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Ophthalmology is a subject that highly depends on imaging examination. Artificial intelligence (AI) technology has great potential in medical imaging analysis, including image diagnosis, classification, grading, guiding treatment and evaluating prognosis. The combination of the two can realize mass screening of grass-roots eye health, making it possible to seek medical treatment in the mode of “first treatment at the grass-roots level, two-way referral, emergency and slow treatment, and linkage between the upper and lower levels”. On the basis of summarizing the AI technology carried out by scholars and their teams all over the world in the field of ophthalmology, quite a lot of studies have confirmed that machine learning can assist in diagnosis, grading, providing optimal treatment plans and evaluating prognosis in corneal and conjunctival diseases, ametropia, lens diseases, glaucoma, iris diseases, etc. This paper systematically shows the application and progress of AI technology in common anterior segment ocular diseases, the current limitations, and prospects for the future.

Pores are among the primary defects in 316L stainless steel when fabricated through laser powder bed fusion (L-PBF). To better understand and precisely control the formation behavior of pores in the L-PBF-manufactured 316L stainless steel, effects of L-PBF process parameters on the melt pool and pore characteristics have been investigated. A method utilized for extreme values statistics analysis was also applied to investigate and predict the sizes of pores. Relationships among the count of measurements, the laser energy density, the reduced variate, and the maximum pore size were revealed. The findings showed an overall increase in melt pool depth as the laser energy densities was raised, yet the magnitude of this growth weakened as the laser energy density continued to increase. Conversely, it was discovered that the connection between the width of the melt pool and the density of laser energy exhibited a markedly less distinct correlation. As laser energy density escalated, there was a shift in the melt pool mode from conduction-based to a transitional phase, and upon further elevation of the laser energy density, it transitioned to keyhole mode. To obtain a reliable statistical analysis of pores, at least 40 measurements should be acquired for the estimation of the pore sizes by taking comprehensive consideration of time cost. Beside, in all three melt pool modes, at a fixed observation area, the maximum size of pores generally decreased with the escalation in laser energy densities.

Abstract The small Extracellular vesicles (sEV) has been recognized to be significant for intercellular communication due to their ability to transfer important cellular cargoes like miRNAs through circulation. The pituitary gland has not been clearly known about the role of its secreted sEV under normal physiological conditions. And Liver disease is a global public health burden. The present study is the first to investigate the effect of pituitary sEV on the liver. Sequencing and qRT-PCR revealed miR-143-3p is one of the richest in the pituitary sEV. MiR-143 Knockout (KO) mice resulted in a remarkable decrease in insulin-like growth factor 1 (IGF-1) levels and a significant increase in insulin-like growth factor binding protein 5 (IGFBP5) levels along with a reduction in liver primary cell growth. More importantly, compared with miR-143-KO-sEV, WT-sEV possesses a more robust capacity to improve miR-143 KO mice liver repair through the Wnt/β-catenin pathway after an acute injury caused by carbon tetrachloride (CCl4). Our results indicate that pituitary-derived sEV promotes hepatocyte proliferation and liver repair by its cargo miR-143-3p and provides new insight into the regulation mechanism of the pituitary-liver axis, and open a new window for endocrine regulation by using sEV.

As an alloying element in steel, manganese can considerably enhance the mechanical properties of structural steel. However, the Mn volatilisation loss in vacuum melting is severe because of the high saturated vapour pressure, resulting in an unstable Mn yield and Mn content fluctuation. Therefore, a systematic study of the volatilisation behaviour of Mn in vacuum melting is required to obtain a suitable Mn control process to achieve precise control of Mn composition, thereby providing a theoretical basis for industrial melting of high-Mn steel. In order to explore the Mn volatilization behavior, the volatilization thermodynamics and volatilisation rate of Mn, as well as the influence factors are discussed in this study. The results shows that Mn is extremely volatilised into the vapour phase under vacuum, the equilibrium partial pressure is closely related to Mn content and temperature. With an increase in the Mn content, a higher C content has a more obvious inhibitory effect on the equilibrium partial pressure of Mn. The maximum theoretical volatilisation rate of Mn shows a linear upward trend with an increase in Mn content. However, a higher C content has a more obvious effect on the reduction of the maximum theoretical volatilisation rate with the increase of Mn content. This study provides an improved understanding of Mn volatilisation behaviour as well as a theoretical foundation for consistent Mn yield control during the vacuum melting process of high-Mn steel.

Integrated energy system (IES) is the key to achieve the “dual carbon goals” in face of the current energy industry transformation and low-carbon development. In order to improve the carbon emission reduction capacity of the IES, it is necessary to make full use of the load resources on the demand side and the generalized energy storage resources such as traditional energy storage equipment to participate in the optimization of the IES. First, an IES optimization operation model considering renewable energy, energy conversion equipment, generalized energy storage equipment, and energy market transaction is established. Then, the life cycle assessment (LCA) method is used to calculate the carbon emission of the whole process of energy cycle and equipment cycle in the IES, and the carbon emission cost is included in the total cost of the system. The results of simulation experiments show that the proposed model is not only conducive to reducing the total scheduling cost of the IES, but also able to reduce the carbon emissions of the system and effectively promote the low-carbon development of the IES.

Abstract Scene text in natural images carries additional semantic information to aid in image classification. Existing methods lack full consideration of the deep understanding of the text and the visual text relationship, which results in the difficult to judge the semantic accuracy and the relevance of the visual text. This paper proposes image classification based on Cross modal Knowledge Learning of Scene Text (CKLST) method. CKLST consists of three stages: cross‐modal scene text recognition, text semantic enhancement, and visual‐text feature alignment. In the first stage, multi‐attention is used to extract features layer by layer, and a self‐mask‐based iterative correction strategy is utilized to improve the scene text recognition accuracy. In the second stage, knowledge features are extracted using external knowledge and are fused with text features to enhance text semantic information. In the third stage, CKLST realizes visual‐text feature alignment across attention mechanisms with a similarity matrix, thus the correlation between images and text can be captured to improve the accuracy of the image classification tasks. On Con‐Text dataset, Crowd Activity dataset, Drink Bottle dataset, and Synth Text dataset, CKLST can perform significantly better than other baselines on fine‐grained image classification, with improvements of 3.54%, 5.37%, 3.28%, and 2.81% over the best baseline in mAP, respectively.

ObjectiveBacterial vaginosis is a disease caused by vaginal microecology disorder, which seriously affects female health. At present, there are many drugs to treat BV, and this study aims to compare the efficacy and safety of multiple drugs for BV through a network meta-analysis (NMA).MethodsAll studies were sourced from PubMed and Embase databases from the establishment date to April 13, 2023. We evaluated the clinical cure success rate and adverse effects (abnormal increase in vaginal discharge, external genital irritation, and vulvar itching) and performed subgroup analyses of the clinical cure success rate for different modes of administration. All statistical analyses were performed using R and STATA 14.0 software for network meta-analysis.ResultsWe included 42 studies that met the criteria, involving a total of 8382 patients. Network meta-analysis results showed that metronidazole and secnidazole had a higher rate of adverse reactions than placebo (RR 7.06; 95%-CI 2.61-19.10, RR 4.03; 95%-CI 1.63-9.98), the adverse reaction rate of probiotics group was lower than that of metronidazole group (RR 0.44; 95%-CI 0.21-0.93). The clinical cure rate of oral ornidazole was better than clindamycin (RR 16.08; 95%-CI 1.72-150.47), Secnidazole (RR 8.17; 95%-CI 1.66-40.25) and probiotics. Direct meta-analysis results showed that ornidazole had a better clinical cure rate than Secnidazole (RR 1.22; 95%-CI 1.10-1.34), oral ornidazole had a better clinical cure rate than Secnidazole (RR 1.23; 95%-CI 1.11-1.36). The clinical cure rate of vaginal application of sucrose was better than metronidazole (RR 1.12; 95%-CI 1.03-1.21) and metronidazole had a lower clinical cure rate than probiotics (RR 0.68; 95%-CI 0.52-0.88).ConclusionsThe results of this systematic review and network meta-analysis suggest that ornidazole may be an effective alternative for the treatment of BV, and that sucrose and probiotics are potential BV treatments that need to be validated by more high-quality clinical studies in the future.

PurposeThis retrospective study aimed to explore the efficiency and untoward reaction of liposomal paclitaxel versus docetaxel for locally advanced nasopharyngeal carcinoma (NPC).MethodsThis retrospective study included 115 patients diagnosed with NPC at our hospital between January 2018 and December 2021. Patients were stratified into two groups based on their treatment with either liposomal paclitaxel (n = 71) or docetaxel (n = 44) as part of the neoadjuvant chemotherapy regimen. Objective response rate (ORR), progression-free survival (PFS), locoregional relapse-free survival (LRFS), distant metastasis-free survival (DMFS), and overall survival (OS) were compared between the two groups.ResultsORR was significantly improved in the liposomal paclitaxel group than in the docetaxel group (62.0% versus 40.9%, p = 0.028). The 3-year PFS (PFS: 84.4% versus 77.5%, p = 0.303), LRFS (95.8% versus 94.4%, p = 0.810), DMFS (87.2% versus 83.0%, p = 0.443), and OS (90.7% versus 88.8%, p = 0.306) revealed no significance. The neutrophil-to-lymphocyte ratio [hazard ratio (HR): 3.510; p = 0.039] and distant metastasis (HR: 4.384; p = 0.035) were regarded as the risk factors using multivariate regression analysis. Moreover, the incidence of leukopenia at grades 1–2 in the liposomal paclitaxel group was significantly lower than that in the docetaxel group (28.1% versus 79.5%, p < 0.05).ConclusionsLiposomal paclitaxel had better efficacy in terms of short-term effects and lower incidence of leukopenia at grades 1–2 compared with the docetaxel group.

Ridge–furrow with plastic film mulching (RFPFM) is quite successful under dryland agriculture. However, its suitability for sunflower (Helianthus annuus L.) production with different plastic film mulching techniques such as ridge–furrow fully covered with plastic film mulching (FM) and half mulching (HM), in combination with appropriate nitrogen (N) fertilizer management remains uncertain. The current research investigated the performance of sunflower crop under three planting patterns (HM, FM and CP, i.e., conventional planting on flat land without plastic film mulching) and two N doses (120 and 240 kg N ha–1) in northwest China. The objectives were to evaluate the soil hydrothermal conditions, crop performance, water productivity (WP), N harvest index (NHI) and seed yield, under different combinations of these treatments. The results showed that both HM and FM had 1.8 °C higher topsoil temperature during seedling stage and soil moisture (+21 % and +30 %) during the whole growth stage, respectively, when compared to CP. The favorable hydrothermal conditions under HM and FM accelerated the seedling emergence and shortened the crop growth duration by nearly 5 days, and further improved seed yield (+23 and +33 %), WP (+26 and +36 %), and N uptake (+20 and +24 %), compared to CP. A comparison between FM and HM treatments did not show a significant increase in WP or yield for the former, despite improved soil hydrothermal conditions. In addition, increasing N application rate from 120 to 240 kg N ha–1 did not lead to a consistent and significant effect on total N uptake, WP and seed yield. Overall, the present study suggests that HM, when coupled with a reduced N dose, can replace FM in sunflower production. This approach reduces the use of plastic film and N fertilizer, while efficiently conserving water, enhancing WP and improving seed yield of sunflower under dry and semi–humid conditions.

Objective To analyze the therapeutic effect of microsurgery on patients with severe aneurysmal subarachnoid hemorrhage (SaSAH). Methods A retrospective analysis was conducted on 14 SaSAH patients admitted to Beijing Chao-Yang Hospital, Capital Medical University from December 2017 to November 2019. General information, Hunt Hess grading, Glasgow Coma Scale (GCS), time of rebleeding, surgery time, examination method, aneurysm size, prognosis, and postoperative follow-up were collected. Results A total of 14 patients with SaSAH were enrolled, including 5 males and 9 females, 8 patients with Hunt-Hess grade Ⅳ and 6 with grade Ⅴ. Seven cases experienced rebleeding after admission, with an average time between the onset of symptoms and rebleeding being 11.21 hours. Intracranial aneurysm rupture was confirmed by computed tomography angiography (CTA) or digital subtraction angiography (DSA) before operation in 13 cases. All 14 patients underwent microsurgical aneurysm clipping after definite diagnosis. There were 5 cases of transtentorial herniation and 3 cases of subfalcine herniation. Bone flaps were removed during surgery for all patients with cerebral herniation. In 14 cases, Glasgow prognostic score (GOS) was 4 in 2 cases, 3 in 3 cases, 2 in 7 cases, and 1 in 2 case at 6 months follow-up. Conclusion Treating SaSAH responsible aneurysms within 24 hours is an important principle for preventing intracranial rebleeding, reducing mortality, and improving prognosis. Microsurgery remains an important method for treating SaSAH, especially for patients with intracranial hematoma and progressive intracranial hypertension."

Abstract Background Elizabethkingia is emerging as an opportunistic pathogen in humans. The aim of this study was to investigate the clinical epidemiology, antimicrobial susceptibility, virulence factors, and genome features of Elizabethkingia spp. Methods Clinical data from 71 patients who were diagnosed with Elizabethkingia-induced pneumonia and bacteremia between August 2019 and September 2021 were analyzed. Whole-genome sequencing was performed on seven isolates, and the results were compared with a dataset of 83 available Elizabethkingia genomes. Genomic features, Kyoto Encyclopedia of Genes and Genomes (KEGG) results and clusters of orthologous groups (COGs) were analyzed. Results The mean age of the patients was 56.9 ± 20.7 years, and the in-hospital mortality rate was 29.6% (21/71). Elizabethkingia strains were obtained mainly from intensive care units (36.6%, 26/71) and emergency departments (32.4%, 23/71). The majority of the strains were isolated from respiratory tract specimens (85.9%, 61/71). All patients had a history of broad-spectrum antimicrobial exposure. Hospitalization for invasive mechanical ventilation or catheter insertion was found to be a risk factor for infection. The isolates displayed a high rate of resistance to cephalosporins and carbapenems, but all were susceptible to minocycline and colistin. Genomic analysis identified five β-lactamase genes (bla GOB, bla BlaB, bla CME, bla OXA, and bla TEM) responsible for β-lactam resistance and virulence genes involved in stress adaptation (ureB/G, katA/B, and clpP), adherence (groEL, tufA, and htpB) and immune modulation (gmd, tviB, cps4J, wbtIL, cap8E/D/G, and rfbC). Functional analysis of the COGs revealed that “metabolism” constituted the largest category within the core genome, while “information storage and processing” was predominant in both the accessory and unique genomes. The unique genes in our 7 strains were mostly enriched in KEGG pathways related to microRNAs in cancer, drug resistance (β-lactam and vancomycin), ABC transporters, biological metabolism and biosynthesis, and nucleotide excision repair mechanisms. Conclusion The Elizabethkingia genus exhibits multidrug resistance and carries carbapenemase genes. This study presents a comparative genomic analysis of Elizabethkingia, providing knowledge that facilitates a better understanding of this microorganism.

To address the issue of partial feature loss in the single processing method within the time-frequency domain for roll grinding chatter, a combined time-frequency domain method is proposed to process signal feature. An intelligent algorithm is used to achieve online prediction of roll grinding chatter. Firstly, the empirical mode decomposition (EMD) method is utilized to decompose the vibration sensor signals, extrating the intrinsic mode function (IMF) while removing "spurious components" to calculate time domain characteristics associated with roll grinding chatter. Then, wavelet packet energy entropy is used to solve the frequency band node energy entropy values of acoustic emission sensor signals, obtaining frequency domain features characterizing the roll grinding chatter. Finally, the time-frequency domain features after dimension reduction is substituted into the intelligent algorithm model for online prediction of the roller grinding process. The results show that the the LV-SVM model achieves an average classification accuracy of 92.75%, with an average response time of 0.776 5 s. This verifies the validity of EMD and LV-SVM based on wavelet packet energy entropy in the time-frequency domain for online prediction of roller grinding chatter.