Minimum Minutes Machine-Learning Microfluidic Microbe Monitoring Method (M7).

Frequent outbreaks of viral diseases have brought substantial negative impacts on society and the economy, and they are very difficult to detect, as the concentration of viral aerosols in the air is low and the composition is complex. The traditional detection method is manually collection and re-detection, being cumbersome and time-consuming. Here we propose a virus aerosol detection method based on microfluidic inertial separation and spectroscopic analysis technology to rapidly and accurately detect aerosol particles in the air. The microfluidic chip is designed based on the principles of inertial separation and laminar flow characteristics, resulting in an average separation efficiency of 95.99% for 2 µm particles. We build a microfluidic chip composite spectrometer detection platform to capture the spectral information on aerosol particles dynamically. By employing machine-learning techniques, we can accurately classify different types of aerosol particles. The entire experiment took less than 30 min as compared with hours by PCR detection. Furthermore, our model achieves an accuracy of 97.87% in identifying virus aerosols, which is comparable to the results obtained from PCR detection.

Multifunctional Carbon Nanodots for Antibacterial Enhancement, pH Change, and Poisonous Tin(IV) Specifical Detection.

In recent years, antibiotic-based carbon nanodots have been extensively developed and studied, because of their excellent synergistic fluorescence and antibacterial properties. These antibacterial carbon nanodots have also been developed with various new applications, such as heavy iron detection, pH sensitivity, temperature response, and bacterial count detection in various environments. In this article, using vancomycin hydrochloride as the only precursor, vancomycin hydrochloride carbon nanodots were rapidly synthesized by a one-step microwave method. The diameter of the vancomycin hydrochloride carbon nanodots was concentrated at 0.899 ± 0.40 nm with a uniform size and excitation-dependent fluorescence. Vancomycin hydrochloride carbon nanodots showed better antibacterial activity than the original vancomycin hydrochloride with low biological toxicity and good stability. In the pH range of approximately 7-13, there was a good linear relationship between the fluorescence intensity of the carbon nanodots and the pH value (R2 = 0.98516). Moreover, vancomycin hydrochloride carbon nanodots could quickly and specifically detect poisonous Sn4+ through changes in their fluorescence intensity, with a detection limit of approximately 5.2 µM. Multifunctional vancomycin hydrochloride carbon nanodots have good application prospects in the fields of antibacterial, toxic Sn4+ detection, and pH-sensitive aspects.

Carbon nanodots constructed by ginsenosides and their high inhibitory effect on neuroblastoma.

BACKGROUND: Neuroblastoma is one of the common extracranial tumors in children (infants to 2 years), accounting for 8 ~ 10% of all malignant tumors. Few special drugs have been used for clinical treatment currently. RESULTS: In this work, herbal extract ginsenosides were used to synthesize fluorescent ginsenosides carbon nanodots via a one-step hydrothermal method. At a low cocultured concentration (50 µg·mL- 1) of ginsenosides carbon nanodots, the inhibition rate and apoptosis rate of SH-SY5Y cells reached ~ 45.00% and ~ 59.66%. The in vivo experiments showed tumor volume and weight of mice in ginsenosides carbon nanodots group were ~ 49.81% and ~ 34.14% to mice in model group. Since ginsenosides were used as sole reactant, ginsenosides carbon nanodots showed low toxicity and good animal response. CONCLUSION: Low-cost ginsenosides carbon nanodots as a new type of nanomedicine with good curative effect and little toxicity show application prospects for clinical treatment of neuroblastoma. It is proposed a new design for nanomedicine based on bioactive carbon nanodots, which used natural bioactive molecules as sole source.

Adaptive control for downhole nuclear magnetic resonance excitation.

Nuclear magnetic resonance (NMR) measurements are performed with the pulse sequence and acquisition parameters set by the operator, which cannot be adjusted in real time according to sample characteristics. In one acquisition cycle, usually thousands of high-power pulses are transmitted and thousands of echo points are acquired. The power consumption cause the RF amplifier to overheat, and large amounts of acquired data may be invalid. Therefore, the optimization of excitation and acquisition processes is necessary to improve measurement efficiency. We explore a scheme for the real-time measurement of the samples by adaptively regulating the pulse sequence, which adapts the variable TE pulse sequence as the reconnaissance mode. The appropriate pulse sequence and reasonable parameters (NE, TE) can be selected according to the relaxation characteristics of the samples.This adaptive control strategy has great significance in guiding both dynamic and static measurements, and it is especially suitable for occasions where low magnetic field gradients and diffusion terms can be ignored. We also design a test circuit for adaptive control, which has the function of automatic parameter adjustment. By adjusting parameters such as the number of refocusing pulses, echo spacing, etc., the effective measurement of the samples can be achieved in practice.

A study on multi-exponential inversion of nuclear magnetic resonance relaxation data using deep learning.

Nuclear magnetic resonance (NMR) is a powerful tool for formation evaluation in the oil industry to determine parameters, such as pore structure, fluid saturation, and permeability of porous materials, which are critical to reservoir engineering. The inversion of the measured relaxation data is an ill-posed problem and may lead to deviations of inversion results, which may degrade the accuracy of further data analysis and evaluation. This paper proposes a deep learning method for multi-exponential inversion of NMR relaxation data to improve accuracy. Simulated NMR data are first constructed using a priori knowledge based on the signal parameters and Gaussian distribution. These data are then used to train the neural network designed to consider noise characteristics, signal decay characteristics, signal energy variations, and non-negative features of the T2 spectra. With the validation from simulated data, the models introduced by multi-scale convolutional neural network (CNN) and attention mechanism outperform other approaches in terms of denoising and T2 inversion. Finally, NMR measurements of rock cores are used to compare the effectiveness of the attention multi-scale convolutional neural network (ATT-CNN) model in practical applications. The results demonstrate that the proposed method based on deep learning has better performance than the regularization method.

CO2-Containing Reservoir Evaluation Based on the Joint Inversion of Nuclear Logs and Resistivity Logs: A Case Study of Ultrahigh-Temperature and High-Pressure Gas Reservoirs in the Yinggehai Basin, China.

Due to the unique characteristics of reservoirs in the Yinggehai Basin in the South China Sea, such as high temperature and high pressure (HPHT), low porosity, low permeability, complex pore structure, and high lime content, the log responses of these reservoirs have very complex characteristics, which makes it difficult to evaluate reservoir parameters accurately. In addition, most reservoirs in Ledong Block of the Yinggehai Basin in the South China Sea contain CO2, posing great difficulties for subsequent exploration and development. Accurate evaluation of CO2 layers is of paramount importance for the development of oil and gas fields. In this study, we used a method for the joint inversion of multiple well logs to evaluate the reservoirs and determine CO2 saturation level and other formation parameters. We optimized the joint inversion model based on the characteristics of the reservoirs in the Yinggehai Basin and adjusted the forward simulation model to consider the effects of high temperature and high pressure on gas density. In view of high lime content in the formations in this area, we adjusted the resistivity forward simulation model to consider the effect of lime content. The inversion results show that the values of porosity, permeability, and water saturation level obtained through inversion are largely consistent with the core data. The CO2 saturation level determined through joint inversion is 22%, which represents a deviation of less than 10% from the drilling system testing (DST) result, indicating that the joint inversion method is accurate. The error in the water saturation level determined through the joint inversion method is smaller than that in the calculated results from conventional multimineral inversion models. We performed forward simulation of the results calculated with the joint inversion method and compared the results of forward simulation with actual log curves. For the sandstone interval, the results of forward simulation are largely consistent with the actual log curves, indicating that the joint inversion method is accurate. In summary, the method presented in this paper can accurately determine reservoir parameters and provide strong support for the exploration and development of oil and gas fields in the Yinggehai Basin in the South China Sea.

Hyperprogressive Disease After Immunotherapy: A Case Report of Pulmonary Enteric Adenocarcinoma.

Primary pulmonary enteric adenocarcinoma (PEAC) is a rare invasive adenocarcinoma clinically similar to metastatic colorectal adenocarcinoma (MCRC). Although many studies have addressed the differential diagnosis of PEAC, few have described the treatment of PEAC, especially using immunotherapy. This report describes a 61-year-old man who presented initially with pain in the ribs. Pathological analysis of biopsy samples shows malignant tumors of the right pleura, and next-generation sequencing of 26 genes showed a KRAS gene mutation. Positron emission tomography-computed tomography (PET-CT) found no evidence of gastrointestinal malignancy. Due to multiple metastases, the patient could not undergo radical surgery. The patient was treated with a combination chemotherapy regimen of paclitaxel plus carboplatin, along with sindilizumab immunotherapy, but, after one cycle of treatment, the tumor showed a hyperprogressive state. The patient is still being monitored regularly. These findings indicate that chemotherapy combined with immunotherapy may be ineffective in the treatment of primary PEAC with positive driver genes.

Positron emission tomography imaging for the assessment of mild traumatic brain injury and chronic traumatic encephalopathy: recent advances in radiotracers.

A chronic phase following repetitive mild traumatic brain injury can present as chronic traumatic encephalopathy in some cases, which requires a neuropathological examination to make a definitive diagnosis. Positron emission tomography (PET) is a molecular imaging modality that has high sensitivity for detecting even very small molecular changes, and can be used to quantitatively measure a range of molecular biological processes in the brain using different radioactive tracers. Functional changes have also been reported in patients with different forms of traumatic brain injury, especially mild traumatic brain injury and subsequent chronic traumatic encephalopathy. Thus, PET provides a novel approach for the further evaluation of mild traumatic brain injury at molecular levels. In this review, we discuss the recent advances in PET imaging with different radiotracers, including radioligands for PET imaging of glucose metabolism, tau, amyloid-beta, γ-aminobutyric acid type A receptors, and neuroinflammation, in the identification of altered neurological function. These novel radiolabeled ligands are likely to have widespread clinical application, and may be helpful for the treatment of mild traumatic brain injury. Moreover, PET functional imaging with different ligands can be used in the future to perform large-scale and sequential studies exploring the time-dependent changes that occur in mild traumatic brain injury.

A Novel Conductive Antibacterial Nanocomposite Hydrogel Dressing for Healing of Severely Infected Wounds.

Wound infections are serious medical complications that can endanger human health. Latest researches show that conductive composite materials may make endogenous/exogenous electrical stimulation more effective, guide/comb cell migration to the wound, and subsequently promote wound healing. To accelerate infected wound healing, a novel medical silver nanoparticle-doped conductive polymer-based hydrogel system (Ag NPs/CPH) dressing with good conductivity, biocompatibility, and mechanical and antibacterial properties was fabricated. For the hydrogel dressing, Ag NPs/CPH, polyvinyl alcohol (PVA), and gelatin were used as the host matrix materials, and phytic acid (PA) was used as the cross-linking agent to introduce conductive polyaniline into the matrix, with antibacterial Ag NPs loaded via impregnation. After a series of analyses, the material containing 5 wt% of PVA by concentration, 1.5 wt% gelatin, 600 µL of AN reactive volume, and 600 µL of PA reactive volume was chosen for Ag NPs/CPH preparation. XPS and FTIR analysis had been further used to characterize the composition of the prepared Ag NPs/CPH. The test on the swelling property showed that the hydrogels had abundant pores with good water absorption (≈140% within 12 h). They can be loaded and continuously release Ag NPs. Thus, the prepared Ag NPs/CPH showed excellent antibacterial property with increasing duration of immersion of Ag NPs. Additionally, to evaluate in vivo safety, CCK-8 experiments of HaCat, LO2 and 293T cells were treated with different concentrations of the Ag NPs/CPH hydrogel soaking solution. The experimental results showed the Ag NPs/CPH had no significant inhibitory effect on any of the cells. Finally, an innovative infection and inflammation model was designed to evaluate the prepared Ag NPs/CPH hydrogel dressing for the treatment of severely infected wounds. The results showed that even when infected with bacteria for long periods of time (more than 20 h), the proposed conductive antibacterial hydrogel could treat severely infected wounds.

Optimization of shaped pulses for radio frequency excitation in NMR logging.

The radio frequency (RF) excitation pulse of the nuclear magnetic resonance (NMR) logging tool can realize slice measurement by designing shaped pulses. In the case of a certain main magnetic field, the accuracy of the shaped pulse design has a very important impact on the signal-to-noise ratio (SNR) of the NMR signal and the measurement of the short relaxation signal. Hard pulse excitation will produce an undesirable infinite number of side lobes that may perturb the spins in unwanted regions. Soft pulse can achieve selective excitation and has a better slice profile and shorter energy release time while it is not conducive to the measurement of short relaxation signals. This article focuses on the design of shaped pulses in extreme downhole environments and analyzes the characteristics of the three shaped pulses in the two cases of equivalent bandwidth and equivalent pulse duration. At the same time, a kind of RF-shaped pulse transmitting circuit with phase difference control is realized. According to the pulse type optimization strategy, the appropriate shaped pulse is selected. When echo spacing (TE) >0.6 ms, the SNR can be increased to more than 12%. When TE is small, it will automatically switch to the hard pulse mode, which is good for short relaxation measurement.

Adsorption and migration of heavy metals between sediments and overlying water in the Xinhe River in central China.

Long-term polluted rivers often lead to the accumulation of heavy metals in sediments. Anthropogenic activities or biological disturbances break the adsorption balance, causing them to return from the bottom mud to the overlying water and change the aquatic environment. In order to understand the variation of heavy metals between sediments and river water, we collected the riverbed sediments in the polluted Xinhe River and carried out static continuous infiltration and dynamic uninterrupted disturbance experiments. The leaching experiment shows that the absorbability of Cd and Pb is stronger than Cr in the sediment; at the same time, the properties of the medium have a great influence on the adsorption of heavy metals. The disturbance can prompt heavy metals in the sediment to resuspend into the overlying water. The impact is the greatest during the first 12 h, and the influence degree is stronger in the relatively static water than in the moving river. In addition, pH and other factors have different degrees of influence on the desorption of heavy metals.

Borehole Nuclear Magnetic Resonance Study at the China University of Petroleum.

The research of borehole nuclear magnetic resonance (NMR) began in the 1950 s, but the maturity and large-scale applications of relevant instruments started in the mid-1990. To date, borehole NMR is an important means for borehole in-situ analysis and oil and gas evaluation, which significantly improves the success rate of exploration and the evaluation accuracy of oil and gas reservoirs. Its development has also contributed importantly to low-field and industrial NMR theories and experimental methodologies. Companies and individuals in the United States, China and other countries have developed the capabilities to engineer and deploy borehole NMR instruments and measurements independently. NMR imaging and evaluation of heterogeneous reservoirs and unconventional oil and gas are worldwide problems, involving the innovation of borehole NMR and the advanced manufacture of instruments and equipment. The commercial technology of borehole oil and gas exploration is highly competitive and proprietary. It is difficult to gain full insight into the details of the technologies and development from published literatures. Based on the research of the author's NMR laboratory at the China University of Petroleum (CUP), this paper reviews the core technologies of borehole NMR and its applications, discusses selected important issues that have not been fully solved, and looks forward to the direction and prospects of future development.

Transparent Conductive Supramolecular Hydrogels with Stimuli-Responsive Properties for On-Demand Dissolvable Diabetic Foot Wound Dressings.

Diabetic foot ulcers (DFU) remain a very considerable health care burden, and their treatment is difficult. Hydrogel-based wound dressings are appealing to provide an optimal environment for wound repair. However, the currently available hydrogel dressings still need surgical or mechanical debridement from the wound, causing reinjury of the newly formed tissues, wound infection, delayed healing time, and personal suffering. Additionally, to meet people's increasing demand, hydrogel wound dressings with improved performance and multifunctionality are urgently required. Here, a new multifunctional supramolecular hydrogel for on-demand dissolvable diabetic foot wound dressings is designed and constructed. Based on multihydrogen bonds between hydrophilic polymers, the resultant supramolecular hydrogels present controlled and excellent properties, such as good transparency, antibacterial ability, conductive, and self-healing properties. Thus, the supramolecular hydrogels improve the new tissue formation and provide a significant therapeutic effect on DFU by inducing angiogenesis, enhancing collagen deposition, preventing bacterial infection, and controlling wound infection. Remarkably, the resultant hydrogels also exhibit stimuli-responsive ability, which renders its capability to be dissolved on-demand, allowing for a facile DFU dressing removal. This multifunctional supramolecular hydrogel may provide a novel concept in the design of on-demand dissolvable wound dressings.

Design of a new LWD NMR tool with high mechanical reliability.

Nuclear magnetic resonance (NMR) provides useful information for formation evaluation on pore size and pore volume. Depending on field operations, there are two types of borehole NMR: wireline logging and logging-while-drilling (LWD). The latter type is more convenient. But due to the high mechanical failure risk caused by insufficient mechanical strength of the tool and vibrations during measurement, the quality of LWD NMR measurements are severely affected. In this paper, to enable high reliability and vibration tolerance, we propose a new design and implement a new LWD NMR tool, whose features includes a double hollow cylindric magnet (DHCM) structure and a solenoid-optimized antenna. The DHCM structure greatly reduces the proportion of the magnet in the cross-section of the tool without reducing B0 field strength. Thus, the mechanical strength and the reliability of the tool is greatly improved. The antenna is improved by optimizing the parameters of each coil of the solenoid for finding the generated B1 distribution best matching B0. The new design has a saddle sensing area in the axial and radial plane with a width greater than 50 mm, which is wide enough to ensure the validity of the T2 measurement under strong vibrations. We had demonstrated that this new tool performs well when TE = 0.6 ms, ensuring the measurement richness is suitable for LWD prospecting for unconventional oil and gas reservoirs. Besides, this design is suitable for that in slim holes.

Core-Shell Nanohydrogels with Programmable Swelling for Conformance Control in Porous Media.

Conformance control during waterflooding in an oil reservoir is utilized to redistribute water and increase the sweep efficiency and hence oil production. Using preformed gel particles can effectively redirect the flow by blocking the high-permeability zones and forcing water into low-permeability zones where the oil is trapped. However, the size of such gel particles can limit their applications deeper within the reservoir and can result in shear-induced degradation near the well bore. Here, we fabricate core-shell nanohydrogels with delayed swelling behavior; their volume increases by a factor of 200 after about 30 days in brine under reservoir conditions. We study their effect on the flow behavior in a three-dimensional porous medium micromodel consisting of randomly packed glass beads. Using confocal microscopy, we directly visualize the spatial variations of flow in the micromodel before and after nanohydrogel injection and swelling. The swollen nanohydrogels block some pores reducing the permeability of the micromodel and diverting the water into low-permeability regions. A core flood experiment further confirms that the nanohydrogels can significantly reduce the permeability of a reservoir sample and divert the fluid flow. Our results demonstrate that these core-shell nanohydrogels might be useful for flow control in porous media and can be used as a conformance control agent.

Inside-out azimuthally selective NMR tool using array coil and capacitive decoupling.

Inside-out nuclear magnetic resonance (NMR) is a unique technique for investigating large in-situ objects outside of tools, to provide pore structure and pore-bearing fluids properties. However, in borehole, objects towards azimuthal orientations pose different properties, referred to as azimuthal spatial heterogeneity. This may lead to ambiguous evaluations by utilizing present inside-out NMR measurement, which hardly resolves azimuthal information and loses the location information of oil/gas. In this paper, we for the first time design and construct an innovative tool to investigate the heterogeneity of large in-situ samples. The most key component, array coil, which performs with azimuthal selection, measurement consistency and interactive isolation, configured in this novel tool to capture heterogeneity information. Whereas, strong coupling between neighboring coil elements largely decrease the coil sensitivity. Capacitive decoupling network is bridged into adjacent ports without segmenting coils to be decoupled and could be easily adjusted by electrical relays. The coil model and numerical simulation are firstly given to demonstrate the array coil configuration, B1 field map and mutual coupling effects on coil sensitivity. Capacitive network is then introduced to be theoretically and practically analyzed to minimize coupling effects. Simulation and experimental results demonstrate that these coil elements have excellent consistency and independence to feasibly acquire the azimuthal NMR data.

[Corrigendum] Involvement of endothelial nitric oxide synthase pathway in IGF­1 protects endothelial progenitor cells against injury from oxidized LDLs.

Subsequently to the publication of this article, the authors have realized that the name of the first author was spelt incorrectly: The name was spelt as 'Hao­jing Wen', whereas the name should have been presented as 'Jing­wen Hao. The name as it should have appeared in the author list is featured above. The authors regret that this this error was not corrected prior to the publication of the above article, and apologize to the author in question and to the readership for any inconvenience caused.[the original article was published in Molecular Medicine Reports 19: 660­666, 2019; DOI:10.3892/mmr.2018.9633].

Polystyrene@poly(ar-vinylbenzyl)trimethylammonium-co-acrylic acid core/shell pH-responsive nanoparticles for active targeting and imaging of cancer cell based on aggregation induced emission.

Doubly charged pH-responsive core/shell hydrogel nanoparticles with green fluorescence were prepared and were shown to be viable bioprobes for active targeting tumor tissue and imaging of cancer cells. Via emulsionfree copolymerization hydrogel nanoparticles as VANPs were prepared, the core of which was polystyrene (Ps) and the shell was comprised of strongly positive electrolyte (ar-vinylbenzyl)trimethylammonium (VBTAC) with weak negative electrolyte acrylic acid (AA). Through conventional amidation, the shell was conjugated with cell-specific folic acid (FA), denoted as VANPs-FA. Then, negatively charged sulfonated 9,10-distyrylanthracene derivatives (SDSA) based on aggregation induced emission (AIE), was binding tightly to positively charged VBTAC of VANPs-FA shell. The prepared double charged fluorescent core/shell hydrogel nanoparticles abbreviated as VANPs-FS, showed excitation/emission wavelengths at ~420/528 nm. Dynamic light scattering (DLS) measurements were performed to determine the size and surficial zeta potential of VANPs-FS. Under proper ratio of VBTAC to AA, the VANPs-FS was stable (~ 64.63 nm, -20.2 mV) at high pH (> 7), started to aggregate (~ 683.0 nm, -3.2 mV) at pH around 6, and can redispers at low pH (< 5). The MTT analysis proved that VANPs-FS had good biocompatibility and low cytotoxicity. The targeting effectiveness of VANPs-FS was confirmed by confocal laser scanning microscopy (CLSM). Graphical abstract Detailed synthetic route of VANPs-FS (top) and schematic cancer tumor-target aggregation of pH-sensitive VANPs-FS with enhanced retention and rapid cancer cell imaging (bottom).

Optimization of multidimensional MR data acquisition for relaxation and diffusion.

Multidimensional MR experiments of relaxation and diffusion have been successful for material characterization and have attracted attention recently for biomedical applications. However, such experiments typically require many scans of data acquisition and are time-consuming. This work discusses a method for systematic optimization of the pulse-sequence parameters to obtain optimal resolution within the experimental conditions, such as the number of acquisitions. Other optimization goals can also be incorporated in this framework.

A novel two-dimensional NMR relaxometry pulse sequence for petrophysical characterization of shale at low field.

Low field two-dimensional nuclear magnetic resonance (2D-NMR) relaxometry is a powerful probe for the characterization of heterogenous, porous media and provides geometrical, physical and chemical information about samples at a molecular level and has been widely used in shale studies. However, NMR signals of shale decay so rapidly, dry sample for particular, that the conventional two-dimensional pulse sequence is either not sensitive enough to short relaxation components or takes too much measurement time. In this paper, 2D-NMR relaxometry correlation based on partial inversion recovery CPMG (PIR-CPMG) pulse sequence is proposed and illustrated to improve the contrast over saturation recovery CPMG (SR-CPMG) and reduces the T1 encoding time of inversion recovery CPMG (IR-CPMG) for petrophysical characterization of shale. Subsequently, the kernel function and inversion method of this sequence are presented and the reliability of the inversion method is testified by numerical simulation. Next, theoretical analysis is conducted to validate the advantages of PIR-CPMG. Ultimately, experiments on copper sulfate solution, artificial sandstone, and shale samples are performed, respectively, to verify the feasibility and effectiveness of the proposed pulse sequence. The results demonstrate that the PIR-CPMG sequence is time-saving and high-contrast, especially for the short relaxation components. This pulse sequence can be utilized in bench-top NMR core analyzer and downhole well logging, potentially, to achieve integrated petrophysical characterization of shale.