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Down syndrome (DS) induces a variable phenotype including intellectual disabilities and early development of Alzheimer's disease (AD). Moreover, individuals with DS display accelerated aging that affects diverse organs, among them the brain. The Ts65Dn mouse is the most widely used model to study DS. Progressive loss of cholinergic neurons is one of the hallmarks of AD present in DS and in the Ts65Dn model. In this study, we quantify the number of cholinergic neurons in control and Ts65Dn mice, observing a general reduction in their number with age but in particular, a greater loss in old Ts65Dn mice. Increased expression of the m1 muscarinic receptor in the hippocampus counteracts this loss. Cholinergic neurons in the Ts65Dn mice display overexpression of the early expression gene c-fos and an increase in the expression of β-galactosidase, a marker of senescence. A possible mechanism for senescence induction could be phosphorylation of the transcription factor FOXO1 and its retention in the cytoplasm, which we are able to confirm in the Ts65Dn model. In our study, using Ts65Dn mice, we observe increased cholinergic activity, which induces a process of early senescence that culminates in the loss of these neurons.

Women exposed to diethylstilbestrol (DES) in utero were at elevated risk of clear-cell adenocarcinoma of the vagina and cervix (CCA) as young women. Previous research suggested that this elevated risk of CCA may persist into adulthood. We extended a published analysis to measure CCA risk as these women aged.

Standardized incidence ratios (SIR) compared CCA risk among women born from 1947 through 1971 (the DES-era) to CCA risk among the comparison group of women born prior to 1947, using registry data that covered the US population.

Incidence rates of CCA among both cohorts increased with age. Among the DES-era birth cohort, higher rates of CCA were observed across all age groups except 55-59years. SIR estimates had wide confidence intervals that often included the null value.

Results are consistent with prior research and suggest an elevated risk of CCA in midlife and at older ages among women exposed in utero to DES. These results highlight unresolved issues regarding cancer risk among aging DES daughters and appropriate screening guidance. The examination of population-based cancer surveillance data may be a useful tool for monitoring trends in the incidence of other rare cancers over time among specific birth cohorts.

Results are consistent with prior research and suggest an elevated risk of CCA in midlife and at older ages among women exposed in utero to DES. These results highlight unresolved issues regarding cancer risk among aging DES daughters and appropriate screening guidance. The examination of population-based cancer surveillance data may be a useful tool for monitoring trends in the incidence of other rare cancers over time among specific birth cohorts.

The robot-assisted automated puncture system under ultrasound guidance can well improve the puncture accuracy in ablation surgery. The automated puncture system requires advanced definition of the puncture location, while the displacement of thoracic-abdominal tumors caused by respiratory motion makes it difficult for the system to locate the best puncture position. Predicting tumor motion is an effective way to help the automated puncture system output a more accurate puncture position.

In this paper, we propose a self-attention-based feature pyramid algorithm FPSANet for time-series forecasting, which can extract both linear and nonlinear dependencies of time series. Firstly, we use the temporal convolutional network as the backbone to extract different scale time-series features, and the self-attention module is followed to weigh more significant features to improve nonlinear prediction. Secondly, we use autoregressive models to perform linear prediction. Finally, we directly combine the above two kinds having less distinct periodic patterns. Under these conditions, our algorithm has the advantage of excellent stability for prediction on various sequences, and its running time of performing single sequence prediction can meet clinical requirements.Reduced bone mineral density, and muscle strength are the hallmark of aging-related motor coordination deficits and related neuropathologies. Since cerebellum regulates motor movements and balance perception of our body, therefore it may be an important target to control the age-related progression of motor dysfunctions. Dry stem powder of Tinospora cordifolia (TCP) was tested as a food supplement to elucidate its activity to attenuate age-associated locomotor dysfunctions. Intact acyclic middle-aged female rats were used in this study as the model system of the transition phase from premenopause to menopause in women along with cycling young adult rats. Normal chow or 30% High Fat Diet (HFD), supplemented with or without TCP was fed to animals for 12 weeks and then tested for locomotor performance on rotarod followed by post-sacrifice protein expression studies. In comparison to young adults, middle-aged animals showed an increase in number of falls and lesser time spent in rotarod performance test, whereas, animals given TCP supplemented feed showed improvement in performance with more pronounced effects observed in normal chow than HFD fed middle-aged rats. Further, due to its multicomponent nature TCP was found to target the expression of various markers of neuroinflammation, apoptosis, cell survival, and synaptic plasticity in the cerebellum region. The current findings suggest that TCP supplementation in the diet may prove to be a potential interventional strategy for the management of frailty and fall-associated morbidities caused by aging-related deterioration of bone mineral density, and muscle strength.Low temperature inhibits photosynthesis and negatively affects plant growth. Cucumber (Cucumis sativus L.) is a chilling-sensitive plant, and its greenhouse production requires considerable energy during the winter. Therefore, a useful stress marker for selecting chilling-tolerant cucumber cultivars is desirable. In this study, we evaluated chilling-stress damage in different cucumber cultivars by measuring photosynthetic parameters. The majority of cultivars showed decreases in the quantum yield of photosystem (PS) II [Fv/Fm and Y(II)] and the quantity of active PS I (Pm) after chilling stress. In contrast, Y(ND)-the ratio of the oxidized state of PSI reaction center chlorophyll P700 (P700+)-differed among cultivars and was perfectly inversely correlated with Y(NA)-the ratio of the non-photooxidizable P700. It has been known that P700+ accumulates under stress conditions and protects plants to suppress the generation of reactive oxygen species. In fact, cultivars unable to induce Y(ND) after chilling stress showed growth retardation with reductions in chlorophyll content and leaf area. Therefore, Y(ND) can be a useful marker to evaluate chilling-stress tolerance in cucumber.Quantitative structure-activity relationship (QSAR) and read-across techniques have recently been merged into a new emerging field of read-across structure-activity relationship (RASAR) that uses the chemical similarity concepts of read-across (an unsupervised step) and finally develops a supervised learning model (like QSAR). The RASAR method has so far been used only in case of graded predictions or classification modeling. In this work, we attempt, for the first time, to apply RASAR for quantitative predictions (q-RASAR) using a case study of androgen receptor binding affinity data. We have computed a number of error-based and similarity-based measures such as weighted standard deviation of the predicted values, coefficient of variation of the computed predictions, average similarity level of close training compounds for each query molecule, standard deviation and coefficient of variation of similarity levels, maximum similarity levels to positive and negative close training compounds, a concordance measure indicating similarity to positive, negative or both classes of close training compounds, etc. We have clubbed these additional measures along with the selected chemical descriptors from the previously developed QSAR model and redeveloped new partial least squares models from the training set, and predicted the endpoint using the query data set. Interestingly, these new models outperform the internal and external validation quality of the original QSAR model. In this study, we have also introduced a new similarity-based concordance measure (Banerjee-Roy coefficient) that can significantly contribute to the model quality. A q-RASAR model also has the advantage over read-across predictions in providing easy interpretation and indicating quantitative contributions of important chemical features. The strategy described here should be applicable to other biological/toxicological/property data modeling for enhanced quality of predictions, easy interpretability, and efficient transferability.3D-QSAR models were established by collecting 46 multivariate-substituted 4-oxyquinazoline HDAC6 inhibitors. The relationship of molecular structure and inhibitory activity was studied by comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). The results showed the models established by CoMFA (q2 = 0.590, r2 = 0.965) and CoMSIA (q2 = 0.594, r2 = 0.931) had good prediction ability. At the same time, 3D-QSAR models met the internal verification, external verification and AD test. Ten new compounds were designed based on CoMFA and CoMSIA contour maps and their pharmacokinetic/toxic properties (ADME/T) were evaluated. It was found that most compounds have well safety profile and pharmacokinetic property. Then, we explored the interaction between HDAC6 and compounds by molecular docking. The results showed that the binding mode of the new compounds with HDAC6 was the same as the template compound 46, and the hydrogen bond and hydrophobic bond played a vital role in the binding process. Molecular dynamics simulation results showed that residues Ser531, His574 and Tyr745 played key roles in the binding process. All newly designed compounds had lower energy gap and binding energy than compound 46 according to DFT analysis and free energy analysis. selleck This study provided a theoretical reference for designing compounds of higher activity and a new idea for the development of novel HDAC6 inhibitors.

The purpose of this study was to identify oncologist-reported barriers and motivators in addressing long-term effects with breast cancer survivors.

This study is a secondary analysis of data from a survey of U.S. medical oncologists (n = 217) about breast cancer survivorship care in clinical practice. Using both closed- and open-ended questions, we asked oncologists to report barriers and motivators they perceived in addressing long-term effects with breast cancer patients. Descriptive statistics were used to summarize and rank items endorsed by oncologists in analyses of quantitative data; content analysis was used to identify salient categories of barriers and motivators in qualitative data.

Key barriers to managing physical long-term effects included lack of time during appointments (n = 128 oncologists, 59%) and perceived lack of evidence-based interventions (n = 89, 41%). With respect to psychosocial effects, oncologists reported lack of knowledge (n = 88, 40.6%) and challenges making referrals to mental health providers (n = 115, 53%).