Miracle-dz/UniFAR-FTUs huggingface dataset:
Intratumoral Fusobacterium Nucleatum Levels Predict Therapeutic Response to Neoadjuvant Chemotherapy in Esophageal Squamous Cell Carcinoma

Purpose: Emerging evidence indicates that gut microbiome plays a crucial role in the cancer pathogenesis. Although Fusobacterium nucleatum (F. nucleatum) is associated with poor prognosis in multiple cancers, its clinical significance in predicting response to chemotherapy in patients with esophageal squamous cell carcinoma (ESCC) remains unclear. Experimental Design: The F. nucleatum levels were quantified by qPCR assays in tumor tissues from 551 patients with ESCC from two independent cohorts, including 101 patients who received neoadjuvant chemotherapy prior to curative resection. Associations between F. nucleatum burden and recurrence-free survival (RFS), as well with chemotherapeutic response were evaluated using response evaluation criteria in solid tumors (RECISTs), primary tumor metabolic response defined by maximum standardized uptake value (SUVmax) changes in positron emission tomography-CT (PET/CT), and pathologic tumor regression grade (TRG). Results: High burden of F. nucleatum in patients with ESCC associated with poor RFS in both training [log-rank P = 0.02; HR = 1.61; P = 0.03] and validation cohorts (log-rank P = 0.003; HR = 1.96; P = 0.004). Importantly, patients with ESCC with high levels of F. nucleatum displayed poor chemotherapeutic response for all three evaluation methods: RECIST (P = 0.04), SUVmax change in PET/CT (P = 0.0004), and TRG (P = 0.003). Conclusions: We conclude that high levels of intratumoral F. nucleatum have a prognostic significance for predicting poor RFS in patients with ESCC. More importantly, our data indicates that higher F. nucleatum burden correlates with poor response to neoadjuvant chemotherapy, suggesting the possibility that an antibiotic intervention against this bacterium may significantly improve therapeutic response in patients with ESCC.
Admission NarxCare Narcotics Scores are not Associated with Adverse Surgical Outcomes or Self-Reported Patient Satisfaction Following Elective Spine Surgery.

STUDY DESIGN Retrospective cohort study OBJECTIVE. : To investigate how elective spine surgery patient preoperative opioid use (as determined by admission NarxCare narcotics use scores) correlated with 30-day peri-operative outcomes and post-operative patient satisfaction. SUMMARY OF BACKGROUND DATA The effect of preoperative narcotics usage on post-operative outcomes and patient satisfaction following spine surgery has been of question. The NarxCare platform analyzes the patients' state Physician Drug Monitoring Program (PDMP) records to assign numerical scores that approximate a patient's overall opioid drug usage. METHODS Elective spine surgery cases performed at a single institution between October 2017 and March 2018 were evaluated. NarxCare narcotics use scores at the time of admission were assessed. Patient characteristics, as well as 30-day adverse events, readmissions, reoperations, and mortality, were abstracted from the medical record. Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey data was also abstracted when available.Cases were binned based on the following ranges of admission NarxCare scores: 0, 1-99, 100-299, 300-499, and 500+. Multivariate logistic regressions were performed to compare the odds of having an adverse events, readmission, reoperation, and mortality between the different narcotics groups. One-way ANOVA analyses were performed to compare HCAHPS survey response rates and HCAHPS survey results between the different narcotics score groups. RESULTS In total, 346 patients met criteria for inclusion in the study (NarxScore 0: n = 74, 1-99: n = 58, 300-499: n = 117, and 500+: n = 21). Multivariate logistic regressions did not detect statistically significant differential odds of experiencing adverse events, readmission, reoperation, or mortality between the different groups of admissions narcotics scores. Analyses of variance did not detect statistically significant differences in HCAHPS survey response rates, total HCAHPS scores, or HCAHP sub-group scores between the different narcotics score groups. CONCLUSION Although there are many reasons to address preoperative patient narcotic utilization, the current study did not detect perioperative outcome differences or patient satisfaction based on the narcotic use scores as stratified here. LEVEL OF EVIDENCE 3.
Nitrogen Fertilizer Induced Alterations in The Root Proteome of Two Rice Cultivars

Nitrogen (N) is an essential nutrient for plants and a key limiting factor of crop production. However, excessive application of N fertilizers and the low nitrogen use efficiency (NUE) have brought in severe damage to the environment. Therefore, improving NUE is urgent and critical for the reductions of N fertilizer pollution and production cost. In the present study, we investigated the effects of N nutrition on the growth and yield of the two rice (Oryza sativa L.) cultivars, conventional rice Huanghuazhan and indica hybrid rice Quanliangyou 681, which were grown at three levels of N fertilizer (including 135, 180 and 225 kg/hm2, labeled as N9, N12, N15, respectively). Then, a proteomic approach was employed in the roots of the two rice cultivars treated with N fertilizer at the level of N15. A total of 6728 proteins were identified, among which 6093 proteins were quantified, and 511 differentially expressed proteins were found in the two rice cultivars after N fertilizer treatment. These differentially expressed proteins were mainly involved in ammonium assimilation, amino acid metabolism, carbohydrate metabolism, lipid metabolism, signal transduction, energy production/regulation, material transport, and stress/defense response. Together, this study provides new insights into the regulatory mechanism of nitrogen fertilization in cereal crops.
Overview of Current Targeted Anti-Cancer Drugs for Therapy in Onco-Hematology

The upgraded knowledge of tumor biology and microenviroment provides information on differences in neoplastic and normal cells. Thus, the need to target these differences led to the development of novel molecules (targeted therapy) active against the neoplastic cells’ inner workings. There are several types of targeted agents, including Small Molecules Inhibitors (SMIs), monoclonal antibodies (mAbs), interfering RNA (iRNA) molecules and microRNA. In the clinical practice, these new medicines generate a multilayered step in pharmacokinetics (PK), which encompasses a broad individual PK variability, and unpredictable outcomes according to the pharmacogenetics (PG) profile of the patient (e.g., cytochrome P450 enzyme), and to patient characteristics such as adherence to treatment and environmental factors. This review focuses on the use of targeted agents in-human phase I/II/III clinical trials in cancer-hematology. Thus, it outlines the up-to-date anticancer drugs suitable for targeted therapies and the most recent finding in pharmacogenomics related to drug response. Besides, a summary assessment of the genotyping costs has been discussed. Targeted therapy seems to be an effective and less toxic therapeutic approach in onco-hematology. The identification of individual PG profile should be a new resource for oncologists to make treatment decisions for the patients to minimize the toxicity and or inefficacy of therapy. This could allow the clinicians to evaluate benefits and restrictions, regarding costs and applicability, of the most suitable pharmacological approach for performing a tailor-made therapy.
Green synthesis of silver nanoparticles from Alpinia officinarum mitigates cisplatin-induced nephrotoxicity via down-regulating apoptotic pathway in rats

Abstract The rhizome of A. officinarum possesses immense pharmaceutical properties like antioxidant, anti-inflammatory, antiapoptotic, anticancer activities. The foremost downside of herbal-based drugs is their poor bioavailability, to trounce this we synthesized a herbal based silver nanodrug with Alpinia officinarum rhizome extract and assessed its effect against the cisplatin-induced nephrotoxicity in in vivo model. The A. officinarum biosynthesized silver nanoparticles (AG-AO) were characterized using UV-Spec, FTIR, XRD, TEM and SAED analysis. The antioxidant and the nephroprotective property of biosynthesized AG-AO nanoparticles were assessed by estimating the levels of kidney biomarkers, cytokine, inflammatory markers, free radicals and antioxidants induced in control and experimental. Antiapoptotic effect of AG-AO nanoparticles were evaluated by measuring the levels of apoptotic proteins in control and experimental rats. Further, it is confirmed with histopathological analysis of kidney tissue with haematoxylin and eosin staining. Our physical analysis confirms the biosynthesized silver nanoparticles by A. officinarum and it satisfies the qualities of potent nanoparticles to be used for medication. Our biochemical, molecular and histopathological results confirm the antioxidant, antiapoptotic, anti-inflammatory properties of AG-AO. Overall our results authentically confirm AG-AO is a potent nephroprotective drug, which can be a supplementary drug to prevent cisplatin-induced nephrotoxicity.
Conformal High-K Dielectric Coating of Suspended Single-Walled Carbon Nanotubes by Atomic Layer Deposition

As one of the highest mobility semiconductor materials, carbon nanotubes (CNTs) have been extensively studied for use in field effect transistors (FETs). To fabricate surround-gate FETs— which offer the best switching performance—deposition of conformal, weakly-interacting dielectric layers is necessary. This is challenging due to the chemically inert surface of CNTs and a lack of nucleation sites—especially for defect-free CNTs. As a result, a technique that enables integration of uniform high-k dielectrics, while preserving the CNT’s exceptional properties is required. In this work, we show a method that enables conformal atomic layer deposition (ALD) of high-k dielectrics on defect-free CNTs. By depositing a thin Ti metal film, followed by oxidation to TiO2 under ambient conditions, a nucleation layer is formed for subsequent ALD deposition of Al2O3. The technique is easy to implement and is VLSI-compatible. We show that the ALD coatings are uniform, continuous and conformal, and Raman spectroscopy reveals that the technique does not induce defects in the CNT. The resulting bilayer TiO2/Al2O3 thin-film shows an improved dielectric constant of 21.7 and an equivalent oxide thickness of 2.7 nm. The electrical properties of back-gated and top-gated devices fabricated using this method are presented.
A Composite Hydrogel Scaffold Permits Self‐Organization and Matrix Deposition by Cocultured Human Glomerular Cells

3D scaffolds provide cells with a spatial environment that more closely resembles that of in vivo tissue, when compared to 2D culture on a plastic substrate. However, many scaffolding materials commonly used in tissue engineering tend to exhibit anisotropic morphologies that exhibit a narrow range of fiber diameters and pore sizes, which do not recapitulate extracellular matrices. In this study, a fibrin hydrogel is formed within the interstitial spaces of an electrospun poly(glycolic) acid (PGA) monolith to generate a composite, bimodal scaffold for the coculture of kidney glomerular cell lines. This new scaffold exhibits multiple fiber morphologies, containing both PGA microfibers (14.5 ± 2 µm) and fibrin gel nanofibers (0.14 ± 0.09 µm), which increase the compressive Young's modulus beyond that of either of the constituents. The composite structure provides an enhanced 3D environment that increases proliferation and adhesion of immortalized human podocytes and glomerular endothelial cells. Moreover, the micro/nanoscale fibrous morphology promotes motility and reorganization of the glomerular cells into glomerulus‐like structures, resulting in the deposition of organized collagen IV; the primary component of the glomerular basement membrane (GBM).
Multimedia Graphical Grid Based Text Password Authentication for Advanced User

: Multimedia Graphical Grid Based Text Password Authentication For Advance User deals with graphical password structure. It is used to increase the reliability of text based password for advanced users by modifying a combination of text and graphical passwords. It will ensure more secure way to users for granting access to an authenticated system. This idea can be very useful in banking system.
Comparing Perioperative Mortality and Morbidity of Minimally Invasive Esophagectomy Versus Open Esophagectomy for Esophageal Cancer

Objective: We compared the surgical outcomes of minimally invasive esophagectomy (MIE) and open esophagectomy (OE) for esophageal cancer. Summary Background Data: MIE has become a widespread procedure. However, the definitive advantages of MIE over OE at a nationwide level have not been established. Methods: We analyzed patients who underwent esophagectomy for clinical stage 0 to III esophageal cancer from April 2014 to March 2017 using a Japanese inpatient database. We performed propensity score matching to compare in-hospital mortality and morbidities between MIE and OE, accounting for clustering of patients within hospitals. Results: Among 14,880 patients, propensity matching generated 4572 pairs. MIE was associated with lower incidences of in-hospital mortality (1.2% vs 1.7%, P = 0.048), surgical site infection (1.9% vs 2.6%, P = 0.04), anastomotic leakage (12.8% vs 16.8%, P < 0.001), blood transfusion (21.9% vs 33.8%, P < 0.001), reoperation (8.6% vs 9.9%, P = 0.03), tracheotomy (4.8% vs 6.3%, P = 0.002), and unplanned intubation (6.3% vs 8.4%, P < 0.001); a shorter postoperative length of stay (23 vs 26 days, P < 0.001); higher incidences of vocal cord dysfunction (9.2% vs 7.5%, P < 0.001) and prolonged intubation period after esophagectomy (23.2% vs 19.3%, P < 0.001); and a longer duration of anesthesia (408 vs 363 minutes, P < 0.001). Conclusion: MIE had favorable outcomes in terms of in-hospital mortality, morbidities, and the postoperative hospital stay.
Efficient dynamical downscaling of general circulation models using continuous data assimilation

Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dynamical downscaling of a global atmospheric reanalysis. A comparison of the performance of CDA with the standard grid and spectral nudging techniques for representing long‐ and short‐scale features in the downscaled fields using the Weather Research and Forecast (WRF) model is further presented and analysed. The WRF model is configured at 0.25° × 0.25° horizontal resolution and is driven by 2.5° × 2.5° initial and boundary conditions from NCEP/NCAR reanalysis fields. Downscaling experiments are performed over a one‐month period in January 2016. The similarity metric is used to evaluate the performance of the downscaling methods for large (2,000 km) and small (300 km) scales. Similarity results are compared for the outputs of the WRF model with different downscaling techniques, NCEP/NCAR reanalysis, and NCEP Final Analysis (FNL, available at 0.25° × 0.25° horizontal resolution). Both spectral nudging and CDA describe better the small‐scale features compared to grid nudging. The choice of the wave number is critical in spectral nudging; increasing the number of retained frequencies generally produced better small‐scale features, but only up to a certain threshold after which its solution gradually became closer to grid nudging. CDA maintains the balance of the large‐ and small‐scale features similar to that of the best simulation achieved by the best spectral nudging configuration, without the need of a spectral decomposition. The different downscaled atmospheric variables, including rainfall distribution, with CDA is most consistent with the observations. The Brier skill score values further indicate that the added value of CDA is distributed over the entire model domain. The overall results clearly suggest that CDA provides an efficient new approach for dynamical downscaling by maintaining better balance between the global model and the downscaled fields.
On the Nisan-Ronen conjecture for submodular valuations

We consider incentive compatible mechanisms for a domain that is very close to the domain of scheduling n unrelated machines: the single exception is that the valuation of just one machine is submodular. For the scheduling problem with such cost functions, we give a lower bound of Ω(√n) on the approximation ratio of incentive compatible deterministic mechanisms. This is a strong information-theoretic impossibility result on the approximation ratio of mechanisms that provides strong evidence for the Nisan-Ronen conjecture. This is the first non-constant lower bound that assumes no restriction on the mechanism side; in contrast, all previous general results hold for only special classes of mechanisms such as local, strongly monotone, and anonymous mechanisms. Our approach is based on a novel multi-player characterization of appropriately selected instances that allows us to focus on particular type of algorithms, linear mechanisms, and it is a potential stepping stone towards the full resolution of the conjecture.
NuSTAR observations of wind-fed X-ray pulsar GX 301–2 during unusual spin-up event

We report on NuSTAR observations of the well-known wind-accreting X-ray pulsar GX 301–2 during a strong spin-up episode that took place in January–March 2019. A measurement of high luminosity of the source in the most recent observation allowed us to detect a positive correlation of the cyclotron line energy with luminosity. Beyond that, only minor differences in spectral and temporal properties of the source during the spin-up, presumably associated with the formation of a transient accretion disk, and the normal wind-fed state could be detected. Finally, we discuss conditions for the formation of the disk and possible reasons for lack of any appreciable variations in most of the observed source properties induced by the change of the accretion mechanism, and conclude that the bulk of the observed X-ray emission is still likely powered by direct accretion from the wind.
Orientation-Aware Semantic Segmentation on Icosahedron Spheres

We address semantic segmentation on omnidirectional images, to leverage a holistic understanding of the surrounding scene for applications like autonomous driving systems. For the spherical domain, several methods recently adopt an icosahedron mesh, but systems are typically rotation invariant or require significant memory and parameters, thus enabling execution only at very low resolutions. In our work, we propose an orientation-aware CNN framework for the icosahedron mesh. Our representation allows for fast network operations, as our design simplifies to standard network operations of classical CNNs, but under consideration of north-aligned kernel convolutions for features on the sphere. We implement our representation and demonstrate its memory efficiency up-to a level-8 resolution mesh (equivalent to 640 x 1024 equirectangular images). Finally, since our kernels operate on the tangent of the sphere, standard feature weights, pretrained on perspective data, can be directly transferred with only small need for weight refinement. In our evaluation our orientation-aware CNN becomes a new state of the art for the recent 2D3DS dataset, and our Omni-SYNTHIA version of SYNTHIA. Rotation invariant classification and segmentation tasks are additionally presented for comparison to prior art.
DANTE: Deep Affinity Network for Clustering Conversational Interactants

We propose a data-driven approach to visually detect conversational groups by identifying spatial arrangements typical of these focused social encounters. Our approach uses a novel Deep Affinity Network (DANTE) to predict the likelihood that two individuals in a scene are part of the same conversational group, considering contextual information like the position and orientation of other nearby individuals. The predicted pair-wise affinities are then used in a graph clustering framework to identify both small (e.g., dyads) and bigger groups. The results from our evaluation on two standard benchmarks suggest that the combination of powerful deep learning methods with classical clustering techniques can improve the detection of conversational groups in comparison to prior approaches. Our technique has a wide range of applications from visual scene understanding, e.g., for surveillance, to social robotics.
Is There Any Recovery Guarantee with Coupled Structured Matrix Factorization for Hyperspectral Super-Resolution?

Coupled structured matrix factorization (CoSMF) for hyperspectral super-resolution (HSR) has recently drawn significant interest in hyperspectral imaging for remote sensing. Presently there are very few studies on the theoretical recovery guarantees of CoSMF. This paper makes one such endeavor by considering the CoSMF formulation by Wei et al., which, simply speaking, is similar to coupled non-negative matrix factorization. Assuming no noise, we show sufficient conditions under which the globably optimal solution to the CoSMF problem is guaranteed to deliver certain recovery accuracies. Our analysis suggests that sparsity and the pure-pixel (or separability) condition play a hidden role in enabling CoSMF to achieve some good recovery characteristics.
Influence of nonuniformity in sapphire substrates for a gravitational wave telescope

The construction of a large-scale cryogenic gravitational wave telescope, KAGRA, has been completed, and four sapphire test masses have been installed in cryostat vacuum chambers. Recently, it was observed that a sapphire substrate used for one of the input test masses showed a characteristic structure in its transmission map due to nonuniformity of the crystal. We performed an interferometer simulation to observe the influence of the nonuniformity using measured transmission/reflection maps. Shot noise increased by 7% at low frequencies and by 16% at high frequencies. Laser frequency noise coupling increased by 1 order of magnitude. We also found deformation of an alignment control signal and higher tilt coupling in the output optics.
Bilateral Operators for Functional Maps

A majority of shape correspondence frameworks are based on devising pointwise and pairwise constraints on the correspondence map. The functional maps framework allows for formulating these constraints in the spectral domain. In this paper, we develop a functional map framework for the shape correspondence problem by constructing pairwise constraints using point-wise descriptors. Our core observation is that, every point-wise descriptor allows for the construction a pairwise kernel operator whose low frequency eigenfunctions depict regions of similar descriptor values at various scales of frequency. By aggregating the pairwise information from the descriptor and the intrinsic geometry of the surface encoded in the heat kernel, we construct a hybrid kernel and call it the bilateral operator. Analogous to the edge preserving bilateral filter in image processing, the action of the bilateral operator on a function defined over the manifold yields a descriptor dependent local smoothing of that function. By forcing the correspondence map to commute with the Bilateral operator, we show that we can maximally exploit the information from a given set of pointwise descriptors in a functional map framework.