Background
The overall prevalence of papillary thyroid carcinoma (PTC) patients is expanding along with an ongoing increase in thyroid cancer incidence. Patients with PTC who have lymph node ...metastases have a poor prognosis and a high death rate. There is an urgent need for indicators that can predict lymph node metastasis (LNM) before surgery as current imaging techniques, such as ultrasonography, do not have sufficient sensitivity to detect LNM. To predict independent risk factors for Central lymph node metastasis (CLNM) or Lateral lymph node metastasis (LLNM), we therefore developed two nomograms based on CLNM and LLNM, separately.
Methods
In two centers, the Second Affiliated Hospital of Nanchang University and Yichun People’s Hospital, we retrospectively analyzed clinicopathological characteristics of PTC patients. We utilized multivariate analysis to screen for variables that might be suspiciously related to CLNM or LLNM. Furthermore, we developed nomograms to graphically depict the independent risk valuables connected to lymph node metastasis in PTC patients.
Result
Ultimately, 6068 PTC patients in all were included in the research. Six factors, including age<45, male, mETE, TSH>1.418, tumor size>4cm, and location (multicentric and lobe), were observed to be related to CLNM. Age<45, male, mETE (minimal extrathyroidal extension), multifocality, TSH≥2.910, CLNM positive, and tumor size>4cm were regarded as related risk factors for LLNM. The two nomograms developed subsequently proved to have good predictive power with 0.706 and 0.818 and demonstrated good clinical guidance functionality with clinical decision curves and impact curves.
Conclusion
Based on the successful establishment of this dual-institution-based visual nomogram model, we found that some clinical features are highly correlated with cervical lymph node metastasis, including CLNM and LLNM, which will better help clinicians make individualized clinical decisions for more effectively rationalizing managing PTC patients.
Cognitive impairment (CI) is a common neurological complication in patients with end-stage renal disease undergoing maintenance hemodialysis (MHD). Brain network analysis based on graph theory is a ...promising tool for studying CI. Therefore, the purpose of this study was to analyze the changes of functional brain networks in patients on MHD with and without CI by using graph theory and further explore the underlying neuropathological mechanism of CI in these patients.
A total of 39 patients on MHD (19 cases with CI and 20 without) and 25 healthy controls (HCs) matched for age, sex, and years of education were enrolled in the study. Resting-state functional magnetic resonance imaging (rs-fMRI) and T1-weighted high-resolution anatomical data were obtained, and functional brain networks for each subject were constructed. The brain network parameters at the global and regional levels were calculated, and a one-way analysis of covariance was used to compare the differences across the three groups. The associations between the changed graph-theory parameters and cognitive function scores in patients on MHD were evaluated using Spearman correlation analysis.
Compared with HCs, the global parameters sigma, gamma, and local efficiency (Eloc) in both patient groups decreased significantly (
< 0.05, Bonferroni corrected). The clustering coefficient (Cp) in patients with CI was significantly lower than that in the other two groups (
< 0.05, Bonferroni corrected). The regional parameters were significantly lower in the right superior frontal gyrus, dorsolateral (SFGdor) and gyrus rectus (REC) of patients with CI than those of patients without CI; however the nodal local efficiency in the left amygdala was significantly increased (all
< 0.05, Bonferroni corrected). The global Cp and regional parameters in the three brain regions (right SFGdor, REC, and left amygdala) were significantly correlated with the cognitive function scores (all FDR
< 0.05).
This study confirmed that the topology of the functional brain network was disrupted in patients on MHD with and without CI and the disruption of brain network was more severe in patients with CI. The abnormal brain network parameters are closely related to cognitive function in patients on MHD.
•The accessibility was measured using POI, OSM, land cover, and WorldPop data.•The accessibility was measured in terms of travel time to the nearest service.•The average time costs of hospital and ...school are 20 and 22 min, respectively.•Accessibility is high in eastern China and low in western China.•Low-GDP counties require high mean time cost to reach hospital and school.
Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes. Health and education are critical domains of the Unites Nations’ Sustainable Development Goals (SDGs), yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies. This means that such studies lack accessibility metrics for large-scale quantitative evaluations. To address this deficiency, we evaluated the accessibility of health and education services in mainland China in 2021 using point-of-interest data, OpenStreetMap road data, land cover data, and WorldPop spatial demographic data. The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h. On the basis of the road network and land cover information, the overall average time costs of reaching hospital and school were 20 and 22 min, respectively. In terms of population coverage, 94.7% and 92.5% of the population in China has a time cost of less than 1 h in obtaining hospital and school services, respectively. Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions, with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas. Furthermore, the cumulative time cost incurred by the bottom 20% of counties (by GDP) from access to hospital and school services reached approximately 80% of the national total. Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties. The accessibility metrics proposed in this study are highly related to SDGs 3 and 4, and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes. The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.
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This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic ...medical records (EMRs).
Sixty-one medical characteristics (including demography information, laboratory measurements, and complicating disease) readily available from EMRs were retained for clinical analysis. These characteristics further aided the development of prediction models by using seven ML algorithms light gradient-boosting machine (LightGBM), support vector machine (SVM), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), decision tree, multilayer perceptron (MLP), and logistic regression. The performance of this model was assessed using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was further applied to interpret the findings of the best-performing model.
The LightGBM model exhibited the highest AUC (0.849; 95% CI, 0.814-0.883). Additionally, the SHAP plot per the LightGBM depicted that age, heart failure, hypertension, glucose, serum creatinine, indirect bilirubin, serum uric acid, and amylase can help identify PLHIV who were at a high or low risk of developing CHD.
This study developed a CHD risk prediction model for PLHIV utilizing ML techniques and EMR data. The LightGBM model exhibited improved comprehensive performance and thus had higher reliability in assessing the risk predictors of CHD. Hence, it can potentially facilitate the development of clinical management techniques for PLHIV care in the era of EMRs.
To establish castration-resistant prostate cancer (CRPC) - Lncap androgen-independent (AI) cell line from Lncap androgen-dependent (AD) cell line, and explore the different molecular biological ...between these two cell lines. The Lncap-AD cell line was cultured and passaged 60 times over 16 months. The morphology of the Lncap-AI cell line was observed. AR levels identification were detected in qRT-PCR and Western Blot assay. CCK-8, EdU assay, wound healing assay and cell adhesion assays were used to observe the ability of proliferation, migration, and adhesion. SEM and TEM were used to observe microculture structure. At last, the PSA secrete ability was evaluated by Elisa assay. The Lncap-AD cell line was cultured and passaged 60 times over 16 months. The Lncap-AI cell line showed a morphologic change at the end stage of culture, the cells turned slender and cell space turned separated compared to the Lncap-AD cell line. The relative levels of AR-related genes in the Lncap-AI cell line were up-regulation compared to the Lncap-AD cell line both in mRNA and protein levels. The expression of AR and HK2 proteins were influenced and down-regulation by Enzalutamide in the Lncap-AD cell line, but no obvious difference in Lncap-AI cell lines. Lncap-AI cell line showed strong viability of proliferation, migration, and adhesion by CCK-8, EdU assay, wound healing assay, and adhesion assay. The microstructure of Scanning Electron Microscopy (SEM) showed many synapses in the Lncap-AI cell line and PC3 cell line, but not in the Lncap-AD cell line. At last, the PSA secrete ability was evaluated by Elisa assay, and PCa cell lines showed no significant difference. Simulation of CRPC progression, Lncap-AD cell line turned to Lncap-AI cell line with androgen deprivation therapy.
•A novel mobility-based spatial sampling framework to improve the detection efficiency of emerging infections.•Spatiotemporal patterns of human mobility derived from mobile phone and ...point-of-interest data.•Four different sampling approaches for optimizing the testing resource allocation.•Evaluate the performance of sampling methods under actual and simulated scenarios of COVID-19 transmissions.
Timely and precise detection of emerging infections is imperative for effective outbreak management and disease control. Human mobility significantly influences the spatial transmission dynamics of infectious diseases. Spatial sampling, integrating the spatial structure of the target, holds promise as an approach for testing allocation in detecting infections, and leveraging information on individuals’ movement and contact behavior can enhance targeting precision. This study introduces a spatial sampling framework informed by spatiotemporal analysis of human mobility data, aiming to optimize the allocation of testing resources for detecting emerging infections. Mobility patterns, derived from clustering point-of-interest and travel data, are integrated into four spatial sampling approaches at the community level. We evaluate the proposed mobility-based spatial sampling by analyzing both actual and simulated outbreaks, considering scenarios of transmissibility, intervention timing, and population density in cities. Results indicate that leveraging inter-community movement data and initial case locations, the proposed Case Flow Intensity (CFI) and Case Transmission Intensity (CTI)-informed spatial sampling enhances community-level testing efficiency by reducing the number of individuals screened while maintaining a high accuracy rate in infection identification. Furthermore, the prompt application of CFI and CTI within cities is crucial for effective detection, especially in highly contagious infections within densely populated areas. With the widespread use of human mobility data for infectious disease responses, the proposed theoretical framework extends spatiotemporal data analysis of mobility patterns into spatial sampling, providing a cost-effective solution to optimize testing resource deployment for containing emerging infectious diseases.
Spinal cord injury is a serious traumatic disease. As Ferroptosis has been increasingly studied in recent years, it has been found to be closely related to the pathophysiological processes of spinal ...cord injury. Iron overload, reactive oxygen species accumulation, lipid peroxidation and glutamate accumulation associated with Ferroptosis are all present in spinal cord injury, and thus Ferroptosis is thought to be involved in the pathological processes secondary to spinal cord injury. This article highlights the relationship between Ferroptosis and spinal cord injury, lists substances that improve spinal cord injury by inhibiting Ferroptosis, and concludes with a discussion of the problems that may be encountered in the clinical translation of Ferroptosis inhibitors as a means of enabling their faster use in clinical treatment.
Rationale
Sex differences in cocaine abuse have been well documented. However, the underlying mechanism remains unclear.
Objectives
To explore the potential role of ovarian hormones in the regulation ...of dopamine (DA) neuron firing activity in ventral tegmental area (VTA) induced by acute cocaine in intact female or ovariectomized (OVX) rats.
Results
The basal firing activity of VTA DA neurons was changed in a manner phase-locked to the estrous cycle: being highest in estrus and lowest in proestrus. Acute cocaine produced greater inhibition (
P
< 0.05) on the firing of VTA DA neurons during proestrus than during estrus. The inhibitory effect was completely blocked by OVX and restored by replacement of 17-β-estradiol or, to a less extent, by replacement of progesterone. In addition, we also detected female hormone-associated changes in slow oscillation in VTA DA neurons. The results indicate that ovarian hormones, particularly estrogen, not only synergize with the inhibitory effect of cocaine on VTA DA neuron activity but also play an essential role in maintaining the sensitivity of DA neurons to cocaine-mediated inhibition on firing. Moreover, pretreatment of estrogen receptor (ER) antagonist raloxifene or a selective ERα antagonist Y134 largely attenuated the cocaine-inhibited DA neuron firing. We also found that cocaine-induced locomotor activity was estrous cycle dependant; 17-β-estradiol but not progesterone replacement restored the cocaine-induced locomotor activity in OVX rats.
Conclusion
The present results demonstrated that ovarian hormones, particularly estrogen, produce profound effect on VTA DA neuron activity, which, in turn, may contribute to the sex differences in response to psychostimulants.
Abstract
Background
Proteins containing the Jumonji C (JmjC) domain participated in tumorigenesis and cancer progression. However, the mechanisms underlying this effect are still poorly understood. ...Our objective was to investigate the role of Jumonji and the AT‐rich interaction domain‐containing 2 (JARID2) — a JmjC family protein — in breast cancer, as well as its latent association with obesity.
Methods
Immunohistochemistry, The Cancer Genome Atlas, Gene Expression Omnibus, and other databases were used to analyze the expression of JARID2 in breast cancer cells. Growth curve, 5‐ethynyl‐2‐deoxyuridine (EdU), colony formation, and cell invasion experiments were used to detect whether JARID2 affected breast cancer cell proliferation and invasion. Spheroidization‐based experiments and xenotumor transplantation in NOD/SCID mice were used to examine the association between JARID2 and breast cancer stemness. RNA‐sequencing, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to identify the cell processes in which JARID2 participates. Immunoaffinity purification and silver staining mass spectrometry were conducted to search for proteins that might interact with JARID2. The results were further verified using co‐immunoprecipitation and glutathione S‐transferase (GST) pull‐down experiments. Using chromatin immunoprecipitation (ChIP) sequencing, we sought the target genes that JARID2 and metastasis‐associated protein 1 (MTA1) jointly regulated; the results were validated by ChIP‐PCR, quantitative ChIP (qChIP) and ChIP‐reChIP assays. A coculture experiment was used to explore the interactions between breast cancer cells and adipocytes.
Results
In this study, we found that JARID2 was highly expressed in multiple types of cancer including breast cancer. JARID2 promoted glycolysis, lipid metabolism, proliferation, invasion, and stemness of breast cancer cells. Furthermore, JARID2 physically interacted with the nucleosome remodeling and deacetylase (NuRD) complex, transcriptionally repressing a series of tumor suppressor genes such as BRCA2 DNA repair associated (
BRCA2
), RB transcriptional corepressor 1 (
RB1
), and inositol polyphosphate‐4‐phosphatase type II B (
INPP4B
). Additionally, JARID2 expression was regulated by the obesity‐associated adipokine leptin via Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) pathway in the breast cancer microenvironment. Analysis of various online databases also indicated that JARID2/MTA1 was associated with a poor prognosis of breast cancer.
Conclusion
Our data indicated that JARID2 promoted breast tumorigenesis and development, confirming JARID2 as a target for cancer treatment.
Mitophagy is a degradative pathway that mediates the degradation of the entire mitochondria, and defects in this process are implicated in many diseases including cancer. In mammals, mitophagy is ...mediated by BNIP3L (also known as NIX) that is a dual regulator of mitochondrial turnover and programmed cell death pathways. Acute myeloid leukemia (AML) cells with deficiency of BNIP3L are more sensitive to mitochondria-targeting drugs. But small molecular inhibitors for BNIP3L are currently not available. Some immunomodulatory drugs (IMiDs) have been proved by FDA for hematologic malignancies, however, the underlining molecular mechanisms are still elusive, which hindered the applications of BNIP3L inhibition for AML treatment. In this study we carried out MS-based quantitative proteomics analysis to identify the potential neosubstrates of a novel thalidomide derivative CC-885 in A549 cells. In total, we quantified 5029 proteins with 36 downregulated in CRBN
cell after CC-885 administration. Bioinformatic analysis showed that macromitophagy pathway was enriched in the negative pathway after CC-885 treatment. We further found that CC-885 caused both dose- and time-dependent degradation of BNIP3L in CRBN
, but not CRBN
cell. Thus, our data uncover a novel role of CC-885 in the regulation of mitophagy by targeting BNIP3L for CRL4CRBN E3 ligase-dependent ubiquitination and degradation, suggesting that CC-885 could be used as a selective BNIP3L degradator for the further investigation. Furthermore, we demonstrated that CC-885 could enhance AML cell sensitivity to the mitochondria-targeting drug rotenone, suggesting that combining CC-885 and mitochondria-targeting drugs may be a therapeutic strategy for AML patients.
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