Search

The main characteristics of Parkinson’s disease (PD) are the loss of dopaminergic (DA) neurons and abnormal aggregation of cytosolic proteins. However, the exact pathogenesis of PD remains unclear, with ferroptosis emerging as one of the key factors driven by iron accumulation and lipid peroxidation. Glial cells, including microglia, astrocytes, and oligodendrocytes, serve as supportive cells in the central nervous system (CNS), but their abnormal activation can lead to DA neuron death and ferroptosis. This paper explores the interactions between glial cells and DA neurons, reviews the changes in glial cells during the pathological process of PD, and reports on how glial cells regulate ferroptosis in PD through iron homeostasis and lipid peroxidation. This opens up a new pathway for basic research and therapeutic strategies in Parkinson’s disease.

ObjectiveTo evaluate the clinical efficacy of different androgen deprivation therapies for prostate cancer (PCa) based on dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI).Methods104 patients with PCa were studied, all of whom were treated with androgen deprivation therapy. The patients were divided into a continuous group (continuous androgen deprivation therapy) and an intermittent group (intermittent androgen deprivation therapy) by random number table method, 52 cases/group. The therapeutic effect and DCE-MRI indices were compared and the relationship between DCE-MRI indices and clinical efficacy and the evaluation value of therapeutic efficacy were analyzed.ResultsThe objective response rate (ORR) of the intermittent group was higher than that of the continuous group (p < 0.05), and there was no significant difference in disease control rate (DCR) between the two groups (p > 0.05). After treatment, volume transfer coefficient (Ktrans), reverse transfer constant (Kep), volume fraction (Ve), blood volume (BV), and blood flow (BF) in both groups were lowered, and those in the intermittent group were lower than the continuous group (p < 0.05). Ktrans, Kep, Ve, BF, and BV in the ORR group were lower than those in the non-ORR group (p < 0.05). Ktrans, Kep, Ve, BF, and BV were correlated with the therapeutic effect of PCa (p < 0.05). The AUC value of the combined detection of DCE-MRI indices in evaluating the therapeutic effect of PCa was greater than that of each index alone (p < 0.05).ConclusionCompared with continuous androgen deprivation therapy, intermittent androgen deprivation therapy has better clinical efficacy in the treatment of PCa, and DCE-MRI indices are related to the treatment efficacy of PCa and have an evaluation value.

BackgroundDysregulation of feeding behavior leads to a variety of pathological manifestations ranging from obesity to anorexia. The foraging behavior of animals affected by food deficiency is not fully understood.MethodsHome-Cage system was used to monitor the behaviors. Immunohistochemical staining was used to monitor the trend of neuronal activity. Chemogenetic approach was used to modify neuronal activity.ResultsWe described here a unique mouse model of foraging behavior and unveiled that food deprivation significantly increases the general activities of mice with a daily rhythmic pattern, particularly foraging behavior. The increased foraging behavior is potentiated by food cues (mouthfeel, odor, size, and shape) and energy deficit, rather than macronutrient protein, carbohydrate, and fat. Notably, energy deficiency increases nocturnal neuronal activity in paraventricular hypothalamic nucleus (PVH), accompanying a similar change in rhythmic foraging behavior. Activating neuronal activity in PVH enhances the amplitude of foraging behavior in mice. Conversely, inactivating neuronal activity in PVH decreases the amplitude of foraging behavior and impairs the rhythm of foraging behavior.DiscussionThese results illustrate that energy status and food cues regulate the rhythmic foraging behavior via PVH neuronal activity. Understanding foraging behavior provides insights into the underlying mechanism of eating-related disorders.

BackgroundStroke is the second leading cause of death worldwide and a major cause of long-term neurological disability, imposing an enormous financial burden on families and society. This study aimed to identify the predictors in stroke patients and construct a nomogram prediction model based on these predictors.MethodsThis retrospective study included 11,435 participants aged >20 years who were selected from the NHANES 2011–2018. Randomly selected subjects (n = 8531; 75%) and the remaining subjects comprised the development and validation groups, respectively. The least absolute shrinkage and selection operator (LASSO) binomial and logistic regression models were used to select the optimal predictive variables. The stroke probability was calculated using a predictor-based nomogram. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 1000 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram.ResultsAccording to the minimum criteria of non-zero coefficients of Lasso and logistic regression screening, older age, lower education level, lower family income, hypertension, depression status, diabetes, heavy smoking, heavy drinking, trouble sleeping, congestive heart failure (CHF), coronary heart disease (CHD), angina pectoris and myocardial infarction were independently associated with a higher stroke risk. A nomogram model for stroke patient risk was established based on these predictors. The AUC (C statistic) of the nomogram was 0.843 (95% CI: 0.8186–0.8430) in the development group and 0.826 (95% CI: 0.7811, 0.8716) in the validation group. The calibration curves after 1000 bootstraps displayed a good fit between the actual and predicted probabilities in both the development and validation groups. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0–0.2 and 0–0.25, respectively.DiscussionThis study effectively established a nomogram including demographic characteristics, vascular risk factors, emotional factors and lifestyle behaviors to predict stroke risk. This nomogram is helpful for screening high-risk stroke individuals and could assist physicians in making better treatment decisions to reduce stroke occurrence.

BackgroundCancer as a deathly disease with high prevalence has impelled researchers to investigate its causative mechanisms in the search for effective therapeutics. Recently, the concept of phase separation has been introduced to biological science and extended to cancer research, which helps reveal various pathogenic processes that have not been identified before. As a process of soluble biomolecules condensed into solid-like and membraneless structures, phase separation is associated with multiple oncogenic processes. However, there are no bibliometric characteristics for these results. To provide future trends and identify new frontiers in this field, a bibliometric analysis was conducted in this study.MethodsThe Web of Science Core Collection (WoSCC) was used to search for literature on phase separation in cancer from 1/1/2009 to 31/12/2022. After screening the literature, statistical analysis and visualization were carried out by the VOSviewer software (version 1.6.18) and Citespace software (Version 6.1.R6).ResultsA total of 264 publications, covering 413 organizations and 32 countries, were published in 137 journals, with an increasing trend in publication and citation numbers per year. The USA and China were the two countries with the largest number of publications, and the University of Chinese Academy of Sciences was the most active institution based on the number of articles and cooperations. Molecular Cell was the most frequent publisher with high citations and H-index. The most productive authors were Fox AH, De Oliveira GAP, and Tompa P. Overlay, whilst few authors had a strong collaboration with each other. The combined analysis of concurrent and burst keywords revealed that the future research hotspots of phase separation in cancer were related to tumor microenvironments, immunotherapy, prognosis, p53, and cell death.ConclusionPhase separation-related cancer research remained in the hot streak period and exhibited a promising outlook. Although inter-agency collaboration existed, cooperation among research groups was rare, and no author dominated this field at the current stage. Investigating the interfaced effects between phase separation and tumor microenvironments on carcinoma behaviors, and constructing relevant prognoses and therapeutics such as immune infiltration-based prognosis and immunotherapy might be the next research trend in the study of phase separation and cancer.

Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer’s disease (AD), and thus identifying who among the increasing T2DM populations may develop into AD is important for early intervention. By using TMT-labeling coupled high-throughput mass spectrometry, we conducted a comprehensive plasma proteomic analysis in none-T2DM people (Ctrl, n = 30), and the age-/sex-matched T2DM patients with mild cognitive impairment (T2DM-MCI, n = 30) or T2DM without MCI (T2DM-nMCI, n = 25). The candidate biomarkers identified by proteomics and bioinformatics analyses were verified by ELISA, and their diagnostic capabilities were evaluated with machine learning. A total of 53 differentially expressed proteins (DEPs) were identified in T2DM-MCI compared with T2DM-nMCI patients. These DEPs were significantly enriched in multiple biological processes, such as amyloid neuropathies, CNS disorders, and metabolic acidosis. Among the DEPs, alpha-1-antitrypsin (SERPINA1), major viral protein (PRNP), and valosin-containing protein (VCP) showed strong correlation with AD high-risk genes APP, MAPT, APOE, PSEN1, and PSEN2. Also, the levels of PP2A cancer inhibitor (CIP2A), PRNP, corticotropin-releasing factor-binding protein (CRHBP) were significantly increased, while the level of VCP was decreased in T2DM-MCI patients compared with that of the T2DM-nMCI, and these changes were correlated with the Mini-Mental State Examination (MMSE) score. Further machine learning data showed that increases in PRNP, CRHBP, VCP, and rGSK-3β(T/S9) (ratio of total to serine-9-phosphorylated glycogen synthase kinase-3β) had the greatest power to identify mild cognitive decline in T2DM patients.

BackgroundAlthough non-motor symptoms of Parkinson’s disease (PD) are serious, effective treatments are still lacking. Acupuncture may have clinical benefits for non-motor symptoms of PD patients, but high-quality evidence supporting this possibility is still limited. Hence, we conducted this meta-analysis to evaluate the effect of acupuncture treatment on non-motor symptoms in patients with PD.MethodsRandomized controlled trials (RCTs) of acupuncture treatment for PD were retrieved from the following electronic databases: Medline (OVID), Embase (OVID), Cochrane Library, Web of Science, China National Knowledge Infrastructure, Chinese BioMedical Literature Database, Chonqing VIP (CQVIP), and Wangfang database. Studies evaluating non-motor symptoms of PD were retrieved. Methodological quality was assessed using the Cochrane Handbook for Systematic Reviews of Interventions.ResultsA total of 27 RCTs were included, among which 8 outcomes related to non-motor symptoms were evaluated. The results showed that acupuncture combined with medication had benefits for PD-related insomnia relative to medication alone or sham acupuncture [standardized mean difference (SMD) = 0.517; 95% confidence interval (CI) = 0.242–0.793; p = 0.000], and acupuncture treatment had benefits at 8 weeks (SMD = 0.519; 95% CI = 0.181–0.857; p = 0.003). Regarding depression, acupuncture treatment was more effective (SMD = −0.353; 95% CI = −0.669 to −0.037; p = 0.029) within 2 months (SMD = −0.671; 95% CI = −1.332 to −0.011; p = 0.046). Regarding cognition, quality of life, and Unified Parkinson’s Disease Rating Scale (UPDRS) I and II scores, acupuncture treatment was effective [SMD = 0.878, 95% CI = 0.046–1.711, p = 0.039; SMD = −0.690, 95% CI = −1.226 to −0.155, p = 0.011; weighted mean difference (WMD) = −1.536, 95% CI = −2.201 to −0.871, p = 0.000; WMD = −2.071, 95% CI = −3.792 to −0.351, p = 0.018; respectively]. A significant difference was not found in terms of PD-related constipation. Only one study evaluated PD-related fatigue.ConclusionThe results of the analysis suggested that acupuncture treatment could ameliorate the symptoms of depression, quality of life, cognition, total mentation, behavior and mood, and activities of daily living in PD patients. Nevertheless, more prospective, well-designed RCTs with larger sample sizes are required to confirm our findings.

The Mediterranean diet (MED), a dietary pattern rich in fruits and vegetables, whole grains, legumes, nuts, fish, and olive oil, has anti-oxidative and anti-inflammatory effects. Although some data suggest that MED adherence is associated with decreased manifestation of depressive symptoms, it remains necessary to further analyze this apparent non-linear association as well as the influence of different factors on the relationship between MED and depression. Here, we investigated associations between the alternate MED (aMED) score and depressive symptom via multivariate logistic regression, weighted generalized additive (GAM) and two-step linear regression models, analyzing data from the 2005–2018 National Health and Nutrition Examination Survey (NHANES). The most important factor relevant to aMED score that contributed to the prevalence of depressive symptom was assessed using random forest. Furthermore, we examined whether the relationship between aMED score and depressive symptom differs by age, race, sex, socioeconomic variables, lifestyle- and health-related variables, and chronic medical conditions, via subgroup analyses. A total of 19,477 participants (20–80 years of age) were included in this cross-sectional study. In crude and adjusted (1–5) multivariate logistic regression models, increased aMED score was noted to associate with non-depressive status, as defined using the Patient Health Questionnaire-9 (P < 0.05). Data analyses via GAM and two-piecewise linear regression revealed a non-linear association between aMED and depressive symptom, which had an inflection point of 3. Random forest results revealed that vegetable score contributes greatest to the relationship between aMED and depressive symptom. Subgroup analyses revealed that aMED score is significantly negatively related with depressive symptom in most different populations (P < 0.05) with the exception of high annual income, diabetes, borderline blood glucose level and Parkinson's disease (PD) (P > 0.05). In conclusion, we observed a non-linear association between aMED score and depressive symptom. Further studies are needed to validate our results.

Introduction: Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer’s disease (AD), and populations with mild cognitive impairment (MCI) have high incidence to suffer from AD. Therefore, discerning who may be more vulnerable to MCI, among the increasing T2DM populations, is important for early intervention and eventually decreasing the prevalence rate of AD. This study was to explore whether the change of plasma β-amyloid (Aβ) could be a biomarker to distinguish MCI (T2DM-MCI) from non-MCI (T2DM-nMCI) in T2DM patients.Methods: Eight hundred fifty-two T2DM patients collected from five medical centers were assigned randomly to training and validation cohorts. Plasma Aβ, platelet glycogen synthase kinase-3β (GSK-3β), apolipoprotein E (ApoE) genotypes, and olfactory and cognitive functions were measured by ELISA, dot blot, RT-PCR, Connecticut Chemosensory Clinical Research Center (CCCRC) olfactory test based on the diluted butanol, and Minimum Mental State Examination (MMSE) test, respectively, and multivariate logistic regression analyses were applied.Results: Elevation of plasma Aβ1-42/Aβ1-40 is an independent risk factor of MCI in T2DM patients. Although using Aβ1-42/Aβ1-40 alone only reached an AUC of 0.631 for MCI diagnosis, addition of the elevated Aβ1-42/Aβ1-40 to our previous model (i.e., activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging) significantly increased the discriminating efficiency of T2DM-MCI from T2DM-nMCI, with an AUC of 0.846 (95% CI: 0.794–0.897) to 0.869 (95% CI: 0.822–0.916) in the training cohort and an AUC of 0.848 (95% CI: 0.815–0.882) to 0.867 (95% CI: 0.835–0.899) in the validation cohort, respectively.Conclusion: A combination of the elevated plasma Aβ1-42/Aβ1-40 with activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging could efficiently diagnose MCI in T2DM patients. Further longitudinal studies may consummate the model for early prediction of AD.

PurposeEpidemiological studies have demonstrated the clinical link between Hunner interstitial cystitis (HIC) and autoimmune diseases (ADs), suggesting potential shared genetic bases for their comorbidity. We aimed to investigate the shared genetic architecture and causal relationships between HIC and ADs.MethodsWe conducted a genome-wide cross-trait study with ~170000 individuals of East Asian ancestry to investigate the shared architecture between HIC and ADs. Bidirectional Mendelian randomization (MR) was used to assess potential causal relationships and a multi-trait analysis of GWAS (MTAG) was conducted to identify their associated pleiotropic loci. Fine-mapping analysis narrowed candidate gene susceptibility loci and colocalization analysis was performed to identify shared variants at specific locus. Lastly, transcriptome-wide association (TWAS) and functional analysis were utilized to explore potential shared gene-tissue associations.ResultsThrough bidirectional MR analysis, we observed a positive causal effect of AIH(ORIVW=1.09, PIVW=1.00×10-3) and RA (ORIVW=1.47, PIVW

To determine the appropriate seeding rate for machine-transplanted hybrid rice, field experiments were conducted during 2022–2023 using the hybrid rice variety Huazhe You 210 as the material. Four seeding rate treatments were set up: 40 (T1), 60 (T2), 80 (T3) and 100 g tray-1 (T4), to investigate the effects of seeding rate on the seedling quality, transplanting quality, yield formation, and economic benefits of high-quality indica hybrid rice seedlings. The results showed that with increasing seeding rate, the seedling base stem diameter and seedling plumpness of hybrid rice seedlings decreased, but the root entwining force gradually increased, leading to a deterioration in individual seedling quality but an improvement in collective characteristics. As the seeding rate increased, the missing hill rate during mechanical planting of hybrid rice significantly decreased, while the number of seedlings per hill and the damaged seedling rate showed an upward trend. The growth volume of tillers, tillering spikelet rate, and harvest index of hybrid rice in the field showed an overall downward trend with increasing seeding rate, while the accumulation of dry matter initially increased and then decreased. The yield and economic benefits of hybrid rice grains showed an initial increase followed by a decrease with increasing seeding rate, with the highest yield and economic benefits achieved with the T2 treatment. In conclusion, the appropriate seeding rate for machine-transplanted hybrid rice is T2 (60 g tray-1), which can maintain good seedling quality and improve transplanting quality, coordinate larger collective growth and appropriate harvest index, contributing to high yield and good economic benefits.

Biaxial rotary tillage is considered an effective approach for enhancing the structure of soil in rice fields. There are few reports on the effects of biaxial rotary tillage on the carbon footprint (CF), energy budget, and net ecosystem economic efficiency (NEEB) of rice fields. Here, we evaluated the effects of dryland biaxial rotary tillage (DBRT), as well as two traditional tillage methods, dryland and paddy field in uniaxial rotary tillage (DPURT) and paddy field in uniaxial rotary tillage (PURT), on the CF, energy budget, and NEEB of rice production to clarify the economic and ecological utility of DBRT. The tillage depth was 9.5–15.4% higher under DBRT than under DPURT and PURT (p

Objective: China and many developing countries has placed high expectations on the general practice healthcare system in terms of lowering medical costs and improving the health status of the multimorbid population in recent years. However, the prevalence of multimorbidity among inpatients attending the general practice department of hospitals and its policy implications are largely unknown. The current study aimed to analyze the prevalence of comorbidities among inpatients attending the general practice department of the tertiary Grade-A Hospitals in China, and put forward evidence-based policy recommendations.Methods: Between December 2016 and November 2020, 351 registered general practitioners from 27 tertiary hospitals were selected, and their direct admissions were evaluated. The rate and composition ratio were used for descriptive analysis of the clinical and epidemiological characteristics of multimorbidity. A backward stepwise algorithm was used to explore independent variables. The absence of multicollinearity and plausible interactions among variables were tested to ensure the robustness of the logistic regression model. The pyramid diagram was used to show the link between gender and the involved human body system in multimorbidity.Results: Multimorbidity was present in 93.1% of the 64, 395 patients who were admitted directly. Multimorbidity was significantly more prevalent in patients aged 45–59 years (OR=3.018, 95% CI=1.945–4.683), 60–74 years (OR = 4.349, 95% CI = 2.574–7.349), ≥75 years (OR = 7.804, 95% CI = 3.665–16.616), and those with body mass index (BMI) ≥ 28 kg/m2 (OR = 3.770, 95% CI = 1.453–9.785). The circulatory system was found to be the most commonly involved human body system in multimorbidity, accounting for 79.2% (95% CI = 78.8–79.5%) of all cases. Significant gender inequity was further observed in the involved human body system in multimorbidity.Conclusion: Multimorbidity is likely common among the inpatients attending the general practice department of hospitals in China and many developing countries, with significant gender inequity in the involved human body systems. Effective countermeasures include establishing a GP-PCIC multimorbidity prevention and control model and enhancing the multimorbidity of elderly and obese patients at both the clinical and healthy lifestyle levels. The diagnosis and treatment capabilities of GPs on the circulatory, endocrine, metabolic, digestive, and respiratory systems should be prioritized.