A whole-slide foundation model for digital pathology from real-world data.

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

Association between urinary flora and urinary stones.

Urinary system stones are a common clinical disease, with significant differences in incidence and recurrence rates between different countries and regions. The etiology and pathogenesis of urinary system stones have not been fully elucidated, but many studies have found that some bacteria and fungi that are difficult to detect in urine constitute a unique urinary microbiome. This special urinary microbiome is closely related to the occurrence and development of urinary system stones. By analyzing the urinary microbiome and its metabolic products, early diagnosis and treatment of urinary system stones can be carried out. This article reviews the relationship between the urinary microbiome and urinary system stones, discusses the impact of the microbiome on the formation of urinary system stones and its potential therapeutic value, with the aim of providing a reference for the early diagnosis, prevention, and treatment of urinary system stones.

Orbital septum attachment site on the levator aponeurosis sling for mild congenital blepharoptosis.

PURPOSE: This study aimed to investigate the value of the orbital septum attachment site on the levator aponeurosis (OSASLA) sling in correcting mild congenital blepharoptosis. METHODS: A total of 60 patients (92 eyes) with mild congenital blepharoptosis (levator function ≥ 8 mm) were treated in our hospital from January to October 2021, and relevant data of these patients were collected. All patients underwent OSASLA sling for ptosis correction. The distances from the superior tarsal border to the OSASLA were measured. The primary outcome was the number of postoperative changes in the marginal reflex distance 1 (MRD1). Pearson's correlation coefficient between the distance from the superior tarsal border to the OSASLA and the height of the upper eyelid elevated was analyzed. RESULTS: Fifty-eight patients (89 eyes) successfully underwent OSASLA sling surgery. The preoperative MRD1 was 1.4-3.6 mm (mean 2.1 ± 0.5 mm), and the postoperative MRD1 was 3.4-5.0 mm (mean 3.7 ± 0.6 mm). The distance from the superior tarsal border to the OSASLA sling was significantly and positively correlated with the height of the upper eyelid elevation (r = 0.7328, P < 0.0001). The eyelid margin positions of the patients did not regress substantially during 6-18 months of follow-up. CONCLUSIONS: Compared with the shortening of levator palpebrae superioris (LPS) and pleating of LPS, the OSASLA sling is a less invasive, more effective, and easy-operating surgery for mild congenital blepharoptosis.

[Clinical and genetic features of children with 3-methylcrotonyl-coenzyme A carboxylase deficiency: an analysis of six cases]. / 3-ç”²åŸºå·´è±†é °è¾ é ¶Aç¾§åŒ–é ¶ç¼ºä¹ç—‡6ä¾‹æ‚£å„¿çš„ä¸´åºŠç‰¹å¾åŠé—ä¼ å­¦åˆ†æž.

OBJECTIVES: To investigate the clinical and genetic features of children with 3-methylcrotonyl-coenzyme A carboxylase deficiency (MCCD). METHODS: A retrospective analysis was conducted on the clinical manifestations and genetic testing results of six children with MCCD who attended Children's Hospital Affiliated to Zhengzhou University from January 2018 to October 2023. RESULTS: Among the six children with MCCD, there were 4 boys and 2 girls, with a mean age of 7 days at the time of attending the hospital and 45 days at the time of confirmed diagnosis. Of all children, one had abnormal urine odor and five had no clinical symptoms. All six children had increases in blood 3-hydroxyisovaleryl carnitine and urinary 3-hydroxyisovaleric acid and 3-methylcrotonoylglycine, and five of them had a reduction in free carnitine. A total of six mutations were identified in the MCCC1 gene, i.e., c.1630del(p.R544Dfs*2), c.269A>G(p.D90G), c.1609T>A(p.F537I), c.639+2T>A, c.761+1G>T, and c.1331G>A(p.R444H), and three mutations were identified in the MCCC2 gene, i.e., c.838G>T(p.D280Y), c.592C>T(p.Q198*,366), and c.1342G>A(p.G448A). Among these mutations, c.269A>G(p.D90G) and c.1609T>A(p.F537I) had not been previously reported in the literature. There was one case of maternal MCCD, and the child carried a heterozygous mutation from her mother. Five children with a reduction in free carnitine were given supplementation of L-carnitine, and free carnitine was restored to the normal level at the last follow-up visit. CONCLUSIONS: This study identifies two new mutations, c.269A>G(p.D90G) and c.1609T>A(p.F537I), thereby expanding the mutation spectrum of the MCCC1 gene. A combination of blood amino acid and acylcarnitine profiles, urine organic acid analysis, and genetic testing can facilitate early diagnosis and treatment of MCCD, and provide essential data for genetic counseling.

Safety and efficacy of apatinib in patients with advanced gastric or gastroesophageal junction adenocarcinoma after the failure of two or more lines of chemotherapy (AHEAD): a prospective, single-arm, multicenter, phase IV study.

BACKGROUND: Apatinib, a highly selective VEGFR2 inhibitor, significantly improved efficacy versus placebo as a third- and later-line treatment for advanced gastric cancer in phase 2 and 3 trials. This prospective, single-arm, multicenter phase IV AHEAD study was conducted to verify the safety and efficacy of apatinib in patients with advanced or metastatic gastric or gastroesophageal adenocarcinoma after at least two lines of systematic therapy in clinical practice settings. METHODS: Patients with advanced gastric cancer who had previously failed at least two lines of chemotherapy received oral apatinib until disease progression, death or unacceptable toxicity. The primary endpoint was safety. The secondary endpoints included objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS) and overall survival (OS). Adverse events were summarized by the incidence rate. Median OS and PFS were estimated using the Kaplan-Meier method. ORR, DCR, OS at 3 and 6 months, and PFS at 3 and 6 months were calculated, and their 95% CIs were estimated according to the Clopper-Pearson method. RESULTS: Between May 2015 and November 2019, a total of 2004 patients were enrolled, and 1999 patients who received at least one dose of apatinib were assessed for safety. In the safety population, 87.9% of patients experienced treatment-related adverse events (TRAEs), with the most common hypertension (45.2%), proteinuria (26.5%), and white blood cell count decreased (25.3%). Additionally, 51% of patients experienced grade ≥ 3 TRAEs. Fatal TRAEs occurred in 57 (2.9%) patients. No new safety concerns were reported. Among the 2004 patients included in the intention-to-treat population, the ORR was 4.4% (95% CI, 3.6-5.4%), and DCR was 35.8% (95% CI, 33.7-38.0%). The median PFS was 2.7 months (95% CI 2.2-2.8), and the median OS was 5.8 months (95% CI 5.4-6.1). CONCLUSIONS: The findings in the AHEAD study confirmed the acceptable and manageable safety profile and clinical benefit of apatinib in patients with advanced gastric cancer as a third- or later-line of treatment. TRIAL REGISTRATION: This study was registered with ClinicalTrials.gov NCT02426034. Registration date was April 24, 2015.

Effect of volatile compounds produced by the cotton endophytic bacterial strain Bacillus sp. T6 against Verticillium wilt.

BACKGROUND: Verticillium wilt, caused by the fungus Verticillium dahliae, leads to significant losses in cotton yield worldwide. Biocontrol management is a promising means of suppressing verticillium wilt. The purpose of the study was to obtain and analyze endophytic bacteria with Verticillium wilt-resistant activities from the roots of Gossypium barbadense 'Xinhai15' and to explore the interactions between the soil and plants. RESULTS: An endophytic bacterium Bacillus sp. T6 was obtained from the Verticillium wilt-resistant cotton G. barbadense 'Xinhai15', which showed significant antagonistic abilities against cotton Verticillium wilt. The bioassay results indicated that the strain possessed strong antagonistic abilities that inhibited V. dahliae spore germination and mycelial growth without contact, and thus it was speculated that the active factor of the bacteria might be volatile compounds. A total of 46 volatile substances were detected via headspace solid-phase microextraction and gas chromatography-mass spectrometry analysis. The pure product verification experiment confirmed that the styrene produced by the T6 strain was the main virulence factor. Transcriptome analysis showed that following styrene induction, 247 genes in V. dahliae, including four hydrolase genes, eight dehydrogenase genes, 11 reductase genes, 17 genes related to transport and transfer were upregulated. Additionally, 72 genes, including two chitinase genes, two protease genes, five transport-related genes, and 33 hypothetical protein genes, were downregulated. The quantitative real-time PCR results confirmed that the expression of the four genes VDAG_02838, VDAG_09554, VDAG_045572, and VDAG_08251 was increased by 3.18, 78.83, 2.71, and 2.92 times, respectively, compared with the uninduced control group. CONCLUSIONS: The research provides a new reference for the development and application of the volatile compounds of endophytic bacteria as new biocontrol agents for the control of Verticillium wilt and as biological preservatives for agricultural products.

Lymphocyte-to-C-Reactive Protein Ratio as an Early Sepsis Biomarker for Neonates with Suspected Sepsis.

Background: Neonatal sepsis is an extremely dangerous and fatal disease among neonates, and its timely diagnosis is critical to treatment. This research is aimed at evaluating the clinical significance of the lymphocyte-to-C-reactive protein ratio (LCR) as an early sepsis indicator in neonates with suspected sepsis. Methods: Between January 2016 and December 2021, 1269 neonates suspected of developing sepsis were included in this research. Among them, sepsis was diagnosed in 819 neonates, with 448 severe cases, as per the International Pediatric Sepsis Consensus. Data related to clinical and laboratory tests were obtained via electronic medical records. LCR was calculated as total lymphocyte (109 cells/L)/C-reactive protein (mg/L). Multivariate logistic regression analysis was employed to evaluate the effectiveness of LCR as an independent indicator for determining sepsis in susceptible sepsis neonates. Receiver operating characteristic (ROC) curve analysis was conducted for investigating the diagnostic significance of LCR in sepsis. When suitable, the statistical tool SPSS 24.0 was used for statistical analyses. Results: LCR decreased significantly in the control, mild, and severe sepsis groups. Further analyses exhibited that there was a substantially greater incidence of sepsis in neonates in the low-LCR group (LCR ≤ 3.94) as opposed to the higher LCR group (LCR > 3.94) (77.6% vs. 51.4%, p < 0.001). Correlation analysis indicated a substantial negative association of LCR with procalcitonin (r = -0.519, p < 0.001) and hospital stay duration (r = -0.258, p < 0.001). Multiple logistic regression analysis depicted LCR as an independent indicator for identifying sepsis and severe cases of this disease. ROC curve analysis indicated the optimal cutoff value of LCR in identifying sepsis to be 2.10, with 88% sensitivity and 55% specificity. Conclusions: LCR has proven to be a potentially strong biomarker capable of identifying sepsis in a timely manner in neonates suspected to have the disease.

An Adaptive Parameterized Domain Mapping Method and Its Application in Wheel-Rail Coupled Fault Diagnosis for Rail Vehicles.

The rapid development of cities in recent years has increased the operational pressure of rail vehicles, and due to the characteristics of rail vehicles, including harsh operating environment, frequent starting and braking, resulting in rails and wheels being prone to rail corrugation, polygons, flat scars and other faults. These faults are coupled in actual operation, leading to the deterioration of the wheel-rail contact relationship and causing harm to driving safety. Hence, the accurate detection of wheel-rail coupled faults will improve the safety of rail vehicles' operation. The dynamic modeling of rail vehicles is carried out to establish the character models of wheel-rail faults including rail corrugation, polygonization and flat scars to explore the coupling relationship and characteristics under variable speed conditions and to obtain the vertical acceleration of the axle box. An APDM time-frequency analysis method is proposed in this paper based on the PDMF adopting Rényi entropy as the evaluation index and employing a WOA to optimize the parameter set. The number of iterations of the WOA adopted in this paper is decreased by 26% and 23%, respectively, compared with PSO and SSA, which means that the WOA performs at faster convergence speed and with a more accurate Rényi entropy value. Additionally, TFR obtained using APDM realizes the localization and extraction of the coupled fault characteristics under rail vehicles' variable speed working conditions with higher energy concentration and stronger noise resistance corresponding to prominent ability of fault diagnosis. Finally, the effectiveness of the proposed method is verified using simulation and experimental results that prove the engineering application value of the proposed method.

Sintilimab Plus Chemotherapy for Unresectable Gastric or Gastroesophageal Junction Cancer: The ORIENT-16 Randomized Clinical Trial.

Importance: Gastric and gastroesophageal junction cancers are diagnosed in more than 1 million people worldwide annually, and few effective treatments are available. Sintilimab, a recombinant human IgG4 monoclonal antibody that binds to programmed cell death 1 (PD-1), in combination with chemotherapy, has demonstrated promising efficacy. Objective: To compare overall survival of patients with unresectable locally advanced or metastatic gastric or gastroesophageal junction cancers who were treated with sintilimab with chemotherapy vs placebo with chemotherapy. Also compared were a subset of patients with a PD ligand 1 (PD-L1) combined positive score (CPS) of 5 or more (range, 1-100). Design, Setting, and Participants: Randomized, double-blind, placebo-controlled, phase 3 clinical trial conducted at 62 hospitals in China that enrolled 650 patients with unresectable locally advanced or metastatic gastric or gastroesophageal junction adenocarcinoma between January 3, 2019, and August 5, 2020. Final follow-up occurred on June 20, 2021. Interventions: Patients were randomized 1:1 to either sintilimab (n = 327) or placebo (n = 323) combined with capecitabine and oxaliplatin (the XELOX regimen) every 3 weeks for a maximum of 6 cycles. Maintenance therapy with sintilimab or placebo plus capecitabine continued for up to 2 years. Main Outcomes and Measures: The primary end point was overall survival time from randomization. Results: Of the 650 patients (mean age, 59 years; 483 [74.3%] men), 327 were randomized to sintilimab plus chemotherapy and 323 to placebo plus chemotherapy. Among the randomized patients, 397 (61.1%) had tumors with a PD-L1 CPS of 5 or more; 563 (86.6%) discontinued study treatment and 388 (59.7%) died; 1 patient (<0.1%) was lost to follow-up. Among all randomized patients, sintilimab improved overall survival compared with placebo (median, 15.2 vs 12.3 months; stratified hazard ratio [HR], 0.77 [95% CI, 0.63-0.94]; P = .009). Among patients with a CPS of 5 or more, sintilimab improved overall survival compared with placebo (median, 18.4 vs 12.9 months; HR, 0.66 [95% CI, 0.50-0.86]; P = .002). The most common grade 3 or higher treatment-related adverse events were decreased platelet count (sintilimab, 24.7% vs placebo, 21.3%), decreased neutrophil count (sintilimab, 20.1% vs placebo, 18.8%), and anemia (sintilimab, 12.5% vs placebo, 8.8%). Conclusions and Relevance: Among patients with unresectable locally advanced or metastatic gastric and gastroesophageal junction adenocarcinoma treated with first-line chemotherapy, sintilimab significantly improved overall survival for all patients and for patients with a CPS of 5 or more compared with placebo. Trial Registration: ClinicalTrials.gov Identifier: NCT03745170.

α-Cyperone Improves Rat Spinal Cord Tissue Damage via Akt/Nrf2 and NF-κB Pathways.

INTRODUCTION: α-Cyperone has anti-inflammatory activities, but its effects on spinal cord injury (SCI) remain obscure. Thus, this study attempts to investigate the effects and modulatory mechanisms of α-Cyperone on SCI. MATERIALS AND METHODS: An SCI model was established in rats which were further treated with α-Cyperone. Basso-Beattie-Bresnahan (BBB) scoring was used to assess motor rehabilitation of rats modeled with SCI. The spinal cord tissues were collected, and the effect of α-Cyperone on the histopathology of rats modeled with SCI was detected by hematoxylin-eosin staining. Rat primary cortical neuron was stimulated with H2O2 and further treated with α-Cyperone and nuclear factor erythroid 2-related factor 2 (Nrf2) inhibitor ML385. The levels of Nrf2, interleukin-6 (IL-6), nuclear factor kappa B (NF-κB), Akt, toll-like receptor 4 (TLR4), and tumor necrosis factor-alpha (TNF-α) were detected by immunofluorescence staining and western blotting. RESULTS: α-Cyperone elevated the BBB score and ameliorated the damage of spinal cord tissue in rats modeled with SCI. The levels of IL-6, Nrf2, NF-κB, TLR4, and TNF-α were upregulated, whereas that of Akt was downregulated in rats and cells modeled with SCI. Furthermore, α-Cyperone diminished the levels of IL-6, NF-κB, TLR4, and TNF-α, while augmenting those of Nrf2 and Akt in rats and cells modeled with SCI. ML385 inhibited the Nrf2 level that had been promoted by α-Cyperone in the nucleus and elevated the Nrf2 level that had been suppressed by α-Cyperone in the cytosol of cells modeled with SCI. ML385 increased the levels of IL-6, NF-κB, TLR4, and TNF-α that had been inhibited by α-Cyperone and decreased the Akt level that had been enhanced by α-Cyperone in cells modeled with SCI. CONCLUSIONS: α-Cyperone suppressed SCI-induced inflammation and spinal cord tissue damage via activating Akt/Nrf2 and suppressing NF-κB pathways.

The synaptic marker neurogranin as a disease state biomarker in Alzheimer's disease: a systematic review and meta-analysis.

Objective: Synaptic degeneration is the pathologic foundation of cognitive decline in the Alzheimer's disease (AD) continuum. We aimed to determine whether cerebrospinal fluid (CSF) synaptic marker neurogranin (Ng) is a disease state or a disease stage biomarker in the AD continuum.Methods: Studies comparing CSF Ng levels among AD, mild cognitive impairment (MCI) and healthy participants were included. Studies were eligible if the correlation between CSF Ng levels and Mini-Mental Status Examination (MMSE) scores was investigated.Results: Twenty-one studies met our inclusion criteria (n = 4515). The magnitude of effect sizes was more apparent in AD (standardized mean difference [SMD] = 1.72; 95% confidence interval [CI] = 1.23-2.22), than in MCI (SMD = 0.82; 95% CI = 0.29-1.34) compared to control populations. These results suggest that CSF Ng can discriminate AD and MCI from control populations, implying that synaptic degeneration worsens as patients progress from MCI to AD. However, there was a very weak correlation between CSF Ng levels and MMSE scores (r = -0.15; 95% CI = -0.21--0.08) among the whole populations, suggesting that an increment of CSF Ng is best considered a biological evidence of disease state in the AD continuum.Conclusion: Our study provides evidence that the synaptic marker CSF Ng can be used as a disease state biomarker for the AD continuum. Because synaptic degeneration is a distinct pathologic event from amyloid deposition and neurofibrillary tangle formation, CSF Ng may provide an important supplementation to the AT(N) biomarker system to reveal the sequence of neuropathology.

Acoustic Emission Signal Fault Diagnosis Based on Compressed Sensing for RV Reducer.

The rotate vector (RV) reducer has a complex structure and highly coupled internal components. Acoustic emission (AE) signal, which is more sensitive to a weak fault, is selected for fault diagnosis of the RV reducer. The high sampling frequency and big data are the challenges for AE signal store and analysis. This study combines compressed sensing (CS) and convolutional neural networks. As a result, data redundancy is significantly reduced while retaining most of the information, and the analysis efficiency is improved. Firstly, the time-domain AE signal was projected into the compression domain to obtain the compression signal; then, the wavelet packet decomposition in the compressed domain was performed to obtain the information of each frequency band. Next, the frequency band information was sent into the input layer of the multi-channel convolutional layer, and the energy pooling layer mines the energy characteristics of each frequency band. Finally, the softmax classifier was used to classify and predict different fault types of RV reducers. The self-fabricated RV reducer experimental platform was used to verify the proposed method. The experimental results show that the proposed method can effectively extract the fault features in the AE signal of the RV reducer, improve the efficiency of signal processing and analysis, and achieve the accurate classification of RV reducer faults.

An Improved MobileNet Network with Wavelet Energy and Global Average Pooling for Rotating Machinery Fault Diagnosis.

In recent years, neural networks have shown good performance in terms of accuracy and efficiency. However, along with the continuous improvement in diagnostic accuracy, the number of parameters in the network is increasing and the models can often only be run in servers with high computing power. Embedded devices are widely used in on-site monitoring and fault diagnosis. However, due to the limitation of hardware resources, it is difficult to effectively deploy complex models trained by deep learning, which limits the application of deep learning methods in engineering practice. To address this problem, this article carries out research on network lightweight and performance optimization based on the MobileNet network. The network structure is modified to make it directly suitable for one-dimensional signal processing. The wavelet convolution is introduced into the convolution structure to enhance the feature extraction ability and robustness of the model. The excessive number of network parameters is a challenge for the deployment of networks and also for the running performance problems. This article analyzes the influence of the full connection layer size on the total network. A network parameter reduction method is proposed based on GAP to reduce the network parameters. Experiments on gears and bearings show that the proposed method can achieve more than 97% classification accuracy under the strong noise interference of -6 dB, showing good anti-noise performance. In terms of performance, the network proposed in this article has only one-tenth of the number of parameters and one-third of the running time of standard networks. The method proposed in this article provides a good reference for the deployment of deep learning intelligent diagnosis methods in embedded node systems.

A metabolite panel that differentiates Alzheimer's disease from other dementia types.

INTRODUCTION: Alzheimer's disease (AD) is associated with altered metabolites. This study aimed to determine the validity of using circulating metabolites to differentiate AD from other dementias. METHODS: Blood metabolites were measured in three data sets. Data set 1 (controls, 27; AD, 28) was used for analyzing differential metabolites. Data set 2 (controls, 93; AD, 92) was used to establish a diagnostic AD model with use of a metabolite panel. The model was applied to Data set 3 (controls, 76; AD, 76; other dementias, 205) to verify its capacity for differentiating AD from other dementias. RESULTS: Data set 1 revealed 7 upregulated and 77 downregulated metabolites. In Data set 2, a panel of 11 metabolites was included in a model that could distinguish AD from controls. In Data set 3, this panel was used to successfully differentiate AD from other dementias. DISCUSSION: This study revealed an AD-specific panel of 11 metabolites that may be used for AD diagnosis.

A New Method of Wheelset Bearing Fault Diagnosis.

During the movement of rail trains, trains are often subjected to harsh operating conditions such as variable speed and heavy loads. It is therefore vital to find a solution for the issue of rolling bearing malfunction diagnostics in such circumstances. This study proposes an adaptive technique for defect identification based on multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) and Ramanujan subspace decomposition. MOMEDA optimally filters the signal and enhances the shock component corresponding to the defect, after which the signal is automatically decomposed into a sequence of signal components using Ramanujan subspace decomposition. The method's benefit stems from the flawless integration of the two methods and the addition of the adaptable module. It addresses the issues that the conventional signal decomposition and subspace decomposition methods have with redundant parts and significant inaccuracies in fault feature extraction for the vibration signals under loud noise. Finally, it is evaluated through simulation and experimentation in comparison to the current widely used signal decomposition techniques. According to the findings of the envelope spectrum analysis, the novel technique can precisely extract the composite flaws that are present in the bearing, even when there is significant noise interference. Additionally, the signal-to-noise ratio (SNR) and fault defect index were introduced to quantitatively demonstrate the novel method's denoising and potent fault extraction capabilities, respectively. The approach works well for identifying bearing faults in train wheelsets.

Syntheses of Covalent Organic Frameworks via a One-Pot Suzuki Coupling and Schiff's Base Reaction for C2 H4 /C3 H6 Separation.

Covalent organic frameworks (COFs) featuring permanent porosity, designable topologies, and tailorable functionalities have attracted great interest in the past two decades. Developing efficient modular approaches to rationally constructing COFs from a set of molecules via covalent linking has been long pursued. Herein, we report a facile one-pot strategy to prepare COFs via an irreversible Suzuki coupling reaction followed by a reversible Schiff's base reaction without the need for intermediate isolation. Gram-scale ordered frameworks with kgm topology and rich porosities can be obtained by using diamino-aryl halide and dialdehyde aryl-borate compounds as monomers. The resultant microporous CR-COFs were used for efficient C2 H4 /C3 H6 separation. This strategy reduces the waste generated and efforts consumed by stepwise reactions and relative purification processes, making the large-scale syntheses of stable COFs feasible. Moreover, it offers a novel modular approach to designing COF materials.

Prediction of P-tau/Aß42 in the cerebrospinal fluid with blood microRNAs in Alzheimer's disease.

BACKGROUND: The most common biomarkers of Alzheimer's disease (AD) are amyloid ß (Aß) and tau, detected in cerebrospinal fluid (CSF) or with positron emission tomography imaging. However, these procedures are invasive and expensive, which hamper their availability to the general population. Here, we report a panel of microRNAs (miRNAs) in serum that can predict P-tau/Aß42 in CSF and readily differentiate AD from other dementias, including vascular dementia (VaD), Parkinson disease dementia (PDD), behavioral variant frontotemporal dementia (bvFTD), and dementia with Lewy body (DLB). METHODS: RNA samples were extracted from the participant's blood. P-tau/Aß42 of CSF was examined for diagnostic purposes. A pilot study (controls, 21; AD, 23), followed by second (controls, 216; AD, 190) and third groups (controls, 153; AD, 151), is used to establish and verify a predictive model of P-tau/Aß42 in CSF. The test is then applied to a fourth group of patients with different dementias (controls, 139; AD,155; amnestic mild cognitive impairment [aMCI], 55; VaD, 51; PDD, 53; bvFTD, 53; DLB, 52) to assess its diagnostic capacity. RESULTS: In the pilot study, 29 upregulated and 31 downregulated miRNAs in the AD group were found. In Dataset 2, these miRNAs were then included as independent variables in the linear regression model. A seven-microRNA panel (miR-139-3p, miR-143-3p, miR-146a-5p, miR-485-5p, miR-10a-5P, miR-26b-5p, and miR-451a-5p) accurately predicted values of P-tau/Aß42 of CSF. In Datasets 3 and 4, by applying the predicted P-tau/Aß42, the predictive model successfully differentiates AD from controls and VaD, PDD, bvFTD, and DLB. CONCLUSIONS: This study suggests that the panel of microRNAs is a promising substitute for traditional measurement of P-tau/Aß42 in CSF as an effective biomarker of AD.

Nucleophosmin 1 overexpression correlates with 18F-FDG PET/CT metabolic parameters and improves diagnostic accuracy in patients with lung adenocarcinoma.

PURPOSE: This study investigated the correlation of nucleophosmin 1 (NPM1) expression with 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computerised tomography scan (PET/CT)-related parameters and compared the diagnostic value of NPM1 with that of the positive biomarker TTF1 in lung adenocarcinoma patients. METHODS: Forty-six lung adenocarcinoma patients who underwent 18F-FDG PET/CT before pulmonary surgery were retrospectively analysed. Metabolic parameters including SUVmax, SUVmean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were calculated from 18F-FDG PET imaging data. The expression levels of NPM1 and TTF1 were assessed using The Cancer Genome Atlas (TCGA) database and immunohistochemistry of tumour tissues and adjacent normal lung tissues. We examined the association between the frequency of NPM1 and TTF1 expression and the metabolic parameters. RESULTS: Lung adenocarcinoma samples expressed higher levels of NPM1 than adjacent normal lung epithelial tissues. NPM1 showed higher specificity and sensitivity for lung adenocarcinoma compared with TTF1 (p < 0.001). SUVmax, SUVmean and TLG correlated with NPM1 expression (p < 0.001). MTV was inversely correlated with TTF1 (p < 0.01). SUVmax was the primary predictor of NPM1 expression by lung adenocarcinoma (p < 0.01). A cutoff value for the SUVmax of 3.93 allowed 90.9% sensitivity and 84.6% specificity for predicting NPM1 overexpression in lung adenocarcinoma. CONCLUSION: NPM1 overexpression correlated with 18F-FDG PET/CT metabolic parameters and improved diagnostic accuracy in lung adenocarcinoma. SUVmax on 18F-FDG PET/CT may estimate NPM1 expression for targeted therapy of lung adenocarcinoma.

Larotinib in patients with advanced and previously treated esophageal squamous cell carcinoma with epidermal growth factor receptor overexpression or amplification: an open-label, multicenter phase 1b study.

BACKGROUND: Larotinib is a new first-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor. This open-label, phase 1b study is aimed to evaluate the efficacy, safety of larotinib in patients with advanced esophageal squamous cell carcinoma (ESCC) with EGFR overexpression or amplification pretreated with one or more system regimens, and to recommend an appropriate dose for its further study. METHODS: Patients received larotinib orally at 3 doses (250, 300, 350 mg), once daily. Clinical response was evaluated every 8 weeks according to RECIST v1.1 criteria by both investigators and independent radiology review (IRC). RESULTS: 81 patients were enrolled. The investigator-assessed overall response rate (ORR) was 13.7% (10/73), all responses were observed in the 350 mg group of which ORR up to 20.0% (10/50), with 10 of them having EGFR overexpression and 4 having EGFR amplification. Per IRC assessment, ORR for all patients and 350 mg group were 13.9% (10/72) and 16.3% (8/50). In the 350 mg group, median overall survival (OS) and progression-free survival (PFS) were 8.0 (95% CI 4.9-10.2) months and 3.4 (95% CI 2.4-3.7) months, respectively. The most common treatment-related adverse events (TRAEs) were diarrhea, rash, and palmar-plantar erythrodysesthesia syndrome, elevated AST/ALT, vomiting, similarly with other EGFR TKIs. CONCLUSIONS: Larotinib demonstrated promising antitumor activity and manageable safety profiles in patients with pre-treated advanced ESCC with EGFR overexpression or amplification, especially at the dose of 350 mg, which showed better efficacy and acceptable safety. A phase 3 study is underway on 350 mg larotinib in ESCC patients with EGFR overexpression. TRIAL REGISTRATION: This trial was retrospectively registered on 25/03/2019, NCT03888092. https://clinicaltrials.gov/ct2/show/NCT03888092 .

A Study on Railway Surface Defects Detection Based on Machine Vision.

The detection of rail surface defects is an important tool to ensure the safe operation of rail transit. Due to the complex diversity of track surface defect features and the small size of the defect area, it is difficult to obtain satisfying detection results by traditional machine vision methods. The existing deep learning-based methods have the problems of large model sizes, excessive parameters, low accuracy and slow speed. Therefore, this paper proposes a new method based on an improved YOLOv4 (You Only Look Once, YOLO) for railway surface defect detection. In this method, MobileNetv3 is used as the backbone network of YOLOv4 to extract image features, and at the same time, deep separable convolution is applied on the PANet layer in YOLOv4, which realizes the lightweight network and real-time detection of the railway surface. The test results show that, compared with YOLOv4, the study can reduce the amount of the parameters by 78.04%, speed up the detection by 10.36 frames per second and decrease the model volume by 78%. Compared with other methods, the proposed method can achieve a higher detection accuracy, making it suitable for the fast and accurate detection of railway surface defects.