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Abstract The prognosis of septic patients with cirrhosis is worse compared to septic patients without cirrhosis. Early and accurate prognosis determination in patients with cirrhosis and sepsis is pivotal for guiding treatment decisions. The aim of this study was to investigate the association between albumin-corrected anion gap (ACAG) and clinical prognosis of patients with sepsis and cirrhosis. This study extracted data of patients with sepsis and cirrhosis from the Medical Information Mart for Intensive Care (MIMIC-IV) database. A total of 1340 patients (64.6% male) were enrolled. After confounders adjusting, elevated ACAG had a significant association with 28-day mortality (HR1.604; 95% CI 1.258–2.048; P

Abstract Background Chronic kidney disease (CKD) is highly prevalent worldwide, and its global burden is substantial and growing. CKD displays a number of features of accelerated senescence. Tubular cell senescence is a common biological process that contributes to CKD progression. Tubulointerstitial inflammation is a driver of tubular cell senescence and a common characteristic of CKD. However, the mechanism by which the interstitial inflammation drives tubular cell senescence remains unclear. This paper aims to explore the role of exosomal miRNAs derived from macrophages in the development of tubular cell senescence. Methods Among the identified inflammation-related miRNAs, miR-155 is considered to be one of the most important miRNAs involved in the inflammatory response. Macrophages, the primary immune cells that mediate inflammatory processes, contain a high abundance of miR-155 in their released exosomes. We assessed the potential role of miR-155 in tubular cell senescence and renal fibrosis. We subjected miR-155−/− mice and wild-type controls, as well as tubular epithelial cells (TECs), to angiotensin II (AngII)-induced kidney injury. We assessed kidney function and injury using standard techniques. TECs were evaluated for cell senescence and telomere dysfunction in vivo and in vitro. Telomeres were measured by the fluorescence in situ hybridization. Results Compared with normal controls, miR-155 was up-regulated in proximal renal tubule cells in CKD patients and mouse models of CKD. Moreover, the expression of miR-155 was positively correlated with the extent of renal fibrosis, eGFR decline and p16INK4A expression. The overexpression of miR-155 exacerbated tubular senescence, evidenced by increased detection of p16INK4A/p21expression and senescence-associated β-galactosidase activity. Notably, miR-155 knockout attenuates renal fibrosis and tubule cell senescence in vivo. Interestingly, once released, macrophages-derived exosomal miR-155 was internalized by TECs, leading to telomere shortening and dysfunction through targeting TRF1. A dual-luciferase reporter assay confirmed that TRF1 was the direct target of miR-155. Thus, our study clearly demonstrates that exosomal miR-155 may mediate communication between macrophages and TECs, subsequently inducing telomere dysfunction and senescence in TECs. Conclusions Our work suggests a new mechanism by which macrophage exosomes are involved in the development of tubule senescence and renal fibrosis, in part by delivering miR-155 to target TRF1 to promote telomere dysfunction. Our study may provide novel strategies for the treatment of AngII-induced kidney injury.

BackgroundThe co-occurrence of pulmonary hypertension (PH) in patients with pulmonary fibrosis (PF) is linked to a more unfavorable prognosis and increased mortality compared to PF cases without PH. Early intervention and comprehensive management are pivotal for improving survival outcomes. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a protein essential in cholesterol metabolism. However, the potential for PCSK9 inhibition to alleviate PF-induced PH has not been previously reported.MethodsA mouse model of PF-induced PH was established using intratracheal injection of bleomycin (BLM), followed by administration of a PCSK9 inhibitor every other day. Data on right ventricle (RV) remodeling and changes in pulmonary arteries were collected and analyzed. Transforming growth factor-beta (TGF-β) was also administered to MLE-12 cells as an experimental lung fibrosis model. The mechanisms of PCSK9’s impact on lung fibrosis were examined both in vivo and in vitro.ResultsInhibition of PCSK9 significantly reduced pulmonary artery thickening and RV remodeling in the BLM-induced mouse model. Moreover, the blockage of PCSK9 effectively attenuated the migration and epithelial-mesenchymal transition (EMT) process of TGF-β-induced MLE-12 cells. We also observed that the PCSK9 inhibitor suppressed the expression of the Wnt/β-catenin pathway in both animal and cell experiments.ConclusionPCSK9 plays a crucial role in the progression of PF-induced PH by regulating cell EMT and Wnt/β-catenin signaling. Targeting PCSK9 expression or activity could effectively control lung fibrosis and its PH complication.

ObjectiveBipolar affective disorder (BAD) is a mood disorder with high morbidity and mortality. Quetiapine can be used in the treatment of patients with BAD; however, the precise administration regimen of quetiapine in these patients is still unknown. In this study, a population pharmacokinetic (PPK) model of quetiapine in patients with BAD was constructed based on model-informed precision dosing (MIPD) and real-world clinical data and an optimal initial dose of quetiapine in these patients was recommended.MethodsA total of 99 patients with BAD treated with quetiapine were included. At the same time, the quetiapine concentrations, the physical and chemical indices of the patients, and the drug combination information were collected. A quetiapine PPK model for patients with BAD was then constructed and an initial dose based on Monte Carlo simulation was recommended.ResultsIn the final model of quetiapine for patients with BAD, the apparent oral clearance (CL/F) and the apparent volume of distribution (V/F) were 76.1 L/h and 530 L, respectively. For patients with BAD weighing 40–66 kg, the initial dose recommendation was 16 mg kg−1 day−1, the probability of reaching the therapeutic window was 78.8%–82.2%, and the probability of exceeding the upper limit of the therapeutic window was 5.2%–10.3%. For patients with BAD weighing 66–120 kg, the initial dose recommendation was 12 mg kg−1 day−1, the probability of reaching the therapeutic window was 81.5%–85.5%, and the probability of exceeding the upper limit of the therapeutic window was 3.6%–8.1%.ConclusionThe present study, for the first time, recommended an initial dose of quetiapine in patients with BAD based on MIPD and real-world data, providing an individualized reference for the administration of quetiapine in these patients.

ObjectiveAlthough quetiapine has been approved for use in schizophrenic patients, its individualized dosage regimen remains unclear, especially with respect to drug–drug interactions (DDIs). Thus, we investigated the potential DDIs and optimal initial dosage of quetiapine in schizophrenic patients based on population pharmacokinetics (PPK).MethodsNinety-six schizophrenic patients treated with quetiapine were included to establish the PPK model, which also includes coadministration of multiple drugs.ResultsIt was found that the patient weights and fluvoxamine or duloxetine coadministration affected quetiapine clearance in schizophrenic patients. Without fluvoxamine or duloxetine coadministration, 16 and 12 mg/kg/day of quetiapine were recommended to schizophrenic patients whose weights were in the ranges of 40–50 and 50–120 kg, respectively. With fluvoxamine coadministration, 8 mg/kg/day of quetiapine was recommended to patients with weights in the range of 40–120 kg. With duloxetine coadministration, 8 mg/kg/day of quetiapine was recommended to patients with weights in the 40–120 kg range. With simultaneous coadministration of fluvoxamine and duloxetine, 4 mg/kg/day of quetiapine was recommended to patients with weights in the 40–120 kg range.ConclusionThe present study was a pilot effort at investigating the potential DDIs and optimal initial dosage of quetiapine in schizophrenic patients based on PPK. The initial dosages of quetiapine administered to the patients were optimized according to the coadministration of fluvoxamine or duloxetine.

Abstract Designing high‐entropy oxyhydroxides (HEOs) electrocatalysts with controlled nanostructures is vital for efficient and stable water‐splitting electrocatalysts. Herein, a novel HEOs material (FeCoNiWCuOOH@Cu) containing five non‐noble metal elements derived by electrodeposition on a 3D double‐continuous porous Cu support is created. This support, prepared via the liquid metal dealloying method, offers a high specific surface area and rapid mass/charge transfer channels. The resulting high‐entropy FeCoNiWCuOOH nanosheets provide a dense distribution of active sites. The heterostructure between Cu skeletons and FeCoNiWCuOOH nanosheets enhances mass transfer, electronic structure coupling, and overall structural stability, leading to excellent activities in the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and water splitting reaction. At 10 mA cm−2, the overpotentials for OER, HER, and water splitting in 1.0 m KOH solution are 200, 18, and 1.40 V, respectively, outperforming most current electrocatalysts. The catalytic performance remains stable even after operating at 300 mA cm−2 for 100, 100, and over 1000 h, correspondingly. This material has potential applications in integrated hydrogen energy systems. More importantly, density functional theory (DFT) calculations demonstrate the synergy of the five elements in enhancing water‐splitting activity. This work offers valuable insights for designing industrial water electrolysis systems.

Current signal processing for synthetic aperture radar (SAR) cannot satisfy the requirements for high resolution, high squint angle, and wide swath due to the limitations of the traditional stop-and-go model. This model does not take into account the continuous motion between the satellite and the ground, leading to incomplete compensation for the corresponding phase. To address this issue, we first introduce an accurate range equation (ARE) based on the continuous satellite and ground motion, which allows for more precise slant range calculations. Second, we derive the point target spectrum according to the ARE, revealing additional phase components not considered in the traditional stop-and-go model. Third, we propose an advanced two-step processing algorithm to compensate for phase errors due to nonstop-and-go continuous motion. In the first-step processing, we eliminate range-independent components in the two-dimensional frequency domain. In the second-step processing, we compensate for residual phase errors related to range and azimuth frequency in the range-Doppler domain. We verified the proposed compensation method through simulation and compared it with the two-step compensation method used in high-resolution SAR data processing. Experimental results show that we provide an effective compensation method for high-resolution, high-squint-angle, wide-swath spaceborne SAR, which can correct azimuth shifts and solve the problem of defocusing at the edges of large scenes.

Abstract High synthesis temperatures and specific growth substrates are typically required to obtain crystalline or oriented inorganic functional thin films, posing a significant challenge for their utilization in large-scale, low-cost (opto-)electronic applications on conventional flexible substrates. Here, we explore a pulse irradiation synthesis (PIS) to prepare thermoelectric metal chalcogenide (e.g., Bi2Se3, SnSe2, and Bi2Te3) films on multiple polymeric substrates. The self-propagating combustion process enables PIS to achieve a synthesis temperature as low as 150 °C, with an ultrafast reaction completed within one second. Beyond the photothermoelectric (PTE) property, the thermal coupling between polymeric substrates and bismuth selenide films is also examined to enhance the PTE performance, resulting in a responsivity of 71.9 V/W and a response time of less than 50 ms at 1550 nm, surpassing most of its counterparts. This PIS platform offers a promising route for realizing flexible PTE or thermoelectric devices in an energy-, time-, and cost-efficient manner.

Synthetic aperture radar (SAR) is often affected by other high-power electromagnetic devices during ground observation, which causes unintentional radio frequency interference (RFI) with the acquired echo, bringing adverse effects into data processing and image interpretation. When faced with the task of screening massive SAR data, there is an urgent need for the global perception and detection of interference. The existing RFI detection method usually only uses a single type of data for detection, ignoring the information association between the data at all levels of the real SAR product, resulting in some computational redundancy. Meanwhile, current deep learning-based algorithms are often unable to locate the range of RFI coverage in the azimuth direction. Therefore, a novel RFI processing framework from quick-looks to single-look complex (SLC) data and then to raw echo is proposed. We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. Then, through the analysis of the TOPSAR imaging principle, the position of the RFI in the SLC image is preliminarily confirmed. The possible distribution of the RFI in the corresponding raw echo is further inferred, which is one of the first attempts to use spaceborne SAR data to elucidate the RFI location mapping relationship between image data and raw echo. Compared with directly detecting all of the SLC data, the time for the proposed framework to determine the RFI distribution in the SLC data can be shortened by 53.526%. All the research in this paper is conducted on Sentinel-1 real data, which verify the feasibility and effectiveness of the proposed framework for radio frequency signals monitoring in advanced spaceborne SAR systems.

Organic-inorganic halide perovskite, as a low-cost, solution-processable material with remarkable optoelectronic properties, is ideal candidate to fabricate high-performance photodetectors and is expected to significantly reduce device costs. Compared to the common Dion-Jacobson and Ruddlesden-Popper two-dimensional (2D) layered hybrid perovskite compounds, the perovskites with alternating cations in the interlayer (ACI) phase show higher crystal symmetry and narrower optical bandgaps, which exhibit great potential for excellent photodetection performance. Herein, we report a high-performance photodetector based on the 2D bilayered hybrid lead halide perovskite single crystal with the ACI phase (GAMA2Pb2I7; GA = C(NH2)3 and MA = CH3NH3). The single-crystal photodetector exhibits high photoresponsivity of 1.56, 2.54, and 2.60 A/W for incident light wavelengths of 405, 532, and 635 nm under 9.82 nW, respectively, together with the correspondingly high detectivity values of 1.86 × 1012, 3.04 × 1012, and 3.11 × 1012 Jones under the same operating conditions. Meanwhile, a high-resolution imaging sensor is built based on the GAMA2Pb2I7 single-crystal photodetector, confirming the high stability and photosensitivity of the imaging system. These results show that the 2D hybrid lead halide perovskites with alternating interlayer cations are promising for high-performance visible light photodetectors and imaging systems.

In recent years, cell migration assays (CMAs) have emerged as a tool to study the migration of cells along with their physiological responses under various stimuli, including both mechanical and bio-chemical properties. CMAs are a generic system in that they support various biological applications, such as wound healing assays. In this paper, we review the development of the CMA in the context of its application to wound healing assays. As such, the wound healing assay will be used to derive the requirements on CMAs. This paper will provide a comprehensive and critical review of the development of CMAs along with their application to wound healing assays. One salient feature of our methodology in this paper is the application of the so-called design thinking; namely we define the requirements of CMAs first and then take them as a benchmark for various developments of CMAs in the literature. The state-of-the-art CMAs are compared with this benchmark to derive the knowledge and technological gap with CMAs in the literature. We will also discuss future research directions for the CMA together with its application to wound healing assays.

Yearly epidemics of seasonal influenza cause an enormous disease burden around the globe. An understanding of the rules behind the immune response with repeated vaccination still presents a significant challenge, which would be helpful for optimizing the vaccination strategy. In this study, 34 healthy volunteers with 16 vaccinated were recruited, and the dynamics of the BCR repertoire for consecutive vaccinations in two seasons were tracked. In terms of diversity, length, network, V and J gene segments usage, somatic hypermutation (SHM) rate and isotype, it was found that the overall changes were stronger in the acute phase of the first vaccination than the second vaccination. However, the V gene segments of IGHV4-39, IGHV3-9, IGHV3-7 and IGHV1-69 were amplified in the acute phase of the first vaccination, with IGHV3-7 dominant. On the other hand, for the second vaccination, the changes were dominated by IGHV1-69, with potential for coding broad neutralizing antibody. Additional analysis indicates that the application of V gene segment for IGHV3-7 in the acute phase of the first vaccination was due to the elevated usage of isotypes IgM and IgG3. While for IGHV1-69 in the second vaccination, it was contributed by isotypes IgG1 and IgG2. Finally, 41 public BCR clusters were identified in the vaccine group, with both IGHV3-7 and IGHV1-69 were involved and representative complementarity determining region 3 (CDR3) motifs were characterized. This study provides insights into the immune response dynamics following repeated influenza vaccination in humans and can inform universal vaccine design and vaccine strategies in the future.

BackgroundPre-existing cross-reactive immunity among different coronaviruses, also termed immune imprinting, may have a comprehensive impact on subsequent SARS-CoV-2 infection and COVID-19 vaccination effectiveness. Here, we aim to explore the interplay between pre-existing seasonal coronaviruses (sCoVs) antibodies and the humoral immunity induced by COVID-19 vaccination.MethodsWe first collected serum samples from healthy donors prior to COVID-19 pandemic and individuals who had received COVID-19 vaccination post-pandemic in China, and the levels of IgG antibodies against sCoVs and SARS-CoV-2 were detected by ELISA. Wilcoxon rank sum test and chi-square test were used to compare the difference in magnitude and seropositivity rate between two groups. Then, we recruited a longitudinal cohort to collect serum samples before and after COVID-19 vaccination. The levels of IgG antibodies against SARS-CoV-2 S, S1, S2 and N antigen were monitored. Association between pre-existing sCoVs antibody and COVID-19 vaccination-induced antibodies were analyzed by Spearman rank correlation.Results96.0% samples (339/353) showed the presence of IgG antibodies against at least one subtype of sCoVs. 229E and OC43 exhibited the highest seroprevalence rates at 78.5% and 72.0%, respectively, followed by NL63 (60.9%) and HKU1 (52.4%). The levels of IgG antibodies against two β coronaviruses (OC43 and HKU1) were significantly higher in these donors who had inoculated with COVID-19 vaccines compared to pre-pandemic healthy donors. However, we found that COVID-19 vaccine-induced antibody levels were not significant different between two groups with high levelor low level of pre-existing sCoVs antibody among the longitudinal cohort.ConclusionWe found a high prevalence of antibodies against sCoVs in Chinese population. The immune imprinting by sCoVs could be reactivated by COVID-19 vaccination, but it did not appear to be a major factor affecting the immunogenicity of COVID-19 vaccine. These findings will provide insights into understanding the impact of immune imprinting on subsequent multiple shots of COVID-19 vaccines.

Astrocyte elevated gene-1 (AEG-1) is an important oncogene that overexpresses in gliomas and plays a vital role in their occurrence and progression. However, few reports have shown which biomarkers could reflect the level of AEG-1 expression in vivo so far. In recent years, intracellular metabolites monitored by proton magnetic resonance spectroscopy (1H MRS) as non-invasive imaging biomarkers have been applied to the precise diagnosis and therapy feedback of gliomas. Therefore, understanding the correlation between 1H MRS metabolites and AEG-1 gene expression in U251 cells may help to identify relevant biomarkers. This study constructed three monoclonal AEG-1-knockout U251 cell lines using the clustered regularly interspaced short palindromic repeat (CRISPR) /Cas9 technique and evaluated the biological behaviors and metabolite ratios of these cell lines. With the decline in AEG-1 expression, the apoptosis rate of the AEG-1-knockout cell lines increased. At the same time, the metastatic capacities decreased, and the relative contents of total choline (tCho) and lactate (Lac) were also reduced. In conclusion, deviations in AEG-1 expression influence the apoptosis rate and metastasis capacity of U251 cells, which the 1H MRS metabolite ratio could monitor. The tCho/creatinine(Cr) and Lac/Cr ratios positively correlated with the AEG-1 expression and malignant cell behavior. This study may provide potential biomarkers for accurate preoperative diagnosis and future AEG-1-targeting treatment evaluation of gliomas in vivo.

Background COVID-19 pandemic continues to pose a huge threat to public health. Mass vaccination is needed to achieve herd immunity against SARS-CoV-2. Currently, several vaccines are being inoculated on a large-scale. The willingness of COVID-19 vaccination had been well investigated in the pre-vaccination era, but no reported data in the post-vaccination era yet. Methods We conducted a large-scale survey among industrial workers during the vaccination campaign in China. Chi-square test and rank sum test were used to identify differences for various intentions regarding COVID-19 vaccination. Univariate analysis and multivariate regression models were utilized to analyze the relationship among demographic factors, related influencing factors and acceptance of COVID-19 vaccination. Results A total of 23,940 industrial workers were included, 66.0% were willing to take COVID-19 vaccine, 16.6% were unwilling, and 17.4% were unsure. Participants were more likely to get vaccinated if they were male, aged 45–65, being good educated, married, or being recommended by doctors or nurses. Participants with strong risk perception of COVID-19 infection, strong confidence in COVID-19 vaccine, high attention to COVID-19 vaccine, good health status, bad health habit, and a history of vaccination within three months were also more likely to be vaccinated. Conclusions This study calls for more attention and health-related education among industrial workers to improve their acceptance of COVID-19 vaccination.

PurposeTo develop and validate a clinical-radiomics nomogram based on radiomics features and clinical risk factors for identification of human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer (BC).MethodsTwo hundred and thirty-five female patients with BC were enrolled from July 2018 to February 2022 and divided into a training group (from center I, 115 patients), internal validation group (from center I, 49 patients), and external validation group (from centers II and III, 71 patients). The preoperative MRI of all patients was obtained, and radiomics features were extracted by a free open-source software called 3D Slicer. The Least Absolute Shrinkage and Selection Operator regression model was used to identify the most useful features. The radiomics score (Rad-score) was calculated by using the radiomics signature-based formula. A clinical-radiomics nomogram combining clinical factors and Rad-score was developed through multivariate logistic regression analysis. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA).ResultsA total of 2,553 radiomics features were extracted, and 21 radiomics features were selected as the most useful radiomics features. Multivariate logistic regression analysis indicated that Rad-score, progesterone receptor (PR), and Ki-67 were independent parameters to distinguish HER2 status. The clinical-radiomics nomogram, which comprised Rad-score, PR, and Ki-67, showed a favorable classification capability, with AUC of 0.87 [95% confidence internal (CI), 0.80 to 0.93] in the training group, 0.81 (95% CI, 0.69 to 0.94) in the internal validation group, and 0.84 (95% CI, 0.75 to 0.93) in the external validation group. DCA illustrated that the nomogram was useful in clinical practice.ConclusionsThe nomogram combined with Rad-score, PR, and Ki-67 can identify the HER2 status of BC.

The highly virulent and antigenic variant of Pseudorabies virus (PRV) that emerged from classical Bartha-K61-vaccinated pig herds has caused substantial economic losses to the swine industry in China since 2011. A safe and more effective vaccine is most desirable. In this study, a gE/TK gene-deficient PRV, namely, HD/c, was constructed based on a PRV type II DX strain isolated from a commercial vaccine-immunized farm and the HD/c-based inactivated vaccine was formulated and evaluated for its safety, immunogenicity, and protective efficacy in mice and piglets. The resulting PRV HD/c strain has a similar growth curve to the parental DX strain. After vaccination, the inactivated HD/c vaccine did not cause any visible gross pathological or histopathological changes in the tissues of mice and piglets and provided rapid and potent protection against the challenge of the classical and variant PRVs at day 21 post-vaccination in mice. A single immunization of 108.5TCID50 inactivated PRV HD/c strain-elicited robust immunity with high titer of neutralizing antibody and provided complete protection from the lethal challenge of PRV DX strain in piglets. These results indicated that the inactivated PRV HD/c vaccine with the deletion of gE/TK genes was a safe and effective PRV vaccine candidate for the control of PRV.

We present a case report of successful treatment with nirmatrelvir/ritonavir (Paxlvoid) for a severe aplastic anemia child with COVID-19, cytopenia, and mixed chimerism of donor hematopoietic cells at 3 months after allogeneic hematopoietic stem cell transplantation. After the 5-day entire course of treatment, the clinical symptoms were relieved, cycle threshold values of ORF1a/b and N genes increased from 22.60 and 22.15 to 34.52 and 33.84, respectively, and the peripheral blood counts gradually recovered without graft failure. Nirmatrelvir/ritonavir can effectively inhibit the replication of SARS-CoV-2 without any significant adverse effects.

PurposeTo build CT perfusion (CTP)-based delta-radiomics models to identify collateral vessel formation after revascularization in patients with moyamoya disease (MMD).MethodsFifty-three MMD patients who underwent CTP and digital subtraction angiography (DSA) examination were retrospectively enrolled. Patients were divided into good and poor groups based on postoperative DSA. CTP parameters, such as mean transit time (MTT), time to drain (TTD), time to maximal plasma concentration (Tmax), and flow extraction product (FE), were obtained. CTP efficacy in evaluating surgical treatment were compared between the good and poor groups. The changes in the relative CTP parameters (ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE) were calculated to evaluate the differences between pre- and postoperative CTP values. CTP parameters were selected to build delta-radiomics models for identifying collateral vessel formation. The identification performance of machine learning classifiers was assessed using area under the receiver operating characteristic curve (AUC).ResultsOf the 53 patients, 36 (67.9%) and 17 (32.1%) were divided into the good and poor groups, respectively. The postoperative changes of ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE in the good group were significantly better than the poor group (p < 0.05). Among all CTP parameters in the perfusion improvement evaluation, the ΔrTTD had the largest AUC (0.873). Eleven features were selected from the TTD parameter to build the delta-radiomics model. The classifiers of the support vector machine and k-nearest neighbors showed good diagnostic performance with AUC values of 0.933 and 0.867, respectively.ConclusionThe TTD-based delta-radiomics model has the potential to identify collateral vessel formation after the operation.

Introduction: Diabetic nephropathy (DN) remains a major cause of end-stage renal disease. The development of novel biomarkers and early diagnosis of DN are of great clinical importance. The goal of this study was to identify hub genes with diagnostic potential for DN by weighted gene co-expression network analysis (WGCNA). Methods: Gene Expression Omnibus database was searched for microarray data including distinct types of CKD. Gene co-expression network was constructed, and modules specific for DN were identified by WGCNA. Gene ontology (GO) analysis was performed, and the hub genes were screened out within the selected gene modules. In addition, cross-validation was performed in an independent dataset and in samples of renal biopsies with DN and other types of glomerular diseases. Results: Dataset GSE99339 was selected, and a total of 179 microdissected glomeruli samples were analyzed, including DN, normal control, and 7 groups of other glomerular diseases. Twenty-three modules of the total 10,947 genes were grouped by WGCNA, and a module was specifically correlated with DN (r = 0.54, p = 9e−15). GO analysis showed that module genes were mainly enriched in the accumulation of extracellular matrix (ECM). LUM, ELN, FBLN1, MMP2, FBLN5, and FMOD were identified as hub genes. Cross verification showed LUM and FMOD were higher in the DN group and were negatively correlated with estimated glomerular filtration rate (eGFR). In renal biopsies, expression levels of LUM and FMOD were higher in DN than IgA nephropathy, membranous nephropathy, and normal controls. Conclusion: By using WGCNA approach, we identified LUM and FMOD related to ECM accumulation and were specific for DN. These 2 genes may represent potential candidate diagnostic biomarkers of DN.

Activated carbon particle electrodes modified by oxygen or nitrogen groups could be promising electrode candidates for capacitive deionization (CDI) processes. In this work, activated carbon particle electrodes were modified by phosphoric acid, nitric acid, urea, melamine, and zinc chloride to enhance desalination of an aqueous electrolytic solution. The modified activated carbon particles were characterized by scanning electron microscopy, energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, Brunauer–Emmett–Teller measurements and electrochemical scanning. The electrodes with oxygen or nitrogen groups on the surface exhibited a much higher desalination capacity and charge efficiency than those without any surface modification. Particularly, the activated carbon particle electrode modified by phosphoric acid exhibited a desalination capacity of 15.52 mg/g at 1.4 V in 500 mg/L NaCl solution, which was approximately eight times that of the unmodified electrode (2.46 mg/g). The enhancement was attributed to a higher specific capacitance, a lower electrochemical impedance and an increase in oxygen or nitrogen-containing groups on the surface.

Ship detection from synthetic aperture radar (SAR) images has become a major research field in recent years. It plays a major role in monitoring the ocean, marine rescue activities, and marine safety warnings. However, there are still some factors that restrict further improvements in detecting performance, e.g., multi-scale ship transformation and unfocused images caused by motion. In order to resolve these issues, in this paper, a doppler feature matrix fused with a multi-layer feature pyramid network (D-MFPN) is proposed for SAR ship detection. The D-MFPN takes single-look complex image data as input and consists of two branches: the image branch designs a multi-layer feature pyramid network to enhance the positioning capacity for large ships combined with an attention module to refine the feature map’s expressiveness, and the doppler branch aims to build a feature matrix that characterizes the ship’s motion state by estimating the doppler center frequency and frequency modulation rate offset. To confirm the validity of each branch, individual ablation experiments are conducted. The experimental results on the Gaofen-3 satellite ship dataset illustrate the D-MFPN’s optimal performance in defocused ship detection tasks compared with six other competitive convolutional neural network (CNN)-based SAR ship detectors. Its satisfactory results demonstrate the application value of the deep-learning model fused with doppler features in the field of SAR ship detection.

Background: The production of intestinal gases and fecal short-chain fatty acids (SCFAs) by infant gut microbiota may have a significant impact on their health, but information about the composition and volume of intestinal gases and SCFA profiles in preterm infants is scarce.Objective: This study examined the change of the composition and volume of intestinal gases and SCFA profiles produced by preterm infant gut microbiota in vitro during the first 4 weeks of life.Methods: Fecal samples were obtained at five time points (within 3 days, 1 week, 2 weeks, 3 weeks, and 4 weeks) from 19 preterm infants hospitalized in the neonatal intensive care unit (NICU) of Shanghai Children's Hospital, Shanghai Jiao Tong University between May and July 2020. These samples were initially inoculated into four different media containing lactose (LAT), fructooligosaccharide (FOS), 2′-fucosyllactose (FL-2), and galactooligosaccharide (GOS) and thereafter fermented for 24 h under conditions mimicking those of the large intestine at 37.8°C under anaerobic conditions. The volume of total intestinal gases and the concentrations of individual carbon dioxide (CO2), hydrogen (H2), methane (CH4), and hydrogen sulfide (H2S) were measured by a gas analyzer. The concentrations of total SCFAs, individual acetic acid, propanoic acid, butyric acid, isobutyric acid, pentanoic acid, and valeric acid were measured by gas chromatography (GC).Results: The total volume of intestinal gases (ranging from 0.01 to 1.64 ml in medium with LAT; 0–1.42 ml with GOS; 0–0.91 ml with FOS; and 0–0.44 ml with FL-2) and the concentrations of CO2, H2, H2S, and all six fecal SCFAs increased with age (p-trends < 0.05). Among them, CO2 was usually the predominant intestinal gas, and acetic acid was usually the predominant SCFA. When stratified by birth weight (

Reduction in and recovery of precious metals are research hotspots in the environmental engineering field. In this study, we investigated the transformation and distribution of platinum in microbial fuel cells (MFCs) and demonstrated a feasible approach to recover platinum (Pt) from wastewater with less than 16.88 mg/L platinum through charring biofilms in MFCs and generate Pt/C catalyst. The optimal reaction condition was identified, and charred biofilms were analyzed via SEM-EDS, XRD and XPS. Results showed that less than 10% of Pt was in MFC effluents, and less than 0.5% was in the cathode chamber when the influent concentration was below 16.88 mg/L. Close to 40% of Pt could be recovered. The recovery efficiency could be higher should the reactions run longer. SEM-EDS and XRD results indicated that the metallic form Pt0 is one of the reduction products in MFCs. XPS results induced that Pt (IV) was reduced to Pt (II) and Pt0. Keywords: Microbial fuel cells, Platinum, Bio-reduction, Recovery, Sludge

Cell migration refers to the directional movement of cells to the surrounding cell-free zone in response to chemical and mechanical stimuli. A cell migration assay is an essential device for studying pharmaceutical and medical problems. In this paper, we present a novel approach to a cell migration assay on a chip with two merits, namely (i) simultaneous creation of many cell samples on the same condition and (ii) cells migrating while being stressed in a fluidic environment. The first merit has addressed the problem of poor reproducibility in experimental studies for medical problems such as wound healing, and the second merit has made the cell migration device, which is an in vitro environment, more biomimetic. The two merits are attributed to a novel mechanical method to simultaneously create many cell-free zones and to the design of a microfluidic process to create shear stress in cells uniformly. Two applications were studied on our device to explore its effectiveness. The first application is regarding the combination chemotherapy of cisplatin and doxorubicin (Adriamycin) on cervical cancer cells (HeLa). The second application is regarding inhibiting the migration of endothelial cells (HUVEC) in the process of anti-angiogenesis.

The different skeletal muscle fiber types exhibit distinctively different physiological and metabolic properties, and have been linked to both human metabolic diseases and meat quality traits in livestock. Circular RNAs (circRNAs) are a new class of endogenous RNA regulating gene expression, but regulatory mechanisms of skeletal muscle fibers involved in circRNAs remain poorly understood. Here, we constructed circRNA expression profiles of three fast-twitch biceps femoris (Bf) and three slow-twitch soleus (Sol) muscles in pigs using RNA-seq and identified 16,342 distinct circRNA candidates. Notably, 242 differentially expressed (DE) circRNAs between Bf and Sol muscles were identified, including 105 upregulated and 137 downregulated circRNAs, and are thus potential candidates for the regulation of skeletal muscle fiber conversion. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of host genes of DE circRNAs revealed that host genes were mainly involved in skeletal muscle fiber-related GO terms (e.g., muscle contraction, contractile fiber part, and Z disk) and skeletal muscle fiber-related signaling pathways (e.g., AMPK and cGMP-PKG). We also constructed co-expression networks of DE circRNA-miRNA-mRNA using previously acquired high-throughput sequencing mRNA and miRNA data, from which 112 circRNA-miRNA and 95 miRNA-mRNA interactions were identified. Multiple circRNAs essentially serve as a sponge for miR-499-5p, which is preferentially expressed in slow-twitch muscle and reduces the severity of Duchenne muscular dystrophy (DMD). Taken together, a series of novel candidate circRNAs involved in the growth and development of porcine skeletal muscle was identified. Furthermore, they provide a comprehensive circRNA resource for further in-depth research on the regulatory mechanisms of circRNA in the formation of skeletal muscle fiber, and may provide insights into human skeletal muscle diseases.

Mass vaccination against the COVID-19 pandemic is ongoing worldwide to achieve herd immunity among the general population. However, little is known about how the COVID-19 vaccination would affect mental health and preventive behaviors toward the COVID-19 pandemic. In this study, we conducted a cross-sectional survey to address this issue among 4244 individuals at several COVID-19 vaccination sites in Guangzhou, China. Using univariate analysis and multiple linear regression models, we found that major demographic characteristics, such as biological sex, age, education level, and family per capita income, are the dominant influencing factors associated with health beliefs, mental health, and preventive behaviors. After propensity score matching (PSM) treatment, we further assessed the changes in the scores of health belief, mental health, and preventive behaviors between the pre-vaccination group and the post-vaccination group. When compared to individuals in the pre-vaccination group, a moderate but statistically significant lower score was observed in the post-vaccination group (p = 0.010), implying possibly improved psychological conditions after COVID-19 vaccination. In addition, there was also a moderate but statistically higher score of preventive behaviors in the post-vaccination group than in the pre-vaccination group (p < 0.001), suggesting a higher probability to take preventive measures after COVID-19 vaccination. These findings have implications for implementing non-pharmaceutical interventions combined with mass vaccination to control the rebound of COVID-19 outbreaks.

Safety-conscious design and implementation of automotive electronics is now being important in safe driving under severe electromagnetic disturbance. In this paper, we introduce our experience and development framework to develop a safe electronic control unit (ECU) automotive controller algorithm using hardware-in-the-loop (HILS) based on Matlab/Simulink models, which are connected to ECU hardware. We propose a design flow of Matlab/Simulink based on model-based algorithm implementation of ECU controller and chip level ECU function emulation methodology using dSPACE’s MicroAutoBoxTM, which is an off the shelf embedded system for ECU software-hardware emulation. As a case study, we shows that fast design and implementation of the specific ECU hardware, which is integrated with custom-designed its controller algorithm for adaptive front-light system (AFLS) is easily evaluated by using the proposed development framework.