Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive values of combined platelet count, neutrophil-lymphocyte ratio, and platelet-lymphocyte ratio in preeclampsia

Abstract We aimed to determine predictive values of the platelet count (PC), Neutrophil lymphocyte ratio (NLR), and platelet lymphocyte ratio (PLR) in preeclampsia independently and in combination. One hundred and eighty pregnant women (96 normal pregnancies, 84 preeclampsia) were included in this study. ROC evaluated the predictive value of PC, NLR, and PLR. AUC, Youden’s index, and optimal cut-off thresholds were calculated independently and in combination. The PC significantly decreased in preeclampsia (p < .0001, 95% CI −60.6437 to −24.5963) with cut-off level ≤250.3, whereas NLR was significantly increased in preeclampsia (5.28 ± 4.77, p = .0001, 95% CI 0.9813–2.9187) with cut-off level >4.47. In preeclampsia, PLR significantly decreased (94.32 ± 30.81, p = .0001, 95% CI 58.2583 to −29.6817) with cut-off level ≤100.48. Combined indices of PC, NLR, and PLR were significantly more predictive of preeclampsia when compared to independent indices (AUC 0.86, p < .001, 95% CI 0.801–0.907, sensitivity 75.0, and specificity 81.2) compared to independent indices. IMPACT STATEMENT What is already known on this subject? Many studies have tried to find out a simple screening test that would predict the risk of developing preeclampsia. Platelet count, Neutrophil lymphocyte ratio, and platelet lymphocyte ratio have been investigated independently to predict preeclampsia. These parameters are simple, cheap, and are usually available for all patients. Unfortunately, there are no universal cut-off levels accepted. What do the results of this study add? The use of a combination of platelet count, neutrophil-lymphocyte ratio, and platelet lymphocyte ratio is a simple and effective test to predict preeclampsia. The use of a scoring system involving cut-off levels of platelet count, neutrophil-lymphocyte ratio, and platelet lymphocyte ratio is a highly predictive index for developing preeclampsia. What are the implications of these findings for clinical practice and/or further research? In this study, we aimed to highlight the importance of using a combination of platelet count, neutrophil-lymphocyte ratio, and platelet lymphocyte ratio as a scoring index instead of using these parameters independently. More studies are needed to reach a universal cut-off level for each parameter.
Functionally deficient TRPV6 variants contribute to hereditary and familial chronic pancreatitis

The recent discovery of TRPV6 as a pancreatitis susceptibility gene served to identify a novel mechanism of chronic pancreatitis (CP) due to Ca2+ dysregulation. Herein, we analyzed TRPV6 in 81 probands with hereditary CP (HCP), 204 probands with familial CP (FCP), and 462 patients with idiopathic CP (ICP) by targeted next‐generation sequencing. We identified 25 rare nonsynonymous TRPV6 variants, 18 of which had not been previously reported. All 18 variants were characterized by a Ca2+ imaging assay, with 8 being identified as functionally deficient. Evaluation of functionally deficient variants in the three CP cohorts revealed two novel findings: (i) functionally deficient TRPV6 variants appear to occur more frequently in HCP/FCP patients than in ICP patients (3.2% vs. 1.5%) and (ii) functionally deficient TRPV6 variants found in HCP and FCP probands appear to be more frequently coinherited with known risk variants in SPINK1, CTRC, and/or CFTR than those found in ICP patients (66.7% vs 28.6%). Additionally, genetic analysis of available HCP and FCP family members revealed complex patterns of inheritance in some families. Our findings confirm that functionally deficient TRPV6 variants represent an important contributor to CP. Importantly, functionally deficient TRPV6 variants account for a significant proportion of cases of HCP/FCP.
Incidence of lung and human papilloma virus-associated malignancies in HIV-infected patients

Objective: Cancers represent one of the leading cause of mortality/morbidity in patients with HIV (PWH) in industrialized countries. The objective of our study was to compare incidence of lung and human papilloma virus (HPV)-related cancers among PWH with general population over the 2010–2017 period. Design: Prospective and multicenter cohort study. Methods: The study included patients with lung and HPV-related cancers from the ANRS CO3 Aquitaine cohort (PWH) and the general population-based cancer registry in Gironde area. We calculated incidence rates for 100 000 person-years and incidence rate ratios (IRR). Results: Among the 3572 PWH, 70 cancers were diagnosed in 68 patients including 35 lung and 35 HPV-related cancers (18 oropharyngeal, 11 anal, 6 cervix). Incidence rates of lung and HPV-related-cancers were 311.1 in PWH and 209.8 in general population for 100 000 person-years, respectively. IRR were significantly increased in PWH for lung 1.8 [1.4–2.2] and HPV-related cancer 1.3 [1.0–1.6] and particularly high for patients between 40 and 49 years old [IRR 4.4 (2.3–8.4) for lung cancer and 3.7 (2.1–6.5) for HPV-related cancer]. Conclusion: We emphasized the persistent high risk of lung and HPV-related cancer despite advent of antiretroviral therapies, particularly in the age strata of 40–49 years. Screening procedures should take into account this finding.
Long-Term Effect of Eco-Driving Education On Fuel Consumption Using An On-Board Logging Device

This paper on the impact of eco-driving education on fuel consumption is from the proceedings of 14th international Conference on Urban Transport and the Environment in the 21st Century, which was held in Malta in 2008. The authors report on a study that measured the long-term effects on fuel consumption of ecodriving education, which focused explaining the impact of driving choices on fuel consumption. The study monitored the travel and driving behavior of 28 participants over a period of several months, using an on-board vehicle device and a web-application. The on-board device is equipped with a GPRS-modem, a WiFi connection, a GPS system and a CANinterface. Driving behavior included choices such as gear-shifting rpm, relative amount of hard acceleration, relative amount of time letting the car roll in gear. The authors note that the data gleaned in this way might also be used as feedback to the driver, to visualize driving behavior, and to help the driver understand what he or she can do to further improve driving style. They focus on the results found on the long-term effect of an eco-driving course on fuel economy and driving style for eight participants. For 7 of the 8 drivers, fuel consumption diminished in the range of 1.7 to 7.3% in the eight weeks after they completed the eco-driving course.
Sensory deprivation leads to subpopulation‐specific changes in layer 6 corticothalamic cells

The effect of sensory deprivation on anatomical and physiological properties in two genetically defined types of layer 6 corticothalamic pyramidal cells in mouse somatosensory barrel cortex was investigated using in vitro electrophysiology. The two types analysed were the L6‐Ntsr1 subtype, found preferentially in the upper region of layer 6 and projecting to both ventral posterior medial nucleus of the thalamus and posterior medial nucleus of the thalamus, and the L6‐Drd1a subtype, located mostly in the lower regions of layer 6 and projecting to posterior medial nucleus. We found that the apical dendrite in L6‐Ntsr1 cells is longer and more branched, compared with L6‐Drd1a cells, and that the increase in firing frequency with increasing current stimulation is steeper in L6‐Drd1a cells. Sensory deprivation was achieved clipping one row of whiskers from birth until the day of experiment (16 ± 2 days). Mice of this age are actively exploring. In L6‐Ntsr1, but not in L6‐Drd1a cells, sensory deprivation decreased apical and basal dendrite outgrowth, and calcium influx evoked by backpropagating action potentials. These results contribute to the ongoing functional characterisation of corticothalamic layer 6 cells and indicate differences in the postnatal cortical refinement of two distinct corticothalamic circuits.
Clinical Hypnosis For Pain Reduction In Breast Cancer Mastectomy: A Randomized Clinical Trial

ABSTRACT Surgical procedures for breast cancer treatment are commonly followed by pain. Clinical hypnosis has been shown to be effective in reducing pain during and after surgery, but most of the studies have used analogical scales, which only measure pain intensity. The aim of this study was to evaluate the effect of clinical hypnosis on pain intensity and its interference in daily activities in patients before and after mastectomy. The patients were evaluated using the Brief Pain Inventory. Forty patients were randomly assigned to an experimental or control group and evaluated 5 times: 1) baseline, 2) after clinical hypnosis session, 3) before surgery, 4) 1 day after surgery, and 5) 1 week after the surgery (follow-up). The results showed that after surgery the hypnosis group had a statistically significant reduction in pain intensity, less interference of pain with daily activities, sleep and life enjoyment compared with a control group. Clinical hypnosis may be recommended as a complementary treatment procedure for postmastectomy pain reduction and improving the quality of life of these patients.
Evaluating the effect of nipple stimulation during labour on labour progression in term pregnant women

Abstract This study aimed to assess the effect of nipple stimulation during labour on duration of latent and active phases of labour in the term pregnant women. Pregnant women (222) were divided into two groups of nipple stimulation and control. Duration of latent and active phases of labour, the number of women treated with oxytocin, rate of caesarean section (C-section) and foetal outcomes were compared. The median of the latent phase duration of labour in the intervention and control groups was 3.2 (1.3–6.3) and 4.8 (0.8–3.0) h, respectively (p = .008); however, the median of active phase duration was 2.3 (1.4–3.0) in the intervention group and 2.5 (2.0–3.3) in control group, which was not significantly different (p = .249). Additionally, the number of women treated with oxytocin in nipple stimulation group was significantly (p = .001) less than the control group. More studies are needed to evaluate optimum frequency and duration of nipple stimulation during labour. IMPACT STATEMENT What is already known on this subject? In limited studies, nipple stimulation is considered as a low-complication method for stimulating labour at onset. What do the results of this study add? Nipple stimulation can be applied during labour for accelerating latent phase and reducing oxytocin infusion. What are the implications of these findings for clinical practice and/or further research? Nipple stimulation can be applied as a non-pharmacological and non-invasive method allowing patient to control her own labour progression more effectively.
HOTAIR Induces the Downregulation of miR-200 Family Members in Gastric Cancer Cell Lines

Background: Gastric cancer is the fourth most common human malignancy and the second reason for cancer morbidity worldwide. LncRNA HOTAIR has recently emerged as a promoter of metastasis in various cancer types, including GC, through the EMT process. However, the exact mechanism of HOTAIR in promoting EMT is unknown. Aberrant expression of the miR-200 family has been linked to the occurrence and development of various types of malignant tumors. This study investigates the correlation between the HOTAIR and miR-200 family gene expression patterns in GC cell lines. We investigated the miR-200 and HOTAIR due to their common molecular features in the EMT process. Methods: AGS and MKN45 cell lines were transfected with si-HOTAIR, along with a negative control. The effect of HOTAIR knockdown was also analyzed on cell viability and also on the expression of miR-200 family members, including miR-200a, -200b, and -200c, in cell lines using qRT-PCR. Statistical analysis was performed to find the potential correlation between the expression level of HOTAIR and miRs. Results: Our results showed significant increased miR-200 family expression level in transfected AGS and MKN45 GC cells (fold changes > 2; p < 0.001). Moreover, a negative correlation was observed between HOTAIR and miR-200 expression levels in GC cell lines (p < 0.05). Conclusion: Our findings showed a significant association between miR-200 family and HOTAIR expression levels in GC cell lines. Taken together, the HOTAIR-miR-200 axis seems to play a vital role in human GC, suggesting a potential therapeutic target in future GC treatment.
UFPMP-Det: Toward Accurate and Efficient Object Detection on Drone Imagery

This paper proposes a novel approach to object detection on drone imagery, namely Multi-Proxy Detection Network with Unified Foreground Packing (UFPMP-Det). To deal with the numerous instances of very small scales, different from the common solution that divides the high-resolution input image into quite a number of chips with low foreground ratios to perform detection on them each, the Unified Foreground Packing (UFP) module is designed, where the sub-regions given by a coarse detector are initially merged through clustering to suppress background and the resulting ones are subsequently packed into a mosaic for a single inference, thus significantly reducing overall time cost. Furthermore, to address the more serious confusion between inter-class similarities and intra-class variations of instances, which deteriorates detection performance but is rarely discussed, the Multi-Proxy Detection Network (MP-Det) is presented to model object distributions in a fine-grained manner by employing multiple proxy learning, and the proxies are enforced to be diverse by minimizing a Bag-of-Instance-Words (BoIW) guided optimal transport loss. By such means, UFPMP-Det largely promotes both the detection accuracy and efficiency. Extensive experiments are carried out on the widely used VisDrone and UAVDT datasets, and UFPMP-Det reports new state-of-the-art scores at a much higher speed, highlighting its advantages. The code is available at https://github.com/PuAnysh/UFPMP-Det.
Study of the hidden charm 
DD¯*
 interactions in chiral effective field theory

We study the chiral interactions of the hidden charm DD̄∗ system within chiral effective field theory. Chiral Lagrangians are constructed by incorporating the chiral symmetry, heavy quark symmetry as well as proper charge conjugation properties of the heavy mesons. The interacting potentials of the S -wave DD̄∗ are calculated up to second chiral order at 1-loop level, where complete two-pion exchange interactions are included. We further investigate the behaviors of the potentials in coordinate space, as well as their bound state properties. Our studies indicate that there exists a interacting strength ordering among considered four channels: str. [0(1)] > str. [0−(1+−)] > str. [1+(1+−)] > str. [1−(1++)] where str. stands for the strength of the DD̄∗ interaction. Moreover, we find that X(3872) can be treated as a good candidate of 0(1) molecular state. There also tends to form 0−(1+−) and 1+(1+−) molecular states and we expect the experiments to search for the predicted multi-structures around the DD̄∗ mass region.
Exact matrix product state representation and convergence of a fully correlated electronic wavefunction in the infinite-basis limit

In this article we present the exact representation of a fully correlated electronic wavefunction as the single-particle basis approaches completeness. It consists of a half-infinite chain of matrices of exponentially increasing size. The complete basis limit is illustrated numerically using the density matrix renormalization group method by computing the core-valence entanglement in the C$_2$ ground state in increasing subsets of cc-pVTZ and pVQZ bases until convergence is reached.
Early first‐line treatment response and subsequent disability worsening in relapsing–remitting multiple sclerosis

Treatment success in relapsing–remitting multiple sclerosis (RRMS) is generally determined using relapse frequency and magnetic resonance imaging (MRI) activity in the first 6 or 12 months on treatment. The association of these definitions of short‐term treatment success with disability worsening and disease activity in the longer term is unclear. In this study, we investigated risk factors associated with early first‐line treatment failure in RRMS, and the association of early treatment failure with subsequent disability worsening or "no evidence of disease activity" (NEDA‐3) status.
Examining depression symptoms within OCD: the role of experiential avoidance

Abstract Background: Obsessive compulsive disorder (OCD) and depression commonly co-occur. Past research has evaluated underlying mechanisms of depression in the context of other diagnoses, but few to no studies have done this within OCD. Aims: This study examines the relationships between distress tolerance (DT), experiential avoidance (EA), depression, and OCD symptom severity across intensive/residential treatment (IRT) for OCD. It was hypothesized that all variables would be significantly moderately related and EA would emerge as a potential contributing factor to change in depression and OCD symptoms across IRT for OCD. Method: The sample included 311 participants with a primary diagnosis of OCD seeking IRT. Correlations were performed between all variables at both admission and discharge. A two-step hierarchical regression with change in OCD symptoms and change in DT in the first block and change in EA in the second block examined if change in EA explained change in depression above and beyond change in OCD and DT ability. Results: At both admission and discharge, higher EA, lower DT, and higher OCD symptom severity were significantly associated with more depressive symptoms. Change in EA explained a significant amount of variance in change in depression above and beyond change in OCD symptom severity and change in DT. Conclusions: This study expands past results within an OCD sample, emphasizing EA as an important treatment target in OCD. Future studies could utilize samples from other treatment contexts, use a measure of EA specific to OCD, and utilize a longitudinal model that takes temporal precedence into account.
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder translating DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties could enable clinical review of the most uncertain regions, thereby building trust and paving the way toward clinical translation. Several uncertainty estimation methods have recently been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentage of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, highlighting the need for uncertainty quantification in medical image analyses. Finally, in favor of transparency and reproducibility, our evaluation code is made publicly available at https://github.com/RagMeh11/QU-BraTS.
Gravitational waves from dark matter isocurvature

The primordial fluctuations on large scales are adiabatic, but on smaller scales this need not be the case. Here we derive the general analytical framework to compute the stochastic gravitational wave background induced by primordial cold dark matter isocurvature fluctuations on small scales. We find that large isocurvature fluctuations can yield an observable gravitational wave signal, with a spectrum distinct from the one induced by adiabatic perturbations, and we provide for the first time the exact analytic expression of the kernel necessary to compute this signal. We then forecast the constraining power of future gravitational wave detectors on dark matter isocurvature on small scales and find they will dramatically improve on existing constraints.
Revisiting Memory Efficient Kernel Approximation: An Indefinite Learning Perspective

Matrix approximations are a key element in large-scale algebraic machine learning approaches. The recently proposed method MEKA (Si et al., 2014) effectively employs two common assumptions in Hilbert spaces: the low-rank property of an inner product matrix obtained from a shift-invariant kernel function and a data compactness hypothesis by means of an inherent block-cluster structure. In this work, we extend MEKA to be applicable not only for shift-invariant kernels but also for non-stationary kernels like polynomial kernels and an extreme learning kernel. We also address in detail how to handle non-positive semi-definite kernel functions within MEKA, either caused by the approximation itself or by the intentional use of general kernel functions. We present a Lanczos-based estimation of a spectrum shift to develop a stable positive semi-definite MEKA approximation, also usable in classical convex optimization frameworks. Furthermore, we support our findings with theoretical considerations and a variety of experiments on synthetic and real-world data.
Temperature independent pseudogap from $^{17}$O and $^{89}$Y NMR and the single component picture

Nuclear Magnetic Resonance (NMR) is a powerful local quantum probe of the electronic structure of materials, but in the absence of reliable theory the interpretation of the NMR data can be challenging. This is true in particular for the cuprate high-temperature superconductors. Over the years, a large base of NMR data became available, which makes a review of the early interpretation possible. Recently, it was shown that all planar O NMR shift and relaxation data available in the literature point to a temperature independent but doping dependent pseudogap, very similar to what was proposed from the electronic entropy. Here we analyze the anisotropy of the shift and relaxation of planar O to establish whether a single electronic spin component is applicable, since the planar Cu shift anisotropy clearly fails such a description. We find that the orbital shift terms deduced from the data are in agreement with first principle calculations, and the shift data show a temperature independent anisotropy also in agreement with hyperfine coefficients predicted by first principles, which also account for the relaxation anisotropy. Furthermore, we show that the original Y shift and relaxation data are in agreement with the proposed temperature independent pseudogap. This pseudogap depends on doping, but also on the family of materials, and the density of states outside or in the absence of the gap is universal for the cuprates; this suggests that the entropy should be similar for all cuprates, as well. Further consequences will be discussed.