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Abstract Endoscopic evaluation is the key to the management of ulcerative colitis (UC). However, there is interobserver variability in interpreting endoscopic images among gastroenterologists. Furthermore, it is time‐consuming. Convolutional neural networks (CNNs) can help overcome these obstacles and has yielded preliminary positive results. We aimed to develop a new CNN‐based algorithm to improve the performance for evaluation tasks of endoscopic images in patients with UC. A total of 12,163 endoscopic images from 308 patients with UC were collected from January 2014 to December 2021. The training set and test set images were randomly divided into 37,515 and 3191 after excluding possible interference and data augmentation. Mayo Endoscopic Subscores (MES) were predicted by different CNN‐based models with different loss functions. Their performances were evaluated by several metrics. After comparing the results of different CNN‐based models with different loss functions, High‐Resolution Network with Class‐Balanced Loss achieved the best performances in all MES classification subtasks. It was especially great at determining endoscopic remission in UC, which achieved a high accuracy of 95.07% and good performances in other evaluation metrics with sensitivity 92.87%, specificity 95.41%, kappa coefficient 0.8836, positive predictive value 93.44%, negative predictive value 95.00% and area value under the receiver operating characteristic curve 0.9834, respectively. In conclusion, we proposed a new CNN‐based algorithm, Class‐Balanced High‐Resolution Network (CB‐HRNet), to evaluate endoscopic activity of UC with excellent performance. Besides, we made an open‐source dataset and it can be a new benchmark in the task of MES classification.

Abstract Sacubitril/valsartan, simultaneously inhibits neprilysin and angiotensin II receptor, showed an effect in reducing blood pressure (BP). The authors aimed to study whether it can be used as an antihypertensive agent in patients with refractory hypertension who have already been treated. A total of 66 Chinese patients with refractory hypertension were enrolled. Patients received sacubitril/valsartan 200 instead of angiotensin II receptor blocker or angiotensin converting enzyme inhibitor while other agents continued. If BP was uncontrolled after 4 weeks, sacubitril/valsartan was increased to 400 mg. The BP reduction was evaluated by office BP and ambulatory BP monitoring after 8‐week treatment. The baseline office BP and mean arterial pressure (MAP) were 150.0/95.0 mmHg and 113.3 mmHg. BP and MAP reduced to 130.6/83.2 mmHg and 99.0 mmHg at week 8. Office BP and MAP reductions were 19.4/11.8 mmHg and 14.3 mmHg at endpoint (all p

Abstract Cadmium (Cd) is a high‐risk pathogenic toxin for hepatic diseases. Excessive mitophagy is a hallmark in Cd‐induced hepatotoxicity. However, the underlying mechanism remains obscure. Mitochondrial calcium uniporter (MCU) is a key regulator for mitochondrial and cellular homeostasis. Here, Cd exposure upregulated MCU expression and increased mitochondrial Ca2+ uptake are found. MCU inhibition through siRNA or by Ru360 significantly attenuates Cd‐induced excessive mitophagy, thereby rescues mitochondrial dysfunction and increases hepatocyte viability. Heterozygous MCU knockout mice exhibit improved liver function, ameliorated pathological damage, less mitochondrial fragmentation, and mitophagy after Cd exposure. Mechanistically, Cd upregulates MCU expression through phosphorylation activation of cAMP‐response element binding protein at Ser133(CREBS133) and subsequent binding of MCU promoter at the TGAGGTCT, ACGTCA, and CTCCGTGATGTA regions, leading to increased MCU gene transcription. The upregulated MCU intensively interacts with voltage‐dependent anion‐selective channel protein 1 (VDAC1), enhances its dimerization and ubiquitination, resulting in excessive mitophagy. This study reveals a novel mechanism, through which Cd upregulates MCU to enhance mitophagy and hepatotoxicity.

Abstract Concurrent natural evolution of glyphosate resistance single‐ and double‐point EPSPS mutations in weed species provides an opportunity for the estimation of resistance fitness benefits and prediction of equilibrium resistance frequencies in environments under glyphosate selection. Assessment of glyphosate resistance benefit was conducted for the most commonly identified single Pro‐106‐Ser and less‐frequent double TIPS mutations in the EPSPS gene evolved in the global damaging weed Eleusine indica. Under glyphosate selection at the field dose, plants with the single Pro‐106‐Ser mutation at homozygous state (P106S‐rr) showed reduced survival and compromised vegetative growth and fecundity compared with TIPS plants. Whereas both homozygous (TIPS‐RR) and compound heterozygous (TIPS‐Rr) plants with the double TIPS resistance mutation displayed similar survival rates when exposed to glyphosate, a significantly higher fecundity in the currency of seed number was observed in TIPS‐Rr than TIPS‐RR plants. The highest plant fitness benefit was associated with the heterozygous TIPS‐Rr mutation, whereas plants with the homozygous Pro‐106‐Ser and TIPS mutations exhibited, respectively, 31% and 39% of the fitness benefit revealed by the TIPS‐Rr plants. Populations are predicted to reach stable allelic and genotypic frequencies after 20 years of glyphosate selection at which the WT allele is lost and the stable genotypic polymorphism is comprised by 2% of heterozygous TIPS‐Rr, 52% of homozygous TIPS‐RR and 46% of homozygous P106S‐rr. The high inbreeding nature of E. indica is responsible for the expected frequency decrease in the fittest TIPS‐Rr in favour of the homozygous TIPS‐RR and P106S‐rr. Mutated alleles associated with the glyphosate resistance EPSPS single EPSPS Pro‐106‐Ser and double TIPS mutations confer contrasting fitness benefits to E. indica under glyphosate treatment and therefore are expected to exhibit contrasting evolution rates in cropping systems under recurrent glyphosate selection.

Abstract The genetically engineered chimeric antigen receptor T cell (CAR‐T) therapy has shown remarkable clinical efficacy in the treatment of hematological malignancies. Nonetheless, it is difficult to harvest adequate autologous T cells to manufacture potent CAR‐T cell products in patients with high tumor burden and prior tumor‐reductive treatment. Here we reported a relapsed/refractory acute lymphoblastic leukemia patient with high leukemia burden and central nervous system (CNS) involvement. The patient responded to donor‐derived HLA‐matched allogeneic CAR‐T treatment, with the achievement of quick complete remission. And for the first time, we revealed the development of a cerebral CRS in situ after allogeneic CAR‐T therapy.

Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation (ALFF) is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the treatment of brain diseases and other fields. However, due to the low accuracy of the current analysis methods for low frequency signal extraction of ALFF, we propose the Fourier-based synchrosqueezing transform (FSST), which is often used in the field of signal processing to extract the ALFF of the low frequency power spectrum of the whole-time dimension. The low frequency characteristics of the extracted signal are compared with those of FSST and fast Fourier transform (FFT) through the resting-state data. It is clear that the signal extracted by FSST has more low frequency characteristics, which is significantly different from FFT.

This study aimed to compare the prevalence of hypertension between the island and rural residents in Dalian, China, and to explore associated risk factors of hypertension in order to provide evidence for the establishment of targeted strategy of hypertension prevention and treatment for island and rural residents. The modified MONICA questionnaire survey was performed on 7764 island and rural residents aged ≥40 years (including 2652 island residents and 5112 rural residents). Our data showed that totally weighted prevalence of hypertension was significantly higher in rural residents than in island residents (61.9% vs. 55.2%, P

Background. High-resolution impedance manometry (HRIM) can calculate the bolus motion parameters and the ratio of complete esophageal transit besides the conventional esophageal dynamic parameters; therefore, we could better manage the patients with nonobstructive dysphagia (NOD) clinically. Aim. To analyze the HRIM parameter results of NOD patients and evaluate the characteristics of their esophageal motility and transit function. Methods. In total, 58 NOD patients were assessed and the clinical diagnoses were determined. HRIM was performed, and both conventional high-resolution manometry and esophageal transit parameters were analyzed. Results. In 58 NOD patients, 28 patients had achalasia, 3 esophagogastric junction outflow obstruction, and 20 nonspecific esophageal motility disorders, and 7 were normal. Impedance results demonstrated that all the patients with achalasia exhibited incomplete esophageal transit (ICET), three patients with esophagogastric junction outflow obstruction showed ICET, and the average bolus transit time (BTT) was 6.6 ± 1.2 sec. In 20 nonspecific esophageal motility disorders, 13 patients with gastroenterologly reflux disease (GERD) presented ineffective esophageal motility and fragmented peristalsis, and 65.0% swallows had exhibited ICET. However, 49.1% swallows of 7 nonspecific esophageal motility disorder patients with non-GERD had exhibited ICET. The average BTT in 13 GERD patients was longer than that in the non-GERD patients (8.1 ± 1.1 sec versus 5.5 ± 0.3 sec, P

A series of surfactive amphiphilic polymer PAADs were prepared from the copolymerization of sodium acrylate, dodecyl polyoxyethylene acrylate (DPA, a surfmer), and acrylamide under the action of a mixed initiating agent consisting of ammonium persulfate-sodium bisulfite/2,2′-azobis[2-(2-imidazolin-2-yl) propane] dihydrochloride. The aggregative behaviors of PAADs were explored by 13C nuclear magnetic resonance, a viscometer, and a surface tension instrument. It was found that the apparent viscosity and surface activity of PAADs were significantly improved by the increase of average sequence length of hydrophobic micro blocks, strong intermolecular hydrophobic association, or the formation of mixed micelles between hydrophobic micro blocks and micromolecular surface-active agent. The introduction of long-chain alkyls on molecular chains prolonged the average sequence length of hydrophobic micro blocks in molecular chains and enhanced the hydrophobic association between molecular chains and the tight arrangement of molecular chains on water surfaces, thereby increasing the surface activity. Moreover, the anionic monomer sodium acrylate on molecular chains, via electrostatic repulsion, promoted the conversion from intrachain association to intermolecular association and thereby facilitated the formation of dense interfacial films, enhancing the surface activity of water solutions. Then, the anion surfmer sodium dodecylbenzenesulfonate interacted with the hydrophobic micro blocks on the molecular chains to form mixed micelles, which accelerated the interchain association and enhanced the polymer surface activity. The novel polymeric micelle with higher viscosifying ability and surface activity was expected to be a promising oil drive agent for tertiary oil recovery.

Microspheres have excellent sealing performances such as injectivity, bridging-off, deep migration, and deformation performances, but their plugging effects are limited by the fast swelling rate and poor viscoelasticity. In this study, we synthesized a novel modified microsphere with polymerizable surfactant monomers and cationic monomers. We investigated the influence factors on the swelling performance and rheological properties of the microspheres and explored the ways to improve the plugging performance of hydrophobic-associating microspheres. The association behaviors in aqueous media of poly(acrylamide-co-methacry loyloxyethyl trimethyl ammonium chloride-co-n-dodecyl poly(etheroxy acrylate) P(AM-DMC-DEA) are proven to be mediated by the DEA content. Moreover, the hydrophobic association interaction has a strong effect on the performance of microspheres such as swelling properties, the rheological performance, and plugging properties. The swelling properties of microsphere studies exhibited the slow swelling rate. The rheological performance measurements showed significant improvements; yield stress, and creep compliance increased rapidly from 404 to 2060 Pa and 3.89 × 10−4 to 1.41 × 10−2 1/Pa, respectively, with DEA content in microspheres rising from 0.0% to 0.22%. The plugging properties of microspheres were enhanced by the slow swelling performance and good viscoelasticity.

As WSNs gain popularity, they are becoming more and more necessary for traffic anomaly detection. Because worms, attacks, intrusions, and other kinds of malicious behaviors can be recognized by traffic analysis and anomaly detection, WSN traffic anomaly detection provides useful tools for timely reaction and appropriate prevention in network security. In the paper, we improve exploitation of GM(1,1) model to make traffic prediction and judge the traffic anomaly in WSNs. Based on our systematical researches on the characteristics of WSN traffic, the causes of WSN abnormal traffic, and latest related research and development, we better exploit the GM(1,1) model following four guidelines: using a sliding window to determine historical data for modeling, optimizing initial value of one-order grey differential equation, making traffic prediction by short step exponential weighted average method, and judging whether the traffic of the next moment is abnormal by Euclidean distance. Then, we propose a traffic anomaly detection algorithm for WSNs based on the improved exploitation of GM(1,1) model. Simulation results and comparative analyses demonstrate that our proposed WSN traffic anomaly detection algorithm can reduce the undetected rate and has better anomaly detection accuracy than traditional traffic anomaly detection algorithms.

Traffic anomaly detection is emerging as a necessary component as wireless networks gain popularity. In this paper, based on the improved Autoregressive Integrated Moving Average (ARIMA) model, we propose a traffic anomaly detection algorithm for wireless sensor networks (WSNs) which considers the particular imbalanced, nonstationary properties of the WSN traffic and the limited energy and computing capacity of the wireless sensors at the same time. We systematically analyze the characteristics of WSN traffic, the causes of WSN abnormal traffic, and the latest related research and development. Specifically, we improve the traditional time series ARIMA model to make traffic prediction and judge the traffic anomaly in a WSN. Simulated and real WSN traffic data gathered from University of North Carolina are used to carry out simulations on Matlab. Simulation results and comparative analyses demonstrate that our proposed WSN traffic anomaly detection scheme has better anomaly detection accuracy than traditional traffic anomaly detection algorithms.