Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of body mass index on quality of life after distal gastrectomy for gastric cancer

Purpose Few studies have evaluated changes in quality of life (QoL) in relation to changes in body mass index (BMI) after gastrectomy. This study aimed to evaluate the impact of postoperative changes in BMI on QoL after distal gastrectomy in gastric cancer patients. Methods QoL data from the European Organization for the Research and Treatment of Cancer (EORTC) gathered via the QLQ-C30 and QLQ-STO22 questionnaires were obtained from 1,036 patients preoperatively and at 1 year postoperatively. The patients were divided into 2 groups: group 1 - decreased postoperative BMI and group 2 - unchanged or increased postoperative BMI. Results There were 577 patients in group 1 and 459 in group 2. According to global health status and functional scales, emotional functioning (P = 0.035) was significantly worse in group 1 than in group 2 at 1 year postoperatively. Furthermore, there were significant decreases in QoL symptom scale scores, including fatigue (P = 0.016), nausea and vomiting (P = 0.002), and appetite loss (P = 0.001) scores, in group 1 compared with group 2. Regarding QLQ-STO22, reflux symptoms (P = 0.020), anxiety (P = 0.003), and body image (P = 0.003) were significantly worse in group 1 than in group 2 at 1 year after surgery. Conclusion BMI changes after distal gastrectomy influence QoL. Focus on controlling gastrointestinal symptoms and providing psychological support is essential in patients with decreased BMI after surgery. Patients should be offered follow-up care to assist them in maintaining BMI, for example, through dietary-behavior modifications and via intensive nutritional support, to prevent QoL deterioration after distal gastrectomy.
TORINO Repository ISTITUZIONALE

Identifying the cause of an underperforming WLAN can be challenging due to the presence of a plethora of devices and networks operating in the ISM band. Such devices cause electromagnetic interference that can potentially undermine the throughput of residential and enterprise WiFi networks. In this paper, we propose an interference estimation and monitoring technique for 802.11 Access Points that can be implemented without specialized hardware and without any modi ﬁ cation to wireless stations. We validate our technique with commercial hardware, evaluating its accuracy with different types of interferers.
Face Recognition Based on PCA and LDA Combination Feature Extraction

A whole face recognition system was proposed in the paper based on PCA and LDA combination feature extraction. Normalization was used to eliminate the redundant information interference. Principal Component Analysis (PCA) was used for feature extraction and dimension reduction. Linear Discriminate Analysis (LDA) was used to further improve the separability of samples in the subspace and extract LDA features. Nearest Neighbor Classifier (NNC) was adopted for face recognition. Face recognition rate was improved in our experiments on ORL face database with our approach.
Neuronal Phenotype in the Mature Nervous System Is Maintained by Persistent Retrograde Bone Morphogenetic Protein Signaling

The terminal differentiation of many developing neurons occurs after they innervate their target cells and is triggered by secreted target-derived signals that are transduced by presynaptic cognate receptors. Such retrograde signaling induces the expression of genes that are often distinctive markers of neuronal phenotype and function. However, whether long-term maintenance of neuronal phenotype requires persistent retrograde signaling remains poorly understood. Previously, we demonstrated that retrograde bone morphogenetic protein (BMP) signaling induces expression of a phenotypic marker of Drosophila Tv neurons, the neuropeptide FMRFamide (FMRFa). Here, we used a genetic technique that spatiotemporally targets transgene expression in Drosophila to test the role of persistent BMP signaling in the maintenance of Tv phenotype. We show that expression of dominant blockers of BMP signaling selectively in adult Tv neurons dramatically downregulated FMRFa expression. Moreover, adult-onset expression of mutant Glued, which blocks dynein/dynactin-mediated retrograde axonal transport, eliminated retrograde BMP signaling and dramatically downregulated FMRFa expression. Finally, we found that BMP deprivation did not affect Tv neuron survival and that FMRFa expression fully recovered to control levels after the termination of BMP blockade or Glued expression. Our results show that persistent retrograde BMP signaling is required to induce and to subsequently maintain the expression of a stably expressed phenotypic marker in a subset of mature Drosophila neurons. We postulate that retrograde maintenance of neuronal phenotype is conserved in vertebrates, and as a consequence, neuronal phenotype is likely vulnerable to neurodegenerative disease pathologies that disrupt neuronal connectivity or axonal transport.
HBEGF+ macrophages in rheumatoid arthritis induce fibroblast invasiveness

Macrophages promote fibroblast invasiveness and demonstrate variable response to anti-inflammatory medications in patients with rheumatoid arthritis. Malleable and manipulative macrophages Macrophages play a critical role in rheumatoid arthritis (RA), an autoimmune disease characterized by chronic joint inflammation. Kuo et al. used single-cell RNA sequencing to identify a subset of inflammatory macrophages within human RA joints that promoted synovial fibroblast invasiveness. Testing several approved treatments for RA in ex vivo explants revealed that most drugs target inflammatory macrophages but may not resolve pathologic response. An epidermal growth factor receptor inhibitor used to treat cancer could block macrophage-fibroblast cross-talk in RA samples. This study helps elucidate macrophage phenotypes and macrophage-fibroblast cross-talk in RA, with implications for therapeutic targeting. Macrophages tailor their function according to the signals found in tissue microenvironments, assuming a wide spectrum of phenotypes. A detailed understanding of macrophage phenotypes in human tissues is limited. Using single-cell RNA sequencing, we defined distinct macrophage subsets in the joints of patients with the autoimmune disease rheumatoid arthritis (RA), which affects ~1% of the population. The subset we refer to as HBEGF+ inflammatory macrophages is enriched in RA tissues and is shaped by resident fibroblasts and the cytokine tumor necrosis factor (TNF). These macrophages promoted fibroblast invasiveness in an epidermal growth factor receptor–dependent manner, indicating that intercellular cross-talk in this inflamed setting reshapes both cell types and contributes to fibroblast-mediated joint destruction. In an ex vivo synovial tissue assay, most medications used to treat RA patients targeted HBEGF+ inflammatory macrophages; however, in some cases, medication redirected them into a state that is not expected to resolve inflammation. These data highlight how advances in our understanding of chronically inflamed human tissues and the effects of medications therein can be achieved by studies on local macrophage phenotypes and intercellular interactions.
Wnt signaling regulates cytosolic translocation of Connexin 43.

The availability of intracellular, stabilized ß-catenin, a transcription factor co-activator, is tightly regulated; ß-catenin is translocated into the nucleus in response to Wnt ligand binding to its cell membrane receptors. Here we show that Wnt signal activation in mammalian cells activates intracellular mobilization of Connexin 43 which belongs to a gap junction protein family, a new target protein in response to extracellular Wnt signal activation. Transmission electron microscopy (TEM) showed that the nuclear localization of Cx43 was increased by 8-10 fold in Wnt5A and 9B treated cells compared to controls; this Wnt induced increase was negated in the cells where Cx43 and ß-catenin were knocked down using shRNA. There was a significant (p<0.001) and concomitant depletion of the cell membrane and cytosolic signal of Cx43 in Wnt treated cells with an increase in the nuclear signal for Cx43; this was more obvious in cells where β-catenin was knocked down using shRNA. Conversely, Cx43 knockdown resulted in increased ß-catenin in the nucleus, in the absence of Wnt activation. Co-immunoprecipitation of Cx43 and ß-catenin proteins with a casein kinase (CKIδ) antibody showed that Cx43 interacts with ß-catenin and may form part of the so-called destruction complex. Functionally, Wnt activation increased the rate of wound re-epithelization in rat skin, in vivo.
Diagnosis and management of sensory polyneuropathy

Abstract Sensory polyneuropathies, which are caused by dysfunction of peripheral sensory nerve fibers, are a heterogeneous group of disorders that range from the common diabetic neuropathy to the rare sensory neuronopathies. The presenting symptoms, acuity, time course, severity, and subsequent morbidity vary and depend on the type of fiber that is affected and the underlying cause. Damage to small thinly myelinated and unmyelinated nerve fibers results in neuropathic pain, whereas damage to large myelinated sensory afferents results in proprioceptive deficits and ataxia. The causes of these disorders are diverse and include metabolic, toxic, infectious, inflammatory, autoimmune, and genetic conditions. Idiopathic sensory polyneuropathies are common although they should be considered a diagnosis of exclusion. The diagnostic evaluation involves electrophysiologic testing including nerve conduction studies, histopathologic analysis of nerve tissue, serum studies, and sometimes autonomic testing and cerebrospinal fluid analysis. The treatment of these diseases depends on the underlying cause and may include immunotherapy, mitigation of risk factors, symptomatic treatment, and gene therapy, such as the recently developed RNA interference and antisense oligonucleotide therapies for transthyretin familial amyloid polyneuropathy. Many of these disorders have no directed treatment, in which case management remains symptomatic and supportive. More research is needed into the underlying pathophysiology of nerve damage in these polyneuropathies to guide advances in treatment.
Calcitonin stimulation tests for the early diagnosis and follow-up of patients with C cell disease: a descriptive analysis.

BACKGROUND/AIM Residual or recurrent medullary thyroid carcinoma (MTC) after thyroidectomy is diagnosed by elevated serum calcitonin (CT) levels. However, in minimal residual MTC or C-cell hyperplasia (CCH), where imaging studies are often negative, basal CT levels are frequently normal and CT stimulation tests are required. We aimed to compare CT stimulation tests with calcium, pentagastrin and their combination in identifying minimal residual MTC and CCH. MATERIAL AND METHODS We studied 10 post-thyroidectomy patients with MTC and 20 first-degree relatives of the patients who had no clinically apparent MTC. We performed 54 combined (calcium plus pentagastrin) stimulation tests, 35 calcium stimulation tests and 26 pentagastrin stimulation tests. RESULTS Basal CT levels were abnormal (≥500 pg/ml) in 4 patients with apparent metastatic disease (Group 1A) and in 2 patients with minimal residual disease (Group 1B) but were normal (0-300 pg/ml) in 4 patients with no residual disease (Group 1C) and in the relatives (Group 2). In Groups 1A, 1B and 1C, maximal elevation in CT levels was greater after the combined stimulation test than after calcium or pentagastrin tests. The combined stimulation test induced the greatest increases (920, 700 and 706 pg/ml, respectively) in 3 relatives (Group 2); CCH was confirmed histologically in these patients. Side-effects were mild, short-lasting and of similar intensity and duration during all tests. CONCLUSIONS Patients with subclinical MTC (minimal residual or recurrent MTC) or their relatives (with CCH) usually have normal basal CT levels and stimulation tests are necessary. Combined test represents the most sensitive and safe stimulation test for the diagnosis of subclinical hypercalcitonemia.
Thrombolysis Guided by Perfusion Imaging up to 9 Hours after Onset of Stroke

Background The time to initiate intravenous thrombolysis for acute ischemic stroke is generally limited to within 4.5 hours after the onset of symptoms. Some trials have suggested that the treatment window may be extended in patients who are shown to have ischemic but not yet infarcted brain tissue on imaging. Methods We conducted a multicenter, randomized, placebo‐controlled trial involving patients with ischemic stroke who had hypoperfused but salvageable regions of brain detected on automated perfusion imaging. The patients were randomly assigned to receive intravenous alteplase or placebo between 4.5 and 9.0 hours after the onset of stroke or on awakening with stroke (if within 9 hours from the midpoint of sleep). The primary outcome was a score of 0 or 1 on the modified Rankin scale, on which scores range from 0 (no symptoms) to 6 (death), at 90 days. The risk ratio for the primary outcome was adjusted for age and clinical severity at baseline. Results After 225 of the planned 310 patients had been enrolled, the trial was terminated because of a loss of equipoise after the publication of positive results from a previous trial. A total of 113 patients were randomly assigned to the alteplase group and 112 to the placebo group. The primary outcome occurred in 40 patients (35.4%) in the alteplase group and in 33 patients (29.5%) in the placebo group (adjusted risk ratio, 1.44; 95% confidence interval [CI], 1.01 to 2.06; P=0.04). Symptomatic intracerebral hemorrhage occurred in 7 patients (6.2%) in the alteplase group and in 1 patient (0.9%) in the placebo group (adjusted risk ratio, 7.22; 95% CI, 0.97 to 53.5; P=0.05). A secondary ordinal analysis of the distribution of scores on the modified Rankin scale did not show a significant between‐group difference in functional improvement at 90 days. Conclusions Among the patients in this trial who had ischemic stroke and salvageable brain tissue, the use of alteplase between 4.5 and 9.0 hours after stroke onset or at the time the patient awoke with stroke symptoms resulted in a higher percentage of patients with no or minor neurologic deficits than the use of placebo. There were more cases of symptomatic cerebral hemorrhage in the alteplase group than in the placebo group. (Funded by the Australian National Health and Medical Research Council and others; EXTEND ClinicalTrials.gov numbers, NCT00887328 and NCT01580839.)
Investigating the psychometric properties of the Suicide Stroop Task.

Behavioral measures are increasingly used to assess suicidal thoughts and behaviors. Some measures, such as the Suicide Stroop Task, have yielded mixed findings in the literature. An understudied feature of these behavioral measures has been their psychometric properties, which may affect the probability of detecting significant effects and reproducibility. In the largest investigation of its kind, we tested the internal consistency and concurrent validity of the Suicide Stroop Task in its current form, drawing from seven separate studies (N = 875 participants, 64% female, aged 12 to 81 years). Results indicated that the most common Suicide Stroop scoring approach, interference scores, yielded unacceptably low internal consistency (rs = -.09-.13) and failed to demonstrate concurrent validity. Internal consistency coefficients for mean reaction times (RTs) to each stimulus type ranged from rs = . 93-. 94. All scoring approaches for suicide-related interference demonstrated poor classification accuracy (AUCs = .52-.56) indicating that scores performed near chance in their ability to classify suicide attempters from nonattempters. In the case of mean RTs, we did not find evidence for concurrent validity despite our excellent reliability findings, highlighting that reliability does not guarantee a measure is clinically useful. These results are discussed in the context of the wider implications for testing and reporting psychometric properties of behavioral measures in mental health research. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Analysis of DLL3 and ASCL1 in Surgically Resected Small Cell Lung Cancer (HOT1702).

BACKGROUND Delta-like protein 3 (DLL3) is a Notch ligand that has an important role in the tumorigenesis of small cell lung cancer (SCLC). Recently, rovalpituzumab tesirine (Rova-T), a DLL3-targeted antibody-drug conjugate, has been developed for treating SCLC. DLL3 is a transcriptional target of the achaete-scute homolog-1 (ASCL1) transcription factor, which is involved in pulmonary neuroendocrine cell development. However, the relationship between DLL3 and/or ASCL1 expression and the clinical features of SCLC remains unknown, especially for early-stage resected SCLC. This study aimed to investigate the expression of DLL3 and ASCL1 in resected SCLC samples using immunohistochemical analysis. MATERIALS AND METHODS We collected 95 surgically resected SCLC samples, which were formalin fixed and paraffin embedded. Immunohistochemistry staining was performed to investigate the correlation between the expression of either DLL3 or ASCL1 and clinicopathological features of study patients. RESULTS Seventy-seven (83%) of 93 immunohistochemically evaluable samples were positive for DLL3 (expression in ≥1% of tumor cells), and DLL3-high expression (≥75%) was observed in 44 samples (47%). Sixty-one (64%) of 95 samples were positive for ASCL1 (expression in ≥5% of tumor cells). A positive correlation was observed between DLL3 and ASCL1 expression. DLL3 and ASCL1 expression were not associated with survival in SCLC patients. DLL3 was more prevalent in patients with advanced clinical disease. CONCLUSION DLL3 and ASCL1 were highly expressed in patients with surgically resected SCLC. DLL3 and ASCL1 may be targets for the treatment of SCLC. IMPLICATIONS FOR PRACTICE This article examines the relationship between delta-like protein 3 (DLL3) and achaete-scute homolog-1 (ASCL1) protein expression with the clinical features of 95 surgically resected small cell lung cancer (SCLC). DLL3 is attracting attention because rovalpituzumab tesirine (Rova-T), a DLL3-targeted antibody-drug conjugate, was developed recently. DLL3 and ASCL1 were highly expressed in patients with surgically resected SCLC. DLL3 and ASCL1 may be targets for the treatment of early-stage SCLC, including with Rova-T.
Can DCE-MRI Explain the Heterogeneity in Radiopeptide Uptake Imaged by SPECT in a Pancreatic Neuroendocrine Tumor Model?

Although efficient delivery and distribution of treatment agents over the whole tumor is essential for successful tumor treatment, the distribution of most of these agents cannot be visualized. However, with single-photon emission computed tomography (SPECT), both delivery and uptake of radiolabeled peptides can be visualized in a neuroendocrine tumor model overexpressing somatostatin receptors. A heterogeneous peptide uptake is often observed in these tumors. We hypothesized that peptide distribution in the tumor is spatially related to tumor perfusion, vessel density and permeability, as imaged and quantified by DCE-MRI in a neuroendocrine tumor model. Four subcutaneous CA20948 tumor-bearing Lewis rats were injected with the somatostatin-analog 111In-DTPA-Octreotide (50 MBq). SPECT-CT and MRI scans were acquired and MRI was spatially registered to SPECT-CT. DCE-MRI was analyzed using semi-quantitative and quantitative methods. Correlation between SPECT and DCE-MRI was investigated with 1) Spearman’s rank correlation coefficient; 2) SPECT uptake values grouped into deciles with corresponding median DCE-MRI parametric values and vice versa; and 3) linear regression analysis for median parameter values in combined datasets. In all tumors, areas with low peptide uptake correlated with low perfusion/density/ /permeability for all DCE-MRI-derived parameters. Combining all datasets, highest linear regression was found between peptide uptake and semi-quantitative parameters (R2>0.7). The average correlation coefficient between SPECT and DCE-MRI-derived parameters ranged from 0.52-0.56 (p<0.05) for parameters primarily associated with exchange between blood and extracellular extravascular space. For these parameters a linear relation with peptide uptake was observed. In conclusion, the ‘exchange-related’ DCE-MRI-derived parameters seemed to predict peptide uptake better than the ‘contrast amount- related’ parameters. Consequently, fast and efficient diffusion through the vessel wall into tissue is an important factor for peptide delivery. DCE-MRI helps to elucidate the relation between vascular characteristics, peptide delivery and treatment efficacy, and may form a basis to predict targeting efficiency.
MuFuRU: The Multi-Function Recurrent Unit

Recurrent neural networks such as the GRU and LSTM found wide adoption in natural language processing and achieve state-of-the-art results for many tasks. These models are characterized by a memory state that can be written to and read from by applying gated composition operations to the current input and the previous state. However, they only cover a small subset of potentially useful compositions. We propose Multi-Function Recurrent Units (MuFuRUs) that allow for arbitrary differentiable functions as composition operations. Furthermore, MuFuRUs allow for an input- and state-dependent choice of these composition operations that is learned. Our experiments demonstrate that the additional functionality helps in different sequence modeling tasks, including the evaluation of propositional logic formulae, language modeling and sentiment analysis.
Universal Sound Separation

Recent deep learning approaches have achieved impressive performance on speech enhancement and separation tasks. However, these approaches have not been investigated for separating mixtures of arbitrary sounds of different types, a task we refer to as universal sound separation, and it is unknown how performance on speech tasks carries over to non-speech tasks. To study this question, we develop a dataset of mixtures containing arbitrary sounds, and use it to investigate the space of mask-based separation architectures, varying both the overall network architecture and the framewise analysis-synthesis basis for signal transformations. These network architectures include convolutional long short-term memory networks and time-dilated convolution stacks inspired by the recent success of time-domain enhancement networks like ConvTasNet. For the latter architecture, we also propose novel modifications that further improve separation performance. In terms of the frame-wise analysis-synthesis basis, we explore both a short-time Fourier transform (STFT) and a learnable basis, as used in ConvTasNet. For both of these bases, we also examine the effect of window size. In particular, for STFTs, we find that longer windows (25-50 ms) work best for speech/non-speech separation, while shorter windows (2.5 ms) work best for arbitrary sounds. For learnable bases, shorter windows (2.5 ms) work best on all tasks. Surprisingly, for universal sound separation, STFTs outperform learnable bases. Our best methods produce an improvement in scale-invariant signal-to-distortion ratio of over 13 dB for speech/non-speech separation and close to 10 dB for universal sound separation.
The Hull-White Model under Knightian Uncertainty about the Volatility

We construct an arbitrage-free short rate model under Knightian uncertainty about the volatility. The uncertainty is represented by a set of priors, which naturally leads to a G-Brownian motion. Within this framework, it is shown how to characterize the whole term structure without admitting arbitrage. The pricing of zero-coupon bonds in such a setting differs substantially from traditional models, since the prices need to be chosen in a different way in order to exclude arbitrage.