Modulating Inter-Muscular Coordination Patterns in the Upper Extremity Induces Changes to Inter-Muscular, Cortico-Muscular, and Cortico-Cortical Connectivity.

OBJECTIVE: The changes in neural drive to muscles associated with modulation of inter-muscular coordination in the upper extremity have not yet been investigated. Such information could help elucidate the neural mechanisms behind motor skill learning. METHODS: Six young, neurologically healthy participants underwent a six-week training protocol to decouple two synergist elbow flexor muscles as a newly learned motor skill in the isometric force generation in upward and medial directions. Concurrent electroencephalography and surface electromyography from twelve upper extremity muscles were recorded in two conditions (As-Trained & Habitual) across two assessments (Week 0 vs. Week 6). Changes to inter-muscular connectivity (IMC), functional muscle networks, cortico-muscular connectivity (CMC), cortico-cortical connectivity (CCC) as well as functional brain network controllability (FBNC) associated with the modulation of inter-muscular coordination patterns were assessed to provide a perspective on the neural mechanisms for the newly learned motor skills. RESULTS: Significant decreases in elbow flexor IMC, CMC, and increases in CCC were observed. No significant changes were observed for FBNC. CONCLUSION: The results of this study suggest that modulating the inter-muscular coordination of the elbow flexor muscle synergy during isometric force generation is associated with multiple yet distinct changes in functional connectivity across the central and peripheral perspectives. SIGNIFICANCE: Understanding the neural mechanisms of modulating inter-muscular coordination patterns can help inform motor rehabilitation regimens.

EEG emotion recognition based on data-driven signal auto-segmentation and feature fusion.

Pattern recognition based on network connections has recently been applied to the brain-computer interface (BCI) research, offering new ideas for emotion recognition using Electroencephalogram (EEG) signal. However unified standards are currently lacking for selecting emotional signals in emotion recognition research, and potential associations between activation differences in brain regions and network connectivity pattern are often being overlooked. To bridge this technical gap, a data-driven signal auto-segmentation and feature fusion algorithm (DASF) is proposed in this paper. First, the Phase Locking Value (PLV) method was used to construct the brain functional adjacency matrix of each subject, and the dynamic brain functional network across subjects was then constructed. Next, tucker decomposition was performed and the Grassmann distance of the connectivity submatrix was calculated. Subsequently, different brain network states were distinguished and signal segments under emotional states were automatically extract using data-driven methods. Then, tensor sparse representation was adopted on the intercepted EEG signals to effectively extract functional connections under different emotional states. Finally, power-distribution related features (differential entropy and energy feature) and brain functional connection features were effectively combined for classification using the support vector machines (SVM) classifier. The proposed method was validated on ERN and DEAP datasets. The single-feature emotion classification accuracy of 86.57 % and 87.74 % were achieved on valence and arousal dimensions, respectively. The accuracy of the proposed feature fusion method was achieved at 89.14 % and 89.65 %, accordingly, demonstrating an improvement in emotion recognition accuracy. The results demonstrated the superior classification performance of the proposed data-driven signal auto-segmentation and feature fusion algorithm in emotion recognition compared to state-of-the-art classification methods.

Vaginal flora in HPV infection: a cross­sectional analysis.

OBJECTIVE: The vaginal flora has been reported to be associated with human papillomavirus (HPV) infection. The purpose of this study was to investigate the characteristics of the cervical microbiota in patients with HPV infection and to analyse the changes in the vaginal flora and enzyme profiles in females with HPV infection. METHODS: We conducted a cross-sectional study involving 206 participants who underwent HPV genotyping, sexually transmitted diseases pathogen testing, cytology examination, and microbiome analysis. Additionally, we collected 115 HPV-negative samples and 48 HPV-positive samples for 16S rRNA amplicon sequencing. The vaginal microbial communities of both groups were analysed for diversity and differences to explore their association with HPV infection. RESULTS: The abundance of Lactobacillus was found to be reduced, while Gardnerella vaginalis was significantly more prevalent in the HPV + group. In terms of alpha diversity indices, the Shannon index (P = .0036) and Simpson index (P = .02) were higher in the HPV + group compared to the HPV - group, indicating greater community diversity in the HPV + group. Among the 10 sexually transmitted diseases pathogens analysed, Uup3 and Uup6 were significantly associated with HPV infection. Statistically significant differences were observed in Nugent scores and bacterial vaginosis between the two groups (P < .05). In functional analysis, 11 proteins and 13 enzymes were found to be significantly altered in the HPV + group. CONCLUSION: Our study demonstrates that disruptions in the vaginal flora are associated with HPV infection. Reduced levels of Lactobacillus, increased prevalence of Gardnerella, and abnormal enzyme profiles are closely linked to HPV infection.

The purpose of this study was to investigate the characteristics of the cervical microbiota in patients with human papillomavirus infection and to analyse the changes in the vaginal flora and enzyme profiles in females with human papillomavirus infection. We conducted a cross-sectional study involving 206 participants who underwent human papillomavirus genotyping, sexually transmitted diseases pathogen testing, cytology examination, and microbiome analysis. Additionally, we collected 115 HPV-negative samples and 48 HPV-positive samples for 16S rRNA amplicon sequencing. The abundance of Lactobacillus was found to be reduced, while Gardnerella vaginalis was significantly more prevalent in the HPV + group. In functional analysis, 11 proteins and 13 enzymes were found to be significantly altered in the HPV + group. Our study demonstrates that disruptions in the vaginal flora are associated with HPV infection. Reduced levels of Lactobacillus, increased prevalence of Gardnerella, and abnormal enzyme profiles are closely linked to HPV infection.

A case report of intrahepatic bile duct dilatation caused by WDR19 gene mutation and presented as Caroli syndrome.

Background: Caroli syndrome or Caroli disease is characterized by focal dilation of the intrahepatic bile ducts, with or without congenital liver fibrosis. Mutations in the WDR19 gene can result in nephropathy, an autosomal recessive cystic kidney disease. However, this genetic mutation is clinically associated with Caroli syndrome or disease. We hypothesize that WDR19 gene mutations may contribute to extrarenal phenotypes such as Caroli disease or syndrome. Case Description: The outpatient department received a 1-year-old male patient with persistent dilated bile ducts for over four months. Subsequent ultrasound examination revealed liver cirrhosis, splenomegaly, and cystic dilatation of the intrahepatic bile duct. He was subsequently admitted for comprehensive diagnosis and treatment. Accordingly, we performed computed tomography (CT)-hepatic portal venography, magnetic resonance-cholangiography, and the plain liver scan, the results revealed liver cirrhosis, splenomegaly, cystic dilatation of the intrahepatic bile duct, as well as atypical hyperplasia nodules in the right posterior lobe of the liver and lymphatic hyperplasia and enlargement in the porta hepatis and the space between the liver and stomach. As the possibility of early small liver cancer could not be excluded due to the presence of nodules, surgical resection was performed followed by pathological examination and whole genome exome testing. The pathological findings revealed hepatocyte swelling, hydropic degeneration, and sporadic necrosis. Fibrous tissue hyperplasia was observed in the portal vein area, along with local pseudolobule formation. Also, numerous small bile duct hyperplasia was observed with lymphocyte infiltration, which is consistent with cirrhosis. Moreover, the hepatocytes of the small focal area showed atypical hyperplasia. Considering the above findings, Caroli syndrome was diagnosed. The genetic results showed two heterozygous mutations in the WDR19 gene, c.2290delC (p.Q764Nfs*29) and c.2401G>C (p.G801R). Therefore, the child's intrahepatic bile duct dilatation and cirrhosis were considered as the manifestations of Caroli syndrome caused by mutations in the WDR19 gene. Conclusions: Mutations in the WDR19 gene can manifest as Caroli disease or Caroli syndrome. For the definite diagnosis of liver diseases of unknown etiology, whole exome sequencing may be more conducive.

The etiology and differential diagnosis of "autoimmune hepatitis-like liver disease" in children: a single-center retrospective study.

Background: Children with autoimmune hepatitis (AIH) often present with symptoms similar to those of other liver diseases. This study consists of a comparison between the clinical and histological characteristics of AIH and those of other four AIH-like liver diseases [i.e., drug-induced liver injury (DILI), gene deficiency, infectious liver disease and other etiology of liver disease], as well as an evaluation of the AIH scoring system's diagnostic performance. Methods: All children with AIH-like liver disease at our center from January 2013 to December 2022 were included. The clinical and histological characteristics of the AIH group were retrospectively analyzed and compared with those of the other four groups. Results: A total of 208 children were included and divided into AIH group (18 patients), DILI group (38 patients), gene deficiency group (44 patients), infectious liver disease group (74 patients), and other etiology group (34 patients). The antinuclear antibodies (ANA) ≥ 1:320 rate was significantly higher in the AIH compared to the other four groups after multiple testing correction (p < 0.0125), while patients with positive antibodies to liver-kidney microsomal-1 (anti-LKM1, n = 3) and smooth muscle antibodies (SMA, n = 2) were only observed in the AIH group. The positive rates of antibodies to liver cytosol type1 (anti-LC1) and Ro52 were higher than those in the other four groups. The serum immunoglobulin G (IgG) and globulin levels, as well as the proportions of portal lymphoplasmacytic infiltration, lobular hepatitis with more than moderate interface hepatitis, and lobular hepatitis with lymphoplasmacytic infiltration, were significantly higher in the AIH group than in the other four groups after multiple testing correction (p < 0.0125). The cirrhosis rate in the AIH group was higher than that in the DILI and infectious liver disease groups (p < 0.0125). Both the simplified (AUC > 0.73) and the revised systems (AUC > 0.93) for AIH have good diagnostic performance, with the latter being superior (p < 0.05). Conclusion: Positive autoantibodies (ANA ≥ 1:320 or anti-LKM1 positive, or accompanied by SMA, anti-LC1 or Ro-52 positive) and elevated serum IgG or globulin levels contribute to early recognition of AIH. The presence of lobular hepatitis with more than moderate interface hepatitis and lymphoplasmacytic infiltration contribute to the diagnosis of AIH.

Enhancing cross-subject EEG emotion recognition through multi-source manifold metric transfer learning.

Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptation challenges in affective brain-computer interfaces (aBCI). However, previous TL methods usually use a stationary distance, such as Euclidean distance, to quantify the distribution dissimilarity between two domains, overlooking the inherent links among similar samples, potentially leading to suboptimal feature mapping. In this study, we introduced a novel algorithm called multi-source manifold metric transfer learning (MSMMTL) to enhance the efficacy of conventional TL. Specifically, we first selected the source domain based on Mahalanobis distance to enhance the quality of the source domains and then used manifold feature mapping approach to map the source and target domains on the Grassmann manifold to mitigate data drift between domains. In this newly established shared space, we optimized the Mahalanobis metric by maximizing the inter-class distances while minimizing the intra-class distances in the target domain. Recognizing that significant distribution discrepancies might persist across different domains even on the manifold, to ensure similar distributions between the source and target domains, we further imposed constraints on both domains under the Mahalanobis metric. This approach aims to reduce distributional disparities and enhance the electroencephalogram (EEG) emotion recognition performance. In cross-subject experiments, the MSMMTL model exhibits average classification accuracies of 88.83 % and 65.04 % for SEED and DEAP, respectively, underscoring the superiority of our proposed MSMMTL over other state-of-the-art methods. MSMMTL can effectively solve the problem of individual differences in EEG-based affective computing.

The epidemiological characteristics of liver disease in hospitalized children: a 10-year single-center retrospective study.

Background: This investigation aimed to examine the epidemiological characteristics of children with liver disease hospitalized for the first time between June 2012 and May 2022 in a tertiary hospital. Methods: The study retrospectively recruited children aged between 29 days and 18 years who had been hospitalized for liver disease. Clinical characteristics were categorized by age and etiology, and time trends were assessed using linear regression analysis. Results: A total of 4,313 children were recruited, with a median age of 0.7 (0.2-4.5) years, and 54.5% of the cases were in the 0-1 years age group. Infection was the primary cause of liver disease (30.0%), followed by undiagnosed cases (25.8%), biliary obstructive disease (15.9%), inherited metabolic liver disease (13.9%), and non-alcoholic fatty liver disease (NAFLD) (3.2%). Genetic diagnoses were established in 43.9% (478/1,088) of patients. The percentage of NAFLD demonstrated an upward trend from 1.2% in 2012 to 12.6% in 2022 (p = 0.006). In contrast, the percentage of cytomegalovirus hepatitis decreased from 13.3% in 2012 to 3.4% in 2022 (p = 0.002). Conclusions: Liver disease in infancy makes up the largest group in pediatric liver disease. Infection remains the leading cause of pediatric liver disease. Hospital admissions for NAFLD in children have increased rapidly over the past decade, while cytomegalovirus hepatitis has declined markedly.

Zn-Doped MnCO3/CS Composite Photocatalyst for Visible-Light-Driven Decomposition of Organic Pollutants.

Zn-doped MnCO3/carbon sphere (Zn-doped MnCO3/CS) composites were synthesized using a simple hydrothermal procedure. Among various samples (ZM-50, ZM-05, and ZMC-0), the ternary Zn-doped MnCO3/CS (ZMC-2) catalyst demonstrated excellent visible light-induced photocatalytic activity. This improvement comes from the Zn addition and the conductive CS, which facilitate electron movement and charge transport. The catalyst exhibited efficient degradation of methylene blue (MB) over a wide pH range, achieving a removal efficiency of 99.6% under visible light. Radical trapping experiments suggested that •OH and •O2- played essential roles in the mechanism of organic pollutant degradation. Moreover, the catalyst maintained good degradation performance after five cycles. This study offers valuable perspectives into the fabrication of carbon-based composites with promising photocatalytic activity.

Locating sources of Szegedy's quantum network.

Source location in quantum networks is a critical area of research with profound implications for cutting-edge fields such as quantum state tomography, quantum computing, and quantum communication. In this study, we present groundbreaking research on the technique and theory of source location in Szegedy's quantum networks. We develop a linear system evolution model for a Szegedy's quantum network system using matrix vectorization techniques. Subsequently, we propose a highly precise and robust source-location algorithm based on compressed sensing specifically tailored for Szegedy's quantum network. To validate the effectiveness and feasibility of our algorithm, we conduct numerical simulations on various model and real networks, yielding compelling results. These findings underscore the potential of our approach in practical applications.

Identification of a novel heterozygous variant in the PEX26 gene in an infant: a case report.

Background: The protein PEX26 is involved in the biogenesis and maintenance of peroxisomes, which are organelles within cells. Dysfunction of PEX26 results in peroxisome biogenesis disorders (PBDs) complementation group 8 (CG8), leading to Zellweger spectrum disorders (ZSDs). These disorders present as a syndrome with multiple congenital anomalies, varying in clinical severity. Case Description: We present the case of a 7-month-old boy who exhibited hepatic impairment with hepatomegaly, sensorineural hearing loss, developmental delay, abnormal ossification, and mild craniofacial dysmorphology. Tandem mass spectrometry analysis of plasma isolated from whole blood revealed a significant increase in the levels of very long chain fatty acids (VLCFAs) C26:0, C26:0/C22:0, and C24:0/C22:0, consistent with peroxisomal fatty acid oxidation disorder. Exome sequencing identified two variants in the PEX26 gene (c.347T>C and c.616C>T), with the latter being a suspected pathogenic variation. The variant can lead to a defect in the PEX26 gene, resulting in impaired peroxisome biogenesis, ß-oxidation of VLCFAs, and disruption of other biochemical pathways. Ultimately, this cascade of events manifests as ZSDs. Currently, symptomatic supportive treatment is the main approach for managing this condition and regular follow-up is being conducted for the patient. Conclusions: The present study introduces a novel heterozygous variant comprising two previously unidentified variants in the PEX26 gene, thereby expanding the range of known genetic alterations and highlighting the effectiveness of highly efficient exome sequencing in patients with undetermined multiple system dysfunctions.

The control patterns of affective processing and cognitive reappraisal: insights from brain controllability analysis.

Perceiving and modulating emotions is vital for cognitive function and is often impaired in neuropsychiatric conditions. Current tools for evaluating emotional dysregulation suffer from subjectivity and lack of precision, especially when it comes to understanding emotion from a regulatory or control-based perspective. To address these limitations, this study leverages an advanced methodology known as functional brain controllability analysis. We simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data from 17 healthy subjects engaged in emotion processing and regulation tasks. We then employed a novel EEG/fMRI integration technique to reconstruct cortical activity in a high spatiotemporal resolution manner. Subsequently, we conducted functional brain controllability analysis to explore the neural network control patterns underlying different emotion conditions. Our findings demonstrated that the dorsolateral and ventrolateral prefrontal cortex exhibited increased controllability during the processing and regulation of negative emotions compared to processing of neutral emotion. Besides, the anterior cingulate cortex was notably more active in managing negative emotion than in either controlling neutral emotion or regulating negative emotion. Finally, the posterior parietal cortex emerged as a central network controller for the regulation of negative emotion. This study offers valuable insights into the cortical control mechanisms that support emotion perception and regulation.

Lipid nanoparticle-encapsulated DNA vaccine robustly induce superior immune responses to the mRNA vaccine in Syrian hamsters.

DNA vaccines for infectious diseases and cancer have been explored for years. To date, only one DNA vaccine (ZyCoV-D) has been authorized for emergency use in India. DNA vaccines are inexpensive and long-term thermostable, however, limited by the low efficiency of intracellular delivery. The recent success of mRNA/lipid nanoparticle (LNP) technology in the coronavirus disease 2019 (COVID-19) pandemic has opened a new application for nucleic acid-based vaccines. Here, we report that plasmid encoding a trimeric spike protein with LNP delivery (pTS/LNP), similar to those in Moderna's COVID-19 vaccine, induced more effective humoral responses than naked pTS or pTS delivered via electroporation. Compared with TSmRNA/LNP, pTS/LNP immunization induced a comparable level of neutralizing antibody titers and significant T helper 1-biased immunity in mice; it also prolonged the maintenance of higher antigen-specific IgG and neutralizing antibody titers in hamsters. Importantly, pTS/LNP immunization exhibits enhanced cross-neutralizing activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and protects hamsters from the challenge of SARS-CoV-2 (Wuhan strain and the Omicron BA.1 variant). This study indicates that pDNA/LNPs as a promising platform could be a next-generation vaccine technology.

Expanding the repertoire of intermuscular coordination patterns and modulating intermuscular connectivity in stroke-affected upper extremity through electromyogram-guided training: a pilot study.

Abnormal intermuscular coordination is a major stroke-induced functional motor impairment in the upper extremity (UE). Previous studies have computationally identified the abnormalities in the intermuscular coordination in the stroke-affected UE and their negative impacts on motor outputs. Therefore, targeting the aberrant muscle synergies has the potential as an effective approach for stroke rehabilitation. Recently, we verified the modifiability of the naturally expressed muscle synergies of young able-bodied adults in UE through an electromyographic (EMG) signal-guided exercise protocol. This study tested if an EMG-guided exercise will induce new muscle synergies, alter the associated intermuscular connectivity, and improve UE motor outcome in stroke-affected UE with moderate-to-severe motor impairment. The study used the six-week isometric EMG signal-guided exercise protocol that focused on independently activating two specific muscles, the biceps and brachioradialis, to develop new muscle activation groups. The study found that both the stroke and age-matched, able-bodied groups were able to develop new muscle coordination patterns through the exercise while habitual muscle activation was still available, which led to improvements in the motor control of the trained arm. In addition, the results provided preliminary evidence of increased intermuscular connectivity between targeted muscles in the beta-band frequencies for stroke patients after training, suggesting a modulation of the common neural drive. These findings suggest that our isometric exercise protocol has the potential to improve stroke survivors' performance of UE in their activities in daily lives (ADLs) and, ultimately, their quality of life through expanding their repertoire of intermuscular coordination.Clinical Relevance- This study shows the feasibility of expanding the intermuscular coordination pattern in stroke-affected UE through an isometric EMG-guided exercise which positively affects task performance and intermuscular connectivity.

Uncertainty-guided cross learning via CNN and transformer for semi-supervised honeycomb lung lesion segmentation.

Objective. Deep learning networks such as convolutional neural networks (CNN) and Transformer have shown excellent performance on the task of medical image segmentation, however, the usual problem with medical images is the lack of large-scale, high-quality pixel-level annotations, which is a very time-consuming and laborious task, and its further leads to compromised the performance of medical image segmentation under limited annotation conditions.Approach. In this paper, we propose a new semi-supervised learning method, uncertainty-guided cross learning, which uses a limited number of annotated samples along with a large number of unlabeled images to train the network. Specifically, we use two networks with different learning paradigms, CNN and Transformer, for cross learning, and use the prediction of one of them as a pseudo label to supervise the other, so that they can learn from each other, fully extract the local and global features of the images, and combine explicit and implicit consistency regularization constraints with pseudo label methods. On the other hand, we use epistemic uncertainty as a guiding message to encourage the model to learn high-certainty pixel information in high-confidence regions, and minimize the impact of erroneous pseudo labels on the overall learning process to improve the performance of semi-supervised segmentation methods.Main results. We conducted honeycomb lung lesion segmentation experiments using a honeycomb lung CT image dataset, and designed several sets of comparison experiments and ablation experiments to validate the effectiveness of our method. The final experimental results show that the Dice coefficient of our proposed method reaches 88.49% on the test set, and our method achieves state-of-the-art performance in honeycomb lung lesion segmentation compared to other semi-supervised learning methods.Significance. Our proposed method can effectively improve the accuracy of segmentation of honeycomb lung lesions, which provides an important reference for physicians in the diagnosis and treatment of this disease.

A broad-spectrum pneumococcal vaccine induces mucosal immunity and protects against lethal Streptococcus pneumoniae challenge.

Pneumococcal disease is a major threat to public health globally, impacting individuals across all age groups, particularly infants and elderly individuals. The use of current vaccines has led to unintended consequences, including serotype replacement, leading to a need for a new approach to combat pneumococcal disease. A promising solution is the development of a broad-spectrum pneumococcal vaccine. In this study, we present the development of a broad-spectrum protein-based pneumococcal vaccine that contains three pneumococcal virulence factors: rlipo-PsaA (lipidated form), rPspAΔC (truncated form), and rPspCΔC (truncated form). Intranasal immunization with rlipo-PsaA, rPspAΔC, and rPspCΔC (LAAC) resulted in significantly higher IgG titres than those induced by administration of nonlipidated rPsaA, rPspAΔC, and rPspCΔC (AAC). Furthermore, LAAC immunization induced the production of higher IgA titres in vaginal washes, feces, and sera in mice, indicating that LAAC can induce systemic mucosal immunity. In addition, administration of LAAC also induced Th1/Th17-biased immune responses and promoted opsonic phagocytosis of Streptococcus pneumoniae strains of various serotypes, implying that the immunogenicity of LAAC immunization provides a protective effect against pneumococcal infection. Importantly, challenge data showed that the LAAC-immunized mice had a reduced bacterial load not only for several serotypes of the 13-valent conjugate pneumococcal vaccine (PCV13) but also for selected non-PCV13 serotypes. Consistently, LAAC immunization increased the survival rate of mice after bacterial challenge with both PCV13 and non-PCV13 serotypes. In conclusion, our protein-based pneumococcal vaccine provides protective effects against a broad spectrum of Streptococcus pneumoniae serotypes.

Enhancing cord blood stem cell-derived NK cell growth and differentiation through hyperosmosis.

BACKGROUND: Natural killer (NK) cells hold great promise in treating diverse hematopoietic and solid tumors. Despite their availability from peripheral blood and cord blood, stem cell-derived NK cells offer an 'off-the-shelf' solution. Hematopoietic stem and progenitor cells (HSPCs) derived from cord blood pose no risk to the newborn or mother and are virtually ideal sources for NK cell differentiation. METHODS: We developed a modified protocol to differentiate HSPCs to NK cells under serum-free conditions using defined factors. The HSPC-derived NK (HSC-NK) cells could be expanded in a K562 feeder cell-dependent manner. Furthermore, using lentivirus transduction, chimeric antigen receptor (CAR)-modified HSPCs could be differentiated into NK cells, leading to the establishment of CAR-NK cells. RESULTS: The efficiency of NK cell differentiation from HSPCs was increased through the simple modulation of osmotic pressure by the addition of sodium chloride or glucose. Furthermore, the hyperosmosis-primed HSC-NK cells exhibited enhanced proliferation capacity and maintained normal functional characteristics, including transcriptome and antitumor efficacy. The optimized protocol yielded approximately 1.8 million NK cells from a single CD34-positive cell within a 28-day cycle, which signifies more than a ten-fold increase in efficiency relative to the conventional methods. This optimized protocol was also suitable for generating CAR-NK cells with high yields compared to standard conditions. CONCLUSIONS: The results of this study establish high osmotic pressure as a simple yet powerful adjustment that significantly enhances the efficiency and functionality of HSC-NK cells, including CAR-NK cells. This optimized protocol could lead to cost-effective, high-yield NK cell therapies, potentially revolutionizing cancer immunotherapy strategies.

[Temporal and Spatial Distributions of O3 Concentration and Potential Source Area Analysis of Hexi Corridor Based on Satellite and Ground Monitoring].

Based on 2005-2020 O3 column concentration data of OMI remote sensing satellite, combined with air pollutant data from 10 nationally controlled environmental automatic monitoring stations in the Hexi Corridor and global data assimilation system meteorological data, we used Kriging interpolation, correlation analysis, and backward trajectory (HYSPLIT) models to explore the temporal and spatial distribution characteristics, meteorological factors, transmission paths, and potential sources of O3 in the Hexi Corridor. The results showed the following:① in terms of temporal distribution, O3 column concentration showed an upward trend in 2005-2010 and 2014-2020 and downward trend in 2010-2014; the maximum and minimum values were reached in 2010 and 2014 (332.31 DU and 301.00 DU), respectively, and seasonal changes showed that those in spring and winter were significantly higher than those in summer and autumn. ② In terms of spatial distribution, O3 column concentration showed a latitudinal band distribution characteristic of increasing from southwest to northeast; the high-value areas were primarily distributed in urban areas with low terrain, and the median zone was latitudinally striped with the basic alignment of the Qilian foothills. ③ The analysis of meteorological conditions revealed that temperature, wind speed, and sunshine hours were positively correlated with O3, and relative humidity was negatively correlated with O3. ④ By simulating the airflow transportation trajectory of the receiving point in Wuwei City, it was found that the direction of the O3 conveying path was relatively singular; the dominant airflow in each season was primarily in the west and northwest; and the proportions were 71.62%, 66.85%, 61.22%, and 77.78%, respectively. There were certain seasonal differences in the source areas of O3 potential contribution:the high-value areas of O3 potential sources in spring, summer, and autumn were distributed in Baiyin City and Lanzhou City, which were southeast wind sources, and the high-value areas in winter were distributed between the Badain Jaran Desert and the Tengger Desert, which was the north wind source.

Co-delivery of a trimeric spike DNA and protein vaccine with aluminum hydroxide enhanced Th1-dominant humoral and cellular immunity against SARS-CoV-2.

Protein subunit vaccines have been used as prophylactic vaccines for a long time. The well-established properties of these vaccines make them the first choice for the coronavirus disease 2019 (COVID-19) outbreak. However, it is not easy to develop a protein vaccine that induces cytotoxic T lymphocyte responses and requires a longer time for manufacturing, which limits the usage of this vaccine type. Here, we report the combination of a recombinant spike (S)-trimer protein with a DNA vaccine-encoded S protein as a novel COVID-19 vaccine. The recombinant S protein was formulated with different adjuvants and mixed with the DNA plasmid before injection. We found that the recombinant S protein formulated with the adjuvant aluminum hydroxide and mixed with the DNA plasmid could enhance antigen-specific antibody titers, neutralizing antibody titers. We further evaluated the IgG2a/IgG1 isotype and cytokine profiles of the specific boosted T-cell response, which indicated that the combined vaccine induced a T-helper 1 cell-biased immune response. Immunized hamsters were challenged with severe acute respiratory syndrome coronavirus 2, and the body weight of the hamsters that received the recombinant S protein with aluminum hydroxide and/or the DNA plasmid was not reduced. Alternatively, those that received control or only the DNA plasmid immunization were reduced. Interestingly, after the third day of the viral load in the lungs, the viral challenge could not be detected in hamsters immunized with the recombinant S protein in aluminum hydroxide mixed with DNA (tissue culture infectious dose < 10). The viral load in the lungs was 109 , 106 , and 107 for the phosphate-buffered saline, protein in aluminum hydroxide, and DNA-only immunizations, respectively. These results indicated that antiviral mechanisms neutralizing antibodies play important roles. Furthermore, we found that the combination of protein and DNA vaccination could induce relatively strong CD8+ T-cell responses. In summary, the protein subunit vaccine combined with a DNA vaccine could induce strong CD8+ T-cell responses to increase antiviral immunity for disease control.

Lenvatinib plus sintilimab with or without transarterial chemoembolization for intermediate or advanced stage hepatocellular carcinoma: a propensity score-matching cohort study.

In this retrospective study, we compared the efficacy and safety of lenvatinib plus sintilimab, with or without transarterial chemoembolization (TLS vs. LS), in patients with intermediate or advanced stage hepatocellular carcinoma (HCC). Eligible patients who received combination therapy with TLS or LS at Tianjin Medical University Cancer Institute & Hospital from December 2018 to October 2020 were propensity score matched (PSM) to correct for potential confounding biases between the two groups. The primary endpoint was progression-free survival (PFS) and secondary endpoints were overall survival (OS), overall response rate (ORR) and treatment-related adverse events (TRAEs). Cox proportional hazards models were used to identify prognostic factors. The study included 152 patients (LS group, n=54, TLS group, n=98). After PSM, patients in the TLS group had significantly longer PFS (11.1 versus 5.1 months, P=0.033), OS (not reached versus 14.0 months, P=0.0039) and ORR (modified Response Evaluation Criteria in Solid Tumors: 44.0% versus 23.1%; P=0.028) than those in the LS group. In the multivariate Cox regression analysis, the treatment regimen (TLS versus LS) was an independent predictor for both PFS (HR=0.551; 95% CI: 0.334-0.912; P=0.020) and OS (HR=0.349; 95% CI: 0.176-0.692; P=0.003) and CA19-9 level was an independent predictor for OS (HR=1.005; 95% CI: 1.002-1.008; P=0.000). No significant differences in the incidence of grade ≥3 TRAEs were reported between the two treatment groups. In conclusion, triple combination therapy with TLS improved survival with an acceptable safety profile compared with LS in patients with intermediate or advanced stage HCC.

Enhancing Oxygen Evolution Reaction Performance in Prussian Blue Analogues: Triple-Play of Metal Exsolution, Hollow Interiors, and Anionic Regulation.

Prussian blue analogs (PBAs) are promising catalysts for green hydrogen production. However, the rational design of high-performing PBAs is challenging, which requires an in-depth understanding of the catalytic mechanism. Here FeMn@CoNi core-shell PBAs are employed as precursors, together with Se powders, in low-temperature pyrolysis in an argon atmosphere. This synthesis method enables the partial dissociation of inner FeMn PBAs that results in hollow interiors, Ni nanoparticles (NPs) exsolution to the surface, and Se incorporation onto the PBA shell. The resulting material presents ultralow oxygen evolution reaction (OER) overpotential (184 mV at 10 mA cm-2 ) and low Tafel slope (43.4 mV dec-1 ), outperforming leading-edge PBA-based electrocatalysts. The mechanism responsible for such a high OER activity is revealed, assisted by density functional theory (DFT) calculations and the surface examination before and after the OER process. The exsolved Ni NPs are found to help turn the PBAs into Se-doped core-shell metal oxyhydroxides during the OER, in which the heterojunction with Ni and the Se incorporation are combined to improve the OER kinetics. This work shows that efficient OER catalysts could be developed by using a novel synthesis method backed up by a sound understanding and control of the catalytic pathway.