Stretchable Metamaterials with Tunable Infrared Emissivity for Dynamic Thermal Management.

Manipulation of infrared emissivity, which is closely related to surface structure and optical parameters of materials, is a crucial approach for realizing dynamic thermal management. In this study, we design a metamaterial consisting of an array of aluminum disks embedded on a surface of a stretchable elastomeric substrate. Mechanical stretching-induced deformation allows dynamic modification of the surface structure and equivalent optical parameters, thus enabling dynamic control of the emissivity. By utilizing the elastomer polydimethylsiloxane (PDMS) as the substrate, the microstructure interdisk gap can be altered by stretching the PDMS. Through theoretical calculations, the plausibility of this approach is explained by the excitation of plasmon resonance and the variation in the exposed area of highly absorbent PDMS, and the optimal structures for tuning the infrared emissivity are revealed to be 6 µm in diameter and 100 nm in height. Based on this design, we prepare samples with periods of 7 and 7.9 µm and experimentally demonstrate that a change in the period can cause a change in the emissivity and thus tunability in thermal control performance. The temperature difference between the two samples reaches 44.1 °C at a heating power of 0.28 W/cm2 for both samples. Furthermore, we construct a stretching platform that enables in situ mechanical stretching to realize dynamic changes in emissivity. The integral infrared emissivity of the sample increases from 0.32 to 0.5 at a biaxial tensile strain of 13%, achieving a 56% modulation rate of the integral infrared emissivity. The material is expected to enable dynamic thermal management.

Ultrasound Genomics Reveals a Signature for Predicting Breast Cancer Prognosis and Therapy Response.

Background: Breast cancer (BC) in women is the most common malignancy worldwide, but there is still a lack of validated tools to accurately assess patient prognosis and response to available chemotherapy treatment regimens. Method: We collected ultrasound images and transcriptome data of BC from our breast center and public database. Key ultrasound features were then identified by using the support vector machine (SVM) algorithm and correlated with prognostic genes. Long-term survival-related genes were identified through differential expression analysis, and a prognostic evaluation model was established by using Cox regression. In addition, VPS28 from the model was identified as a promising biomarker for BC. Results: Using univariate logistic regression and SVM algorithms, we identified 12 ultrasound features significantly associated with chemotherapy response. Subsequent correlation and differential expression analyses linked 401 genes to these features, from which five key signature genes were derived using Lasso and multivariate Cox regression models. This signature not only facilitates the stratification of patients into risk-specific treatment pathways but also predicts their chemotherapy response, thus supporting personalized medicine in clinical settings. Notably, VPS28, in the signature, emerged as a significant biomarker, strongly associated with poor prognosis, greater tumor invasiveness, and differing expression across demographic groups. Conclusion: In this study, we use ultrasound genomics to reveal a signature that can provide an effective tool for prognostic assessment and predicting chemotherapy response in patients with BC.

Diagnostic Value of Serum Apolipoprotein B100 Combined With Hippocampal Volume in Alzheimer's Disease.

PURPOSE: To explore the diagnostic value of serum apolipoprotein B100 (Apo B100) combined with hippocampal volume in Alzheimer's disease (AD). METHODS: A total of 59 AD patients and 59 healthy subjects were selected. The Mini-Mental State Examination (MMSE) was used for neuropsychological assessment. Blood glucose and serum lipid levels were detected by biochemical analyzer. Polymerase chain reaction (PCR) was used to detect apolipoprotein E (Apo E) ε3/ε4 genotypes in the plasma. Hippocampal volume was calculated using Slicer software. Independent-sample t test or Mann-Whitney U test were used to compare the levels of various indicators between the two groups. Spearman's correlation analysis was used to analyze the correlation between each level. The receiver operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated to compare the diagnostic efficacy of individual and combined detection of serum Apo B100 levels and hippocampal volume in AD. RESULTS: Compared with the healthy control group, the levels of serum total cholesterol (TC), low-density lipoprotein (LDL), Apo B100, and plasma Apo E ε3/ε4 were higher in the AD group, and serum high-density lipoprotein (HDL) level was lower in the AD group (both p < 0.05). The hippocampal volume in the AD group was lower than in the control group (p < 0.01). The serum Apo B100 level was negatively correlated with MMSE score (r = -0.646), whereas hippocampal volume was positively correlated with MMSE score (r = 0.630). ROC curve analysis showed that the AUC of the combined serum Apo B100 level and hippocampal volume for AD was higher than that of either alone (AUC = 0.821, p < 0.01). CONCLUSION: Serum Apo B100 level is elevated, and the hippocampal volume is reduced in AD patients. The combined detection of the two has a higher diagnostic efficiency for AD than other alone and has the potential to become an important indicator for the diagnosis of AD in the future.

Treatment response of venlafaxine induced alterations of gut microbiota and metabolites in a mouse model of depression.

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16 S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response.

Development and initial validation of the contemporary Chinese Familism Scale.

OBJECTIVES: Familism is a core ideology in Chinese society, yet it has been understudied in this cultural context, potentially attributed to the lack of quantifiable measures. This study sought to develop a reliable and valid scale, the Contemporary Chinese Familism Scale (CCFS), to assess Chinese familism and analyze its structural and psychological characteristics in contemporary China. METHOD: The scale development and validation process comprised four studies: in Study 1, literature review, qualitative interviews, and item evaluations by experts were conducted to develop the initial item pool for the CCFS; in Studies 2 and 3, item analysis, exploratory and confirmatory factor analyses, competing model comparisons, and measurement invariance tests were conducted to examine the structure underlying familism (N1 = 958, Mage = 25.4 years; N2 = 570, Mage = 32.01 years); in Study 4, reliability and validity assessments were conducted to further explore the psychometric properties of the final 27-item CCFS using three samples (N2 = 570, Mage = 32.01 years; N3 = 710, Mage = 22.37 years; N4 = 932, Mage = 40.98 years). RESULT: A bifactor structure with one general factor and five specific factors (Connection and Closeness, Offspring and Lineage, Honor and Reference, Harmony and Sacrifice, and Care and Help) demonstrated the best fit for the data and supported the multidimensionality of familism in contemporary China. Subsequent psychometric analyses provided initial evidence for the optimal psychometric properties of the CCFS. CONCLUSION: This study contributes to our understanding of the multifaceted nature of familism in contemporary China by developing a culturally sensitive scale on Chinese familism. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Wearable and Multiplexed Biosensors based on Oxide Field-Effect Transistors.

Wearable sensors designed for continuous, non-invasive monitoring of physicochemical signals are important for portable healthcare. Oxide field-effect transistor (FET)-type biosensors provide high sensitivity and scalability. However, they face challenges in mechanical flexibility, multiplexed sensing of different modules, and the absence of integrated on-site signal processing and wireless transmission functionalities for wearable sensing. In this work, a fully integrated wearable oxide FET-based biosensor array is developed to facilitate the multiplexed and simultaneous measurement of ion concentrations (H+, Na+, K+) and temperature. The FET-sensor array is achieved by utilizing a solution-processed ultrathin (≈6 nm thick) In2O3 active channel layer, exhibiting high compatibility with standard semiconductor technology, good mechanical flexibility, high uniformity, and low operational voltage of 0.005 V. This work provides an effective method to enable oxide FET-based biosensors for the fusion of multiplexed physicochemical information and wearable health monitoring applications.

An Ion-Mediated Spiking Chemical Neuron based on Mott Memristor.

Artificial spiking neurons capable of interpreting ionic information into electrical spikes are critical to mimic biological signaling systems. Mott memristors are attractive for constructing artificial spiking neurons due to their simple structure, low energy consumption, and rich neural dynamics. However, challenges remain in achieving ion-mediated spiking and biohybrid-interfacing in Mott neurons. Here, a biomimetic spiking chemical neuron (SCN) utilizing an NbOx Mott memristor and oxide field-effect transistor-type chemical sensor is introduced. The SCN exhibits both excitation and inhibition spiking behaviors toward ionic concentrations akin to biological neural systems. It demonstrates spiking responses across physiological and pathological Na+ concentrations (1-200 × 10-3 m). The Na+-mediated SCN enables both frequency encoding and time-to-first-spike coding schemes, illustrating the rich neural dynamics of Mott neuron. In addition, the SCN interfaced with L929 cells facilitates real-time modulation of ion-mediated spiking under both normal and salty cellular microenvironments.

A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot.

To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidic chip to simultaneously capture neural activity and body movement in small freely behaving Drosophila larva. We develop a transfer learning based method to simultaneously track the continuously changing body posture and activity of neurons that move together using a sub-region tracking network with a precise landmark estimation network for the inference of target landmark trajectory. Based on the tracking of each labelled neuron, the activity of the neuron indicated by fluorescent intensity is calculated. For each video, annotation of only 20 frames in a video is sufficient to yield human-level accuracy for all other frames. The validity of this method is further confirmed by reproducing the activity pattern of PMSIs (period-positive median segmental interneurons) and larval movement as previously reported. Using this method, we disclosed the correlation between larval movement and left-right asymmetry in activity of a group of unidentified neurons labelled by R52H01-Gal4 and further confirmed the roles of these neurons in bilateral balance of body contraction during larval crawling by genetic inhibition of these neurons. Our method provides a new tool for accurate extraction of neural activities and movement of freely behaving small-size transparent animals.

Intrinsically reactive hyperbranched interface governs graphene oxide dispersion and crosslinking in epoxy for enhanced flame retardancy.

Enhancing the flame retardancy of epoxy (EP) resins typically entailed a trade-off with other physical properties. Herein, hyperbranched poly(amidoamine) (HPAA) and phytic acid (PA) were used to functionalize graphene oxide (GO) via electrostatic self-assembly in water to prepare a phosphorus-nitrogen functionalized graphene oxide nanosheet (PN-GOs), which could be utilized as high efficient flame-retardant additive of epoxy resin without sacrificing other properties. The PN-GOs demonstrated improved dispersion and compatibility within the EP matrix, which resulted in significant concurrent enhancements in both the mechanical performance and flame-retardant properties of the PN-GOs/EP nanocomposites over virgin EP. Notably, the incorporation of just 1.0 wt% PN-GOs yielded a 20.4, 6.4 and 42.7 % increases in flexural strength, flexural modulus and impact strength for the PN-GOs/EP nanocomposites, respectively. Furthermore, simultaneous reductions were achieved in the peak heat release rate (pHRR) by 60.0 %, total smoke production (TSP) by 43.0 %, peak CO production rate (pCOP) by 57.9 %, and peak CO2 production rate (pCO2P) by 63.9 %. This study presented a facile method for the design of GO-based nano flame retardants, expanding their application potential in polymer-matrix composites.

Identification of Potential Biomarkers for Major Depressive Disorder: Based on Integrated Bioinformatics and Clinical Validation.

Major depressive disorder (MDD) is a severe mental illness characterized by a lack of objective biomarkers. Mounting evidence suggests there are extensive transcriptional molecular changes in the prefrontal cortex (PFC) of individuals with MDD. However, it remains unclear whether there are specific genes that are consistently altered and possess diagnostic power. In this study, we conducted a systematic search of PFC datasets of MDD patients from the Gene Expression Omnibus database. We calculated the differential expression of genes (DEGs) and identified robust DEGs using the RRA and MetaDE methods. Furthermore, we validated the consistently altered genes and assessed their diagnostic power through enzyme-linked immunosorbent assay experiments in our clinical blood cohort. Additionally, we evaluated the diagnostic power of hub DEGs in independent public blood datasets. We obtained eight PFC datasets, comprising 158 MDD patients and 263 healthy controls, and identified a total of 1468 unique DEGs. Through integrated analysis, we identified 290 robustly altered DEGs. Among these, seven hub DEGs (SLC1A3, PON2, AQP1, EFEMP1, GJA1, CENPD, HSD11B1) were significantly down-regulated at the protein level in our clinical blood cohort. Moreover, these hub DEGs exhibited a negative correlation with the Hamilton Depression Scale score (P < 0.05). Furthermore, these hub DEGs formed a panel with promising diagnostic power in three independent public blood datasets (average AUCs of 0.85) and our clinical blood cohort (AUC of 0.92). The biomarker panel composed of these genes demonstrated promising diagnostic efficacy for MDD and serves as a useful tool for its diagnosis.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Microbiological Mechanisms of Collaborative Remediation of Cadmium-Contaminated Soil with Bacillus cereus and Lawn Plants.

Severe cadmium contamination poses a serious threat to food security and human health. Plant-microbial combined remediation represents a potential technique for reducing heavy metals in soil. The main objective of this study is to explore the remediation mechanism of cadmium-contaminated soil using a combined approach of lawn plants and microbes. The target bacterium Bacillus cereus was selected from cadmium-contaminated soil in mining areas, and two lawn plants (Festuca arundinacea A'rid III' and Poa pratensis M'idnight II') were chosen as the target plants. We investigated the remediation effect of different concentrations of bacterial solution on cadmium-contaminated soil using two lawn plants through pot experiments, as well as the impact on the soil microbial community structure. The results demonstrate that Bacillus cereus promotes plant growth, and the combined action of lawn plants and Bacillus cereus improves soil quality, enhancing the bioavailability of cadmium in the soil. At a bacterial suspension concentration of 105 CFU/mL, the optimal remediation treatment was observed. The removal efficiency of cadmium in the soil under Festuca arundinacea and Poa pratensis treatments reached 33.69% and 33.33%, respectively. Additionally, the content of bioavailable cadmium in the rhizosphere soil increased by up to 13.43% and 26.54%, respectively. Bacillus cereus increased the bacterial diversity in the non-rhizosphere soil of both lawn plants but reduced it in the rhizosphere soil. Additionally, the relative abundance of Actinobacteriota and Firmicutes, which have potential for heavy metal remediation, increased after the application of the bacterial solution. This study demonstrates that Bacillus cereus can enhance the potential of lawn plants to remediate cadmium-contaminated soil and reshape the microbial communities in both rhizosphere and non-rhizosphere soils.

Alterations of the gut microbiota in patients with schizophrenia.

Introduction: Schizophrenia is a complex psychiatric disorder, of which molecular pathogenesis remains largely unknown. Accumulating evidence suggest that gut microbiota may affect brain function via the complex gut-brain axis, which may be a potential contributor to schizophrenia. However, the alteration of gut microbiota showed high heterogeneity across different studies. Therefore, this study aims to identify the consistently altered gut microbial taxa associated with schizophrenia. Methods: We conducted a systematic search and synthesis of the up-to-date human gut microbiome studies on schizophrenia, and performed vote counting analyses to identify consistently changed microbiota. Further, we investigated the effects of potential confounders on the alteration of gut microbiota. Results: We obtained 30 available clinical studies, and found that there was no strong evidence to support significant differences in α-diversity and ß-diversity between schizophrenic patients and healthy controls. Among 428 differential gut microbial taxa collected from original studies, we found that 8 gut microbial taxa were consistently up-regulated in schizophrenic patients, including Proteobacteria, Gammaproteobacteria, Lactobacillaceae, Enterobacteriaceae, Lactobacillus, Succinivibrio, Prevotella and Acidaminococcus. While 5 taxa were consistently down-regulated in schizophrenia, including Fusicatenibacter, Faecalibacterium, Roseburia, Coprococcus and Anaerostipes. Discussion: These findings suggested that gut microbial changes in patients with schizophrenia were characterized by the depletion of anti-inflammatory butyrate-producing genera, and the enrichment of certain opportunistic bacteria genera and probiotics. This study contributes to further understanding the role of gut microbiota in schizophrenia, and developing microbiota-based diagnosis and therapy for schizophrenia.

Clinical and economic comparison of laparoscopic versus open hepatectomy for primary hepatolithiasis: a propensity score-matched cohort study.

BACKGROUND: It is unclear whether laparoscopic hepatectomy (LH) for hepatolithiasis confers better clinical benefit and lower hospital costs than open hepatectomy (OH). This study aim to evaluate the clinical and economic value of LH versus OH. METHODS: Patients undergoing OH or LH for primary hepatolithiasis at Yijishan Hospital of Wannan Medical College between 2015 and 2022 were divided into OH group and LH group. Propensity score matching (PSM) was used to balance the baseline data. Deviation-based cost modelling and weighted average median cost (WAMC) were used to assess and compare the economic value. RESULTS: A total of 853 patients were identified. After exclusions, 403 patients with primary hepatolithiasis underwent anatomical hepatectomy (OH n=143; LH n=260). PSM resulted in 2 groups of 100 patients each. Although LH required a longer median operation duration compared with OH (285.0 versus 240.0 min, respectively, P<0.001), LH patients had fewer wound infections, fewer pre-discharge overall complications (26 versus 43%, respectively, P=0.009), and shorter median postoperative hospital stays (8.0 versus 12.0 days, respectively, P<0.001). No differences were found in blood loss, major complications, stone clearance, and mortality between the two matched groups. However, the median overall hospital cost of LH was significantly higher than that of OH (CNY¥52,196.1 versus 45,349.5, respectively, P=0.007). Although LH patients had shorter median postoperative hospital stays and fewer complications than OH patients, the WAMC was still higher for the LH group than for the OH group with an increase of CNY¥9,755.2 per patient undergoing LH. CONCLUSION: The overall clinical benefit of LH for hepatolithiasis is comparable or even superior to that of OH, but with an economic disadvantage. There is a need to effectively reduce the hospital costs of LH and the gap between costs and diagnosis-related group reimbursement to promote its adoption.

Nitrogen dynamics of alpine swamp meadows are less responsive to climate warming than that of alpine meadows.

The freeze-thaw cycle mediates permafrost soil hydrothermal status, nitrogen (N) mineralization, and loss. Furthermore, it affects root development and competition among nitrophilic and other species, shaping the pattern of N distribution in alpine ecosystems. However, the specific N dynamics during the growing season and N loss during the non-growing season in response to climate warming under low- and high-moisture conditions are not well documented. Therefore, we added 15N tracers to trace the fate of N in warmed and ambient alpine meadows and alpine swamp meadows in the permafrost region of the Qinghai-Tibet Plateau. During the growing season, warming increased 15N recovery (15Nrec) in shoots of K. humilis, litters, 0-5 and 5-20 cm roots in the alpine meadow by 149.94 % ± 52.87 %, 114.58 % ± 24.43 %, 61.11 % ± 32.27 %, and 97.12 % ± 42.92 %, respectively, while increased 15Nrec of litters by 151.55 % ± 27.06 % in the alpine swamp meadow. During the non-growing season, warming reduced 15N stored in roots by 486.77 % ± 57.90 %, though increased the 15N recovery in 5-20 cm soil depth by 76.68 % ± 39.42 % in the alpine meadow, whereas it did not affect N loss during the non-growing season in the alpine swamp meadow. Overall, warming promoted N utilization by increasing the plant N pool during the growing season, and enhanced root N loss and downward migration during the non-growing season due to the freeze-thaw process, which may result in fine root turnover and cell destruction releasing N in the alpine meadow. Conversely, the N dynamics of alpine swamp meadows were less responsive to climate warming.

Dan-shen Yin promotes bile acid metabolism and excretion to prevent atherosclerosis via activating FXR/BSEP signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Dan-shen Yin (DSY), a traditional prescription, has been demonstrated to be effective in decreasing hyperlipidemia and preventing atherosclerosis (AS), but its mechanism remains unknown. We hypothesized that DSY activates farnesoid X receptor (FXR) to promote bile acid metabolism and excretion, thereby alleviating AS. AIM OF THE STUDY: This study was designed to explore whether DSY reduces liver lipid accumulation and prevents AS by activating FXR and increasing cholesterol metabolism and bile acid excretion. MATERIALS AND METHODS: The comprehensive chemical characterization of DSY was analyzed by UHPLC-MS/MS. The AS models of ApoE-/- mice and SD rats was established by high-fat diet and high-fat diet combined with intraperitoneal injection of vitamin D3, respectively. The aortic plaque and pathological changes were used to evaluate AS. Lipid levels, H&E staining and oil red O staining were used to evaluate liver lipid accumulation. The cholesterol metabolism and bile acid excretion were evaluated by enzyme-linked immunosorbent assay, UPLC-QQQ/MS. In vitro, the lipid and FXR/bile salt export pump (BSEP) levels were evaluated by oil red O staining, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting. RESULTS: A total of 36 ingredients in DSY were identified by UPLC-MS/MS analysis. In vivo, high-dose DSY significantly inhibited aortic intimal thickening, improved arrangement disorder, tortuosity, and rupture of elastic fibers, decreased lipid levels, and reduced the number of fat vacuoles and lipid droplets in liver tissue in SD rats and ApoE-/- mice. Further studies found that high-dose DSY significantly reduced liver lipid and total bile acids levels, increased liver ursodeoxycholic acid (UDCA) and other non-conjugated bile acids levels, increased fecal total cholesterol (TC) levels, and augmented FXR, BSEP, cholesterol 7-alpha hydroxylase (CYP7A1), ATP binding cassette subfamily G5/G8 (ABCG5/8) expression levels, while decreasing ASBT expression levels. In vitro studies showed that DSY significantly reduced TC and TG levels, as well as lipid droplets, while also increasing the expression of ABCG5/8, FXR, and BSEP in both HepG2 and Nr1h4 knockdown HepG2 cells. CONCLUSION: This study demonstrated that DSY promotes bile acid metabolism and excretion to prevent AS by activating FXR. For the prevent of AS and drug discovery provided experimental basis.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex.

Background: Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. Methods: We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. Results: Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. Conclusions: The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Breaking genetic shackles: The advance of base editing in genetic disorder treatment.

The rapid evolution of gene editing technology has markedly improved the outlook for treating genetic diseases. Base editing, recognized as an exceptionally precise genetic modification tool, is emerging as a focus in the realm of genetic disease therapy. We provide a comprehensive overview of the fundamental principles and delivery methods of cytosine base editors (CBE), adenine base editors (ABE), and RNA base editors, with a particular focus on their applications and recent research advances in the treatment of genetic diseases. We have also explored the potential challenges faced by base editing technology in treatment, including aspects such as targeting specificity, safety, and efficacy, and have enumerated a series of possible solutions to propel the clinical translation of base editing technology. In conclusion, this article not only underscores the present state of base editing technology but also envisions its tremendous potential in the future, providing a novel perspective on the treatment of genetic diseases. It underscores the vast potential of base editing technology in the realm of genetic medicine, providing support for the progression of gene medicine and the development of innovative approaches to genetic disease therapy.

Preoperative plasma fibrinogen and C-reactive protein/albumin ratio as prognostic biomarkers for pancreatic carcinoma.

Objective: Pancreatic carcinoma is characterised by high aggressiveness and a bleak prognosis; optimising related treatment decisions depends on the availability of reliable prognostic markers. This study was designed to compare various blood biomarkers, such as neutrophil/lymphocyte ratio (NLR), lymphocyte/monocyte ratio (LMR), platelet/lymphocyte ratio (PLR), C-reactive protein (CRP), albumin (Alb), plasma fibrinogen (PF), and CRP/Alb in patients with pancreatic carcinoma. Methods: Our study retrospectively reviewed 250 patients with pancreatic carcinoma diagnosed between July 2007 and December 2018. The Cutoff Finder application was used to calculate the optimal values of CRP/Alb and PF. The Chi-square test or Fisher's exact test was used to analyse the correlation of CRP/Alb and PF with other clinicopathological factors. Conducting univariate and multivariate analyses allowed further survival analysis of these prognostic factors. Results: Multivariate analysis revealed that, in a cohort of 232 patients with pancreatic ductal adenocarcinoma (PDAC), the PF level exhibited statistical significance for overall survival (hazard ratio (HR) = 0.464; p = 0.023); however, this correlation was not found in the entire group of 250 patients with pancreatic carcinoma. Contrastingly, the CRP/Alb ratio was demonstrated statistical significance in both the entire pancreatic carcinoma cohort (HR = 0.471; p = 0.026) and the PDAC subgroup (HR = 0.484; p = 0.034). CRP/Alb and PF demonstrated a positive association (r=0.489, p<0.001) as indicated by Spearman's rank correlation analysis. Additionally, in 232 PDAC patients, the combination of the CRP/Alb ratio and PF had synergistic effects on prognosis when compared with either the CRP/Alb ratio or the PF concentration alone. Conclusion: PF concentration is a convenient, rapid, and noninvasive biomarker, and its combination with the CRP/Alb ratio could significantly enhance the accuracy of prognosis prediction in pancreatic carcinoma patients, especially those with the most common histological subtype of PDAC.

Comprehensive profiling of cell subsets of gastric cancer and liver metastasis based on single cell RNA-sequencing analysis.

Background: Liver metastasis (Li) is one of the most common distant metastatic sites for gastric cancer. A deeper understanding of its mechanism of action from a bioinformatics perspective may provide new insights. Therefore, the aim of this study was to use single cell RNA sequencing (scRNA-seq) to evaluate cell subtypes and understand the molecular mechanism of gastric cancer Li. Methods: The scRNA-seq data GSE163558 of gastric cancer and Li were downloaded from Gene Expression Omnibus (GEO). Single cell data were analyzed by various R packages such as Seurat, CellChat, gene set variation analysis (GSVA), monocle, gene set enrichment analysis (GSEA), and survival analysis and the results were plotted by ggplot2, R4.1.1. Protein expression was confirmed by immunohistochemistry in an additional patient cohort. Results: The genes APOD, CXCL5, and JUN are involved in epithelial cell metastasis. The infiltration of cytotoxic CD8 T cells was more frequent in gastric primary tumors (PTs) than in Lis. IL7R high natural killer (NK) cells that had high TXNIP and RIPOR2 expression were located at the site of Li and corresponded to a favorable prognosis. NK cells with high TNFAIP3 expression were located at the PT site and corresponded to a poor prognosis. Furthermore, the gene expression of myeloid cells was different depending on their localization in the PT site or Li. MHC-I signaling pathway was found to be activated in the PT compared to MHC-II at the site of Li, as revealed by cell-cell interaction, and HLA-E-CD94/NKG2A of NK cells was only activated in the PT and not in the Li. Conclusions: The present study revealed the difference between Li and gastric PT by scRNA-seq, demonstrating the impact of partial gene expression on patient prognosis. Our study provides new insights into gastric cancer and Li.