Role of gut microbiota in doxorubicin-induced cardiotoxicity: from pathogenesis to related interventions.

Doxorubicin (DOX) is a broad-spectrum and highly efficient anticancer agent, but its clinical implication is limited by lethal cardiotoxicity. Growing evidences have shown that alterations in intestinal microbial composition and function, namely dysbiosis, are closely linked to the progression of DOX-induced cardiotoxicity (DIC) through regulating the gut-microbiota-heart (GMH) axis. The role of gut microbiota and its metabolites in DIC, however, is largely unelucidated. Our review will focus on the potential mechanism between gut microbiota dysbiosis and DIC, so as to provide novel insights into the pathophysiology of DIC. Furthermore, we summarize the underlying interventions of microbial-targeted therapeutics in DIC, encompassing dietary interventions, fecal microbiota transplantation (FMT), probiotics, antibiotics, and natural phytochemicals. Given the emergence of microbial investigation in DIC, finally we aim to point out a novel direction for future research and clinical intervention of DIC, which may be helpful for the DIC patients.

Vascular-water-exchange MRI (VEXI) enables the detection of subtle AXR alterations in Alzheimer's disease without MRI contrast agent, which may relate to BBB integrity.

Blood-brain barrier (BBB) impairment is an important pathophysiological process in Alzheimer's disease (AD) and a potential biomarker for early diagnosis of AD. However, most current neuroimaging methods assessing BBB function need the injection of exogenous contrast agents (or tracers), which limits the application of these methods in a large population. In this study, we aim to explore the feasibility of vascular water exchange MRI (VEXI), a diffusion-MRI-based method proposed to assess the BBB permeability to water molecules without using a contrast agent, in the detection of the BBB breakdown in AD. We tested VEXI on a 3T MRI scanner on three groups: AD patients (AD group), mild cognitive impairment (MCI) patients due to AD (MCI group), and the age-matched normal cognition subjects (NC group). Interestingly, we find that the apparent water exchange across the BBB (AXRBBB) measured by VEXI shows higher values in MCI compared with NC, and this higher AXRBBB happens specifically in the hippocampus. This increase in AXRBBB value gets larger and extends to more brain regions (medial orbital frontal cortex and thalamus) from MCI group to the AD group. Furthermore, we find that the AXRBBB values of these three regions is correlated significantly with the impairment of respective cognitive domains independent of age, sex and education. These results suggest VEXI is a promising method to assess the BBB breakdown in AD.

The Consistence of Dynamic Contrast-Enhanced MRI and Filter-Exchange Imaging in Measuring Water Exchange Across the Blood-Brain Barrier in High-Grade Glioma.

BACKGROUND: Water exchange across blood-brain barrier (BBB) (WEXBBB ) is an emerging biomarker of BBB dysfunction with potential applications in many brain diseases. Several MRI methods have been proposed to measure WEXBBB , but evidence remains scarce whether different methods can produce comparable WEXBBB . PURPOSE: To explore whether dynamic contrast-enhanced (DCE)-MRI and vascular water exchange imaging (VEXI) could produce comparable WEXBBB in high-grade glioma (HGG) patients. STUDY TYPE: Prospective cross-sectional. SUBJECTS: 13 HGG patients (58.4 ± 9.4 years, 9 females, 4 WHO III and 9 WHO IV). FIELD STRENGTH/SEQUENCE: A 3 T, spoiled gradient-recalled-echo DCE-MRI and VEXI containing two pulsed-gradient spin-echo blocks separated by a mixing block. ASSESSMENTS: The enhanced tumor and contralateral normal-appearing white matter (cNAWM) volume-of-interests (VOIs) were drew by two neuroradiologists. And whole-brain NAWM and normal-appearing gray matter (NAGM) without tumor-affected regions were segmented by automated segmentation algorithm in FSL. STATISTICAL TESTS: Student's t-test was used to evaluate parameters difference between cNAWM and tumor, NAGM and NAWM, respectively. The correlation between vascular water efflux rate constant (kbo ) from DCE-MRI and apparent exchange rate across BBB (AXRBBB ) from VEXI was evaluated by Pearson correlation. P < 0.05 was considered statistically significant. RESULTS: Compared with cNAWM, both kbo and AXRBBB were significantly reduced in tumor (kbo = 3.50 ± 1.18 sec-1 vs. 1.03 ± 0.75 sec-1 ; AXRBBB = 3.54 ± 1.11 sec-1 vs. 1.94 ± 1.04 sec-1 ). Both kbo and AXRBBB showed significantly higher values in NAWM than NAGM (kbo = 3.50 ± 0.59 sec-1 vs. 2.10 ± 0.56 sec-1 ; AXRBBB = 3.35 ± 0.77 sec-1 vs. 2.07 ± 0.52 sec-1 ). The VOI-averaged kbo and AXRBBB were also linearly correlated in tumor, NAWM, and NAGM (r = 0.59). DATA CONCLUSION: DCE-MRI and VEXI showed comparable and correlated WEXBBB in HGG patients, suggesting that the consistence and reliability of these two MRI methods in measuring WEXBBB . EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 1.

The direction-dependence of apparent water exchange rate in human white matter.

Transmembrane water exchange is a potential biomarker in the diagnosis and understanding of cancers, brain disorders, and other diseases. Filter-exchange imaging (FEXI), a special case of diffusion exchange spectroscopy adapted for clinical applications, has the potential to reveal different physiological water exchange processes. However, it is still controversial whether modulating the diffusion encoding gradient direction can affect the apparent exchange rate (AXR) measurements of FEXI in white matter (WM) where water diffusion shows strong anisotropy. In this study, we explored the diffusion-encoding direction dependence of FEXI in human brain white matter by performing FEXI with 20 diffusion-encoding directions on a clinical 3T scanner in-vivo. The results show that the AXR values measured when the gradients are perpendicular to the fiber orientation (0.77 ± 0.13 s - 1, mean ± standard deviation of all the subjects) are significantly larger than the AXR estimates when the gradients are parallel to the fiber orientation (0.33 ± 0.14 s - 1, p < 0.001) in WM voxels with coherently-orientated fibers. In addition, no significant correlation is found between AXRs measured along these two directions, indicating that they are measuring different water exchange processes. What's more, only the perpendicular AXR rather than the parallel AXR shows dependence on axonal diameter, indicating that the perpendicular AXR might reflect transmembrane water exchange between intra-axonal and extra-cellular spaces. Further finite difference (FD) simulations having three water compartments (intra-axonal, intra-glial, and extra-cellular spaces) to mimic WM micro-environments also suggest that the perpendicular AXR is more sensitive to the axonal water transmembrane exchange than parallel AXR. Taken together, our results show that AXR measured along different directions could be utilized to probe different water exchange processes in WM.

Abnormal brain functional and structural connectivity between the left supplementary motor area and inferior frontal gyrus in moyamoya disease.

BACKGROUND: Disruption of brain functional connectivity has been detected after stroke, but whether it also occurs in moyamoya disease (MMD) is unknown. Impaired functional connectivity is always correlated with abnormal white matter fibers. Herein, we used multimodal imaging techniques to explore the changes in brain functional and structural connectivity in MMD patients. METHODS: We collected structural images, resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging for each subject. Cognitive functions of MMD patients were evaluated using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Trail Making Test parts A and B (TMT-A/-B). We calculated the functional connectivity for every paired region using 90 regions of interest from the Anatomical Automatic Labeling Atlas and then determined the differences between MMD patients and HCs. We extracted the functional connectivity of paired brain regions with significant differences between the two groups. Correlation analyses were then performed between the functional connectivity and variable cognitive functions. To explore whether the impaired functional connectivity and cognitive performances were attributed to the destruction of white matter fibers, we further analyzed fiber integrity using tractography between paired regions that were correlated with cognition. RESULTS: There was lower functional connectivity in MMD patients as compared to HCs between the bilateral inferior frontal gyrus, between the bilateral supramarginal gyrus, between the left supplementary motor area (SMA) and the left orbital part of the inferior frontal gyrus (IFGorb), and between the left SMA and the left middle temporal gyrus (P < 0.01, FDR corrected). The decreased functional connectivity between the left SMA and the left IFGorb was significantly correlated with the MMSE (r = 0.52, P = 0.024), MoCA (r = 0.60, P = 0.006), and TMT-B (r = -0.54, P = 0.048) in MMD patients. White matter fibers were also injured between the SMA and IFGorb in the left hemisphere and were positively correlated with reduced functional connectivity. CONCLUSIONS: Brain functional and structural connectivity between the supplementary motor area and inferior frontal gyrus in the left hemisphere are damaged in MMD. These findings could be useful in the evaluation of disease progression and prognosis of MMD.

Performance Comparison of Different Neuroimaging Methods for Predicting Upper Limb Motor Outcomes in Patients after Stroke.

Several neuroimaging methods have been proposed to assess the integrity of the corticospinal tract (CST) for predicting recovery of motor function after stroke, including conventional structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI). In this study, we aimed to compare the predicative performance of these methods using different neuroimaging modalities and optimize the prediction protocol for upper limb motor function after stroke in a clinical environment. We assessed 28 first-ever stroke patients with upper limb motor impairment. We used the upper extremity module of the Fugl-Meyer assessment (UE-FM) within 1 month of onset (baseline) and again 3 months poststroke. sMRI (T1- and T2-based) was used to measure CST-weighted lesion load (CST-wLL), and DTI was used to measure the fractional anisotropy asymmetry index (FAAI) and the ratio of fractional anisotropy (rFA). The CST-wLL within 1 month poststroke was closely correlated with upper limb motor outcomes and recovery potential. CST-wLL ≥ 2.068 cc indicated serious CST damage and a poor outcome (100%). CST-wLL < 1.799 cc was correlated with a considerable rate (>70%) of upper limb motor function recovery. CST-wLL showed a comparable area under the curve (AUC) to that of the CST-FAAI (p = 0.71). Inclusion of extra-CST-FAAI did not significantly increase the AUC (p = 0.58). Our findings suggest that sMRI-derived CST-wLL is a precise predictor of upper limb motor outcomes 3 months poststroke. We recommend this parameter as a predictive imaging biomarker for classifying patients' recovery prognosis in clinical practice. Conversely, including DTI appeared to induce no significant benefits.

PLAC8 promotes adriamycin resistance via blocking autophagy in breast cancer.

Adriamycin (ADM) is currently one of the most effective chemotherapeutic agents in breast cancer treatment. However, growing resistance to ADM could lead to treatment failure and poor outcome. PLAC8 was reported as a novel highly conserved protein and functioned as an oncogene or tumour suppressor in various tumours. Here, we found higher PLAC8 expression was correlated with worse outcome and aggressive phenotype in breast cancer. Breast cancer patients with higher PLAC8 expression showed potential ADM resistance. In vitro experiments further confirmed that PLAC8 inhibited by siRNA or enforced overexpression by infecting pcDNA3.1(C)-PLAC8 plasmid correspondingly decreased or increased ADM resistance. Subsequently, we demonstrated that ectopic PLAC8 expression in MCF-7/ADMR cell blocked the accumulation of the autophagy-associated protein LC3 and resulted in cellular accumulation of p62. Rapamycin-triggered autophagy significantly increased cell response to ADM, while the autophagy inhibitor 3-MA enhanced ADM resistance. 3-MA and PLAC8 could synergistically cause ADM resistance via blocking the autophagy process. Additionally, the down-regulation of p62 by siRNA attenuated the activation of autophagy and PLAC8 expression in breast cancer cells. Thus, our findings suggest that PLAC8, through the participation of p62, inhibits autophagy and consequently results in ADM resistance in breast cancer. PLAC8/p62 pathway may act as novel therapeutic targets in breast cancer treatment and has potential clinical application in overcoming ADM resistance.

Flexible autofocusing properties of ring Pearcey beams by means of a cross phase.

In this Letter, we introduce a new class of angular dependent autofocusing ring Pearcey beams by imposing a cross-phase structure. Due to this structure, the beam exhibits a non-uniform abrupt autofocusing behavior. Unlike the properties of the ring Pearcey beam without a cross phase [Opt. Lett.43, 3626 (2018)OPLEDP0146-959210.1364/OL.43.003626], we can flexibly adjust the focal length of the beam and its focusing ability, as well as the direction of the ring Pearcey beams, with the help of only the cross-phase structure. Furthermore, the Poynting vectors are employed to demonstrate convincingly the beam-focusing mechanism. Such beams with these fascinating characteristics are anticipated to find potential applications in optical tweezing, three-dimensional printing, material processing, and so on.

Convolutional neural network for accelerating the computation of the extended Tofts model in dynamic contrast-enhanced magnetic resonance imaging.

Quantitative physiological parameters can be obtained from nonlinear pharmacokinetic models, such as the extended Tofts (eTofts) model, applied to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). However, the computation of such nonlinear models is time consuming. The aim of this study was to develop a convolutional neural network (CNN) for accelerating the computation of fitting eTofts model without sacrificing agreement with conventional nonlinear-least-square (NLLS) fitting. This was a retrospective study, which included 13 patients with brain glioma for training (75%) and validation (25%), and 11 patients (three glioma, four brain metastases, and four lymphoma) for testing. CAIPIRINHA-Dixon-TWIST DCE-MRI and double flip angle T1 map acquired at 3 T were used. A CNN with both local pathway and global pathway modules was designed to estimate the eTofts model parameters, the volume transfer constant (Ktrans ), blood volume fraction (vp ), and volume fraction of extracellular extravascular space (ve ), from DCE-MRI data of tumor and normal-appearing voxels. The CNN was trained on mixed dataset consisting of synthetic and patient data. The CNN result and computation speed were compared with NLLS fitting. The robustness to noise variations and generalization to brain metastases and lymphoma data were also evaluated. Statistical tests used were Student's t test on mean absolute error, concordance correlation coefficient (CCC), and normalized root mean squared error. Including global pathway modules in the CNN and training the network with mixed data significantly (p < 0.05) improved the CNN performance. Compared with NLLS fitting, CNN yields an average CCC greater than 0.986 for Ktrans , greater than 0.965 for vp , and greater than 0.948 for ve . The CNN accelerated computation speed approximately 2000 times compared to NLLS, showed robustness to noise (signal-to-noise ratio >34.42 dB), and had no significant (p > 0.21) difference applied to brain metastases and lymphoma data. In conclusion, the proposed CNN to estimate eTofts parameters showed comparable result as NLLS fitting while significantly reducing the computation time. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 1.

Feasibility of filter-exchange imaging (FEXI) in measuring different exchange processes in human brain.

Transmembrane water exchange, including intra-to-extravascular and intra-to-extracellular ones, are potential biomarkers in the diagnosis and understanding of cancers, brain disorders, and other diseases. Filter-exchange imaging (FEXI), a special case of diffusion exchange spectroscopy (DEXSY) adapted for clinical applications, has the potential to reveal different physiological water exchange processes using the same MRI sequence. In this study, we aim to explore the feasibility of FEXI in measuring different water exchange processes by modulating the diffusion filter (bf) and detection blocks in FEXI. Two FEXI protocols were implemented on a 3T MRI clinical scanner and reveal distinct apparent exchange rate (AXR) contrast in brain tissues in seven healthy volunteers. AXR estimated from a FEXI protocol with bf â€‹= â€‹250 â€‹s/mm2, which is expected to filter out the vascular water specifically, are significantly larger than those of a FEXI protocol with bf â€‹= â€‹900 â€‹s/mm2. Besides, the filter efficiency of FEXI with bf â€‹= â€‹250 â€‹s/mm2 shows a strong correlation with vascular density, a metric estimated as the fraction of water exhibiting intravoxel incoherent motion (IVIM). AXR of FEXI with bf â€‹= â€‹250 â€‹s/mm2 agrees with the vascular water efflux rate constants reported by other independent measurements, although the physiological basis of the AXR of FEXI with bf â€‹= â€‹900 â€‹s/mm2 is not clear yet. Collectively, our current results demonstrate the feasibility of FEXI in measuring different water exchange processes in vivo, and that FEXI targeting the vascular water could help characterize the intra-to-extravascular water exchange process.

Shutter-Speed DCE-MRI Analyses of Human Glioblastoma Multiforme (GBM) Data.

BACKGROUND: The shutter-speed model dynamic contrast-enhanced (SSM-DCE) MRI pharmacokinetic analysis adds a metabolic dimension to DCE-MRI. This is of particular interest in cancers, since abnormal metabolic activity might happen. PURPOSE: To develop a DCE-MRI SSM analysis framework for glioblastoma multiforme (GBM) cases considering the heterogeneous tissue found in GBM. STUDY TYPE: Prospective. SUBJECTS: Ten GBM patients. FIELD STRENGTH/SEQUENCE: 3T MRI with DCE-MRI. ASSESSMENTS: The corrected Akaike information criterion (AICc ) was used to automatically separate DCE-MRI data into proper SSM versions based on the contrast agent (CA) extravasation in each pixel. The supra-intensive parameters, including the vascular water efflux rate constant (kbo ), the cellular efflux rate constant (kio ), and the CA vascular efflux rate constant (kpe ), together with intravascular and extravascular-extracellular water mole fractions (pb and po , respectively) were determined. Further error analyses were also performed to eliminate unreliable estimations on kio and kbo . STATISTICAL TESTS: Student's t-test. RESULTS: For tumor pixels of all subjects, 88% show lower AICc with SSM than with the Tofts model. Compared to normal-appearing white matter (NAWM), tumor tissue showed significantly larger pb (0.045 vs. 0.011, P < 0.001) and higher kpe (3.0 × 10-2 s-1 vs. 6.1 × 10-4 s-1 , P < 0.001). In the contrast, significant kbo reduction was observed from NAWM to GBM tumor tissue (2.8 s-1 vs. 1.0 s-1 , P < 0.001). In addition, kbo is four orders and two orders of magnitude greater than kpe in the NAWM and GBM tumor, respectively. These results indicate that CA and water molecule have different transmembrane pathways. The mean tumor kio of all subjects was 0.57 s-1 . DATA CONCLUSION: We demonstrate the feasibility of applying SSM models in GBM cases. Within the proposed SSM analysis framework, kio and kbo could be estimated, which might be useful biomarkers for GBM diagnosis and survival prediction in future. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:850-863.

Global analysis of an environmental disease transmission model linking within-host and between-host dynamics.

In this paper, a multi-scale mathematical model for environmentally transmitted diseases is proposed which couples the pathogen-immune interaction inside the human body with the disease transmission at the population level. The model is based on the nested approach that incorporates the infection-age-structured immunological dynamics into an epidemiological system structured by the chronological time, the infection age and the vaccination age. We conduct detailed analysis for both the within-host and between-host disease dynamics. Particularly, we derive the basic reproduction number R 0 for the between-host model and prove the uniform persistence of the system. Furthermore, using carefully constructed Lyapunov functions, we establish threshold-type results regarding the global dynamics of the between-host system: the disease-free equilibrium is globally asymptotically stable when R 0 < 1, and the endemic equilibrium is globally asymptotically stable when R 0 > 1. We explore the connection between the within-host and between-host dynamics through both mathematical analysis and numerical simulation. We show that the pathogen load and immune strength at the individual level contribute to the disease transmission and spread at the population level. We also find that, although the between-host transmission risk correlates positively with the within-host pathogen load, there is no simple monotonic relationship between the disease prevalence and the individual pathogen load.

PLCA8 suppresses breast cancer apoptosis by activating the PI3k/AKT/NF-κB pathway.

The cysteine-rich lysosomal protein placenta-specific 8 (PLAC8), also called onzin, has been shown to be involved in many types of cancers, and its role is highly dependent on cellular and physiological contexts. However, the precise function of PLAC8 in breast cancer (BC) progression remains unclear. In this study, we investigated both the clinical significance and biological functions of PLAC8 in BC progression. First, high PLAC8 expression was observed in primary BC tissues compared with adjacent normal tissues through immunohistochemistry analysis. The results of in vitro and in vivo assays further confirmed that PLAC8 overexpression promotes cell proliferation and suppress BC cell apoptosis, whereas PLAC8 silencing has the opposite effect. In addition, the forced expression of PLAC8 greatly induces cell migration, partially by affecting the EMT-related genes, including down-regulating E-cadherin expression and facilitating vimentin expression. Further mechanistic analysis confirmed that PLAC8 contributes to cell proliferation and suppresses cell apoptosis in BC by activating the PI3K/AKT/NF-κB pathway. The results of our study provide new insights into an oncogenic role of PLAC8 and reveal a novel PLAC8/ PI3K/AKT/NF-κB pathway as a potential therapeutic target for BC.

Suppression of epidemic spreading process on multiplex networks via active immunization.

Spatial epidemic spreading, a fundamental dynamical process upon complex networks, attracts huge research interest during the past few decades. To suppress the spreading of epidemic, a couple of effective methods have been proposed, including node vaccination. Under such a scenario, nodes are immunized passively and fail to reveal the mechanisms of active activity. Here, we suggest one novel model of an observer node, which can identify infection through interacting with infected neighbors and inform the other neighbors for vaccination, on multiplex networks, consisting of epidemic spreading layer and information spreading layer. In detail, the epidemic spreading layer supports susceptible-infected-recovered process, while observer nodes will be selected according to several algorithms derived from percolation theory. Numerical simulation results show that the algorithm based on large degree performs better than random placement, while the algorithm based on nodes' degree in the information spreading layer performs the best (i.e., the best suppression efficacy is guaranteed when placing observer nodes based on nodes' degree in the information spreading layer). With the help of state probability transition equation, the above phenomena can be validated accurately. Our work thus may shed new light into understanding control of empirical epidemic control.

Global analysis of an epidemic model with vaccination.

In this paper, an epidemic dynamical model with vaccination is proposed. Vaccination of both newborn and susceptible is included in the present model. The impact of the vaccination strategy with the vaccine efficacy is explored. In particular, the model exhibits backward bifurcations under the vaccination level, and bistability occurrence can be observed. Mathematically, a bifurcation analysis is performed, and the conditions ensuring that the system exhibits backward bifurcation are provided. The global dynamics of the equilibrium in the model are also investigated. Numerical simulations are also conducted to confirm and extend the analytic results.

Differential distribution patterns of ammonia-oxidizing archaea and bacteria in acidic soils of Nanling National Nature Reserve forests in subtropical China.

In addition to ammonia-oxidizing bacteria (AOB) the more recently discovered ammonia-oxidizing archaea (AOA) can also oxidize ammonia, but little is known about AOA community structure and abundance in subtropical forest soils. In this study, both AOA and AOB were investigated with molecular techniques in eight types of forests at surface soils (0-2 cm) and deep layers (18-20 cm) in Nanling National Nature Reserve in subtropical China. The results showed that the forest soils, all acidic (pH 4.24-5.10), harbored a wide range of AOA phylotypes, including the genera Nitrosotalea, Nitrososphaera, and another 6 clusters, one of which was reported for the first time. For AOB, only members of Nitrosospira were retrieved. Moreover, the abundance of the ammonia monooxygenase gene (amoA) from AOA dominated over AOB in most soil samples (13/16). Soil depth, rather than forest type, was an important factor shaping the community structure of AOA and AOB. The distribution patterns of AOA and AOB in soil layers were reversed: AOA diversity and abundances in the deep layers were higher than those in the surface layers; on the contrary, AOB diversity and abundances in the deep layers were lower than those in the surface layers. Interestingly, the diversity of AOA was positively correlated with pH, but negatively correlated with organic carbon, total nitrogen and total phosphorus, and the abundance of AOA was negatively correlated with available phosphorus. Our results demonstrated that AOA and AOB were differentially distributed in acidic soils in subtropical forests and affected differently by soil characteristics.

Thyroid dysfunction and Alzheimer's disease, a vicious circle.

Recently, research into the link between thyroid dysfunction and Alzheimer's disease (AD) remains a current topic of interest. Previous research has primarily concentrated on examining the impact of thyroid dysfunction on the risk of developing AD, or solely explored the mechanisms of interaction between hypothyroidism and AD, a comprehensive analysis of the mechanisms linking thyroid dysfunction, including hyperthyroidism and hypothyroidism, to Alzheimer's disease (AD) still require further elucidation. Therefore, the aim of this review is to offer a thorough and comprehensive explanation of the potential mechanisms underlying the causal relationship between thyroid dysfunction and AD, highlighting the existence of a vicious circle. The effect of thyroid dysfunction on AD includes neuron death, impaired synaptic plasticity and memory, misfolded protein deposition, oxidative stress, and diffuse and global neurochemical disturbances. Conversely, AD can also contribute to thyroid dysfunction by affecting the stress repair response and disrupting pathways involved in thyroid hormone (TH) production, transport, and activation. Furthermore, this review briefly discusses the role and significance of utilizing the thyroid as a therapeutic target for cognitive recovery in AD. By exploring potential mechanisms and therapeutic avenues, this research contributes to our understanding and management of this devastating neurodegenerative disease.

Effect of mitotane in patients with ectopic adrenocorticotropic hormone syndrome caused by advanced pancreatic neuroendocrine tumors: a case series and review of the literature.

Ectopic adrenocorticotropic hormone syndrome (EAS) is a rare condition caused by pancreatic neuroendocrine tumors (p-NETs). The severe hypercortisolemia that characterizes EAS is associated with a poor prognosis and survival. Mitotane is the only adrenolytic drug approved by the Food and Drug Administration and is often used to treat adrenocortical carcinoma. Combination therapy with mitotane and other adrenal steroidogenesis inhibitors is common for patients with Cushing's syndrome (CS). Here, we describe three patients who developed EAS secondary to the liver metastasis of p-NETs. All three rapidly developed hypercortisolemia but no typical features of CS. They underwent anti-tumor and mitotane therapy, which rapidly reduced their blood cortisol concentrations and ameliorated their symptoms. Their hypercortisolemia was controlled long term using a low dose of mitotane. The principal adverse effects were a slight loss of appetite and occasional dizziness, and there were no severe adverse effects. Importantly, even when the tumor progressed, the patients' circulating cortisol concentrations remained within the normal range. In summary, the present case series suggests that mitotane could be used to treat hypercortisolemia in patients with EAS caused by advanced p-NETs, in the absence of significant adverse effects.

Cardiovascular disease risk in early-onset vs late-onset type 2 diabetes in China: A population-based cross-sectional study.

BACKGROUND: This study investigated the effects of early-onset type 2 diabetes (EOD) vs late-onset type 2 diabetes (LOD) on nonfatal cardiovascular diseases (CVD) in China. METHODS: We conducted a cross-sectional survey of 46 239 participants from 14 provinces in China from 2007 to 2008, selecting 4949 participants with type 2 diabetes for analysis. Participants were categorized as EOD (<40 years) or LOD (≥40 years) based on age at diabetes diagnosis. Sociodemographic and nonfatal CVD information was collected through an interviewer-assisted questionnaire and clinical examination. Logistic regression analysis was used to investigate the nonfatal CVD risk. RESULTS: Out of 4949 participants with type 2 diabetes, 390 (7.88%) had nonfatal CVD. Participants with EOD had a higher age-standardized prevalence of nonfatal CVD than those with LOD (11.4% vs 4.4%). Compared to LOD patients, EOD patients tended to be males and had a higher family history of diabetes, unhealthy lifestyle behaviors, and lower blood pressure levels. After adjustment for age and sex, EOD patients had a higher risk of nonfatal CVD than LOD patients (odds ratio [OR] 2.3, 95% CI 1.5-3.5). After further adjustment for diabetes duration, use of drugs, and other risk factors, the OR of nonfatal CVD was reduced but significant (OR 1.8, 95% CI 1.1-2.9). Sensitivity analysis revealed that EOD patients with metabolic syndrome had an increased nonfatal CVD risk compared to LOD patients (OR 2.0, 95% CI 1.2-3.5). CONCLUSIONS: EOD patients are at increased risk of nonfatal CVD. Individualized intervention and management measures for EOD patients are necessary.

Analysis and Validation of Critical Signatures and Immune Cell Infiltration Characteristics in Doxorubicin-Induced Cardiotoxicity by Integrating Bioinformatics and Machine Learning.

Purpose: Doxorubicin-induced cardiotoxicity (DIC) is a severe side reaction in cancer chemotherapy that greatly impacts the well-being of cancer patients. Currently, there is still an insufficiency of effective and reliable biomarkers in the field of clinical practice for the early detection of DIC. This study aimed to determine and validate the potential diagnostic and predictive values of critical signatures in DIC. Methods: We obtained high-throughput sequencing data from the GEO database and performed data analysis and visualization using R software, GO, KEGG and Cytoscape. Machine learning methods and weighted gene coexpression network (WGCNA) were used to identify key genes for diagnostic model construction. Receiver operating characteristic (ROC) analysis and a nomogram were used to assess their diagnostic values. A multiregulatory network was built to reveal the possible regulatory relationships of critical signatures. Cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) analysis was used to investigate differential immune cell infiltration. Additionally, a cell and animal model were constructed to investigate the relationship between the identified genes and DIC. Results: Among the 3713 differentially expressed genes, three key genes (CSGALNACT1, ZNF296 and FANCB) were identified. A nomogram and ROC curves based on three key genes showed excellent diagnostic predictive performance. The regulatory network analysis showed that the TFs CREB1, EP300, FLI1, FOXA1, MAX, and MAZ modulated three key genes. An analysis of immune cell infiltration indicated that many immune cells (activated NK cells, M0 macrophages, activated dendritic cells and neutrophils) might be related to the progression of DIC. Furthermore, there may be various degrees of correlation between the three critical signatures and immune cells. RT‒qPCR demonstrated that the mRNA expression of CSGALNACT1 and ZNF296 was significantly upregulated, while FANCB was significantly downregulated in DOX-treated cardiomyocytes in vitro and in vivo. Conclusion: Our study suggested that the differential expression of CSGALNACT1, ZNF296 and FANCB is associated with cardiotoxicity and is also involved in immune cell infiltration in DIC. They might be potential biomarkers for the early occurrence of DIC.