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Abstract Background Lumbar puncture is challenging for patients with scoliosis. Previous ultrasound-assisted techniques for lumbar puncture used the angle of the probe as the needle trajectory; however, reproducing the angle is difficult and increases the number of needle manipulations. In response, we developed a technique that eliminated both the craniocaudal and lateromedial angulation of the needle trajectory to overall improve this technique. We assessed the feasibility and safety of this method in patients with scoliosis and identify factors related to difficult lumbar puncture. Methods Patients with spinal muscular atrophy and scoliosis who were referred to the anesthesia department for intrathecal nusinersen administrations were included. With a novel approach that utilized patient position and geometry, lumbar puncture was performed under ultrasound guidance. Success rates, performance times and adverse events were recorded. Clinical-demographic and spinal radiographic data pertaining to difficult procedures were analyzed. Results Success was achieved in all 260 (100%) lumbar punctures for 44 patients, with first pass and first attempt success rates of 70% (183/260) and 87% (226/260), respectively. Adverse events were infrequent and benign. Higher BMI, greater skin dural sac depth and smaller interlaminar size might be associated with greater difficulty in lumbar puncture. Conclusions The novel ultrasound-assisted horizontal and perpendicular interlaminar needle trajectory approach is an effective and safe method for lumbar puncture in patients with spinal deformities. This method can be reliably performed at the bedside and avoids other more typical and complex imaging such as computed tomography guided procedure.

Background: Escherichia coli is the most common gram-negative pathogen to cause neonatal infections. Contemporary virulence characterization and antimicrobial resistance (AMR) data of neonatal E. coli isolates in China are limited. Methods: A total of 159 E. coli strains isolated from neonates were collected and classified into invasive and non-invasive infection groups, according to their site of origin. The presence of virulence genes was determined using polymerase chain reaction (PCR). All the strains were subjected to antimicrobial susceptibility testing using the broth dilution method. Results: The top three virulence genes with the highest detection rates were fimH (90.6 %), iutA (88.7 %), and kspMT II (88.1 %). The prevalences of fyuA (p = 0.023), kpsMT K1 (p = 0.019), ibeA (p

ABSTRACTPiezoelectric semiconductors (PSs) have widespread applications in semiconductor devices due to the coexistence of piezoelectricity and semiconducting properties. It is very important to conduct a theoretical analysis of PS structures. However, the present of nonlinearity in the partial differential equations (PDEs) that describe those multi-field coupling mechanical behaviors of PSs poses a significant mathematical challenge when studying these PS structures. In this paper, we present a novel approach based on machine learning for solving multi-field coupling problems in PS structures. A physics-informed neural networks (PINNs) is constructed for predicting the multi-field coupling behaviors of PS rods with extensional deformation. By utilizing the proposed PINNs, we evaluate the multi-field coupling responses of a ZnO rod under static and dynamic axial forces. Numerical results demonstrate that the proposed PINNs exhibit high accuracy in solving both static and dynamic problems associated with PS structures. It provides an effective approach to predicting the nonlinear multi-field coupling phenomena in PS structures.

Abstract Background Although mid-thoracic epidural analgesia benefits patients undergoing major surgery, technical difficulties often discourage its use. Improvements in technology are warranted to improve the success rate on first pass and patient comfort. The previously reported ultrasound-assisted technique using a generic needle insertion site failed to demonstrate superiority over conventional landmark techniques. A stratified needle insertion site based on sonoanatomic features may improve the technique. Methods Patients who presented for elective abdominal or thoracic surgery requesting thoracic epidural analgesia for postoperative pain control were included in this observational study. A modified ultrasound-assisted technique using a stratified needle insertion site based on ultrasound images was adopted. The number of needle passes, needle skin punctures, procedure time, overall success rate, and incidence of procedure complications were recorded. Results One hundred and twenty-eight subjects were included. The first-pass success and overall success rates were 75% (96/128) and 98% (126/128), respectively. In 95% (122/128) of patients, only one needle skin puncture was needed to access the epidural space. The median [IQR] time needed from needle insertion to access the epidural space was 59 [47–122] seconds. No complications were observed during the procedure. Conclusions This modified ultrasound-assisted mid-thoracic epidural technique has the potential to improve success rates and reduce the needling time. The data shown in our study may be a feasible basis for a prospective study comparing our ultrasound-assisted epidural placements to conventional landmark-based techniques.

BackgroundStatins were regarded as a main medication for managing hypercholesterolemia. Administration of statin therapy could reduce the incidence of cardiovascular disease in individuals diagnosed with type 2 diabetes mellitus (DM), which was recognized by multipal clinical guidelines. But previous studies had conflicting results on whether the long-term use of statins could benefit the renal function in diabetic patients.AimTo evaluate the association between statin treatment and Chronic Kidney Disease in DM patients.MethodsThis is a retrospective disproportionality analysis and cohort study based on real-world data. All DM cases reported in US Food and Drug Administration adverse event reporting system (FAERS) between the first quarter of 2004 and the fourth quarter of 2022 were included. Disproportionality analyses were conducted by estimating the reporting odds ratio (ROR) and the information component (IC). We further compared the CKD odds ratio (OR) between the statins group and the other primary suspected drug group among the included diabetes mellitus cases.ResultsWe finally included 593647 DM cases from FAERS, 5113 (5.31%) CKD cases in the statins group and 8810 (1.77%) CKD cases in the control group. Data analysis showed that the statins group showed a significant CKD signal (ROR: 3.11, 95% CI: 3.00–3.22; IC: 1.18, 95% CI: 1.07–1.29). In case group with two or more statins treatment history, the CKD signal was even stronger (ROR: 19.56, 95% CI: 18.10–21.13; IC: 3.70, 95% CI:3.44–3.93) compared with cases with one statin treatment history.ConclusionThe impact of statin therapy on the progression of renal disease in individuals diagnosed with type 2 diabetes mellitus (DM) remains inconclusive. After data mining on the current FAERS dataset, we discovered significant signals between statin treatment and CKD in diabetic patients. Furthermore, the incidence rate of CKD was higher among DM patients who used statins compared to those who did not.

Abstract Continuous cultivation of faba beans often results in a high occurrence of Fusarium wilt. Nevertheless, this issue can be successfully managed through wheat‐faba bean intercropping. Our objective is to elucidate the function of non‐host wheat in combating faba bean Fusarium wilt. We assessed the impact of wheat on the development of faba bean Fusarium wilt through field and pot experiments, and examined and identified the compounds in the root exudates of wheat. The influence of wheat root exudates on Fusarium commun mycelial growth and spore multiplication was investigated through indoor culture experiments. Wheat‐faba bean intercropping significantly reduced the occurrence of Fusarium wilt in field trials. Root separation experiments in pots indicated that wheat root exudates might play a vital role in this outcome. The exogenous addition of wheat root exudates to faba bean grown alone notably decreased the occurrence and severity of Fusarium wilt. Furthermore, the exogenous addition of wheat root exudates effectively hindered the growth and reproduction of Fusarium commun's mycelium. And, wheat root exudates contained six compounds with relatively high concentrations, including salicylic acid, p‐hydroxybenzoic acid, tartaric acid, malic acid, glutamic acid, and threonine, all of which inhibited the growth and spore formation of Fusarium commun. In a wheat‐faba bean intercropping system, these six compounds found in the root exudate of non‐host wheat can help control Fusarium wilt in faba bean by inhibiting the mycelial growth and sporulation of Fusarium commun.

Abstract Background The use of ultrasound has been reported to be beneficial in challenging neuraxial procedures. The angled probe is responsible for the main limitations of previous ultrasound-assisted techniques. We developed a novel technique for challenging lumbar puncture, aiming to locate the needle entry point which allowed for a horizontal and perpendicular needle trajectory and thereby addressed the drawbacks of earlier ultrasound-assisted techniques. Case presentation Patient 1 was an adult patient with severe scoliosis who underwent a series of intrathecal injections of nusinersen. The preprocedural ultrasound scan revealed a cephalad probe’s angulation (relative to the edge of the bed) in the paramedian sagittal oblique view, and then the probe was rotated 90° into a transverse plane and we noted that a rocking maneuver was required to obtain normalized views. Then the shoulders were moved forward to eliminate the need for cephalad angulation of the probe. The degree of rocking was translated to a lateral offset from the midline of the spine through an imaginary lumbar puncture’s triangle model, and a needle entry point was marked. The spinal needle was advanced through this marking-point without craniocaudal and lateromedial angulation, and first-pass success was achieved in all eight lumbar punctures. Patient 2 was an elderly patient with ankylosing spondylitis who underwent spinal anesthesia for transurethral resection of the prostate. The patient was positioned anteriorly obliquely to create a vertebral rotation that eliminated medial angulation in the paramedian approach. The procedure succeeded on the first pass. Conclusions This ultrasound-assisted paramedian approach with a horizontal and perpendicular needle trajectory may be a promising technique that can help circumvent challenging anatomy. Larger case series and prospective studies are warranted to define its superiority to alternative approaches of lumbar puncture for patients with difficulties.

BackgroundLifestyle modification based on exercise intervention is still the primary way to delay or reverse the development of diabetes in patients with prediabetes. However, there are still challenges in setting up a detailed exercise prescription for people with prediabetes. This study mainly ranks exercise prescriptions by comparing the improvement of glucose and lipid metabolism and the level of weight loss in patients.MethodAll studies on exercise intervention in prediabetes were identified by searching five electronic databases. Risk assessment and meta-analysis were performed on eligible studies.ResultsTwenty-four studies involving 1946 patients with prediabetes and seven exercise intervention models were included in the final analysis. The meta-analysis showed that exercise of any type was more effective for glycemic control in prediabetes than no exercise. However, the changes in blood glucose were moderate. In prediabetes, combining moderate-intensity aerobic exercise with low-to moderate-load resistance training showed the most significant improvements in glycosylated hemoglobin (HbA1c), body mass index (BMI), body weight (BW), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL) (P-score=0.82; 0.70; 0.87; 1; 0.99), low-to moderate-load resistance training showed the most significant improvements in fasting blood glucose (FBG) (P-score=0.98), the vigorous-intensity aerobic exercise showed the most significant improvements in 2-hour post-meal blood glucose (2hPG) and systolic blood pressure (SBP) (P-score=0.79; 0.78), and moderate-intensity aerobic exercise showed the most significant improvements in diastolic blood pressure (DBP) (P-score=0.78).ConclusionIn summary, moderate-intensity aerobic exercise, low-to moderate-load resistance training and the combination of both have beneficial effects on glycemic control, weight loss, and cardiovascular health in patients with prediabetes. These findings provide valuable guidance for rehabilitation clinicians and patients alike to follow.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42021284922.

Dissolution of lithium cobalt oxide (LCO) is the key step for the recovery of valuable metals (e.g., Co and Li) from spent LCO-based lithium-ion batteries (LIBs). However, the dissolution process of LCO either needs toxic solvents, and high temperature, or shows low efficiency. Deep eutectic solvents (DESs) are potential green solvents to dissolve LCO. Here, DESs with polyethylene glycol (PEG) as hydrogen bond acceptor and ascorbic acid (AA) as hydrogen bond donor are found to dissolve LCO with 84.2% Co leaching efficiency at 80 oC and 72 h, which is higher than that from the reported references by common DESs. Furthermore, both DESs components (i.e., PEG and AA) are cheap, biodegradable, and biocompatible. AA could be easily and abundantly extracted from natural fruits or vegetables. It provides a new guide for the green, mild, and efficient dissolution of LCO aiming at sustainable recovery of spent LIBs.

Coking wastewater is a typical organic refractory wastewater characterized by high chemical oxygen demand (COD), NH4+-N, and total organic carbon (TOC). Herein, coking wastewater was treated using a heterogeneous electro-Fenton (EF) system comprising a novel iron-loaded needle coke composite cathode (Fe-NCCC) and a dimensionally stable anode. The response surface methodology was used to optimize the reaction conditions. The predicted and actual COD removal rates were 92.13 and 89.96% under optimum conditions of an applied voltage of 4.92 V, an electrode spacing of 2.29 cm, and an initial pH of 3.01. The optimized removal rate of NH4+-N and TOC was 84.12 and 73.44%, respectively. The color of coking wastewater decreased from 250-fold to colorless, and the BOD5/COD increased from 0.126 to 0.34. Gas chromatography–mass spectrometry and Fourier transform infrared spectroscopy show that macromolecular heterocyclic organic compounds decomposed into straight-chain small molecules and even completely mineralized. The energy consumption of the EF process was 23.5 RMB Yuan per cubic meter of coking wastewater. The EF system comprising the Fe-NCCC can effectively remove pollutants from coking wastewater, has low electricity consumption, and can simultaneously reduce various pollution indicators with potential applications in the treatment of high-concentration and difficult-to-degrade organic wastewater. HIGHLIGHTS A novel needle coke composite cathode was fabricated to treat coking wastewater.; The maximum COD removal was ∼90% using an electro-Fenton process.; The COD, -N, and TOC removal rates were optimized using the Box–Behnken design.; Macromolecular organic matter in coking wastewater was degraded after treatment.;

A novel coordination polymer [Zn(atyha)2]n (1) (Hatyha = 2-(2-aminothiazole-4-yl)-2- hydroxyiminoacetic acid) was constructed by hydrothermal reaction of Zn2+ with Hatyha ligand. CP 1 exhibits a 2D (4,4)-connected topological framework with Schläfli symbol of {44·62}, where atyha− anions serve as tridentate ligands, bridging with Zn2+ through carboxylate, thiazole and oxime groups. CP 1 displays a strong ligand-based photoluminescence at 390 nm in the solid state, and remains significantly structurally stable in water. Interestingly, it can be utilized as a fluorescent probe for selective and sensitive sensing of Fe3+, Cr2O72− and MnO4− through the fluorescent turn-off effect with limit of detection (LOD) of 3.66 × 10−6, 2.38 × 10−5 and 2.94 × 10−6 M, respectively. Moreover, the efficient recyclability for detection of Fe3+ and Cr2O72− is better than that for MnO4−. The mechanisms of fluorescent quenching involve reversible overlap of UV-Vis absorption bands of the analytes (Fe3+, Cr2O72− and MnO4−) with fluorescence excitation and emission bands for CP 1, respectively.

This study examined the differences in the pausing behavior between native and non-native English speakers. Specifically, it examined the location and duration of pauses in relation to the syntactic and lexical complexity of the clauses in which these pauses occur and the nature of the prosodic phrasing of the utterances containing pauses. Speech samples from 10 native (L1) English and 10 Mandarin non-native English speakers from the Archive of L1 and L2 Scripted and Spontaneous Transcripts and Recordings (ALLSSTAR) were included in the analysis. The results showed that lower-level prosodic boundaries and syntactically complex phrases were associated with significantly longer pause duration in the L2 speech. Additionally, phrases with less frequent words tended to induce longer pauses. These findings suggest that insufficient knowledge of the L2 syntax, lexicon, and prosody might determine the location and duration of pauses and ultimately affect the speech fluency of L2 speakers.

The dataset described is an aspect-level sentiment analysis dataset for therapies, including medication, behavioral and other therapies, created by leveraging user-generated text from Twitter. The dataset was constructed by collecting Twitter posts using keywords associated with the therapies (often referred to as treatments). Subsequently, subsets of the collected posts were manually reviewed, and annotation guidelines were developed to categorize the posts as positive, negative, or neutral.The dataset contains a total of 5364 posts mentioning 32 therapies. These posts are further categorized manually into 998 (18.6%) positive, 619 (11.5%) negatives, and 3747 (69.9%) neutral sentiments. The inter-annotation agreement for the dataset was evaluated using Cohen's Kappa score, achieving an 0.82 score.The potential use of this dataset lies in the development of automatic systems that can detect users' sentiments toward therapies based on their posts. While there are other sentiment analysis datasets available, this is the first that encodes sentiments associated with specific therapies. Researchers and developers can utilize this dataset to train sentiment analysis models, natural language processing algorithms, or machine learning systems to accurately identify and analyze the sentiments expressed by consumers on social media platforms like Twitter.

New techniques are revolutionizing single-cell research, allowing us to study microbes at unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art technologies in single-cell analysis in microbial ecology applications, with particular attention to both optical tools, i.e., specialized use of flow cytometry and Raman spectroscopy and emerging electrical techniques. The objectives of this review include showcasing the diversity of single-cell optical approaches for studying microbiological phenomena, highlighting successful applications in understanding microbial systems, discussing emerging techniques, and encouraging the combination of established and novel approaches to address research questions. The review aims to answer key questions such as how single-cell approaches have advanced our understanding of individual and interacting cells, how they have been used to study uncultured microbes, which new analysis tools will become widespread, and how they contribute to our knowledge of ecological interactions.

Background The Fontan operation is associated with significant morbidity and premature mortality. Fontan cases cannot always be identified by International Classification of Diseases (ICD) codes, making it challenging to create large Fontan patient cohorts. We sought to develop natural language processing–based machine learning models to automatically detect Fontan cases from free texts in electronic health records, and compare their performances with ICD code–based classification. Methods and Results We included free‐text notes of 10 935 manually validated patients, 778 (7.1%) Fontan and 10 157 (92.9%) non‐Fontan, from 2 health care systems. Using 80% of the patient data, we trained and optimized multiple machine learning models, support vector machines and 2 versions of RoBERTa (a robustly optimized transformer‐based model for language understanding), for automatically identifying Fontan cases based on notes. For RoBERTa, we implemented a novel sliding window strategy to overcome its length limit. We evaluated the machine learning models and ICD code–based classification on 20% of the held‐out patient data using the F1 score metric. The ICD classification model, support vector machine, and RoBERTa achieved F1 scores of 0.81 (95% CI, 0.79–0.83), 0.95 (95% CI, 0.92–0.97), and 0.89 (95% CI, 0.88–0.85) for the positive (Fontan) class, respectively. Support vector machines obtained the best performance (P

Abstract Recently, Gao and Yao established the global existence and temporal decay rates of solutions for a system of compressible Hall-magnetohydrodynamic fluids (Gao and Yao in Discrete Contin. Dyn. Syst. 36: 3077–3106, 2016). However, because of the difficulty of derivative loss in the nonlinear terms, Gao and Yao could not provide the temporal decay for the highest-order derivatives of classical solutions. In this paper, motivated by the decomposition technique of both low and high frequencies of solutions in (Wang and Wen in Sci. China Math. 65: 1199–1228 2022), we further derive the temporal decay for the highest-order derivatives of the strong solutions. Moreover, the decay rate is optimal, since it agrees with the solutions of the linearized system.

Recent urbanization and growing food consumption have had a severely detrimental effect on the ecological environment of the Jianghan Plain. The ecological fragility of the Jianghan Plain must be continually monitored for environmental conservation and sustainable development. This study utilized principal component analysis (PCA) to quantitatively assess the ecological vulnerability of the Jianghan Plain based on the remote sensing ecological index (RSEI) and analyzed the space-time changes and drivers in the Jianghan Plain from 2000 to 2020 using the Google Earth Engine Platform (GEE). The findings of this research indicated that the ecological vulnerability of the Jianghan Plain from 2000 to 2020 was predominantly Moderate or Strong level. But still, the EVI displayed a changing decreasing trend, revealing a small development towards a healthier ecological environment. The most significant ecological vulnerability deterioration occurred between 2005 and 2010, accounting for roughly 44.90 percent, whereas the highest improvement occurred between 2000 and 2005, occupying approximately 37.52% of the area. Moran’s I of EVI was greater than 0 in Jianghan Plain and displayed a growing and subsequently a falling trend, representing that the spatial distribution of regional ecological vulnerability was strongly correlated and aggregated and that the degree of aggregation has declined. The effects of heat, greenness, wetness, and dryness on the ecological vulnerability of Jianghan Plain were all significant, with greenness and wetness being the primary determinants of the change in Jianghan Plain’s ecological vulnerability. The results of this study can offer a theoretical and scientific foundation for ecological protection and restoration in the Jianghan Plain. Meanwhile, this study also provides a practical and rapid method for monitoring regional ecological vulnerability using RSEI, GEE, and PCA, which can be applied elsewhere for ecological vulnerability evaluation.

Background: To investigate the effects of social factors including social support and social restriction on postpartum depression (PPD) during the COVID-19 pandemic. Methods: We conducted a systematic review with PubMed and Web of Science from 1 January 2020 to 1 April 2023. Articles focusing on social factors and PPD during COVID-19 pandemic were investigated. Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality Scale were used to evaluate quality of literatures. Results: We included 31 articles (22 cross-sectional studies and 9 cohort studies) with good quality. Edinburgh Postnatal Depression Scale (EPDS) was used as the preferred measure for defining PPD. Social support reduced the prevalence of developing PPD by 30%–40%. Social restriction increased the risk of PPD but there was lack of evidence or effective scales to define restriction. Conclusions: We found that social support acted as an important protective factor for PPD during the COVID-19 pandemic and that social restriction increased the risk of PPD. EPDS may be an optimal choice for researchers to define PPD. Obstetricians should underline social factors for both pregnancy women and their families. The study was registered on PROSPERO (https://www.crd.york.ac.uk/prospero/), registration number: CRD42023434485.

Abstract Recently, Hattori–Lagha established the global existence and asymptotic behavior of the solutions for a three-dimensional compressible chemotaxis system with chemoattractant and repellent (Hattori and Lagha in Discrete Contin. Dyn. Syst. 41(11):5141–5164, 2021). Motivated by Hattori–Lagha’s work, we further investigated the optimal time-decay rates of strong solutions with small perturbation to the three-dimensional Keller–Segel system coupled to the compressible Navier–Stokes equations, which models for the motion of swimming bacteria in a compressible viscous fluid. First, we reformulate the system into a perturbation form. Then we establish a prior estimates of solutions and prove the existence of the global-in-time solutions based on the local existence of unique solutions. Finally, we will establish the optimal time-decay rates of the nonhomogeneous system by the decomposition technique of both low and high frequencies of solutions as in (Wang and Wen in Sci. China Math., 2020, https://doi.org/10.1007/s11425-020-1779-7 ). Moreover, the decay rate is optimal since it agrees with the solutions of the linearized system.

【Objective】The research was carried out to scientifically evaluate the water conservation function of Hunchun Natural Forest Protection Project area, with a view to providing a basis for ensuring rational utilization of regional water resources and formulation of national ecological security policy.【Method】Based on the multi-period land resources statistics data, forest resources archives and meteorological data, the temporal and spatial dynamic characteristics of water conservation function after the implementation of Natural Forest Protection Project was explored based on InVEST model, and grey relational analysis was adopted to study the influencing factors of water conservation function.【Result】Since 2000, the area of forestland in Hunchun area has increased by 16 793.25 hm2; the water conservation of Natural Forest Protection Project in the first phase (2000-2010)has decreased by 5.67×108 m3 and decreased by 1.02×108 m3 in second phase (2010-2015), while it increased by 4.97×108 m3 during 2015-2020; water purification function has seen steady improvement though fluctuation existing, among which the mean outputs value of N and P have decreased from 0.1806 kg/hm2 to 0.1703 kg/hm2 per year and 0.0206 kg/hm2 to 0.0200 kg/hm2 per year in 20 years. Forest volume, precipitation and output value of primary industry have been the most influential indexes for water conservation function.【Conclusion】The implementation of Huinchun Natural Forest Protection Project has effectively improved the water conservation function, and the research results can provide support for scientific decision-making of the government, and strengthening of resource protection and management as well as public protection awareness.

Ulcerative Colitis (UC) is a chronic disease, in the progression of which an immune overreaction may play an important role. IL-22 is a member of the IL-10 superfamily of cytokines and is pleiotropic in immune regulation and inflammatory responses. IL-22 can produce protective effects, promote wound healing and tissue regeneration, while it can also induce inflammatory reactions when it is chronically overexpressed. Extensive literatures reported that IL-22 played an essential role in the pathogenic development of UC. IL-22 participates in the whole disease process of UC involving signaling pathways, gene expression regulation, and intestinal flora imbalance, making IL-22 a possible candidate for the treatment of UC. In this paper, the latest knowledge to further elucidate the role of IL-22 in UC was summarized and analyzed.

Background: Due to the high burden of chronic pain, and the detrimental public health consequences of its treatment with opioids, there is a high-priority need to identify effective alternative therapies. Social media is a potentially valuable resource for knowledge about self-reported therapies by chronic pain sufferers. Methods: We attempted to (a) verify the presence of large-scale chronic pain-related chatter on Twitter, (b) develop natural language processing and machine learning methods for automatically detecting self-disclosures, (c) collect longitudinal data posted by them, and (d) semiautomatically analyze the types of chronic pain-related information reported by them. We collected data using chronic pain-related hashtags and keywords and manually annotated 4,998 posts to indicate if they were self-reports of chronic pain experiences. We trained and evaluated several state-of-the-art supervised text classification models and deployed the best-performing classifier. We collected all publicly available posts from detected cohort members and conducted manual and natural language processing-driven descriptive analyses. Results: Interannotator agreement for the binary annotation was 0.82 (Cohen’s kappa). The RoBERTa model performed best (F1 score: 0.84; 95% confidence interval: 0.80 to 0.89), and we used this model to classify all collected unlabeled posts. We discovered 22,795 self-reported chronic pain sufferers and collected over 3 million of their past posts. Further analyses revealed information about, but not limited to, alternative treatments, patient sentiments about treatments, side effects, and self-management strategies. Conclusion: Our social media based approach will result in an automatically growing large cohort over time, and the data can be leveraged to identify effective opioid-alternative therapies for diverse chronic pain types.

Abstract As the basis of image processing, single image deraining has always been a significant and challenging issue. Due to the lack of real rainy images and corresponding clean images, most deraining networks are trained by synthetic datasets, which makes the output images unsatisfactory in real applications. Besides, note that a heavy rainfall is typically accompanied with some fog. Although some deraining networks have been proposed to remove the rain streaks in the rainy images, the output images may still be blurred due to the accompanied fog. In this paper, these problems existing in single image deraining is comprehensively considered, and propose a Cycle‐Derain network based on an unsupervised attention‐guided mechanism. Specifically, the Cycle‐Derain network takes advantage of generative adversarial networks with two mappings and the cycle consistency loss to train both unpaired rainy images and rain‐free images. Moreover, it introduces an unsupervised attention‐guided mechanism and exploits the loop‐search positioning algorithm to deal with the details of rain and fog in images. Extensive experiments have been carried out, and the results show that the proposed Cycle‐Derain network is preferable compared with other deraining networks, especially in term of rainy image restoration.

Photoperiod is acknowledged as a crucial environmental factor for plant flowering. According to different responses to photoperiod, plants were divided into short-day plants (SDPs), long-day plants (LDPs), and day-neutral plants (DNPs). The day length measurement system of SDPs is different from LDPs. Many SDPs, such as rice, have a critical threshold for day length (CDL) and can even detect changes of 15 minutes for flowering decisions. Over the last 20 years, molecular mechanisms of flowering time in SDP rice and LDP Arabidopsis have gradually clarified, which offers a chance to elucidate the differences in day length measurement between the two types of plants. In Arabidopsis, CO is a pivotal hub in integrating numerous internal and external signals for inducing photoperiodic flowering. By contrast, Hd1 in rice, the homolog of CO, promotes and prevents flowering under SD and LD, respectively. Subsequently, numerous dual function regulators, such as phytochromes, Ghd7, DHT8, OsPRR37, OsGI, OsLHY, and OsELF3, were gradually identified. This review assesses the relationship among these regulators and a proposed regulatory framework for the reversible mechanism, which will deepen our understanding of the CDL regulation mechanism and the negative response to photoperiod between SDPs and LDPs.

After years of continuous cultivation of faba beans (Vicia faba L.), autotoxic substances accumulate in the soil, leading to a high incidence of Fusarium oxysporum (FOF) wilt. Faba bean–wheat intercropping is often used to alleviate these problems. The goal of this research was to explore the role of benzoic acid and cinnamic acid in promoting the occurrence of faba bean Fusarium wilt and the potential mechanism of faba bean–wheat intercropping to control the occurrence of this disease. We established a field experiment and a hydroponic experiment that involved the inoculation of FOF and the exploration of exogenous addition of cinnamic acid and benzoic acid at different concentrations, the effects on the degree of peroxidation, resistance system, and ultrastructure of faba bean roots. In addition, the antioxidative response of faba bean–wheat intercropping against the autotoxicity of benzoic acid and cinnamic acid was examined. In the field experiment, compared with monoculture, faba bean–wheat intercropping effectively controlled the occurrence of Fusarium wilt, significantly reduced the contents of H2O2 and O2− in faba bean roots, increased the expression and activity of antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT), maintained cell stability, and significantly reduced the contents of benzoic acid and cinnamic acid in faba bean rhizosphere. In the pot experiment, it was found that compared with the control, different concentrations of benzoic acid and cinnamic acid (50, 100, and 200 mg·L−1) significantly increased the content of H2O2 and O2− in faba bean, decreased the activity and gene expression of antioxidant enzymes SOD and CAT, and damaged cell membrane structure. Furthermore, it promoted the occurrence of Fusarium wilt of faba bean. The faba bean–wheat intercropping alleviated the stress. Benzoic acid and cinnamic acid can increase the content of hydrogen peroxide and superoxide anions in faba bean plants, reduce the enzymatic activity and expression of antioxidant enzyme genes, damage the cell membrane structure, and promote the occurrence of faba bean Fusarium wilt. The faba bean–wheat intercropping can effectively alleviate the autotoxicity of benzoic acid and cinnamic acid and reduce the occurrence of faba bean Fusarium wilt.

Abstract Previous study indicates that kernel of areca nut is susceptible to enzymatic browning caused by phenolic oxidation, which involves the ingression of oxygen into interior tissue. However, the reason for permeation of oxygen into the interior of areca nut and its possible influencing factors (e.g., temperatures) are little known. In the present study, we set three storage temperatures (25, 10, and 5°C) and investigated the effects on kernel browning and related physic‐biochemical and tissue morphological changes. The results showed that the most severe kernel browning was observed in areca nut stored at 25°C, followed by 5°C. Comparatively, a slower browning development was found in areca nut stored at 10°C. More serious kernel browning at 25 and 5°C might be attributed to increased membrane permeability and aggravated tissue damage in view of morphological observations on pericarp, mesocarp, and kernel shell. Higher lignin content and phenylalanine ammonia‐lyase activity were observed in mesocarp of areca nuts stored at 25 and 5°C as compared to 10°C, indicating that mesocarp lignification could facilitate the permeability of oxygen. Furthermore, the data showed that storage at 25 and 5°C induced the higher polyphenol oxidase activity while accelerating the decline in total phenolic content in areca nut kernel, which could contribute to higher occurrence of enzymatic browning reaction compared to that at 10°C. These results suggest that natural senescence at 25°C and severe chilling stress at 5°C could be influencing factors triggering the permeation of oxygen, leading to internal kernel browning in areca nut.

BackgroundType 2 diabetes (T2DM) is a major risk factor for myocardial infarction. Thrombus aspiration was considered a good way to deal with coronary thrombus in the treatment of acute myocardial infarction. However, recent studies have found that routine thrombus aspiration is not beneficial. This study is designed to investigate whether intracoronary artery retrograde thrombolysis (ICART) is more effective than thrombus aspiration or percutaneous transluminal coronary angioplasty (PTCA) in improving myocardial perfusion in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI).Methods/DesignIntraCoronary Artery Retrograde Thrombolysis (ICART) vs. thrombus aspiration or PTCA in STEMI trial is a single-center, prospective, randomized open-label trial with blinded evaluation of endpoints. A total of 286 patients with STEMI undergoing PPCI are randomly assigned to two groups: ICART and thrombus aspiration or PTCA. The primary endpoint is the incidence of >70% ST-segment elevation resolution. Secondary outcomes include distal embolization, myocardial blush grade, thrombolysis in myocardial infarction (TIMI) flow grade, and in-hospital bleeding.DiscussionThe ICART trial is the first randomized clinical trial (RCT) to date to verify the effect of ICART vs. thrombus aspiration or PTCA on myocardial perfusion in patients with STEMI undergoing PPCI.Clinical Trial Registration[https://www.chictr.org.cn/], identifier [ChiCTR1900023849].

Intimate partner violence (IPV) is a preventable public health problem that affects millions of people worldwide. Approximately one in four women are estimated to be or have been victims of severe violence at some point in their lives, irrespective of age, ethnicity, and economic status. Victims often report IPV experiences on social media, and automatic detection of such reports via machine learning may enable improved surveillance and targeted distribution of support and/or interventions for those in need. However, no artificial intelligence systems for automatic detection currently exists, and we attempted to address this research gap. We collected posts from Twitter using a list of IPV-related keywords, manually reviewed subsets of retrieved posts, and prepared annotation guidelines to categorize tweets into IPV-report or non-IPV-report. We annotated 6,348 tweets in total, with the inter-annotator agreement (IAA) of 0.86 (Cohen's kappa) among 1,834 double-annotated tweets. The class distribution in the annotated dataset was highly imbalanced, with only 668 posts (∼11%) labeled as IPV-report. We then developed an effective natural language processing model to identify IPV-reporting tweets automatically. The developed model achieved classification F1-scores of 0.76 for the IPV-report class and 0.97 for the non-IPV-report class. We conducted post-classification analyses to determine the causes of system errors and to ensure that the system did not exhibit biases in its decision making, particularly with respect to race and gender. Our automatic model can be an essential component for a proactive social media-based intervention and support framework, while also aiding population-level surveillance and large-scale cohort studies.

Hepatic alveolar echinococcosis (HAE) is a zoonotic parasitic disease caused by the larvae of Echinococcus multilocularis. Because of its characteristics of diffuse infiltration and growth similar to tumors, the disability rate and mortality rate are high among patients. Although surgery (including hepatectomy, liver transplantation, and autologous liver transplantation) is the first choice for the treatment of hepatic alveolar echinococcosis in clinic, drug treatment still plays an important and irreplaceable role in patients with end-stage echinococcosis, including patients with multiple organ metastasis, patients with inferior vena cava invasion, or patients with surgical contraindications, etc. However, Albendazole is the only recommended clinical drug which could exhibit a parasitostatic rather than a parasitocidal effect. Novel drugs are needed but few investment was made in the field because the rarity of the cases. Drug repurposing might be a solution. In this review, FDA-approved drugs that have a potential curative effect on hepatic alveolar echinococcosis in animal models are summarized. Further, nano drug delivery systems boosting the therapeutic effect on hepatic alveolar echinococcosis are also reviewed. Taken together, these might contribute to the development of novel strategy for advanced hepatic alveolar echinococcosis.

BackgroundHow to deal with large thrombus burdens of culprit’s blood vessel remains a great challenge in the treatment of acute myocardial infarction.Case presentationA 32-year-old Chinese man was diagnosed with ST-segment elevation myocardial infarction (STEMI). Coronary angiography revealed that the distal end of a tortuous left circumflex was completely occluded by a large amount of thrombus. Cutted balloon-directed intracoronary artery retrograde thrombolysis (ICART) with urokinase led to the restoration of coronary blood flow. Because there was no obvious plaque rupture or artery stenosis in the coronary artery, it was only dilated, and no stent was implanted.ConclusionCutted balloon-directed ICART can be performed effectively and safely in some STEMI patients with tortuous coronary vessels and large thrombus. (REST or named ICART ClinicalTrials.gov number, ChiCTR1900023849).

BackgroundThe management of a large thrombus burden in patients with acute myocardial infarction and diabetes is still a worldwide problem.Case presentationA 74-year-old Chinese woman presented with ST-segment elevation myocardial infarction (STEMI) complicated with diabetes mellitus and hypertension. Angiography revealed massive thrombus formation in the mid-segment of the right coronary artery leading to vascular occlusion. The sheared balloon was placed far from the occlusion segment and urokinase (100,000 u) was administered for intracoronary artery retrograde thrombolysis, and thrombolysis in myocardial infarction (TIMI) grade 3 blood flow was restored within 7 min. At last, one stent was accurately implanted into the culprit’s vessel. No-reflow, coronary slow flow, and reperfusion arrhythmia were not observed during this process.ConclusionIntracoronary artery retrograde thrombolysis (ICART) can be effectively and safely used in patients with STEMI along with diabetes mellitus and hypertension, even if the myocardial infarction exceeds 12 h (REST or named ICART ClinicalTrials.gov number, ChiCTR1900023849).

In folklore medicine, Conocarpus lancifolius is used to treat various illnesses. The main objective of this study was a comprehensive investigation of Conocarpus lancifolius leaf aqueous extract (CLAE) for its antioxidant, cardioprotective, anxiolytic, antidepressant and memory-enhancing capabilities by using different in vitro, in vivo and in silico models. The in vitro experimentation revealed that CLAE consumed an ample amount of total phenolics (67.70 ± 0.15 µg GAE/mg) and flavonoids (47.54 ± 0.45 µg QE/mg) with stronger antiradical effects through DPPH (IC50 = 16.66 ± 0.42 µg/mL), TAC (77.33 ± 0.41 µg AAE/mg) and TRP (79.11 ± 0.67 µg GAE/mg) assays. The extract also displayed suitable acetylcholinesterase (AChE) inhibitory (IC50 = 110.13 ± 1.71 µg/mL) activity through a modified Ellman’s method. The toxicology examination presented no mortality or any signs of clinical toxicity in both single-dose and repeated-dose tests. In line with the cardioprotective study, the pretreatment of CLAE was found to be effective in relieving the isoproterenol (ISO)-induced myocardial injury in rats by normalizing the heart weight index, serum cardiac biomarkers, lipid profile and various histopathological variations. In the noise-stress-induced model for behavior attributes, the results demonstrated that CLAE has the tendency to increase the time spent in the central zone and elevated open arms in the open field and elevated plus maze tests (examined for anxiety assessment), reduced periods of immobility in the forced swimming test (for depression) and improved recognition and working memory in the novel object recognition and Morris water maze tests, respectively. Moreover, the LC-ESI-MS/MS profiling predicted 53 phytocompounds in CLAE. The drug-likeness and ADMET analysis exhibited that the majority of the identified compounds have reasonable physicochemical and pharmacokinetic profiles. The co-expression of molecular docking and network analysis indicated that top-ranked CLAE phytoconstituents act efficiently against the key proteins and target multiple signaling pathways to exert its cardiovascular-protectant, anxiolytic, antidepressant and memory-enhancing activity. Hence, this artifact illustrates that the observed biological properties of CLAE elucidate its significance as a sustainable source of bioactive phytochemicals, which appears to be advantageous for pursuing further studies for the development of new therapeutic agents of desired interest.

Quantifying rapidly progressing three-dimensional forces generated by cells remains a major challenge in mechanobiology. Here, the authors show that combining traction force microscopy with astigmatic imaging permits sensitive out-of-plane force estimation on the second timescale.

BackgroundThe pattern of intercropping wheat and faba bean is an effective means to alleviate continuous cropping obstacles.AimTo study the mechanism by which cinnamic acid promotes faba bean wilt and the mechanism by which intercropping alleviates this effect.MethodsHydroponics was used to study the effects of inoculation with or without Fusarium oxysporum f. sp. fabae (FOF) and the effect of addition of different concentrations of cinnamic acid on seedling growth, Fusarium wilt, stem cell wall degrading enzyme activity, lignin content, tissue structure of the stem and leaf photosynthesis in monocropping and intercropping systems following the inoculation of faba bean with FOF.ResultsTreatment with FOF significantly reduced the biomass and leaf photosynthesis of faba bean compared with the control. Microscopic observation showed that the xylem vessels of the stem were slightly thickened. Compared with FOF alone, the combination of FOF and cinnamic acid stress significantly increased the activity of cell wall degrading enzymes (CWDEs) produced by FOF in the stem and content of lignin in the stem. Microstructural observation showed that cell wall thickening of the xylem conduit, stratification, formation of a cavity and even caused the dispersion of tissue cell structure in the stem tissue of faba bean. Furthermore, the biomass and leaf photosynthesis of faba bean decreased significantly, and the occurrence of faba bean wilt increased. Compared with the faba bean monocropping treatment, the wheat and faba bean intercropping treatment significantly reduced the activity of CWDEs of FOF produced in faba bean stems and increased the lignin content. In addition, observation of the microstructure indicated that the tissue structural cell wall thickened after the stem had decreased, and the amount of colloidal substances and their containment decreased, causing a further decrease in tissue deformation, smaller intercellular spaces, less divided layer cell damage, an increase in the aboveground biomass and leaf photosynthesis of faba bean and a decrease in the occurrence of faba bean wilt.ConclusionCinnamic acid decreased the resistance of tissue structure and promoted the occurrence of wilt. Wheat and faba bean intercropping improved the resistance of tissue structure, which reduced the occurrence of wilt.

Objective: After coronary artery bypass grafting (CABG) surgery, the main causes of poor instant patency of left internal mammary arteries (LIMAs) are competitive flow and anastomotic stenosis, but how to determine the cause of LIMA non-patency without interfering with the native coronary artery is still a difficult problem to be solved urgently.Methods: In this study, a 0D-3D coupled multiscaled CABG model of anastomotic stenosis and competitive flow was constructed. After calculation, the flow waveform of the LIMA was extracted, and the waveform shape, common clinical parameters (average flow, PI, and DF), and graft flow FFT ratio results (F0/H1 and F0/H2) were analyzed.Results: For LIMA, these three common clinical parameters did not differ significantly between the anastomotic stenosis group and competitive flow group. However, the waveform shape and FFT ratio (especially F0/H2) of the competitive flow group were significantly different from those of the anastomotic stenosis group. When the cause was competitive flow, there was systolic backflow, and F0/H2 was too high (>14.89). When the cause was anastomotic stenosis, the waveform maintained a bimodal state and F0/H2 was in a normal state (about 1.17).Conclusion: When poor instant patency of the LIMA is found after CABG, the causes can be determined by graft flow waveform shape and F0/H2.

This study examines the relation between plosive aspiration and post-plosive f0 (fundamental frequency) in the production and perception of the laryngeal contrast in Mandarin. Production data from 25 Mandarin speakers showed that, in word onsets, VOTs (voice onset time) of aspirated and unaspirated plosives were different, as expected. At the same time, the speakers produced different post-plosive f0 between aspirated and unaspirated plosives, but the difference varied according to the lexical tones – post-aspirated f0 was higher than post-unaspirated f0 in high-initial tones (i.e., lexical tones with high onset f0), but the pattern was the opposite and less robust in low-initial tones. In the perception of the same participants, VOT was the primary cue to aspiration but, when VOT was ambiguous, high post-plosive f0 yielded more aspirated responses in general. We claim that the asymmetry in f0 perturbation between high-initial and low-initial tones in production arises from different laryngeal maneuvers for different tonal targets. In low-initial tones, in which the vocal folds are slack and the glottal opening is wider, aspirated plosives have a lower subglottal air pressure than unaspirated plosives at the voicing onset, resulting in lower post-aspirated f0 than post-unaspirated f0. But in high-initial tones, the vocal folds are tense, which requires a higher trans-glottal pressure threshold to initiate phonation at the onset of voicing. As a result, the subglottal pressure does not decrease as much. Instead, the faster airflow in aspirated than unaspirated plosives gives rise to the pattern that post-aspirated f0 is higher than post-unaspirated f0. Regardless of this variation in production, our perception data suggest that Mandarin listeners generalize the f0 perturbation patterns from high-initial tones and associate high post-plosive f0 with aspirated plosives even in low-initial tone contexts. We cautiously claim that the observed perceptual pattern is consistent with the robustly represented production pattern, as high-initial tones are more prevalent and salient in the language and exhibit stronger f0 perturbation in the speakers' productions.

Ferroptosis is an iron-dependent regulated cell death characterized by lipid peroxidation and iron overload, which is different from other types of programmed cell death, including apoptosis, necroptosis, autophagy, and pyroptosis. Over the past years, emerging studies have shown a close relation between ferroptosis and various cardiovascular diseases such as atherosclerosis, acute myocardial infarction, ischemia/reperfusion injury, cardiomyopathy, and heart failure. Herein, we will review the contributions of ferroptosis to multiple cardiovascular diseases and the related targets. Further, we discuss the potential ferroptosis-targeting strategies for treating different cardiovascular diseases.

Continuous cultivation of the faba bean will lead to its autotoxicity. Faba bean–wheat intercropping can effectively alleviate the autotoxicity of the faba bean. In order to investigate the autotoxicity of water extracts of various parts of the faba bean, we prepared water extracts of various parts of the faba bean, such as the roots, stems, leaves, and rhizosphere soil. The results showed various parts of the faba bean significantly inhibited the germination of faba bean seeds. The main autotoxins in these parts were analyzed using HPLC. Six autotoxins, namely, p-hydroxybenzoic acid, vanillic acid, salicylic acid, ferulic acid, benzoic acid, and cinnamic acid, were identified. The exogenous addition of these six autotoxins significantly inhibited the germination of faba bean seeds in a concentration-dependent manner. Furthermore, field experiments were conducted to investigate the effects of various levels of nitrogen fertilizer on the autotoxin content and the aboveground dry weight of the faba bean in a faba bean–wheat intercropping system. The application of various levels of nitrogen fertilizer in the faba bean–wheat intercropping system could significantly reduce the content of autotoxins and increase the aboveground dry weight in faba bean, particularly at the N2 level (90 kg/hm2). The above results showed that the water extracts of faba bean roots, stems, leaves, and rhizosphere soil inhibited faba bean seed germination. The autotoxicity in faba bean under continuous cropping could be caused by p-hydroxybenzoic acid, vanillic acid, salicylic acid, ferulic acid, benzoic acid, and cinnamic acid. The autotoxic effects in the faba bean were effectively mitigated by the application of nitrogen fertilizer in a faba bean–wheat intercropping system.

In recent years, semantic segmentation with pixel-level classification has become one of the types of research focus in the field of polarimetric synthetic aperture radar (PolSAR) image interpretation. Fully convolutional network (FCN) can achieve end-to-end semantic segmentation, which provides a basic framework for subsequent improved networks. As a classic FCN-based network, U-Net has been applied to semantic segmentation of remote sensing images. Although good segmentation results have been obtained, scalar neurons have made it difficult for the network to obtain multiple properties of entities in the image. The vector neurons used in the capsule network can effectively solve this problem. In this paper, we propose a complex-valued (CV) U-Net with a CV capsule network embedded for semantic segmentation of a PolSAR image. The structure of CV U-Net is lightweight to match the small PolSAR data, and the embedded CV capsule network is designed to extract more abundant features of the PolSAR image than the CV U-Net. Furthermore, CV dynamic routing is proposed to realize the connection between capsules in two adjacent layers. Experiments on two airborne datasets and one Gaofen-3 dataset show that the proposed network is capable of distinguishing different types of land covers with a similar scattering mechanism and extracting complex boundaries between two adjacent land covers. The network achieves better segmentation performance than other state-of-art networks, especially when the training set size is small.

Adequate vascularization is a critical determinant for the successful construction and clinical implementation of complex organotypic tissue models. Currently, low cell and vessel density and insufficient vascular maturation make vascularized organotypic tissue construction difficult, greatly limiting its use in tissue engineering and regenerative medicine. To address these limitations, recent studies have adopted pre-vascularized microtissue assembly for the rapid generation of functional tissue analogs with dense vascular networks and high cell density. In this article, we summarize the development of module assembly-based vascularized organotypic tissue construction and its application in tissue repair and regeneration, organ-scale tissue biomanufacturing, as well as advanced tissue modeling.

BackgroundIt is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.ObjectiveThis study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.MethodThe cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.ResultsWith respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.ConclusionA deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.

Background. Hepatocellular carcinoma (HCC) is recognized as the fourth in incidence and the third in mortality worldwide. The onset of HCC is insidious and often asymptomatic at the early stage. HCC is more prone to metastasis, recurrence, and drug resistance than other solid tumors owing to its feature of high heterogeneity. Therefore, what particularly important is to search for effective molecular markers in the occurrence and progression of HCC. Aim. To probe into the therapeutic potential of circACTG1 (hsa_circ_0046144) in HCC cell migration and invasion, providing a new insight and molecular target to diagnose and cure HCC patients. Methods. The circACTG1 expression in collected HCC cells was determined by quantitative polymerase chain reaction (qPCR). Assessment for circACTG1 diagnosing capability was analyzed by receiver operating characteristic (ROC) curves. Transwell assay, wound healing assay, and cell counting kit-8 assay were used for monitoring the effect of circACTG1 in HCC cell invasion, migration, and proliferation, respectively; qPCR, luciferase reporter assay, databases, and Western blot analysis were used for identifying the modulation mechanisms among circACTG1, miRNA-940, and RIF1. What is more, our study verified AKT-mTOR signaling after miR-940 mimic treatment or circACTG1 knockdown. Results. circACTG1 was overexpressed in HCC cells and tissues. Knockdown of circACTG1 restrained 97H and Huh7 cell migration and invasion. Significantly, circACTG1 was discovered to serve as a miR-940 sponge. miR-940 activation rebated the circACTG1 level, and conversely, miR-940 inhibition boosted the circACTG1 level. However, this effect or relationship was not seen after circACTG1 mutation. Furtherly, miR-940-downregulated expression was also found in HCC patients, and importantly, miR-940 inhibition reversed circACTG1 expression in 97H cells with circACTG1 knockdown. Moreover, the expression of RIF1 was significantly reduced after inhibiting circACTG1 or overexpressing miR-940 but rescued when both circACTG1 and miR-940 were inhibited. Finally, circACTG1 and miR-940 played significant roles of regulating AKT-mTOR signaling. Conclusion. circACTG1 expression remarkably ascended in HCC, which is of certain diagnostic value. Moreover, circACTG1 potentially regulates HCC cell proliferation, invasion, and migration via miR-940/RIF1/AKT/mTOR pathway.

Background. The behaviors and emotions associated with and reasons for nonmedical prescription drug use (NMPDU) are not well-captured through traditional instruments such as surveys and insurance claims. Publicly available NMPDU-related posts on social media can potentially be leveraged to study these aspects unobtrusively and at scale. Methods. We applied a machine learning classifier to detect self-reports of NMPDU on Twitter and extracted all public posts of the associated users. We analyzed approximately 137 million posts from 87,718 Twitter users in terms of expressed emotions, sentiments, concerns, and possible reasons for NMPDU via natural language processing. Results. Users in the NMPDU group express more negative emotions and less positive emotions, more concerns about family, the past, and body, and less concerns related to work, leisure, home, money, religion, health, and achievement compared to a control group (i.e., users who never reported NMPDU). NMPDU posts tend to be highly polarized, indicating potential emotional triggers. Gender-specific analyses show that female users in the NMPDU group express more content related to positive emotions, anticipation, sadness, joy, concerns about family, friends, home, health, and the past, and less about anger than males. The findings are consistent across distinct prescription drug categories (opioids, benzodiazepines, stimulants, and polysubstance). Conclusion. Our analyses of large-scale data show that substantial differences exist between the texts of the posts from users who self-report NMPDU on Twitter and those who do not, and between males and females who report NMPDU. Our findings can enrich our understanding of NMPDU and the population involved.

Mitochondrial DNA is found in nucleoids, which are distributed throughout the mitochondrial network and are thought to be passively distributed. Here, the authors show that mitochondrial dynamic tubulation at ER-mitochondria contact sites actively transports nucleoids.

Membrane contact sites between organelles have been shown to play important biological roles. Here, the authors show that at the ER, PDZD8 associates with Protrudin and also with Rab7 endosomes and recruits mitochondria to form three-way contacts.

Abstract Taking betel nut (Betel catechu L.) kernel as raw materials, to analyze the browning mechanism of betel nut kernel. First, we extract and separate the phenolic substances and polyphenol oxidase (PPO) from the betel nut kernel and then find out how O2 penetrates into the kernel, study the above 3 key factors of enzymatic browning so as to prove the possibility of enzymatic browning, and further study the browning products to clarify the mechanism of browning of betel nut kernel during storage process. The results showed that 11 kinds of phenolic compounds were isolated and identified from the betel nut kernel by liquid chromatography–mass spectrometry, among which chlorogenic acid was the highest, followed by dopamine and L‐epicatechin, and other contents were relatively low. Meanwhile, PPO was also separated from the betel nut kernel by DEAE–Sepharose Fast Flow and Phenyl–Sepharose 6 Fast Flow column chromatography. On this basis, scanning electron microscopy showed that the damage of the betel nut tissue was aggravated with the prolonged storage time, the wax was gradually decomposed, and the stratum corneum of the peel is destroyed in a honeycomb‐shaped; the lignification of the flesh was aggravated, and the interstitial space was increased; and the crack of the kernel membrane was also enlarged. These changes of structure contribute to increase gas exchange within and outside the organization, including the entry of O2. Finally, the oxidation products generated from simulated reaction of chlorogenic acid, dopamine, and epicatechin with purified PPO under aerobic conditions in vitro were compared with the products extracted from naturally brown betel nut, and the same absorption spectra were found. Therefore, it indicates that the browning of betel nut kernel is an enzymatic browning caused by the reaction of phenolic substrates were oxidized by PPO.

Intracerebral hemorrhage (ICH) is the most lethal subtype of stroke, but effective treatments are lacking, and neuroinflammation plays a key role in the pathogenesis. In the innate immune response to cerebral hemorrhage, microglia first appear around the injured tissue and are involved in the inflammatory cascade response. Microglia respond to acute brain injury by being activated and polarized to either a typical M1-like (pro-inflammatory) or an alternative M2-like (anti-inflammatory) phenotype. These two polarization states produce pro-inflammatory or anti-inflammatory. With the discovery of the molecular mechanisms and key signaling molecules related to the polarization of microglia in the brain, some targets that regulate the polarization of microglia to reduce the inflammatory response are considered a treatment for secondary brain tissue after ICH damage effective strategies. Therefore, how to promote the polarization of microglia to the M2 phenotype after ICH has become the focus of attention in recent years. This article reviews the mechanism of action of microglia’s M1 and M2 phenotypes in secondary brain injury after ICH. Moreover, it discusses compounds and natural pharmaceutical ingredients that can polarize the M1 to the M2 phenotype.

The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function

Effect of hydrogen-bonding donor, hydrogen-bonding acceptor, mole ratio, components and temperature on the refractive index of amino acid-based DESs is investigated. Results show that decreasing the mole ratio of hydrogen-bonding donor to hydrogen-bonding acceptor would decrease the refractive index. Refractive index of amino acid-based DESs shows negatively linear correlation with the temperature. This work would expand the application of amino acid-based DESs for the green optical device and sustainable characterization.