Every year cervical cancer affects more than 300,000 people, and on average one woman is diagnosed with cervical cancer every minute. Early diagnosis and classification of cervical lesions greatly ...boosts up the chance of successful treatments of patients, and automated diagnosis and classification of cervical lesions from Papanicolaou (Pap) smear images have become highly demanded. To the authors' best knowledge, this is the first study of fully automated cervical lesions analysis on whole slide images (WSIs) of conventional Pap smear samples. The presented deep learning-based cervical lesions diagnosis system is demonstrated to be able to detect high grade squamous intraepithelial lesions (HSILs) or higher (squamous cell carcinoma; SQCC), which usually immediately indicate patients must be referred to colposcopy, but also to rapidly process WSIs in seconds for practical clinical usage. We evaluate this framework at scale on a dataset of 143 whole slide images, and the proposed method achieves a high precision 0.93, recall 0.90, F-measure 0.88, and Jaccard index 0.84, showing that the proposed system is capable of segmenting HSILs or higher (SQCC) with high precision and reaches sensitivity comparable to the referenced standard produced by pathologists. Based on Fisher's Least Significant Difference (LSD) test (P < 0.0001), the proposed method performs significantly better than the two state-of-the-art benchmark methods (U-Net and SegNet) in precision, F-Measure, Jaccard index. For the run time analysis, the proposed method takes only 210 seconds to process a WSI and is 20 times faster than U-Net and 19 times faster than SegNet, respectively. In summary, the proposed method is demonstrated to be able to both detect HSILs or higher (SQCC), which indicate patients for further treatments, including colposcopy and surgery to remove the lesion, and rapidly processing WSIs in seconds for practical clinical usages.
Cancer stem cells (CSCs) are critical for cancer progression and chemoresistance. How lipid metabolism regulates CSCs and chemoresistance remains elusive. Here, we demonstrate that JAK/STAT3 ...regulates lipid metabolism, which promotes breast CSCs (BCSCs) and cancer chemoresistance. Inhibiting JAK/STAT3 blocks BCSC self-renewal and expression of diverse lipid metabolic genes, including carnitine palmitoyltransferase 1B (CPT1B), which encodes the critical enzyme for fatty acid β-oxidation (FAO). Moreover, mammary-adipocyte-derived leptin upregulates STAT3-induced CPT1B expression and FAO activity in BCSCs. Human breast-cancer-derived data suggest that the STAT3-CPT1B-FAO pathway promotes cancer cell stemness and chemoresistance. Blocking FAO and/or leptin re-sensitizes them to chemotherapy and inhibits BCSCs in mouse breast tumors in vivo. We identify a critical pathway for BCSC maintenance and breast cancer chemoresistance.
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•Inhibition of FAO preferentially eliminates BCSCs•JAK/STAT3 activates FAO through transcription of CPT1B•Adipocyte-derived leptin is critical for JAK/STAT3-FAO in BCSCs•Targeting FAO/leptin inhibits BCSCs, chemoresistance, and breast tumor growth
Cancer stem cells play an important role in cancer development and chemoresistance. Wang et al. show that leptin-JAK/STAT3 regulates lipid metabolism through fatty acid β-oxidation (FAO), promoting breast cancer stemness and chemoresistance. Blocking FAO and/or depleting leptin re-sensitize cancer cells to chemotherapy while reducing cancer stemness in vivo.
Abstract
Stroke and cognitive impairment are common in older population. They often occur together and their combined effects significantly increase disability in both basic (BADLs) and instrumental ...(IADLs) activities of daily living. We investigated the individual and combined impacts of stroke and cognitive impairment on BADLs and IADLs. A total of 3331 community-dwelling older adults were enrolled from the Taiwan longitudinal study on aging in 2011. Both BADLs and IADLs were analyzed. Combination of stroke and cognitive impairment increased severity of ADL disabilities, but similar prevalence, similar numbers of summed BADL and IADL tasks with disability, and similar levels of difficulty for each BADL and IADL task were found between the stroke group and cognitive impairment group. The former had more difficult in dressing while the latter had more difficult in using the telephone, transport, and managing finances. A hierarchy of ADLs was also observed in all groups. ADL skill training supplemented with cognitive and physical interventions should focus on secondary prevention of dementia and improve motor functional capacity to reduce loss of ADLs.
Solder/Cu joints are important components responsible for interconnection in microelectronics. Construction of the solder/Cu joints through liquid/solid (L/S) reactions accompanies the formation of ...the Cu–Sn intermetallic compounds (IMCs) at the joint interface. The Cu6Sn5 IMC exhibits remarkable distinctions in thickness and morphology upon increasing the L/S reaction time. Effects of the initial characteristics of thickness and morphology on the growth kinetics of Cu6Sn5 during subsequent isothermal aging were investigated. SAC305 solder was reflowed on a Cu electroplated layer at 265 °C for 1 to 60 min to produce the Cu6Sn5 IMC with different thickness and morphology at the SAC305/Cu interface. The as-fabricated SAC305/Cu joint samples were aged at 200 °C for 72 to 360 h to investigate the growth kinetics of Cu6Sn5. The results show that the initial characteristics of thickness and morphology significantly influenced the growth kinetics of Cu6Sn5 during the subsequent solid/solid (S/S) reaction. A prolonged L/S reaction time of 60 min (L/S-60) produced a scallop-type Cu6Sn5 IMC with a larger grain size and a thicker thickness, which reduced the quantity of fast diffusion path (grain boundary) and the magnitude of concentration gradient, thus slowing down the growth rate of Cu6Sn5. According to the growth kinetics analysis, the growth rate constant of Cu6Sn5 could be remarkably reduced to 0.151 µm/h0.5 for the L/S-60 sample, representing a significant reduction of 70 % compared to that of the L/S-1 sample (0.508 µm/h0.5 for L/S reaction time of 1 min).
Thyroid cancer is the most common endocrine cancer. Papillary thyroid cancer (PTC) is the most prevalent form of malignancy among all thyroid cancers arising from follicular cells. Fine needle ...aspiration cytology (FNAC) is a non-invasive method regarded as the most cost-effective and accurate diagnostic method of choice in diagnosing PTC. Identification of BRAF (V600E) mutation in thyroid neoplasia may be beneficial because it is specific for malignancy, implies a worse prognosis, and is the target for selective BRAF inhibitors. To the authors' best knowledge, this is the first automated precision oncology framework effectively predict BRAF (V600E) immunostaining result in thyroidectomy specimen directly from Papanicolaou-stained thyroid fine-needle aspiration cytology and ThinPrep cytological slides, which is helpful for novel targeted therapies and prognosis prediction. The proposed deep learning (DL) framework is evaluated on a dataset of 118 whole slide images. The results show that the proposed DL-based technique achieves an accuracy of 87%, a precision of 94%, a sensitivity of 91%, a specificity of 71% and a mean of sensitivity and specificity at 81% and outperformed three state-of-the-art deep learning approaches. This study demonstrates the feasibility of DL-based prediction of critical molecular features in cytological slides, which not only aid in accurate diagnosis but also provide useful information in guiding clinical decision-making in patients with thyroid cancer. With the accumulation of data and the continuous advancement of technology, the performance of DL systems is expected to be improved in the near future. Therefore, we expect that DL can provide a cost-effective and time-effective alternative tool for patients in the era of precision oncology.
Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion ...conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular and blood-flow perfusion conditions among 3 groups (44 male volunteers) according to the time taken to run 3 km: Level 1, Level 2, and Level 3.
The radial blood pressure waveform (BPW), finger photoplethygraphy (PPG), and skin-surface laser-Doppler flowmetry (LDF) signals of the subjects were measured. Frequency-domain analysis was applied to BPW and PPG signals; time- and frequency-domain analyses were applied to LDF signals.
Pulse waveform and LDF indices differed significantly among the three groups. These could be used to evaluate the advantageous cardiovascular effects provided by long-term endurance-running training, such as vessel relaxation (pulse waveform indices), improvement in blood supply perfusion (LDF indices), and changes in cardiovascular regulation activities (pulse and LDF variability indices). Using the relative changes in pulse-effect indices, we achieved almost perfect discrimination between Level 3 and Level 2 (AUC = 0.878). Furthermore, the present pulse waveform analysis could also be used to discriminate between the Level-1 and Level-2 groups.
The present findings contribute to the development of a noninvasive, easy-to-use, and objective evaluation technique for the cardiovascular benefits of prolonged endurance-running training.
Electric cell-substrate impedance sensing (ECIS) is an emerging technique for sensitively monitoring morphological changes of adherent cells in tissue culture. In this study, human mesenchymal stem ...cells (hMSCs) were exposed to different concentrations of carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) for 20 h and their subsequent concentration-dependent responses in micromotion and wound healing migration were measured by ECIS. FCCP disrupts ATP synthesis and results in a decrease in cell migration rates. To detect the change of cell micromotion in response to FCCP challenge, time-series resistances of cell-covered electrodes were monitored and the values of variance were calculated to verify the difference. While Seahorse XF-24 extracellular flux analyzer can detect the effect of FCCP at 3 μM concentration, the variance calculation of the time-series resistances measured at 4 kHz can detect the effect of FCCP at concentrations as low as 1 μM. For wound healing migration, the recovery resistance curves were fitted by sigmoid curve and the hill slope showed a concentration-dependent decline from 0.3 μM to 3 μM, indicating a decrease in cell migration rate. Moreover, dose dependent incline of the inflection points from 0.3 μM to 3 μM FCCP implied the increase of the half time for wound recovery migration. Together, our results demonstrate that partial uncoupling of mitochondrial oxidative phosphorylation reduces micromotion and wound healing migration of hMSCs. The ECIS method used in this study offers a simple and sensitive approach to investigate stem cell migration and its regulation by mitochondrial dynamics.
Learning a sports skill is a complex process in which practitioners are challenged to cater for individual differences. The main purpose of this study was to explore the effectiveness of a Nonlinear ...Pedagogy approach for learning a sports skill. Twenty-four 10-year-old females participated in a 4-week intervention involving either a Nonlinear Pedagogy (i.e.,manipulation of task constraints including equipment and rules) or a Linear Pedagogy (i.e., prescriptive, repetitive drills) approach to learn a tennis forehand stroke. Performance accuracy scores, movement criterion scores and kinematic data were measured during pre-intervention, post-intervention and retention tests. While both groups showed improvements in performance accuracy scores over time, the Nonlinear Pedagogy group displayed a greater number of movement clusters at post-test indicating the presence of degeneracy (i.e., many ways to achieve the same outcome). The results suggest that degeneracy is effective for learning a sports skill facilitated by a Nonlinear Pedagogy approach. These findings challenge the common misconception that there must be only one ideal movement solution for a task and thus have implications for coaches and educators when designing instructions for skill acquisition.
Thyroid cancer is the most common cancer in the endocrine system, and papillary thyroid carcinoma (PTC) is the most prevalent type of thyroid cancer, accounting for 70 to 80% of all thyroid cancer ...cases. In clinical practice, visual inspection of cytopathological slides is an essential initial method used by the pathologist to diagnose PTC. Manual visual assessment of the whole slide images is difficult, time consuming, and subjective, with a high inter-observer variability, which can sometimes lead to suboptimal patient management due to false-positive and false-negative. In this study, we present a fully automatic, efficient, and fast deep learning framework for fast screening of papanicolaou-stained thyroid fine needle aspiration (FNA) and ThinPrep (TP) cytological slides. To the authors’ best of knowledge, this work is the first study to build an automated deep learning framework for identification of PTC from both FNA and TP slides. The proposed deep learning framework is evaluated on a dataset of 131 WSIs, and the results show that the proposed method achieves an accuracy of 99%, precision of 85%, recall of 94% and F1-score of 87% in segmentation of PTC in FNA slides and an accuracy of 99%, precision of 97%, recall of 98%, F1-score of 98%, and Jaccard-Index of 96% in TP slides. In addition, the proposed method significantly outperforms the two state-of-the-art deep learning methods, i.e., U-Net and SegNet, in terms of accuracy, recall, F1-score, and Jaccard-Index (p<0.001). Furthermore, for run-time analysis, the proposed fast screening method takes 0.4 min to process a WSI and is 7.8 times faster than U-Net and 9.1 times faster than SegNet, respectively.
Induced pluripotent stem cells (iPSCs) generated from somatic cells of patients can be used to model different human diseases. They may also serve as sources of transplantable cells that can be used ...in novel cell therapies. Here, we analyzed neuronal properties of an iPSC line derived from a patient with a juvenile form of Huntington's disease (HD) carrying 72 CAG repeats (HD-iPSC). Although its initial neural inducing activity was lower than that of human embryonic stem cells, we found that HD-iPSC can give rise to GABAergic striatal neurons, the neuronal cell type that is most susceptible to degeneration in HD. We then transplanted HD-iPSC-derived neural precursors into a rat model of HD with a unilateral excitotoxic striatal lesion and observed a significant behavioral recovery in the grafted rats. Interestingly, during our in vitro culture and when the grafts were examined at 12 weeks after transplantation, no aggregate formation was detected. However, when the culture was treated with a proteasome inhibitor (MG132) or when the cells engrafted into neonatal brains were analyzed at 33 weeks, there were clear signs of HD pathology. Taken together, these results indicate that, although HD-iPSC carrying 72 CAG repeats can form GABAergic neurons and give rise to functional effects in vivo, without showing an overt HD phenotype, it is highly susceptible to proteasome inhibition and develops HD pathology at later stages of transplantation. These unique features of HD-iPSC will serve as useful tools to study HD pathology and develop novel therapeutics.
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