Search

AbstractClustering is a widely used unsupervised learning technique that groups data into homogeneous clusters. However, when dealing with real-world data that contain categorical values, existing algorithms can be computationally costly in high dimensions and can struggle with noisy data that has missing values. Furthermore, except for one algorithm, no others provide theoretical guarantees of clustering accuracy. In this article, we propose a general categorical data encoding method and a computationally efficient spectral-based algorithm to cluster high-dimensional noisy categorical data (nominal or ordinal). Under a statistical model for data on m attributes from n subjects in r clusters with missing probability ϵ, we show that our algorithm exactly recovers the true clusters with high probability when mn(1−ϵ)≥CMr2 log 3M, with M=max(n,m) and a fixed constant C. In addition, we show that mn(1−ϵ)2≥rδ/2 with 0<δ<1 is necessary for any algorithm to succeed with probability at least (1+δ)/2. In cases where m = n and r are fixed, the sufficient condition matches with the necessary condition up to a polylog(n) factor. In numerical studies our algorithm outperforms several existing algorithms in both clustering accuracy and computational efficiency. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

There are different approaches for studying linear models (and multivariate statistical analysis in general); for example, decision analytic approach, algebraic approach, and geometric approach. Quite a few books on linear [...]

BackgroundStroke has profound impacts on families. Often, family members, including stroke survivors and the person who takes up the role of the primary caregiver, would encounter demands on finances, rehabilitation arrangement, and even conflicts. Hence, a family-oriented intervention is expected to enable families to rebuild internal and external resources to achieve optimal rehabilitation and community reintegration. ObjectiveThis study aims to describe a design of a two-tier family-oriented care management intervention for enhancing the family functioning and care capacity of the caregivers of stroke survivors. MethodsThe two-tier care management intervention was guided by a standardized protocol conducted by trained professional care managers (first tier) with the support of trained volunteers (second tier), which lasted for 8-12 weeks. Participants were recruited through collaborating hospitals according to inclusion and exclusion criteria. In order to examine the effectiveness and cost-effectiveness of the two-tier care management intervention, a two-arm randomization multicenter study was designed, including an active comparison group, which was guided by a standardized protocol conducted by trained volunteers. Dyadic participants, including both stroke survivors and their primary caregivers for both groups, were invited to participate in a questionnaire survey using standardized and purposefully developed measures 3 times: before the intervention, immediately after the intervention, and 2 months after the intervention. The primary outcome was family functioning measured by the Family Role Performance Scale and Family Assessment Device-General Functioning Scale. The secondary outcomes included caregiving burden, depressive symptoms, care management strategies, and the incremental cost-effectiveness ratio. ResultsRecruitment began in January 2017 and was completed at the end of April 2019. Data collection was completed at the end of March 2020. As of March 2020, enrollment has been completed (n=264 stroke caregivers). A total of 200 participants completed the baseline questionnaires. We aim to publish the results by mid-2021. ConclusionsThis study successfully developed a two-tier care management protocol that aims to enhance the family functioning of the caregivers of stroke survivors. Guided by a standardized protocol, this family-oriented two-tier intervention protocol was found to be feasible among Chinese families. Trial RegistrationClinicalTrials.gov NCT03034330; https://ichgcp.net/clinical-trials-registry/NCT03034330 International Registered Report Identifier (IRRID)RR1-10.2196/16703

Accelerated Life Testing (ALT) is used to provide timely estimates of a product's lifetime distribution. Step-Stress ALT (SSALT) is one of the most widely adopted stress loadings and the optimum design of a SSALT plan has been extensively studied. However, few research efforts have been devoted to establishing the theoretical rationale for using SSALT in lieu of other types of stress loadings. This article proves the existence of statistically equivalent SSALT plans that can provide equally precise estimates to those derived from any continuous stress loading for the log-location-scale lifetime distributions with Type-I censoring. That is, for any optimization criterion based on the Fisher information matrix, SSALT is identical in comparison to other continuous stress loadings. The Weibull and lognormal distributions are introduced as special cases. For these two distributions, the relationship among statistical equivalencies is investigated and it is shown that two equivalent ALT plans must be equivalent in terms of the strongest version of equivalency for many objective functions. A numerical example for a ramp-stress ALT, using data from an existing study on miniature lamps, is used to illustrate equivalent SSALT plans. Results show that SSALT is not only equivalent to the existing ramp-stress test plans but also more cost-effective in terms of the total test cost. [ABSTRACT FROM AUTHOR]

Physalis plants are commonly used traditional medicinal herbs, and most of their extracts containing withanolides show anticancer effects. Physapruin A (PHA), a withanolide isolated from P. peruviana, shows antiproliferative effects on breast cancer cells involving oxidative stress, apoptosis, and autophagy. However, the other oxidative stress-associated response, such as endoplasmic reticulum (ER) stress, and its participation in regulating apoptosis in PHA-treated breast cancer cells remain unclear. This study aims to explore the function of oxidative stress and ER stress in modulating the proliferation and apoptosis of breast cancer cells treated with PHA. PHA induced a more significant ER expansion and aggresome formation of breast cancer cells (MCF7 and MDA-MB-231). The mRNA and protein levels of ER stress-responsive genes (IRE1α and BIP) were upregulated by PHA in breast cancer cells. The co-treatment of PHA with the ER stress-inducer (thapsigargin, TG), i.e., TG/PHA, demonstrated synergistic antiproliferation, reactive oxygen species generation, subG1 accumulation, and apoptosis (annexin V and caspases 3/8 activation) as examined by ATP assay, flow cytometry, and western blotting. These ER stress responses, their associated antiproliferation, and apoptosis changes were partly alleviated by the N-acetylcysteine, an oxidative stress inhibitor. Taken together, PHA exhibits ER stress-inducing function to promote antiproliferation and apoptosis of breast cancer cells involving oxidative stress. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is insensitive to target therapy for non-TNBC and needs novel drug discovery. Extracts of the traditional herb Boesenbergia plant in Southern Asia exhibit anticancer effects and contain novel bioactive compounds but merely show cytotoxicity. We recently isolated a new compound from B. stenophylla, stenophyllol B (StenB), but the impact and mechanism of its proliferation-modulating function on TNBC cells remain uninvestigated. This study aimed to assess the antiproliferative responses of StenB in TNBC cells and examine the drug safety in normal cells. StenB effectively suppressed the proliferation of TNBC cells rather than normal cells in terms of an ATP assay. This preferential antiproliferative function was alleviated by pretreating inhibitors for oxidative stress (N-acetylcysteine (NAC)) and apoptosis (Z-VAD-FMK). Accordingly, the oxidative-stress-related mechanisms were further assessed. StenB caused subG1 and G2/M accumulation but reduced the G1 phase in TNBC cells, while normal cells remained unchanged between the control and StenB treatments. The apoptosis behavior of TNBC cells was suppressed by StenB, whereas that of normal cells was not suppressed according to an annexin V assay. StenB-modulated apoptosis signaling, such as for caspases 3, 8, and 9, was more significantly activated in TNBC than in normal cells. StenB also caused oxidative stress in TNBC cells but not in normal cells according to a flow cytometry assay monitoring reactive oxygen species, mitochondrial superoxide, and their membrane potential. StenB induced greater DNA damage responses (γH2AX and 8-hydroxy-2-deoxyguanosine) in TNBC than in normal cells. All these StenB responses were alleviated by NAC pretreatment. Collectively, StenB modulated oxidative stress responses, leading to the antiproliferation of TNBC cells with little cytotoxicity in normal cells. [ABSTRACT FROM AUTHOR]