TRPC6 Knockout Alleviates Renal Fibrosis through PI3K/AKT/GSK3B Pathway.

OBJECTIVE: Renal fibrosis is the ultimate pathway of various forms of acute and chronic kidney damage. Notably, the knockout of transient receptor potential channel 6 (TRPC6) has shown promise in alleviating renal fibrosis. However, the regulatory impact of TRPC6 on renal fibrosis remains unclear. METHODS: In vivo, TRPC6 knockout (TRPC6-/-) mice and age-matched 129 SvEv (WT) mice underwent unilateral renal ischemia-reperfusion (uIR) injury surgery on the left renal pedicle or sham operation. Kidneys and serum were collected on days 7, 14, 21, and 28 after euthanasia. In vitro, primary tubular epithelial cells (PTECs) were isolated from TRPC6-/- and WT mice, followed by treatment with transforming growth factor ß1 (TGFß1) for 72 h. The anti-fibrotic effect of TRPC6-/- and the underlying mechanisms were assessed through hematoxylin-eosin staining, Masson staining, immunostaining, qRT-PCR, and Western blotting. RESULTS: Increased TRPC6 expression was observed in uIR mice and PTECs treated with TGFß1. TRPC6-/- alleviated renal fibrosis by reducing the expression of fibrotic markers (Col-1, α-SMA, and vimentin), as well as decreasing the apoptosis and inflammation of PTECs during fibrotic progression both in vivo and in vitro. Additionally, we found that the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/glycogen synthase kinase 3 beta (GSK3ß) signaling pathway, a pivotal player in renal fibrosis, was down-regulated following TRPC6 deletion. CONCLUSION: These results suggest that the ablation of TRPC6 may mitigate renal fibrosis by inhibiting the apoptosis and inflammation of PTECs through down-regulation of the PI3K/AKT/GSK3ß pathway. Targeting TRPC6 could be a novel therapeutic strategy for preventing chronic kidney disease.

Developing Deep LSTMs With Later Temporal Attention for Predicting COVID-19 Severity, Clinical Outcome, and Antibody Level by Screening Serological Indicators Over Time.

OBJECTIVE: The clinical course of COVID-19, as well as the immunological reaction, is notable for its extreme variability. Identifying the main associated factors might help understand the disease progression and physiological status of COVID-19 patients. The dynamic changes of the antibody against Spike protein are crucial for understanding the immune response. This work explores a temporal attention (TA) mechanism of deep learning to predict COVID-19 disease severity, clinical outcomes, and Spike antibody levels by screening serological indicators over time. METHODS: We use feature selection techniques to filter feature subsets that are highly correlated with the target. The specific deep Long Short-Term Memory (LSTM) models are employed to capture the dynamic changes of disease severity, clinical outcome, and Spike antibody level. We also propose deep LSTMs with a TA mechanism to emphasize the later blood test records because later records often attract more attention from doctors. RESULTS: Risk factors highly correlated with COVID-19 are revealed. LSTM achieves the highest classification accuracy for disease severity prediction. Temporal Attention Long Short-Term Memory (TA-LSTM) achieves the best performance for clinical outcome prediction. For Spike antibody level prediction, LSTM achieves the best permanence. CONCLUSION: The experimental results demonstrate the effectiveness of the proposed models. The proposed models can provide a computer-aided medical diagnostics system by simply using time series of serological indicators.

Circulating soluble CD30 is associated with renal tertiary lymphoid structures and the progression of IgA nephropathy.

BACKGROUND: Renal tertiary lymphoid structures (TLSs) are involved in renal pathology and prognosis of IgA nephropathy (IgAN). CD30 and its ligands participate in the formation of renal TLSs. However, the relationship between circulating CD30 and renal prognosis is unclear. The objective of this study was to evaluate the relationship between circulating CD30 and prognosis in patients with IgAN. METHODS: We conducted a retrospective study including 351 patients with biopsy proved IgAN. We collected clinical and pathologic features at the time of biopsy and recorded renal follow-up outcomes. Circulating CD30 levels in IgAN patients at the time of biopsy were measured via enzyme-linked immunosorbent assay (ELISA). The association between elevated CD30 levels and the composite endpoint (defined as a ≥ 50 % decline in eGFR from baseline, end-stage renal disease, or death) was investigated using Cox regression analysis. RESULTS: During a median follow-up period of 5.12 years, 44 (12.5 %) patients in the cohort reached the composite endpoint. Kaplan-Meier survival curve analysis revealed a significant association between higher circulating CD30 levels and a poorer renal prognosis (log-rank P < 0.001). Cox regression analysis showed that high CD30 was an independent factor for the composite endpoints in multivariable-adjusted models (HR 3.397, 95 % CI: 1.230-9.384, P = 0.018). These associations were also observed in a subgroup of patients with concomitant renal TLSs formation (10.443, 95 % CI: 1.680-65.545, P = 0.012), proteinuria > 1 g/d (HR 12.287, 95 % CI: 1.499-100.711, P = 0.019), and female patients (HR 22.372, 95 % CI: 1.797-278.520, P = 0.016). CONCLUSION: Elevated level of circulating CD30 is an independent risk factor for renal disease progression in patients with IgAN.

SerpinA3N Regulates the Secretory Phenotype of Mouse Senescent Astrocytes Contributing to Neurodegeneration.

Senescent astrocyte accumulation in the brain during normal aging is a driver of age-related neurodegenerative diseases such as Alzheimer's disease. However, the molecular events underlying astrocyte senescence in Alzheimer's disease are not fully understood. In this study, we demonstrated that senescent astrocytes display a secretory phenotype known as the senescence-associated secretory phenotype (SASP), which is associated with the upregulation of various proinflammatory factors and the downregulation of neurotrophic growth factors (eg, NGF and BDNF), resulting in a decrease in astrocyte-mediated neuroprotection and increased risk of neurodegeneration. We found that SerpinA3N is upregulated in senescent primary mouse astrocytes after serial passaging in vitro or by H2O2 treatment. Further exploration of the underlying mechanism revealed that SerpinA3N deficiency protects against senescent astrocyte-induced neurodegeneration by suppressing SASP-related factors and inducing neurotrophic growth factors. Brain tissues from Alzheimer's disease model mice possessed increased numbers of senescent astrocytes. Moreover, senescent astrocytes exhibited upregulated SerpinA3N expression in vitro and in vivo, confirming that our cell model recapitulated the in vivo pathology of these neurodegenerative diseases. Altogether, our study reveals a novel molecular strategy to regulate the secretory phenotype of senescent astrocytes and implies that SerpinA3N and its regulatory mechanisms may be potential targets for delaying brain aging and aging-related neurodegenerative diseases.

Effect of four chitinase genes on the female fecundity in Sogatella furcifera (Horváth).

BACKGROUND: The white-backed planthopper (WPH), Sogatella furcifera (Horváth), is a destructive rice pest with strong reproductive capacity. To gain insights into the roles of chitinases in the reproductive process of this insect species, this study represents the first-ever endeavor to conduct an in-depth exploration into the reproductive functions of four chitinase genes. RESULTS: In this study, it was observed that four chitinase genes were expressed in female adults, with a relatively high expression level in the ovaries. SfCht2 and SfIDGF1 were highly expressed during later ovarian development. while SfENGase increased and then decreased with ovarian development. SfCht2, SfCht6-2 and SfENGase were highly expressed in fat body on the first and second days after eclosion, whereas SfIDGF1 highest on day 7. Compared with control group, Silencing four chitinase genes inhibited ovarian development and significantly shortened the oviposition period of S. furcifera, reducing egg-laying capacity but not affecting egg hatching. The detection demonstrated that the expression levels of SfVg, SfVgR and 70-90% juvenile hormone (JH) signaling pathway-related reproductive genes was significantly down-regulated. Moreover, SfCht6-2 and SfENGase significantly affected the expression levels of Target of Rapamycin (TOR) signaling pathway genes. SfENGase had the ability to impact nutrient signaling pathways and fatty acid metabolism, repressing vitellogenin synthesis and ultimately influencing ovarian development of S. furcifera. CONCLUSIONS: Overall, this study provides insight into the function of chitinases in insect fecundity and is of great significance for enriching the cognition of insect chitinase function. They will become the suitable target genes for controlling the most destructive rice planthoppers. © 2023 Society of Chemical Industry.

Point-Based Learnable Query Generator for Human-Object Interaction Detection.

Transformer-based and interaction point-based methods have demonstrated promising performance and potential in human-object interaction detection. However, due to differences in structure and properties, direct integration of these two types of models is not feasible. Recent Transformer-based methods divide the decoder into two branches: an instance decoder for human-object pair detection and a classification decoder for interaction recognition. While the attention mechanism within the Transformer enhances the connection between localization and classification, this paper focuses on further improving HOI detection performance by increasing the intrinsic correlation between instance and action features. To address these challenges, this paper proposes a novel Transformer-based HOI Detection framework. In the proposed method, the decoder contains three parts: learnable query generator, instance decoder, and interaction classifier. The learnable query generator aims to build an effective query to guide the instance decoder and interaction classifier to learn more accurate instance and interaction features. These features are then applied to update the query generator for the next layer. Especially, inspired by the interaction point-based HOI and object detection methods, this paper introduces the prior bounding boxes, keypoints detection and spatial relation feature to build the novel learnable query generator. Finally, the proposed method is verified on HICO-DET and V-COCO datasets. The experimental results show that the proposed method has the better performance compared with the state-of-the-art methods.

A Contrastive Learning Network for Performance Metric and Assessment of Physical Rehabilitation Exercises.

Human activity analysis in the legal monitoring environment plays an important role in the physical rehabilitation field, as it helps patients with physical injuries improve their postoperative conditions and reduce their medical costs. Recently, several deep learning-based action quality assessment (AQA) frameworks have been proposed to evaluate physical rehabilitation exercises. However, most of them treat this problem as a simple regression task, which requires both the action instance and its score label as input. This approach is limited by the fact that the annotations in this field usually consist of healthy or unhealthy labels rather than quality scores provided by professional physicians. Additionally, most of these methods cannot provide informative feedback on a patient's motion defects, which weakens their practical application. To address these problems, we propose a multi-task contrastive learning framework to learn subtle and critical differences from skeleton sequences to deal with the performance metric and AQA problems of physical rehabilitation exercises. Specifically, we propose a performance metric network that takes triplets of training samples as input for score generation. For the AQA task, the same contrast learning strategy is used, but pairwise training samples are fed into the action quality assessment network for score prediction. Notably, we propose quantifying the deviation of the joint attention matrix between different skeleton sequences and introducing it into the loss function of our learning network. It is proven that considering both score prediction loss and joint attention deviation loss improves physical exercises AQA performance. Furthermore, it helps to obtain informative feedback for patients to improve their motion defects by visualizing the joint attention matrix's difference. The proposed method is verified on the UI-PRMD and KIMORE datasets. Experimental results show that the proposed method achieves state-of-the-art performance.

Machine-learning-based method for fiber-bending eavesdropping detection.

In this Letter, we present a scheme for detecting fiber-bending eavesdropping based on feature extraction and machine learning (ML). First, 5-dimensional features from the time-domain signal are extracted from the optical signal, and then a long short-term memory (LSTM) network is applied for eavesdropping and normal event classification. Experimental data are collected from a 60 km single-mode fiber transmission link with eavesdropping implemented by a clip-on coupler. Results show that the proposed scheme achieves a 95.83% detection accuracy. Furthermore, since the scheme focuses on the time-domain waveform of the received optical signal, additional devices and a special link design are not required.

Bestrophin3 Deficiency in Vascular Smooth Muscle Cells Activates MEKK2/3-MAPK Signaling to Trigger Spontaneous Aortic Dissection.

BACKGROUND: Aortic dissection (AD) is a fatal cardiovascular disorder without effective medications due to unclear pathogenic mechanisms. Bestrophin3 (Best3), the predominant isoform of bestrophin family in vessels, has emerged as critical for vascular pathological processes. However, the contribution of Best3 to vascular diseases remains elusive. METHODS: Smooth muscle cell-specific and endothelial cell-specific Best3 knockout mice (Best3SMKO and Best3ECKO, respectively) were engineered to investigate the role of Best3 in vascular pathophysiology. Functional studies, single-cell RNA sequencing, proteomics analysis, and coimmunoprecipitation coupled with mass spectrometry were performed to evaluate the function of Best3 in vessels. RESULTS: Best3 expression in aortas of human AD samples and mouse AD models was decreased. Best3SMKO but not Best3ECKO mice spontaneously developed AD with age, and the incidence reached 48% at 72 weeks of age. Reanalysis of single-cell transcriptome data revealed that reduction of fibromyocytes, a fibroblast-like smooth muscle cell cluster, was a typical feature of human ascending AD and aneurysm. Consistently, Best3 deficiency in smooth muscle cells decreased the number of fibromyocytes. Mechanistically, Best3 interacted with both MEKK2 and MEKK3, and this interaction inhibited phosphorylation of MEKK2 at serine153 and MEKK3 at serine61. Best3 deficiency induced phosphorylation-dependent inhibition of ubiquitination and protein turnover of MEKK2/3, thereby activating the downstream mitogen-activated protein kinase signaling cascade. Furthermore, restoration of Best3 or inhibition of MEKK2/3 prevented AD progression in angiotensin II-infused Best3SMKO and ApoE-/- mice. CONCLUSIONS: These findings unveil a critical role of Best3 in regulating smooth muscle cell phenotypic switch and aortic structural integrity through controlling MEKK2/3 degradation. Best3-MEKK2/3 signaling represents a novel therapeutic target for AD.

High Renal Mast Cell Density Is Associated with Poor Prognosis in Patients with Immunoglobulin A Nephropathy.

INTRODUCTION: This observational cohort study evaluated the prognostic value of mast cells in the pathogenesis and progression of IgA nephropathy. METHODS: A total of 76 adult IgAN patients were enrolled into this study from Jan 2007 and June 2010. Immunohistochemistry and immunofluorescence were used to identify tryptase-positive mast cells in renal biopsy samples. Patients were classified into Tryptasehigh and Tryptaselow groups. Depending on an average of 96-month follow-up, the predictive value of tryptase-positive mast cells in IgAN progression was analyzed. RESULTS: Tryptase-positive mast cells were found frequently in IgAN kidneys while rarely observed in normal kidneys. We also found IgAN patients in Tryptasehigh group presented both severe clinical and pathological renal manifestations. Furthermore, Tryptasehigh group contained more interstitial macrophages and lymphocytes infiltration than Tryptaselow group. Higher tryptase-positive cells density is associated with poor prognosis in patients with IgAN. CONCLUSIONS: High renal mast cells density is associated with severe renal lesions and poor prognosis in patients with Immunoglobulin A nephropathy. High renal mast cells density might be used as a predictor of poor prognosis in patients with IgAN.

Label-reconstruction-based pseudo-subscore learning for action quality assessment in sporting events.

Most existing action quality assessment (AQA) methods provide only an overall quality score for the input video and lack an evaluation of each substage of the movement process; thus, these methods cannot provide detailed feedback for users. Moreover, the existing datasets do not provide labels for substage quality assessment. To address these problems, in this work, a new label-reconstruction-based pseudo-subscore learning (PSL) method is proposed for AQA in sporting events. In the proposed method, the overall score of an action is not only regarded as a quality label but also used as a feature of the training set. A label-reconstruction-based learning algorithm is built to generate pseudo-subscore labels for the training set. Moreover, based on the pseudo-subscore labels and overall score labels, a multi-substage AQA model is fine-tuned from the PSL model to predict the action quality score of each substage and the overall score for an athlete. Several ablation experiments are performed to verify the effectiveness of each module. The experimental results show that our approach achieves state-of-the-art performance.

Efficacy comparison between iliosacral screw fixation of the posterior pelvic ring fracture with the assistance of modified percutaneous three-dimensional printing guide template and conventional fluoroscopy. / æ”¹è‰¯ç»çš®ä¸‰ç»´æ‰“å°å¯¼æ¿ä¸Žä¼ ç»Ÿé€è§†è¾ åŠ©éª¶é«‚èžºé’‰å›ºå®šéª¨ç›†åŽçŽ¯éª¨æŠ˜çš„ç–—æ•ˆæ¯”è¾ƒ.

OBJECTIVES: The effect of three-dimensional (3D) printed bone-attached guide plate assisted cannulated screw fixation of pelvic fracture is reliable, but extensive soft tissue dissection is still required when installing the guide plate. This study aims to compare the efficacy of posterior pelvic ring fracture fixation with iliosacral screw insertion between the assistance of modified percutaneous patient specific 3D printed guide template and conventional fluoroscopy. METHODS: From May, 2019 and September 2021, 28 patients sustained posterior pelvic ring fractures were randomized into 2 groups: A guide template group, in which the iliosacral screw was inserted for fixation of the posterior pelvic ring fracture with the assistance of modified percutaneous patient specific 3D printed guide template, and a fluoroscopy group, in which the iliosacral screw was inserted under the guidance of conventional fluoroscopy. The operation time, fluoroscopic frequency, intraoperative blood loss, and incision length were recorded for each screw insertion. Fracture reduction was evaluated according to the Matta criteria. The screw position was evaluated according to the modified Gras classification, and the functional outcome was evaluated according to Majeed score. The parameters of both groups were compared, and statistical analysis was performed. RESULTS: All the 28 patients were followed up for 12-24 months. Of them, 15 iliosacral screws were inserted in 14 patients in the guide template group, and 14 iliosacral screws were inserted in 14 patients in the fluoroscopy group. The operation time, fluoroscopic frequency, screw deviation, incision length, and blood loss in the guide template group were 20-30(25.8±2.8) min, 9-15(12.2±1.9), 2-4(2.6±0.7) mm, 4-5(4.6±0.5) cm, and 5-10 (7.8±1.7) mL, respectively, whereas those in the fluoroscopy group were 30-60(48.1±7.5) min, 40-96(64.7±16.3), 3-6(4.2±0.9) mm, 0.8-1.2(1.0±0.1) cm, and 2-5(3.1±1.3) mL, respectively, and there were statistical significance (all P<0.001). Fracture reduction was evaluated according to the Matta criteria, and all the patients reached excellence and good (P=0.584) in the 2 groups. According to modified Gras classification, there were 12 Grade I screws, 3 Grade II screws, and 0 Grade III screws in the guide template group, and 10 Grade I screws, 3 Grade II screws, and 1 Grade III screw in the fluoroscopy group, with no statistical significance (P=0.334). The functional outcome was evaluated according to Majeed score at the last follow-up, without significant difference between the guide template group and the fluoroscopy group (P=0.908). CONCLUSIONS: Compared with the conventional fluoroscopy, it would cost less operation time, less fluoroscopic frequency and increase more accurate screw insertion to fixate the posterior pelvic ring fracture with the assistance of modified percutaneous patient specific 3D printed guide template.

Growth Prediction of the Total Bacterial Count in Freshly Squeezed Strawberry Juice during Cold Storage Using Electronic Nose and Electronic Tongue.

The growth models of total bacterial count in freshly squeezed strawberry juice were established by gas and taste sensors in this paper. By selecting the optimal sensors and fusing the response values, the Modified Gompertz, Logistic, Huang and Baranyi models were used to predict and simulate the growth of bacteria. The results showed that the R2 values for fitting the growth model of total bacterial count of the sensor S7 (an electronic nose sensor), of sweetness and of the principal components scores were 0.890-0.944, 0.861-0.885 and 0.954-0.964, respectively. The correlation coefficients, or R-values, between models fitted by the response values and total bacterial count ranged from 0.815 to 0.999. A single system of electronic nose (E-nose) or electronic tongue (E-tongue) sensors could be used to predict the total bacterial count in freshly squeezed strawberry juice during cold storage, while the higher rate was gained by the combination of these two systems. The fusion of E-nose and E-tongue had the best fitting-precision in predicting the total bacterial count in freshly squeezed strawberry juice during cold storage. This study proved that it was feasible to predict the growth of bacteria in freshly squeezed strawberry juice using E-nose and E-tongue sensors.

Age- and Severity-Associated Humoral Immunity Response in COVID-19 Patients: A Cohort Study from Wuhan, China.

Age has been found to be the single most significant factor in COVID-19 severity and outcome. However, the age-related severity factors of COVID-19 have not been definitively established. In this study, we detected SARS-CoV-2-specific antibody responses and infectious disease-related blood indicators in 2360 sera from 783 COVID-19 patients, with an age range of 1−92 years. In addition, we recorded the individual information and clinical symptoms of the patients. We found that the IgG responses for S1, N, and ORF3a and the IgM for NSP7 were associated with severe COVID-19 at different ages. The IgM responses for the S-protein peptides S1-113 (aa 673−684) and S2-97 (aa 1262−1273) were associated with severe COVID-19 in patients aged <60. Furthermore, we found that the IgM for S1-113 and NSP7 may play a protective role in patients aged <60 and >80, respectively. Regarding clinical parameters, we analyzed the diagnostic ability of five clinical parameters for severe COVID-19 in six age groups and identified three-target panel, glucose, IL-6, myoglobin, IL-6, and NT proBNP as the appropriate diagnostic markers for severe COVID-19 in patients aged <41, 41−50, 51−60, 61−70, 71−80, and >80, respectively. The age-associated severity factors revealed here will facilitate our understanding of COVID-19 immunity and diagnosis, and eventually provide meaningful information for combating the pandemic.

Efficacy and safety of monotherapy and combination therapy of immune checkpoint inhibitors as first-line treatment for unresectable hepatocellular carcinoma: a systematic review, meta-analysis and network meta-analysis.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the cancers with the highest morbidity and mortality. Sorafenib used to be the main treatment for unresectable HCC patients. However, regimens based on immune checkpoint inhibitors (ICIs) have attracted attention in recent years because of their reported benefits. This study aimed to evaluate the efficacy and safety of monotherapy and combination therapy of ICIs as first-line treatment for unresectable HCC patients by conducting a systematic review, meta-analysis, and network meta-analysis. METHODS: Studies published up to 11st August 2022 were searched from 4 commonly used databases, including PubMed, Web of Science, Embase, and Clinical trials.gov. All eligible clinical trials were included. Data about reported objective response rate (ORR), disease control rate (DCR), overall survival (OS), progression-free survival (PFS), and treatment-related adverse events (TRAEs) were extracted. RESULTS: Of the 8579 studies retrieved, 24 met the inclusion criteria. In patients with unresectable HCC taking ICIs-based therapy as first-line treatment, the pooled result of median PFS and median OS was 5.76 months (95% CI 4.82-6.69) and 16.35 months (95% CI 15.19-17.51) The ORR and DCR were 25.1% (95% CI 20.8-29.5%) and 75.2% (95% CI 70.3-80.2%) measured by RECIST v1.1 or 40.2% (95% CI 31.7-48.6%) with 75.2% (95% CI 68.3-82.1%) measured by mRECIST v1.1. Compared to sorafenib, ICIs-based therapy significantly prolonged OS. The combination treatment of sintilimab plus IBI305 had the highest ORR, while atezolizumab plus bevacizumab had the highest DCR. The pooled incidence of any grade TRAEs was 82.3% (95% CI 73.9-90.7%), with highest incidence appeared in dysphonia. CONCLUSIONS: This study demonstrated that first-line ICIs-based therapies could provide survival benefits for patients with unresectable HCC, with manageable TRAEs. The potential of combination treatment to become the new treatment trend in clinical practice is promising.

A Systematic Review with Meta-Analysis of Comparative Efficacy and Safety of Risankizumab and Ustekinumab for Psoriasis Treatment.

Biological targeted therapy serves as a new alternative treatment for psoriasis due to its minimal side effects. This study is aimed at examining the drug effectiveness and safety of risankizumab and ustekinumab for psoriasis treatment, so as to provide a reference for clinical decision-making. Databases from Embase, Web of Science, PubMed, and Cochrane Library were gathered, starting from inception to March 1, 2022, for randomized controlled trials regarding risankizumab and ustekinumab for psoriasis treatment. All retrieved articles were carefully selected in strict accordance with a set of inclusion and exclusion criteria. Stata 15.0 and RevMan 5.4 were applied to perform meta-analysis and risk of bias assessment. A total of two trials with three NCTs were selected, with 384 participants in the risankizumab group and 140 participants in ustekinumab. Meta-analysis showed that in the long-term and short-term PASI100, risankizumab was more effective than ustekinumab (RR = 2.27, 95% CI (1.77, 2.90), p < 0.05; RR = 2.33, 95% CI (1.75, 3.08), p < 0.05). In PASI90, RR = 1.77, 95% CI (1.54, 2.03), and p < 0.05 and RR = 1.72, 95% CI (1.48, 2.00), and p < 0.05. In short-term PASI75, RR = 1.23, 95% CI (1.13, 1.34), and p < 0.05. In sPGA of 0, the results at week-16 and week-52 showed that risankizumab was significantly more effective than ustekinumab (RR = 2.24, 95% CI (1.67, 3.01), p < 0.05; RR = 2.30, 95% CI (1.80, 2.95), p < 0.05). Risankizumab was significantly more effective than ustekinumab in improving the quality of life and PSS scores (RR = 1.48, 95% CI (1.26, 1.75), p < 0.05; RR = 2.01, 95% CI (1.41, 2.85), p < 0.05). Nevertheless, risankizumab and ustekinumab did not show significant difference in the incidence of adverse responses (RR = 1.02, 95% CI (0.75, 1.39), p > 0.05). Risankizumab was more effective than ustekinumab for the treatment of psoriasis. The adverse reactions of both risankizumab and ustekinumab were similar and could be tolerated. Risankizumab might be a better alternative option for their treatment.

Economic Burden and Quality of Life of Hepatocellular Carcinoma in Greater China: A Systematic Review.

Background: Hepatocellular carcinoma (HCC) accounts for more than 85%-90% of primary liver cancer globally, and approximately 45% of deaths from HCC occur in greater China. This disease poses a significant economic burden for patients, payers and society and significantly affects patients' quality of life (QoL). However, such impact of HCC in greater China has not been well characterized. This review was conducted to analyze the current evidence about the economic and humanistic impact of HCC in greater China for informing national disease management and identifying clinical gaps yet to be resolved. Methods: A systematic search literature using seven databases (Web of Science, PubMed, Medline, Cochrane Central, China National Knowledge Infrastructure, Wanfang, and Weipu) was performed to identify interventional and observational studies that reported the impact of HCC on cost or QoL and published before April 6, 2021. The focus population included adult patients with HCC in greater China. This review excluded any studies that focused on any specific treatment. Study quality was assessed using the Effective Public Health Practice Project tool. Results: Of 39,930 studies retrieved, 27 were deemed eligible for inclusion. The methodologies, perspectives and data sources used in studies were heterogeneous. In greater China, while few studies reported the health expenditures of HCC patients and investigations about economic burden at national level was lacking, the significant economic impact of HCC on patients and their families had been reported. Health-related costs increased as the disease deteriorated. Additionally, HCC also has a negative impact on the QoL of patients, mostly in terms of physical, cognitive, social functioning and severe symptoms. Conclusions: HCC has brought significant economic and QoL burden to patients in greater China. Both physical and psychological factors predicted QoL in patients with HCC in greater China. Future studies should explore the disease-related economic effects on Chinese patients and their families, the effects of physical and psychological factors on QoL and the relationships of physical and psychological factors in the region.Systematic Review Registration: www.crd.york.ac.uk/prospero/display_record.php?RecordID=278421, PROSPERO: CRD42021278421.

SARS-CoV-2-specific antibody response characteristics in COVID-19 patients of different ages.

Age has been found to be one of the main risk factors for the severity and outcome of COVID-19. However, differences in SARS-CoV-2 specific antibody responses among COVID-19 patients of different age groups remain largely unknown. In this study, we analyzed the IgG/IgM responses to 21 SARS-CoV-2 proteins and 197 peptides that fully cover the spike protein against 731 sera collected from 731 COVID-19 patients aged from 1 to We show that there is no overall difference in SARS-CoV-2 antibody responses in COVID-19 patients in the 4 age groups. By antibody response landscape maps, we find that the IgG response profiles of SARS-CoV-2 proteins are positively correlated with age. The S protein linear epitope map shows that the immunogenicity of the S-protein peptides is related to peptide sequence, disease severity and age of the COVID-19 patients. Furthermore, the enrichment analysis indicates that low S1 IgG responses are enriched in patients aged <50 and high S1 IgG responses are enriched in mild COVID-19 patients aged >60. In addition, high responses of non-structural/accessory proteins are enriched in severe COVID-19 patients aged >70. These results suggest the distinct immune response of IgG/IgM to each SARS-CoV-2 protein in patients of different age, which may facilitate a deeper understanding of the immune responses in COVID-19 patients.

Potential Regulators of the Senescence-Associated Secretory Phenotype During Senescence and Aging.

Senescent cells express and secrete a variety of extracellular modulators that include cytokines, chemokines, proteases, growth factors, and some enzymes associated with extracellular matrix remodeling, defined as the senescence-associated secretory phenotype (SASP). SASP reinforces senescent cell cycle arrest, stimulates and recruits immune cells for immune-mediated clearance of potentially tumorigenic cells, limits or induces fibrosis, and promotes wound healing and tissue regeneration. On the other hand, SASP mediates chronic inflammation leading to the destruction of tissue structure and function and stimulating the growth and survival of tumor cells. SASP is highly heterogeneous and the role of SASP depends on the context. The regulation of SASP occurs at multiple levels including chromatin remodeling, transcription, mRNA translation, intracellular trafficking, and secretion. Several SASP modulators have already been identified setting the stage for future research on their clinical applications. In this review, we summarize in detail the potential signaling pathways that trigger and regulate SASP production during aging and senescence.

Prediction of Energy Storage Performance in Polymer Composites Using High-Throughput Stochastic Breakdown Simulation and Machine Learning.

Polymer dielectric capacitors are widely utilized in pulse power devices owing to their high power density. Because of the low dielectric constants of pure polymers, inorganic fillers are needed to improve their properties. The size and dielectric properties of fillers will affect the dielectric breakdown of polymer-based composites. However, the effect of fillers on breakdown strength cannot be completely obtained through experiments alone. In this paper, three of the most important variables affecting the breakdown strength of polymer-based composites are considered: the filler dielectric constants, filler sizes, and filler contents. High-throughput stochastic breakdown simulation is performed on 504 groups of data, and the simulation results are used as the machine learning database to obtain the breakdown strength prediction of polymer-based composites. Combined with the classical dielectric prediction formula, the energy storage density prediction of polymer-based composites is obtained. The accuracy of the prediction is verified by the directional experiments, including dielectric constant and breakdown strength. This work provides insight into the design and fabrication of polymer-based composites with high energy density for capacitive energy storage applications.