Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Executive Function Influence Walking in Acutely Hospitalized Patients With Advanced Parkinson's Disease: A Quantitative Analysis

Introduction It is well-known that, in Parkinson's disease (PD), executive function (EF) and motor deficits lead to reduced walking performance. As previous studies investigated mainly patients during the compensated phases of the disease, the aim of this study was to investigate the above associations in acutely hospitalized patients with PD. Methods A total of seventy-four acutely hospitalized patients with PD were assessed with the delta Trail Making Test (ΔTMT, TMT-B minus TMT-A) and the Movement Disorder Society-revised version of the motor part of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS III). Walking performance was assessed with wearable sensors under single (ST; fast and normal pace) and dual-task (DT; walking and checking boxes as the motor secondary task and walking and subtracting seven consecutively from a given three-digit number as the cognitive secondary task) conditions over 20 m. Multiple linear regression and Bayes factor BF10 were performed for each walking parameter and their dual-task costs while walking (DTC) as dependent variables and also included ΔTMT, MDS-UPDRS III, age, and gender. Results Under ST, significant negative effects of the use of a walking aid and MDS-UPDRS III on gait speed and at a fast pace on the number of steps were observed. Moreover, depending on the pace, the use of a walking aid, age, and gender affected step time variability. Under walking-cognitive DT, a resolved variance of 23% was observed in the overall model for step time variability DTC, driven mainly by age (β = 0.26, p = 0.09). Under DT, no other significant effects could be observed. ΔTMT showed no significant associations with any of the walking conditions. Discussion The results of this study suggest that, in acutely hospitalized patients with PD, reduced walking performance is mainly explained by the use of a walking aid, motor symptoms, age, and gender, and EF deficits surprisingly do not seem to play a significant role. However, these patients with PD should avoid walking-cognitive DT situations, as under this condition, especially step time variability, a parameter associated with the risk of falling in PD worsens.
Islands Within Islands: Bacterial Phylogenetic Structure and Consortia in Hawaiian Lava Caves and Fumaroles

Lava caves, tubes, and fumaroles in Hawai‘i present a range of volcanic, oligotrophic environments from different lava flows and host unexpectedly high levels of bacterial diversity. These features provide an opportunity to study the ecological drivers that structure bacterial community diversity and assemblies in volcanic ecosystems and compare the older, more stable environments of lava tubes, to the more variable and extreme conditions of younger, geothermally active caves and fumaroles. Using 16S rRNA amplicon-based sequencing methods, we investigated the phylogenetic distinctness and diversity and identified microbial interactions and consortia through co-occurrence networks in 70 samples from lava tubes, geothermal lava caves, and fumaroles on the island of Hawai‘i. Our data illustrate that lava caves and geothermal sites harbor unique microbial communities, with very little overlap between caves or sites. We also found that older lava tubes (500–800 yrs old) hosted greater phylogenetic diversity (Faith's PD) than sites that were either geothermally active or younger (<400 yrs old). Geothermally active sites had a greater number of interactions and complexity than lava tubes. Average phylogenetic distinctness, a measure of the phylogenetic relatedness of a community, was higher than would be expected if communities were structured at random. This suggests that bacterial communities of Hawaiian volcanic environments are phylogenetically over-dispersed and that competitive exclusion is the main driver in structuring these communities. This was supported by network analyses that found that taxa (Class level) co-occurred with more distantly related organisms than close relatives, particularly in geothermal sites. Network “hubs” (taxa of potentially higher ecological importance) were not the most abundant taxa in either geothermal sites or lava tubes and were identified as unknown families or genera of the phyla, Chloroflexi and Acidobacteria. These results highlight the need for further study on the ecological role of microbes in caves through targeted culturing methods, metagenomics, and long-read sequence technologies.
The Role of Tumor Microenvironment and Immune Response in Colorectal Cancer Development and Prognosis

Colorectal cancer (CRC) is one of the most common cancers worldwide. The patient’s prognosis largely depends on the tumor stage at diagnosis. The pathological TNM Classification of Malignant Tumors (pTNM) staging of surgically resected cancers represents the main prognostic factor and guidance for decision-making in CRC patients. However, this approach alone is insufficient as a prognostic predictor because clinical outcomes in patients at the same histological tumor stage can still differ. Recently, significant progress in the treatment of CRC has been made due to improvements in both chemotherapy and surgical management. Immunotherapy-based approaches are one of the most rapidly developing areas of tumor therapy. This review summarizes the current knowledge about the tumor microenvironment (TME), immune response and its interactions with CRC development, immunotherapy and prognosis.
What Keeps Kids Coming Back? Retention in a Sport-Based Positive Youth Development Program

Research finds engagement in sport-based positive youth development (PYD) programs contribute to key outcomes related to physical, social, emotional, cognitive, and mental health. Consistent, long-term participation ensures youth, especially those who are socially vulnerable, reap the most benefits. Even when common barriers are removed, retention remains a challenge. Using mixed methods, this study explored factors related to long-term retention among youth from socially vulnerable circumstances attending one sport-based PYD program. Factors related to youth participation in the previous year's program, as well as general youth demographics, were examined using difference tests and binomial logistic regression to explore retention among 124 of the 384 youth who returned to the program the following year. Results of the regression analyses showed the full model (with all predictors included), vs. an intercept-only model, was statistically significant, χ2 (11, N = 235) = 23.38, p = 0.02. The model correctly classified 88.2% of the non-returners and 28.0% of the returners for an overall correct classification rate of 67.2%. Better fitness levels, higher perceived social responsibility (an outcome targeted in the program), and some demographic variables (such as lower poverty rates and younger age) were associated with a greater probability of returning, although effect sizes were small. Additionally, interviews were conducted with 18 parent/caregivers of returning youth and 18 match comparison parent/caregivers of non-returning youth. Qualitative analyses revealed few differences in previous year's program experiences between returners and non-returners, as well as similarities in reported benefits from involvement. Both sets of parent/caregivers cited positive experiences overall, and particular benefits related to meeting new people and learning new sports. Parents/caregivers of non-returners, however, noted the value of physical literacy components of the program more so than their counterparts. Social interactions, both positive and negative, seem to have particular relevance for retention. Findings overall, however, demonstrate challenges with predicting retention and fostering long-term engagement among youth from socially vulnerable circumstances in programming.
Detection of Shiga Toxin-Producing Escherichia coli (STEC) in the Endocervix of Asymptomatic Pregnant Women. Can STEC Be a Risk Factor for Adverse Pregnancy Outcomes?

The presence of Escherichia coli in the vaginal microbiome has been associated with pregnancy complications. In previous works, we demonstrated that Shiga toxin-producing Escherichia coli (STEC) can produce abortion and premature delivery in rats and that Shiga toxin type 2 (Stx2) can impair human trophoblast cell lines. The hypothesis of this work was that STEC may colonize the lower female reproductive tract and be responsible for adverse pregnancy outcomes. Thus, the aim of this work was to evaluate the presence and prevalence of virulence factor genes from STEC in the endocervix of asymptomatic pregnant women. For that purpose, endocervical swabs were collected from pregnant women during their prenatal examination. Swab samples were enriched in a differential medium to select Enterobacteria. Then, positive samples were analyzed by PCR to detect genes characteristic of Escherichia sp. (such as uidA and yaiO), genes specific for portions of the rfb (O-antigen-encoding) regions of STEC O157 (rfb O157), and STEC virulence factor genes (such as stx1, stx2, eae, lpfA O113, hcpA, iha, sab, subAB). The cytotoxic effects of stx2-positive supernatants from E. coli recovered from the endocervix were evaluated in Vero cells. Our results showed that 11.7% of the endocervical samples were positive for E. coli. Additionally, we found samples positive for stx2 and other virulence factors for STEC. The bacterial supernatant from an isolate identified as E. coli O113:NT, carrying the stx2 gene, exhibited cytotoxic activity in Vero, Swan 71 and Hela cells. Our results open a new perspective regarding the presence of STEC during pregnancy.
Integrated Community Case Management Utilization Status and Associated Factors Among Caretakers of Sick Children Under the Age of 5 Years in West Shewa, Ethiopia

Objective To assess the utilization status and associated factors of integrated community case management (ICCM) of caretakers with <5 years of sick children. Methods Community-based cross-sectional study was employed with caretakers whose child was sick in the last 3 months before data collection. Bivariate and multivariable logistic regression analyses were employed. Results About 624 respondents participated in the study; 325 (52.1%) utilized integrated community case management. Caring for children between the ages 24–36 months old, (AOR = 1.26, 95%CI: 0.23, 0.90); women health development army (WHDA) training, (AOR = 5.76, 95%CI: 3.57, 9.30); certified as model family, (AOR = 3.98, 95%CI: 2.45, 6.46); perceived severity, (AOR = 5.29, 95%CI: 2.64, 10.60); awareness of danger sign, (AOR = 2.76, 95%CI: 1.69, 4.50), and awareness of ICCM, (AOR = 5.42, 95%CI: 1.67, 17.58) were associated with ICCM utilization. Conclusion This study revealed that age of the child, caretakers' awareness of ICCM, awareness of danger signs, illness severity, women's health developmental army training, and graduation as a model family were associated with ICCM utilization. Therefore, it is recommended that promote health education using community-level intervention modalities focusing on common childhood illness symptoms, danger signs, severity, and care-seeking behavior.
A*pex: Efficient Approximate Multi-Objective Search on Graphs

In multi-objective search, edges are annotated with cost vectors consisting of multiple cost components. A path dominates another path with the same start and goal vertices iff the component-wise sum of the cost vectors of the edges of the former path is ``less than'' the component-wise sum of the cost vectors of the edges of the latter path. The Pareto-optimal solution set is the set of all undominated paths from a given start vertex to a given goal vertex. Its size can be exponential in the size of the graph being searched, which makes multi-objective search time-consuming. In this paper, we therefore study how to find an approximate Pareto-optimal solution set for a user-provided vector of approximation factors. The size of such a solution set can be significantly smaller than the size of the Pareto-optimal solution set, which enables the design of approximate multi-objective search algorithms that are efficient and produce small solution sets. We present such an algorithm in this paper which we call A*pex and which builds on PP-A*, a state-of-the-art approximate bi-objective search algorithm (where there are only two cost components) but (1) makes PP-A* more efficient for bi-objective search and (2) generalizes it to multi-objective search for any number of cost components. We first analyze the correctness of A*pex and then experimentally demonstrate its efficiency advantage over existing approximate algorithms for bi- and tri-objective search.
LFG-Net: Low-Level Feature Guided Network for Precise Ship Instance Segmentation in SAR Images

Ship instance segmentation of high-resolution (HR) synthetic aperture radar (SAR) images is a valuable and challenging task due to the complex scattering and noise properties. In this article, we pioneered the construction of the low-level feature to discriminate the ships and complemented the super-resolution (SR) denoising techniques in the network modules, termed low-level feature guided network (LFG-Net), for precise ship instance segmentation in SAR images. LFG-Net consists of the low-level feature concerned pyramid (LFCP), the high-resolution feature interaction module (HR-FIM), and the compression recovery segmentation branch (CRSB). LFCP extends the vanilla feature pyramid network (FPN) with the ${P_{1}}$ layer and complements SR techniques to capture the regional and texture information at the image level for small object segmentation. HR-FIM interacts with the bounding box region of interest (RoI) feature and mask RoI feature at the instance level with HR techniques to enhance the mask RoI feature. CRSB aims at recovering the HR mask predictions to improve the ship segmentation performance. Comprehensive experiments on high-resolution SAR images dataset (HRSID), polygon segmentation SAR ship detection dataset (PSeg-SSDD), and AirSARShip indicate that LFG-Net* achieves 11.7%, 6.3%, and 12.7% AP increments compared with the Mask R-CNN baseline, respectively. Besides, it receives 9.5%, 4.9%, and 7.3% AP increments compared with the state-of-the-art method, which bridges the gap of instance segmentation precision in SAR images. In terms of the visualized instance segmentation results, LFG-Net* is capable of segmenting the complex scenes, e.g., the adjacent distributed ships and ships with strong reflection noise interference, in SAR images. The code is available at: https://github.com/Evarray/LFG-Net.
An End-to-End Automatic Cache Replacement Policy Using Deep Reinforcement Learning

In the past few decades, much research has been conducted on the design of cache replacement policies. Prior work frequently relies on manually-engineered heuristics to capture the most common cache access patterns, or predict the reuse distance and try to identify the blocks that are either cache-friendly or cache-averse. Researchers are now applying recent advances in machine learning to guide cache replacement policy, augmenting or replacing traditional heuristics and data structures. However, most existing approaches depend on the certain environment which restricted their application, e.g, most of the approaches only consider the on-chip cache consisting of program counters (PCs). Moreover, those approaches with attractive hit rates are usually unable to deal with modern irregular workloads, due to the limited feature used. In contrast, we propose a pervasive cache replacement framework to automatically learn the relationship between the probability distribution of different replacement policies and workload distribution by using deep reinforcement learning. We train an end-to-end cache replacement policy only on the past requested address through two simple and stable cache replacement policies. Furthermore, the overall framework can be easily plugged into any scenario that requires cache. Our simulation results on 8 production storage traces run against 3 different cache configurations confirm that the proposed cache replacement policy is effective and outperforms several state-of-the-art approaches.
PTEENet: Post-Trained Early-Exit Neural Networks Augmentation for Inference Cost Optimization

For many practical applications, a high computational cost of inference over deep network architectures might be unacceptable. A small degradation in the overall inference accuracy might be a reasonable price to pay for a significant reduction in the required computational resources. In this work, we describe a method for introducing “shortcuts” into the DNN feedforward inference process by skipping costly feedforward computations whenever possible. The proposed method is based on the previously described BranchyNet [2] and the EEnet [1] architectures that jointly train the main network and early exit branches. We extend those methods by attaching branches to pretrained models and, thus, eliminating the need to alter the original weights of the network. We also suggest a new branch architecture based on convolutional building blocks to allow enough training capacity when applied on large DNN’s. The proposed architecture includes “confidence” heads that are used for predicting the confidence level in the corresponding early exits. By defining adjusted thresholds on these confidence extensions, we can control in real-time the amount of data exiting from each branch and the overall tradeoff between speed and accuracy of our model. In our experiments, we evaluate our method using image datasets (SVHN and CIFAR10) and several DNN architectures (ResNet, DenseNet, VGG) with varied depth. Our results demonstrate that the proposed method enables us to reduce the average inference computational cost and further controlling the tradeoff between the model accuracy and the computations cost.
LINE-1 Hypomethylation is a Marker of Poor Prognosis in Stage IA Non-small Cell Lung Cancer

Purpose: Global hypomethylation and the hypermethylation of gene promoter regions are common events in tumor DNA. The aim of this study was to evaluate the prognostic significance of both global hypomethylation and gene promoter hypermethylation in DNA from non-small cell lung cancer (NSCLC). Experimental Design: Genomic DNA was obtained from tumor tissue of 379 NSCLC patients who underwent surgery. Methylation levels were measured by real-time PCR following bisulfite modification of DNA and were correlated with clinicopathological parameters and patient prognosis. Methylation of long interspersed nuclear element 1 (LINE-1) was used as a surrogate marker for global methylation. Hypermethylation of the APC, CDH13 and RASSF1 promoter regions was also evaluated. Results: Tumor tissue showed significantly higher CDH13 and RASSF1 methylation levels compared to normal lung tissue, but lower LINE-1 methylation levels. APC, RASSF1 and LINE-1 methylation levels were significant prognostic factors in univariate analysis of an initial cohort of 234 cases. APC and LINE-1 methylation remained significant prognostic factors in multivariate analysis that included age, gender, smoking history, histological type and pathological stage. LINE-1 methylation showed marginally significant prognostic value in stage IA and IB disease. Expansion of the study cohort to 364 cases revealed that LINE-1 methylation had significant prognostic value for stage IA NSCLC patients in multivariate analysis. Conclusions: LINE-1 hypomethylation was an independent marker of poor prognosis in stage IA NSCLC. Validation of this finding in additional tumor cohorts could have clinical relevance for the management of early stage NSCLC. (243 words)
Endothelial Priming: A New Role for Lymphatic T Cell + Cross-Presentation, and CD8 Steady-State Antigen Scavenging,

Until recently, the known roles of lymphatic endothelial cells (LECs) in immune modulation were limited to directing immune cell trafﬁcking and passively transporting peripheral Ags to lymph nodes. Recent studies demonstrated that LECs can directly suppress dendritic cell maturation and present peripheral tissue and tumor Ags for autoreactive T cell deletion. We asked whether LECs play a constitutive role in T cell deletion under homeostatic conditions. In this study, we demonstrate that murine LECs under noninﬂamed conditions actively scavenge and cross-present foreign exogenous Ags to cognate CD8 + T cells. This cross-presentation was sensitive to inhibitors of lysosomal acidiﬁcation and endoplasmic reticulum–golgi transport and was TAP1 dependent. Furthermore, LECs upregulated MHC class I and the PD-1 ligand PD-L1, but not the costimulatory molecules CD40, CD80, or CD86, upon Ag-speciﬁc interactions with CD8 + T cells. Finally, Ag-speciﬁc CD8 + T cells that were activated by LECs underwent proliferation, with early-generation apoptosis and dysfunctionally activated phenotypes that could not be reversed by exogenous IL-2. These ﬁndings help to establish LECs as APCs that are capable of scavenging and cross-presenting exogenous Ags, in turn causing dysfunctional activation of CD8 + T cells under homeostatic conditions. Thus, we suggest that steady-state lymphatic drainage may contribute to peripheral tolerance by delivering self-Ags to lymph node–resident leukocytes,
A Search for the Decay $B^{-}\to K^{-} \nu \bar{\nu}$

We present a search for the rare flavour-changing neutral-current decay $B^{-}\to K^{-} \nu \bar{\nu}$ based on a sample of $(86.9 \pm 1.0) \times 10^{6}$ $\Upsilon (4S) \to $B\bar{B}$ events collected by the BABAR experiment at the SLAC B-factory. Signal candidate events are selected by fully reconstructing a $B^+ \to \bar{D}^{0} X^+$ decay, where $X^+$ represents a combination of up to three charged pions or kaons and up to two $\pi^0$ candidates. The charged tracks and calorimeter clusters not used in the $B^+$ reconstruction are required to be compatible with a $B^{-}\to K^{-} \nu \bar{\nu}$ decay. We observe a total of three signal candidate events with an expected background of $2.7 \pm 0.8$, resulting in a preliminary limit of $\mathcal{B}(B^{-}\to K^{-} \nu \bar{\nu})<1.05 \times 10^{-4}$ at the 90% confidence level. This search is combined with the results of a previous and statistically independent preliminary BABAR search for $B^{-}\to K^{-} \nu \bar{\nu}$ to give a limit of $\mathcal{B}(B^{-}\to K^{-} \nu \bar{\nu})<7.0 \times 10^{-5}$ at the 90% confidence level.
ADENOCARCINOMA OF THE PROSTATE IN NIGERIAN IGBOS; A CLINICOPATHOLOGIC REVIEW

AIM: To describe the demographic, clinical and histopathological characteristics of carcinoma of the prostate among Igbos of Eastern Nigeria. Methodology: The surgical daybook, request forms and histology reports were perused and the demographic, clinical, chemical pathology reports of the total PSA (PSA) values were recorded. DRE was carried out by Urologists and abnormal DRE findings suspicious of prostate cancer were documented. Results: This is a histopathological analysis of 265 consecutive cases of carcinoma of Prostate (CaP) in men of Nigeria Igbos between April 2010 and March 2016 at Federal Medical Centre Owerri. The mean age was 70.7±11.0 with age range of 46 to 104 years. The peak age group was 71-80 years followed by 61-70 years. The mean total prostate-specific antigen (tPSA) was 47.7±30.9ngml -1 with a range of 2.0 to 512ngml -1 . The mean duration of symptoms was 27.6 months with a range of 2 to 180 months. Lower urinary tracts symptoms were reported by 225 (84.9%) patients. The abnormal digital rectal examination was present in 47 (17.73%) cases. Metastatic disease was present in 15 cases (5.7%). The histological variants of the CaP were adenocarcinoma 98.87% (262 cases), and one case (0.38%) each for Adenoid cystic carcinoma and Mucinous carcinoma. A suspected case of Primary Melanoma of the prostate was also present.