Paeonia genus: a systematic review of active ingredients, pharmacological effects and mechanisms, and clinical applications for the treatment of cancer.

The main active constituents of plants of the Paeonia genus are known to have antitumor activity. Hundreds of compounds with a wide range of pharmacological activities, including monoterpene glycosides, flavonoids, tannins, stilbenes, triterpenoids, steroids, and phenolic compounds have been isolated. Among them, monoterpenes and their glycosides, flavonoids, phenolic acids, and other constituents have been shown to have good therapeutic effects on various cancers, with the main mechanisms including the induction of apoptosis; the inhibition of tumor cell proliferation, migration, and invasion; and the modulation of immunity. In this study, many citations related to the traditional uses, phytochemical constituents, antitumor effects, and clinical applications of the Paeonia genus were retrieved from popular and widely used databases such as Web of Science, Science Direct, Google Scholar, and PubMed using different search strings. A systematic review of the antitumor constituents of the Paeonia genus and their therapeutic effects on various cancers was conducted and the mechanisms of action and pathways of these phytochemicals were summarised to provide a further basis for antitumor research.

Site effects in multisite fetal brain MRI: morphological insights into early brain development.

OBJECTIVE: To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects. MATERIALS AND METHODS: Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch's test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases. RESULTS: The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7-40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns. CONCLUSION: Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations. KEY POINTS: Question How do specific site MRI acquisition factors affect fetal brain imaging? Finding Lower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution. Clinical relevance This study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies.

Nuclear Factor Erythroid 2-Related Factor 1 Regulates the Expression of Proteasomal Genes in Ketotic Cows and Protects Mammary Cells Against Free Fatty Acid-Induced Endoplasmic Reticulum Stress.

Ketosis is a common metabolic disorder in high-yielding cows and is characterized by high concentrations of BHB and free fatty acids (FFA). High concentrations of FFA induce endoplasmic reticulum (ER) stress in multiple organs including mammary tissue, and result in reduced milk production and lower milk quality. In non-ruminants, loss of nuclear factor erythroid 2-related factor 1 (NFE2L1) results in ER stress. The physiological functions and molecular mechanisms controlled by NFE2L1 in bovine mammary tissue are poorly understood. Thus, the present study aimed to elucidate the role of the NFE2L1 on proteasomal homeostasis and ER stress in mammary tissue from early-lactation (DIM 6 to 14) healthy cows (CON, blood concentration of BHB <1.2 mM, n = 10) and cows with clinical ketosis (CK blood concentration of BHB >3 mM, n = 10). Compared with CON, serum concentration of glucose was lower due to CK, while serum concentrations of BHB and FFA were greater. Protein and mRNA abundance of NFE2L1 along with abundance of proteasomal subunits (PSMD1, PSMD14, PSMA1, PSMB1, and PSMB5 genes and PSMB4 and PSMB6 proteins) were lower in cows with CK, indicating that expression of NFE2L1 and proteasomal homeostasis was impaired by ketosis. In vitro, primary bovine mammary epithelial cells were exposed to various concentrations of FFA (0, 0.3, 0.6, or 1.2 mM). Compared with the 0 mM FFA, the ratio of phosphorylated (p)-protein kinase R-like ER kinase (PERK)/PERK along with the expression of inositol-requiring enzyme 1 (IRE1) α, activating transcription factor 6 (ATF6), glucose regulated protein 78 (GRP78), and C/EBP homologous protein (CHOP) was higher with 1.2 mM FFA. A similar response was observed for ER stress-associated genes (CHOP, GRP78, and XBP1) indicating that high concentrations of FFA induced ER stress. In line with in vivo results, 1.2 mM FFA downregulated the protein and mRNA abundance of NFE2L1, the abundance of PSMB6 protein, and PSM genes (PSMC1, PSMC3, and PSMD1), and increased the accumulation of ubiquitin. This suggested a marked negative effect of high FFA on NFE2L1 and proteasomal homeostasis. Silencing of NFE2L1 triggered upregulation of ER stress-associated genes as well as protein abundance of GRP78 and CHOP. Further, compared with CON-siRNA, the abundance of PSM genes was downregulated in the NFE2L1-siRNA group. In contrast, abundance of markers of ER stress and PSM genes and proteins indicated that overexpression of NFE2L1 relieved the FFA-induced ER stress and improved 26S proteasome homeostasis. Our data suggested that the mammary gland experiences ER stress during ketosis partly due to disruption of proteasomal homeostasis from the excess FFA. As such, NFE2L1 could represent a target for potential therapeutic applications in the field to alleviate the accumulation of malformed proteins that may impair the long-term lactogenic capacity of the udder.

Association of metabolic syndrome and frailty with postoperative complications in older gastric cancer patients: A body composition perspective.

OBJECTIVES: To compare the characteristics of body compositions between metabolic syndrome (MetS) and frailty, and determine the independent and overlapping of MetS and frailty with postoperative complications among older patients with gastric cancer. DESIGN: A prospectively observational study. SETTING AND PARTICIPANTS: Two hundred and eighty six older patients from 60 to 80 years undergoing radical gastrectomy for the first time. MEASUREMENTS: MetS was diagnosed by the criteria from the 2020 edition of Chinese guideline for the prevention and treatment of type 2 diabetes mellitus, and frailty was defined by frailty phenotype. An InBody770 impedance analyzer was used to measure body compositions and with 10 fat- and muscle-related indicators being included in this study. Based on the presence of frailty and MetS, patients were divided into the frailty group, MetS group, frailty+MetS group, and normal group, and the body compositions indicators of these groups were compared. Clavien-Dindo classification was used to grade the severity of postoperative complications. Univariate and multivariate regression models were performed to explore the independent and joint association of MetS and frailty with postoperative complications. RESULTS: The incidence rate of MetS, frailty, and frailty+MetS being 20.3%, 15.7%, and 4.2% respectively. Compared with the normal group, both fat and muscle compositions were decreased significantly in the frailty group (p < 0.05), while the statistically significant difference of fat-to-muscle mass ratio (FMR) and skeletal muscle mass to visceral fat area ratio (SVR) were not observed (p > 0.05). In contrast, except SVR, the other indicators of the MetS group were higher than the normal group (p < 0.05). As to the frailty+MetS group, there was a significant increase in fat compositions and FMR, as well as a significant decline in SVR (p < 0.05), while the difference of muscle compositions was not statistically significant (p > 0.05). There was an association of frailty with postoperative total (OR = 3.068, 95% CI: 1.402-6.713) and severe (OR = 9.423, 95% CI: 2.725-32.589) complications, but no association was found of MetS alone. MetS coexisting with frailty was associated with the highest risk of both total (OR = 3.852, 95% CI: 1.020-14.539) and severe (OR = 12.096, 95% CI: 2.183-67.024) complications. CONCLUSIONS: Both frailty and MetS coexisting with frailty had adverse effects on postoperative complications, which appeared greatly different characteristics in body compositions and therefore reinforced the importance of targeted nutritional or metabolic intervention. Although MetS alone were not significantly associated with postoperative complications, it is essential to focus on the causal relationship and development trend between MetS and frailty to prevent MetS from shifting into frailty, considering the highest risk in their coexistence state.

Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes.

Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

Research of multi-label text classification based on label attention and correlation networks.

Multi-Label Text Classification (MLTC) is a crucial task in natural language processing. Compared to single-label text classification, MLTC is more challenging due to its vast collection of labels which include extracting local semantic information, learning label correlations, and solving label data imbalance problems. This paper proposes a model of Label Attention and Correlation Networks (LACN) to address the challenges of classifying multi-label text and enhance classification performance. The proposed model employs the label attention mechanism for a more discriminative text representation and uses the correlation network based on label distribution to enhance the classification results. Also, a weight factor based on the number of samples and a modulation function based on prediction probability are combined to alleviate the label data imbalance effectively. Extensive experiments are conducted on the widely-used conventional datasets AAPD and RCV1-v2, and extreme datasets EUR-LEX and AmazonCat-13K. The results indicate that the proposed model can be used to deal with extreme multi-label data and achieve optimal or suboptimal results versus state-of-the-art methods. For the AAPD dataset, compared with the suboptimal method, it outperforms the second-best method by 2.05% ∼ 5.07% in precision@k and by 2.10% ∼ 3.24% in NDCG@k for k = 1, 3, 5. The superior outcomes demonstrate the effectiveness of LACN and its competitiveness in dealing with MLTC tasks.

Integrated network pharmacology and metabolomics to study the potential mechanism of Jiawei Yinchenhao decoction in chronic hepatitis B.

Chronic hepatitis B infection (CHB) is a major risk factor for the development of hepatocellular carcinoma (HCC) globally and continues to pose a significant global health challenge. Jiawei Yinchenhao decoction (JWYCH) is a modified version of Yinchenhao decoction (YCHD), which is widely used to treat liver diseases including icteric hepatitis, cholelithiasis, and hepatic ascites. However, the effectiveness and underlying mechanism of JWYCH on CHB are still unclear. This study aimed to investigate the impact of JWYCH on CHB and explore the underlying mechanism via network pharmacology and metabolomics. C57BL/6 mice were administered rAAV-HBV1.3 via hydrodynamic injection (HDI) to establish the CHB model. The infected mice were orally administered JWYCH for 4 weeks. HBsAg, HBeAg, HBV DNA, the serum liver function index, and histopathology were detected. In addition, network pharmacology was used to investigate potential targets, whereas untargeted metabolomics analysis was employed to explore the hepatic metabolic changes in JWYCH in CHB mice and identify relevant biomarkers and metabolic pathways. JWYCH was able to reduce HBeAg levels and improve liver pathological changes in mice with CHB. Additionally, metabolomics analysis indicated that JWYCH can influence 105 metabolites, including pipecolic acid, alpha-terpinene, adenosine, and L-phenylalanine, among others. Bile acid metabolism, arachidonic acid metabolism, and retinol metabolism are suggested to be potential targets of JWYCH in CHB. In conclusion, JWYCH demonstrated a hepatoprotective effect on a mouse model of CHB, suggesting a potential alternative therapeutic strategy for CHB. The effect of JWYCH is associated mainly with regulating the metabolism of bile acid, arachidonic acid, and retinol. These differentially abundant metabolites may serve as potential biomarkers and therapeutic targets for CHB.

Changes in Skeletal Muscle Mass in the First 3 Months Following Gastrointestinal Cancer Surgery: A Prospective Study.

BACKGROUND: Surgical resection is the primary treatment for gastrointestinal (GI) cancers, but postoperative skeletal muscle loss (SML) is common and linked to poor prognosis. This study aims to identify patterns of muscle change, examine its association with quality of life (QoL), and explore predictors of SML in the first 3 months. PATIENTS AND METHODS: A prospective cohort study was conducted on patients newly diagnosed with GI cancer and undergoing surgery in China between September 2021 and May 2022. Skeletal muscle mass (SMM) and QoL were assessed at admission, 7 days, 1 month, and 3 months post-surgery. Demographic, clinical data, and biomarkers were collected. Missing data were imputed using multiple imputation. Data were analyzed using growth mixture modelling, bivariate analyses, and logistic regression. RESULTS: A total of 483 patients completed baseline assessment. Of the 242 patients with complete muscle assessments, 92% experienced SML. Three distinct patterns of muscle change were identified: 57% had normal preoperative SMM with mild postoperative SML, 16% had low preoperative SMM with moderate SML, and 27% had normal preoperative mass but severe postoperative SML. Moderate/severe SML was associated with more postoperative complications, poorer health, and higher symptom burden. Independent predictors included advanced age, preoperative sarcopenia, advanced cancer stage, and low prognostic nutrition index (PNI ≤ 45). The results did not change when using imputed values. CONCLUSIONS: Although SML is prevalent, patterns of muscle change are heterogeneous among patients. Advanced age, preoperative sarcopenia, advanced cancer stage, and cancer-related inflammation are predictors for moderate/severe SML, highlighting the need for early detection and management.

A motion assessment method for reference stack selection in fetal brain MRI reconstruction based on tensor rank approximation.

Slice-to-volume registration and super-resolution reconstruction are commonly used to generate 3D volumes of the fetal brain from 2D stacks of slices acquired in multiple orientations. A critical initial step in this pipeline is to select one stack with the minimum motion among all input stacks as a reference for registration. An accurate and unbiased motion assessment (MA) is thus crucial for successful selection. Here, we presented an MA method that determines the minimum motion stack based on 3D low-rank approximation using CANDECOMP/PARAFAC (CP) decomposition. Compared to the current 2D singular value decomposition (SVD) based method that requires flattening stacks into matrices to obtain ranks, in which the spatial information is lost, the CP-based method can factorize 3D stack into low-rank and sparse components in a computationally efficient manner. The difference between the original stack and its low-rank approximation was proposed as the motion indicator. Experiments on linearly and randomly simulated motion illustrated that CP demonstrated higher sensitivity in detecting small motion with a lower baseline bias, and achieved a higher assessment accuracy of 95.45% in identifying the minimum motion stack, compared to the SVD-based method with 58.18%. CP also showed superior motion assessment capabilities in real-data evaluations. Additionally, combining CP with the existing SRR-SVR pipeline significantly improved 3D volume reconstruction. The results indicated that our proposed CP showed superior performance compared to SVD-based methods with higher sensitivity to motion, assessment accuracy, and lower baseline bias, and can be used as a prior step to improve fetal brain reconstruction.

Explainable machine learning framework to predict the risk of work-related neck and shoulder musculoskeletal disorders among healthcare professionals.

Objective: This study aims to develop risk prediction models for neck and shoulder musculoskeletal disorders among healthcare professionals. Methods: A stratified sampling method was employed to select employees from medical institutions in Nanning City, yielding 617 samples. The Boruta algorithm was used for feature selection, and various models, including Tree-Based Models, Single Hidden-Layer Neural Network Models (MLP), Elastic Net Models (ENet), and Support Vector Machines (SVM), were applied to predict the selected variables, utilizing SHAP algorithms for individual-level local explanations. Results: The SVM model excels in both Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) and exhibits more stable performance when generalizing to unseen data. The Random Forest model exhibited relatively high overall performance on the training set. The MLP model emerges as the most consistent and accurate in predicting shoulder musculoskeletal disorders, while the SVM model shows strong fitting capabilities during the training phase, with occupational factors identified as the main contributors to WMSDs. Conclusion: This study successfully constructs work-related musculoskeletal disorder risk prediction models for healthcare professionals, enabling a quantitative analysis of the impact of occupational factors. This advancement is beneficial for future economical and convenient work-related musculoskeletal disorder screening in healthcare professions.

Diabetes Distress and Associated Factors Among Chinese Americans with Type 2 Diabetes in New York City.

Purpose: The purpose of this study is to describe diabetes distress and related factors among Chinese Americans with type 2 diabetes in New York City (NYC). Methods: We conducted a secondary data analysis of the baseline data from three research studies conducted among community-dwelling Chinese American adults with type 2 diabetes. Diabetes Distress Scale (DDS) was used to measure sources of diabetes distress including emotional-, regimen-, interpersonal-, and physician-related distress. A score of 2 or greater indicates moderate diabetes distress or higher. Patient Health Questionnaire-2 (PHQ-2) was used to measure depressive symptoms. Participants' sociodemographic information was also collected. Descriptive statistics were used to describe diabetes distress, and logistic least absolute shrinkage and selection operator (LASSO) regression was used to examine factors associated with diabetes distress level. Results: Data from 178 participants (mean age 63.55±13.56 years) were analyzed. Most participants were married (76.40%), had a high school degree or less (65.73%), had a household annual income < $25,000 (70.25%), and reported limited English proficiency (93.22%). About 25.84% reported moderate or higher overall distress. The most common sources of distress were emotional burden (29.78%), followed by regimen- (28.65%), interpersonal- (18.54%), and physician-related distress (14.04%). Participants who were younger, female, limited English proficient, and had elevated depressive symptoms were more likely to have higher diabetes distress. Conclusion: Diabetes distress is prevalent among Chinese immigrants with type 2 diabetes, especially emotional- and regimen-related distress. Given the known link between diabetes distress and poor glycemic control, it is critical to screen for diabetes distress at primary care clinics and incorporate psychological counseling in diabetes care in this underserved population.

Tumor oxygenation nanoliposomes promote deep photodynamic therapy for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer and has many characteristics including high metastatic rates, poor overall survival, and low response to traditional chemotherapy. Photodynamic therapy (PDT), emerging as a precise treatment modality, has shown promise in improving the antitumor response. However, it still faces challenges such as limited light penetration depth, rapid oxygen consumption, and inadequate targeting ability. In this study, we developed Rose Bengal (RB, photosensitizer) and oxygen co-loaded CREKA-modified UCNP-based nanoliposomes (CLIP-RB-PFOB@UCNP) for tumor targeting and near-infrared (NIR)-triggered deep and long-lasting PDT. Our results demonstrated that CLIP-RB-PFOB@UCNP effectively targeted and accumulated in tumor tissue through the interaction between CREKA and fibronectin, which is overexpressed in tumor cells. Under NIR irradiation, CLIP-RB-PFOB@UCNP exhibited significant destruction of orthotopic tumors, reduced the level of HIF-1α, and efficiently suppressed lung metastasis in a metastatic TNBC model. In conclusion, this study offers new avenues for improving the therapeutic outcomes of PDT for clinical TNBC treatment.

Influences of Social Disengagement and Depressive Symptoms on Sleep Disturbance in Dementia Caregiving Dyads: A Nationally Representative Study.

OBJECTIVES: To examine the influence of social disengagement and depressive symptoms on sleep disturbance among dementia caregiving dyads and the actor-partner interdependence nature of these influences. DESIGN: Actor-partner interdependence model through structural equation modeling for dyadic analyses. SETTING AND PARTICIPANTS: A total of 310 dyads of older adults with dementia and their care partners from 2 national representative studies in the United States, the National Health and Aging Trends Study (NHATS) and its companion study, the National Study of Caregiving (NSOC). METHODS: Data from the NHATS Round 11 and NSOC IV were analyzed using descriptive statistics, Pearson correlation analysis, and the actor-partner interdependence model. Structural equation modeling was used to assess the mediation effects of depressive symptoms within the actor-partner interdependence models. RESULTS: In the model of caregivers, social disengagement had a direct impact on sleep disturbance (ß = 0.49, P < .001) and an indirect impact through depressive symptoms (ß = 0.25, P < .001). In the model of older adults with dementia, social disengagement only had an indirect effect on sleep disturbance through depressive symptoms. In models examining partner effects, caregivers' social disengagement directly influenced their care partners' depressive symptoms (ß = 0.20, P = .019), which subsequently affected caregivers' sleep disturbance (ß = 0.17, P < .001). Social disengagement (ß = 0.17, P = .001) and depressive symptoms (ß = 0.17, P < .001) in older adults with dementia directly impacted their caregivers' sleep disturbance. Depressive symptoms of older adults with dementia served as multiple mediators linking one member's social disengagement to both their own and partner's sleep. CONCLUSIONS AND IMPLICATIONS: This study represents one of the first attempts to investigate the influencing mechanism of sleep disturbances among older adults with dementia and their informal caregivers through a dyadic perspective. The sleep disturbance of caregivers may be directly influenced by the social disengagement and depressive symptoms exhibited by both members of the dyad, whereas the sleep disturbance experienced by older adults with dementia can only be indirectly influenced by the dyad's social disengagement via their own depressive symptoms. Dyadic social activities targeting depressive symptoms could be designed to address sleep disturbances in dementia caregiving dyads.

SMYD5 is a ribosomal methyltransferase that catalyzes RPL40 lysine methylation to enhance translation output and promote hepatocellular carcinoma.

While lysine methylation is well-known for regulating gene expression transcriptionally, its implications in translation have been largely uncharted. Trimethylation at lysine 22 (K22me3) on RPL40, a core ribosomal protein located in the GTPase activation center, was first reported 27 years ago. Yet, its methyltransferase and role in translation remain unexplored. Here, we report that SMYD5 has robust in vitro activity toward RPL40 K22 and primarily catalyzes RPL40 K22me3 in cells. The loss of SMYD5 and RPL40 K22me3 leads to reduced translation output and disturbed elongation as evidenced by increased ribosome collisions. SMYD5 and RPL40 K22me3 are upregulated in hepatocellular carcinoma (HCC) and negatively correlated with patient prognosis. Depleting SMYD5 renders HCC cells hypersensitive to mTOR inhibition in both 2D and 3D cultures. Additionally, the loss of SMYD5 markedly inhibits HCC development and growth in both genetically engineered mouse and patient-derived xenograft (PDX) models, with the inhibitory effect in the PDX model further enhanced by concurrent mTOR suppression. Our findings reveal a novel role of the SMYD5 and RPL40 K22me3 axis in translation elongation and highlight the therapeutic potential of targeting SMYD5 in HCC, particularly with concurrent mTOR inhibition. This work also conceptually broadens the understanding of lysine methylation, extending its significance from transcriptional regulation to translational control.

Effects of multicomponent exercise on cognitive function in persons with mild cognitive impairment: A systematic review and meta-analysis.

BACKGROUND: Multicomponent exercise has the potential to improve cognitive function in people with mild cognitive impairment. However, the effects of multicomponent exercise on specific cognitive subdomains in mild cognitive impairment and the optimal combination of exercise components remain unclear. OBJECTIVE: This systematic review aimed to (a) investigate the effects of multicomponent exercise on different cognitive subdomains in people with mild cognitive impairment and (b) investigate the effects of different combinations of multicomponent exercise on global cognition in people with mild cognitive impairment. DESIGN: A systematic review and meta-analysis. METHODS: Six electronic databases, including PubMed, Medline, EMBASE, Web of Science, Cochrane Library, and CINAHL were systematically searched from inception to January 1st, 2023. Randomized controlled trials assessing the effect of multicomponent exercise interventions on cognitive function in people with mild cognitive impairment were included. The risk of bias was assessed using the Cochrane collaborative bias assessment tool. A random-effects model was used to calculate standardized mean difference. Subgroup analyses, meta-regression, and sensitive analysis were performed. If a meta-analysis was not feasible, studies were synthesized narratively. RESULTS: Twenty studies were identified for systematic review and meta-analysis. Multicomponent exercise significantly improved global cognition [SMD = 1.04; 95 % confidence interval (CI): 0.53, 1.55], cognitive flexibility (SMD = -1.04; 95 % CI: -1.81, -0.27), processing speed (SMD = 0.43; 95 % CI: 0.04, 0.82), verbal fluency (SMD = 0.38; 95 % CI: 0.13, 0.63), attention (SMD = -0.90; 95 % CI: -1.68, -0.12) and memory (SMD = 0.36; 95 % CI: 0.04, 0.69) in mild cognitive impairment. The multicomponent exercise including cardiovascular (exercise that promotes cardiovascular health, such as endurance training or aerobic exercise) and motor (exercises that improve physical abilities, such as balance, coordination, agility, flexibility, etc.) components positively affected global cognition in people with mild cognitive impairment (SMD = 1.06; 95 % CI: 0.55, 1.57). CONCLUSIONS: The findings of this study suggest that multicomponent exercise has a positive impact on various cognitive domains, including global cognition, cognitive flexibility, processing speed, verbal fluency, attention and memory in mild cognitive impairment. Specifically, the combination of exercises including cardiovascular and motor components was found to be effective in improving global cognition. However, further research is needed to investigate the optimal frequency and intensity of the multicomponent exercise intervention, and more detail about exercise combinations of the motor component (not classified in this study) for individuals with mild cognitive impairment. REGISTRATION: The protocol was registered on PROSPERO (CRD42023400302).

Towards an optimized model of food allergy in zebrafish.

BACKGROUND: The prevalence of food allergies is on the rise, posing a significant challenge to public health. Rodents serve as the predominant animal model in food allergy research; yet, the application of rodent models proves to be a laborious and time-consuming endeavor. It is imperative to develop novel in vivo models. METHODS: Ovalbumin (OVA) was administered as the allergen, following the recommended dosage used in other species. During the sensitization phase, a dosage of 0.25 mg per 10 tails per 1 L was administered twice daily, and during the challenge phase, the dosage was increased to 3 times the initial level. The study explored two dimensions of sensitization: the mode of exposure, which can be either continuous or intermittent, and the duration of exposure, which includes 3 days, 5 days, and 7 days. We examined midgut pathological changes, immunoglobulins contents, and mRNA expressions associated to T helper cells (Th) 2 cytokines following exposure. RESULTS: A significant 109.3 % increase in the number of eosinophils was observed in the midgut histopathology following intermittent 5-day OVA exposure, which emerged as the most effective model. OVA exposure increased concentrations of immunoglobulin M (IgM) (105.2 %), IgZ (312.1 %), and IgD (304.3 %) in this model. The mRNA expressions of Th2-related interleukin (IL)-4 and IL-13 were also elevated by 132.8 % and 421.0 %, respectively. CONCLUSION: The intermittent 5-day OVA exposure was suggested to be the best constructed zebrafish food allergy model, which may be a potential tool for research into food allergies.

Hybrid hair follicle stem cell extracellular vesicles co-delivering finasteride and gold nanoparticles for androgenetic alopecia treatment.

Androgenetic alopecia (AGA) is a non-fatal disease prevalent worldwide. However, mixed efficacy has been observed among different therapies for hair regrowth in AGA patients. Thus, a nano-platform with synergistic treatments based on a hybrid extracellular vesicle encapsulating gold nanoparticles (AuNPs) and finasteride (Hybrid/Au@Fi) was constructed through membrane fusion between hair follicle stem cell (HFSC)-derived extracellular vesicles and liposomes. These hybrid vesicles (HVs) not only fuel hair regrowth by providing cellular signals in extracellular vesicles, but also improve storage stability, follicle retention, and drug encapsulation efficiency (EE%) for finasteride inhibiting 5α-reductase, and nano-size AuNPs that simulate low-level laser therapy (LLLT) with similar photothermal effects in vitro. The EE% of finasteride in these HVs reached 45.33%. The dual administration of these extracellular vesicles and finasteride showed a strong synergistic effect on HFSCs in vitro. In an AGA mouse model, once-daily topical Hybrid/Au@Fi (115.07 ± 0.32 nm, -7.50 ± 1.68 mV) gel led to a faster transition of hair follicles (HFs) from the catagen to the anagen, increased hair regrowth coverage, and higher quality of regrowth hair, compared to once-daily 5% minoxidil treatment. Compared to topical minoxidil, the multifaceted synergistic therapy of Hybrid/Au@Fi through topical administration offers a new option for intractable AGA patients with low side effects.

Blocking ACSL6 Compromises Autophagy via FLI1-Mediated Downregulation of COLs to Radiosensitize Lung Cancer.

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide. Radiotherapy is the main component of LC treatment; however, its efficacy is often limited by radioresistance development, resulting in unsatisfactory clinical outcomes. Here, we found that LC radiosensitivity is up-regulated by decreased expression of long-chain acyl-CoA synthase 6 (ACSL6) after irradiation. Deletion of ACSL6 results in significant elevation of Friend leukemia integration 1 transcription factor (FLI1) and a marked decline of collagens (COLs). Blocking of ACSL6 impairs the tumor growth and upregulates FLI1, which reduces the levels of COLs and compromises irradiation-induced autophagy, leading to considerable therapeutic benefits during radiotherapy. Moreover, the direct interaction between ACSL6 and FLI1 and engagement between FLI1 and COLs indicates the involvement of the ACSL6-FLI1-COL axis. Finally, the potently adjusted autophagy flux reduces its otherwise contributive capability in surviving irradiation stress and leads to satisfactory radiosensitization for LC radiotherapy. These results demonstrate that enhanced ACSL6 expression promotes the aggressive performance of irradiated LC through increased FLI1-COL-mediated autophagy flux. Thus, the ACSL6-FLI1-Col-autophagy axis may be targeted to enhance the radiosensitivity of LC and improve the management of LC in radiotherapy.

Metabolic reprogramming in hepatocellular carcinoma: a bibliometric and visualized study from 2011 to 2023.

Background and aims: Metabolic reprogramming has been found to be a typical feature of tumors. Hepatocellular carcinoma (HCC), a cancer with high morbidity and mortality, has been extensively studied for its metabolic reprogramming-related mechanisms. Our study aims to identify the hotspots and frontiers of metabolic reprogramming research in HCC and to provide guidance for future scientific research and decision-making in HCC metabolism. Methods: Relevant studies on the metabolic reprogramming of HCC were derived from the Web of Science Core Collection (WoSCC) database up until November 2023. The bibliometrix tools in R were used for scientometric analysis and visualization. Results: From 2011 to 2023, a total of 575 publications were obtained from WoSCC that met the established criteria. These publications involved 3,904 researchers and 948 organizations in 37 countries, with an average annual growth rate of 39.11% in research. These studies were published in 233 journals, with Cancers (n = 29) ranking first, followed by Frontiers in Oncology (n = 20) and International Journal of Molecular Sciences (n = 19). The top ten journals accounted for 26% of the 575 studies. The most prolific authors were Wang J (n = 14), Li Y (n = 12), and Liu J (n = 12). The country with the most publications is China, followed by the United States, Italy, and France. Fudan University had the largest percentage of research results with 15.48% (n = 89). Ally A's paper in Cell has the most citations. A total of 1,204 keywords were analyzed, with the trend themes such as "glycolysis," "tumor microenvironment," "Warburg effect," "mitochondria," "hypoxia ," etc. Co-occurrence network and cluster analysis revealed the relationships between keywords, authors, publications, and journals. Moreover, the close collaboration between countries in this field was elucidated. Conclusion: This bibliometric and visual analysis delves into studies related to metabolic reprogramming in HCC between 2012 and 2023, elucidating the characteristics of research in this field, which has gradually moved away from single glycolipid metabolism studies to the integration of overall metabolism in the body, pointing out the trend of research topics, and the dynamics of the interaction between the tumor microenvironment and metabolic reprogramming will be the future direction of research, which provides blueprints and inspirations for HCC prevention and treatment programs to the researchers in this field.Systematic Review Registration: [https://www.bibliometrix.org].

Up-Conversion Luminescence and Optical Temperature Sensing Properties of NaLuF4:Yb3+/Ho3+ Micron-Sized Crystals at Low Temperature.

Non-contact temperature sensors utilising the fluorescence intensity ratio and the unique up-conversion (UC) luminescence of rare-earth ions have numerous benefits; however, their operational temperature range has remained limited. In this study, NaLuF4:Yb3+/Ho3+ samples were prepared by the hydrothermal method. The samples exhibited exceptional UC luminescence properties at low temperatures. The intensity of the green emission (with peak wavelengths of 540 and 546 nm) gradually decreased with increasing temperature, and the green emissions showed a unique change at low temperatures. In addition, we studied the dependence of the UC luminescence intensity on the excitation power and the variation in the decay lifetime with temperature. The experiments revealed excellent luminous performance and significantly enhanced sensitivity at low temperatures; the maximum absolute sensitivity Sa and relative sensitivity Sr of the 540 and 546 nm thermally coupled energy levels were 1.02% and 0.55% K-1, respectively. The potential temperature sensing properties of Yb3+/Ho3+-co-doped NaLuF4 makes it suitable for temperature sensing applications at temperatures as low as 30 K. This study offers a novel approach for the advancement of temperature sensing technology at low temperatures.