Advanced Characterization and Optical Properties of Single-Walled Carbon Nanotubes and Graphene Oxide

Photophysical, electronic, and compositional properties of single-walled carbon nanotubes (SWCNTs) and bulk nanotube samples were investigated together with graphene oxide photoluminescence. First, we studied the effect of external electric fields on SWCNT photoluminescence. Fields of up to 10 7 V/m caused dramatic, reversible decreases in emission intensity. Quenching efficiency was proportional to the projection of the field on the SWCNT axis, and showed inverse correlation with optical band gap. The magnitude of the effect was experimentally related to exciton binding energy, as consistent with a proposed field-induced exciton dissociation model. Further, the electronic composition of various SWCNT samples was studied. A new method was developed to measure the fraction of semiconducting nanotubes in as- grown or processed samples. SWCNT number densities were compared in images from near-IR photoluminescence (semiconducting species) and AFM (all species) to compute the semiconducting fraction. The results provide important information about SWCNT sample compositions that can guide controlled growth methods and help calibrate bulk characterization techniques. The nature of absorption backgrounds in SWCNT samples was also studied. A number of extrinsic perturbations such as extensive ultrasonication, sidewall functionalization, amorphous carbon impurities, and SWCNT aggregation were applied and their background contributions quantified. Spectral congestion backgrounds from overlapping absorption bands were assessed with spectral modeling. Unlike semiconducting nanotubes, metallic SWCNTs gave broad intrinsic absorption backgrounds. The shape of the metallic background component and its absorptivity coefficient were determined. These results can be used to minimize and evaluate SWCNT absorption backgrounds. Length dependence of SWCNT optical properties was investigated. Samples were dispersed by ultrasonication or shear processing, and then length-fractionated by gel electrophoresis or controlled ultrasonication shortening. Fractions from both methods showed no significant absorbance variations with SWCNT length. The photoluminescence intensity increased linearly with length, and the relative quantum yield gradually increased, approaching a limiting value. Finally, a strong pH dependence of graphene oxide photoluminescence was observed. Sharp and structured excitation/emission features resembling the spectra of molecular fluorophores were obtained in basic conditions. Based on the observed pH-dependence and quantum calculations, these spectral features were assigned to quasi-molecular fluorophores formed by the electronic coupling of oxygen-containing addends with nearby graphene carbon atoms

An NGQD Based Diagnostic Tool for Pancreatic Cancer

Background: Pancreatic cancer remains difficult to detect at early stages which contributes to a poor five-yearsurvival rate. Therefore, early detection approaches based on novel technologies should be explored to address this critical health issue. Nanomaterials have recently emerged as frontrunners for diagnostic applications due to their small size in the 1-100 nm range, which facilitates one-on-one interactions with a variety of biomolecules like oligonucleotides and makes them suitable for a plethora of detection and delivery applications. In this work, the presence of specific pancreatic cancer miRNA (pre-miR-132) is detected utilizing the fluorescence properties of highly biocompatible nitrogen-doped graphene quantum dots (NGQDs). Methods: NGQDs were synthesized from Glucosamine HCl and deionized H2O. Cuvettes were filled with a mixture of bait ssDNA (13.7μM) and NGQDs (0.5 mg/ml) in deionized H2O that was vortexed for 5s before adding target strands. Samples were again vortexed for 5s and incubated at 4 ºC for 2hrs before excitation at 400 nm with an emission wavelength measured from 420 nm to 780 nm using a spectrofluorometer. Data analysis was performed using Origin software. Results: From the Zeta potential measurements, this platform is comprised of positively charged (1.14±0.36 mV) NGQDs binding with negatively charged (-22.4±6.00 mV) ssDNA electrostatically and/or via − stacking to form an NGQDs/ssDNA complex with an estimated size of 20 nm verified with TEM. Observing variations in fluorescence spectra of NGQDs/ssDNA complexes allows for the distinguishing of single-stranded and double-stranded DNA, as well as specific single-stranded DNA sequences due to bait-target complementarity. Furthermore, this enables detection of the loop of pre-miRNA of interest and can identify target miRNA from random controls with sensitivity in the nanomolar range. Conclusions: This approach allows for pancreatic cancer-specific miRNA sensing to facilitate pancreatic cancer detection at the early stages. Such early diagnosis is ultimately aimed to increase cancer patient survival rates

Detection of Pancreatic Cancer miRNA with Biocompatible Nitrogen-Doped Graphene Quantum Dots

Early-stage pancreatic cancer remains challenging to detect, leading to a poor five-year patient survival rate. This obstacle necessitates the development of early detection approaches based on novel technologies and materials. In this work, the presence of a specific pancreatic cancer-derived miRNA (pre-miR-132) is detected using the fluorescence properties of biocompatible nitrogen-doped graphene quantum dots (NGQDs) synthesized using a bottom-up approach from a single glucosamine precursor. The sensor platform is comprised of slightly positively charged (1.14 ± 0.36 mV) NGQDs bound via π-π stacking and/or electrostatic interactions to the negatively charged (-22.4 ± 6.00 mV) bait ssDNA; together, they form a complex with a 20 nm average size. The NGQDs\u27 fluorescence distinguishes specific single-stranded DNA sequences due to bait-target complementarity, discriminating them from random control sequences with sensitivity in the micromolar range. Furthermore, this targetability can also detect the stem and loop portions of pre-miR-132, adding to the practicality of the biosensor. This non-invasive approach allows cancer-specific miRNA detection to facilitate early diagnosis of various forms of cancer

EndoNet: model for automatic calculation of H-score on histological slides

H-score is a semi-quantitative method used to assess the presence and distribution of proteins in tissue samples by combining the intensity of staining and percentage of stained nuclei. It is widely used but time-consuming and can be limited in accuracy and precision. Computer-aided methods may help overcome these limitations and improve the efficiency of pathologists' workflows. In this work, we developed a model EndoNet for automatic calculation of H-score on histological slides. Our proposed method uses neural networks and consists of two main parts. The first is a detection model which predicts keypoints of centers of nuclei. The second is a H-score module which calculates the value of the H-score using mean pixel values of predicted keypoints. Our model was trained and validated on 1780 annotated tiles with a shape of 100x100 $\mu m$ and performed 0.77 mAP on a test dataset. Moreover, the model can be adjusted to a specific specialist or whole laboratory to reproduce the manner of calculating the H-score. Thus, EndoNet is effective and robust in the analysis of histology slides, which can improve and significantly accelerate the work of pathologists

Neural network interpretation techniques for analysis of histological images of breast abnormalities

Background. Neural networks are actively used in digital pathology to analyze histological images and support medical decision-making. A common approach is to solve the classification problem, where only class labels are the only model responses. However, one should understand which areas of the image have the most significant impact on the model's response. Machine learning interpretation techniques help solve this problem. Aim. To study the consistency of different methods of neural network interpretation when classifying histological images of the breast and to obtain an expert assessment of the results of the evaluated methods. Materials and methods. We performed a preliminary analysis and pre-processing of the existing data set used to train pre-selected neural network models. The existing methods of visualizing the areas of attention of trained models on easy-to-understand data were applied, followed by verification of their correct use. The same neural network models were trained on histological data, and the selected interpretation methods were used to systematize histological images, followed by the evaluation of the results consistency and an expert assessment of the results. Results. In this paper, several methods of interpreting machine learning are studied using two different neural network architectures and a set of histological images of breast abnormalities. Results of ResNet18 and ViT-B-16 models training on a set of histological images on the test sample: accuracy metric 0.89 and 0.89, ROC_AUC metric 0.99 and 0.96, respectively. The results were also evaluated by an expert using the Label Studio tool. For each pair of images, the expert was asked to select the most appropriate answer ("Yes" or "No") to the question: "The highlighted areas generally correspond to the Malignant class." The "Yes" response rate for the ResNet_Malignant category was 0.56; for ViT_Malignant, it was 1.0. Conclusion. Interpretability experiments were conducted with two different architectures: the ResNet18 convolutional network and the ViT-B-16 attention-enhanced network. The results of the trained models were visualized using the GradCAM and Attention Rollout methods, respectively. First, experiments were conducted on a simple-to-interpret dataset to ensure they were used correctly. The methods are then applied to the set of histological images. In easy-to-understand images (cat images), the convolutional network is more consistent with human perception; on the contrary, in histological images of breast cancer, ViT-B-16 provided results much more similar to the expert's perception

ИНТЕРВЕНЦИОННЫЕ МЕТОДЫ ЛЕЧЕНИЯ ВЕРТЕБРОГЕННОЙ БОЛИ: ОБЗОР ЛИТЕРАТУРЫ И СОБСТВЕННЫЙ ОПЫТ

The work is devoted to the consideration of treatment options for vertebrogenic pain syndrome. Its frequent occurrence is associated with changes in living and working conditions in the modern world. Prolonged axial loads on the spine, inactivity, increased body weight negatively affect the balance of the spinal column, which at the initial stage is expressed in the appearance of pain syndrome. The authors, in their work, distinguish the main types of blockades depending on their purpose. The modern technological means for verification of anatomical structures, allowing to target the source of pain, are emphasized separately. Various methods of blockade such as epidural, caudal, transforaminal epidural, myofascial, sacroiliac joint blockade, intervertebral joints and piriformis muscle are described. Indications for their use, as well as important tactical nuances are highlighted. The analysis of the possibilities of using various drugs in the relief of vertebrogenic pain. The probable risks of their application are specified. In conclusion, the authors emphasize the importance of minimally invasive interventional interventions in the complex treatment of vertebrogenic pain syndrome.Работа посвящена рассмотрению вариантов лечения вертеброгенного болевого синдрома. Частая встречаемость его связана с изменениями условий жизни и работы в современном мире. Длительные осевые нагрузки на позвоночник, гиподинамия, повышенная масса тела негативно влияют на баланс позвоночного столба, что на начальном этапе выражается в появлении болевого синдрома. Авторы, в своей работе, выделяют основные виды блокад в зависимости от их цели. Отдельно подчеркнуты современные технологические средства для верификации анатомических структур, позволяющие таргетированно воздействовать на источник боли. Описаны различные методы проведения блокад такие как эпидуральная, каудальная, трaнсфoрaминальная эпидурaльнaя, миoфaсциальная, блокада крестцово-подвздошного сочленения, межпозвонковых суставов и грушевидной мышцы. Выделены показания к их применению, а также важные тактические нюансы. Проведен анализ возможностей применения различных лекарственных препаратов в купировании вертеброгенной боли. Указаны вероятные риски их применения. В заключении авторы подчеркивают важность малоинвазивных интервенционных вмешательств в комплексном лечении вертеброгенного болевого синдрома

Letter of interest for a neutrino beam from Protvino to KM3NeT/ORCA

The Protvino accelerator facility located in the Moscow region, Russia, is in a good position to offer a rich experimental research program in the field of neutrino physics. Of particular interest is the possibility to direct a neutrino beam from Protvino towards the KM3NeT/ORCA detector, which is currently under construction in the Mediterranean Sea 40 km offshore Toulon, France. This proposal is known as P2O. Thanks to its baseline of 2595 km, this experiment would yield an unparalleled sensitivity to matter effects in the Earth, allowing for the determination of the neutrino mass ordering with a high level of certainty after only a few years of running at a modest beam intensity of ≈ 90 kW. With a prolonged exposure (≈1500 kWyear), a 2σ sensitivity to the leptonic CP-violating Dirac phase can be achieved. A second stage of the experiment, comprising a further intensity upgrade of the accelerator complex and a densified version of the ORCA detector (Super-ORCA), would allow for up to a 6σ sensitivity to CP violation and a 10º−17º resolution on the CP phase after 10 years of running with a 450 kW beam, competitive with other planned experiments. The initial composition and energy spectrum of the neutrino beam would need to be monitored by a near detector, to be constructed several hundred meters downstream from the proton beam target. The same neutrino beam and near detector set-up would also allow for neutrino-nucleus cross section measurements to be performed. A short-baseline sterile neutrino search experiment would also be possible

Measurement of the W+W- production cross section in p(p)over-bar collisions at root s=1.96 TeV using dilepton events

We present a measurement of the W+W- production cross section using 184 pb(-1) of p (p) over bar collisions at a center-of-mass energy of 1.96 TeV collected with the Collider Detector at Fermilab. Using the dilepton decay channel W+W-→ l(+)ν l(-)(ν) over bar, where the charged leptons can be either electrons or muons, we find 17 candidate events compared to an expected background of 5.0(-0.8)(+2.2) events. The resulting W+W- production cross-section measurement of σ(p (p) over bar → W+W-)=14.6(-5.1)(+5.8)(stat)(-3.0)(+1.8)(syst)± 0.9(lum) pb agrees well with the standard model expectation