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A deformation coordination method is proposed in this study to account for the distortion effects on a box girder. The differential equation for distortion in vertical web box girders is derived based on the deformation coordination condition of the distortion angle, considering both external loads and internal forces. Subsequently, a comparative analysis is conducted to explore the similarities and differences between the differential equations derived from the proposed deformation coordination method, the plate element analysis method and the total potential energy variation method. The accuracy of the proposed approach is verified through bench-scale tests and numerical simulations. The findings indicate that the derived governing distortion differential equation and distortion attenuation coefficients in the proposed method align with those obtained from the plate element analysis method and the total potential energy variational method, which enhances the applicability to allow for the distortion equations to be obtained simply by calculating the distortion displacements. The analytical findings regarding the distortion warping normal stresses on the cross-sections of the box girders demonstrate favorable correspondence with the experimental results, displaying an acceptable error ranging from - 0.3% to 5.4%. Moreover, the peak of distortion warping normal stresses on the mid-span cross-section increases with higher span-to-depth ratios and height-to-thickness ratios of the web. Consequently, augmenting the thickness of the box wall proves to be an effective means of reducing the distortion effect in box girders.
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Background: Preoperative nutritional support studies for patients undergoing gastrointestinal (GI) surgery mostly focused on enteral nutrition (EN) or long-term (≥7 days) parenteral nutrition (PN). Some studies also found that preoperative short-term PN could improve the postoperative short-term nutritional status of tumor patients. But whether short-term PN support (1-6 days) before surgery can improve the prognosis of patients undergoing surgery for gastric cancer (GC) remains unclear. Therefore, we focused on assessing the effect of preoperative short-term PN on the outcomes of patients undergoing radical surgery for GC. Methods: A retrospective analysis of 1,155 patients who underwent radical gastrectomy for GC between July 2014 and February 2019 was conducted. According to whether patients received short-term (1-6 days) PN support before surgery, patients were divided into non-PN group and PN group. After 1:1 propensity score matching (PSM), two groups of patients with similar baseline clinical characteristics were obtained. The incidence of various complications and overall survival (OS) rate were compared between the two groups, and logistic regression analysis for complications, Cox regression analysis for OS, and subgroup analysis were performed. Results: Each group had 478 patients after PSM, and the clinical characteristics were balanced. There were no significant differences in overall postoperative complications (pre-PSM: P=0.495; post-PSM: P>0.99), postoperative length of stay (LOS; pre-PSM: P=0.092; post-PSM: P=0.460), or readmission rate within 30 days (pre-PSM: P=0.496; post-PSM: P=0.793) between the two groups before and after PSM. The OS of PN group before matching was lower than that of non-PN group (P=0.023), but this difference was not significant after matching (P=0.950), but the PN group's hospitalization expenses were substantially greater than those of the control group (post-PSM: P<0.001). Preoperative short-term PN support was not an independent factor in the incidence of postoperative complications (P>0.99) and OS (P=0.949). Subgroup analyses failed to identify those patients who might benefit from preoperative short-term PN support. Conclusions: Preoperative short-term PN support may have no significant benefit on short-term postoperative complications or the long-term OS of patients with GC but increase hospitalization costs. It thus should not be the first choice of treatment for these patients.
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Edwardsiella piscicida is a severe fish pathogen with wide host range, causing the huge economic losses in the aquaculture industry. Cyclic adenosine monophosphate (cAMP) as an important second messenger regulates the physiological and behavioral responses to environmental cues in eukaryotic and prokaryotic. The intracellular level of cAMP for effective activity is tightly controlled by the synthesis of adenylate cyclase, excretion and degradation of phosphodiesterase. In this study, we identified and characterized a class III cAMP phosphodiesterase, named as CpdA, in the E. piscicida. To investigate the role of CpdA in the physiology and pathogenicity, we constructed the in-frame deletion mutant of cpdA of E. piscicida, TX01ΔcpdA. The results showed that TX01ΔcpdA accumulated the higher intracellular cAMP concentration than TX01, indicating that CpdA exerted the hydrolysis of cAMP. In addition, compared to the TX01, the TX01ΔcpdA slowed growth rate, diminished biofilm formation and lost motility. More importantly, pathogenicity analysis confirmed that TX01ΔcpdA significantly impaired the ability of invading the epithelial cells, reproduction in macrophages, tissues dissemination and lethality for healthy tilapias. The most of lost properties of TX01ΔcpdA were restored partially or fully by the introduction of cpdA gene. These results suggest that cpdA is required for regulation of the physiology and virulence of E. piscicida.
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Edwardsiella , Infecções por Enterobacteriaceae , Doenças dos Peixes , Animais , Virulência , Diester Fosfórico Hidrolases/genética , AMP Cíclico/metabolismo , Biofilmes , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismoRESUMO
α-Aryl substituted nitroalkanes are valuable synthetic building blocks that can be easily converted into α-aryl substituted aldehydes, ketones, carboxylic acids, as well as amines. Herein, an efficient Cu/oxalamide-catalyzed coupling between nitroalkanes and (hetero)aryl halides (Br, I) was developed to direct access highly diverse α-aryl substituted nitroalkanes. Compared with the current state of art, this protocol is more environmentally friendly and practical for synthetic chemists. This approach is characterized by a broad substrate scope on both nitroalkane part (primary nitroalkanes and nitromethane) and sp2 halide part ((hetero)aryl bromides/iodides and alkenyl bromides/iodides). The excellent functional group tolerance was observed, which would enable real world synthetic applications. More importantly, TON of current transformation reached to 3640, when some aryl iodides were used as coupling partners. This represents currently the highest catalyst turnover for transition-metal catalyzed α-arylation of nitroalkanes. Furthermore, the successful application in late-stage modification of complex molecules and synthesis of a known retinoid X receptor (RXR) antagonist exemplified its synthetic potential.
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Laryngeal cancer poses a significant global health burden, with late-stage diagnoses contributing to reduced survival rates. This study explores the application of deep convolutional neural networks (DCNNs), specifically the Densenet201 architecture, in the computer-aided diagnosis of laryngeal cancer using laryngoscopic images. Our dataset comprised images from two medical centers, including benign and malignant cases, and was divided into training, internal validation, and external validation groups. We compared the performance of Densenet201 with other commonly used DCNN models and clinical assessments by experienced clinicians. Densenet201 exhibited outstanding performance, with an accuracy of 98.5% in the training cohort, 92.0% in the internal validation cohort, and 86.3% in the external validation cohort. The area under the curve (AUC) values consistently exceeded 92%, signifying robust discriminatory ability. Remarkably, Densenet201 achieved high sensitivity (98.9%) and specificity (98.2%) in the training cohort, ensuring accurate detection of both positive and negative cases. In contrast, other DCNN models displayed varying degrees of performance degradation in the external validation cohort, indicating the superiority of Densenet201. Moreover, Densenet201's performance was comparable to that of an experienced clinician (Clinician A) and outperformed another clinician (Clinician B), particularly in the external validation cohort. Statistical analysis, including the DeLong test, confirmed the significance of these performance differences. Our study demonstrates that Densenet201 is a highly accurate and reliable tool for the computer-aided diagnosis of laryngeal cancer based on laryngoscopic images. The findings underscore the potential of deep learning as a complementary tool for clinicians and the importance of incorporating advanced technology in improving diagnostic accuracy and patient care in laryngeal cancer diagnosis. Future work will involve expanding the dataset and further optimizing the deep learning model.
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Introduction: Arteriovenous fistula (AVF) is the first choice of vascular access for hemodialysis treatment, and its surgical maturity rate is not high, and its postoperative complications (mostly stenosis) significantly shorten its life. At present, there are few studies on treatment methods to improve the maturity and survival of AVF. In this study, the effect of far infrared therapy (FIR) on the maturity and longevity of arteriovenous fistula in hemodialysis patients was discussed, and the protective mechanism of AVF induced by FIR therapy was explored, aiming at exploring a new treatment method. Methods: The hemodialysis patients admitted to the 900th Hospital of the Chinese Joint Logistics Support Force of the People's Liberation Army from January 2021 to April 2023 were randomly divided into control group and intervention group, with 40 cases in each group. Among them, the control group was coated with mucopolysaccharide polysulfonate cream; Intervention group: The patients were treated with mucopolysaccharide polysulfonate cream and far infrared radiation at the same time. After 3 months' intervention, the arteriovenous fistula (vein diameter, mature time of arteriovenous fistula, blood flow controlled by pump during dialysis, blood flow of brachial artery during dialysis and the occurrence of complications of internal fistula (oozing, occlusion and infection) and the pain score (numerical rating scale, NRS) of the two groups were compared, and the curative effects were compared. Results: There was no significant difference in general data between the two groups (P > 0.05), which indicated that the study was comparable. After 3 months' intervention, the vein diameter, pump-controlled blood flow and brachial artery blood flow in the intervention group were significantly higher than those in the control group (P < 0.05). And the maturity time, NRS score and complication rate of arteriovenous fistula were significantly lower than those of the control group (P < 0.05). The primary patency rate of AVF in the intervention group was higher than that in the control group, and the overall patency rate between the two groups was statistically significant (P < 0.05). Conclusions: As a promising new treatment method, far infrared therapy can effectively promote the maturity of AVF, increase venous diameter, pump controlled blood flow during dialysis, brachial artery blood flow during dialysis, and prolong the service life of AVF.
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BACKGROUND: Propranolol is the first choice for treating infantile hemangioma (IH). How propranolol works in IH remains unclear. Infantile hemangioma endothelial cells (HemECs) express Notch1, Jagged, Hey1, and other molecules in the Notch pathway, suggesting that Notch pathway-related molecules play an important role in affecting vascular endothelial cell proliferation. Whether propranolol can affect the Notch signaling pathway in IH treatment is unclear. METHODS: We performed this study to observe the effect of propranolol on the expression of Notch signaling pathway molecules in human umbilical vein endothelial cells (HUVECs) and to explore the therapeutic mechanism of propranolol on IH. HUVECs cultured in vitro were exposed to 60, 120, 240, 360, or 480 µM propranolol. The morphological changes of the HUVECs were observed under an inverted microscope. HUVECs proliferation was detected with Cell Counting Kit-8 (CCK-8). The effects of propranolol on HUVECs apoptosis were detected by flow cytometry. The role of Notch in propranolol inhibition of HUVEC proliferation was analyzed with real-time polymerase chain reaction (PCR) and western blotting. RESULTS: Propranolol reduced HUVECs numbers and altered their morphology. The inhibitory effect of propranolol on cell proliferation was dependent on the reaction time and drug concentration. Propranolol upregulated Jagged1, Notch1, and Hey1 expression and downregulated delta-like ligand4 (DLL4) expression. CONCLUSIONS: Propranolol may play a role in IH treatment by increasing Jagged1 expression in endothelial cells, activating the Notch pathway and inducing the upregulation of the downstream target gene HEY1.
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Hemangioma , Propranolol , Humanos , Células Endoteliais da Veia Umbilical Humana , Propranolol/farmacologia , Propranolol/uso terapêutico , Transdução de Sinais/genética , Hemangioma/tratamento farmacológico , Hemangioma/genética , Biologia , Proliferação de CélulasRESUMO
Haemophilus parasuis is a commensal organism of the upper respiratory tract of pigs, but virulent strains can cause Glässer's disease, resulting in significant economic losses to the swine industry. OmpP2 is an outer membrane protein of this organism that shows considerable heterogeneity between virulent and non-virulent strains, with classification into genotypes I and II. It also acts as a dominant antigen and is involved in the inflammatory response. In this study, 32 monoclonal antibodies (mAbs) against recombinant OmpP2 (rOmpP2) of different genotypes were tested for reactivity to a panel of OmpP2 peptides. Nine linear B cell epitopes were screened, including five common genotype epitopes (Pt1a, Pt7/Pt7a, Pt9a, Pt17, and Pt19/Pt19a) and two groups of genotype-specific epitopes (Pt5 and Pt5-II, Pt11/Pt11a, and Pt11a-II). In addition, we used positive sera from mice and pigs to screen for five linear B-cell epitopes (Pt4, Pt14, Pt15, Pt21, and Pt22). After porcine alveolar macrophages (PAMs) were stimulated with overlapping OmpP2 peptides, we found that the epitope peptides Pt1 and Pt9, and the loop peptide Pt20 which was adjacent epitopes could all significantly upregulated the mRNA expression levels of IL-1α, IL-1ß, IL-6, IL-8, and TNF-α. Additionally, we identified epitope peptides Pt7, Pt11/Pt11a, Pt17, Pt19, and Pt21 and loop peptides Pt13 and Pt18 which adjacent epitopes could also upregulate the mRNA expression levels of most proinflammatory cytokines. This suggested that these peptides may be the virulence-related sites of the OmpP2 protein, with proinflammatory activity. Further study revealed differences in the mRNA expression levels of proinflammatory cytokines, including IL-1ß and IL-6, between genotype-specific epitopes, which may be responsible for pathogenic differences between different genotype strains. Here, we profiled a linear B-cell epitope map of the OmpP2 protein and preliminarily analyzed the proinflammatory activities and effects of these epitopes on bacterial virulence, providing a reliable theoretical basis for establishing a method to distinguish strain pathogenicity and to screen candidate peptides for subunit vaccines.
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Infecções por Haemophilus , Haemophilus parasuis , Doenças dos Suínos , Suínos , Animais , Camundongos , Epitopos de Linfócito B/genética , Interleucina-6/metabolismo , Citocinas/metabolismo , Proteínas da Membrana Bacteriana Externa/genética , Proteínas da Membrana Bacteriana Externa/metabolismo , Infecções por Haemophilus/microbiologia , Doenças dos Suínos/microbiologia , RNA Mensageiro/metabolismoRESUMO
BACKGROUND: With the increasing number of studies on osteoporosis and muscle adipose tissue, existing studies have shown that skeletal muscle tissue and adipose tissue are closely related to osteoporosis by dual-energy x-ray absorptiometry (DXA) measurement. However, few studies have explored whether the skeletal muscle and adipose tissue index measured at the lumbar spine 3 (L3) level are closely related to bone mineral density (BMD) and can even predict osteoporosis. Therefore, this study aimed to prove whether skeletal muscle and adipose tissue index measured by computed tomography (CT) images based on a single layer are closely related to BMD. METHODS: A total of 180 participants were enrolled in this study to obtain skeletal muscle index (SMI), psoas muscle index (PMI), subcutaneous fat index (SFI), visceral fat index (VFI), and the visceral-to-subcutaneous ratio of the fat area (VSR) at L3 levels and divide them into osteoporotic and normal groups based on the T-score of DXA. Spearman rank correlation was used to analyze the correlation between SMI, PMI, SFI, VFI, VSR, and BMD. Similarly, spearman rank correlation was also used to analyze the correlation between SMI, PMI, SFI, VFI, VSR, and the fracture risk assessment tool (FRAX). Receiver operating characteristic (ROC) was used to analyze the efficacy of SMI, PMI, SFI, VFI, and VSR in predicting osteoporosis. RESULTS: BMD of L1-4 was closely correlated with SMI, PMI, VFI and VSR (r = 0.199 p = 0.008, r = 0.422 p < 0.001, r = 0.253 p = 0.001, r = 0.310 p < 0.001). BMD of the femoral neck was only correlated with PMI and SFI (r = 0.268 p < 0.001, r = - 0.164 p-0.028). FRAX (major osteoporotic fracture) was only closely related to PMI (r = - 0.397 p < 0.001). FRAX (hip fracture) was closely related to SMI and PMI (r = - 0.183 p = 0.014, r = - 0.353 p < 0.001). Besides, FRAX (major osteoporotic fracture and hip fracture) did not correlate with VFI, SFI, and VSR. SMI and PMI were statistically significant, with the area under the curve (AUC) of 0.400 (95% confidence interval 0.312-0.488 p = 0.024) and 0.327 (95% confidence interval 0.244-0.410 p < 0.001), respectively. VFI, SFI, and VSR were not statistically significant in predicting osteoporosis. CONCLUSIONS: This study demonstrated that L3-based muscle index could assist clinicians in the diagnosis of osteoporosis to a certain extent, and PMI is superior to SMI in the diagnosis of osteoporosis. In addition, VFI, SFI, and VSR do not help clinicians to diagnose osteoporosis well.
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Fraturas do Quadril , Osteoporose , Fraturas por Osteoporose , Humanos , Fraturas por Osteoporose/diagnóstico , Músculos Psoas/diagnóstico por imagem , Fatores de Risco , Medição de Risco/métodos , Osteoporose/diagnóstico por imagem , Absorciometria de Fóton/métodos , Densidade Óssea/fisiologia , Fraturas do Quadril/diagnóstico , Vértebras Lombares/diagnóstico por imagem , Tomografia Computadorizada por Raios XRESUMO
As defined by the Global Leaders Malnutrition Initiative (GLIM), malnutrition is strongly associated with a lower quality of life and poor prognosis in gastric cancer patients. However, few studies have precisely explored the predictors of malnutrition, as defined by the GLIM, for overall survival (OS) after gastric cancer surgery in subgroups of patients stratified according to population characteristics. Our research aimed to analyze whether the predictors of malnutrition defined by the GLIM for postoperative OS in gastric cancer patients differ across subgroups. Patients who underwent radical gastric cancer surgery at our center between July 2014 and February 2019 were included in the study. Propensity score matching (PSM) was used to minimize bias. The study population was divided into malnourished and normal groups based on whether they were malnourished as defined by the GLIM. Univariate and multivariate analyses were performed to identify the risk factors affecting OS. The Kaplan-Meier curve and log-rank test were performed to determine the survival rate difference between subgroups. Overall, 1,007 patients were enrolled in the research. Multivariate analysis showed that malnutrition among the patients was 33.47%. Additionally, GLIM-defined malnutrition was an independent risk factor [hazard ratio (HR): 1.429, P = 0.001] for a shorter OS in gastric cancer patients. Furthermore, subgroup analysis showed that the GLIM was more appropriate for predicting OS in older aged patients (≥65 years), females, those with comorbidities (Charlson comorbidity index ≥ 2), and those with advanced gastric cancer (TNM stage = 3). GLIM-defined malnutrition affects the long-term survival of gastric cancer patients, especially older patients, females, patients with comorbidities, and patients with advanced gastric cancer.
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Isocyanides are common compounds in fine and bulk chemical syntheses. However, the direct addition of isocyanide to simple unactivated cyclopropene via transition metal catalysis is challenging. Most of the current approaches focus on 1,1-insertion of isocyanide to M-R or nucleophilc insertion. That is often complicated by the competitive homo-oligomerization reactivity occurring at room temperature, such as isocyanide 1,1-insertion by Ni(II). Here we show a (N-heterocyclic carbene)Ni(II) catalyst that enables cyclopropene-isocyanide [5 + 1] benzannulation. As shown in the broad substrate scope and a [trans-(N-heterocyclic carbene)Ni(isocyanide)Br2] crystal structure, the desired cross-reactivity is cooperatively controlled by the high reactivity of the cyclopropene, the sterically bulky N-heterocyclic carbene, and the strong coordination ability of the isocyanide. This direct addition strategy offers aromatic amine derivatives and complements the Dötz benzannulation and Semmelhack/Wulff 1,4-hydroquinone synthesis. Several sterically bulky, fused, and multi-substituted anilines and unsymmetric functionalized spiro-ring structures are prepared from those easily accessible starting materials expediently.
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Model fine-tuning is a widely used transfer learning approach in person Re-identification (ReID) applications, which fine-tuning a pre-trained feature extraction model into the target scenario instead of training a model from scratch. It is challenging due to the significant variations inside the target scenario, e.g., different camera viewpoint, illumination changes, and occlusion. These variations result in a gap between each mini-batch's distribution and the whole dataset's distribution when using mini-batch training. In this paper, we study model fine-tuning from the perspective of the aggregation and utilization of the dataset's global information when using mini-batch training. Specifically, we introduce a novel network structure called Batch-related Convolutional Cell (BConv-Cell), which progressively collects the dataset's global information into a latent state and uses it to rectify the extracted feature. Based on BConv-Cells, we further proposed the Progressive Transfer Learning (PTL) method to facilitate the model fine-tuning process by jointly optimizing BConv-Cells and the pre-trained ReID model. Empirical experiments show that our proposal can greatly improve the ReID model's performance on MSMT17, Market-1501, CUHK03, and DukeMTMC-reID datasets. Moreover, we extend our proposal to the general image classification task. The experiments in several image classification benchmark datasets demonstrate that our proposal can significantly improve baseline models' performance. The code has been released at https://github.com/ZJULearning/PTL.
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Aprendizado de Máquina , HumanosRESUMO
Background: Spontaneous isolated superior mesenteric artery dissection (SISMAD) is a rare disease with abdominal pain as the main clinical manifestation, but its optimal treatment strategy has not yet been determined. Based on this, this study explored a safe and effective treatment method by analyzing and comparing the safety and efficacy of conservative treatment and endovascular treatment in SISMAD patients. Methods: The clinical and imaging data and treatment effects of 85 patients with SISMAD who were admitted to the General Surgery Department of the 900th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army from January 2008 to December 2020 were retrospectively analyzed. Two groups were treated, the data of patients in conservative treatment group and endovascular treatment group were analyzed, and a safe and effective treatment method for SISMAD was discussed. Results: The mean follow-up time was 36.58 ± 25.03â months. The success rate of interventional operation was 86.11% (31/36), and the operation failed because the guide wire could not enter the true lumen in four cases. One case was terminated due to poor physical condition of the patient who could not tolerate surgery. There were no significant differences in gender, body mass index, clinical manifestations, and past history between conservative treatment and endovascular treatment (P > 0.05), but in age, superior mesenteric artery-distal aorta angle, distance from the superior mesenteric artery opening to dissection, dissection length, and true lumen stenosis. There was a statistical difference between the two groups in the rate and Yun classification (P < 0.05). Conclusions: Conservative treatment is effective for most symptomatic SISMAD patients, and close monitoring is required; for patients with persistent symptoms and severe true lumen stenosis (especially Yun classification type III), endovascular treatment is preferred; endovascular treatment is mainly based on endovascular bare stent placement. Patients receiving stent implantation may suffer from stent stenosis or occlusion in the long term, and most of them have no obvious symptoms of intestinal ischemia; the prognosis is good.
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In recent years, supervised hashing has been validated to greatly boost the performance of image retrieval. However, the label-hungry property requires massive label collection, making it intractable in practical scenarios. To liberate the model training procedure from laborious manual annotations, some unsupervised methods are proposed. However, the following two factors make unsupervised algorithms inferior to their supervised counterparts: (1) Without manually-defined labels, it is difficult to capture the semantic information across data, which is of crucial importance to guide robust binary code learning. (2) The widely adopted relaxation on binary constraints results in quantization error accumulation in the optimization procedure. To address the above-mentioned problems, in this paper, we propose a novel Unsupervised Discrete Hashing method (UDH). Specifically, to capture the semantic information, we propose a balanced graph-based semantic loss which explores the affinity priors in the original feature space. Then, we propose a novel self-supervised loss, termed orthogonal consistent loss, which can leverage semantic loss of instance and impose independence of codes. Moreover, by integrating the discrete optimization into the proposed unsupervised framework, the binary constraints are consistently preserved, alleviating the influence of quantization errors. Extensive experiments demonstrate that UDH outperforms state-of-the-art unsupervised methods for image retrieval.
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BACKGROUND: Systemic corticosteroids are now recommended in many treatment guidelines, although supporting evidence is limited to 1 randomized controlled clinical trial (RECOVERY). OBJECTIVE: To identify whether corticosteroids were beneficial to COVID-19 patients. METHODS: A total of 1514 severe and 249 critical hospitalized COVID-19 patients from 2 medical centers in Wuhan, China. Multivariable Cox models, Cox model with time-varying exposure and propensity score analysis (inverse-probability-of-treatment-weighting [IPTW] and propensity score matching [PSM]) were used to estimate the association of corticosteroid use with risk of in-hospital mortality in severe and critical cases. RESULTS: Corticosteroids were administered in 531 (35.1%) severe and 159 (63.9%) critical patients. Compared to the non-corticosteroid group, systemic corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality in either severe cases (HRâ =â 1.77; 95% CI, 1.08-2.89; Pâ =â 0.023), or critical cases (HRâ =â 2.07; 95% CI, 1.08-3.98; Pâ =â 0.028). Findings were similar in time-varying Cox analysis. For patients with severe COVID-19 at admission, corticosteroid use was not associated with improved or harmful outcome in either PSM or IPTW analysis. For critical COVID-19 patients at admission, results were consistent with multivariable Cox model analysis. CONCLUSION: Corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality for severe or critical cases in Wuhan. Absence of the beneficial effect in our study in contrast to that observed in the RECOVERY clinical trial may be due to biases in observational data, in particular prescription by indication bias, differences in clinical characteristics of patients, choice of corticosteroid used, timing of initiation of treatment, and duration of treatment.
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Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/mortalidade , Mortalidade Hospitalar/tendências , Hospitalização/estatística & dados numéricos , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/mortalidade , Corticosteroides/uso terapêutico , Idoso , COVID-19 , Infecções por Coronavirus/virologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/virologia , Prognóstico , Estudos Retrospectivos , SARS-CoV-2 , Taxa de SobrevidaRESUMO
Photonic jets (PJs) formed on the shadow side of micro-sized dielectric spheres excited by focused Gaussian beams are investigated within the framework of the generalized Lorenz-Mie theory (GLMT). The intrinsic advantages of rapidity and high accuracy of the GLMT in calculations enable us to conduct a systematic study of PJs at a low cost and a high reliability. To reveal the influence of beam parameters on the properties of PJs, numerical results concerning variations of key parameters of PJs, including the maximal intensity, the focal distance, which is linked to the position of maximal intensity, and longitudinal and transversal dimensions are presented with the change of the beam waist radius and the focal center location of the Gaussian beam. The results show that as the beam waist radius approaches the radius of the particle, the energy stream of the Gaussian beam contributes more efficiently to the formation of PJs. By properly tuning the location of the beam focal center, the PJ pattern can be efficiently engineered to a large extent.
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INTRODUCTION: With intense deficiency of medical resources during COVID-19 pandemic, risk stratification is of strategic importance. Blood glucose level is an important risk factor for the prognosis of infection and critically ill patients. We aimed to investigate the prognostic value of blood glucose level in patients with COVID-19. RESEARCH DESIGN AND METHODS: We collected clinical and survival information of 2041 consecutive hospitalized patients with COVID-19 from two medical centers in Wuhan. Patients without available blood glucose level were excluded. We performed multivariable Cox regression to calculate HRs of blood glucose-associated indexes for the risk of progression to critical cases/mortality among non-critical cases, as well as in-hospital mortality in critical cases. Sensitivity analysis were conducted in patient without diabetes. RESULTS: Elevation of admission blood glucose level was an independent risk factor for progression to critical cases/death among non-critical cases (HR=1.30, 95% CI 1.03 to 1.63, p=0.026). Elevation of initial blood glucose level of critical diagnosis was an independent risk factor for in-hospital mortality in critical cases (HR=1.84, 95% CI 1.14 to 2.98, p=0.013). Higher median glucose level during hospital stay or after critical diagnosis (≥6.1 mmol/L) was independently associated with increased risks of progression to critical cases/death among non-critical cases, as well as in-hospital mortality in critical cases. Above results were consistent in the sensitivity analysis in patients without diabetes. CONCLUSIONS: Elevation of blood glucose level predicted worse outcomes in hospitalized patients with COVID-19. Our findings may provide a simple and practical way to risk stratify COVID-19 inpatients for hierarchical management, particularly where medical resources are in severe shortage during the pandemic.
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Betacoronavirus , Glicemia/análise , Infecções por Coronavirus/sangue , Infecções por Coronavirus/mortalidade , Hospitalização , Hiperglicemia/diagnóstico , Pneumonia Viral/sangue , Pneumonia Viral/mortalidade , Idoso , COVID-19 , Infecções por Coronavirus/virologia , Estado Terminal , Progressão da Doença , Feminino , Seguimentos , Mortalidade Hospitalar , Humanos , Pacientes Internados , Tempo de Internação , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/virologia , Prognóstico , Estudos Retrospectivos , Fatores de Risco , SARS-CoV-2 , Resultado do TratamentoRESUMO
The re-identification (ReID) task has received increasing studies in recent years and its performance has gained significant improvement. The progress mainly comes from searching for new network structures to learn person representations. Most of these networks are trained using the classic stochastic gradient descent optimizer. However, limited efforts have been made to explore potential performance of existing ReID networks directly by better training scheme, which leaves a large space for ReID research. In this paper, we propose a Self-Inspirited Feature Learning (SIF) method to enhance performance of given ReID networks from the viewpoint of optimization. We design a simple adversarial learning scheme to encourage a network to learn more discriminative person representation. In our method, an auxiliary branch is added into the network only in the training stage, while the structure of the original network stays unchanged during the testing stage. In summary, SIF has three aspects of advantages: (1) it is designed under general setting; (2) it is compatible with many existing feature learning networks on the ReID task; (3) it is easy to implement and has steady performance. We evaluate the performance of SIF on three public ReID datasets: Market1501, DuckMTMC-reID, and CUHK03(both labeled and detected). The results demonstrate significant improvement in performance brought by SIF. We also apply SIF to obtain state-of-the-art results on all the three datasets. Specifically, mAP / Rank-1 accuracy are: 87.6% / 95.2% (without re-rank) on Market1501, 79.4% / 89.8% on DuckMTMC-reID, 77.0% / 79.5% on CUHK03 (labeled) and 73.9% / 76.6% on CUHK03 (detected), respectively. The code of SIF will be available soon.