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Abstract Background Retinopathy of Prematurity (ROP) is a proliferative retinal vascular disease occurring in the retina of premature infants and is the main cause of childhood blindness. Nowadays anti-VEGF and retinal photocoagulation are mainstream treatments for ROP, but they develop a variety of complications. Hydrogen (H2) is widely considered as a useful neuroprotective and antioxidative therapeutic method for hypoxic-ischemic disease without toxic effects. However, whether H2 provides physiological angiogenesis promotion, neovascularization suppression and glial protection in the progression of ROP is largely unknown.This study aims to investigate the effects of H2 on retinal angiogenesis, neovascularization and neuroglial dysfunction in the retinas of oxygen-induced retinopathy (OIR) mice. Methods In this study, mice that were seven days old and either wild-type (WT) or Nrf2-deficient (Nrf2−/−) were exposed to 75% oxygen for 5 days and then returned to normal air conditions. Different stages of hydrogen gas (H2) inhalation were administered. Vascular obliteration, neovascularization, and blood vessel leakage were analyzed and compared. To count the number of neovascularization endothelial nuclei, routine HE staining of retinal sections was conducted. Immunohistochemistry was performed using DyLight 594 labeled GSL I-isolectin B4 (IB4), as well as primary antibodies against proliferating cell nuclear antigen (PCNA), glial fibrillary acidic protein (GFAP), and Iba-1. Western blots were used to measure the expression of NF-E2-related factor 2 (Nrf2), vascular endothelial growth factor (VEGF), Notch1, Dll4, and HIF-1α. Additionally, the expression of target genes such as NQO1, HO-1, Notch1, Hey1, Hey2, and Dll4 was measured. Human umbilical vein endothelial cells (HUVECs) treated with H2 under hypoxia were used as an in vitro model. RT-PCR was used to evaluate the mRNA expression of Nrf2, Notch/Dll4, and the target genes. The expression of reactive oxygen species (ROS) was observed using immunofluorescence staining. Results Our results indicate that 3–4% H2 does not disturb retinal physiological angiogenesis, but ameliorates vaso-obliteration and neovascularization in OIR mice. Moreover, H2 prevents the decreased density and reverses the morphologic and functional changes in retinal astrocytes caused by oxygen-induced injury. In addition, H2 inhalation reduces microglial activation, especially in the area of neovascularization in OIR mice. H2 plays a protective role in vascular regeneration by promoting Nrf2 activation and suppressing the Dll4-induced Notch signaling pathway in vivo. Also, H2 promotes the proliferation of HUVECs under hypoxia by negatively regulating the Dll4/Notch pathway and reducing ROS levels through Nrf2 pathway aligning with our findings in vivo.Moreover, the retinal oxygen-sensing mechanisms (HIF-1α/VEGF) are also involved in hydrogen-mediated retinal revascularization and neovascularization suppression. Conclusions Collectively, our results indicate that H2 could be a promising therapeutic agent for POR treatment and that its beneficial effect in human ROP might involve the activation of the Nrf2-Notch axis as well as HIF-1α/VEGF pathways. Graphical Abstract

PurposeThe aim of this study was to develop a novel approach for predicting the expression status of Epidermal Growth Factor Receptor (EGFR) and its subtypes in patients with Non-Small Cell Lung Cancer (NSCLC) using a Three-Dimensional Convolutional Neural Network (3D-CNN) ConvNeXt, radiomics features and clinical features.Materials and methodsA total of 732 NSCLC patients with available CT imaging and EGFR expression data were included in this retrospective study. The region of interest (ROI) was manually segmented, and clinicopathological features were collected. Radiomic and deep learning features were extracted. The instances were randomly divided into training, validation, and test sets. Feature selection was performed, and XGBoost was used to create solo models and combined models to predict the presence of EGFR and subtypes mutations. The effectiveness of the models was assessed using ROC and PRC curves.ResultsWe established the following models: ModelCNN, Modelradiomic, Modelclinical, ModelCNN+radiomic, ModelCNN+clinical, Modelradiomic+clinical, and ModelCNN+radiomic+clinical, which were based on deep learning features, radiomic features, clinical data and combinations of these, respectively. In predicting EGFR mutations, ModelCNN+radiomic+clinical demonstrated superior performance compared to other prediction models, achieving an AUC of 0.801. For distinguishing between EGFR subtypes ex19del and L858R, ModelCNN+radiomic reached the highest AUC value of 0.775.ConclusionsBoth deep learning models and radiomic signature-based models offer reasonably accurate non-invasive predictions of EGFR status and its subtypes. Fusion models hold the potential to enhance noninvasive methods for predicting EGFR mutations and subtypes, presenting a more reliable prediction approach.

We report a novel widely tunable Ka-band optoelectronic oscillator (OEO) realized by integrating a Mach–Zehnder modulator (MZM), a thermally-tunable add-drop micro-ring resonator (MRR), and a Mach–Zehnder interferometer (MZI) on the thin film lithium niobate platform, with the MZM and the MRR sequentially situated in one of the MZI arms. The MZM is for modulating the optical carrier, while the add-drop MRR is for selecting a single modulation sideband to beat with the unmodulated optical carrier from the other arm of the MZI, such that the OEO oscillation frequency is determined by the frequency spacing between the optical carrier and the selected modulation sideband, while the frequency tuning range is determined by the free spectral range of the MRR. By tuning the resonances of the add-drop MRR, the oscillation frequency can be tuned from 20 to 35 GHz, with the phase noises of −85 dBc/Hz @10 kHz and −116 dBc/Hz @100 kHz in the whole tuning range, which represent much higher oscillation frequency, much wider frequency tuning range, and lower phase noise than those of the photonic integrated OEOs realized with other material platforms reported previously.

Bioaerosols produced during animal production have potential adverse effects on the health of workers and animals. Our objective was to investigate characteristics, antibiotic-resistance genes (ARGs), and health risks of bioaerosols in various animal barns. Poultry and swine barns had high concentrations of airborne bacteria (11156 and 10917 CFU/m3, respectively). Acinetobacter, Clostridium sensu stricto, Corynebacterium, Pseudomonas, Psychrobacter, Streptococcus, and Staphylococcus were dominant pathogenic bacteria in animal barns, with Firmicutes being the most abundant bacterial phylum. Based on linear discriminant analysis effect size (LEfSe), there were more discriminative biomarkers in cattle barns than in poultry or swine barns, although the latter had the highest abundance of bacterial pathogens and high abundances of ARGs (including tetM, tetO, tetQ, tetW sul1, sul2, ermA, ermB) and intI1). Based on network analyses, there were higher co-occurrence patterns between bacteria and ARGs in bioaerosol from swine barns. Furthermore, in these barns, relative abundance of bacteria in bioaerosol samples was greatly affected by environmental factors, mainly temperature, relative humidity, and concentrations of CO2, NH3, and PM2.5. This study provided novel data regarding airborne bio-contaminants in animal enclosures and an impetus to improve management to reduce potential health impacts on humans and animals.

It has long been asserted that failure to recover from central nervous system diseases is due to the system’s intricate structure and the regenerative incapacity of adult neurons. Yet over recent decades, numerous studies have established that endogenous neurogenesis occurs in the adult central nervous system, including humans’. This has challenged the long-held scientific consensus that the number of adult neurons remains constant, and that new central nervous system neurons cannot be created or renewed. Herein, we present a comprehensive overview of the alterations and regulatory mechanisms of endogenous neurogenesis following central nervous system injury, and describe novel treatment strategies that target endogenous neurogenesis and newborn neurons in the treatment of central nervous system injury. Central nervous system injury frequently results in alterations of endogenous neurogenesis, encompassing the activation, proliferation, ectopic migration, differentiation, and functional integration of endogenous neural stem cells. Because of the unfavorable local microenvironment, most activated neural stem cells differentiate into glial cells rather than neurons. Consequently, the injury-induced endogenous neurogenesis response is inadequate for repairing impaired neural function. Scientists have attempted to enhance endogenous neurogenesis using various strategies, including using neurotrophic factors, bioactive materials, and cell reprogramming techniques. Used alone or in combination, these therapeutic strategies can promote targeted migration of neural stem cells to an injured area, ensure their survival and differentiation into mature functional neurons, and facilitate their integration into the neural circuit. Thus can integration replenish lost neurons after central nervous system injury, by improving the local microenvironment. By regulating each phase of endogenous neurogenesis, endogenous neural stem cells can be harnessed to promote effective regeneration of newborn neurons. This offers a novel approach for treating central nervous system injury.

Attempts have been made to use cell transplantation and biomaterials to promote cell proliferation, differentiation, migration, and survival, as well as angiogenesis, in the context of brain injury. However, whether bioactive materials can repair the damage caused by ischemic stroke by activating endogenous neurogenesis and angiogenesis is still unknown. In this study, we applied chitosan gel loaded with basic fibroblast growth factor to the stroke cavity 7 days after ischemic stroke in rats. The gel slowly released basic fibroblast growth factor, which improved the local microenvironment, activated endogenous neural stem/progenitor cells, and recruited these cells to migrate toward the penumbra and stroke cavity and subsequently differentiate into neurons, while enhancing angiogenesis in the penumbra and stroke cavity and ultimately leading to partial functional recovery. This study revealed the mechanism by which bioactive materials repair ischemic strokes, thus providing a new strategy for the clinical application of bioactive materials in the treatment of ischemic stroke.

The rapid development of the electric vehicle market has greatly stimulated the demand for public charging infrastructure (PCI) and made it a pertinent topic to improve its charging service quality in the industry. Data from perceived preference, PCI and electric vehicles cannot reflect the factors influencing potential users’ anxiety. This study designed a PCI development evaluation framework to investigate the impact of economic, technological, market, policy, and social environmental factors on PCI development from the perspective of potential users. We collected a dataset including 386 potential users in Tianjin, China, and employed structural equation model to survey the implementation of PCI. The following conclusions were drawn from this study: 1) Reducing operating costs will not significantly increase PCI charging user demand and improve use efficiency for potential users; 2) Technical factors cannot directly promote the development of PCI but will reverse lag the development of the market; 3) The growing market demand is the main impetus to the development of electric vehicle industry, and the incentive policy and social environment can indirectly incentivize PCI development. The policy implications suggest that the PCI industry can experience sustainable development by continuously innovating market-oriented business models, and improving policy systems and industry mechanisms. This study provides analytical foundation and decision support for policymakers and pertinent industry participants, promotes the development of electric vehicle-related industries, and helps achieve the strategic goal of carbon neutrality.

Sulfide is a toxic and hazardous substance in the agricultural environment, which can cause damage to humans and livestock when exposed to large amounts of air. In this study, we performed one-factor optimization of the culture conditions and culture fractions of the Cellulosimicrobium sp. strain L1 and combined it with a biological trickling filter cell for the degradation of hydrogen sulfide for 24 consecutive days. The degradation effect of strain L1 and the biological trickling filter (BTF) on hydrogen sulfide was investigated, and the changes in intermediate products in the degradation process were briefly analyzed. The results showed that strain L1 had the highest conversion efficiency when incubated with 3 g/L sucrose as the carbon source and 1 g/L NH4Cl as the nitrogen source at a temperature of 35 °C, an initial pH of 5, and a NaCl concentration of 1%. The concentration of thiosulfate increased and then decreased during the degradation process, and the concentration of sulfate increased continuously. When strain L1 was applied to the biological trickling filter, it could degrade 359.53 mg/m3 of H2S. This study provides a deeper understanding of sulfide degradation in biological trickling filters and helps promote the development of desulfurization technology and the treatment of malodorous gasses produced by the accumulation of large quantities of livestock manure.

Abstract Inflammation is a key factor in the pathogenesis of dry eye disease (DED). We aimed to investigate the role of microRNA-146a (miR-146a) in regulating corneal inflammation in a mouse model of benzalkonium chloride (BAC)-induced dry eye and the TNF-α-induced NF-κB signaling pathway in human corneal epithelial cells (HCECs). A mouse model of dry eye was established by administering with BAC to BALB/c mice, and the expression of TNF-α, IL-1β, IL-6, IL-8, cyclooxygenase 2 (COX2), interleukin-1 receptor-associated kinase 1 (IRAK1) and TNF receptor-associated factor 6 (TRAF6) in the corneas of dry eye model mice was significantly increased; this was accompanied by the upregulation of miR-146a and activation of the NF-κB pathway. In vitro, TNF-α induced miR-146a expression in HCECs, while the NF-κB inhibitor SC-514 reduced the expression of miR-146a. Overexpression of miR-146a decreased the expression of IRAK1 and TRAF6, which have been identified as targets of miR-146a. Furthermore, overexpression of miR-146a suppressed NF-κB p65 translocation from the cytoplasm to the nucleus. Moreover, overexpression of miR-146a attenuated the TNF-α-induced expression of IL-6, IL-8, COX2 and intercellular adhesion molecule 1 (ICAM1), while inhibition of miR-146a exerted the opposite effect. Our results suggest that miR-146a mediates the inflammatory response in DED. MiR-146a negatively regulates inflammation in HCECs through the IRAK1/TRAF6/NF-κB pathway, and this may serve as a potential therapeutic approach for the treatment of DED.

Abstract Background 17β-estradiol (E2) residues exhibit harmful effects both for human and animals and have got global attention of the scientific community. Microbial enzymes are considered as one of the effective strategies having great potential for removal E2 residues from the environment. However, limited literature is available on the removal of E2 from wastewater using short-chain dehydrogenase. Results In this study, 17β-estradiol degrading enzyme (17β-HSD-0095) was expressed and purified from Microbacterium sp. MZT7. The optimal pH and temperature for reaction was 7 and 40 °C, respectively. Molecular docking studies have shown that the ARG215 residue form a hydrogen bond with oxygen atom of the substrate E2. Likewise, the point mutation results have revealed that the ARG215 residue play an important role in the E2 degradation by 17β-HSD-0095. In addition, 17β-HSD-0095 could remediate E2 contamination in synthetic livestock wastewater. Conclusions These findings offer some fresh perspectives on the molecular process of E2 degradation and the creation of enzyme preparations that can degrade E2. Graphical Abstract

Periprosthetic hip infection caused by Brucella abortus is rare and only a few cases have been reported. This current case report presents a case of a man in his early 50s who developed periprosthetic hip infection 2 years after right hip arthroplasty. There was no fever or pain, the usual cardinal signs of infection, except for a sinus tract at the previous surgical incision. Laboratory and arthrocentesis culture examinations (done twice) confirmed infection with B. abortus . Accordingly, a two-stage revision surgery was performed accompanied by antibiotic treatment with doxycycline and rifampicin after each stage. There was no recurrence at the 2-year follow-up, with good functional recovery of the hip joint. Clinically, this case serves to highlight the fact that periprosthetic hip infections caused by B. abortus might not present with the typical symptoms such as fever or hip pain. Furthermore, this current case involved a chronic sinus tract, so the diagnostic and therapeutic course of this case offers useful insights for managing similar cases in the future. In addition, a review of the literature on the diagnosis and treatment of Brucella -caused periprosthetic hip infection is presented.

Abstract Background Sepsis is a life-threatening organ dysfunction caused by the infection-related host response disorder. Adequate mean arterial pressure is an important prerequisite of tissue and organ perfusion, which runs through the treatment of sepsis patients, and an appropriate mean arterial pressure titration in the early-stage correlates to the positive outcome of the treatment. Therefore, in the present study, we aimed to elucidate the relationship between early mean arterial pressure levels and short-term mortality in sepsis patients. Methods We included all suspected sepsis patients from MIMIC-III database with average mean arterial pressure ≥ 60 mmHg on the first day of intensive care unit stay. Those patients were then divided into a permissive low-mean arterial pressure group (60–65 mmHg) and a high-mean arterial pressure group (> 65 mmHg). Multivariate Cox regression analysis was conducted to analyze the relationship between MAP level and 30-day, 60-day, and 100-day mortality of suspected sepsis patients in the two groups. Propensity score matching, inverse probability of treatment weighing, standardized mortality ratio weighting, PA weighting, overlap weighting, and doubly robust analysis were used to verify our results. Results A total of 14,031 suspected sepsis patients were eligible for inclusion in our study, among which 1305 (9.3%) had an average first-day mean arterial pressure of 60–65 mmHg, and the remaining 12,726 patients had an average first-day mean arterial pressure of more than 65 mmHg. The risk of 30-day mortality was reduced in the high mean arterial pressure group compared with the permissive low-mean arterial pressure group (HR 0.67 (95% CI 0.60–0.75; p

Abstract With the rapid development of the cooperative vehicle infrastructure system, eco‐approach and departure has been attracting increasing attention for mitigating the impact of signalized intersections, which helps improve the energy efficiency of equipped vehicles. However, existing studies have rarely considered the balance of electric bus energy consumption and traveling time. Meanwhile, the joint effect of bus stops and signalized intersections, and their interactions were not discussed widely with connected and automated electric buses (CAEBs). In this study, an integrated CAEB trajectory planning methodology with the balance of traveling time and energy consumption is proposed. A bi‐level programming model is developed to obtain the optimal trajectories of CAEBs. Numerical experiments are conducted to analyse and compare the model with two baseline models. The results demonstrate the optimal performance of the derived scheme in terms of bus energy consumption, with approximately 30–50% energy savings. Furthermore, model sensitivity analysis is conducted to quantify the impacts of the related system parameters. The findings also reveal that the entry time, conversion coefficient, and final speed have significant impacts on electric bus energy consumption along signalized arterials with bus stops.

Abstract Background The size and cost of outpatient capacity directly affect the operational efficiency of a whole hospital. Many scholars have faced the study of outpatient capacity planning from an operations management perspective. Objective The outpatient service is refined, and the quantity allocation problem of each type of outpatient service is modeled as an integer linear programming problem. Thus, doctors’ work efficiency can be improved, patients’ waiting time can be effectively reduced, and patients can be provided with more satisfactory medical services. Methods Outpatient service is divided into examination and diagnosis service according to lean thinking. CPLEX is used to solve the integer linear programming problem of outpatient service allocation, and the maximum working time is minimized by constraint solution. Results A variety of values are taken for the relevant parameters of the outpatient service, using CPLEX to obtain the minimum and maximum working time corresponding to each situation. Compared with no refinement stratification, the work efficiency of senior doctors has increased by an average of 25%. In comparison, the patient flow of associate senior doctors has increased by an average of 50%. Conclusion In this paper, the method of outpatient capacity planning improves the work efficiency of senior doctors and provides outpatient services for more patients in need; At the same time, it indirectly reduces the waiting time of patients receiving outpatient services from senior doctors. And the patient flow of the associate senior doctors is improved, which helps to improve doctors’ technical level and solve the problem of shortage of medical resources.

A new photonic-assisted instantaneous frequency measurement system is presented. It overcomes the latency problem in the reported structures based on the frequency-to-time mapping technique or the frequency-to-power mapping technique that involves a long length of fiber, and at the same time, enables the incoming microwave signal frequency to be measured over a wide frequency range with only small errors. The system generates three low-frequency signals. The phases of the three low-frequency signals are compared. One of the two low-frequency signal phase differences is used to estimate the incoming microwave signal frequency unambiguously over a wide frequency range and the other is used to provide accurate microwave signal frequency measurement. A proof-of-concept experiment is set up. Experimental results show, by measuring the phase difference of two low-frequency signals, the frequency of the input microwave signal can be determined unambiguously in 15 GHz and 500 MHz frequency ranges with errors below ±220 MHz and ±10 MHz respectively. Hence, by using two low-frequency signal phase differences, the input microwave signal frequency can be determined accurately over a wide frequency range. The new photonic-assisted frequency measurement system has a fast response time, which is an order of magnitude shorter than that of the systems based on the frequency-to-time mapping technique and the frequency-to-power mapping technique with a kilometer-long fiber.

The accurate characterization and prediction of current–voltage (I–V) characteristics of photovoltaic (PV) modules under different weather conditions are essential for solar power forecasting and ensuring grid stability. This paper proposed a novel method based on the power-law model (PLM) for estimating PV module performance under different weather conditions without setting reference conditions. The effects of solar irradiance, ambient temperature, and module types are all fully considered. The dependence of shape parameters in PLM on irradiance and temperature are thoroughly investigated and the effect of the selection of reference conditions is eliminated by modifying a set of new transforming equations. The parameters of the new transforming equations can be extracted from experimental data by an optimization algorithm. Due to the advantages of PLM, the proposed method applies to any type of PV module and the I–V characteristics can be expressed explicitly without Lambert W-function or iterative solution. The effectiveness and accuracy proposed method are verified and tested on the large datasets of eighteen PV modules in three locations. Compared with existing methods, the proposed method shows higher accuracy and better performance in the estimation of I–V characteristics and maximum power under different weather conditions.

The electrochemical behavior of Li2O in KCl-LiCl molten salt has been studied by cyclic voltammetry and chronopotentiometry. The diffusion coefficient D=0.5×10-5 cm2/s of O2- in KCl-LiCl molten salt at 923 K has been calculated by convolutional voltammetry. Gd2O3, Nd2O3, Sm2O3 and Dy2O3 were used as cathodes to conduct electrolysis in KCl-LiCl-Li2O(w=1%) molten salt(constant voltage 3.40 V, electrolysis temperature 923 K, electrolysis time 25 h). By XRD analysis, it was confirmed that the rare earth oxides are partially reduced to metals, and the possible reactions during the electrolysis process were analyzed. At the same time, the PRS model was used to analyze the electrolytic reduction models of these rare earth oxides, and the optimal porosity(Popt) of Gd2O3, Nd2O3, Sm2O3 and Dy2O3 are 18.7%, 24.2%, 30.6%,16.7%, respectively. The minimum electrolysis time of them are 133, 157, 143, and 119 h, respectively, which are compared with the results of the electrolytic experiment, it is found that the porosity and electrolysis time of the cathode do not meet the requirements for complete reduction of metal oxides, and the corresponding explanation is given.

Real-time heterogeneous parallel embedded digital signal processor (DSP) systems process multiple data streams in parallel in a stringent time interval. This type of system on chip (SoC) requires the network on chip (NoC) to establish multiple symbiotic parallel data transmission paths with ultra-low transmission latency in real time. Our early NoC research PCCNOC meets this need. The PCCNOC uses packet routing to establish and lock a transmission circuit, so that PCCNOC is perfectly suitable for ultra-low latency and high-bandwidth transmission of long data packets. However, a parallel multi-data stream DSP system also needs to transmit roughly the same number of short data packets for job configuration and job execution status reports. While transferring short data packets, the link establishment routing delay of short data packets becomes relatively obvious. Our further research, thus, introduced PaCHNOC, a hybrid NoC in which long data packets are transmitted through a circuit established and locked by routing, and short data packets are attached to the routing packet and the transmission is completed during the routing process, thus avoiding the PCCNOC setup delay. Simulation shows that PaCHNOC performs well in supporting real-time heterogeneous parallel embedded DSP systems and achieves overall latency reduction 65% compared with related works. Finally, we used PaCHNOC in the baseband subsystem of a real 5G base station, which proved that our research is the best NoC for baseband subsystem of 5G base stations, which reduce 31% comprehensive latency in comparison to related works.

Abstract Doxorubicin (Dox) is the standard treatment approach for osteosarcoma (OS), while acquired drug resistance seriously attenuates its treatment efficiency. The present study aimed to investigate the potential roles of metabolic reprogramming and the related regulatory mechanism in Dox-resistant OS cells. The results showed that the ATP levels, lactate generation, glucose consumption and oxygen consumption rate were significantly increased in Dox-resistant OS cells compared with parental cells. Furthermore, the results revealed that the increased expression of estrogen-related receptor alpha (ERRα) was involved in metabolic reprogramming in chemotherapy resistant OS cells, since targeted inhibition of ERRα restored the shifting of metabolic profiles. Mechanistic analysis indicated that the mRNA stability, rather than ERRα transcription was markedly increased in chemoresistant OS cells. Therefore, it was hypothesized that the 3ʹ-untranslated region of ERRα mRNA was methylated by N6-methyladenine, which could further recruit insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) to suppress mRNA decay and increase mRNA stability. IGF2BP1 knockdown downregulated ERRα and reversed the metabolic alteration of resistant OS cells. Additionally, the oncogenic effect of the IGF2BP1/ERRα axis on Dox-resistant OS cells was verified by in vitro and in vivo experiments. Clinical analysis also revealed that the expression levels of IGF2BP1 and ERRα were associated with the clinical progression of OS. Collectively, the current study suggested that the IGF2BP1/ERRα axis could regulate metabolic reprogramming to contribute to the chemoresistance of OS cells.

Abstract Background Oxidative stress can induce age-related diseases. Age-related retinal diseases, such as age-related macular degeneration (AMD), are difficult to cure owing to their complicated mechanisms. Although anti-neovascular therapeutics are used to treat wet AMD, vision cannot always be completely restored, and disease progression cannot always be inhibited. Therefore, determining a method to prevent or slow retinal damage is important. This study aimed to investigate the protective effect of a chrysanthemum water extract rich in flavone on the oxidatively stressed retina of mice. Methods Light damage was induced to establish oxidative stress mouse models. For in vitro experiments, ARPE-19 cells were cultured and divided into four groups: control, light-damaged, and low- and high-dose chrysanthemum extract. No treatment was administered in the control group. The light-damaged and low- and high-dose chrysanthemum extract groups were exposed to a similar white light level. The chrysanthemum extract was added at a low dose of 0.4 mg/mL or a high dose of 1.0 mg/mL before cell exposure to 2500-lx white light. Reactive oxygen species (ROS) level and cellular viability were measured using MTT and immunofluorescence staining. For in vivo experiments, C57BL/6 J mice were divided into the same four groups. Low- (0.23 g/kg/day) and high-dose (0.38 g/kg/day) chrysanthemum extracts were continuously intragastrically administered for 8 weeks before mouse exposure to 10,000-lx white light. Retinal function was evaluated using electroretinography. In vivo optical coherence tomography and in vitro haematoxylin and eosin staining were performed to observe the pathological retinal changes in each group after light damage. Fluorescein fundus angiography of the arteriovenous vessel was performed, and the findings were analysed using the AngioTool software. TUNEL immunofluorescence staining was used to assess isolated retinal apoptosis. Results In vitro, increased ROS production and decreased ARPE-19 cell viability were found in the light-damaged group. Improved ARPE-19 cell viability and reduced ROS levels were observed in the chrysanthemum extract treatment groups. In vivo, dysfunctional retinas and abnormal retinal structures were found in the light-damaged group, as well as increased apoptosis in the retinal ganglion cells (RGCs) and inner and outer nuclear layers. The apoptosis rate in the same layers was lower in the chrysanthemum extract treatment groups than in the light-damaged group. The production of antioxidant enzymes, including superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px), increased in the treatment groups. NF-κB in the nucleus and TNF-α were more highly expressed in the light-damaged group than in the low- and high-dose chrysanthemum extract groups. Conclusions Light damage-induced retinal oxidative stress can lead to ROS accumulation in the retinal tissues. Herein, RGC and photoreceptor layer apoptosis was triggered, and NF-κB in the nucleus and TNF-α were highly expressed in the light-damaged group. Preventive chrysanthemum extract administration decreased ROS production by increasing SOD, CAT, and GSH-Px activities and reversing the negative changes, demonstrating a potential protective effect on the retina.

Target detection is to detect the specified target in the image. This technology has been widely used in automatic driving, face recognition and other fields, and has become a major research hotspot in the field of computer vision at home and abroad. Traditional target detection often requires a large number of annotated datasets, so it is a challenge to detect targets with only a small number of annotated samples. To address this problem, this paper proposes a multi-scale selection pyramid network algorithm for small sample target detection so that detection no longer relies on large-scale labeled datasets. Firstly, this paper designs a multi-scale selection pyramid network for small sample target detection, which consists of three components: context layer attention module, feature scale enhancement module, and feature scale selection module. Secondly, this paper performs feature fusion after the RoI features generated by the RPN network using maximum pooling and average pooling to improve the correlation between features. This paper uses feature subtraction to highlight the category information in the features, which can improve the sensitivity to new class parameters while maintaining the stability of the model to the sample parameters. Finally, the orthogonal mapping loss function is used to constrain the features before the classification layer, which can well measure the similarity between features even in the case of a small number of samples.

Abstract Spinal cord injury (SCI) is a severe damage usually leading to limb dysesthesia, motor dysfunction, and other physiological disability. We have previously shown that NT3-chitosan could trigger an acute SCI repairment in rats and non-human primates. Due to the negative effect of inhibitory molecules in glial scar on axonal regeneration, however, the role of NT3-chitosan in the treatment of chronic SCI remains unclear. Compared with the fresh wound of acute SCI, how to handle the lesion core and glial scars is a major issue related to chronic-SCI repair. Here we report, in a chronic complete SCI rat model, establishment of magnetic resonance-diffusion tensor imaging (MR-DTI) methods to monitor spatial and temporal changes of the lesion area, which matched well with anatomical analyses. Clearance of the lesion core via suction of cystic tissues and trimming of solid scar tissues before introducing NT3-chitosan using either a rigid tubular scaffold or a soft gel form led to robust neural regeneration, which interconnected the severed ascending and descending axons and accompanied with electrophysiological and motor functional recovery. In contrast, cystic tissue extraction without scar trimming followed by NT3-chitosan injection, resulted in little, if any regeneration. Taken together, after lesion core clearance, NT3-chitosan can be used to enable chronic-SCI repair and MR-DTI-based mapping of lesion area and monitoring of ongoing regeneration can potentially be implemented in clinical studies for subacute/chronic-SCI repair.

Objective Hip fracture is a prevalent condition with a significant death rate among the elderly. We sought to develop a nomogram-based survival prediction model for older patients with hip fracture.Design A retrospective case–control study.Setting The data from Medical Information Mart for Intensive Care III (MIMIC-III V.1.4).Participants The clinical features of elderly patients with hip fracture, including basic information, comorbidities, severity score, laboratory tests and therapy, were filtered out based on the MIMIC-III V.1.4.Methods and main outcome measures All patients included in the study were from critical care and randomly divided into training and validation sets (7:3). On the basis of retrieved data, the least absolute shrinkage and selection operator (LASSO) regression and multiple logistic regression analysis were used to identify independent predictive variables of 1-year mortality, and then constructed a risk prediction nomogram. The predictive values of the nomogram model were evaluated by the concordance indexes (C-indexes), receiver operating characteristic curve, decision curve analysis (DCA) and calibration curve.Results A total of 341 elderly patients with hip fracture were included in this study; 121 cases died within 1 year. After LASSO regression and multiple logistic regression analysis, a novel nomogram contained the predictive variables of age, weight, the proportion of lymphocyte count, liver disease, malignant tumour and congestive heart failure. The constructed model proved satisfactory discrimination with C-indexes of 0.738 (95% CI 0.674 to 0.802) in the training set and 0.713 (95% CI 0.608 to 0.819) in the validation set. The calibration curve shows a good degree of fitting between the predicted and observed probabilities and the DCA confirms the model’s clinical practicability.Conclusions The novel prediction model provides personalised predictions for 1-year mortality in elderly patients with hip fractures. Compared with other hip fracture models, our nomogram is particularly suitable for predicting long-term mortality in critical patients.

Although autogenous nerve transplantation is the gold standard for treating peripheral nerve defects of considerable length, it still has some shortcomings, such as insufficient donors and secondary injury. Composite chitosan scaffolds loaded with controlled release of nerve growth factor can promote neuronal survival and axonal regeneration after short-segment sciatic nerve defects. However, the effects on extended nerve defects remain poorly understood. In this study, we used chitosan scaffolds loaded with nerve growth factor for 8 weeks to repair long-segment (20 mm) sciatic nerve defects in adult rats. The results showed that treatment markedly promoted the recovery of motor and sensory functions. The regenerated sciatic nerve not only reconnected with neurons but neural circuits with the central nervous system were also reconstructed. In addition, the regenerated sciatic nerve reconnected the motor endplate with the target muscle. Therefore, this novel biomimetic scaffold can promote the regeneration of extended sciatic nerve defects and reconstruct functional circuits. This provides a promising method for the clinical treatment of extended peripheral nerve injury. This study was approved by the Animal Ethics Committee of Capital Medical University, China (approval No. AEEI-2017-033) on March 21, 2017.

Abstract Purpose To investigate the protective effects of thymosin β4 (Tβ4) on ethanol injured human corneal keratocytes (HCKs). Methods HCKs and BALB/c mice were chosen as the study subject. Ethanol was used to treat the cells and corneal stroma of mice to build the ethanol injured model in vitro and vivo respectively. CCK-8 was used to evaluate the cell metabolic activity. DCFH-DA was used to detect the intracellular reactive oxygen species level. TUNEL was chose to detect the cell apoptosis rate. The cell proliferation and migration were investigated by using wound healing insert. Wound healing of corneal surface and stroma was observed by using fluorescein sodium eyedrop and HE stain. RT-qPCR, ELISA, and immunostaining were performed to detect gene and protein expression in keratocytes or corneal stroma tissue of mice. Results Ethanol induced oxidative stress injury and cell apoptosis on HCKs, and Tβ4 can alleviate it by up-regulating the expression of Bcl-2, catalase, and CuZnSOD, and inhibiting the expression of Caspase-3. Tβ4 promotes the proliferation of HCKs and the process of corneal wound healing. It may relevant to the up-regulated expression of Ki67. Conclusions Our study established an ethanol-injured corneal stroma model in both vitro and vivo. The present study confirmed that Tβ4 play a protective effect on the reconstruction process of ethanol-injured corneal stroma.

High-intensity focused ultrasound (HIFU) surgery is a noninvasive thermal ablation treatment modality, and its clinical application is increasingly introduced into gynecological practices in China and Asia. To further strengthen the technology's standardized management, the Asia-Pacific Association for Gynecologic Endoscopy and Minimally Invasive Therapy (APAGE) collected the consensus of well-known experts in the field. They shared opinions on the management standards of the basic requirements for developing this HIFU technology in medical institutions, operators' training requirements, technical management, HIFU training program, etc., Based on the recommendations from APAGE, Hong Kong Focused Ultrasound Surgery Association developed its proposed HIFU training program for gynecologists in Hong Kong. This paper will present the training requirements and hopefully share its training and credentialing rationales with other HIFU medical institutes.

Significant wave height (SWH) prediction can effectively improve the safety of marine activities and reduce the occurrence of maritime accidents, which is of great significance to national security and the development of the marine economy. In this study, we comprehensively analyzed the SWH prediction performance of the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit network (GRU) by considering different input lengths, prediction lengths, and model complexity. The experimental results show that (1) the input length impacts the prediction results of SWH, but it does not mean that the longer the input length, the better the prediction performance. When the input length is 24h, the prediction performance of RNN, LSTM, and GRU models is better. (2) The prediction length influences the SWH prediction results. As the prediction length increases, the prediction performance gradually decreases. Among them, RNN is not suitable for 48h long-term SWH prediction. (3) The more layers of the model, the better the SWH prediction performance is not necessarily. When the number of layers is set to 3 or 4, the model’s prediction performance is better.

Different types of traumatic brain injury (TBI) have posed a hazard to human health for a while, and their aftereffects have a significant negative impact on patients' quality of life. Despite the increased attention that TBI has received recently, the clinical treatment plan that is currently in place only consists of palliative therapy for neuroprotection or the mitigation of secondary injury, which has only a minimally positive impact on the prognosis and quality of life in TBI patients. After TBI, regenerative therapy seeks to improve the patient's function. Cell therapy, which has become one of the hottest research fields, is expected to improve the therapeutic effect of this disease. This article will briefly discuss recent developments in research of TBI and available treatments, and then give a general assessment of the outlook.

Multiple myeloma (MM) accounts for ~10% of all haematologic malignancies. Little is known about high intratumour heterogeneities in patients stratified by the Revised International Staging System (R-ISS). Herein, we constructed a single-cell transcriptome atlas to compare differential expression patterns among stages. We found that a novel cytotoxic plasma cell (PC) population exhibited with NKG7 positive was obviously enriched in stage II patients. Additionally, a malignant PC population with significantly elevated expression of MKI67 and PCNA was associated with unfavourable prognosis and Epstein-Barr virus (EBV) infection in our collected samples. Moreover, ribonucleotide reductase regulatory subunit M2 (RRM2) was found and verified to promote proliferation of MM cell lines, suggesting RRM2 may serve as a detrimental marker in MM. The percentages of CD8+ T cells and NKT cells decreased along with R-ISS stages, reflecting the plasticity of the tumour immune microenvironment. Importantly, their crosstalks with myeloid cells and PC identified several potential immunotargets such as SIRPA-CD47 and CD74-MIF, respectively. Collectively, this study provided an R-ISS-related single-cell MM atlas and revealed the clinical significance of novel PC clusters, as well as potential immunotargets in MM progression.

PurposeTo develop an appropriate machine learning model for predicting anaplastic lymphoma kinase (ALK) rearrangement status in non-small cell lung cancer (NSCLC) patients using computed tomography (CT) images and clinical features.Method and materialsThis study included 193 patients with NSCLC (154 in the training cohort, 39 in the validation cohort), 68 of whom tested positive for ALK rearrangements and 125 of whom tested negative. From the nonenhanced CT scans, 157 radiomic characteristics were extracted, and 8 clinical features were collected. Five machine learning (ML) models were assessed to find the best classification model for predicting ALK rearrangement status. A radiomic signature was developed using the least absolute shrinkage and selection operator (LASSO) algorithm. The predictive performance of the models based on radiomic features, clinical features, and their combination was assessed by receiver operating characteristic (ROC) curves.ResultsThe support vector machine (SVM) model had the highest AUC of 0.914 for classification. The clinical features model had an AUC=0.805 (95% CI 0.731–0.877) and an AUC=0.735 (95% CI 0.566–0.863) in the training and validation cohorts, respectively. The CT image-based ML model had an AUC=0.953 (95% CI 0.913–1.0) in the training cohort and an AUC=0.890 (95% CI 0.778–0.971) in the validation cohort. For predicting ALK rearrangement status, the ML model based on CT images and clinical features performed better than the model based on only clinical information or CT images, with an AUC of 0.965 (95% CI 0.826–0.882) in the primary cohort and an AUC of 0.914 (95% CI 0.804–0.893) in the validation cohort.ConclusionOur findings revealed that ALK rearrangement status could be accurately predicted using an ML-based classification model based on CT images and clinical data.

We herein report a rare case of leiomyoma of the urethra. A young woman with no history of malignancy was referred to our hospital because of a 1-year history of frequent urination, urgency, and dysuria. Postoperative pathologic examination confirmed the diagnosis of urethral leiomyoma. After tumor resection, the patient was followed up for 2 months in the outpatient department and developed no obvious postoperative complications such as urinary incontinence.

In this study, a femtosecond laser with a wavelength of 800 nm was used to modify the surface of a titanium alloy bone scaffold created via selective laser melting (SLM). The outcomes demonstrated that the surface morphology of the bone scaffold after femtosecond laser treatment was micro-nano morphology. The hydrophobic structure of the scaffold was changed into a super-hydrophilic structure, improving the surface roughness, which was highly helpful for osteoblast adhesion and differentiation. The femtosecond laser surface treatment in vitro samples produced a thick layer of hydroxyapatite (HAP) with improved surface bioactivity. The effectiveness of osseointegration and interstitial growth of the specimens treated with the femtosecond laser surface were found to be better when bone scaffolds were implanted into the epiphysis of the tibia of rabbits. As a result, femtosecond laser therapy dramatically enhanced the surface activity of bone scaffolds and their capacity to integrate with the surrounding bone tissues, serving as a trustworthy benchmark for future biological scaffold research.

Objectives Due to the functional requirements of structures, a large number of thin-walled structures with cutouts are adopted in the structural design of aviation, aerospace, shipbuilding and other fields, leading to a significant reduction in the bearing capacity of such structures. Although the curved stiffening method has great potential in improving the load-bearing performance of open structures, the sharp increase in design variables presents a challenge for structural optimization.The data-driven deep learning method is used to optimize the design of hierarchical stiffened thin-walled structures with cutouts reinforced by curvilinear stiffeners. Methods For structures with cutouts, the hierarchical curvilinearly stiffened method is designed, and the image representation method of structural parameters is proposed. The deep learning network model for structural response feature-learning is established to realize structural optimization design under data-driven conditions. Results The results show that compared with the classical surrogate models constructed by structural numerical parameters, the prediction accuracy of the proposed structural response feature-learning model based on image recognition is improved roughly twofold. In the optimization design of structures based on the learning model, the bearing capacity of hierarchical orthogonal stiffened structures increased by 10.78%, and the bearing capacity of hierarchical curvilinearly stiffened structures increased by 18.19%. Conclusions The results show that this deep learning-based structural optimization method is more effective for hierarchical stiffened structures with large numbers of design variables and dynamic changes in the number of design variables. Compared with traditional straightly stiffened panels, the curvilinearly stiffened panel is more effective in strengthening the bearing capacity of thin-walled structures with cutouts.

Significant wave height (SWH) prediction plays an important role in marine engineering fields such as fishery, exploration, power generation, and ocean transportation. Traditional SWH prediction methods based on numerical models cannot achieve high accuracy. In addition, the current SWH prediction methods are largely limited to single-point SWH prediction, without considering regional SWH prediction. In order to explore a new SWH prediction method, this paper proposes a deep neural network model for regional SWH prediction based on the attention mechanism, namely CBA-Net. In this study, the wind and wave height of the ERA5 data set in the South China Sea from 2011 to 2018 were used as input features to train the model to evaluate the SWH prediction performance at 1 h, 12 h, and 24 h. The results show that the single use of a convolutional neural network cannot accurately predict SWH. After adding the Bi-LSTM layer and attention mechanism, the prediction of SWH is greatly improved. In the 1 h SWH prediction using CBA-Net, SARMSE, SAMAPE, SACC are 0.299, 0.136, 0.971 respectively. Compared with the CNN + Bi-LSTM method that does not use the attention mechanism, SARMSE and SAMAPE are reduced by 43.4% and 48.7%, respectively, while SACC is increased by 5%. In the 12 h SWH prediction, SARMSE, SAMAPE, and SACC of CBA-Net are 0.379, 0.177, 0.954 respectively. In the 24 h SWH prediction, SARMSE, SAMAPE, and SACC of CBA-Net are 0.500, 0.236, 0.912 respectively. Although with the increase of prediction time, the performance is slightly lower than that of 12 h, the prediction error is still maintained at a small level, which is still better than other methods.

Sea surface temperature is an important physical parameter in marine research. Accurate prediction of sea surface temperature is important for coping with climate change, marine ecological protection, and marine economic development. In this study, the SST prediction performance of ConvLSTM and ST-ConvLSTM with different input lengths, prediction lengths, and hidden sizes is investigated. The experimental results show that: (1) The input length has an impact on the prediction results of SST, but it does not mean that the longer the input length, the better the prediction performance. ConvLSTM and ST-ConvLSTM have the best prediction performance when the input length is set to 1, and the prediction performance gradually decreases as the input length increases. (2) Prediction length affects SST prediction. As the prediction length increases, the prediction performance gradually decreases. When other parameters are kept constant and only the prediction length is changed, the ConvLSTM gets the best result when the prediction length is set to 2, and the ST-ConvLSTM gets the best result when the prediction length is set to 1. (3) The setting of the hidden size has a great influence on the prediction ability of the sea surface temperature, but the hidden size cannot be set blindly. For ST-ConvLSTM, although the prediction performance of SST is better when the hidden size is set to 128 than when it is set to 64, the consequent computational cost increases by about 50%, and the performance only improves by about 10%.

This paper reflects a Hong Kong doctors group's journey to learn the high-intensity focused ultrasound (HIFU) ablation treatment for gynecological diseases in China. The procedures of HIFU ablation for fibroids, adenomyosis, and other gynecological diseases are described. After completing our training, the authors applied the HIFU ablation techniques they have learned to establish an outpatient HIFU clinic and provided HIFU ablation treatment in Hong Kong. This paper describes their early experience in providing HIFU services.