urinary contents of AAMA, AAMA-sul, GAMA, and iso-GAMA were 52.2, 19.1, 4.4, and 1.7 nmol/g Ucr (urine creatinine), respectively. Support vector regression (SVR) model showed the best prediction performance with a R of 0.415, followed by light gradient boosting machine (LightGBM) model (R = 0.396), adjusted multiple linear regression (MLR) model (R = 0.378), neural networks (NN) model (R = 0.365), MLR model (R = 0.363), and extreme gradient boosting (XGBoost) model (R = 0.337). The present study firstly correlated dietary exposure with internal exposure to acrylamide among Chinese elderly population, providing an innovative perspective for the exposure assessment of acrylamide.

Atmospheric pressure plasma jet pretreatment to facilitate cassava starch modification with octenyl succinic anhydride.

Cassava starch (CS) was pretreated with atmospheric pressure plasma jet (APPJ), followed by esterification with octenyl succinic anhydride (OSA). This study was the first report investigating the effect of APPJ on CS modification with OSA. Results showed that APPJ pretreatment could change the morphological characteristics and crystallinity of CS. Consequently, the degree of substitution and reaction efficiency significantly improved compared with the unpretreated CS (P < 0.05). In Confocal laser scanning microscopy, the fluorescence intensity of OSA-modified CS pretreated with APPJ for 10 min and 15 min was higher than those pretreated with APPJ for 1, 3, and 5 min. The onset temperature and enthalpy (ΔH) of native starch decreased after APPJ pretreatment and further decreased by OSA modification. APPJ-OSA-CS also showed better emulsion stability and emulsion activity. This study demonstrated that APPJ could be used as a novel approach to facilitate starch modification with OSA.

Role of mTOR-Regulated Autophagy in Synaptic Plasticity Related Proteins Downregulation and the Reference Memory Deficits Induced by Anesthesia/Surgery in Aged Mice.

Postoperative cognitive dysfunction increases mortality and morbidity in perioperative patients and has become a major concern for patients and caregivers. Previous studies demonstrated that synaptic plasticity is closely related to cognitive function, anesthesia and surgery inhibit synaptic function. In central nervous system, autophagy is vital to synaptic plasticity, homeostasis of synapticproteins, synapse elimination, spine pruning, proper axon guidance, and when dysregulated, is associated with behavioral and memory functions disorders. The mammalian target of rapamycin (mTOR) negatively regulates the process of autophagy. This study aimed to explore whether rapamycin can ameliorate anesthesia/surgery-induced cognitive deficits by inhibiting mTOR, activating autophagy and rising synaptic plasticity-related proteins in the hippocampus. Aged C57BL/6J mice were used to establish POCD models with exploratory laparotomy under isoflurane anesthesia. The Morris Water Maze (MWM) was used to measure reference memory after anesthesia and surgery. The levels of mTOR phosphorylation (p-mTOR), Beclin-1 and LC3-II were examined on postoperative days 1, 3 and 7 by western blotting. The levels of synaptophysin (SYN) and postsynaptic density protein 95 (PSD-95) in the hippocampus were also examined by western blotting. Here we showed that anesthesia/surgery impaired reference memory and induced the activation of mTOR, decreased the expression of autophagy-related proteins such as Beclin-1 and LC3-II. A corresponding decline in the expression of neuronal/synaptic, plasticity-related proteins such as SYN and PSD-95 was also observed. Pretreating mice with rapamycin inhibited the activation of mTOR and restored autophagy function, also increased the expression of SYN and PSD-95. Furthermore, anesthesia/surgery-induced learning and memory deficits were also reversed by rapamycin pretreatment. In conclusion, anesthesia/surgery induced mTOR hyperactivation and autophagy impairments, and then reduced the levels of SYN and PSD-95 in the hippocampus. An mTOR inhibitor, rapamycin, ameliorated anesthesia/surgery-related cognitive impairments by inhibiting the mTOR activity, inducing activation of autophagy, enhancing SYN and PSD-95 expression.